# Microsoft Azure Data Lake Store Connector - Deprecated Source: https://www.domo.com/docs/s/article/000003928 **Note:** This connector connects to Azure Data Lake Gen1. Microsoft [deprecated this service as of February 2024](https://azure.microsoft.com/en-us/updates?id=action-required-switch-to-azure-data-lake-storage-gen2-by-29-february-2024). To connect to Azure Data Lake Gen2 resources, use one of the following connectors: * [Microsoft Azure Storage Data Lake Gen2 Connector](/docs/s/article/360056826394) * [Azure Data Lake Storage Gen2 Using AAD Connector](/docs/s/article/1500007660641) * [Azure Data Lake Gen2 OAuth Connector](/docs/s/article/000005162) ## Intro Azure Data Lake Store is an enterprise-wide hyper-scale repository for big data analytic workloads. Use this connector to pull data files from your Data Lake Store into Domo. You can retrieve data files in any of the following file types: CSV, XLS, XLSX, and JSON. For more information about Azure's API, see [Azure Data Lake Store documentation](https://docs.microsoft.com/en-us/azure/data-lake-store/). You connect to your Microsoft Azure Data Lake Store account in the Data Center. This article discusses the fields and menus that are specific to the Microsoft Azure Data Lake Store connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). *** ## Prerequisites To connect to your Microsoft Azure Data Lake Store account and create a DataSet, you must have the following: * Your Microsoft Azure Data Lake Store tenant ID * Your Microsoft Azure Data Lake Store client ID * Your Microsoft Azure Data Lake Store client secret To obtain credentials, reach out to your Microsoft account representative. ## Connect to Your Microsoft Azure Data Lake Store Account This section enumerates the options in the **Credentials** and **Details** panes in the Microsoft Azure Data Lake Store Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ### Credentials Pane This pane contains fields for entering credentials to connect to your Microsoft Azure Data Lake Store account. The following table describes what is needed for each field: | Field | Description | | ------------- | ---------------------------------------------------------------------------------------------------------------------------- | | Tenant ID | Enter your Microsoft Azure Data Lake Store tenant ID. | | Client ID | Enter your Microsoft Azure Data Lake Store client ID. | | Client Secret | Enter your Microsoft Azure Data Lake Store client secret. | | Account FQDN | Enter the fully-qualified domain name of your Azure Data Lake Store account. For example: `mycompany.azuredatalakestore.net` | Once you have entered valid Microsoft Azure Data Lake Store credentials, you can use the same account any time you go to create a new Microsoft Azure Data Lake Store DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054). ### Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select. | Menu | Description | | -------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Report | Select the Microsoft Azure Data Lake Store report you want to run. The following reports are available:
ReportDescription
ACL StatusReturns the ACL status for a given file or directory.
Content SummaryReturns a content summary for a given file or directory.
Directory/File InformationRetrieves the metadata for a given file or directory.
Download FileImports the content of a selected file into a Domo DataSet.
| | Directory Path | Enter the directory path of the file you want to import into Domo. | | Path | Enter the complete path of the file or directory you want to retrieve information for. For example: `/test/abc.csv` | | How Would You Like to Choose Your File Name? | Select how you want to choose the file you intend to import into Domo. Select **Files Discovery** to choose your file from a list of files. Select **Enter File Name** to enter the name yourself.
Select **Download All Files** to download all files at once. | | Select File | Select the file you want to import into Domo. | | File Name | Enter the name of the file you want to import into Domo. | | File Name Match Type | Specify whether the retrieved file starts with or contains the name you have entered in **File Name**. | | File Format | Select the format of the file you want to import. Options include CSV, XLS, XLSX, and JSON. | | Delimiter | Select the delimiter to use to parse your CSV file. To choose a custom delimiter, select **Other**, then enter your delimiter in the **Custom Delimiter** field. | | Custom Delimiter | Enter the custom delimiter you want to use to parse your CSV file. Enter tab or Unicode characters in `\uxxxx` form (e.g. `^`). | | Quote Character | Select the desired quote character for parsing your CSV file. (A double quote is the CSV standard.) To choose a custom quote character, select **Other**, then enter your quote character in the **Custom Quote Character** field. | | Custom Quote Character | Enter the custom quote character you want to use to parse your CSV file. Enter tab or Unicode characters in `\uxxxx` form (e.g. `^`). | | Escape Character | Select the escape character to use to parse your CSV file. To choose a custom escape character, select **Other**, then enter your delimiter in the **Custom Escape Character** field. | | Header Start Row (Optional) | Enter the header start row for your Excel file. | | Data Start Row (Optional) | Enter the data start row for your Excel file. | | Footer Rows to Skip (Optional) | Enter the number of rows to skip at the end of your Excel file, if any. | | Sheet Name (Optional) | If your Excel file contains more than one sheet, enter the name of the sheet you want to import. Be sure to check the sheet name for accidental spaces. If this field is left blank, the first sheet of the workbook will be used. | | Data Field Key (Optional) | Enter the data field key for the JSON file you want to import. | | Sublist to Flatten (Optional) | Enter the lists you want to flatten in your data. Separate multiple lists with commas. | ### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). # Databricks AWS Writeback Connector Source: https://www.domo.com/docs/s/article/000003989 ## Intro This article explains how to use Domo's Databricks AWS Writeback Connector to export data from a Domo DataSet to a Databricks table, configure connection credentials, and specify the destination table for the writeback. *** ## Prerequisites To configure this connector, you must have the following: * The username and password you use to log into your Databricks host * The host name for the database * The port number for the database * The database name or schema name * The HTTP path * Your AWS S3 access key and secret key * The name of your S3 bucket * The AWS region where your S3 bucket is located **Note:** The owner of a writeback DataSet must also be an owner or co-owner of the input DataSet. Databricks is a cloud-based collaborative data science, data engineering, and data analytics platform that combines the best of data warehouses and data lakes into a lakehouse architecture. With the Databricks AWS Writeback Connector, you can export data from a Domo DataSet to a specified Databricks table. For more information about the Databricks API, see the [Databricks API documentation](https://docs.databricks.com/dev-tools/api/index.html). This article covers the fields and menus specific to the Databricks AWS Writeback Connector user interface. For general information about adding DataSets, setting update schedules, and editing DataSet information, see [Add a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Configure the Connection This section describes the options in the **Credentials** and **Details** panes on the Databricks AWS Writeback Connector page. The components of the **Scheduling** and **Name & Describe Your DataSet** panes are universal across most connector types and are discussed in [Add a DataSet Using a Data Connector](/docs/s/article/360042926274). ### Enter Your Credentials The **Credentials** pane contains fields for entering credentials to connect to the Databricks account where you want your data to be copied. The following table describes what is needed for each field. | Field | Description | | ----------------- | ------------------------------------------------------------------------------- | | Host | Enter the host name for the Databricks database. For example: `db.company.com`. | | Port | Enter the port number for the Databricks database. | | Database Name | Enter the name of the Databricks database. | | Username | Enter your Databricks username. | | Password | Enter your Databricks password. | | HTTP Path | Enter the HTTP path. | | AWS S3 Access Key | Enter your AWS access key. | | AWS S3 Secret Key | Enter your AWS secret key. | | AWS S3 Bucket | Enter the name of your S3 bucket. | | AWS S3 Region | Select the region where your S3 bucket is located. | For more information about obtaining these credentials, see [Prerequisites](#prerequisites) above. After you have entered valid credentials, you can use the same account any time you set up a new Databricks-Domo connection. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Manage User Accounts for Connectors](/docs/s/article/360042926054). ### Configure the Details Pane In the **Details** pane, you specify the input DataSet and the destination Databricks table. | Menu | Description | | --------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Input DataSet ID | Enter your Domo DataSet ID (GUID) located in the DataSet URL. For example: `https://customer.domo.com/datasources/`*aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee*`/details/settings`. | | Enter Databricks Table Name | Enter the Databricks table name where you want to copy the data from your Domo DataSet. | ## Configure Other Options For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Add a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQ You need the username, password, host name, port number, and database name of your Databricks database. You also need to provide the HTTP path, your AWS S3 access key and secret key, your S3 bucket name, and the AWS region where your S3 bucket is located. You can find the host name, database, port number, and HTTP path by going to your cluster in Databricks and viewing the JDBC/ODBC tab in the Advanced section of the cluster details. Limits depend on your server configuration. As often as needed. Your Domo input DataSet ID is in the URL of the DataSet you are exporting data from. For example: `https://customer.domo.com/datasources/`*aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee*`/details/settings`. The Databricks table name is the table where you want to copy the data from your Domo DataSet. # Domo on Dremio Source: https://www.domo.com/docs/s/article/000005139 ## Intro With Cloud Integrations, you can power your Domo instance using Dremio. You can register both Dremio Cloud and Dremio Software with Domo, and this process is described below. To learn more about Cloud Integrations, see the [overview](https://domo-support.domo.com/s/article/4412849158167). *** ## Architectural Overview Dremio architecture diagram.png ## Prerequisites Before setting up the Dremio connection, we strongly recommend that you complete the following: * **(Recommended) Create a Dremio service account —** We recommend creating a new Dremio account specifically for this integration. You can use any account with Read access in Dremio, but it is best practice to use a service account. This account must have read access to your default Dremio environment in order to create virtual Dremio tables in Domo. * **(Recommended) Create a Domo service account —** We recommend creating a new Domo account specifically for this integration. The account role must have the Manage Cloud Accounts and Manage DataSet grants enabled. For more information about roles and grants, see our article about [Managing Custom Roles](https://domo-support.domo.com/s/article/360043438973). ## Setup The process to register either Dremio Cloud or Dremio Software begins with the same steps, described below. When the process branches, the steps for each product appear under their own headings: [Dremio Cloud Registration](#dremio-cloud-registration) and [Dremio Software Registration](#dremio-software-registration). **To begin:** Log into your Domo service account and go to the Data Center (**More**>**Data**). 1. If you're not already there, go to the **Data Warehouse** in the left sidebar. 2. Select **** **Add New Cloud**. The new integration modal displays 3. In the modal under **Native integration**, select **Dremio**. (If Dremio doesn't display, select **See More** to see all possible integrations.) select dremio.jpg 4. Select **+** **Add New Integration**. The **Enter account information** tab of the Connect a Dremio cloud integration page of the modal displays. 5. Enter a name and optional description in the **Integration name** and **Integration description** fields. 6. Select the radio button for the correct Dremio product: **Dremio Cloud** or **Dremio Software**. At this point in the setup, the steps vary depending on the product you select. Go to the correct process for your product: [Dremio Cloud Registration](#dremio-cloud-registration) or [Dremio Software Registration](#dremio-software-registration). ## Dremio Cloud Registration 1. After you select the radio button for **Dremio Cloud**, select **Next**. dremio cloud reg.png 2. Enter a URL in the **Dremio connection URL** field. You can find this URL in the settings of your Dremio Cloud account. 3. Create a personal access token in your Dremio Cloud account. Copy the token for your records, because you cannot recover the token after you leave the page. 4. Paste the token into the **Personal Access Token** field in the configuration modal in Domo. 5. Select **Next**. 6. Browse for and select the schemas and tables you want to use to create DataSets in Domo. Dremio Select Tables[51].jpg 7. Select **Create DataSets**. You have successfully registered Dremio Cloud. ## Dremio Software Registration 1. After you select the radio button for **Dremio Software**, select **Next**. dremio software reg.png 2. Enter a URL in the **Dremio connection URL** field. 3. Enter your Dremio Software credentials in the **Username** and **Password** fields. 4. Select **Next**. 5. Browse for and select the schemas and tables you want to use to create DataSets in Domo. You have successfully registered Dremio Software. # Azure Storage Blob SAS Token Connector Source: https://www.domo.com/docs/s/article/000005140 ## Intro Microsoft Azure Blob Storage is designed to easily and efficiently store any type of unstructured data, such as images, videos, audio, and documents. Use this connector to pull data files from your Microsoft Azure Blob Storage account into Domo. Combine your Azure data with data from other data sources throughout your company for a comprehensive view of your business. Set up custom alerts to be notified in real-time when your key metrics change, so you can make faster, better business decisions. To learn more about the Azure Blob Storage API, visit their page ([https://docs.microsoft.com/en-us/res...rvice-rest-api](https://docs.microsoft.com/en-us/rest/api/storageservices/blob-service-rest-api "https://docs.microsoft.com/en-us/rest/api/storageservices/blob-service-rest-api") ). You export data to Azure Blob Storage in the Data Center. This topic discusses the fields and menus that are specific to the Azure Blob Storage SAS Token connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Prerequisites To configure this connector, you will need the following: * The Storage Account Name * An Account access level SAS token **Note:** This connector works only with the **account access level SAS** token. So, if you receive an authentication error, please confirm if you are entering a container access level token instead. ## Configuring the Connection This section enumerates the options in the ****Credentials**** and ****Details**** panes in the Azure Blob Storage SAS Token Connector page. The components of the other panes in this page, ****Scheduling**** and ****Name & Describe Your DataSet****, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Azure Blob Storage container. The following table describes what is needed for each field:

Field

Description

Account Name Enter the storage account name.
Shared Access Signature (SAS) Token Enter your account access level SAS token .
After you have entered valid credentials, you can use the same account any time you go to set up a new Domo-Azure Blob Storage connection. You can manage connector accounts in the ****Accounts**** tab in the Data Center. For more information about this tab, see [Manage Connector Accounts](https://domo-support.domo.com/s/article/360042926054?language=en_US "Manage Connector Accounts"). ### Details Pane This pane contains a number of fields for specifying your data and indicating where it's going.

Menu

Description

What file type would you like to import? Select the file type you want to import.
Blob Containers Select the Azure Blob container you want to send your Domo data to.
How would you like to choose your Blob? Specify how would you like to pull your blob file.
Enter Blob Name Prefix Enter the blob name prefix.
Blob Match Type In the Enter Blob Name Prefix, specify whether the blob should contains, startsWith or endsWith the name you have entered.
File Encoding Select the file encoding. By default, UTF-8 is selected.
Advanced
Select the delimiting character Select the delimiting character used in your file. If your delimiter is not listed select Other .
Specify your delimiter Enter the character used to delimit your character separated values (CSV) text.

Input DataSet ID

Enter the DataSet ID (GUID) for the DataSet you want to copy to the selected Azure Blob Storage container. You can find the ID by opening the details view for the DataSet in the Data Center and looking at the portion of the URL following datasources/. For example, in the URL [https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview](https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview) , the DataSet ID is 845305d8-da3d-4107-a9d6-13ef3f86d4a4.

Select Filename Select whether you want to reference your DataSet using the Input DataSet ID or an output file name.
Filename Enter the output file name for your data.
### Advanced
Menu Description
Select the delimiting character Select the delimiting character used in your file. If your delimiter is not listed select 'Other.
Specify your delimiter Enter the character used to delimit your character separated values (CSV) text.
Quote Character Select the desired quote character for parsing CSV files (Double quote is the default quote character for CSV standard.)
Custom Quote Character Enter the desired CSV Quote character.
Escape Character Select the desired escape character for parsing CSV files.
Custom Escape Character Enter the desired CSV escape character.
### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). # Azure Data Lake Gen2 OAuth Connector Source: https://www.domo.com/docs/s/article/000005162 ## Intro Azure Data Lake Gen2 OAuth connector is an enterprise-wide hyper-scale repository for big data analytic workloads. It makes Azure Storage the foundation for building enterprise data lakes on Azure. It allows you to easily manage massive amounts of data and helps to speed up your transition from proof of concept to production. You can retrieve data files in any of the following file types: CSV, XLS, XLSX and JSON. For more information about Azure's API, see [https://docs.microsoft.com/en-us/azu...ta-lake-store/](https://docs.microsoft.com/en-us/azure/data-lake-store/ "https://docs.microsoft.com/en-us/azure/data-lake-store/"). You connect to your Azure Data Lake Gen2 OAuth Connector account in the Data Center. This topic discusses the fields and menus that are specific to the Azure Data Lake Gen2 OAuth Connector Connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Prerequisites To connect to your Azure Data Lake Gen2 OAuth Connector account and create a DataSet, you must have the following: * Microsoft Azure App Client ID * Microsoft Azure App Client Secret * Tenant ID To obtain credentials, please reach out to your Microsoft account representative. ## Connecting to Your Azure Data Lake Gen2 OAuth Connector Connector This section enumerates the options in the **Credentials** and **Details** panes in the Azure Data Lake Gen2 OAuth Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Azure Data Lake Store Gen2 OAuth account. The following table describes what is needed for each field:

Field

Description

Microsoft Azure App Client ID Enter the client ID (GUID) of the client web app obtained from Azure Active Directory configuration.
Microsoft Azure App Client Secret Enter the secret key of the client web app.
Tenant ID Enter your Tenant ID.
To locate the tenant ID, do the following:
Navigate to Portal.azure.com > Azure Active Directory > Properties .
The Directory ID is your Tenant ID .
Once you have entered valid Azure Data Lake Gen2 OAuth credentials, you can use the same account any time you go to create a new Azure Data Lake Gen2 OAuth Connector DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Manage Connector Accounts](https://domo-support.domo.com/s/article/360042926054?language=en_US "Manage Connector Accounts"). ### Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

What file type would you like to import? Select the file type that you want to import.
Enter Storage Account Name Enter the storage account name.
Container Name Select the container.
How would you like to choose the directory name? Select how you want to choose the directory name.
Discover Directory Name Select the directory name.

Enter Directory Name

Enter the directory name.

test Example for main or root directory.
test/test Example for sub- directory.
test/test/test Example for sub-sub-directory
Would you like to pull data from multiple files? Select if you want to retrieve data from multiple files in the directory. If you want to pull data from multiple files, select the files with same schema.
Discover Files Select the files with the same schema to pull the data.
How would you like to choose the File name? Select how you want to choose the file name.
Enter File Name Enter the File name.
Discover File Name Select the File name.
### Advanced Pane This pane contains the **Advanced** menu.

Menu

Description

Select the delimiting character Select the delimiting character used in your file. If your delimiter is not listed here, select Other .
Specify your delimiter Enter the character used to delimit your character separated values (CSV) text.
### Troubleshooting #### While trying to authenticate using the connector, the following error message is displayed. Oauth Error This issue is related to permissions. You need the appropriate permission to access Azure Storage otherwise the connection will fail. To add the required permissions, do the following: Select the **App -> API Permissions -> Add a permission -> Select Azure Storage -> Check user\_impersonation -> Add permissions** ### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). # Google BigQuery Workload Identity Federation Connector Source: https://www.domo.com/docs/s/article/000005176 ## Intro Querying massive datasets can be time consuming and expensive without the right hardware and infrastructure. Google Big Query solves this problem by enabling super-fast, SQL-like queries against append-only tables, using the processing power of Google's infrastructure. Data first needed to be loaded into Google BigQuery from where it could be effectively queried by data vendors. Workload Identity Federation allows for more secure connection as the input only contains external credentials metadata without any sensitive information. The external credential metadata can be used on external environment to generate temporary/short-live token for required operations. For more details, refer to [Workload Identity Federation](https://cloud.google.com/iam/docs/workload-identity-federation "Workload Identity Federation"). This topic discusses the fields and menus that are specific to the Google BigQuery Workload Identity Federation Connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). **Note:** The owner of a writeback dataset must also be an owner or co-owner of the input dataset. ## Prerequisites To configure this connector, you will need the following: * **WORKLOAD IDENTITY FEDERATION CLIENT LIBRARY CONFIG JSON KEY** as a JSON Configuration file. * A Project ID for a GCP project. Follow the steps below to obtain the credentials: 1. Create a project in the Google Developers Console if you do not have an existing project in GCP. 2. Enable the Big Query APIs in your GCP instance. 3. Create a Workload Identity Pool and Provider. 4. Create a service account and associate it with the pool or with an existing service account with the pool. 5. Download the JSON configuration file to use with the connector. The following steps explain in detail how to create your project and obtain the needed credentials. ### Step 1: Creating a Project in the Google Developers Console **Note:** If you already have a project you'd like to use, you can skip this step. To create a project in the Google Developers Console, do the following: 1. Go to [https://console.developers.google.com](https://console.developers.google.com "https://console.developers.google.com"). 2. Click the dropdown arrow next to **My Project**. googlesheets_writeback_1.png 3. Click **New Project** and provide a name for the new project and the Parent organization or folder for the new project. Select Project Name.jpg 4. Click **Create**. ### Step 2: Enabling the Google BigQuery API To enable the Google BigQuery API for your project, do the following: 1. Click the burger menu and select the **API & Services** menu. Enable Bigquery api.jpg 2. Select **Library** and then search for the Google BigQuery API. 3. Click the Google **BigQuery API** **Enable** ### Step 3: Creating a Workload Identity Pool and Provider Follow the steps given below to create a Workload Identity Pool and Provider: 1. Click the burger menu in the console and select **IAM & Admin**. IAM and Admin.png 2. Select the **Workload Identity Federation** option. 3. Click **create pool**. create pool.png 4. Enter a name for the pool in Step-1 and ensure that the **enable pool** is selected. Enable Pool.png 5. In step 2, you will be prompted to select a provider. Select **AWS**. 6. Under the **provider details** tab, enter the name of the Provider and ID, for example, **Domo AWS**. Add Provider Pool.png 7. You will need to provide Domo's AWS account id in the **AWS Account ID box**. Based on where your Domo instance is located, use one of the account ids listed below: ``` US: 339405024189 AU: 010251424122 EMEA (IE): 687132894031 JP: 622384692065 CA: 710710207408 ``` 8. Contact Domo Support if you are unsure which id to use. 9. You can optionally configure additional provider attributes in Step-3. ### Step 4: Grant a Service Account access to the Workload Pool 1. On the burger menu, navigate to **IAM** and select **Workload identity federation** list and then select the recently created pool. 2. Select **Grant Access** located at the top of the window. 3. On the right-side pane, you will be prompted to select which service account you want to give access to. 4. Select the appropriate service account from the **Select Service Account** dropdown. 5. Click **Save**. 6. Under **Configure your application**, select the provider you created with Domo's AWS account id. 7. Click the **Download Config** button to download the JSON configuration file. This file will be used to power up the connector. ## Configuring the Connection This section enumerates the options in the **Credentials** and **Details** panes in the Google BigQuery Workload Identity Federation Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in great detail in [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Domo developer account. The following table describes what is needed for each field:

Field

Description

WORKLOAD IDENTITY FEDERATION CLIENT LIBRARY CONFIG JSON KEY

Configuration of external credentials JSON file containing external authentication metadata. This file is obtained from Step-4 in the instructions above.

Project ID Project id of the project in GCP that has access to Google BigQuery and the workload pool.
Once you have entered valid credentials, you can use the same account any time you go to set up a new Domo Google BigQuery Workload Identity Federation connection. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](https://domo-support.domo.com/s/article/360042926054?language=en_US "Managing User Accounts for Connectors"). ### Details Pane This pane contains a number of fields for specifying your data and indicating where it's going.

Menu

Description

Report Run the following reports based on the requirements:
Query Runs a Google BigQuery SQL query and returns results if it is successful.
Table Data Retrieves table data.
Table Information Returns the specified table resource by table ID. This method does not return the data in the table, it only returns the table resource, which describes the structure of this table.
SQL Dialect Select SQL Dialect that you want to use. Defaults to Standard SQL.
Query Enter the query text.
Query Parameters Enter the query parameter value, it is the initial value for query parameter. The last run date is optional by default it is '02/01/1700' if is not provided. For example: `!{lastvalue:_id}!=1,!{lastrundate:start_date}!=02/01/1944`.
Allow Large Results If enabled, allows arbitrarily large results to be written to the temporary destination table and delete it when the job is finished. Dataset name is required to create the temporary table.
Dataset\_Names Select the dataset names from the available list of datasets.
Table Names Select table names from available list of tables.
Processing Location Enter a location where your query will run. Queries that run in a specific location may only reference data in that location.
Max Results Max Results is the number of results returned per page of data. By default, Max Results is 10,000 results per page. If your dataset throws an out of memory error, decrease Max Results.
Use Google BigQuery Schema Select this checkbox to use the schema received from Google BigQuery.\
This is useful when a column's datatype may be perceived incorrectly to Domo: e.g. your table has '123' in a String column.
## Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). # ADLS Gen 2 OAuth Writeback Connector Source: https://www.domo.com/docs/s/article/000005178 ## Intro Azure Data Lake Storage is Microsoft's optimized storage solution for big data analytics workloads. A fundamental part of Data Lake Storage Gen2 is the addition of a hierarchical namespace to Blob storage. Use this connector to bring-in data from Azure storage into Domo for creating visual insights on the data. Azure Data Lake Gen2 OAuth WriteBack connector provides file system semantics, file-level security, and scale. It makes Azure Storage the foundation for building enterprise data lakes on Azure. It allows you to easily manage massive amounts of data and helps to speed up your transition from proof of concept to production. Azure Data Lake Storage Gen2 is a set of capabilities dedicated to big data analytics, built on Azure Blob storage. Azure Data Lake Storage Gen2 is the result of converging the capabilities of the two existing storage services, Azure Blob storage and Azure Data Lake Storage Gen1. Use Domo's prebuilt Azure Data Lake Storage Gen2 WriteBack connector that connects with Azure Active Directory to export your data from a Domo dataset to your Microsoft Azure Data Lake Storage Gen2. For more information about Microsoft Azure Data Lake Gen2, see [https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-introduction](https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-introduction "https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-introduction"). You export data to a Azure Data Lake Gen2 in the Data Center. This topic discusses the fields and menus that are specific to the Microsoft Azure Data Lake Gen2 Writeback connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). **Note:** The owner of a writeback dataset must also be an owner or co-owner of the input dataset. ## Prerequisites To configure this connector, you need the following: * Your client ID (GUID) and secret key of the client web app obtained from Azure Active Directory configuration * Your Microsoft Azure Data Lake Storage account name * Your Tenant ID * Client Secret Key ### Configuring Your Azure App To create a connection with your Microsoft Exchange Metrics account, you must first create a Microsoft Azure Web App to obtain the necessary client ID and secret. \***\*To configure an Azure App\*\***: 1. Login into [Azure Portal](https://portal.azure.com/#home "https://portal.azure.com/#home"). 2. Select \***\*Azure Active Directory > App Registrations > New Registration\*\***. New_registration.png 3. Fill out the registration form as follows: * Name: Enter name for your application. * Supported account types: Select an option to specify who can use this application or access this API. * Redirect URI: Enter the redirect URI. The authentication response is sent to this URI after successfully authenticating the user. Providing the URI at this stage is optional and it can be changed later, but a value is required for most of the authentication scenarios. clipboard_eac88f9aa2966a791f11417756903afc4.png 4. Click **\*\*\*\***Register\*\*\*\*\*\***. An overview of your registered App will appear. The \***\*Application ID\*\*\*\* that appears here is the \***\*Client ID\*\*** you will enter in the \***\*Credentials\*\*** pane in Domo. 5. Click **\*\*\*\***API Permissions >> +Add a permission\*\*\*\*\*\*\*\*. 6. \***\*Request API permissions\*\*** section appears. Add the API permissions for your application. clipboard_e9ed1fc0137b700a6e1c7bb384b55b721.png 7. Now, click on **\*\*\*\***Certificates and secrets\*\*\*\*\*\*\*\*. Certificates can be used as secrets to prove the application's identity when requesting a token. Also, can be referred to as public keys. 8. Click \***\*+ \*\***New client secret\*\*\*\*\*\*\*\*. 9. Specify the client secret description and the expiry period for your client secret, and click **\*\*\*\***Add\*\*\*\*\*\*\*\*. 10. Copy the value and paste it into the **\*\*\*\***Client Secret\*\*\*\*\*\*\*\* field in the \***\*Connector credentials\*\*** section in Domo. 11. Specify the client secret description and the expiry period for your client secret, and click **Add**. 12. Copy the value and paste it into the **Client Secret** field in the Connector credentials section in Domo. ### Assigning User Role Permissions 1. Go to the **Container** in which you would like to write back the data. 2. Select **IAM**. 3. Select **Add Roles**. 4. Give **Storage Blob Data Contributor** role to the user. ## Configuring the Connection This section enumerates the options in the **\*\*\*\***Credentials\*\*\*\*\*\*\*\* and **\*\*\*\***Details\*\*\*\*\*\*\*\* panes in the ADLS Gen 2 OAuth Writeback Connector page. The components of the other panes in this page, **\*\*\*\***Scheduling\*\*\*\*\*\*\*\* and **\*\*\*\***Name & Describe Your DataSet\*\*\*\*\*\*\*\*, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Azure Data Lake file system (container). The following table describes what is needed for each field:

Field

Description

Client ID Enter the client ID (GUID) of the client web app obtained from Azure Active Directory configuration. See Prerequisites for more information.
Client Secret Enter the secret key of the client web app.
Tenant ID Enter your Tenant ID. Go to Portal.azure.com \> Azure Active Directory > Properties. The Directory ID is your Tenant ID.
Once you have entered valid credentials, you can use the same account any time you go to set up a new Domo-Azure Data Lake Storage Gen2 connection. You can manage connector accounts in the **\*\*\*\***Accounts\*\*\*\*\*\*\*\* tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane This pane contains a primary **\*\*\*\***Reports\*\*\*\*\*\*\*\* menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

Input DataSet ID

Enter the DataSet ID (GUID) for the DataSet you want to copy to the selected Azure Data Lake Storage file system (container). You can find the ID by opening the details view for the DataSet in the Data Center and looking at the portion of the URL following datasources/.

Example, in the URL [https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview\{](https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview\{)" "} , the DataSet ID is 845305d8-da3d-4107-a9d6-13ef3f86d4a4.

File System Name Enter the file system name where you wish to upload the file. A file system acts as a container for your files.
Select Filename Select whether you want to reference your DataSet using the Input DataSet ID or an output file name .
Filename Enter the output file name for your data.
### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). # Connect Domo to Google BigQuery Source: https://www.domo.com/docs/s/article/000005237 ## Intro This article explains how to connect Domo to Google BigQuery using Cloud Integrations, enable writeback to BigQuery, configure native transform, and set up OAuth authentication. **Note:** Cloud Integrations setup consists of two parts: read-only, which enables virtual tables that read from BigQuery for creating cards, alerts, or inputs in Magic ETL DataFlows; and writeback, which adds the ability to write data back to BigQuery. You can start with read-only and configure writeback later. *** ## Prerequisites Complete these steps before setting up the BigQuery integration. **Create a Domo service account (recommended).** You can use any Domo account, but creating a dedicated account is best practice. Assign the following roles: * Manage Cloud Accounts * Manage DataSet For more information, see [Managing User Roles and Grants](/docs/s/article/360043438973). **Create a service account in Google Cloud Console.** Choose one of the following authentication methods: * **Option 1 —** Key file. Create a BigQuery service account, grant the required roles and permissions (see [Roles and Permissions](#roles-and-permissions) below), add a key to the service account, and download the JSON key file for authentication. * **Option 2 —** Workload Identity Federation (WIF). Open a Domo support ticket to request BigQuery integration using WIF, specifying the provider type (AWS or OIDC). Domo provides an Account ID for AWS or an Issuer URL and Allowed Audiences for OIDC. Create a Workload Identity Pool in Google Cloud IAM, add a provider using the details from Domo Support, and update the mapping to point `assertion.sub` to `google.subject`. Create a BigQuery service account, grant the required roles and permissions, including Workload Identity User (see [Roles and Permissions](#roles-and-permissions) below), and download the JSON configuration file from the Connected Service Accounts panel. When exporting the configuration, use the audience provided by Domo Support. ### Roles and Permissions The BigQuery service account must have the following roles. **Read-only integration** * Roles: BigQuery Data Viewer * No additional permissions are required for read-only access. **Writeback and native transform** * Roles: * BigQuery Job User * Service Account Token Creator (only if using WIF) * Additional permissions: * `bigquery.datasets.create` * `bigquery.datasets.delete` * `bigquery.datasets.get` * `bigquery.tables.create` * `bigquery.tables.delete` * `bigquery.tables.get` * `bigquery.tables.getData` * `bigquery.tables.list` * `bigquery.tables.update` * `bigquery.tables.updateData` * `resourcemanager.projects.get` * `bigquery.jobs.create` * `bigquery.jobs.get` * `bigquery.jobs.update` **Note:** Domo only deletes BigQuery tables and datasets it creates for temporary staging. Domo does not remove objects it did not create or objects intended to be permanent. ## Review the Architectural Overview The following diagram illustrates the Cloud Integrations–BigQuery integration. BigQuery architecture diagram ## Open the Domo on BigQuery Page 1. In the navigation header, select **Data Warehouse**. 2. Select **Connect Data** > **BigQuery**. The **Domo on BigQuery** page appears. Domo on BigQuery page 3. Select **Connect BigQuery** to create a new integration, or select **Manage Integrations** to modify existing integrations. If you selected **Manage Integrations**, a list of your integrations appears. BigQuery cloud integrations list 4. Select the wrench icon next to an integration to view available options. The options shown depend on your access level. From the integration overview, you can create a new integration, update an existing one, or configure writeback, native transform, and OAuth. ## Create a BigQuery Integration Begin on the **Domo on BigQuery** page (see [Open the Domo on BigQuery Page](#open-the-domo-on-bigquery-page)). 1. Enter a name to identify this BigQuery integration in Domo. The name does not need to match anything in BigQuery and can be changed later. 2. (Optional) Enter a short description to help others understand the purpose of this integration. This description is visible only in the integration details. 3. Select an existing service account from **BigQuery Service Account**, or select **Add Account** to create a new one. This account authenticates with BigQuery and determines access to tables. To create a service account, see [Create a BigQuery Account](#create-a-bigquery-account). **Important:** Changing the service account later may require remapping DataSets or Magic ETL DataFlows if access permissions differ. BigQuery integration setup form 4. Select your **BigQuery Region**. 5. Select **Save Integration**. A confirmation screen appears when the integration is created successfully. 6. Select **Proceed to Integration Overview**. The integration opens. Integration created successfully ## Create a BigQuery Account Every BigQuery integration in Domo requires an authenticated BigQuery service account. Once created, a single service account can be reused across multiple integrations. Begin in the BigQuery service account creation flow in Domo. Choose one of the following authentication methods. Authentication method selection ### Option 1: Use a BigQuery Service Account Key File 1. Enter a name to identify the BigQuery service account in Domo. The name can be changed later. **Tip:** Use a clear, distinct name to differentiate between multiple service accounts and integrations. 2. Upload the JSON key file you downloaded from the Google Cloud Console. Key file upload form ### Option 2: Use Workload Identity Federation (WIF) 1. Enter a name to identify the BigQuery service account in Domo. The name can be changed later. 2. Enter the **Project ID** where you created your service account. 3. Upload the JSON configuration file you downloaded from the Google Cloud Console. WIF configuration file upload form ## Enable BigQuery Writeback Writeback allows Domo to create and update tables in your BigQuery instance using the associated service account. Enable it when you want to use BigQuery as an output for Magic ETL DataFlows. **Note:** If you only need to read BigQuery data, skip this section. Even when writeback is enabled, access must be explicitly granted to individuals or groups. Basic access does not automatically include writeback privileges. You can manage access levels on the **Accounts** page by selecting **Account Sharing** next to the relevant BigQuery service account. To configure writeback, begin on the integration's **Settings** page. 1. Navigate to **Data Warehouse** > **Connect Data** > **BigQuery**, select **Manage Integrations**, then select the wrench icon next to your integration. The **Settings** page appears. Integration Settings page 2. In the **Write** section, select **Set up write**. The **Configure Write Access** dialog appears. 3. Select the BigQuery project to use for writing data from Domo. 4. Select the default dataset for data output. Configure Write Access dialog 5. Select the authorization checkbox to confirm that Domo is authorized to create, modify, and delete objects in BigQuery using the service account. 6. Select **Save & Enable Write**. The **Write** section on the **Settings** page displays the configured project and dataset with a green checkmark. Finalize Write Integration dialog Settings page with writeback enabled ## Enable Native Transform Native transform is optional. Without it, Domo uses its own compute resources to read and write BigQuery data. When enabled for an integration, anyone who shares that integration can choose BigQuery compute for individual Magic ETL DataFlows. This is a per-pipeline selection, not a global setting. **Note:** The project and dataset values for native transform are shared with the writeback configuration. Changing them in one place changes both. To configure native transform, begin on the integration's **Settings** page (see [Enable BigQuery Writeback](#enable-bigquery-writeback) for navigation steps). 1. In the **Native transform** section, select **Set up native transform**. The **Configure Native Transform** dialog appears. 2. Select the BigQuery project for native transform. 3. Select the default BigQuery dataset. Configure Native Transform dialog 4. Select the authorization checkbox to confirm that Domo is authorized to create, alter, update, and delete objects in your BigQuery environment. 5. Select **Save & Enable Native Transform**. The **Native transform** section on the **Settings** page displays the configured project and dataset with a green checkmark. Finalize Native Transform dialog Settings page with writeback and native transform enabled ## Configure OAuth When OAuth is enabled for a cloud integration, all DataSets connected through that integration use OAuth authentication. When you view a card or preview a DataSet built with an OAuth-enabled integration, Domo prompts you to enter your Google Cloud Platform (GCP) credentials. Domo then queries BigQuery data in the context of your account, rather than the BigQuery service account. **Note:** Currently, Domo enforces OAuth for reading data from BigQuery. This applies to individuals viewing connected DataSets and derived assets such as cards and dashboards. OAuth does not apply to Magic ETL, writeback, or native transforms. These operations use the BigQuery service account instead of an individual GCP account. OAuth configuration is optional. Even without OAuth, Domo can connect to BigQuery to read data, use BigQuery compute, and write data back to BigQuery (if writeback is enabled). To configure OAuth, begin on the integration's **Settings** page (see [Enable BigQuery Writeback](#enable-bigquery-writeback) for navigation steps). 1. In the **OAuth** section, select **Set up OAuth**. The **Configure OAuth Settings** dialog appears. 2. Select an existing configuration from the **BigQuery OAuth Configuration** dropdown, or select **Add OAuth Config...** to create a new one. Configure OAuth Settings — select configuration 3. (Conditional) For new configurations only, enter an **OAuth Configuration Name** and the **Default billing project ID**. This is the GCP project whose billing account will be charged for query usage. **Note:** Enter the Project ID exactly as it appears in GCP, including case sensitivity. Configure OAuth Settings — add new configuration 4. Select **Connect**. A Google sign-in window appears. Google sign-in 5. Select your GCP account and sign in. 6. Select **Save** to apply the OAuth configuration. ## Review Query Metadata Domo provides additional metadata fields for queries executed through BigQuery integrations. These fields help you track and audit query context. They are visible in BigQuery's job history under the job labels. The following metadata fields are available: | Field | Value | | ---------------- | ----------------------------------------------------------- | | `application` | `"ice"` (Domo's internal identifier for Cloud Integrations) | | `customer` | Customer name | | `connection` | BigQuery integration name | | `dataset` | BigQuery integration dataset name | | `data_source_id` | DataSource ID | | `card_id` | DataSource card ID | ## Connect Tables to DataSets After setting up your BigQuery integration, you can connect BigQuery tables to Domo DataSets using the **Connect Tables** section in the integration overview. Learn more about [connecting tables to Domo](/docs/s/article/Connect-Tables-in-Cloud-Integrations). ## FAQ No, spaces are not allowed in table names. # Domo on Databricks Source: https://www.domo.com/docs/s/article/000005289 With Cloud Integrations, you can power your Domo instance using Databricks. Use this guide to set up a Databricks integration for read-only and read/write access. After setup, you can use Databricks DataSets to create cards, configure alerts, and build Magic ETL DataFlows. Domo on Databricks overview page *** ## Architectural Overview The diagram below shows how Domo connects to Databricks through Cloud Integrations. Domo queries data live from your Databricks environment; no data is copied to Domo storage. databricks architectural overview.jpg ## Before You Begin * (Recommended) Create a Databricks service account—Create a new Databricks account specifically for this integration. You can use any account with read access in Databricks, but best practice is a dedicated service account with read access to your default Databricks environment. * (Recommended) Create a Domo service account—Create a new Domo account specifically for this integration. Your account's custom role must include the **Manage Cloud Accounts** and **Manage DataSet** grants. * (Conditional) If you are migrating from a federated or connector-based integration, review [Migrate from Federated to Cloud Integrations](/docs/s/article/000005675) before proceeding—Beast Mode formulas written in MySQL syntax may not be compatible with Spark SQL. For more information about roles and grants, see [Manage User Roles and Grants](/docs/s/article/360043438973). ## Set Up Read-Only Access 1. In the navigation menu, select **Data Warehouse** > **Connect Data** > **Cloud Integrations** > **Databricks**. The Databricks Cloud Integrations list opens. The Databricks Cloud Integrations list showing existing integrations and the Add new integration button. 2. Select **+ Add new integration**. The new integration form opens. 3. Enter a name and optional description in the **Integration name** and **Integration description** fields. The new integration form with name, description, and service account fields. 4. Under **Databricks service account**, select an existing account from the dropdown. 5. (Conditional) To create a new service account, fill in the connection details in the **New Databricks Service Account** modal: * Enter a name for the account. * Enter your Databricks server hostname and HTTP path. * In the **Connect with** dropdown, select your authentication method: * **Personal Access Token**—Create a personal access token in your Databricks account and paste it into the **Databricks personal access token** field. New Databricks Service Account modal with Personal Access Token selected. **Important:** Copy the token before leaving the page—Databricks does not display it again. * **M2M OAuth**—Enter your Databricks OAuth application's **Client ID** and **Client Secret** in the **Client ID** and **Client Secret** fields. This authentication method is used by the service account and supports write-back and native transforms, since those operations run under the service account regardless of how it authenticates. New Databricks Service Account modal with M2M OAuth selected, showing Client ID and Client Secret fields. **Note:** Do not include protocol identifiers in the connection URL. `jdbc:databricks://` is assumed; `jdbc:spark://` is not supported. 6. Select **Create integration**. On the success screen, select **Navigate to integration overview** to proceed. Screenshot 2024-10-10 at 10.45.07 AM.png 7. Configure your data freshness settings. Learn about [advanced scheduling](/docs/s/article/4412849158167#use-advanced-scheduling-for-data-freshness) for data freshness. 8. Select an existing configuration from the dropdown, or select **Add OAuth Config...** to create a new one. 9. (Conditional) To create a new configuration: 1. In Databricks, navigate to **Account Console** > **Settings** > **App connections** and add a new app connection for Domo. Enable a custom OAuth application for your Domo instance. For details, see the [Databricks OAuth documentation](https://docs.databricks.com/en/integrations/enable-disable-oauth.html). 2. Add the Domo redirect URLs shown in the modal to your Databricks OAuth app. 3. Back in Domo, enter the **OAuth configuration name**, your **Databricks account identifier**, **Client ID**, and **Client Secret**. Configure OAuth Settings modal showing the configuration form fields. 10. Select **Save**. choose tables.jpg 11. Search for and select Databricks schemas and tables you want to use to create DataSets in Domo. 12. Select **Create DataSets**. Success screen confirming the integration was created. ## Add Databricks Tables to Domo After creating your integration, connect Databricks tables as DataSets in Domo. For step-by-step instructions, see [Connect tables in Cloud Integrations](/docs/s/article/Connect-Tables-in-Cloud-Integrations). The Connect Tables interface with the schema browser on the left and the table list on the right. ## Configure OAuth (Optional) Configure OAuth to require users to sign in with their own Databricks credentials when they view cards or DataSets connected through that integration. OAuth does not currently apply to Magic ETL, write-back, or native transforms. **Note:** This refers to per-user OAuth configured here for card and DataSet viewing. It does not apply to M2M OAuth used to authenticate the service account itself. If your service account authenticates via M2M OAuth, write-back and native transforms continue to work normally, since those operations always run under the service account. 1. From the Databricks Cloud Integrations list, select the **wrench** icon on the integration you want to configure, then select **Settings**. 2. In the **Settings** panel, under **OAuth**, select **Set up OAuth**. The **Configure OAuth Settings** modal opens. Integration Settings panel showing the Set up OAuth and Set up write & transform options. 3. Select an existing configuration from the dropdown, or select **Add OAuth Config...** to create a new one. 4. (Conditional) To create a new configuration: 1. In Databricks, navigate to **Account Console** > **Settings** > **App connections** and add a new app connection for Domo. Enable a custom OAuth application for your Domo instance. For details, see the [Databricks OAuth documentation](https://docs.databricks.com/en/integrations/enable-disable-oauth.html). 2. Add the Domo redirect URLs shown in the modal to your Databricks OAuth app. 3. Back in Domo, enter the **OAuth configuration name**, your **Databricks account identifier**, **Client ID**, and **Client Secret**. Configure OAuth Settings modal showing the configuration form fields. 5. Select **Save**. ## Set Up Write & Native Transform Enable write-back, native transforms, or both on an existing Databricks integration. You must complete the read-only setup before proceeding. 1. From the Databricks Cloud Integrations list, select the **wrench** icon on the integration you want to configure, then select **Settings**. 2. In the **Settings** panel, under **Write & native transform**, select **Set up write & transform**. The **Configure Write & Native Transform** modal opens. Integration Settings panel showing the Set up write & transform option. 3. Under **What do you want to be able to do?**, select one or both capabilities: * **Write to Databricks from connectors**—enables Domo to write data back to Databricks. * **Execute Magic ETL transformations natively**—enables Magic ETL DataFlows to run transformations directly within your Databricks environment. 4. Under **Default write location**, select your target **Catalog** and **Schema** from the dropdowns. This is the Databricks location where Domo writes data during write-back operations and native transform executions. Configure Write & Native Transform modal with capability checkboxes and write location dropdowns. 5. Select **Save** to complete the setup. ## Troubleshoot If authentication fails when configuring your integration: * Verify that your personal access token or M2M OAuth credentials (Client ID and Client Secret) are correct and have not expired. * Confirm that the Databricks service account has read access to your default Databricks environment. If the Databricks connection URL is not accepted: * Confirm that you are not including a protocol identifier. `jdbc:databricks://` is assumed; `jdbc:spark://` is not supported. * Confirm you are using the correct server hostname and HTTP path from **SQL Warehouses** > *your warehouse name* > **Connection details** in Databricks. If your catalog or schema does not appear in the dropdowns during write & native transform setup: * Confirm that the Databricks service account has the necessary permissions to access the target catalog and schema. * Try refreshing the integration settings and repeating the setup steps. When a DataFlow uses a Databricks-sourced DataSet, Domo queries the data live from Databricks when the DataFlow runs. Domo checks Databricks-sourced DataSets for updates at the configured freshness interval using the `lastModified` field returned by Databricks's `DESCRIBE DETAIL` command. If Domo detects an update, it triggers any DataFlows that use that table. **Note:** Change detection via `DESCRIBE DETAIL` applies to tables only. Databricks views do not support this check, so Domo treats views as updated on every freshness check cycle — meaning any DataFlow using a Databricks view will be triggered every interval regardless of whether the underlying data changed. ## Next Steps * [Cloud Integrations overview](/docs/s/article/4412849158167)—Learn how Cloud Integrations works and which integrations are supported. * [Magic ETL DataFlows](/docs/s/article/360055259234)—Build and run DataFlows using your Databricks-sourced DataSets. * [Migrate from Federated to Cloud Integrations](/docs/s/article/000005675)—Guidance for migrating existing integrations. # Domo Free | Overview Source: https://www.domo.com/docs/s/article/000005309 ## Intro Domo Free Trial is a 30-day enterprise version of Domo with no credit limit. If you are a Freemium user, you can read about Freemium [here](/docs/s/article/000005309). There are no new sign-ups for Freemium. Domo Free Trial includes the following capabilities: * Data connection * Magic ETL * BI and analytics * Embedded analytics * Business apps * Workflow automation * Governance and security * Cloud scalability * Collaboration Domo Free Trial does not include: * Auto ML * Jupyter Workspaces * Some Governance functions To add these features to your instance, contact your [sales representative ](https://www.domo.com/form/talk-to-sales). **Tip:** Learn more about consumption and using credits by reviewing the [Consumption Supplemental Terms ](https://www.domo.com/consumption-terms) and reading this article: [What Are Consumption Credits and How Do They Work?](https://domo-support.domo.com/s/article/000005280) *** ## Access Domo Free Trial Follow these steps to access Domo Free Trial: 1. Go to [Domo.com ](https://www.domo.com/) and select **Try Free** to display the free account signup page. try free.jpg 2. Enter a business email and select **Create Account**. create free account.jpg Verify your email and configure login credentials for your Domo Free Trial. ## Required Grants Grants are authorizations inside Domo that allow individual users to perform and manage tasks and operations. You can add grants to custom roles, which are a way to give users a set of customizable permissions to your Domo instance. Many Domo features require users to have certain grants to access them. By default, the user who signed up for Domo Free Trial has the following grants. You can create one or more custom roles for other users as needed and include one or both grants for any role. * **Manage card payments —** This grant allows users to manage card payments for a Domo Free Trial instance. * **View credit reports —** This grant allows users to view credit reports for a Domo Free Trial instance. Learn more about [system](/docs/s/article/360043438953) and [custom](/docs/s/article/360043438973) roles. ## Understand Credits in Domo Free Trial Credits are units that quantify usage within the Domo platform. With your 30-day trial, you have no credit caps. **Tip:** Learn more about [consumption credits](/docs/s/article/000005280) or view [pricing and plans](https://www.domo.com/pricing) [](https://www.domo.com/pricing) for the full version of Domo. There are several different types of credit consumption, including: * **Data storage —** 1 credit per million rows stored in the Domo platform. * **Data ingest/refresh —** 1 credit per table created or updated. * **Data write-back —** 1 credit per table written. * **DataFlow: Magic ETL —** 1 credit per output table created or updated. * **DataFlow:** **Data Science —** 2 credits per output table created or updated. To view your credit usage, navigate to **Admin** > **Company Settings** > **Credit Utilization.** From the **Credit Utilization** page, you can view your used credits, subscription information, and credit balance. ## Usage Bar In a Domo Free Trial, users with the appropriate [grants](#required-grants) can see the usage bar at the top of the screen on the landing page. Screenshot 2024-11-11 at 7.49.41 AM.png Depending on your [grants](#required-grants), the usage bar includes the following items: * A counter that displays the amount of credits used versus the amount of available credits * **Upgrade —** This option allows you to schedule a meeting with the Domo team or fill out a contact form. Screenshot 2024-11-11 at 7.55.30 AM.png * **Contact us** **—** This option opens the Get Started modal. You can message the Domo team, view popular articles and the Domo Quick Start Cheat Sheet, and or schedule a meeting with a product expert. Screenshot 2024-11-11 at 7.58.44 AM.png ## Upgrade Your Free Trial You can upgrade to the full version of Domo at any time. Select **Upgrade** in the [usage bar](#usage-bar) to schedule a meeting with a member of the Domo sales team or fill out the [contact form](https://www.domo.com/form/talk-to-sales) [](https://www.domo.com/form/talk-to-sales) to request a call from a Domo sales rep. ## End of Free Trial After 30 days, a pop-up displays the option to upgrade your trial or to schedule a call with the Domo sales team. # Domo on Amazon Redshift Source: https://www.domo.com/docs/s/article/000005312 ## Intro This article explains how to connect Domo's Cloud Integrations to Amazon Redshift, allowing you to query and visualize Amazon Redshift data directly in Domo without moving or duplicating data. *** ## Prerequisites You must have an AWS account with access to Redshift to move forward. ## Create or Manage Your Amazon Redshift Integrations To access the integration management interface, follow these steps: 1. Navigate to **Data Warehouse**. 2. Select **Connect Data**. 3. From the list of Cloud Integrations, choose **Amazon Redshift**.\ The **Domo on Amazon Redshift** page appears. 4. Select **Connect Amazon Redshift** to start creating a new integration (see the [integration setup instructions](#create-an-amazon-redshift-integration-in-domo)). 5. Select **Manage Integrations** to modify existing integrations.\ A list of available integrations displays. 6. Select the wrench icon next to an integration to view available options.\ The options shown depend on your access level. Screenshot ## Create an Amazon Redshift Integration in Domo Every Amazon Redshift integration in Domo requires an authenticated AWS service account. Once created, a single service account can be reused across multiple integrations. Follow these steps to create an Amazon Redshift integration in Domo: 1. Provide a name for the integration. This is simply a label to help you identify the integration within Domo. It does not need to match any names in Amazon Redshift and can be changed later if needed. **Tip:** Multiple Amazon Redshift integrations can exist in the same Domo instance, created by you or your colleagues. Clear naming helps users select the correct integration later. For example, separate integrations might be created to connect different tables or manage access levels. 2\. (Optional) Add a description to explain the purpose of this integration and who created it. Most users will only see the integration name in menus and lists. The description is visible only when viewing integration details. 3\. Select an existing Amazon Redshift service account from the drop-down menu or select **Add account** to create a new one. Screenshot You can change the service account later, but switching accounts may require remapping DataSets and ETLs if the new account lacks access to previously used tables. User access may also be affected unless privileges are identical. **Understanding the Architecture** There are three levels in this setup: * Amazon Redshift instance – Exists independently of Domo. * Amazon Redshift service account – Defined in Domo and connects to the Amazon Redshift instance. * Amazon Redshift integration – Uses the service account and adds settings such as connected tables and caching behavior. **Note:** Multiple service accounts can connect to the same Amazon Redshift instance. Multiple integrations can share a single service account. **Access and Sharing** * Initially, only the owner of the service account has access. * The owner can share access with individuals or groups. * If multiple integrations use the same service account, they inherit the same user privileges. * Changes to privileges affect all integrations tied to that account. To review access settings, go to the Accounts Page and select Account sharing next to the relevant Amazon Redshift service account. **Tip:** You can create multiple service accounts for the same PostgreSQL instance.\ Reasons for doing this include:\ Example A: Managing user access separately for different integrations.\ Example B: Applying different caching TTL settings while sharing user access. ## Create an Amazon Redshift Service Account in Domo Every Amazon Redshift integration in Domo relies on an authenticated Amazon Redshift service account. Once created, this account can be reused across multiple Amazon Redshift integrations. Domo provides a dedicated Accounts Page where you can create and manage service accounts for various external services, including Amazon Redshift. After creation, your Amazon Redshift service account will appear on this page. **Important:** Creating a PostgreSQL service account in Domo allows you, other account owners, Domo admins, and anyone with whom the account is shared, to use its credentials to access PostgreSQL and create connected DataSets in Domo. Users will not have access to sensitive values such as passwords, tokens, or keys used by the service account to connect to PostgreSQL. Follow these steps to create an Amazon Redshift service account in Domo: 1. Choose a name to identify this Amazon Redshift service account within Domo. * The name can be changed later. * Use clear, distinctive names to avoid confusion between Amazon Redshift accounts and integrations. * You can create multiple service accounts even if they all point to the same Amazon Redshift instance. 2. Enter the connection URL for your Amazon Redshift instance. 3. Enter your Redshift Username. 4. Enter your Redshift Password. Screenshot # Update Payment Details for Domo Free Source: https://www.domo.com/docs/s/article/000005332 If you need to update your payment information for Domo Free, such as in the event of a failed payment, follow this link to [Stripe ](https://public.domo.com/payments/v1/subscriptions/portal) to manage your billing details. Log in with your Stripe credentials, rather than with Domo credentials. Alternatively, you can access Stripe from within Domo by following the steps below. Screenshot 2023-12-05 at 6.14.25 AM.png **Note:** If you are experiencing failed payments and updating your payment method is not resolving the issue, please contact your financial institution. To access the billing management portal from inside Domo, follow these steps: 1. Log into the Domo instance for which you are updating payment information. 2. In the usage bar at the top of the screen, select **Manage billing** to access your billing details in Stripe. usage bar.jpg 3. In Stripe, make changes to your payment method, billing information, or other settings as needed. manage domo sub.jpg # Domo on MySQL (Beta - RECOMMENDED) Source: https://www.domo.com/docs/s/article/000005451 ## Intro MySQL users can connect their data to Domo through Cloud Integrations native integration. Provide connection parameters and select the tables you want to see as Domo DataSets. Follow the steps in this article to configure your read-only MySQL-Domo connection with Cloud Integrations. ## Configure Read-only Connection to MySQL 1. Navigate to the Domo Data Center. 2. (Conditional) If you're not already there, use the sidebar to go to the **Data Warehouse**. 3. Select **Add New Cloud Account**. add new cloud account.jpg The **Amplify existing cloud warehouses** modal displays. 4. In the **Native integration** section, choose **See More** to see the rest of the options. see more.jpg 5. Select **MySQL**. mysql.jpg 6. Select **+ Add New Integration**. 7. Enter the following connection parameters in the appropriate fields: * **Integration name —** If you need to update your integration in the future, this is the name to search for in the list of integrations. * **Integration description (optional) —** Enter any additional information about the integration. * **MySQL connection URL —** Enter the host and port that represents the MySQL instance you are connecting to. Ex. *[myhost.com](http://myhost.com):3306* * **MySQL username —** The MySQL instance username that has access to the data you are connecting to. * **MySQL password —** The password for the MySQL user. Screenshot 2024-05-07 at 3.21.47 PM.png 8. Configure caching options. You can choose whether to automatically check for data updates and at what interval. Learn about Cloud Integrations [caching rules](/docs/s/article/4412849158167#caching-rules). Screenshot 2024-05-07 at 3.24.52 PM.png 9. Select **Next**. A success message displays. 10. Select **Choose Tables to Connect** to open the table picker. choose tables to connect.jpg 11. Select from schemas and tables and when you're ready, select **Create DataSets**. create datasets.jpg 12. (Optional) In the confirmation modal, you can share your DataSets with other Domo users. share modal.jpg You can now interact with your MySQL DataSets in Domo. mysql data.jpg # Domo on Azure SQL Source: https://www.domo.com/docs/s/article/000005471 ## Intro This article explains how to connect Domo's Cloud Integrations to Azure SQL, allowing you to query and visualize Azure SQL data directly in Domo without moving or duplicating data. *** ## Prerequisites You must have an account with access to Azure SQL to move forward. ## Create or Manage Your Azure SQL Integrations To access the integration management interface, follow these steps: 1. Navigate to **Data Warehouse**. 2. Select **Connect Data**. 3. From the list of Cloud Integrations, choose **Azure SQL**.\ The **Domo on Azure SQL** page appears. 4. Select **Connect Azure SQL** to start creating a new integration (see the [integration setup instructions](#create-an-azure-sql-integration-in-domo)). 5. Select **Manage Integrations** to modify existing integrations.\ A list of available integrations displays. 6. Select the wrench icon next to an integration to view available options.\ The options shown depend on your access level. Screenshot ## Create an Azure SQL Integration in Domo Every Azure SQL integration in Domo requires an authenticated service account. Once created, a single service account can be reused across multiple integrations. Follow these steps to create your Azure SQL integration in Domo: 1. Provide a name for the integration. This is simply a label to help you identify the integration within Domo. It does not need to match any names in Azure SQL and can be changed later if needed. **Tip:** Multiple Azure SQL integrations can exist in the same Domo instance, created by you or your colleagues. Clear naming helps users select the correct integration later. For example, separate integrations might be created to connect different tables or manage access levels. 2\. (Optional) Add a description to explain the purpose of this integration and who created it. Most users will only see the integration name in menus and lists. The description is visible only when viewing integration details. 3\. Select an existing Azure SQL service account from the drop-down menu or select **Add account** to create a new one.\ You can change the service account later, but switching accounts may require remapping DataSets and ETLs if the new account lacks access to previously used tables. User access may also be affected unless privileges are identical. 4\. Enter the name of the Database that contains your Azure SQL tables. **Understanding the Architecture** There are three levels in this setup: * Azure SQL instance – Exists independently of Domo. * Azure SQL service account – Defined in Domo and connects to the Azure SQL instance. * Azure SQL integration – Uses the service account and adds settings such as connected tables and caching behavior. **Note:** Multiple service accounts can connect to the same Azure SQL instance. Multiple integrations can share a single service account. **Access and Sharing** * Initially, only the owner of the service account has access. * The owner can share access with individuals or groups. * If multiple integrations use the same service account, they inherit the same user privileges. * Changes to privileges affect all integrations tied to that account. To review access settings, go to the Accounts Page and select Account sharing next to the relevant Azure SQL service account. **Tip:** You can create multiple service accounts for the same PostgreSQL instance.\ Reasons for doing this include:\ Example A: Managing user access separately for different integrations.\ Example B: Applying different caching TTL settings while sharing user access. Screenshot ## Create an Azure SQL Service Account in Domo Every Azure SQL integration in Domo relies on an authenticated Azure SQL service account. Once created, this account can be reused across multiple Azure SQL integrations. Domo provides a dedicated Accounts Page where you can create and manage service accounts for various external services, including Azure SQL. After creation, your Azure SQL service account will appear on this page. **Important:** Creating a PostgreSQL service account in Domo allows you, other account owners, Domo admins, and anyone with whom the account is shared, to use its credentials to access PostgreSQL and create connected DataSets in Domo. Users will not have access to sensitive values such as passwords, tokens, or keys used by the service account to connect to PostgreSQL. Follow these steps to create an Azure SQL service account in Domo: 1. Choose a name to identify this Azure SQL service account within Domo. 2. * The name can be changed later. * Use clear, distinctive names to avoid confusion between Azure SQL accounts and integrations. * You can create multiple service accounts even if they all point to the same Azure SQL instance. 3. Enter the name of your server or its IP address. 4. Enter your Azure SQL Username. 5. Enter your Azure SQL Password. Screenshot # Google BigQuery Workload Identity Federation Data Connector Source: https://www.domo.com/docs/s/article/000005473 ## Intro Google BigQuery Enterprise is a cloud-based big data analytics web service for processing very large read-only data sets. You can use Domo's Google BigQuery connector to pull data from a specified project. Google BigQuery queries are written using a variation of the standard SQL SELECT statement. You can connect to your Google BigQuery Workload Identity Federation Data account in the Data Center. This topic discusses the fields and menus that are specific to the Google BigQuery Workload Identity Federation Data connector user interface. To add DataSets, set update schedules, and edit DataSet information, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Prerequisites To connect to your Google BigQuery Workload Identity Federation Data account and create a DataSet, you must have the following: **Note:** The following steps highlight how to create a WIF configuration file, which can also be used when setting up a Cloud Integrations connection to BigQuery. * If you have an existing Workload Identity Federation account set up in the Google Cloud console, then follow the steps below: 1. From the drop-down list, select **Use an existing Workload Identity Federation**. 2. If you select **Enter configuration values manually** from the drop-down list, then: 1. Enter the **Project Number**, **Project ID**, **Pool ID**, **Provider ID**, and the **Service Account Email**. 2. To allow external identities to impersonate a service account, you need to grant Workload Identity User role (roles/iam.workloadIdentityUser) on the service account. You can grant the role to a specific external identity or to multiple external identities. * 2. 1. 1. Navigate to the Workload Identity Pool [Workload Identity Pool page](https://console.cloud.google.com/iam-admin/workload-identity-pools?project=undefined) 2. Click the pool you have created. 3. Click **grant access**. 4. Select the service account you have setup. 5. You can grant access to all identities in the pool by selecting **Allow access to all identities in the pool** from the drop-down list, or you can filter by the user's email address, by selecting **Filter by user email address** from the drop-down list, or you can filter by a unique GUID ID representing the connector and your Domo instance, by selecting **Filter by unique code representing your Domo instance and connector**from the drop-down list. 3. If you select **Enter the JSON configuration from Google Cloud Console** from the drop-down list, then: 1. Enter the JSON Configuration for the Workload Identity Federation. 2. You can limit the external identities access by selecting any one of the following option from the filter: * **Filter by user email address** * **Filter by unique code representing your Domo instance and connector** * **Allow access to all identities in the pool** * If you do not have an existing Workload Identity Federation account setup in Google Cloud console, then follow the below steps: 1. Select **Go through prerequisite** from the drop-down list. 2. You need to setup a google cloud project. 1. Navigate to [Google Cloud Dashboard](https://console.cloud.google.com/projectselector2/home/dashboard). 2. Click **Create Project**. 3. Enter the **Project Name** and **Location** and select **Create**. 4. Navigate to [Google Cloud Console](https://console.cloud.google.com/welcome), the created project information appears. 5. Enter the **Project Number** and **Project ID**. 6. To provide the project with access to **Identity and Access Management (IAM) API**, **Cloud Resource Manager API**, **IAM Service Account Credentials API**, **Security Token Service API**, navigate to [Enable access](https://console.cloud.google.com/apis/enableflow?apiid=iam.googleapis.com,cloudresourcemanager.googleapis.com,iamcredentials.googleapis.com,sts.googleapis.com) API, click **Next**, and click **Enable**. 3. To create a workload identity pool and provider: 1. Navigate to [Workload Identity Pools page](https://console.cloud.google.com/iam-admin/workload-identity-pools?project=undefined). 2. If the previous link does not open, then go to **IAM & Admin** > **Workload Identity Federation**. 3. Click **Get Started**. 4. Enter the created **Pool ID**. 5. From the provider drop-down, select **SAML**. 6. Enter the **Provider ID**. 7. Download the metadata file and upload to [Google](https://app.domo.com/DomoConnectors/DomoWIF/metadata.xml). 8. To configure the provider attributes, in Google 1: **google.subject** is the key and **assertion.subject** is the value. 9. Save your workload identity pool and provider. 4. If you do not have a service account, you need to set up the account: **Note:** Your service account doesn't need to be in the same project as your workload identity pool and provider. 1. To create a service account, navigate to [create service account](https://console.cloud.google.com/projectselector2/iam-admin/serviceaccounts/create).or if you already have a service account, navigate to [service account page](https://console.cloud.google.com/iam-admin/serviceaccounts?project=undefined). 2. Enter the **Service Account Email**. 3. Grant the service account access to resources that you want Domo to access. 4. To allow the external workload to impersonate the service account:\ **Note:** To allow external identities to impersonate a service account, you need to grant the user the Workload Identity User role (roles/iam.workloadIdentityUser) on the service account. You can grant the role to a specific external identity, or to multiple external identities 1. 1. 1. Navigate to the Workload Identity Pool [Workload Identity Pool page](https://console.cloud.google.com/iam-admin/workload-identity-pools?project=undefined) 2. Click the pool you have created. 3. Click **grant access**. 4. Select the service account you have already setup. 5. You can grant access to all identities in the pool by selecting **Allow access to all identities in the pool** from the drop-down list, or you can filter by the user's email address, by selecting **Filter by user email address** from the drop-down list, or you can filter by a unique GUID ID representing the connector and your Domo instance, by selecting **Filter by unique code representing your Domo instance and connector**from the drop-down list. 6. If needed download the configuration file. This file can be used to create an account in Domo later. ## Connecting to Your Google BigQuery Workload Identity Federation Data Account This section enumerates the options in the **Credentials** and **Details** panes in the Google BigQuery Workload Identity Federation Data Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in great detail in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Credentials Pane This pane contains fields for entering credentials to connect to your Google BigQuery Workload Identity Federation Data account. The following table describes what is needed for each field: | Field | Description | | --------------------- | ------------------------------------------------------------------------------------ | | Project Number | Enter the project number of the project you created. | | Project ID | Enter the project ID of the project you created. | | Pool ID | Enter the pool ID. | | Provider ID | Enter the provider ID. | | Service Account Email | Enter the service account email address generated for the chosen service account id. | Once you have entered valid Google BigQuery Workload Identity Federation Data credentials, you can use the same account any time to create a new Google BigQuery Workload Identity Federation Data DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054). ## Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select. | Menu | Description | | | | | | | | | | | | | | | | | | | | -------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | - | - | - | --- | --- | - | --------------- | --------------- | - | ----- | ------------------------------------------------------------------ | - | ----------------- | ------------------------------------- | - | ---------- | -------------------------------- | - | | Report | Select the Google BigQuery Workload Identity Federation Data report you want to run. The following reports are available: | | | | --- | --- | | **Report Name** | **Description** | | Query | Returns the data from Big Query by running legacy or standard SQL. | | Table Information | Returns the information of the Table. | | Table Data | Returns the data from the Table. | | | What Query Type would you like to use? | Select the query type that you would like to use. By default Legacy SQL is selected. | | | | | | | | | | | | | | | | | | | | Query | Enter a fully qualified Google BigQuery query. | | | | | | | | | | | | | | | | | | | | Query Parameter | Enter the query parameter value, it is the initial value for query parameter. The last run date is optional by default it is '02/01/1700' if is not provided. For example: !\{lastvalue:\_id}!=1,!\{lastrundate:start\_date}!=02/01/1944 | | | | | | | | | | | | | | | | | | | | Project ID | Enter the ID for the project you want to retrieve data. | | | | | | | | | | | | | | | | | | | | Expect Large Results | Queries with large results will create a temporary table and deletes it when the job is completed. A dataset ID is required to create the temporary table. | | | | | | | | | | | | | | | | | | | | Dataset ID | Enter the ID for the dataset you want to retrieve data. | | | | | | | | | | | | | | | | | | | | Projects | Select the project from available list of projects. | | | | | | | | | | | | | | | | | | | | Datasets | Select the dataset from available list of datasets. | | | | | | | | | | | | | | | | | | | | Tables | Select the table from available list of tables. | | | | | | | | | | | | | | | | | | | | Location | Enter the location. The location information can be found "[https://cloud.google.com/bigquery/docs/locations.](https://cloud.google.com/bigquery/docs/locations) | | | | | | | | | | | | | | | | | | | | Selected Fields | Select fields. | | | | | | | | | | | | | | | | | | | | Max Results | Max Results is the number of results returned per page of data. By default, Max Results is a 10,000 results per page. If your dataset throws an out of memory error, decrease Max Results. | | | | | | | | | | | | | | | | | | | | Use Google BigQuery Schema | Select this checkbox to use the schema received from Google BigQuery. This is useful when a column's datatype may be perceived incorrectly to Domo. For example, your table has '123' in a String column. | | | | | | | | | | | | | | | | | | | ## Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). # Snowflake Enterprise OAuth Connector Source: https://www.domo.com/docs/s/article/000005477 ## Intro By combining the power of Domo with your Snowflake data warehouse, you can unlock even more data value and democratize data for your business. The Domo Snowflake Enterprise OAuth connector makes it easy to securely bring your data from your Snowflake data warehouse into Domo. If you are already using Snowflake as a data warehousing solution, this connector helps you use Domo in conjunction to get the most from your data. With the Enterprise OAuth connector for Snowflake, you can use your existing Snowflake account to access your data, including your Client ID and the Client Secret provided by Snowflake when you were registered. Once your Snowflake data is in Domo, you can combine it with all your other Domo data to get a centralized view of your most mission-critical data. You can connect to your Snowflake Enterprise OAuth account in the Data Center. This topic discusses the fields and menus that are specific to the Snowflake Enterprise OAuth connector user interface. To add DataSets, set update schedules, and edit DataSet information, see [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). ## Prerequisites To connect to your Snowflake Enterprise OAuth account and create a DataSet, you must have the following: * Account Name * Role ## Connecting to Your Snowflake Enterprise OAuth Account The Snowflake Enterprise OAuth Connector uses the new Enterprise OAuth Configurations feature to complete the Enterprise OAuth process. To know more about the Enterprise OAuth Configurations process, see [Enterprise OAuth Process](https://domo-support.domo.com/s/article/000005476?language=en_US "Enterprise OAuth Process"). This section enumerates the options in the **Credentials** and **Details** panes in the Snowflake Enterprise OAuth Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in great detail in [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). ## Credentials Pane This pane contains fields for entering credentials to connect to your Snowflake Enterprise OAuth account. The following table describes what is needed for each field:

Field

Description

Account Name

Enter the full name of your account (provided by Snowflake).

Role

Enter your role.

Once you have entered valid Snowflake Enterprise OAuth credentials, you can use the same account any time to create a new Snowflake Enterprise OAuth DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](https://domo-support.domo.com/s/article/360042926054?language=en_US "Managing User Accounts for Connectors"). ## Details Pane

Menu

Description

Query Type Select the query type.
Warehouses Select the warehouse.
Databases Select the database.
Database Schema Select the schema.
Query Enter a custom query.
Database Objects Please choose the database object.
Tables Select the table.
Table Columns Select the table columns that you would like to include in your report.
Table Query Helper This field shows the query that is generated based on the selected fields.
Views Select the view.
View Columns Select the view columns that you would like to include in your report.
Query Helper This field shows the query that is generated based on the selected fields.
Fetch Size Enter a fetch size for memory performance. If this field is blank, by default 1000 will be used. If dataset throws an out of memory error, try decreasing the fetch size.
Convert BIGINT to LONG Select this check box if you want to convert the BIGINT columns to LONG.
## Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). # Snowflake Domo Managed High Bandwidth Connector Source: https://www.domo.com/docs/s/article/000005497 ## Intro Snowflake is a data warehouse built for the cloud for all data and users. Use Domo's Snowflake Unload V2 Connector to unload data from your Snowflake account into Amazon S3. Unloaded files are imported from Amazon S3 into Domo. Choose this connector instead of the Snowflake connector if you are executing very large queries. To learn more about the Snowflake Domo Managed High Bandwidth API, see ([https://docs.snowflake.com/en/api-reference](https://docs.snowflake.com/en/api-reference "https://docs.snowflake.com/en/api-reference") ). You can connect to your Snowflake Domo Managed High Bandwidth account in the Data Center. This topic discusses the fields and menus specific to the Snowflake Domo Managed High Bandwidth connector user interface. To add DataSets, set update schedules, and edit DataSet information, see [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). ## Prerequisites To connect to your Snowflake Domo Managed High Bandwidth account and create a DataSet, you must have the following: * Snowflake Account Name * Username * Password ## Connecting to Your Snowflake Domo Managed High Bandwidth Account This section enumerates the options in the **Credentials** and **Details** pane in the Snowflake Domo Managed High Bandwidth Connector page. The components of other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in great detail in [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). ## Credentials Pane This pane contains fields for entering credentials to connect to your Snowflake Domo Managed High Bandwidth account. The following table describes what is needed for each field:

Field

Description

Snowflake Account Name

Enter the name of your account (provided by Snowflake). For US West Region account\_name , and All other regions account\_name.region\_id .

Username

Enter the username associated with your Snowflake host.

Password

Enter the password associated with your Snowflake host.

Role

Enter your role.

Once you have entered valid Snowflake Domo Managed High Bandwidth credentials, you can use the same account any time to create a new Snowflake Domo Managed High Bandwidth DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](https://domo-support.domo.com/s/article/360042926054?language=en_US "Managing User Accounts for Connectors"). ## Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

How Would You Like to Import Data Into Domo? Select the way you want to import your data.
Query Type
Query Type Description
Custom Query Enter the SQL query to execute.
Query Builder Select table and fields to autogenerate your query.
Warehouses Select the warehouse.
Databases Select the database.
Schemas Select the schema.
Database Objects Choose the database object.
Tables Select the table.
Views Select the view.
Table Column Names Select the table columns to be included in your report.
View Column Names Select the view columns to be included in your report.
Table Query Helper Generates the query based on the selected fields.
View Query Helper A query is generated based on the selected fields.
Query Enter the SQL query to execute.
Partition Criteria Select if you want to partition your data using the date keys, non-date keys, or meta query.
Partition Date Key Table Column Name Select the partition column name.
Partition Date Key View Column Name Select the partition column name. Only date fields appears.
Enter Partition Date Key Column Name Enter the partition column name.
Past Days Enter the number of past days that you want to fetch the data for. Value can be X, where X is a positive integer. For example, 30.
Date Format Select the required date format. The default format is (YYYY-MM-DD) .
Custom Date Format Enter the custom date format.
Partition Non Date Key Table Column Name Select the partition column name.
Partition Non Date Key View Column Name Select a non-date key column name to partition the data. All the fields excluding Date fields appears.
Enter Partition Non Date Key Column Name Enter the partition column name.
Partition Query to determine partition tags Enter the partition query to determine the distinct partition tags. The column containing the Date data is your partition column. For example, select Date from Table\_Name.
Upsert Key Column(s) Enter upsert key column name or a comma separated list of upsert key column names. Required only when Update method is Merge .
## Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update **options,** see [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). # Databricks Using Personal Access Token Authentication V2 Source: https://www.domo.com/docs/s/article/000005522 ## Intro Databricks is a cloud-based collaborative data science, data engineering, and data analytics platform that combines the best of data warehouses and data lakes into a lakehouse architecture. With Databricks you can access all your data, analytics, and AI on a single lakehouse platform. This simple, open, and collaborative environment helps reduce the infrastructure complexity, controls your data, and makes it easy for your teams to partner across the entire data and workflow. You can connect to your Databricks using Personal Access Token Authentication V2 account in the Data Center. This topic discusses the fields and menus that are specific to the Databricks using Personal Access Token Authentication V2 connector user interface. To add DataSets, set update schedules, and edit DataSet information, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Prerequisites To connect to your Databricks using Personal Access Token Authentication V2 account and create a DataSet, you must have the following: * Host * Port * Personal Access Token * HTTP Path ## Connecting to Your Databricks using Personal Access Token Authentication V2 Account This section enumerates the options in the **Credentials** and **Details** panes in the Databricks using Personal Access Token Authentication V2 Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in great detail in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Credentials Pane This pane contains fields for entering credentials to connect to your Databricks using Personal Access Token Authentication V2 account. The following table describes what is needed for each field:

Field

Description

Host

Enter the server host name.

Port

Enter the server host port number.

Personal Access Token

Enter the Personal Access Token.

HTTP Path

Enter the HTTP Path.
Once you have entered valid Databricks using Personal Access Token Authentication V2 credentials, you can use the same account any time to create a new Databricks using Personal Access Token Authentication V2 DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Manage Connector Accounts](https://domo-support.domo.com/s/article/360042926054?language=en_US "Manage Connector Accounts"). ## Details Pane
Menu Description
How would you like to import data into Domo? From the drop-down, select how you want to import your data.
Catalogs Select the catalog.
Database Name Select the database name.
Query Type
Query Type Description
Custom Query Enter the query you want to execute.
Query Builder Select a table and fields to autogenerate your query.
Query Enter your query.
Database Tables From the drop-down list, select the table.
Table Columns Select the columns.
Query Helper The generated query appears. Edit the query if required.
Upsert Key Column(s)

Enter the upsert key column name or a comma separated list of upsert key column names.

Note: This is required only when Import Data method is UPSERT.

Partition Criteria

Select if you want to partition your data using the date keys or meta query.

Partition Query to determine partition tags

Enter the partition meta query to determine the distinct partition tags(or keys). The column containing the Date data is your partition column. For example: SELECT DISTINCT(COLUMN\_NAME) FROM TABLENAME.

Partition Column Name

Select the partition column name. Only date fields will appear.

Partition Support Format

Select the partition format.

Past Days

Enter the number of past days for which you want to get the data. Value can be X, where X is a positive integer. For example: 30.

Past Years

Enter the number of past years for which you want to get the data. Value can be X, where X is a positive integer. For example: 30.

Past Months

Enter the number of past months for which you want to get the data. Value can be X, where X is a positive integer. For example: 30.

Future Years

Enter the number of future years for which you want to get the data. Value can be X, where X is a positive integer. For example: 30.

Future Months

Enter the number of future months for which you want to get the data. Value can be X, where X is a positive integer. For example: 30.

Date Format

Select or enter the correct date format as per the date format in the partition column. By default yyyy-MM-dd is used.

Custom Date Format

Enter the custom date format.

Partition Non Date Key Column Name

Select the partition column name.

Fetch Size

Enter the fetch size for memory performance. The default value will be used if the fetch size is not specified. If an out of memory error occurs, then retry by decreasing the fetch size.

## Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). # Snowflake Enterprise OAuth Connector Source: https://www.domo.com/docs/s/article/000005534 ## Intro By combining the power of Domo with your Snowflake data warehouse, you can unlock more data value and make your data accessible to everyone in your business. The Domo Snowflake OAuth connector makes it easy to bring data from your Snowflake data warehouse into Domo securely. If you are already using Snowflake as a data warehousing solution, this connector helps you use Domo in conjunction to get the most from your data. With the OAuth connector for Snowflake, you can use your existing Snowflake account to access your data, including your Client ID and the Client Secret provided by Snowflake when you were registered. Once your Snowflake data is in Domo, you can combine it with all other Domo data to get a centralized view of the most mission-critical data.. You can connect to your Snowflake Enterprise OAuth account in the Data Center. This topic discusses the fields and menus that are specific to the Snowflake Enterprise OAuth connector user interface. To add DataSets, set update schedules, and edit DataSet information, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Prerequisites To connect to your Snowflake Enterprise OAuth account and create a DataSet, you must have the following: * You need to select the OAuth Configuration * Enter the Account Name provided by Snowflake * You need to enter the Role ## Connecting to Your Snowflake Enterprise OAuth Account This section enumerates the options in the **Credentials** and **Details** panes on the Snowflake Enterprise OAuth Connector page. The components of the other panes on this page, **Scheduling**, and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in great detail in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Credentials Pane This pane contains fields for entering credentials to connect to your Snowflake Enterprise OAuth account. The following table describes what is needed for each field:

Field

Description

OAuth Configuration

OAuth Configurations has the service credentials stored by your administrator that automatically logs you in so that only your personal OAuth login is required. Your administrator may create and edit configurations in the Data Center, in the Accounts tab.

Account Name

Enter the full name of your account (provided by Snowflake).

Role

Enter your role.

Once you have entered valid Snowflake Enterprise OAuth credentials, you can use the same account any time to create a new Snowflake Enterprise OAuth DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Manage Connector Accounts](https://domo-support.domo.com/s/article/360042926054?language=en_US "Manage Connector Accounts"). ## Details Pane

Menu

Description

Query Type Select the query type.
Warehouses Select the warehouse.
Databases Select the database.
Database Schema Select the schema.
Query Enter a custom query.
Database Objects Choose the database object.
Tables Select the table.
Table Columns You can select the table columns that you would like to include in your report.
Table Query Helper This field shows the query generated based on the selected fields.
Views Select the view.
View Columns Select the view columns that you would like to include in your report.
Query Helper This field shows the query that is generated based on the selected fields.
Fetch Size Enter a fetch size for the memory performance. If this field is blank, by default the value 1000 will be used. If the dataset throws an out of memory error, then try to decrease the fetch size.
Convert BIGINT to LONG Select this check box if you want to convert the BIGINT columns to LONG.
## Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## FAQs To enable the connector to use the OAuth configuration, follow the below steps: 1. [Create a security integration in Snowflake](https://docs.snowflake.com/en/user-guide/oauth-custom "Create a security integration in Snowflake"). Use [https://oauth.domo.com/api/data/v1/oauth/providers/snowflake-oauth-config-standard/exchange](https://oauth.domo.com/api/data/v1/oauth/providers/snowflake-oauth-config-standard/exchange) for the OAUTH\_REDIRECT\_URI value, and save the generated client id and secret. 2. Create the OAuth Configuration by doing the following: 1. Navigate to the Integration Accounts section of the Data Center using [https://.domo.com/datacenter/accounts](https://.domo.com/datacenter/accounts). 2. On the top right corner, from the **Add New** drop-down, select **OAuth Configuration**. Add New Drop Down 3. In the modal that appears, provide a name for the configuration. 4. Select **Snowflake OAuth Config** from the **Configuration Type** drop-down and then enter the client id and secret obtained from step 1. 5. Click **Connect** to create the configuration. 3. Share the new OAuth Configuration with the users who need to power up this connector. 1. Navigate to the OAuth Configurations tab in the Integrations Accounts section of the Data Center. 2. Search for the OAuth Configuration created in Step 2. 3. Click the wrench menu on the right side and select **Share Account**. Share Account Now, you can share this configuration by selecting groups or individual users. There are 2 possibilities: * An OAuth configuration does not exist yet. Contact your Domo admin to determine if an OAuth configuration exists. * An OAuth configuration exists but has not been shared with you. Contact your Domo admin to ensure that the OAuth Configuration you need has been shared with you. # Azure Synapse Active Directory Service Principal Connector Source: https://www.domo.com/docs/s/article/000005549 ## Intro Azure Synapse Analytics lets you quickly implement a high-performance, globally available, and secure cloud data warehouse. Use Domo's Azure Synapse Active Directory Service Principal SQL connector (formerly the Azure SQL Data Warehouse connector) to bring your Azure data into Domo. Combine your Azure data with data from other sources throughout your company for a comprehensive view of your business. Set up custom alerts to be notified in real-time when your key metrics change, so that you can make faster, better business decisions. You can connect to your Azure Synapse Active Directory Service Principal account in the Data Center. This topic discusses the fields and menus specific to the Azure Synapse Active Directory Service Principal connector user interface. To add DataSets, set update schedules, and edit DataSet information, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Prerequisites To connect to your Azure Synapse Active Directory Service Principal account and create a DataSet, you need the following: * Server Name * Port * Database * Azure App Service Principal Client Id * Azure App Service Principal Client Secret * Host Name In Certificate ## Connecting to Your Azure Synapse Active Directory Service Principal Account This section enumerates the options in the **Credentials** and **Details** panes on the Azure Synapse Active Directory Service Principal Connector page. The components of the other panes on this page, **Scheduling**, and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in great detail in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Credentials Pane This pane contains fields for entering credentials to connect to your Azure Synapse Active Directory Service Principal account. The following table describes what is needed for each field:

Field

Description

Server Name

To know your server name:

  1. Navigate to the Azure Portal.
  2. Click Azure Synapse Analytics.
  3. Click the Synapse SQL Pool you want to connect.
  4. Locate the full server name. For example, yourserver.database.windows.net
Port Enter the port number from where the server is listening.
Database Enter the name of the database that you want to connect to.
Azure App Service Principal Client Id Enter your Active Directory Service Principal client id.
Azure App Service Principal Client Secret``Enter your Active Directory Service Principal client secret.
Host Name In Certificate Enter the host name to be used to validate the SQL Server TLS/SSL certificate.
Once you have entered valid Azure Synapse Active Directory Service Principal credentials, you can use the same account at any time to create a new Azure Synapse Active Directory Service Principal DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Manage Connector Accounts](https://domo-support.domo.com/s/article/360042926054?language=en_US "Manage Connector Accounts"). ## Details Pane
Menu Description
Query Type
Query Type Description
Custom Query Enter the query to execute.
Query Builder Select a table and fields to autogenerate your query.
Query Enter the SQL query to execute.
Database Tables Select the table.
Table Columns Select the columns.
Query Helper This field is automatically generated using the above selected fields. Updating the auto generated query will not update your selections in the above Field table.
Query Time Out The number of seconds to wait before a timeout has occurred on a query. The default value is -1, which indicates infinite timeout. Setting this value to 0 also implies to wait indefinitley.
MaxResultBuffer

maxResultBuffer can be used to set the maximum bytes to read when reading a result set. If this is not specified, then the entire result set is read. Size can be specified in two styles:

  1. As size of bytes (for example, 100, 150M, 300K, 400G).
    1. As a percent of maximum heap memory (for example, 10p, 15pct, 20percent).
## Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). # Azure Data Lake Gen2 OAuth Writeback Connector Source: https://www.domo.com/docs/s/article/000005603 ## Intro Azure Data Lake Storage is Microsoft's optimized storage solution for big data analytics workloads. A fundamental part of Data Lake Storage Gen2 is the addition of a hierarchical namespace to Blob storage. Use this connector to bring in data from Azure storage into Domo for creating visual insights on the data. Azure Data Lake Storage Gen2 is the world's most productive Data Lake. It makes Azure Storage the foundation for building enterprise data lakes on Azure. It allows you to manage massive amounts of data easily and helps to speed up your transition from proof of concept to production. You can connect to your Azure Data Lake Gen2 OAuth Writeback account in the Data Center. This topic discusses the fields and menus that are specific to the Azure Data Lake Gen2 OAuth Writeback connector user interface. To add DataSets, set update schedules, and edit DataSet information, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Prerequisites To connect to your Azure Data Lake Gen2 OAuth Writeback account and create a DataSet, you need the following: * Client ID * Client Secret * Tenant ID ## Configuring Your Azure App To create a connection with your Microsoft Exchange Metrics account, you must first create a Microsoft Azure Web App to obtain the necessary client ID and secret. **To configure an Azure App**: 1. Login into [Azure Portal](https://portal.azure.com/#home "https://portal.azure.com/#home"). 2. Select **Azure Active Directory > App Registrations > New Registration**. New_registration.png 3. Fill out the registration form as follows: * * Name: Enter the name of your application. * Supported account types: Select an option to specify who can use this application or access this API. * Redirect URI: Enter the redirect URI ([https://oauth.domo.com/api/data/v2/oauth/providers/adls-gen2-azure-active-directory-oauth-writeback/exchange](https://oauth.domo.com/api/data/v2/oauth/providers/adls-gen2-azure-active-directory-oauth-writeback/exchange "https://oauth.domo.com/api/data/v2/oauth/providers/adls-gen2-azure-active-directory-oauth-writeback/exchange") ). The authentication response is sent to this URI after successfully authenticating the user. Providing the URI at this stage is optional and it can be changed later, but a value is required for most of the authentication scenarios. clipboard_eac88f9aa2966a791f11417756903afc4.png 4. Click **Register**. An overview of your registered App will appear. The **Application ID** that appears here is the **Client ID** you will enter in the **Credentials** pane in Domo. 5. Click **API Permissions >> +Add a permission**. 6. **Request API permissions** section appears. Add the API permissions for your application. clipboard_e9ed1fc0137b700a6e1c7bb384b55b721.png 7. Now, click on **Certificates and secrets**. Certificates can be used as secrets to prove the application's identity when requesting a token. Also, can be referred to as public keys. 8. Click **+New client secret**. clipboard_ea0abe516411f9db35904232995bd00d9.png 9. Specify the client secret description and the expiry period for your client secret, and click **Add**. 10. Copy the value and paste it into the **Client Secret** field in the **Connector credentials** section in Domo. ## Connecting to Your Azure Data Lake Gen2 OAuth Writeback Account Azure Data Lake Storage Gen2 supports OAuth 2.0 authentication. This section enumerates the options in the **Credentials** and **Details** panes on the Azure Data Lake Gen2 OAuth Writeback Connector page. The components of the other panes on this page, **Scheduling**, and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in great detail in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Credentials Pane This pane contains fields for entering credentials to connect to your Azure Data Lake Gen2 OAuth Writeback account. The following table describes what is needed for each field:

Field

Description

Client ID Enter the client ID (GUID) of the client web app obtained from the Azure Active Directory configuration.
Client Secret Enter the secret key of the client web app.
Tenant ID

Enter your Tenant ID. Navigate to Portal.azure.com \> Azure Active Directory > Properties.

The Directory ID is your Tenant ID.

Once you have entered valid Azure Data Lake Gen2 OAuth Writeback credentials, you can use the same account at any time to create a new Azure Data Lake Gen2 OAuth Writeback DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Manage Connector/Adapter Accounts](https://domo-support.domo.com/s/article/360042926054?language=en_US "Manage Connector/Adapter Accounts"). ## Details Pane

Menu

Description

Enter Storage Account Name Enter the storage account name.
Enter Container Name Enter the Container name.
How would you like to choose the directory name? Select how would you like to choose the directory name.
Discover Directory Name Select the directory name.
Enter Directory Name

Enter the directory name.

test Example for main or root directory
test/test Example for sub directory
test/test/test Example for sub-sub-directory
Input DataSet Id

Enter your Domo DataSet ID ( GUID ) located in the DataSet URL.

Example: [https://customer.domo.com/datasources/aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee/details/settings\{](https://customer.domo.com/datasources/aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee/details/settings\{)" "}

Select filename

Specify whether you want to use the input DataSet GUID or enter a filename manually.

FileName

Enter the output file name.

My Domo Input DataSet is very large

Select this Check box if you are exporting a very large DataSet from Domo to Azure Data Lake. When this box is checked, the connecter uses a different, faster process.

## Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). # Azure Synapse Partition Connector Source: https://www.domo.com/docs/s/article/000005619 ## Intro Azure Synapse Analytics lets you quickly implement a high-performance, globally available, and secure cloud data warehouse. Use Domo's Azure Synapse Partition SQL connector to bring your Azure data into Domo. Combine your Azure data with data from other data sources throughout your company for a comprehensive view of your business. You can set up custom alerts to be notified in real-time when your key metrics change, so you can make faster, better business decisions. You can connect to your Azure Synapse Partition account in the Data Center. This topic discusses the fields and menus that are specific to the Azure Synapse Partition connector user interface. To add DataSets, set update schedules, and edit DataSet information, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Prerequisites To connect to your Azure Synapse Partition account and create a DataSet, you need the following: * You need to select the JDBC Driver Version * Server Name * Database Name * Port number * Username and password * Host Name In Certificate ## Connecting to Your Azure Synapse Partition Account This section enumerates the options in the **Credentials** and **Details** panes on the Azure Synapse Partition Connector page. The components of the other panes on this page, **Scheduling**, and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in great detail in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Credentials Pane This pane contains fields for entering credentials to connect to your Azure Synapse Partition account. The following table describes what is needed for each field:

Field

Description

JDBC Driver Version Select the JDBC driver version.
Server Name

Go to the Azure Portal. Click Azure Synapse Analytics. Click the Synapse SQL Pool you want to connect. Locate the full server name. For example yourserver.database.windows.net

Database Name Enter the database name.
Port Enter the port number.
Username Enter the username.
Password Enter the password.
HostNameInCertificate Enter the hostNameInCertificate obtained from the show database connection strings.
Once you have entered valid Azure Synapse Partition credentials, you can use the same account at any time to create a new Azure Synapse Partition DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Manage Connector Accounts](https://domo-support.domo.com/s/article/360042926054?language=en_US "Manage Connector Accounts"). ## Details Pane

Menu

Description

Partition Criteria Select the Partition Criteria.
Schema Name Select the schema name.
Table Name Select the database table.
Partition Date Key Column Name Select the date key partition column name.
Partition Non Date Key Column Name Select the non date key partition column name.
Partition Meta Query to determine partition tags Enter the partition meta query to determine the distinct partition tags(or keys). Example SELECT DISTINCT(DATE\_COLUMN\_NAME) FROM TABLENAME. In this example DATE\_COLUMN\_NAME is the partition column and distinct values from the table are the keys.
Partition Support Format Select the partition format.
Past Years Enter the number of past years that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Future Years Enter the number of future years that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Past Months Enter the number of past months that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Future Months Enter the number of future months that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Past Days Enter the number of past days that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Custom Date Format Enter the custom date format.
Query Enter the query to execute.
Note: Subqueries are used for partitioning. Read the rules and construct the query accordingly.
Rules: [https://learn.microsoft.com/en-us/sql/relational-databases/performance/subqueries?view=sql-server-ver16#rules](https://learn.microsoft.com/en-us/sql/relational-databases/performance/subqueries?view=sql-server-ver16#rules)
Cast To Date Select this checkbox if you want to cast the partition column to DATE type.
Limit Buffer Size Select this checkbox if you want to Limit the maximum heap memory used by ResultBuffer.
## Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). # Freemium Overview Source: https://www.domo.com/docs/s/article/000005699 ## Intro Freemium is a free-forever enterprise version of Domo that renews monthly with a credit limit. There are no new sign-ups for Freemium; all new sign-ups are enabled by the Domo Free Trial experience. Domo Free Trial is a 30-day enterprise version of Domo with no credit limit. Learn more about [Domo Free Trial](/docs/s/article/000005676). By default, Freemium is a consumption model and includes 300 credits per month. If you need more credits, you can purchase them through a [monthly subscription](#monthly-subscription) via Stripe. You can [cancel a subscription](https://domo.lightning.force.com/lightning/r/Knowledge__kav/ka0Vq0000004iQfIAI/view#freemium_cancel_a_subscription) and return to the free version and 300 default monthly credits at any time.\ [Credit monitoring](/docs/s/article/000005326) allows you to track your usage from month to month. **Tip:** Learn more about consumption and using credits by reviewing the [Consumption Supplemental Terms](https://www.domo.com/consumption-terms) and reading this article: [What Are Consumption Credits and How Do They Work?](https://domo-support.domo.com/s/article/000005280) *** ## Required Grants Grants are authorizations inside Domo that allow individual users to perform and manage tasks and operations. You can add grants to custom roles. Many Domo features require users to have certain grants to access them. By default, the user who signed up for the Domo Free Trial has the following grants. You can create one or more custom roles for other users as needed and include one or both grants for any role. * **Credits.report.view —** This grant allows a user to view the [credit usage bar](#usage-bar) at the top of the screen throughout the instance. * **Payments.stripe.management —** This grant allows a user to buy more credits and manage billing details in Stripe and should be given to any users who need to perform these tasks. Learn more about [system](/docs/s/article/360043438953) and [custom roles](/docs/s/article/360043438973). ## Usage Bar In Freemium, users with the appropriate permission can see the usage bar at the top of the screen on the landing page. See [Required Grants](#required-grants) to learn more about enabling the usage bar for individual users. usage bar.jpg The usage bar is collapsed on any other page of the platform. You can expand it with the chevron handle and collapse it by selecting **Dismiss**. usage bar collapsed.jpeg dismiss bar.jpeg Depending on your [permissions](#required-grants), the usage bar includes the following items: * A counter that displays the amount of credits used versus the amount of available credits * help freemium.jpg **Help —** Selecting this option redirects you to a list of help documentation, including this article. * **Buy more credits —** Selecting this option opens the [**Purchase Credits** modal](#monthly-subscription). * **Manage billing —** This option is only visible if you have an active subscription and the appropriate [grant](#required-grants). Select **Manage billing** to view and manage your account and subscription settings in Stripe. * **See usage history —** Selecting this option redirects you to the **Credit Utilization** page in the Company Settings. See [Usage History](#usage-history) for more information. **Upgrade Credit Limit Alert:** When you approach your credit limit, a modal displays, allowing you to buy more credits. You can select **Upgrade now** to open the Purchase Credits modal or select **Dismiss** to close the modal. The modal only displays once per credit cycle. upgrade modal.jpg ## Usage History Selecting **See usage history** in the [usage bar](#usage-bar) redirects you to the **Credit Utilization** page of the Company Admin Settings. Learn more about [Credit Utilization](/docs/s/article/000005326). Screenshot 2024-02-09 at 2.24.49 PM.png ### Used Credits The **Used Credits** tab summarizes the credits you've used by credit type. You can filter the stacked bar chart by credit type and the '12 month ending' period. Screenshot 2024-11-08 at 8.57.49 AM.png ### Subscription The **Subscription** tab displays your contract information by contract period. Each period can be expanded by selecting the collapsed row to show the credit information for that specific period. Screenshot 2024-11-08 at 9.06.05 AM.png ### Credit Balance The **Credit Balance** tab displays your Current Estimated Balance and estimated balance history. Screenshot 2024-11-08 at 9.22.23 AM.png The Current Estimated Balance shows your current credit period's starting, ending, and total usage balances. I Screenshot 2024-11-08 at 9.30.27 AM.png The estimated balance history shows the balance history for each credit period. You can expand each **Statement ID**to see more information about credit usage during that period. Screenshot 2024-11-08 at 9.31.50 AM.png ## Monthly Subscription You can subscribe to a monthly credits package if you need more than the default monthly credits. Select **Buy more credits** in the usage bar to view the package options and subscribe.\ The **Purchase credits** modal displays. buy more credits usage bar.jpg Choose from the following package options: * **+100 Credits —** This package adds 100 credits to the default 300 credits for a total of 400 monthly credits. * **+200 Credits —** This package adds 200 credits to the default 300 credits for a total of 500 monthly credits. * **+300 Credits —** This package adds 300 credits to the default 300 credits for a total of 600 monthly credits. * **+400 Credits —** This package adds 400 credits to the default 300 credits for a total of 700 monthly credits. Each package includes Tier 1 Support, 1 Free value consultation, and the option to cancel anytime. Screen Shot 2024-05-22 at 17.06.33.png When you choose a package and select **Subscribe** **Now**, you are redirected to the Stripe checkout and prompted to add your credit card details to purchase the selected subscription. **Credits on Subscription:** Credit amounts reset at the end of each calendar month. If you purchase a subscription in the middle of a calendar month, the price is prorated (via Stripe) for your initial month; at the beginning of the following month, you are charged for the full month. If you exceed your credit limit before the month ends, the usage bar changes from blue to orange. You can select **Buy more credits** to purchase additional credits. **Cancel a Subscription:** Those with the appropriate [grant](#required-grants) can cancel a subscription at any time. Select **Manage billing** in the [usage bar](#usage-bar) to be redirected to Stripe to cancel. If you cancel a subscription, your account reverts to the default number of monthly credits after the last day of the last paid month. You can then choose to continue using Freemium with the 300 default monthly credits or select **Buy more credits** in the usage bar to choose a subscription package. ## Manage Billing If you have the appropriate [grant](#required-grants), you can select **Manage billing** in the [usage bar](#usage-bar) to be directed to Stripe, where you can view and manage your subscription. manage domo sub.jpg # Domo on Amazon Athena Source: https://www.domo.com/docs/s/article/000005744 ## Intro Athena users can connect their data to Domo through Cloud Integrations native integrations. Integrating Athena into Domo is as simple as providing connection parameters and selecting the tables you want to see as Domo DataSets. *** ## Prerequisites Before you set up an Athena integration, you must have an IAM role (ARN) with access to the information that you need to connect to Domo. ## Create an Athena Integration Follow the steps below to create a read-only Athena integration: 1. In Domo, go to the data warehouse .jpg **Data Warehouse**and select add.jpg **Add New Cloud Account**. 2. In the **Amplify existing cloud warehouses** modal, under **Native integration**, choose **See More**. see more athena.jpg 3. Choose the **Athena** tile. 4. Select **+** **Add New Integration**. If there are existing integrations, this option displays at the bottom of the list. 5. Enter the information listed in the table below and select **Next**. | Parameter | Description | | ---------------------- | --------------------------------------------------------------------------------------------------------- | | Integration name | This is how you can find your integration in the Athena integrations list for future updates. | | (Optional) Description | Any additional information about the integration. | | Athena connection URL | The Athena JDBC connection URL. | | IAM Role (ARN) | The Identity and Access Management (IAM) role that you've previously configured for your Athena instance. | 6. Configure the caching options and select **Next**. Learn about [caching rules](/docs/s/article/4412849158167) with Cloud Integrations.\ A success message displays. Screenshot 2024-12-17 at 11.02.22 AM.png 7. Select **Choose Data Tables to Connect**. 8. Use the table picker to choose the Athena schemas and tables to connect to Domo. athena table picker.jpg 9. Select **Create DataSets** to open the sharing modal. Here you have the option to share the data with individuals and groups and choose their access level. Your Athena DataSets now display in the Domo **DataSets** feature. athena datasets.jpg # Snowflake Key Pair High Bandwidth Advanced Partitions Connector Source: https://www.domo.com/docs/s/article/000005832 ## Intro Snowflake enables organizations to collaborate, build AI-powered data apps, and unlock data insights—all within a secure and scalable AI Data Cloud. Leverage Snowflake's unload technology into internal staging, and Domo's advanced update methods such as partitioning on all column types, to quickly and reliably ingest your data into Domo. You can connect to your Snowflake Key Pair High Bandwidth Advanced Partitions account in the Data Center. This topic discusses the fields and menus that are specific to the Snowflake Key Pair High Bandwidth Advanced Partitions connector user interface. To add DataSets, set update schedules, and edit DataSet information, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Prerequisites To connect to your Snowflake Key Pair High Bandwidth Advanced Partitions account and create a DataSet, you need the following: * Account name (provided by Snowflake) * Username associated with your Snowflake host. * Private Key ## Connecting to Your Snowflake Key Pair High Bandwidth Advanced Partitions Account This section enumerates the options in the **Credentials** and **Details** panes on the Snowflake Key Pair High Bandwidth Advanced Partitions Connector page. The components of the other panes on this page, **Scheduling**, and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in great detail in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Credentials Pane This pane contains fields for entering credentials to connect to your Snowflake Key Pair High Bandwidth Advanced Partitions account. The following table describes what is needed for each field:

Field

Description

Account Name Enter the name of your account (provided by Snowflake). For US West Region account\_name , and All other regions account\_name.region\_id .
Username Enter the username associated with your Snowflake host.
Private Key Enter the Private Key.
PassPhrase If you create an encrypted private key, then OpenSSL prompts for a passphrase which is used to encrypt the private key file. Enter that PassPhrase here.
Role Enter your role.
Once you have entered valid Snowflake Key Pair High Bandwidth Advanced Partitions credentials, you can use the same account at any time to create a new Snowflake Key Pair High Bandwidth Advanced Partitions DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Manage Connector Accounts](https://domo-support.domo.com/s/article/360042926054?language=en_US "Manage Connector Accounts"). ## Details Pane

Menu

Description

Query Type
QueryType Description
Custom Query Enter the SQL query to execute.
Query Builder Select a table and fields to autogenerate your query.
Warehouses Select the warehouse.
Databases Select the database.
Schemas Select the schema.
Database Objects Please choose the database object.
Tables Select the table.
Table Columns Select the table columns that you would like to include in your report.
Table Query Helper Generated query based on the selected fields.
Views Select the view.
View Columns Select the view columns that you would like to include in your report.
View Query Helper Generated query based on the selected fields.
Query Enter the SQL query to execute.
Partition Criteria Select the Partition Criteria.
Partition Query to determine partition tags Enter the partition meta query to determine the distinct partition tags(or keys). The column containing the Date data is your partition column. Example: SELECT DISTINCT(DATE\_COLUMN\_NAME) FROM TABLENAME
Partition Support Format Select the partition format.
Partition Column Name Select the partition column name.
Past Years Enter the number of past years that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Future Years Enter the number of future years that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Past Months Enter the number of past months that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Future Months Enter the number of future months that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Past Days Enter the number of past days that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Date Format Select the required date format. By default yyyy-MM-dd will be used.
Custom Date Format Enter the custom date format.
Partition Non Date Key Column Name Select the partition column name.
Partition Column Name Enter the partition column name.
## Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). # Snowflake OAuth Unload V2 Connector Source: https://www.domo.com/docs/s/article/000005841 ## Intro Snowflake is a data warehouse built for the cloud that stores all your data and users. Use Domo's Snowflake Unload V2 Connector to unload data from your Snowflake into Amazon S3. Unloaded files are imported from Amazon S3 into Domo. Choose this connector instead of the Snowflake connector if you are executing very large queries. The Snowflake connector is a "Database" connector, meaning it retrieves data from a database using a query. In the Data Center, you can access the connector page for this and other Database connectors by clicking **Database** in the toolbar at the top of the window. This topic discusses the fields and menus that are specific to the Snowflake OAuth Internal Unload V2 connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Connector"). ## Prerequisites To connect to your Snowflake database account and create a DataSet, you must have the following: * Client ID * Client Secret * Full name of your account (provided by Snowflake) * Snowflake Host name * AWS S3 Access Key * AWS S3 Secret Key * Name of the AWS S3 Bucket * Amazon S3 Region ## Connecting to Your Snowflake Account This section enumerates the options in the **Credentials** and **Details** panes in the Snowflake OAuth Internal Unload V2 Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Snowflake account. The following table describes what is needed for each field:

Field

Description

Client ID Enter your Client ID (provided by Snowflake when the client is registered).
Client Secret Enter your Client secret (provided by Snowflake when the client is registered).
Account Name Enter the full name of your account (provided by Snowflake).
Host Enter the snowflake host name.
Role Enter your Snowflake role.
S3 Access Key Enter your AWS access key. It is available in the AWS Console in the Security Credentials section or under Users if you are using IAM.
S3 Secret Key Enter your AWS secret access key. It is available when you create your Access Key. You can generate a new one in the AWS Console.
S3 Bucket Name The name of the AWS S3 Bucket.
S3 Region Select the Amazon S3 Region.
Once you have entered valid Snowflake credentials, you can use the same account any time you go to create a new Snowflake OAuth Internal Unload V2 DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

How would you like to import data into Domo? Select how you want to import your data.
Query Type
QueryType Description
Custom Query Enter the SQL query to execute.
Query Builder Select a table and fields to autogenerate your query.
Warehouses Select the warehouse.
Databases Select the database.
Schemas Select the schema.
Database Objects Choose the database object.
Tables Select the table.
Views Select the view.
Table Column Names Select which table columns you would like included in your report.
View Column Names Select the view columns that you would like to include in your report.
Table Query Helper Generated query based on the selected fields.
View Query Helper A query is generated based on the selected fields.
Query Enter the SQL query to execute.
Partition Criteria Select whether you want to partition your data using the date keys, non-date keys, or meta query.
Select Partition Date Key Column Name Select the partition column name.
Partition Column Name Select the partition column name. Only date fields will be shown in this discovery.
Enter Partition Date Key Column Name Enter the partition column name.
Past Days Enter the number of past days that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Date Format Select the required date format. By default, yyyy-MM-dd will be used.
Custom Date Format Enter the custom date format.
Select Partition Non Date Key Column Name Select the partition column name.
Partition Non Date Key Column Name Select a non-date key column name to partition the data. All the fields excluding Date fields will be shown in this discovery.
Enter Partition Non Date Key Column Name Enter the partition column name.
Partition Query to determine partition tags Enter the partition query to determine the distinct partition tags. The column containing the Date data is your partition column. Example: Select the Date from Table\_Name.
Upsert Key Column(s) Enter the upsert key column name or a comma-separated list of upsert key column names. Required only when Update method is Merge.
### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). # Introduction to Domo: A Comprehensive Overview Source: https://www.domo.com/docs/s/article/000005874 ## Introduction to Domo: A Comprehensive Overview Welcome to the exciting world of Domo! This article is designed to introduce you to Domo, a data experience platform, and to explain what makes it an exceptional choice for data management and analysis. **What is Domo?** Domo is much more than just a data visualization platform; it's a complete ecosystem for data management and analysis. Imagine a place where you can gather data, clean it up, analyze it, and present the data in a way that encourages interaction and drives decision-making based on the data. That's Domo. **Key Features of Domo** ### In the Cloud * **Ease of Access**: One of Domo's standout features is its browser-based accessibility. You don't need to download any software; simply log in from any browser on any computer. This means you can access Domo in the office, at home, or even on a walk with your dog. ### Extensive Connectors * **Rich Data Integration**: With over 1,000 connectors, Domo stands out in its ability to integrate a wide range of data sources. Whether marketing data from Facebook and Google or business data from platforms like Snowflake or BigQuery, Domo brings it all together seamlessly. ### ETL Capabilities * **User-Friendly Data Manipulation**: Domo's ETL (Extract, Transform, Load) capabilities make data processing accessible to everyone. It offers intuitive tools like drag-and-drop interfaces, eliminating the need for advanced coding skills. This user-friendly approach allows you to focus on analysis and insights rather than getting bogged down in technical details. **Powerful Dashboards** * **Engaging Data Visualization**: Domo's dashboards are not just functional; they're also visually appealing. They enable you to present data in an engaging manner, fostering a data-driven culture within your organization. ## Why Choose Domo? Domo is more than just a business intelligence tool; it's a comprehensive platform that simplifies complex data tasks and allows any user to ask questions and get answers in real time. Its accessibility, extensive connectors, user-friendly ETL tools, and powerful dashboards make Domo an ideal choice for businesses looking to leverage their data effectively. ## Where to Go Next Whether you're connecting data or building for end users, choose the path that fits your role: * [Getting Started for Data Engineers](/docs/s/article/Getting-Started-for-Data-Engineers) * [Getting Started for Data Consumers](/docs/s/article/Getting-Started-for-Data-Consumers) # Sign in to Domo Source: https://www.domo.com/docs/s/article/000005875 ## Intro Before you can sign in to Domo for the first time, you must be invited by an admin or other Domo user. (This depends on your organization's SSO configuration.) This article describes how to join Domo from an email invitation and how to sign in after joining. *** ## Join Domo from an Email Follow these steps to join Domo from an email invitation. The subject of the email is "Congrats, you just got Domo'd!". 1. In the email, select **Get Started** to open Domo in your web browser. 2. In the dialog that displays, create your password according to the password requirements for your Domo instance. 3. Select **Create Your Account**. You are signed in to Domo. Your email address is the one where you received the invitation. Welcome to Domo! ## Sign in to Domo After joining Domo, you can sign in to Domo using your configured credentials. By signing in, you agree to the [terms of service](https://www.domo.com/company/service-terms) . **Note:** Need to change your password? [Learn how](https://domo-support.domo.com/s/article/360043427513?language=en_US). To sign in to Domo, go to https\:// *yourdomain*.domo. com.
If you don't remember your domain name, refer to your invitation email or contact an admin. # First 5 Things to Do in Domo Source: https://www.domo.com/docs/s/article/000005878 ## Intro As you begin your journey with Domo, there are a few key steps to ensure a smooth start. This guide will walk you through these initial actions, which include uploading your logo, setting your time zone, inviting users, and more. Let's dive in! *** ## Access Company Settings Most of these tasks can be completed in the company settings. Follow these steps to access them: 1. Open the **Features** menu in the left navigation and go to the **Admin** tab. Screenshot 2. Under **Company settings**, select **Company** **overview**. ## Upload Your Company Logo Your company logo is a critical part of your Domo instance. It not only personalizes your experience but also assures users they are in the right place. Follow these steps: 1. [Access](#access-company-settings) the company settings, described above. 2. Select **Manage Logo** to choose a company logo. Screenshot 3. Save your changes using the **Save** option on the **Company overview** page. Screenshot You can also enter your company's name and choose a default language on this screen. ## Set Your Time Zone Correctly setting your time zone is crucial for scheduling and data triggers. **Note:** Setting your timezone only changes items in the Domo platform. It does not change any raw data coming into Domo. Follow these steps: 1. [Access](#access-company-settings) the company settings, described above. 2. Under **Formatting**, choose your time zone. Screenshot ## Configure Week Dates Week dates influence how your charts and analyses display data by week. Follow these steps: 1. [Access](#access-company-settings) the company settings, described above. 2. Scroll to the bottom of the page and use the **Week display** dropdown to choose your preference. 1. **Week dates —** 1/15/2001 2. **Week numbers —** (Week 1, Week 2, and so on) Screenshot ## Add Security with Domain Restrictions **Optional Domain Security:** For added security, you can restrict user access to your Domo instance based on email domains. That way, only users who have a verified email address from a specific domain can be added to your Domo instance. Follow these steps to configure domain restrictions: 1. Open the **Features** menu in the left navigation and go to the **Admin** tab. Screenshot 2. Under **Network security**, select **Invite authorized domains**. 3. Enter the approved domains. Only email addresses from these domains can join your Domo instance. Screenshot ## Invite Users and Assign Roles Inviting colleagues to your Domo instance and assigning appropriate roles is a fundamental step for success. Follow these steps: 1. Open the **Features** menu in the left navigation and go to the **Admin** tab. Screenshot 2. Under **Governance**, select **People**. 3. Select **Add New Person** and add their name and email address. 4. Choose an appropriate role for them. Editor is generally a good starting point for new users. To learn more about the available roles, see the [System Roles | Reference](/docs/s/article/360043438953). * Screenshot The person you added now displays in the list. Screenshot # Build Your First Dashboard | Tutorial Source: https://www.domo.com/docs/s/article/000005879 ## Intro In this tutorial, we'll show you how to use Domo to build a dashboard from start to finish. We'll walk you through connecting data, cleaning it through a simple ETL (Extract, Transform, Load) process, building a dashboard with four to five dynamic cards, setting a Card Alert, and pushing that alert to your email or phone in real time and sharing it with colleagues. This guide serves as a foundation for your journey with Domo, setting the stage for more advanced functionalities and applications. As we move through the tutorial, you'll gain hands-on experience with Domo's powerful features. We'll provide step-by-step instructions, practical examples, and useful tips to make your learning process smooth and enjoyable. *** ## Prerequisites Before beginning the tutorial, make sure you have the following: * Access to these sample Google Sheets: * [Sales Data](https://docs.google.com/spreadsheets/d/1K8YJxidZkCnc8DjCHLUnKWqm_Gywqoeh6DbamkLJy9w/edit?gid=99140820#gid=99140820) * [Marketing Data](https://docs.google.com/spreadsheets/d/1AmnIH1-EbPl0rguDGDLkiVJp1uFsJYzDkh8Ud-OerXw/edit?gid=0#gid=0) **Identify the spreadsheet IDs:** Notice the spreadsheet IDs in these URLs. These IDs uniquely identify your Google Sheets are one way you can set up the connection in Domo. * For the Sales data, the ID is 1K8YJxidZkCnc8DjCHLUnKWqm\_Gywqoeh6DbamkLJy9w * For the Marketing data, the ID is 1AmnIH1-EbPl0rguDGDLkiVJp1uFsJYzDkh8Ud-OerXw * To stay connected and access your data away from a computer, download the [Domo Mobile](https://www.domo.com/business-intelligence/features/mobile) app: * **For Android users —** Visit the Google Play Store and search for 'Domo'. * **For iOS users —** Go to the Apple App Store and look up 'Domo'.Download and install the app on your device. After installing, log in to the app with your Domo credentials. If your organization uses Single Sign-On (SSO), you may need to follow a different login procedure. **Note:** The mobile app's default screen is the Home dashboard, which displays key pages and metrics. Follow these links to learn more about the Domo mobile app: * [Customize Domo mobile app](/docs/s/article/000005648) * [Mobile Enterprise Security](/docs/s/article/1500007028582) * [Domo Mobile best practices](/docs/s/article/360042923554) * [Edit a dashboard's mobile layout](/docs/s/article/1500010172542) * Import Zips to Fips data **Optional step to join data later:** The Zips to Fips DataSet is a valuable asset from Domo's connector library. It helps in joining ZIP code data to FIPS codes, which can be used to group zip codes at a larger county level. Follow these steps to access this data: 1. In your Domo instance, use the left navigation to go to **Features** > **Data Warehouse**. 2. At the top of the screen, select **Connect Data** > **Connectors**. 3. Search for "dimensions" and choose the **Domo Dimensions Connector** to open the configuration modal. 4. Use the **Files** dropdown to find and select the "zips\_to\_fips\_latest" DataSet. 5. Select **Next** in the top right of the modal and name your DataSet "Zips to Fips." 6. Select **Save and Run** to begin importing the data. ## Connect to Sample Google Sheets Data Domo's connectors can efficiently bring your data into Domo when manual uploads and web forms seem too labor-intensive. This guide describes how to seamlessly integrate the [sample data](#prerequisites) above into Domo for use during this tutorial. **Why use connectors?** Connectors provide an automated "set it and forget it" method for data integration, contrasting the manual effort needed with other data connection methods. Follow these steps to use the Google Sheets Connector with the [sample data](#prerequisites) provided above: **Access the Google Sheets Connector** 1. In your Domo instance, use the left navigation to go to **Features** > **DataSets**. 2. At the top of the screen, select **Connect Data** > **Connectors**. 3. Search for the "Google Sheets" connector and select **Use Recommended**. Screenshot **Important:** It's important to understand that Domo offers different connectors for different needs. For instance, there are separate Facebook connectors for organic and paid traffic. Similarly, Domo provides various connectors to Google Sheets, depending on the data integration requirements. **Connect with the Google Sheets Connector** 4. Use the **Connect** option to choose a Google account. If you need to authenticate your Google account, a pop-up window guides you through the process. 5. In the top right corner of the connector modal, select **Next**. Screenshot 6. In the **Spreadsheet URL** field, enter the spreadsheet IDs from the [prerequisites](#prerequisites) section above and select **Next**.\ In the next steps, the example uses the Sales Data file and spreadsheet ID. Repeat these steps for the Marketing Data, so we can use both DataSets later in this tutorial. Screenshot **Schedule Updates** After connecting to your data, decide how frequently you want to update it. Remember, data pulls consume credits, so choose a frequency that balances need and resource consumption. The **Advanced** tab allows you choose to pull the data more than once a day or on specific days of the week or month. 7. Use the **Basic** and **Advanced** tabs to set a schedule for data updates. Some options may be unavailable with your current permissions. You can ask your admin to allow the data to update more frequently. When ready, select **Next**. Screenshot **Finalize Your Connection** 7. Give your DataSet a name and optional description so you can easily identify it later. Select **Save and Run**. Screenshot 8. Repeat these steps for the Marketing Data with the spreadsheet ID listed [above](#prerequisites). You've successfully used the Google Sheets connector to add two DataSets to Domo! ## Build a Sample ETL This guide provides step-by-step instructions for building an ETL (Extract, Transform, Load) process that connects sales data to zip codes and FIPS codes. This enriches the sales data with geographical details like city, state, and county, which are critical for location-based analytics. **Note:** It's not always necessary to join data sources and clean them in Domo, but this tutorial is good practice for how to join different systems. ### Prerequisites Make sure you have the following: * Access to Domo with necessary permissions. * The Sales Data and ZIP-to-FIPS DataSets in Domo. If you haven't imported them, see the [prerequisites](#prerequisites) and [Connect to Sample Google Sheets Data](#connect-to-sample-google-sheets-data) sections above. When you're ready, follow the steps below: **Examine the Data** 1. Log into Domo and use the left navigation to go to **Features** > **DataSets**. 2. Make sure both the Samples Sales Transactions and Zips to Fips DataSets are available. Screenshot 3. Select **Sample Sales Transactions** and look at the **Data** tab to understand its structure and identify the column it shares with the Zips to Fips data. in this case, the ZIP code. Here, the column is called `Zip Code.` Screenshot 4. Make sure the `Zip Code` column is formatted correctly. Screenshot 5. Return to the DataSets interface and select **Zips to Fips**. 6. In the **Data** tab, use the search columns tool to find potential ZIP codes to match the sales data. Screenshot 7. Three columns are returned as results. Note that the `ZIP` and `ZIP\_STRING` columns don't retain leading zeroes. We need the leading zeroes to match against our sales data, so we want to use the `ZIP\_STRING\_LEADING\_ZERO` column. In this image, note the leading zeroes. Screenshot You're now ready to create your first ETL. **Open Magic ETL** 8. From the Zips to Fips data, select **Open With** > **Magic ETL**. Screenshot 9. Review the training pop-ups as needed, then close them. Screenshot **Tip:** The Magic ETL checklist is great for making sure things are configured properly. Toggle the checklist by selecting **Show Checklist** (checkmark icon) in the toolbar above the Magic ETL canvas. Screenshot **Configure ETL Inputs** 10. From the panel to the left of the canvas under **DataSets**, drag an **Input DataSet** tile to the canvas. Screenshot 11. In the tile configuration area below the canvas, select **Choose DataSet** to open the data selection modal. Screenshot 12. Find and select `Sample Sales Transactions` and select **Choose DataSet** to return to the canvas. Screenshot With the data brought into Magic ETL, we're now ready to transform it. **Add Transform Tiles** 13. From the left panel under **Utility**, drag a Select Columns tile to the canvas and connect the node for the Sample Sales Transactions data to it by clicking and dragging. Screenshot 14. Add a second Select Columns tile and connect it to the Zips to Fips data. Screenshot 15. Choose the Select Columns tile connected to the sales data to open the tile configuration area. Screenshot 16. Select **Add All** **Columns**. Screenshot 17. Repeat these steps to add all columns for the Zips to Fips data. Although we know we only want one of the ZIP code columns, it can be easiest to add all columns at first and then remove the ones we don't want. 18. Now we can remove the ZIP columns we don't need by using the remove options (X icon) at the far right of every column row in the tile configuration tab. Screenshot 19. (Recommended) To make your DataFlow easier to configure, we recommend renaming your Select Columns tiles. In this example, we rename the first Select Columns tile to Sales Columns. Select the column to view the tile's configuration. Then use the **Edit** option (pencil icon) to rename the tile. We'll rename the other Select Columns tile to Zips Columns. Screenshot **Tip:** Running a preview is a great way to be confident in your data configuration. After the green checks are present, we can inspect the data. 20\. (Optional) Select **Run Preview** at the top of the canvas. If the preview is successful, green checkmarks display for each tile. Screenshot Screenshot 21\. Use the **Save** option in the top right corner of the canvas often to preserve your DataFlow. You can make notes about the version or simply save. Screenshot **Create a Join** 22. From the left panel under **Combine Data**, drag a Join Data tile to the canvas. Screenshot 23. Drag the right node from the Sales Columns tile to the triangle on the Join Data tile to connect them. Repeat for the Zips Columns tile. Screenshot **Configure the Join** 24. Select the Join Data tile to open the tile configuration area. 25. Use the **Join Type** dropdown to choose a Left Outer join. Screenshot Now we will select our first Key. Keys are columns that we match across DataSets to bring data together. 26. Choose **+ Equality condition** and choose the `Zip Code` column in the **Column from left table** dropdown. Screenshot Screenshot 27. In the **Column from right table** dropdown, choose the `ZIP\_STRING\_LEADING\_ZERO.` 28. Select **Done** in the top right corner of the tile configuration area. Screenshot **Build an Output** 29. From the left panel under **DataSets**, select an Output DataSet tile and drag it to the canvas. 30. Connect the Join Data tile to the Output DataSet tile. Screenshot 31. Name your DataFlow at the top of the canvas by selecting the name field and entering a name. We recommend naming all your DataFlows and DataSets according to a convention that will help you catalog and manage what you create. Screenshot 32. Select the Output DataSet tile to open the configuration area and name your Output DataSet tile. We recommend naming the DataSet in a way that describes the data it contains. Screenshot 33. Select **Done** in the tile configuration area. Screenshot You've completed the hardest part! Now it's time to schedule how often the DataFlow updates. **Schedule Your DataFlow** 34. Select the dropdown beside **Save** at the top of the canvas and choose **Save and Run**. Screenshot 35. We recommend leaving notes in the version description field to give helpful context for the future. Screenshot 36. (Optional) To add a trigger that will execute your DataFlow, select **Add Trigger**. Screenshot 37. Choose the trigger condition and select to which of the available DataSets the trigger should apply.\ Repeat for as many triggers as you want to add. Screenshot 38. When finished, select **Save and Run**. Wait while the DataFlow runs and opens in the **History** tab of the DataFlow details. Screenshot 39. Hover over the **1 Output DataSet** heading under the DataFlow name to see a link to the DataSet you created. You can use this DataSet to make the cards in the next section of this tutorial. Screenshot You have successfully connected your sales data with geographical details, unlocking new insights for location-based analysis. To best use Domo's powerful transformation tools, it's important to understand and carefully prepare your data. ## Build Cards and a Dashboard Creating insightful and interactive Domo dashboards can be a crucial part of your data strategy. This guide provides step-by-step instructions on how to build cards and a dashboard using our sample data. We'll also cover adding a link card and implementing a page filter to get more from your dashboard. There are different ways to access Analyzer, where cards are made. In this tutorial, we'll access it by first building a dashboard. **Create a Dashboard** 1. In the left navigation, select **Add** (plus icon) > **Dashboard**. Screenshot 2. Give your dashboard a name. Choose a name that relates to the department, business area, or subject matter. Then select **Save**. Screenshot **Note:** After saving your new dashboard, you can find it by going to **Features** > **Dashboards** in the left navigation. **Create Cards** 3. Go to your new dashboard and select **Add** (plus icon) > **Create new Card**. Screenshot 4. In the card type modal, select **Visualization**, then **Existing data**. Screenshot Screenshot 5. Choose the marketing DataSet you created [above](#connect-to-sample-google-sheets-data). Screenshot Your DataSet opens in Analyzer. Watch or close the tour pop-up that displays. Screenshot 6. In the **Chart types** panel on the right side of the screen, use the dropdown to go to **Line** > **Multi-line**. Screenshot When creating a card, Domo fills in the chart with suggested columns from your data. In this example, the `Date` and `Impression` columns are used. Screenshot To use different columns, you'll need to drag them from the **Columns** tab on the left side of the screen to the appropriate areas above the chart. Screenshot 7. When finished creating the card, we select the dropdown next to **Save** and choose **Save and Close**.\ Your dashboard displays, with your card in the dashboard's **Appendix**. Screenshot * Upon completion, select the wrench, edit your dashboard, and drag your new card from the Appendix into position. Then, hit save. **Create a Spend vs Revenue Card (Easy)** 8. In the **Chart types** panel on the right side of the screen, use the dropdown to go to **Vertical b\*\*\*\*ar** > **Grouped bar**. Screenshot 9. From the **Columns** tab on the left side of the screen, drag `Revenue` to the **Value** area above the chart and `Spend` to the **Series** area above the chart.\ By default, the `Date` column is already placed in the **Category** area above the chart, and both the `Revenue` and `Spend` columns are aggregated as a sum. Screenshot 10. Select **Save and Close**. \*\*Map (Medium)\*\*Now we'll make a map card using our Samples Sales Transaction DataSet, the output of our Magic ETL DataFlow. 11. Begin by adding a card to your dashboard, as described above. When you choose an existing DataSet, choose `Sample Sales Transactions v1.1` and select **Choose DataSet** to open the data in Analyzer. Screenshot 12. Use the **Chart types** dropdown to choose **Maps** > **United States**. Screenshot 13. From the **Columns** tab on the left side of the screen, drag the `State` column to the **State name** field above the chart. Screenshot 14. Under **Chart properties**, to the left of the map, select **General** and check the box for **Balanced distribution**. Screenshot This places our values in equal-colored buckets, making our Map Chart tell a more straightforward story. Screenshot 15. Select **Save as** and give the card a descriptive name. Then select **Save** to return to Analyzer. Screenshot 16. Close Analyzer to return to the dashboard. 17. At the top right of the dashboard, select **Settings menu** (wrench icon) > **Edit Dashboard**. Screenshot 18. Drag the `Sales by State` card to the dashboard area. This adds a content frame. Screenshot 19. Drag the card to the dashboard again to add it to the content frame. Screenshot 20. Select **Save** to close the dashboard editor. Screenshot 21. On the dashboard, hover over the `Sales by State` card and select **Card options** (wrench icon) > **Edit Drill Path**. Screenshot 22. Select **Add a view** to create a layer below the original card. This brings us back into Analyzer. Screenshot 23. This time, drag the `ZIP\_STRING\_LEADING\_ZERO` column to the **State name** field. Screenshot 24. Change the card's name to `Sales by Zip Code,` then save and close the card. 25. From the **Drill Path** view, return to **Details**. Screenshot 26. Select a state. 27. See its ZIP codes. Screenshot 28. Navigate back using the breadcrumbs at the top of the chart. Screenshot **Dashboard Functions** There are a lot of time ranges available when viewing your data on a dashboard. 29. Use the **Choose Date** dropdown to explore the available time ranges and aggregations. Screenshot ## Get Started with Alerts Domo Alerts is a powerful tool that can help you monitor specific conditions within your data and notify you when these conditions are met. This guide describes how to set up effective alerts for the five cards you built using the Marketing DataSet. 1. From the dashboard or appendix, hover over a card and select **Card options** (wrench icon) > **Alert Me...**. Screenshot 2. Select **+ New Alert** to open the alert modal. Screenshot 3. Use the **Metric** dropdown to choose the metric you want to monitor. We'll choose **Summary number**. 4. Use the conditions dropdown to choose "Changes by —" and enter the value for that condition. 5. Select **Next** and compose the message you want to receive when the alert triggers. Screenshot 6. Select **Next** and choose anyone with whom to share the alert, then select **Save**. Close the alert modal. **Tip:** After setting an alert, you can choose how you want to receive the alert from the **See Alerts** section on the card. Options include via text, email, and mobile app notification. Screenshot # Access and Start Creating Content through Domo's Navigation and Main Menu Source: https://www.domo.com/docs/s/article/000005900 ## Intro This article explains how to find and start creating content through Domo's navigation bar and main menu and how to personalize your navigation experience. *** ## Access Domo's Navigation You can find Domo Navigation on the left side of your browser window from every screen in Domo—except full-screen editors like those in Workflows or App Studio. Screenshot By default, the navigation displays only the icon for each item. To expand the navigation bar and show all icons with their titles, select the Domo icon at the bottom of the navigation or any empty space within the navigation bar. Screenshot ## Enable Navigation in Your Instance If you are a **Domo Administrator**, you can enable or disable the navigation for all users or a specific group of users. Learn more about the [Domo administrator role](/docs/s/article/360043438953). To enable Domo Navigation in your instance, follow these steps: 1. Navigate to the **Admin** menu. 2. Under **Features**, select **Feature management**. Screenshot 3. Choose one of the following settings: 1. **Not enabled in your instance** — Disables the navigation for all users. 2. **Enabled for everyone** — Enables the navigation for everyone in your instance. 3. **Enabled for admins** — Enables the new navigation for administrators only. 4. **Enabled for a specific group** — Enables the navigation for a specific Domo group.\ You can create a group with a specific subset of users to enable navigation, or you can remove them from a group to exclude them. Screenshot 4. Select **Save** to apply your enablement settings. ## Lock the Navigation Bar When the Domo Navigation is unpinned, it hovers over the rest of the screen. When you select the pin icon in the left corner of the expanded navigation, it stays in the fixed location and does not cover any part of the screen. To lock and unlock the expanded state of the navigation, select the pin icon in the top right corner of the navigation bar. Screenshot Screenshot **Note:** After locking the navigation, it remains pinned throughout Domo until you select **Close** to collapse it. ## Access and Create Content In the Domo navigation bar, you can view your instance's logo, name, and URL, access and create content through the main menu, find your pinned items, and view your user profile. ### Find Your Instance's Logo, Name, and URL Your instance's logo, name, and URL display at the top of the navigation. Screenshot ### Navigate the Main Menu You can navigate Domo's features, create new content, view your most recent content, and access administrative tools in the main menu. Screenshot #### Find Features Select **Features** to find all of Domo's functionality by category. Screenshot #### Search for Content Locate any content in your Domo instance by typing a keyword into the **Search** bar. You also have the option to browse for content by specific feature. **Note:** The navigation's search function prioritizes content you have previously visited. Screenshot #### Create New Content Select **Add** to access the **Create** menu and build new assets such as App Studio apps, cards, datasets, workflows, and tasks. You can also connect and transform data, manage users and groups, and start conversations from this menu. Screenshot #### View Recent Content Select **Recent** to access content and features you've worked on lately, organized by timeframe. Screenshot #### Access Administrative Settings Select **Admin** to navigate all administrative tools, including governance, security, and feature management. Screenshot ### Find Your Pinned Items When you pin an item, such as a Domo feature, App Studio app, card, or link, it shows in the pinned items section of the navigation. Learn how to [pin items to your Domo navigation](#pin-items). **Note:** When you pin multiple items, the navigation bar automatically adjusts. If the space is filled, you can access all your pinned items from a sub-menu, indicated by the **All navigation items** icon. Select this icon to view the complete list and navigate to any of your pinned assets. A screenshot of a phoneAI-generated content may be incorrect. Screenshot ### Open Your Profile You can find personal settings and activity, including **Account Details**, **Notifications**, and **Sign Out,** by selecting the **User Profile** icon at the bottom of the navigation. Screenshot ## Personalize Your Navigation Experience Pin your most-used features, like App Studio or DataFlows, or actions, like uploading a file or opening a card, to your Pinned Items navigation below the main menu. ### Pin Items You can add any feature in the main menu to your pinned items by hovering over then selecting the **Add to navigation** icon . You can pin any number of items to your pinned items section. The new navigation scrolls as you add more items. A screenshot of a computerDescription automatically generated ### Personalize Your Navigation You can pin any item in Domo to your favorites by following these steps: 1. Select **Personalize your navigation** in the left navigation. A screenshot of a computerDescription automatically generated The **Add** **item\*\*\*\*to navigation** modal opens. Screenshot 2. Choose what action should take place when you select the item.\ You can choose one of the following: 1. **Open Domo content** — Choose the content to open and whether to open it in a new browser tab.\ Give the navigation item a label, icon, and icon and background color. A screenshot of a computerDescription automatically generated 2. **Open a feature** — Choose the Domo feature to open and whether to open it in a new browser tab.\ Choose an icon, icon color, and icon background color. A screenshot of a computerDescription automatically generated 3. **Perform an action** — Choose what takes place when you select the icon. Options include uploading a file, creating a new ETL DataFlow, syncing on-premises data, and more.\ You can choose whether to perform the action in a new browser tab and give the item a label, an icon, and icon and background colors. A screenshot of a computerDescription automatically generated 4. **Open** **URL** — Enter the URL that should open and whether to open it in a new browser tab.\ Choose an icon, icon color, and icon background color. **Note:** The URL must begin with "**https\://**". A screenshot of a computerDescription automatically generated ### Edit/Unpin Items You can edit the details for any item in your pinned items by accessing that item's pin settings. 1. Hover over the item and right-click it to open its pin settings. Screenshot 2. Edit, remove, open, or reorder the item. 3. Select **Done** to save your changes. # Snowflake Key Pair Domo Managed Unload Connector Source: https://www.domo.com/docs/s/article/000005921 ## Intro Snowflake is a cloud-based data warehouse designed to support all your data and users. If you need to execute very large queries and move the results to Domo, use the Snowflake Key Pair Domo Managed Connector. * This connector first unloads data from your Snowflake instance into an Amazon S3 bucket. * The unloaded files are then automatically imported from Amazon S3 into Domo. **Note:** Choose this connector as the preferred method over the standard Snowflake connector when processing extremely large query result sets. You can connect to your Snowflake Key Pair Domo Managed Unload account in the Data Center. This topic discusses the fields and menus that are specific to the Snowflake Key Pair Domo Managed Unload connector user interface. To add DataSets, set update schedules, and edit DataSet information, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Prerequisites To connect to your Snowflake Key Pair Domo Managed Unload account and create a DataSet, you need the following: * Account Identifier * Username * Private Key ## Connecting to Your Snowflake Key Pair Domo Managed Unload Account This section enumerates the options in the **Credentials** and **Details** panes on the Snowflake Key Pair Domo Managed Unload Connector page. The components of the other panes on this page, **Scheduling**, and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in great detail in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Credentials Pane This pane contains fields for entering credentials to connect to your Snowflake Key Pair Domo Managed Unload account. The following table describes what is needed for each field:

Field

Description

Account Identifier

Specify the name of your Snowflake account based on its region:

  • US West Region: Use the format account\_name .

  • All Other Regions: Use the format account\_name.region\_id .

Username Enter the username to connect to your Snowflake host.
Private Key Enter the Private Key.
Passphrase

If you choose to create an encrypted private key, OpenSSL will prompt you to enter a passphrase . This passphrase is used to encrypt the private key file. Enter the required passphrase when prompted.

Role

Enter your role.

Once you have entered valid Snowflake Key Pair Domo Managed Unload credentials, you can use the same account at any time to create a new Snowflake Key Pair Domo Managed Unload DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Manage Connector Accounts](https://domo-support.domo.com/s/article/360042926054?language=en_US "Manage Connector Accounts"). ## Details Pane

Menu

Description

How would you like to import data into Domo?

Select any one of the methods below to import your data into Domo.

  • Standard Update
  • Use Partition
  • Use Upsert
Query Type

Select the query type from the drop-down list.

QueryType Description
Custom Query Enter the SQL query you want to execute.
Query Builder Select a table and the fields to autogenerate your query.
Warehouses

Select the warehouse.

Databases

Select the database.

Schemas

Select the schema.

Database Objects

Choose the database object.

Tables

Select the table.

Views

Select the view.

Table Column Names

Select the table columns you want to include in your report.

View Column Names

Select the view columns you want to include in your report.

Table Query Helper

Enter the generated query based on the selected fields.

View Query Helper

A query is generated based on the selected fields.

Query

Enter the SQL query you want to execute.

Partition Criteria

Select whether you want to partition your data using the date keys, non-date keys, or a meta query.

Partition Date Key Table Column Name

Select the partition column name.

Partition Date Key View Column Name

Select the partition column name. Only date fields will be displayed.

Enter Partition Date Key Column Name

Enter the partition column name.

Past Days

Enter the number of past days for which you want to retrieve the data. This value must be a positive integer (e.g., 30).

Date Format

Select the required date format. By default, yyyy-MM-dd will be used.

Custom Date Format

Enter the custom date format.

Partition Non Date Key Table Column Name

Select the partition column name.

Partition Non Date Key View Column Name

Select a non-date key column name to partition the data. All the fields, excluding Date fields, will be displayed.

Enter Partition Non Date Key Column Name

Enter the partition column name.

Partition Query to determine partition tags

Enter the partition query to determine the distinct partition tags. The column containing the Date data is your partition column. Example: Select Date from Table\_Name.

Upsert Key Column(s)

Enter the upsert key column name or a comma-separated list of upsert key column names. Required only when the Update method is Merge.

## Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). # Azure SQL Data Warehouse Connector Source: https://www.domo.com/docs/s/article/1500000281802 ## Azure SQL Datawarehouse is now Azure Synapse SQL Datawarehouse #### What is happening? Starting on Monday Nov 16 th 2020, the **Azure SQL Data Warehouse** **Connector** will be known as the **Azure Synapse SQL Connector**. #### How does this affect me? All Azure SQL Data Warehouse datasets will continue to run as normal. The functionality of the connector has not been changed. Customers using or planning to use the connector will notice the following: 1. There is a new icon for the connector in the Appstore. Existing datasets will now show up on the Data Center with the new icon. 2. Customers who are trying to search for an Azure Data Warehouse dataset in the Data Center using a 'Type' filter will now need to search for datasets of type 'Azure Synapse SQL' instead of 'Azure Data Warehouse'. 3. Customers who want to create a new Azure SQL Data Warehouse will need to search the Appstore for the 'Azure Synapse SQL Connector' instead of the 'Azure SQL Data Warehouse Connector.' 4. Connector Accounts for the Azure SQL Data Warehouse Connector will now be called 'Azure Synapse SQL' Accounts. #### Do I need to take any action if I have any Azure Data Warehouse datasets? No action is required on your part. Your existing Azure Data Warehouse/Azure Synapse SQL datasets will continue to run without interruption, and you will still be able to create new datasets with existing credentials as needed. You do not need to update any of your reports or Accounts. Please visit [Azure Synapse SQL Connector](/docs/s/article/360042931674 "https://knowledge.domo.com/Connect/Connecting_to_Data_with_Connectors/Configuring_Each_Connector/Database_Connectors/Azure_Synapse_SQL_Connector") documentation for any queries related to the connector functionality. # Snowflake KeyPair Unload V2 Connector Source: https://www.domo.com/docs/s/article/1500000555201 ## Intro Snowflake is a data warehouse built for the cloud for all your data and users. The Domo Snowflake KeyPair Unload V2 Connector unloads data from the Snowflake database into Amazon S3 providing an easy and secure access to your Snowflake data. This connector should be preferred over the Snowflake connector if you are executing very large queries. You connect to your Snowflake database in the Data Center. This topic discusses the fields and menus that are specific to the Snowflake KeyPair Unload V2 connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Prerequisites To connect to a Snowflake database and create a DataSet, you must have the following: * The full name of your account (provided by Snowflake). This is the portion of your Snowflake URL immediately following https\://.\ Note that your full account name may include additional segments that identify the region and cloud platform where your account is hosted. For US West Region **account\_name** and All other regions **account\_name.region\_id**. The following table provides account name examples by cloud platform/region. For each row, it assumes your account name is "xy12345." snowflake_account_names.png * The username used to connect to your Snowflake host. * The private key. * The passphrase. If you create an encrypted private key, then OpenSSL prompts for a passphrase used to encrypt the private key file. * The name for your role. * Your AWS access key. It is available in the AWS Console in the **Security Credentials** section or under **Users** if you are using **IAM**. * Your AWS secret key. was provided when you created your Access Key. You can generate a new one in the AWS Console. * The name of the AWS S3 bucket that your Snowflake data will be unloaded into. * Your Amazon S3 Region. ### Configuring the public/private key pair To configure the public/private key pair, follow these steps: 1. From the command line in a terminal window, generate a private key.\ You can generate either an encrypted version of the private key or an unencrypted version of the private key. * To generate an unencrypted version, use the following command: `$ openssl genrsa -out rsa_key.pem 2048` * To generate an encrypted version, use the following command: `$ openssl genrsa 2048 | openssl pkcs8 -topk8 -inform PEM -out rsa_key.p8` It is typically safer to generate an encrypted version. If you use the second command to encrypt the private key, then OpenSSL prompts for a passphrase used to encrypt the private key file. We recommend using a strong passphrase to protect the private key. Record this passphrase in a secure location. You will input it when connecting to Snowflake. Note that the passphrase is only used for protecting the private key and will never be sent to Snowflake. The following is a sample PEM private key: `-----BEGIN ENCRYPTED PRIVATE KEY----- MIIE6TAbBgkqhkiG9w0BBQMwDgQILYPyCppzOwECAggABIIEyLiGSpeeGSe3xHP1 wHLjfCYycUPennlX2bd8yX8xOxGSGfvB+99+PmSlex0FmY9ov1J8H1H9Y3lMWXbL ... -----END ENCRYPTED PRIVATE KEY-----` 2. From the command line, generate the public key by referencing the private key. Assuming the private key is encrypted and contained in the file named “rsa\_key.p8”, use the following command: `$ openssl rsa -in rsa_key.p8 -pubout -out rsa_key.pub` The following is a sample PEM public key: `-----BEGIN PUBLIC KEY----- MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAy+Fw2qv4Roud3l6tjPH4 zxybHjmZ5rhtCz9jppCV8UTWvEXxa88IGRIHbJ/PwKW/mR8LXdfI7l/9vCMXX4mk ... -----END PUBLIC KEY-----` 3. Copy the public and private key files to a local directory for storage. Record the path to the files. Note that the private key is stored using the PKCS#8 (Public Key Cryptography Standards) format and is encrypted using the passphrase you specified in the previous step; however, the file should still be protected from unauthorized access using the file permission mechanism provided by your operating system. It is your responsibility to secure the file when it is not being used. 4. Assign the public key to the Snowflake user using ALTER USER. For example: `alter user jsmith set rsa_public_key='MIIBIjANBgkqh...';` **Notes:** * Only security administrators (i.e. users with the SECURITYADMIN role) or higher can alter a user. * Exclude the public key header and footer in the SQL statement. 5. Verify the user's public key fingerprint using DESCRIBE USER:

Property

Value

Default

Description

Name

JSMITH

null

Name

RSA\_PUBLIC\_KEY\_FP

SHA256:nvnONUsfiuycCLMXIEWG4eTp4FjhVUZQUQbNpbSHXiA=

null

Fingerprint of user's RSA public key.

RSA\_PUBLIC\_KEY\_2\_FP

null

null

Fingerprint of user's second RSA public key.

**Note:** For more information about the RSA\_PUBLIC\_KEY\_2\_FP property, see Key Rotation 6\. Modify and execute the sample code, below. The code decrypts the private key file and passes it to the Snowflake driver to create a connection: * Update the security parameters: * `` specifies the local path to the private key file you created. * Update the session parameters: * `` specifies your Snowflake login name. * `` specifies the name of your account (provided by Snowflake). * The sample code is as follows: ```java theme={"dark"} import java.util.Properties; import java.sql.Connection; import java.sql.Statement; import java.sql.ResultSet; import java.sql.DriverManager; import java.io.File; import java.io.FileInputStream; import java.io.DataInputStream; import java.util.Base64; import java.security.spec.PKCS8EncodedKeySpec; import java.security.KeyFactory; import java.security.PrivateKey; import javax.crypto.EncryptedPrivateKeyInfo; import javax.crypto.SecretKeyFactory; import javax.crypto.spec.PBEKeySpec; public class TestJdbc { public static void main(String[] args) throws Exception { File f = new File("/rsa_key.p8"); FileInputStream fis = new FileInputStream(f); DataInputStream dis = new DataInputStream(fis); byte[] keyBytes = new byte[(int) f.length()]; dis.readFully(keyBytes); dis.close(); String encrypted = new String(keyBytes); String passphrase = System.getenv("PRIVATE_KEY_PASSPHRASE"); encrypted = encrypted.replace("-----BEGIN ENCRYPTED PRIVATE KEY-----", ""); encrypted = encrypted.replace("-----END ENCRYPTED PRIVATE KEY-----", ""); EncryptedPrivateKeyInfo pkInfo = new EncryptedPrivateKeyInfo(Base64.getMimeDecoder().decode(encrypted)); PBEKeySpec keySpec = new PBEKeySpec(passphrase.toCharArray()); SecretKeyFactory pbeKeyFactory = SecretKeyFactory.getInstance(pkInfo.getAlgName()); PKCS8EncodedKeySpec encodedKeySpec = pkInfo.getKeySpec(pbeKeyFactory.generateSecret(keySpec)); KeyFactory keyFactory = KeyFactory.getInstance("RSA"); PrivateKey encryptedPrivateKey = keyFactory.generatePrivate(encodedKeySpec); String url = "jdbc:snowflake://.snowflakecomputing.com"; Properties prop = new Properties(); prop.put("user", ""); prop.put("account", ""); prop.put("privateKey", encryptedPrivateKey); Connection conn = DriverManager.getConnection(url, prop); Statement stat = conn.createStatement(); ResultSet res = stat.executeQuery("select 1"); res.next(); System.out.println(res.getString(1)); conn.close(); } } ``` #### Key Rotation Snowflake supports multiple active keys to allow for uninterrupted rotation. Rotate and replace your public and private keys based on the expiration schedule you follow internally. Currently, you can use the RSA\_PUBLIC\_KEY and RSA\_PUBLIC\_KEY\_2 parameters for ALTER USER to associate up to 2 public keys with a single user. To rotate your keys, 1. Complete the steps in Using Key Pair Authentication to... * Generate a new private and public key set. * Assign the public key to the user. Set the public key value to either RSA\_PUBLIC\_KEY or RSA\_PUBLIC\_KEY\_2 (whichever key value is not currently in use).\ For example: `alter user jsmith set rsa_public_key_2='JERUEHtcve...';` 2. Update the code to connect to Snowflake. Specify the new private key.\ Snowflake verifies the correct active public key for authentication based on the private key submitted with your connection information. 3. Remove the old public key from the user profile. For example: `alter user jsmith unset rsa_public_key;` ## Connecting to Your Snowflake Account This section enumerates the options in the **Credentials** and **Details** panes in the Snowflake KeyPair Unload V2 Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ### Credentials Pane This pane contains fields for entering credentials to your Snowflake account. The following table describes what is needed for each field:

Field

Description

Account Name

Enter the full name of your account (provided by Snowflake.) For US West Region account\_name and All other regions account\_name.region\_id

Username

Enter the username used to connect to your Snowflake host.

Private Key

Enter the private key.

Passphrase

If you create an encrypted private key, then OpenSSL prompts for a passphrase used to encrypt the private key file. Enter that passphrase here.

Role

Enter your role.

Access Key

Enter your AWS access key. It is available in the AWS Console in the Security Credentials section or under Users if you are using IAM.

Secret Key

Enter your AWS secret access key. It was provided when you created your Access Key. You can generate a new one in the AWS Console.

Bucket

Enter the name of the AWS S3 bucket that your Snowflake data will be unloaded into.

Region

Select the Amazon S3 Region.

Encryption Type

Specify the encryption type for unloading data to files in storage locations.

Once you have entered valid credentials, you can use the same account any time you to create a new Snowflake KayPair Unload V2 dataset. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054). ### Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

How would you like to import data into Domo?

Select how you want to import your data.

Query Type

Warehouses

Select the warehouse containing the data you want to retrieve. The list populates with all warehouses you have access to based on your credentials.

Databases

Select the database containing the data you want to retrieve. The list populates with all databases you have access to based on your credentials.

Schemas

Select the database schema containing the data you want to retrieve. The list populates with all schemas you have access to based on your credentials.

Database Objects

Choose the database object.

Tables

Select the database table you want to retrieve. The list populates with all tables you have access to based on your credentials. If you do not select a database table, the connector retrieves your entire database schema.

Views

Select the view.

Table Columns

Select the table columns you would like to include in your report. If you do not select any table column, the connector will retrieve your entire selected database table.

View Column Names

Select the view columns that you would like to include in your report.

Query

Enter the SQL query to execute.

Table Query Helper

Generated the query based on the selected fields.

View Query Helper

A query is generated based on the selected fields.

Partition Criteria

Select whether you want to partition your data using the date keys, non-date keys, or meta query.

Select Partition Date Key Column Name

Select the partition column name.

Partition Column Name

Select the partition column name. Only date fields will be shown in this discovery.

Enter Partition Date Key Column Name

Enter the partition column name.

Past Days

Enter the number of past days that you want to fetch the data for. Value can be X, where X is a positive integer. For example: 30.

Date Format

Select the required date format. By default, yyyy-MM-dd will be used.

Custom Date Format

Enter the custom date format.

Select Partition Non Date Key Column Name

Select the partition column name.

Partition Non Date Key Column Name

Select a non-date key column name to partition the data. All the fields excluding Date fields will be shown in this discovery.

Enter Partition Non Date Key Column Name

Enter the partition column name.

Partition Query to determine partition tags

Enter the partition query to determine the distinct partition tags. The column containing the Date data is your partition column. Example: Select Date from Table\_Name.

Upsert Key Column(s)

Please enter upsert key column name or a comma separated list of upsert key column names. Required only when Update method is Merge.

### Other Panes For information about the remaining sections of the Connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQs The limits depend on your server configuration. DataSets can run as often as every 15 minutes. However, depending on the runtime of the query, DataSets may need to run less frequently. Make sure that all the words, table names, and field names are correctly spelled. Refer to the Query Helper field for query help. Before you can connect to a Snowflake database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses in Domo](/docs/s/article/360043439173). ## Troubleshooting * Make sure your authentication remains valid. * Review the configuration to make sure that all required items have been selected. * Review the Connector history for error messages. * In rare cases, you may be requesting too much information and reaching API limitations or timeouts. If this is the case, you can review the history of the Connector run to see the error message and duration. If this is the case, you can reduce the number of accounts that are being pulled, choose a smaller number of metrics for the report that you are pulling, or reduce the timeframe that you are trying to pull. # Snowflake KeyPair Partition Connector Source: https://www.domo.com/docs/s/article/1500000888261 ## Intro The Domo Snowflake KeyPair Partition makes it easy to bring all your data from your Snowflake data warehouse into Domo based on the number of past days provided. If you are already using Snowflake as a data warehousing solution, this connector helps you use Domo in conjunction with it to get the most from your data. To use this connector, you must have your Snowflake account name (domain) and the username and private key for your Snowflake account. Use Domo's Snowflake KeyPair Partition connector to maximize your cloud data strategy by connecting your data to Domo and making it instantly accessible to everyone in your company.\ Once your Snowflake data is in Domo, you can combine it with all your other Domo data to get a centralized view of your most mission-critical data. *** ## Prerequisites To connect to a Snowflake database and create a DataSet, you must have the following: * The full name of your account (provided by Snowflake). This is the portion of your Snowflake URL immediately following https\://.\ Note that your full account name may include additional segments that identify the region and cloud platform where your account is hosted. For US West Region **account\_name** and All other regions **account\_name.region\_id**. The following table provides account name examples by cloud platform/region. For each row, it assumes your account name is "xy12345." snowflake_account_names.png * The username used to connect to your Snowflake host. * The private key. * The passphrase. If you create an encrypted private key, then OpenSSL prompts for a passphrase used to encrypt the private key file. * Your role name. ### Configuring the public/private key pair To configure the public/private key pair, follow these steps: 1. From the command line in a terminal window, generate a private key.\ You can generate either an encrypted version of the private key or an unencrypted version of the private key. * To generate an unencrypted version, use the following command: `$ openssl genrsa -out rsa_key.pem 2048` * To generate an encrypted version, use the following command: `$ openssl genrsa 2048 | openssl pkcs8 -topk8 -inform PEM -out rsa_key.p8` It is typically safer to generate an encrypted version. If you use the second command to encrypt the private key, then OpenSSL prompts for a passphrase used to encrypt the private key file. We recommend using a strong passphrase to protect the private key. Record this passphrase in a secure location. You will input it when connecting to Snowflake. Note that the passphrase is only used for protecting the private key and will never be sent to Snowflake. The following is a sample PEM private key: `-----BEGIN ENCRYPTED PRIVATE KEY----- MIIE6TAbBgkqhkiG9w0BBQMwDgQILYPyCppzOwECAggABIIEyLiGSpeeGSe3xHP1 wHLjfCYycUPennlX2bd8yX8xOxGSGfvB+99+PmSlex0FmY9ov1J8H1H9Y3lMWXbL ... -----END ENCRYPTED PRIVATE KEY-----` 2. From the command line, generate the public key by referencing the private key. Assuming the private key is encrypted and contained in the file named “rsa\_key.p8”, use the following command: `$ openssl rsa -in rsa_key.p8 -pubout -out rsa_key.pub` The following is a sample PEM public key: `-----BEGIN PUBLIC KEY----- MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAy+Fw2qv4Roud3l6tjPH4 zxybHjmZ5rhtCz9jppCV8UTWvEXxa88IGRIHbJ/PwKW/mR8LXdfI7l/9vCMXX4mk ... -----END PUBLIC KEY-----` 3. Copy the public and private key files to a local directory for storage. Record the path to the files. Note that the private key is stored using the PKCS#8 (Public Key Cryptography Standards) format and is encrypted using the passphrase you specified in the previous step; however, the file should still be protected from unauthorized access using the file permission mechanism provided by your operating system. It is your responsibility to secure the file when it is not being used. 4. Assign the public key to the Snowflake user using ALTER USER. For example: `alter user jsmith set rsa_public_key='MIIBIjANBgkqh...';` **Notes:** * Only security administrators (i.e. users with the SECURITYADMIN role) or higher can alter a user. * Exclude the public key header and footer in the SQL statement. 5. Verify the user's public key fingerprint using DESCRIBE USER:

Property

Value

Default

Description

Name

JSMITH

null

Name

RSA\_PUBLIC\_KEY\_FP

SHA256:nvnONUsfiuycCLMXIEWG4eTp4FjhVUZQUQbNpbSHXiA=

null

Fingerprint of user's RSA public key.

RSA\_PUBLIC\_KEY\_2\_FP

null

null

Fingerprint of user's second RSA public key.

**Note:** For more information about the RSA\_PUBLIC\_KEY\_2\_FP property, see Key Rotation. 6\. Modify and execute the sample code, below. The code decrypts the private key file and passes it to the Snowflake driver to create a connection: * Update the security parameters: * `` specifies the local path to the private key file you created. * Update the session parameters: * `` specifies your Snowflake login name. * `` specifies the name of your account (provided by Snowflake). * The sample code is as follows: ```java theme={"dark"} import java.util.Properties; import java.sql.Connection; import java.sql.Statement; import java.sql.ResultSet; import java.sql.DriverManager; import java.io.File; import java.io.FileInputStream; import java.io.DataInputStream; import java.util.Base64; import java.security.spec.PKCS8EncodedKeySpec; import java.security.KeyFactory; import java.security.PrivateKey; import javax.crypto.EncryptedPrivateKeyInfo; import javax.crypto.SecretKeyFactory; import javax.crypto.spec.PBEKeySpec; public class TestJdbc { public static void main(String[] args) throws Exception { File f = new File("/rsa_key.p8"); FileInputStream fis = new FileInputStream(f); DataInputStream dis = new DataInputStream(fis); byte[] keyBytes = new byte[(int) f.length()]; dis.readFully(keyBytes); dis.close(); String encrypted = new String(keyBytes); String passphrase = System.getenv("PRIVATE_KEY_PASSPHRASE"); encrypted = encrypted.replace("-----BEGIN ENCRYPTED PRIVATE KEY-----", ""); encrypted = encrypted.replace("-----END ENCRYPTED PRIVATE KEY-----", ""); EncryptedPrivateKeyInfo pkInfo = new EncryptedPrivateKeyInfo(Base64.getMimeDecoder().decode(encrypted)); PBEKeySpec keySpec = new PBEKeySpec(passphrase.toCharArray()); SecretKeyFactory pbeKeyFactory = SecretKeyFactory.getInstance(pkInfo.getAlgName()); PKCS8EncodedKeySpec encodedKeySpec = pkInfo.getKeySpec(pbeKeyFactory.generateSecret(keySpec)); KeyFactory keyFactory = KeyFactory.getInstance("RSA"); PrivateKey encryptedPrivateKey = keyFactory.generatePrivate(encodedKeySpec); String url = "jdbc:snowflake://.snowflakecomputing.com"; Properties prop = new Properties(); prop.put("user", ""); prop.put("account", ""); prop.put("privateKey", encryptedPrivateKey); Connection conn = DriverManager.getConnection(url, prop); Statement stat = conn.createStatement(); ResultSet res = stat.executeQuery("select 1"); res.next(); System.out.println(res.getString(1)); conn.close(); } } ``` #### Key Rotation Snowflake supports multiple active keys to allow for uninterrupted rotation. Rotate and replace your public and private keys based on the expiration schedule you follow internally. Currently, you can use the RSA\_PUBLIC\_KEY and RSA\_PUBLIC\_KEY\_2 parameters for ALTER USER to associate up to 2 public keys with a single user. To rotate your keys, 1. Complete the steps in Using Key Pair Authentication to... * Generate a new private and public key set. * Assign the public key to the user. Set the public key value to either RSA\_PUBLIC\_KEY or RSA\_PUBLIC\_KEY\_2 (whichever key value is not currently in use).\ For example: `alter user jsmith set rsa_public_key_2='JERUEHtcve...';` 2. Update the code to connect to Snowflake. Specify the new private key.\ Snowflake verifies the correct active public key for authentication based on the private key submitted with your connection information. 3. Remove the old public key from the user profile. For example: `alter user jsmith unset rsa_public_key;` ## Connecting to Your Snowflake Account This section enumerates the options in the **Credentials** and **Details** panes in the Snowflake KeyPair Partition Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ### Credentials Pane This pane contains fields for entering credentials to your Snowflake account. The following table describes what is needed for each field:

Field

Description

Account Name

Enter the full name of your account (provided by Snowflake.) For US West Region account\_name and All other regions account\_name.region\_id

Username

Enter the username used to connect to your Snowflake host.

Private Key

Enter the private key.

Passphrase

If you create an encrypted private key, then OpenSSL prompts for a passphrase used to encrypt the private key file. Enter that passphrase here.

Role

Enter the name for your role.

Once you have entered valid credentials, you can use the same account any time you to create a new Snowflake KayPair Partition dataset. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054). ### Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

How would you like to import data into Domo?

Select how you want to import your data. The following methods are available: - Standard Update (Replace/Append) - Use Partition - Use Upsert

How would you like to build your Query?

Warehouses

Select the warehouse containing the data you want to retrieve. The list populates with all warehouses you have access to based on your credentials.

Databases

Select the database containing the data you want to retrieve. The list populates with all databases you have access to based on your credentials.

Schemas

Select the database schema containing the data you want to retrieve. The list populates with all schemas you have access to based on your credentials.

Database Objects

Choose a database object.

Tables

Select the database table you want to retrieve.

Table Column Names

Select the table columns that you want to include in your report.

Table Query Helper

A query is generated based on the selected fields.

Views

Select the view.

View Column Names

Select the view columns that you want to include in your report.

View Query Helper

A query is generated based on the selected fields.

Partition Criteria

Select whether you want to partition your data using the date keys, non-date keys, or a meta query.

Partition Column Name

Select the partition column name. Only date fields will be displayed.

Partition Support Format

Select the partition format.

Partition Non Date Key Column Name

Select a non-date key column name to partition the data. All the fields, excluding Date fields, will be displayed.

Query

Enter the query to execute. The query format must be like: select \* from "databaseName"."schemaName"."tableName""

Partition Query to determine partition tags

Enter the partition meta query to determine the distinct partition tags(or keys). The column containing the Date data is your partition column. Example: SELECT DISTINCT(DATE\_COLUMN\_NAME) FROM TABLENAME

Past Days

Enter the number of past days for which you want to fetch the data. Value can be X, where X is a positive integer. For example: 30.

Past Years

Enter the number of past years for which you want to fetch the data. Value can be X, where X is a positive integer. For example: 30.

Future Years

Enter the number of future years for which you want to fetch the data. Value can be X, where X is a positive integer. For example: 30.

Past Months

Enter the number of past months for which you want to fetch the data. Value can be X, where X is a positive integer. For example: 30.

Future Months

Enter the number of future months for which you want to fetch the data. Value can be X, where X is a positive integer. For example: 30.

Data Format

Select/enter the proper date format according to the date format present in the partition column. By default, yyyy-MM-dd will be used.

Custom Date Format

Enter the custom date format.

Upsert Key Column(s)

Enter the upsert key column name or a comma-separated list of upsert key column names. Required only when the Update method is Merge.

Query Tag

Optional parameter that can be used to tag connector SQL executions in Snowflake as a Query Tag.

### Other Panes For information about the remaining sections of the Connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQs The limits depend on your server configuration. DataSets can run as often as every 15 minutes. However, depending on the runtime of the query, DataSets may need to run less frequently. Make sure that all the words, table names, and field names are correctly spelled. Before you can connect to a Snowflake database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses in Domo](/docs/s/article/360043439173). ## Troubleshooting * Make sure your authentication remains valid. * Review the configuration to make sure that all required items have been selected. * Review the Connector history for error messages. * In rare cases, you may be requesting too much information and reaching API limitations or timeouts. If this is the case, you can review the history of the Connector run to see the error message and duration. If this is the case, you can reduce the number of accounts that are being pulled, choose a smaller number of metrics for the report that you are pulling, or reduce the timeframe that you are trying to pull. # Amazon Redshift SSH Writeback Connector Source: https://www.domo.com/docs/s/article/1500001388361 ## Intro Amazon Redshift is a hosted data warehouse project that is part of the larger cloud computing platform Amazon Web Services. The Amazon Redshift SSH Writeback connector allows you to easily and securely export your data from a Domo DataSet to the provided Amazon Redshift database using SSH tunneling. For more information about the Redshift API, visit their website. ([http://docs.aws.amazon.com/redshift/...\_commands.html](http://docs.aws.amazon.com/redshift/latest/dg/c_SQL_commands.html "http://docs.aws.amazon.com/redshift/latest/dg/c_SQL_commands.html") ) You configure your Domo-Redshift connection in the Data Center. This topic discusses the fields and menus that are specific to the Amazon Redshift SSH Writeback Connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). **Note:** The owner of a writeback dataset must also be an owner or co-owner of the input dataset. ## Prerequisites To configure this Connector, you must have the following: * The hostname of the UNIX server you are SSH-tunneling through. * The SSH username and password for your UNIX account. * The SSH port number. * The SSH private key. * The Redshift database hostname or IP address. * The Redshift database name. * The username and password you use to log into your Redshift database. * The port number for the Redshift database. * Your AWS access key. It is available in the AWS Console in the Security Credentials section or under Users, if you are using IAM. * Your AWS secret key. It was provided when you created your Access Key. You can generate a new one in the AWS Console. * The name of the AWS S3 bucket. * The Client ID and Client Secret associated with your Domo account. Learn how to get your [Domo Client ID and Secret](/docs/s/article/000005240#create-api-clients). * The CA certificate text or URL path is required *only* if you select **Certificate String** or **URL Path**, respectively, in the **Certificate Format** menu. **Note: Domo does not support the SSH keys generated using ssh-keygen. The SSH keys need to be the DES or RSA keys (in PEM format) generated by OpenSSL.** ## Configuring the Connection This section enumerates the options in the **Credentials** and **Details** panes in the Amazon Redshift SSH Writeback Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most Connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ### Credentials Pane This pane contains fields for entering credentials to connect to your Domo developer account as well as the Amazon Redshift database. The following table describes what is needed for each field:

Field

Description

SSH Server Hostname Enter the hostname of the UNIX server you are SSH-tunneling through.
SSH Username Enter the SSH username for your UNIX account.
SSH Password Enter the SSH password for your UNIX account.
SSH Port Enter the SSH port number.
SSH Private Key Enter the SSH private key.
Database Hostname Enter the Redshift database hostname or IP address.
Database Name Enter the Redshift database name.
Database Username Enter the username you use to log into your Redshift database.
Database Password Enter the password you use to log into your Redshift database.
Database Port Enter the port number for the Redshift database.
Certificate Format Select a certificate format. If you do not want to include a certificate, select No certificate . If you select Certificate text, you must paste the text for your certificate in the Certificate field. If you select URL path , you must enter the URL where your certificate is in the Certificate field.

Certificate

Paste the text for your CA certificate or enter the URL where your certificate is located. This is optional. If you do not want to include a certificate, select No certificate in the Certificate Type menu.
Access Key Enter your AWS access key. It is available in the AWS Console in the Security Credentials section or under Users, if you are using IAM.
Secret Key Enter your AWS secret key. It was provided when you created your Access Key. You can generate a new one in the AWS Console.
Region Select your Amazon S3 region.
Bucket Enter the name of the AWS S3 bucket.
Domo Client ID Enter your Domo client ID.
Domo Client Secret Enter your Domo client secret.
Once you have entered valid credentials, you can use the same account any time you go to set up a new Domo-Amazon Redshift SSH connection. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane This pane contains a number of fields for specifying your data and indicating where it's going.

Menu

Description

Input DataSet ID Enter your Domo dataset ID(GUID) located in the dataset URL. You can find the ID by opening the details view for the DataSet in the Data Center and looking at the portion of the URL following datasources/ . For example, in the URL [https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview](https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview) , the DataSet ID is 845305d8-da3d-4107-a9d6-13ef3f86d4a4.
Table Name Source Choose how you would like to name the Redshift table.
  • DataSet ID . The Redshift table name will be the number you entered for DataSet ID .
  • DataSet Name . The Redshift table name will be the same as that of the input DataSet.
  • Custom Name . You will give the Redshift table a custom name in the Custom Table Name field.
Custom Table Name Enter the name for the Redshift table.
Schema Name Select the Schema to write the dataset data to.
Operation Type Select whether you want to create a new table or update an existing table.
Create New Table Select this option to create a new table for every execution. The table name will be the name specified in the Table Name Source field, plus a numeric counter.
Update an Existing Table Select this option to update an existing table only if the table name matches the existing one in the Redshift Server; otherwise, the connector will create a new table in the first run.
Append Or Overwrite Select how you like to update the database table. Note : The connector may create a new table if the table does not exist in the first run; then update the table as per the selected option in the subsequent execution/schedule run.
Append Data The connector will append the fetched data to the existing table.
Overwrite With New Data The connector will overwrite the existing data with newly fetched data to the existing table.
### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQs You need your Redshift SSH server hostname, port number, private key, username, and password as well as your database hostname, port number, database name, username, and password. You also need your AWS access key and secret key, AWS S3 bucket name, and your Domo Developer account credentials (client ID and Client secret). Before you can connect to a Redshift database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses for Connectors.](/docs/s/article/360043630093) Limits depend on your server configuration. ## Troubleshooting * Make sure your authentication remains valid. * Review the configuration to make sure that all required items have been selected. * Review the Connector history for error messages. * In rare cases, you may be requesting too much information and reaching API limitations or timeouts. If this is the case, you can review the history of the Connector run to see the error message and duration. If this is the case, you can reduce the number of accounts that are being pulled, choose a smaller number of metrics for the report that you are pulling, or reduce the timeframe that you are trying to pull. # Azure DevOps Connector Source: https://www.domo.com/docs/s/article/1500002644442 ## Intro Azure DevOps Server is a Microsoft product that provides version control, reporting, requirements management, project management, automated builds, testing and release management capabilities. It covers the entire application lifecycle, and enables DevOps capabilities. Use the Domo Azure DevOps connector to retrieve data about your projects, teams and work items. Use Domo's Azure DevOps connector to retrieve data about your projects, teams and work items. To learn more about the Azure DevOps API, visit their page ([https://docs.microsoft.com/en-us/res...evops-rest-6.1](https://docs.microsoft.com/en-us/rest/api/azure/devops/?view=azure-devops-rest-6.1)). You connect to your Azure DevOps account in the Data Center. This topic discusses the fields and menus that are specific to the Azure DevOps connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Prerequisites To connect to your Azure DevOps account and create a DataSet, you must have the following: * The username you use to sign into your Azure DevOps account. If it is an email address, the @subdomain portion may not be necessary. * Your Personal Access Token that you can generate by going to **User Settings > Personal Access Token** in your [Azure DevOps](https://dev.azure.com/) account. * Your Azure DevOps organization. For example, if you logged into your Azure DevOps instance at "[https://dev.azure.com/domo](https://dev.azure.com/domo)", you would enter "domo" here. ## Connecting to Your Azure DevOps Account This section enumerates the options in the **Credentials** and **Details** panes in the Azure DevOps Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Credentials Pane This pane contains fields for entering credentials to connect to your Azure DevOps account. The following table describes what is needed for each field:

Field

Description

Username

Enter the username you use to sign into your Azure DevOps account. If this is an email address, the @subdomain portion may not be necessary.

Personal Access Token

Enter your Personal Access Token that you can generate by going to User Settings > Personal Access Token in your Azure DevOps account.

Organization

Enter your Azure DevOps organization. For example, if you logged into your Azure DevOps instance at "[https://dev.azure.com/domo](https://dev.azure.com/domo)", you would enter "domo" here.

Once you have entered valid Azure DevOps credentials, you can use the same account any time you go to create a new Azure DevOps DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054). ## Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select. | Menu | Description | | --------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Report | Select the Azure DevOps report you want to run. The following reports are available:
Report NameDescription
AreasReturns the work item Area Paths, with properties for grouping and filtering by area hierarchy.
BoardsReturns the Kanban board cell locations, as identified by board column, swimlane, and split, includes historic board settings.
FieldsRetrieves fields from your project. Update mode supported: Replace Only
IterationsRetrieves the work item Iteration Paths, with properties for grouping and filtering by iteration hierarchy.
ProcessesRetrieves Backlog information used to expand or filter work items and work item types.
Profiles (Users)Retrieves the User information.
ProjectsRetrieves details about your projects. Update mode supported: Replace Only
TagsRetrieves work item tags for the specified project.
TeamsRetrieves details about your teams. Update mode supported: Replace Only
Work ItemsRetrieves details about your work items. Update mode supported: Merge Only
Work Items DeletedRetrieves deleted work items from Recycle Bin.
Work Items V2Retrieves details of your work items. Supported update modes: Replace, Append, and Merge only.
Work Item LinksRetrieves the links between work items.
Work Item RevisionsRetrieves all historic work item revisions, including the current revision.
Work Items with Custom QueryRetrieves details about your work items by customizing the query. Update mode supported: Merge Only
| | Projects | Returns a list of all available projects. | | Custom Query Params | Enter the query parameters that you want to provide while pulling the work items, separated by a newline. Example: `parameterName=value`. **Note:** The connector paginates the work items with the help of `System.ID` and `System.ChangedDate`, avoid providing them as the parameters. | | Backfill Date | Select the date to retrieve Work Items from based on the Work Item's 'ChangedDate' field. | | Exclude Kanban Fields | Select this checkbox if you want to exclude all the column names that contain Kanban in the field name. For example, if the field `WEF_3C7EF45428404E54BBDB86AE473EE9B3_Kanban.Column` or `WEF_3C7EF45428404E54BBDB86AE473EE9B3_Kanban.Column.Done` is available in Work items report, the connector will exclude those fields in your Work items report. | | Ignore ordering of Work Items | Select this checkbox if you want to ignore the ordering of the Ids while retrieving the work items. | | Enter the value for top query parameter | Enter a value to specify the maximum number of work items to be pulled in an API call, else it would use the default value. | | Reset the Date | Reset the date to the default supplied value used in the backfill date. | | Preserve Schema | Select this checkbox if you want to preserve the column names within a dataset. | **Note:** In the very first successful run, the **Work Items** and **Work Items with Custom Query** reports use the Backfill Date as the Start Date for retrieving all work items list.\ For example, Query: Select \[System.Id] From WorkItems WHERE \[System.ChangedDate] > 'BACKFILLDATE' - Date format (yyyy-MM-dd HH:mm:ss) In the subsequent runs, the last successful run is used as the System.ChangedDate Subsequent Query: Select \[System.Id] From WorkItems WHERE \[System.ChangedDate] > 'LAST SUCCESSFUL RUN EXECUTION END DATE' - Date format (yyyy-MM-dd HH:mm:ss) The above mentioned reports are supported only in the UPSERT mode. ## Other Panes For information about the remaining sections of the Connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Troubleshooting * Make sure your authentication remains valid. * Review the configuration to make sure that all required items have been selected. * Review the Connector history for error messages. * In rare cases, you may be requesting too much information and reaching API limitations or timeouts. If this is the case, you can review the history of the Connector run to see the error message and duration. If this is the case, you can reduce the number of accounts that are being pulled, choose a smaller number of metrics for the report that you are pulling, or reduce the timeframe that you are trying to pull. # Azure Data Lake Storage Gen2 Using AAD Connector Source: https://www.domo.com/docs/s/article/1500007660641 ## Intro Azure Data Lake Storage Gen2 is the one of the world's most productive Data Lake. It is an enterprise-wide hyper-scale repository for big data analytic workloads. It makes Azure Storage the foundation for building enterprise data lakes on Azure. It allows you to easily manage massive amounts of data and helps to speed up your transition from proof of concept to production. Use Domo's Microsoft Azure Data Lake Store Gen2 using AAD connector to pull data files from your Data Lake Store into Domo. You can retrieve data files in any of the following file types: CSV, TSV, and TXT. For more information about Azure's API, see [https://docs.microsoft.com/en-us/azu...ta-lake-store/](https://docs.microsoft.com/en-us/azure/data-lake-store/ "https://docs.microsoft.com/en-us/azure/data-lake-store/"). You connect to your Microsoft Azure Data Lake Store Gen2 AAD account in the Data Center. This topic discusses the fields and menus that are specific to the Microsoft Azure Data Lake Store Gen2 using AAD connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Prerequisites To connect to your Microsoft Azure Data Lake Store Gen2 AAD account and create a DataSet, you must have the following: * Your client ID (GUID) and secret key of the client web app obtained from Azure Active Directory configuration * Your Microsoft Azure Data Lake Storage account name * Your Tenant ID ### Configuring Your Azure App You must first create a Microsoft Azure Web App to obtain the necessary client ID and secret. **To configure an Azure App**: 1. Login into [Azure Portal](https://portal.azure.com/#home "https://portal.azure.com/#home"). 2. Select **Azure Active Directory > App Registrations > New Registration**. 3. Fill out the registration form as follows: * Name: Enter name for your application. * Supported account types: Select an option to specify who can use this application or access this API. * Redirect URI: Enter the redirect URI. The authentication response is sent to this URI after successfully authenticating the user. Providing the URI at this stage is optional and it can be changed later, but a value is required for most of the authentication scenarios. 4. Click **Register**. An overview of your registered App will appear. 5. The **Application ID** that appears here is the **Client ID** and the he **Directory ID** is the **Tenant ID** that you will enter in the **Credentials** pane in Domo. 6. Now, click on **Certificates and secrets**. Certificates can be used as secrets to prove the application's identity when requesting a token. Also, can be referred to as public keys. 7. Click **+New client secret**. 8. Specify the client secret description and the expiry period for your client secret, and click **Add**. 9. Copy the value and paste it into the **Client Secret** field in the **Connector credentials** section in Domo. ## Connecting to Your Microsoft Azure Data Lake Store Gen2 AAD Account This section enumerates the options in the Credentials and Details panes in the Microsoft Azure Data Lake Store Gen2 using AAD Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ### Credentials Pane This pane contains fields for entering credentials to connect to your Microsoft Azure Data Lake Store Gen2 AAD account. The following table describes what is needed for each field:

Field

Description

Azure Application Client ID Enter the client ID (GUID) of the client web app obtained from Azure Active Directory configuration. See "Prerequisites" for more information.
Azure Application Client Secret Enter the secret key of the client web app. See "Prerequisites" for more information.
Tenant ID Enter your Tenant ID. Go to Portal.azure.com \> Azure Active Directory > Properties. The Directory ID is your Tenant ID.
Account Name Enter your Microsoft Azure Data Lake storage account name.
Once you have entered valid Microsoft Azure Data Lake Store Gen2 AAD credentials, you can use the same account any time you go to create a new Microsoft Azure Data Lake Store Gen2 AAD DataSet. You can manage Connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054). ### Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

What file type would you like to import? Select the type of the file that you want to import.
Container Name Select the conatiner.
How would you like to choose the directory name? Select how would you like to choose the directory name.
Discover Directory Name Select the directory name.
Enter Directory Name

Enter the directory name using the following examples.

Example for main or root directory test
Example for sub directory test/test
Example for sub-sub-directory test/test/test
How would you like to choose the File name? Select how would you like to choose the file name.
Enter File Name Enter the file name.
Discover File Name Select the File name.
File Encoding Select the file encoding. By default, UTF-8 is selected.
Select the delimiting character Select the delimiting character used in your file. If your delimiter is not listed here, select 'Other.'
Specify your delimiter Enter the character used to delimit your character separated values (CSV) text.
Quote Character Select the desired quote character for parsing CSV files (Double quote is the default quote character for CSV standard.)
Custom Quote Character Enter the desired CSV Quote character.
Escape Character Select the desired escape character for parsing CSV files.
Custom Escape Character Enter the desired CSV escape character.
### Other Panes For information about the remaining sections of the Connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQs You need the client ID, client secret, and tenant ID of the client web app obtained from Azure Active Directory configuration, and your storage account name. To obtain the Client ID: * Login to the Azure Portal ([https://protal.azure.com](https://protal.azure.com)). * Navigate to Azure Active Directory >> App registrations. * Click on the Web App > Application ID. * The application ID is your client ID. To obtain the Secret key: * Login to the Azure Portal ([https://protal.azure.com](https://protal.azure.com)). * Navigate to Azure Active Directory >> App registrations. * Click on the Certificates and secrets > +New client secret. * Copy the secret value. Note that the secret is generated only once. To obtain the Tenant ID: * Login to the Azure Portal ([https://protal.azure.com](https://protal.azure.com)). * Navigate to Azure Active Directory >> Properties. * Copy the directory ID. The directory ID is your tenant ID. No As often as needed. Yes ## Troubleshooting * Make sure your authentication remains valid. * Review the configuration to make sure that all required items have been selected. * Review the Connector history for error messages. * In rare cases, you may be requesting too much information and reaching API limitations or timeouts. If this is the case, you can review the history of the Connector run to see the error message and duration. If this is the case, you can reduce the number of accounts that are being pulled, choose a smaller number of metrics for the report that you are pulling, or reduce the timeframe that you are trying to pull. # Snowflake OAuth Internal Unload V2 Connector Source: https://www.domo.com/docs/s/article/1500010196881 ## Intro The Domo Snowflake OAuth Internal Unload V2 connector makes it easy to bring your data from your Snowflake data warehouse into Domo securely via internal S3. Use this connector to unload data from your Snowflake database into internal Amazon S3. The files are then downloaded from internal S3 into Domo. To use this connector, you must have your Snowflake account name, and the client ID and client secret provided by Snowflake when the client is registered. Once your Snowflake data is in Domo, you can combine it with all your other Domo data to get a centralized view of your most mission-critical data. For more information about the Snowflake API, go to [https://docs.snowflake.net/manuals](https://docs.snowflake.net/manuals "https://docs.snowflake.net/manuals"). The Snowflake connector is a "Database" connector, meaning it retrieves data from a database using a query. In the Data Center, you can access the connector page for this and other Database connectors by clicking **Database** in the toolbar at the top of the window. This topic discusses the fields and menus that are specific to the Snowflake OAuth Internal Unload V2 connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ## Best Practices **Important:** Snowflake asserts your need to manually re-connect your Domo account every time the account expires. The Snowflake integration controls how often the account will expire. If it is set to expire the refresh tokens every 90 days, then you will need to reconnect the account every 90 days. If you would like to increase the refresh timeout to more than 90 days, then you will need to contact the **Snowflake Support**, and they can increase the maximum timeout from 90 days to 1 year. ## Prerequisites To connect to your Snowflake database account and create a DataSet, you must have the following: * The full name of your account (provided by Snowflake). This is the portion of your Snowflake URL immediately following https\://. Note that your full account name may include additional segments that identify the region and cloud platform where your account is hosted. The following table provides account name examples by cloud platform/region. For each row, it assumes your account name is "xy12345." Region.png * The Client ID and Client Secret provided by Snowflake when the client is registered. ## Connecting to Your Snowflake Account This section enumerates the options in the **Credentials** and **Details** panes in the Snowflake OAuth Internal Unload V2 Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Snowflake account. The following table describes what is needed for each field:

Field

Description

Account Name

Enter the account name for your Snowflake account. For information about finding your account name, see "Prerequisites."

Client ID

Enter your Client ID provided by Snowflake when the client is registered.

Client Secret

Enter your Client Secret provided by Snowflake when the client is registered.

Role Enter your role.
Once you have entered valid Snowflake credentials, you can use the same account any time you go to create a new Snowflake OAuth Internal Unload V2 DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

Query Type

Select the Query type.

Custom Query Enter the SQL query to execute.
Query Builder Select a table and fields to auto generate your query.

Warehouses Select the warehouse containing the data you want to retrieve. The list populates with all of the warehouses you have access to based on your credentials.
Databases Select the database containing the data you want to retrieve. The list populates with all of the databases you have access to based on your credentials.
Schemas Select the database schema containing the data you want to retrieve. The list populates with all of the schemas you have access to based on your credentials.
Database Objects Select the database object.
Tables Select the database table you want to retrieve. The list populates with all of the tables you have access to based on your credentials. If you do not select a database table, the connector retrieves your entire database schema.
Table Columns Select the table columns you want to retrieve. The list populates with all of the columns you have access to based on your credentials. If you do not select a table column, the connector retrieves your entire selected database table.
Table Query Helper This field shows the query that is generated based on the selected fields.
Views Select the view.
View Columns Select the view columns that you would like to include in your report.
Query Helper When you select warehouses, databases, schemas, tables, etc. from the above menus, a usable SQL query is built for you in this field. Copy and paste the SQL statement in this field into the Query field.
Fetch Size Enter a fetch size for memory performance. If this field is left blank, the default value 1000 will be used. If dataset throws an out of memory error, try decreasing the fetch size.
Query

Enter the SQL query to use to retrieve your data. You can use the Query Helper parameter to help you write a usable SQL query. To use the Query Helper , do the following:

  1. Select your desired warehouse, database, database schema, database table, and table columns in each menu.

  2. Copy the SQL statement that appears in the Query Helper field.

  3. Paste the copied SQL statement into the Query field.

Partition Support Select whether you want to partition your data.
Partition Criteria Select whether you want to partition your data by using date formats or a query.
Partition Query to determine partition tags Enter the partition query to determine the distinct partition tags. The column containing the Date data is your partition column. Example: Select Date from Table\_Name.
Partition Support Format Select the partition format.
Partition Column Name Enter the partition column name.
Past Years Enter the number of past years that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Future Years Enter the number of future years that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Past Months Enter the number of past months that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Future Months Enter the number of future months that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Past Days Enter the number of past days that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Date Format Select the required date format. By default yyyy-MM-dd will be used.
Custom Date Format Enter the custom date format.
### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### FAQs To avoid this error, you need to refresh the token. Snowflake asserts your need to manually re-connect your Domo account every time the account expires. The Snowflake integration controls how often the account will expire. If it is set to expire the refresh tokens every 90 days, then you will need to reconnect the account every 90 days. If you would like to increase the refresh timeout to more than 90 days, then you will need to contact the Snowflake Support, and they can increase the maximum timeout from 90 days to 1 year. You need the full name of your account, and the client ID and client secret provided by Snowflake when the client is registered. You may also provide your role. Limits depend on your server configuration. Datasets can run as often as every 15 minutes. However, depending on the runtime of the query, datasets may need to run less frequently. Make sure that all the words, table names and field names are correctly spelled. Refer to the Query Helper field for query help. Before you can connect to a Snowflake database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses](/docs/s/article/360043630093). The Snowflake OAuth Internal Unload V2 connector supports partitioning. It allows you to select whether you want to partition your data. You can also specify whether you want to partition your data by using date formats or a query. # Snowflake OAuth Writeback Connector Source: https://www.domo.com/docs/s/article/1500011338741 ## Intro The Snowflake OAuth Writeback Connector makes it easy to bring all your data into Domo and normalize it, then send it back to Snowflake while simultaneously making it available for queries. If you are already using Snowflake as a data warehousing solution, this connector helps you use Domo in conjunction with it to get the most from your data. To use this connector, you must have your Snowflake account name (domain), and the client id and client secret provided by Snowflake when the client is registered. For more information about the Snowflake API, go to [https://docs.snowflake.net/manuals](https://docs.snowflake.net/manuals). You connect to your Snowflake account in the Data Center. This topic discusses the fields and menus that are specific to the Snowflake OAuth Writeback connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). **Note:** The owner of a writeback dataset must also be an owner or co-owner of the input dataset. ## Best Practices **Important:** Snowflake asserts your need to manually re-connect your Domo account every time the account expires. The Snowflake integration controls how often the account will expire. If it is set to expire the refresh tokens every 90 days, then you will need to reconnect the account every 90 days. If you would like to increase the refresh timeout to more than 90 days, then you will need to contact the **Snowflake Support**, and they can increase the maximum timeout from 90 days to 1 year. ## Prerequisites To connect to your Snowflake database account and create a DataSet, you must have the following: * The full name of your account (provided by Snowflake). This is the portion of your Snowflake URL immediately following https\://. Note that your full account name may include additional segments that identify the region and cloud platform where your account is hosted. The following table provides account name examples by cloud platform/region. For each row, it assumes your account name is "xy12345." Region.png - The Client ID and Client Secret provided by Snowflake when the client is registered. **Important**: You will need the following permissions on Snowflake: * CREATE TABLE * COPY INTO * PUT * CREATE FILE FORMAT * REMOVE * LIST ## Configuring the connection This section enumerates the options in the **Credentials** and **Details** panes in the Snowflake OAuth Writeback Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ### Credentials Pane This pane contains fields for entering credentials to connect to your Snowflake account. The following table describes what is needed for each field:

Field

Description

Account Name

Enter the account name for your Snowflake account. For information about finding your account name, see "Prerequisites."

Client ID

Enter your Client ID provided by Snowflake when the client is registered.

Client Secret

Enter your Client Secret provided by Snowflake when the client is registered.

Role

Enter your role.

Once you have entered valid Snowflake credentials, you can use the same account any time you go to create a new Domo-Snowflake connection. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054). ### Details Pane This pane contains a number of fields for specifying your data and indicating where it's going.

Menu

Description

Input DataSet ID

Enter the DataSet ID (GUID) for the DataSet you want to copy to Snowflake. You can find the ID by opening the details view for the DataSet in the Data Center and looking at the portion of the URL following datasources/. For example, in the URL [https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview](https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview), the DataSet ID is 845305d8-da3d-4107-a9d6-13ef3f86d4a4.

Select Table Name

Select how you want to name the table where data will be copied. - Use Input DataSet GUID- The table name will be the number you entered for InputDataSet ID. - Enter Table Name- You will give the table a custom name in the Custom Table Name field.

Enter Table Name

Enter the name of the Snowflake table you want your data copied to (spaces and special characters will be replaced with underscores).

Warehouses

Select the warehouse containing the table you want to send data to.

Databases

Select the database containing the table you want to send data to.

Database Schema

Select the database schema containing the data you want to retrieve.

Use All Caps for Column Names and Table Name

Select 'True' if you want to write back your column names and table name in ALL CAPS so the names are case insensitive within Snowflake; otherwise, select 'False.'

My Domo Input DataSet is very large

Select this checkbox to export a very large DataSet from Domo to Snowflake. When this box is selected, the connector uses a different, faster process.

Client session keep alive heart beat

Select this checkbox to reduce the default client session keep alive heart beat frequency.

### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQs This connector allows you to write data from a Domo dataset to a Snowflake instance. The connector uses a user-defined app in Snowflake to support OAuth authentication. To avoid this error, you need to refresh the token. Snowflake asserts your need to manually re-connect your Domo account every time the account expires. The Snowflake integration controls how often the account will expire. If it is set to expire the refresh tokens every 90 days, then you will need to reconnect the account every 90 days. If you would like to increase the refresh timeout to more than 90 days, then you will need to contact the **Snowflake Support**, and they can increase the maximum timeout from 90 days to 1 year. You need the full name of your account, and the client ID and client secret provided by Snowflake when the client is registered. You may also provide your role. This depends on your server configuration. DataSets can run as often as every 15 minutes. However, depending on the runtime of the query, DataSets may need to run less frequently. Your Domo input dataset id is in the URL of the dataset you are exporting data from.\ Example: [https://customer.domo.com/datasources/\*\*aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee\*\*/details/settings](https://customer.domo.com/datasources/**aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee**/details/settings) Before you can connect to a Snowflake database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses in Domo](/docs/s/article/360043630093). # Microsoft Azure Data Factory Connector Source: https://www.domo.com/docs/s/article/360042928854 ## Intro Microsoft Azure Data Factory is a cloud-based data integration service that orchestrates and automates the movement and transformation of data. The Domo Azure Data Factory connector gives you access to data about activity and pipeline runs, datasets, operations, pipelines, and triggers. To learn more about the Data Factory API, visit their page ([https://docs.microsoft.com/en-us/azure/data-factory/](https://docs.microsoft.com/en-us/azure/data-factory/ "https://docs.microsoft.com/en-us/azure/data-factory/") ). You connect to your Data Factory account in the Data Center. This topic discusses the fields and menus that are specific to the Data Factory connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ## Prerequisites To connect to your Data Factory account and create a DataSet, you must have the following: * A Microsoft Azure Data Factory tenant ID * A Microsoft Azure Data Factory client ID * A Microsoft Azure Data Factory client secret To obtain credentials, please reach out to your Microsoft Azure Data Factory account representative. ## Connecting to Your Data Factory Account This section enumerates the options in the **Credentials** and **Details** panes in the Data Factory Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Data Factory account. The following table describes what is needed for each field:

Field

Description

Tenant ID

Enter your Microsoft Azure Data Factory tenant ID.

Client ID

Enter your Microsoft Azure Data Factory client ID.

Client Secret

Enter your Microsoft Azure Data Factory client secret.

Once you have entered valid Data Factory credentials, you can use the same account any time you go to create a new Data Factory DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

Report

Select the Data Factory report you want to run. The following reports are available:

Activity Runs

Returns a list of activity runs.

Datasets

Returns a list of datasets.

Factories

Returns a list of factories under subscription.

Factories by Resource Group

Returns a list of factories, broken down by resource group.

Integration Runtimes

Returns a list of integration runtimes.

Linked Services

Returns a list of linked services.

Operations

Returns a list of available Azure Data Factory API operations.

Pipeline Runs

Returns a list of pipeline runs.

Pipelines

Returns a list of pipelines.

Trigger Runs

Returns a list of trigger runs.

Triggers

Returns a list of triggers.

Subscription ID

Enter the ID of the subscription you want to return data for.

Resource Group Name

Enter the resource group name you want to return data for.

Factory Name

Select the factory you want to return data for.

Trigger Name

Select the trigger you want to return data for.

Run ID

Enter the run ID you want to return data for.

Date Type

Select whether you want to pull data for a specific date or a date range.

Date

Select whether the report data is for a specific date or for a relative number of days back from today.

Date Picker

Select the date for the report.

Date Offset

Enter the number of past days that should appear in the report.

Date From

Specify whether the first date in your date range is a specific or relative date. You select the last date in your range in Date To .

Date To

Specify whether the second date in your date range is a specific or relative date. You select the first date in your range in Date From .

Date From Picker

Select the first date in your date range.

Date To Picker

Select the second date in your date range.

Date From Offset

Enter the number of the farthest day back that should be represented in the report. Combine with Date To Offset to create a range of represented days.

For example, if you entered 10 for Date From Offset and 5 for Date To Offset , the report would contain data for 10 days ago up until 5 days ago.

Date To Offset

Enter the number of the most recent day back that should be represented in the report. Combine with Date From Offset to create a range of represented days.

For example, if you entered 10 for Date From Offset and 5 for Date To Offset , the report would contain data for 10 days ago up until 5 days ago.

### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). # Amazon Redshift SSH Connector Source: https://www.domo.com/docs/s/article/360042931614 ## Intro Amazon Redshift is a hosted data warehouse project that is part of the larger cloud computing platform Amazon Web Services. You can use Domo's Amazon Redshift SSH Connector to create a secure, encrypted connection with your Redshift database to bring your data into Domo and start making better decisions. Simply input your own SSH credentials and write a query to pull the data you need, and ready to go. For more information about the Redshift API, visit their website. ([http://docs.aws.amazon.com/redshift/...\_commands.html](http://docs.aws.amazon.com/redshift/latest/dg/c_SQL_commands.html "http://docs.aws.amazon.com/redshift/latest/dg/c_SQL_commands.html") ) The Amazon Redshift SSH connector is a "Database" connector, meaning it retrieves data from a database based on a query. In the Data Center, you can access the connector page for this and other Database connectors by clicking **Database** in the toolbar at the top of the window. You connect to your Redshift database in the Data Center. This topic discusses the fields and menus that are specific to the Redshift SSH connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). **Note:** Depending on your network's structure, you may need to whitelist any IP addresses necessary for the data connector to retrieve data. Contact your IT administrator for assistance. ## Prerequisites To connect to a Redshift database and create a DataSet, you must have the following: * The hostname of the UNIX server you are SSH-tunneling through * The SSH username and password for your UNIX account * The SSH port number * The SSH private key * The Redshift database hostname or IP address * The Redshift database name * The username and password you use to log into your Redshift database * The port number for the Redshift database * The Redshift database name CA certificate text or URL path is required *only* if you select **Certificate String** or **URL Path**, respectively, in the **Certificate Format** menu. **Note: Domo does not support the SSH keys generated using ssh-keygen. The SSH keys need to be the DES or RSA keys (in PEM format) generated by OpenSSL.** ### Creating a Redshift account To create a Redshift user account, contact your Redshift Database Administrator (DBA) and have them follow these directions: By default, only the master user that you created when you launched the cluster has access to the initial database in the cluster. To grant other users access, you must create one or more user accounts. Database user accounts are global across all the databases in a cluster; they do not belong to individual databases. Use the CREATE USER command to create a new database user. When you create a new user, you specify the name of the new user and a password. A password is required. It must have between 8 and 64 characters, and it must include at least one uppercase letter, one lowercase letter, and one numeral. For example, to create a user named GUEST with password ABCd4321, issue the following command: `create user guest password 'ABCd4321';` ### Whitelisting IP addresses Before you can connect to a Redshift database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses for Connectors](/docs/s/article/360043630093 "Whitelisting IP Addresses for Connectors"). ## Connecting to Your Redshift Database Using SSH This section enumerates the options in the **Credentials** and **Details** panes in the Redshift SSH Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector.](/docs/s/article/360042926274) ### Credentials Pane This pane contains fields for entering credentials to connect to your database. The following table describes what is needed for each field:

Field

Description

SSH Server Hostname

Enter the hostname of the UNIX server you are SSH-tunneling through.

SSH Username

Enter the username for your UNIX account.

SSH Password

Enter the password for your UNIX account.

SSH Port

Enter the port number used for SSH.

SSH Private Key

Enter the SSH private key.

Database Hostname

Enter the Redshift database hostname or URL.

Database Name

Enter the Redshift database name.

Database Username

Enter your username for the Redshift database.

Database Password

Enter your password for the Redshift database.

Database Port

Enter the Redshift database port number.

Certificate Format

Select the certificate format. If you do not want to include a certificate, select No Certificate . If you select Certificate String , you must paste the text for your certificate in the Certificate field. If you select URL Path , you must enter the URL where your certificate is located in the Certificate field.

Certificate

Paste the text for your CA certificate or enter the URL where your certificate is located. This is optional. If you do not want to include a certificate, select No Certificate in the Certificate Format menu.

Once you have entered valid Redshift credentials, you can use the same account any time you go to create a new Redshift SSH DataSet. You can manage connector accounts in the Accounts tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane In this pane you create an SQL query to pull data from your database. You can also choose a specific database table and columns and specify which columns you want to appear in your report.

Menu

Description

Query

Enter the Structured Query Language (SQL) query to use in selecting the data you want. For example:

select \* from Employee

Fetch Size

Enter the fetch size for memory performance. If you leave this blank, a default value of 1000 is used. If you get an "Out of Memory" error, decrease the fetch size.

Database Tables

Select the database table you want to appear in your report.

Table Columns

Select all table columns you want to appear in your report.

Query Helper

Based on the selected columns in the Table Columns field, the Query Helper builds a sample query for you. You can revise the query if desired.

Boolean Format

Select the Boolean format to be used. The following table describes the available formats:

1/0

True values return 1 , and false values return 0 .

t/f

True values return t , and false values return f .

T/F

True values return t , and false values return f .

true/false

True values return true , and false values return false .

Query Timeout

Enter the connector timeout value in minutes.

### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Troubleshooting If you run into connection issues... * Verify the connection works using pgAdmin. * Confirm all of the necessary Domo IPs have been whitelisted (see Whitelisting IP addresses, above). * Run a profile on the SQL query. # Amazon Redshift Unload V2 Connector Source: https://www.domo.com/docs/s/article/360042931634 ## Intro Amazon Redshift is a fast and powerful, fully managed, petabyte-scale data warehouse service in the cloud. Use Domo's Amazon Redshift Unload V2 connector to bring in larger results from Redshift through the assistance of your Amazon S3 service. You connect to your Amazon Redshift Unload account in the Data Center. This topic discusses the fields and menus that are specific to the Amazon Redshift Unload connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Prerequisites To connect to Amazon Redshift so you can begin creating Amazon Redshift Unload DataSets, you must have the following: * The host name for the Redshift database * The database name you created for the cluster * Your Redshift username and password * The port number you specified when you launched the cluster * Your AWS access key * Your AWS secret access key * The name of the S3 bucket data will be unloaded into * The name of the S3 bucket region CA certificate text or URL path is required **only** if you select ****Certificate string**** or ****URL path****, respectively, in the ****Certificate format**** menu. If you do not know any of the information for Redshift, contact your Amazon Redshift Database Administrator. If you have a firewall, ensure the port is open for you to use. To find your AWS Access Key and Secret Access Key: 1. Log in to your AWS Management Console. 2. Click on your username at the top right of the page. 3. Select ****Security Credentials**** in the dropdown menu. 4. In the ****Access Credentials**** section, copy the latest Access Key ID. 5. Click on the ****Show link**** in the same row, and copy the Secret Access Key. ### Whitelisting Before you can connect to Redshift, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses for Connectors](/docs/s/article/360043630093 "Whitelisting IP Addresses for Connectors"). ## Connecting to your Amazon Redshift Unload account This section enumerates the options in the **Credentials** and **Details** panes in the Amazon Redshift Unload V2 Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Amazon Redshift Unload account. The following table describes what is needed for each field:

Field

Description

JDBC Driver Version Select your Redshift JDBC driver.

Host

Enter the host name for the Redshift database you want to pull data from.

Port Enter the port number you specified when you launched the cluster.

Database

Enter the name of the database you created for the cluster.

Username

Enter the username for your Redshift account,

Password

Enter the password for your Redshift account.

Certificate Format

Select a certificate format. If you do not want to include a certificate, leave the default No certificate option selected. If you select Certificate string , you must paste the text for your certificate in the Certificate field. If you select URL path , you must enter the URL where your certificate is located in the Certificate field.

Certificate

Paste the text for your CA certificate or enter the URL where your certificate is located. This is optional. If you do not want to include a certificate, select No certificate in the Certificate Format menu.

Access Key

Enter your AWS access key. For information about obtaining an access key, see "Prerequisites," above.

Secret Access Key

Enter your AWS secret key. For information about obtaining an access key, see "Prerequisites," above.

S3 Bucket

Enter the name of the S3 bucket to use in pulling in data.

S3 Bucket Region

Select the region containing the desired S3 bucket.

Once you have entered valid credentials, you can use the same account any time you go to create a new Amazon Redshift Unload V2 DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane This pane contains various options for specifying the data you want to pull into Domo.

Menu

Description

Query Type

Select the desired query type. If you select Query , you will be prompted to enter a regular SQL query without a parameter. If you select Query Parameter , you will be prompted to enter a SQL query with a parameter.

Query

Enter the SQL query you want to use to pull in data.

For example:

select \* from Employee

You can use the Generated Query parameter to help you write a usable SQL query. To use the Generated Query , do the following:

  1. Select your database table and table columns in the appropriate menus.

  2. Copy the SQL statement that appears in the Generated Query field.

  3. Paste the copied SQL statement into the Query field.

Schema Names

Select the schemas you want to pull data from.

Database Tables

Select the database tables you want to pull into Domo.

Table Columns

Select the table columns you want to pull into Domo.

Generated Query (Optional)

Copy and paste the SQL statement in this field into the Query field. For more information, see Query , above.

### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQs As often as needed. This depends on your server configuration. Before you can connect to a Redshift database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses](/docs/s/article/360043630093 "Whitelisting IP Addresses for Connectors"). # Amazon Redshift Upsert Connector Source: https://www.domo.com/docs/s/article/360042931654 ## Intro Amazon Redshift is a hosted data warehouse project that is part of the larger cloud computing platform Amazon Web Services. Redshift handles analytics workloads on large scale DataSets stored by a column-oriented DBMS principle. With the Amazon Redshift Upsert Connector you have the ability to schedule your data using the merge (upsert) option. You connect to your Amazon Redshift Upsert Account in the Data Center. This topic discusses the fields and menus that are specific to the Amazon Redshift Upsert connector interface. General information for adding DataSets and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ## Prerequisites To connect to Amazon Redshift so you can begin creating Amazon Redshift Upsert DataSets, you must have the following: * JDBC Driver * The host name for the Redshift database * The database name for the Redshift database * Your Redshift username and password * The port number of your Redshift database * The format of your certificate. This must match what you enter in the Certificate field. * The text for your CA certificate or enter the URL where your certificate is located. By default, no certificate is required. ### Whitelisting Before you can connect to a Redshift database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses for Connectors](/docs/s/article/360043630093 "Whitelisting IP Addresses for Connectors"). ## Connecting To Your Amazon Redshift Upsert Account This section enumerates the options in the **Credentials** and **Details** panes in the Amazon Redshift Upsert Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Amazon Redshift Upsert account. The following table describes what is needed for each field:

Field

Description

JDBC Driver

Select the JDBC driver to use.

Host

Enter the host name for the SQL database. If you do not know the host name, contact your Amazon Redshift Database Administrator.

Database

Enter the name of the SQL database. If you do not know the database name, contact your Amazon Redshift Database Administrator.

Username

Enter your Redshift username. If you do not know your username, contact your Amazon Redshift Database Administrator.

Password

Enter your Redshift password. If you do not know your username, contact your Amazon Redshift Database Administrator.

Database Port

Enter the port number of your Redshift database. If you do not know the port number, contact your Amazon Redshift Database Administrator.

Certificate Format

Select a certificate format. This must match what you enter in the Certificate field. If you are not aware of a special certificate, select no certificate.

Certificate

Paste the text for your CA certificate or enter the URL where your certificate is located. By default, no certificate is required.

Once you have entered valid credentials, you can use the same account any time you go to create a new Amazon Redshift Upsert DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane This pane contains various options for specifying the data you want to pull into Domo
Menu Description
Query Type

Select a query type

Query: Regular SQL query without parameters.

Query Parameter: SQL query with parameters.

Query Enter the SQL query to use in selecting the data you want. For example, SELECT \* FROM Employee
Fetch Size Enter the fetch size for memory performance. If it is blank, the default value will be 1000. If it throws out of memory for a value, decrease fetch size.
Query Parameter Enter the query parameter value. It is the initial value for query parameter. The last run date is optional and by default is '02/01/1700' if it is not provided. For example, `!{lastvalue:_id}!=1,!{lastrundate:start_date}!=02/01/1944`
Validate Type

Select the validation type

No Validation: It will not do any validation.

Validate Schema: It will validate the previous schema with current schema, and it will fail the job run if the schema is not the same.

Validate By

Select the validation cases

Column Case Sensitive: If previous and current column names are the same but it is different by case sensitivity, it will not consider them as the same column name.

Column by Order: If previous columns and current columns are not in the same order, it will not consider them as the same column name.

Boolean Format

Select the boolean format for the data to return

1 = true, 0 = false: It will return 1 for true, otherwise 0 for all the boolean data column.

t = true, f = false: It will return t for true, otherwise f for all the boolean data column.

T = true, F = false: It will return T for true, otherwise F for all the boolean data column.

true = true, false = false: It will return true for true, otherwise false for the boolean data column.

Timeout Query (Optional) Enter the desired query timeout value.
### Scheduling The unique scheduling feature of this connector is the ability to merge (upsert) your data. This method will replace all updated rows, while any new rows will be appended. Merge Gif.gif To be able to Merge your updated data correctly, you must identify a Merge Key in your data. A Merge Key can be your primary key or a combination of columns that is unique in the DataSet and will be used to compare rows between different versions of your DataSet. You can use a CONCAT() function in the SELECT statement to establish a complex Merge Key. If you are unsure where the Merge Key is for this DataSet, please consult the DBA who owns the database or your Domo Administrator. ### Other Panes For information about the remaining sections of the connector interface, including how to configure standard scheduling options, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). # Azure Synapse SQL Connector Source: https://www.domo.com/docs/s/article/360042931674 All Azure SQL Data Warehouse datasets will continue to run as normal. The functionality of the connector has not been changed. Customers using or planning to use the connector will notice the following: 1. There is a new icon for the connector in the Appstore. Existing datasets will now show up on the Data Center with the new icon. 2. Customers who are trying to search for an Azure Data Warehouse dataset in the Data Center using a 'Type' filter will now need to search for datasets of type 'Azure Synapse SQL' instead of 'Azure Data Warehouse'. 3. Customers who want to create a new Azure SQL Data Warehouse will need to search the Appstore for the 'Azure Synapse SQL Connector' instead of the 'Azure SQL Data Warehouse Connector.' 4. Connector Accounts for the Azure SQL Data Warehouse Connector will now be called 'Azure Synapse SQL' Accounts. ## Intro Azure Synapse SQL lets you quickly implement a high-performance, globally available, and secure cloud data warehouse. Use Domo's Azure Synapse SQL Connector to bring your Azure data into Domo. You connect to your Azure Synapse SQL database in the Data Center. This topic discusses the fields and menus that are specific to the Azure Synapse SQL Connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Prerequisites To connect to an Azure Synapse SQL database and create a DataSet, you must have the following: * The username and password you use to log into your Azure Synapse database. * The server name for the database. You can find this by doing the following: 1. Log into Azure Portal. 2. Click on **Azure Synapse Analytics**. 3. Click on the Synapse SQL Pool you want to connect to. 4. Locate the full server name. Example **[yourserver.database.windows.net](http://yourserver.database.windows.net)** * The port number for the database * The database name Before you can connect to an Azure Synapse SQL database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses for Connectors](/docs/s/article/360043630093 "Whitelisting IP Addresses for Connectors"). ## Connecting to Your Azure SQL Database This section enumerates the options in the **Credentials** and **Details** panes in the Azure Synapse SQL Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Azure Synapse SQL database. The following table describes what is needed for each field:

Field

Description

JDBC Driver

Select the JDBC driver you want to use from the drop-down list.

Server Name

Enter the name of your server. For information about finding the server name, see "Prerequisites," above.

Database Name

Enter the name of the Azure Synapse database.

Port

Enter the port number for the Azure Synapse database.

Username

Enter the username you use to log into your Azure Synapse database.

Password

Enter the password you use to log into your Azure Synapse database.

Hostname in Certificate

Enter the h ostname in certificate obtained from the show database connection strings.

Once you have entered valid credentials, you can use the same account any time you go to create a new Azure Synapse SQL DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Manage Connector Accounts](https://domo-support.domo.com/s/article/360042926054?language=en_US "Manage Connector Accounts"). ### Details Pane In this pane you create an SQL query to pull data from your database. The **Query** parameter is required. The other three parameters are here to help you construct this query, if you choose.

Menu

Description

Query Type (Mandatory)

Query Type Description
Custom Query Enter the query to execute.
Query Builder Select a table and fields to autogenerate your query.

Query (Mandatory)

Enter the Structured Query Language (SQL) query to use in selecting the data you want. For example:

select \* from Employee

If you want help in constructing your query, copy and paste the automatically-generated query from the Query Helper field into this field.

Database Tables (Mandatory)

Select the table containing the data you want to pull into Domo. The selected table will be added to the automatically generated query in the Query Helper field.

Table Columns (Mandatory)

Select the table columns with data you want to pull into Domo. The selected columns will be added to the automatically generated query in the Query Helper field.

Query Helper (Mandatory)

Copy and paste this query into the Query field if you need in help building a query. This query is automatically generated when you select a table and columns in the Database Table and Table Columns fields, respectively.

Limit Buffer Size

Select the checkbox if you want to limit the maximum heap memory used by ResultBuffer.

Convert BIGINT to LONG

Select this check box if you want to convert the BIGINT columns to LONG.

### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). # Snowflake Connector Source: https://www.domo.com/docs/s/article/360042931814 **Note:** **Snowflake will no longer support the username and password authentication mechanism as of November 2025. As a result, this connector will be retired in November 2025 and will no longer function. Please consider using one of the following connection methods instead:** * [Cloud Integrations](/docs/s/article/4402322966807) * [Snowflake Enterprise OAuth Connector](/docs/s/article/000005534) * [Snowflake Key Pair Authentication Connector](/docs/s/article/360042931854) * [Snowflake OAuth Connector](/docs/s/article/360061552054) ## Snowflake Connector Migration Walkthrough As Snowflake is discontinuing username and password authentication, Snowflake connectors using this authentication method will be migrated to the OAuth version. This section helps users walk through the complete process of migrating their existing username and password Snowflake datasets to utilize the OAuth authentication version. Pls refer to the migration video ([https://youtu.be/rlG\_uNZwl\_U](https://youtu.be/rlG_uNZwl_U)) to make the transition smoother and minimize disruptions. ## Intro Snowflake is data warehouse that makes it easy to bring together all your data and make it available to all of the users and systems that need to analyze it. You can use Domo's Snowflake connector to retrieve data from a specified warehouse, database, and database schema by inputting an SQL query. For more information about the Snowflake API, go to [https://docs.snowflake.net/manuals](https://docs.snowflake.net/manuals). The Snowflake connector is a "Database" connector, meaning it retrieves data from a database using a query. In the Data Center, you can access the connector page for this and other Database connectors by clicking **Database** in the toolbar at the top of the window. This topic discusses the fields and menus that are specific to the Snowflake connector user interface. For general information about adding DataSets, setting update schedules, and editing DataSet information, see [Adding a DataSet Using a Connector](/docs/s/article/360042926274). ## Prerequisites To connect to a Snowflake database and create a DataSet, you must have the following: * The full name of your account (provided by Snowflake). This is the portion of your Snowflake URL immediately following https\://. Note that your full account name may include additional segments that identify the region and cloud platform where your account is hosted. The following table provides account name examples by cloud platform/region. For each row, it assumes your account name is "xy12345." snowflake_account_names.png * The username and password for your Snowflake account. ## Connecting to Your Snowflake Account This section enumerates the options in the **Credentials** and **Details** panes in the Snowflake Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Connector](/docs/s/article/360042926274). ### Credentials Pane This pane contains fields for entering credentials to connect to your Snowflake account. The following table describes what is needed for each field:

Field

Description

Account Name

Enter the name of your account (provided by Snowflake). For US West Region account\_name, and All other regions account\_name.region\_id.

Host

Enter the Host name (provided by Snowflake). For example, snowflakecomputing.com, snowflakecomputing.cn

Username

Enter the username associated with your Snowflake account.

Password

Enter the password associated with your Snowflake account.

Role

Enter your role.

After you have entered valid Snowflake credentials, you can use the same account in Domo any time you create a Snowflake DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Manage Connector/Adapter Accounts](/docs/s/article/360042926054). ### Details Pane This pane contains a number of fields and menus for entering your SQL query and specifying the location of the data you want to retrieve.

Parameter

Description

Query Type

Select the query type.

Enter Query

It enables an option to enter the user defined query.

Query History

It will fetch the data from the Snowflake query history for the last 70 days using the predefined query.

Table Information

It will fetch the metadata information about the objects created in your account.

Warehouse Metering History

It will fetch the warehouse usage and metering information for the last 70 days.

Query

Enter the SQL query to use to retrieve your data. You can use the Query Helper parameter to help you write a usable SQL query. To use the Query Helper, do the following:

  1. Select your desired warehouse, database, database schema, database table, and table columns in each menu.

  2. Copy the SQL statement that appears in the Query Helper field.

  3. Paste the copied SQL statement into the Query field.

Warehouses

Select the warehouse containing the data you want to retrieve. The list populates with all of the warehouses you have access to based on your credentials.

Databases

Select the database containing the data you want to retrieve. The list populates with all of the databases you have access to based on your credentials.

Database Schema

Select the database schema containing the data you want to retrieve. The list populates with all of the schemas you have access to based on your credentials.

Database Objects

Select the database object from the drop-down list.

Database Tables (Optional)

Select the database table you want to retrieve. The list populates with all of the tables you have access to based on your credentials. If you do not select a database table, the connector retrieves your entire database schema.

Table Columns (Optional)

Select the table columns you want to retrieve. The list populates with all of the columns you have access to based on your credentials. If you do not select a table column, the connector retrieves your entire selected database table.

Query Helper (Optional)

When you select warehouses, databases, schemas, tables, etc. from the above menus, a usable SQL query is built for you in this field. Copy and paste the SQL statement in this field into the Query field. For more information, see the entry for Query, above.

Database Views

Select the database view.

View Columns

Select which view columns you want to include in your report.

Fetch Size (Optional)

Enter a fetch size for memory performance. If this field is left blank, the default value of 1000 will be used. If the DataSet throws an "Out of memory" error, try decreasing the fetch size.

Convert BIGINT to LONG

Select this checkbox if you want to convert BIGINT columns to LONG.

Disable NetWork Timeout

Select this checkbox if you observe errors regarding network timeout.

Query Tag

This is an optional parameter that can be used to tag connector SQL executions in Snowflake as a Query Tag.

Convert Columns to String

Enter the column names separated by comma to convert the columns to string. For example, column1, column2, column3.

### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](/docs/s/article/360042926274). ## FAQs This connector allows you to import your data into Domo from Snowflake using Snowflake's JDBC drivers. Use this connector with a Snowflake Account Name, local username, and password to ingest small to large datasets from Snowflake. You need the CREATE TABLE, COPY INTO, PUT, CREATE FILE FORMAT, REMOVE, and LIST permissions on Snowflake. You need the account name (provided by Snowflake), your Snowflake username, and private key. If you are creating an encrypted private key then you will need a passphrase used to encrypt the private key file. You can also provide your role name. Yes Your Domo input dataset ID is in the URL of the dataset you are exporting data from. For example: `https://customer.domo.com/datasources/aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee/details/settings` This depends on your server configuration. DataSets can run as often as every 15 minutes. However, depending on the runtime of the query, DataSets may need to run less frequently. Make sure that all the words, table names, and field names are correctly spelled. Refer to the Query Helper field for query help. Before you can connect to a Snowflake database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses for Connectors & Federated Adapters.](/docs/s/article/360043630093 "Whitelisting IP Addresses for Connectors & Federated Adapters.") Yes. This connector is designed for all-sized DataSets. You only see content that you have access to based on the user role entered for your account in Snowflake. If you aren't seeing something you are expecting, make sure that role has access to that warehouse, database, and table. etc. If you do not enter a role in Snowflake, the SYSADMIN role is used by default. This connector uses Snowflake's built-in OAuth service. To get a client id and secret to use with this connector, you will need to create a security integration in Snowflake as described here: [https://docs.snowflake.com/en/user-guide/oauth-custom](https://docs.snowflake.com/en/user-guide/oauth-custom "https://docs.snowflake.com/en/user-guide/oauth-custom"). When creating the integration, use the following for the OAUTH\_REDIRECT\_URI: [https://oauth.domo.com/api/data/v1/oauth/providers/snowflake-oauth/exchange](https://oauth.domo.com/api/data/v1/oauth/providers/snowflake-oauth/exchange "https://oauth.domo.com/api/data/v1/oauth/providers/snowflake-oauth/exchange"). Yes, this connector requires each user who powers up the connector to provide the client id and secret. An alternative to this connector is the [Snowflake Enterprise OAuth Connector](https://domo-support.domo.com/s/article/000005534?language=en_US "Snowflake Enterprise OAuth Connector"). This connector enables Major Domos to save a client id and secret pair, which users can reference when powering this connector. # Snowflake Unload V2 Connector Source: https://www.domo.com/docs/s/article/360042931834 **Note:** Snowflake will no longer support the username and password authentication mechanism as of November 2025. As a result, this connector will be retired in November 2025 and will no longer function. Please consider using one of the following connection methods instead: * [Cloud Integrations](/docs/s/article/4402322966807) * [Snowflake Key Pair Unload v2](https://domo.lightning.force.com/s/article/1500000555201) * [Snowflake OAuth Unload v2](https://domo.lightning.force.com/s/article/000005841) ## Snowflake Connector Migration Walkthrough As Snowflake is discontinuing username and password authentication, Snowflake connectors using this authentication method will be migrated to the OAuth version. This section helps users walk through the complete process of migrating their existing username and password Snowflake datasets to utilise the OAuth authentication version. Pls refer to the migration video ([https://youtu.be/rlG\_uNZwl\_U](https://youtu.be/rlG_uNZwl_U)) to make the transition smoother and minimise disruptions. ## Intro Snowflake is a data warehouse built for the cloud for all your data and users. Use Domo's Snowflake Unload V2 Connector to unload data from your Snowflake into Amazon S3. Unloaded files are imported from Amazon S3 into Domo. Choose this connector instead of the Snowflake connector if you are executing very large queries. To learn more about the Snowflake API, visit their page ([https://docs.snowflake.net/manuals](https://docs.snowflake.net/manuals)). This Connector is the same as the standard [Snowflake Unload](/docs/s/article/360043436313) connector, except that it allows you to enter your own custom query in addition to using the auto-generate option, whereas the standard version of the connector only includes the auto-generate option. You connect to your Snowflake account in the Data Center. This topic discusses the fields and menus that are specific to the Snowflake Unload V2 connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Prerequisites To connect to your Snowflake account and create a DataSet, you must have the following: * The full name of your account (provided by Snowflake). This is the portion of your Snowflake URL immediately following https\://. Note that your full account name may include additional segments that identify the region and cloud platform where your account is hosted. The following table provides account name examples by cloud platform/region. For each row, it assumes your account name is "xy12345." snowflake_account_names.png * The username and password used to connect to your Snowflake host. * Your AWS access key. This is available in the AWS Console in the **Security Credentials** section (unless you are using IAM, in which case it is under **Users**). * Your AWS secret key. This was provided when you created your access key. You can generate a new key in the AWS Console. * The name of the AWS S3 bucket in which Snowflake data will be unloaded. * The following Permissions are required:

Permission Field

Description

Create Stage

Creates a new stage to unload data from tables into files.

Copy into \

Command to unload all the rows from a table into one or more files into the stage.

Create file format

Create file format.

LIST

Returns a list of files that have been staged.

GET

Downloads data files from the above created Snowflake stage.

REMOVE

Removes files that have been staged - unloaded from a table.

## Connecting to your Snowflake account This section enumerates the options in the **Credentials** and **Details** panes in the Snowflake Unload V2 Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ### Credentials pane This pane contains fields for entering credentials to connect to your Snowflake account. The following table describes what is needed for each field:

Field

Description

Account Name

Enter your Snowflake account name. For more information, see "Prerequisites."

Username

Enter the username you use to connect to your Snowflake host.

Password

Enter the password you use to connect to your Snowflake host.

Access Key

Enter your AWS access key. For information about obtaining an access key, see "Prerequisites," above.

Secret Key

Enter your AWS secret key. For information about obtaining a secret key, see "Prerequisites," above.

Bucket

Enter the name of the AWS S3 bucket.

Region

Select your S3 bucket region.

Role

Enter your role.

Once you have entered valid Snowflake credentials, you can use the same account any time you go to create a new Snowflake Unload V2 DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054). ### Details Pane In this pane you create an SQL query to pull data from your database. You can choose a specific database table and partition column. You can also specify the number of past days you want to get data for.

Menu

Description

How would you like to import data into Domo?

Select whether you want to import your data by using the standard update method (replace/append), by using partition, or upsert mode.

How would you like to build your Query?

Query Type

Description

Custom Query

Enter the SQL query to execute.

Query Builder

Select a table and fields to autogenerate your query.

Warehouses

Select the warehouse containing the data you want to retrieve. The list populates all warehouses you have access to based on your credentials.

Databases

Select the database containing the data you want to retrieve. The list populates all databases you have access to based on your credentials.

Schemas

Select the database schema containing the data you want to retrieve. The list populates all schemas you have access to based on your credentials.

Tables

Select the database table you want to retrieve. The list populates all tables you have access to based on your credentials. If you do not select a database table, the connector retrieves your entire database schema.

Table Column Name

Select the partition column name.

Table Query Helper

A query is generated based on the selected fields. Copy and paste this text into the QUERY field. You may edit this query, if desired.

Query

Enter the SQL query you want to execute.

Partition Criteria

Select whether you want to partition your data using the date keys, non-date keys, or meta query.

Select Partition Date Key Column Name

Select the partition column name. Only date fields will be shown in this discovery.

Past Days

Enter the number of past days that you want to get data for. Value can be X, where X is a positive integer. Example: 30.

Date Format

Please select/enter proper date format according to the date format present in partition column. By default yyyy-MM-dd will be used.

Custom Date Format

Enter the custom date format.

Select Partition Non Date Key Column Name

Select a non-date key column name to partition the data. All fields excluding Date fields will appear in this dropdown.

Enter Partition Non Date Key Column Name

Enter a non-date key column name to partition the data.

Partition Query to determine partition tags

Enter the partition meta query to determine the distinct partition tags (or keys). The column containing the Date data is your partition column.

Example: SELECT DISTINCT (DATE\_COLUMN\_NAME) FROM TABLENAME

Upsert Key Column(s)

Enter upsert key column name or a comma separated list of upsert key column names. Required only when Update method is Merge.

### Selecting the Update Mode Once you decide how you want to import your data into Domo (by using the standard update method (replace/append), by using partition, or upsert mode), you need to select the relevant update mode in the **Scheduling section** in the Connector. * If you select 'Partition' in the Details section, then you need to select the 'Append' update mode in the Scheduling section. Partition-Append.png * If you select 'Upsert' in the Details section, then you need to select 'Merge' update mode in the Scheduling section. Upsert-Merge.png ### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQs This connector allows you to enter your own custom query in addition to using the auto-generate option, whereas the standard version of the connector only includes the auto-generate option. Additionally, with this Connector, you can import your data by using the standard update mode (replace/append), by using partition, or upsert mode. This depends on your server configuration. DataSets can run as often as every 15 minutes. However, depending on the runtime of the query, DataSets may need to run less frequently. Make sure that all the words, table names, and field names are correctly spelled. Refer to the Query Helper field for query help. Before you can connect to a Snowflake database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses in Domo](/docs/s/article/360043439173). # Snowflake Key Pair Authentication Connector Source: https://www.domo.com/docs/s/article/360042931854 ## Intro Snowflake is data warehouse software that makes it easy to bring together all your data and make it available to all of the users and systems that need to analyze it. You can use Domo's Snowflake Using Key Pair Authentication connector to retrieve data from a specified warehouse, database, and database schema by inputting an SQL query. For more information about the Snowflake API, go to [https://docs.snowflake.net/manuals](https://docs.snowflake.net/manuals "https://docs.snowflake.net/manuals"). This version of the Snowflake connector is essentially the same as the standard [Snowflake connector](/docs/s/article/360042931814 "Snowflake Connector") except that it supports using key pair authentication rather than the typical username/password authentication. This authentication method requires a 2048-bit (minimum) RSA key pair. You can generate the public-private key pair using OpenSSL. Steps for generating the key pair are provided below. The public key is assigned to the Snowflake user who will use the Snowflake client. The Snowflake Using Key Pair Authentication connector is a "Database" connector, meaning it retrieves data from a database using a query. In the Data Center, you can access the connector page for this and other Database connectors by clicking **Database** in the toolbar at the top of the window. This topic discusses the fields and menus that are specific to the Snowflake Using Key Pair Authentication connector user interface. For general information about adding DataSets, setting update schedules, and editing DataSet information, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ## Prerequisites To connect to a Snowflake database and create a DataSet, you must have the following: * The full name of your account (provided by Snowflake). This is the portion of your Snowflake URL immediately following ` https://`. Note that your full account name may include additional segments that identify the region and cloud platform where your account is hosted. The following table provides account name examples by cloud platform/region. For each row, it assumes your account name is "xy12345." snowflake_account_names.png * The username used to connect to your Snowflake host * Your Snowflake private key * The passphrase used to encrypt the private key file, if you created an encrypted key ### Configure the Public/Private Key Pair Follow these steps to configure a public/private key pair. #### Generate a Private Key 1. Open a terminal window. 2. Generate a private key. You can create either an unencrypted or encrypted private key. * **For Unencrypted private key, use the following command:** ```bash theme={"dark"} openssl genrsa 2048 | openssl pkcs8 -topk8 -inform PEM -out rsa_key.p8 -nocrypt ``` * **For Encrypted private key, use the following command:** ```bash theme={"dark"} openssl genrsa 2048 | openssl pkcs8 -topk8 -v2 des3 -inform PEM -out rsa_key.p8 ``` The commands generate a private key in PEM format: ``` -----BEGIN ENCRYPTED PRIVATE KEY----- MIIE6T... -----END ENCRYPTED PRIVATE KEY----- ``` #### Generate a Public Key Generate the public key from the command line by referencing the private key. This example assumes the private key is encrypted and stored in the file `rsa_key.p8`. Generate a public key from the private key: ```bash theme={"dark"} openssl rsa -in rsa_key.p8 -pubout -out rsa_key.pub ``` The command generates the public key in PEM format: ``` -----BEGIN PUBLIC KEY----- MIIBIj... -----END PUBLIC KEY----- ``` #### Store the Keys Securely * Store the private and public key files in a secure local directory. * Record the file paths for future reference. * The private key uses the PKCS#8 (Public Key Cryptography Standards) format and is encrypted with the specified passphrase. #### Assign the Public Key to a Snowflake User Use the [ALTER USER](https://docs.snowflake.com/en/sql-reference/sql/alter-user) command to assign the public key to the user by setting the RSA\_PUBLIC\_KEY property. For example: `ALTER USER example_user SET RSA_PUBLIC_KEY='MIIBIjANBgkqh...';` #### Verify the Public Key Fingerprint 1. Run the following command to retrieve the users public key fingerprint, and then copy the output. ```bash theme={"dark"} DESC USER example_user ->> SELECT SUBSTR( (SELECT "value" FROM $1 WHERE "property" = 'RSA_PUBLIC_KEY_FP'), LEN('SHA256:') + 1) AS key; ``` 2. Run the following command on the command line and copy the output. ```bash theme={"dark"} openssl rsa -pubin -in rsa_key.pub -outform DER | openssl dgst -sha256 -binary | openssl enc -base64 ``` 3. Compare both outputs. If the values match, the configuration is correct. #### Key Rotation Snowflake supports multiple active keys to allow for uninterrupted rotation. Rotate and replace your public and private keys based on the expiration schedule you follow internally. Currently, you can use the RSA\_PUBLIC\_KEY and RSA\_PUBLIC\_KEY\_2 parameters for ALTER USER to associate up to 2 public keys with a single user. To rotate your keys, 1. Complete the steps in Using Key Pair Authentication to... * Generate a new private and public key set. * Assign the public key to the user. Set the public key value to either RSA\_PUBLIC\_KEY or RSA\_PUBLIC\_KEY\_2 (whichever key value is not currently in use). For example: `alter user jsmith set rsa_public_key_2='JERUEHtcve...';` 2. Update the code to connect to Snowflake. Specify the new private key. Snowflake verifies the correct active public key for authentication based on the private key submitted with your connection information. 3. Remove the old public key from the user profile. For example: `alter user jsmith unset rsa_public_key;` ## Connecting to your Snowflake account This section enumerates the options in the **Credentials** and **Details** panes in the Snowflake Using Key Pair Authentication Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Snowflake account. The following table describes what is needed for each field:

Field

Description

Account Identifier

Enter the account name for your Snowflake account. For information about finding your account name, see Prerequisites . For US West Region, it should be account\_name and for all other regions, use account\_name.region\_id.

Username

Enter the username associated with your Snowflake account.

Private Key

Enter your private key. For more information about generating your private key, see Configuring the public/private key pair .

Passphrase Enter the passphrase used to encrypt the private key file, if you created an encrypted key.
Role Enter your user role.
After you have entered valid Snowflake credentials, you can use the same account in Domo any time you create a Snowflake Using Key Pair Authentication DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane This pane contains a number of fields and menus for entering your SQL query and specifying the location of the data you want to retrieve.

Parameter

Description

Query

Enter the SQL query to use to retrieve your data. You can use the Query Helper parameter to help you write a usable SQL query. To use the Query Helper , do the following:

  1. Select your desired warehouse, database, database schema, database table, and table columns in each menu.

  2. Copy the SQL statement that appears in the Query Helper field.

  3. Paste the copied SQL statement into the Query field.

Warehouses

Select the warehouse containing the data you want to retrieve. The list populates with all of the warehouses you have access to based on your credentials.

Databases

Select the database containing the data you want to retrieve. The list populates with all of the databases you have access to based on your credentials.

Database Schema

Select the database schema containing the data you want to retrieve. The list populates with all of the schemas you have access to based on your credentials.

Database Tables (Optional)

Select the database table you want to retrieve. The list populates with all of the tables you have access to based on your credentials. If you do not select a database table, the connector retrieves your entire database schema.

Table Columns (Optional)

Select the table columns you want to retrieve. The list populates with all of the columns you have access to based on your credentials. If you do not select a table column, the connector retrieves your entire selected database table.

Query Helper (Optional)

When you select warehouses, databases, schemas, tables, etc. from the above menus, a usable SQL query is built for you in this field. Copy and paste the SQL statement in this field into the Query field. For more information, see Query , above.

Fetch Size (Optional) Enter a fetch size for memory performance. If this field is left blank, the default value of 1000 will be used. If the DataSet throws an "Out of memory" error, try decreasing the fetch size.
Convert Null Values to empty string Selecting this would change all the null values from the source table in Snowflake to empty strings in Domo
Convert Timezone Selecting a timezone here tells the connector about the timezone of the source data. The connector converts the Timestamp values from the selected timezone to UTC using this information.
### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQs This depends on your server configuration. As often as needed. Make sure that all the words, table names, and field names are correctly spelled. Refer to the Query Helper field for query help. Before you can connect to a Snowflake database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses for Connectors](/docs/s/article/360043630093 "Whitelisting IP Addresses in Domo"). This connector is designed for small/medium DataSets and proof of concept work for large DataSets. You only see content that that you have access to based on the user role entered for your account in Snowflake. If you aren't seeing something you are expecting, make sure that role has access to that warehouse, database, table. etc. If you do not enter a role in Snowflake, the SYSADMIN role is used by default. # System Requirements Source: https://www.domo.com/docs/s/article/360043427193 ## Intro Domo requires a certain version of various systems to operate. Learn about each below.

Domo Version

Requirements

Web

You must have a web browser to use Domo on a desktop or laptop computer.

Domo supports the two most recent non-beta versions of the following browsers:

  • Google Chrome
  • Mozilla Firefox
  • Microsoft Chromium Edge (Old Edge version 44 is not supported)
  • Safari (Mac)

\* Recommended

The following items must also be enabled for your browser:

  • JavaScript
  • Popups
  • Cookies

iOS

For security purposes, Domo supports devices running on the latest iOS (iOS 14).

After a new iOS version comes out, we support the new version and the previous version for 6–12 months.

Android

Domo currently supports all devices running the latest Android or Android 10 and later.

# Google Ads via Google BigQuery Service Connector Source: https://www.domo.com/docs/s/article/360043431253 ****Important**** ****:**** Due to Google's change in allowing Domo connectors to use OAuth authentication, all users must now use service account key authentication to create new data connections. To create new Google AdWords via Google BigQuery DataSets, use this connector. All pre-existing AdWords via BigQuery DataSets will continue to run normally. ## Intro Google Ads (formerly Google AdWords) is an online advertising service. Use Domo's Google Ads via BigQuery Service connector to transfer and pull data from a specific project into Domo. To successfully configure this connector, you must first configure a Google BigQuery script within your Google Ads account. The steps for doing this are provided later in this article. For more information about the Google Ads API, see [https://developers.google.com/adword...s/guides/start](https://developers.google.com/adwords/api/docs/guides/start "https://developers.google.com/adwords/api/docs/guides/start"). This topic discusses the fields and menus that are specific to the Google Ads via Google BigQuery Service connector user interface. For general information about adding DataSets, setting update schedules, and editing DataSet information, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ## Prerequisites To connect to a BigQuery service account, you must have a Google BigQuery service account JSON key. To generate a key, do the following: 1. In the GCP Console, open the **IAM & Admin** page. 2. Click ****Service accounts**** in the left-hand navigation pane. 3. Select your project and click ****Open****. 4. Click ****Create Service Account****. 5. Enter a name and description for the service account. 6. Click ****Create****. **Note:** You may need the “BigQuery Admin” role in the service account permissions dialog. Please consult with your Google administrator for additional guidance. 7. Select ****Project Owner****. 8. Click ****Continue****. 9. Click ****Create key****. 10. Select ****JSON**** as the key type. 11. Click ****Create****. A private key will be saved to your computer. ## Connecting to Google Ads via Google BigQuery This section enumerates the options in the **Credentials** and **Details** panes in the Google Ads via Google BigQuery Service Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to Google Ads via BigQuery. The following table describes what is needed for each field:

Field

Description

Service Account Key JSON

Copy and paste the JSON for your BigQuery service account key. For information about creating a key, see "Prerequisites," above.

Once you have entered a valid key, you can use the same account any time you go to create a new Google Ads via BigQuery Service DataSet. You can manage connector accounts in the ****Accounts**** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane This pane contains a number of fields and menus you can use to configure your report.

Menu

Description

Project ID

Enter the name of the specific project you want to add your DataSet to. You can find this in your Google Cloud Console in the project info.

DataSet ID

Enter a name for your DataSet. You can choose any name you want.

Report

Select the AdWords report type to run. The following reports are available:

Account Performance

Returns all statistics aggregated by default at the account level.

Ad Customizers Feed Item Provides statistics for feed items used in Ad Customizers. Statistics are aggregated at the feed item level.

Ad Performance

Returns all statistics aggregated at the ad level.

Ad Group Performance

Returns all statistics aggregated by default at the ad group level.

Age Range Performance Returns all Display Network and YouTube Network statistics aggregated by age range.
Audience Performance Returns performance data from interests and remarketing lists for Display Network and YouTube Network ads, and remarketing lists for search ads (RLSA), aggregated at the audience level.
Automatic Placements Performance Returns all statistics aggregated at the placement level.
Bid Goal Performance Returns statistics for your portfolio bid strategies.

Budget Performance

Returns all statistics aggregated by default at the budget level.

Call Metrics Call Details Returns data for call tracking of call-only ads or call extensions.
Campaign Ad Schedule Target Summarizes the performance of campaigns by AdSchedule criteria.
Campaign Criteria Returns campaign-level criteria.
Campaign Group Performance Returns the overall performance statistics of campaigns that you have included in campaign groups.
Campaign Location Target Summarizes the performance of campaigns by location-based campaign criteria.
Campaign Negative Keywords Performance Retrieves attributes of keyword-based NegativeCampaignCriterion objects.
Campaign Negative Placements Performance Retrieves attributes of placement-based NegativeCampaignCriterion objects.
Campaign Negative Locations Retrieves attributes of location-based NegativeCampaignCriterion objects.

Campaign Performance

Returns all statistics aggregated by default at the campaign level.

Campaign Shared Set Returns all relationships between SharedSet objects and campaigns.
Click Performance Returns all stats aggregated at each click level.
Creative Conversion Returns statistics on free clicks.
Criteria Performance Returns all statistics aggregated at the ad group criteria level.
Destination URL Returns all statistics aggregated at the destination URL level.
Display Keyword Performance Returns all Display Network and YouTube Network statistics aggregated at the keyword level.
Display Topics Performance Returns all Display Network and YouTube Network statistics aggregated at the topic level.
Final URL Returns all statistics aggregated at the final URL level.
Gender Performance Returns all statistics aggregated by gender along with automatic audience performance.
Geo Performance Returns all statistics aggregated at the country/territory level, one row per country/territory.
Keywordless Category Returns keywordless ads (dynamic search ads) statistics aggregated by category.
Keywordless Query Returns keywordless ads (dynamic search ads) statistics based on search terms.

Keywords Performance

Returns all statistics aggregated at the keyword level.

Label Lists all labels for your account.
Landing Page Returns all statistics aggregated by default by the UnexpandedFinalUrlString.
Marketplace Performance Returns all statistics of ads displayed on the Marketplace, aggregated by default at the account level.
Paid Organic Query Returns a holistic view of your search stats across ads and organic listings at the query level.
Parental Status Performance Returns statistics aggregated at the parental status level.
Placeholder Returns statistics for feed-based ad extensions.
Placeholder Feed Item Returns all statistics at the feed-item level.

Placement Performance

Returns all statistics aggregated at the placement level.

Product Partition Returns shopping campaign statistics aggregated at the product partition (ID field) level.
Search Query Performance Returns all statistics aggregated at the search terms level.
Shared Set Returns all SharedSet objects that can be shareable across campaigns.
Shared Set Criteria Returns criteria for each Shared Set.
Shopping Performance Returns shopping campaign statistics aggregated at the product (OfferId field) level.
Top Content Performance Returns statistics for top content bid modifier criteria.
URL Performance Returns all statistics aggregated at the URL and criterion level.
User Ad Distance Returns statistics aggregated by the user's distance from your location extensions.
Video Performance Returns statistics for your account's upgraded AdWords for Video campaigns.

Date Range

Select the date range for the data in your report.

Fields

Check the boxes for all fields you want to import into your report.

Segments

Check the boxes for all segments you want to import into your report.

Once you have entered data into all of the fields and selected options from the menus, your Google Ads script will appear automatically in the **Query preview** pane. Copy this script and paste it into Google Ads as explained in the next section. ## Configuring a BigQuery Script in Google Ads This section explains how to configure a BigQuery script in Google Ads. After you have configured the script, you should be able to use the BigQuery Service connector to pull in data just as you would any other connector. **To configure a BigQuery script in Google Ads,** 1. Configure your connector settings as explaned above. 2. Copy the script from the **Query Preview** pane. 3. Sign into your account in Google Ads. 4. Click the wrench icon in the top right corner of the screen. AWBQ_1.png 5. Click **Scripts** (which is found under "Bulk Actions"). AWBQ_2.png 6. Click the plus button to create a new script. AWBQ_3.png 7. Name the script, then click **Authorize**. AWBQ_4.png 8. Select **Advanced APIs**. 9. Check the **Bigquery** box. AWBQ_5.png 10. Paste the script you copied in step 4 into the textbox. 11. Click **Preview**. 12. (Conditional) If any error messages appear after you preview, follow their instructions. For example, you may be prompted to click on another link to authorize BigQuery or reauthorize. 13. Click **Run** when your configuration is successful. Google Ads now takes you back to the main page, where you are prompted to set up how often a script runs. 14. Click the pencil icon under "Frequency," then set the schedule for your script. AWBQ_6.png 15. Return to the Google Ads via Google BigQuery Service connector page in Domo and continue configuring the connector. ### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Troubleshooting If the data doesn't seem to be updating, make sure your Google Ads script runs before the connector runs. Otherwise, the same data will be pulled again. # Amazon Redshift Advanced Connector Source: https://www.domo.com/docs/s/article/360043436033 ## Intro Amazon Redshift is a hosted data warehouse project that is part of the larger cloud computing platform Amazon Web Services. Redshift handles analytics workloads on large scale DataSets stored by a column-oriented DBMS principle. You can use Domo's Amazon Redshift Connector to pull data from your Redshift database and compile custom reports. You indicate the data you want by inputting an SQL query. For more information about the Redshift API, visit their website. ([http://docs.aws.amazon.com/redshift/...e/Welcome.html)](http://docs.aws.amazon.com/redshift/latest/APIReference/Welcome.html) You connect to your Redshift database in the Data Center. This topic discusses the fields and menus that are specific to the Redshift connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). **Note:** Depending on your network's structure, you may need to whitelist any IP addresses necessary for the data connector to retrieve data. Contact your IT administrator for assistance. ## Prerequisites To connect to a Redshift database and create a DataSet, you must have the following: * The username and password you use to log into your Redshift database * The host name for the database server (e.g. [db.company.com](http://db.company.com) ). * The port number for the database * The database name CA certificate text or URL path is required *only* if you select **Certificate String** or **URL Path**, respectively, in the **Certificate Format** menu. Before you can connect to a Redshift database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses for Connectors](/docs/s/article/360043630093 "Whitelisting IP Addresses for Connectors"). ## Connecting to Your Redshift Account This section enumerates the options in the **Credentials** and **Details** panes in the Redshift Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Redshift account. The following table describes what is needed for each field:

Field

Description

JDBC Driver

Select the JDBC driver you want to use to connect.

Host

Enter the host name for the SQL database. For example: db.company.com

Database

Enter the name of the SQL database.

Username

Enter your Redshift username.

Password

Enter your Redshift password.

Database Port

Enter the port number for the database.

Certificate Format

Select the certificate format. If you do not want to include a certificate, select No Certificate . If you select Certificate String , you must paste the text for your certificate in the Certificate field. If you select URL Path , you must enter the URL where your certificate is located in the Certificate field.

Certificate

Paste the text for your CA certificate or enter the URL where your certificate is located. This is optional. If you do not want to include a certificate, select No Certificate in the Certificate Format menu.

Once you have entered valid Redshift credentials, you can use the same account any time you go to create a new Redshift DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane In this pane you create an SQL query to pull data from your database. You can also choose a specific database table and columns and specify a timeout value.

Menu

Description

Query Type

Select the type of query you want to execute.

Query

Enter the Structured Query Language (SQL) query to use in selecting the data you want.

For example:

select \* from Employee

Parameter Date Format

If you have used the Date data type in the Query Parameters field, enter a parameter date format here. This is optional. If you leave this blank, Domo will attempt to infer the date format. However, for the most accurate query results, you should provide the date format.

All of the following date formats are accepted:

Format

Example

EEE MMM dd HH:mm:ss z yyyy

Mon Dec 02 13:23:22 MST 2013

yyyy-MM-dd'T'HH:mm:ss.S+S

2014-11-30T12:34:56.000+0000

yyyy-MM-dd'T'HH:mm:ss.S

2014-06-10T07:34:16.671

yyyy-MM-dd HH:mm:ss.S

2014-12-22 08:41:33.397

yyyy-MM-dd HH:mm:ssXXX

2014-06-10 05:34:16+00:00

yyyy-MM-dd'T'HH:mm:ss'Z'

2013-03-25T08:45:00Z

yyyy-MM-dd'T'HH:mm:ssXXX

2014-06-10T05:34:16+00:00

yyyy-MM-dd'T'HH:mm:ss.SSS'Z'

2013-03-25T08:45:00.123Z

EEE, dd MMM yyyy HH:mm:ss z

Mon, Jan 20 2014 17:01:38 EST

MMM dd, yyyy

March 20, 2014

yyyy MMM dd

2014 March 20

MMM dd yyyy

March 20 2014

MM/dd/yy

03/20/14

dd/MM/yy

20/03/14

MM-dd-yy

03-20-14

dd-MM-yy

20-03-14

yyyy/MM/dd

2014/03/20

yyyy-MM-dd

2014-03-20

yyyy-MMM-dd

2014-March-20

MM/dd/yyyy

03/20/2014

dd/MM/yyyy

20/03/2014

MM-dd-yyyy

03-20-2014

dd-MM-yyyy

20-03-2014

dd-MMM-yyyy

20-March-2014

MMM-dd-yyyy

March-20-2014

yyyy-MM

2014-03

Database Tables

Select the database table you want to appear in your report.

Table Columns

Select all table columns you want to appear in your report.

Query Helper

Revise this query if desired.

Query Timeout

Enter the connector timeout value in minutes.

### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). # Amazon Redshift Source: https://www.domo.com/docs/s/article/360043436053 ## Intro Amazon Redshift is a hosted data warehouse project that is part of the larger cloud computing platform Amazon Web Services. Redshift handles analytics workloads on large scale DataSets stored by a column-oriented DBMS principle. You can use Domo's Amazon Redshift Connector to pull data from your Redshift database and compile custom reports. You indicate the data you want by inputting an SQL query. For more information about the Redshift API, visit their website. ([https://docs.aws.amazon.com/redshift/latest/dg/c\_redshift-sql.html](https://docs.aws.amazon.com/redshift/latest/dg/c_redshift-sql.html "https://docs.aws.amazon.com/redshift/latest/dg/c_redshift-sql.html") ) The Amazon Redshift connector is a "Database" connector, meaning it retrieves data from a database based on a query. In the Data Center, you can access the connector page for this and other Database connectors by clicking **Database** in the toolbar at the top of the window. You connect to your Redshift database in the Data Center. This topic discusses the fields and menus that are specific to the Redshift connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). **Note:** Depending on your network's structure, you may need to whitelist any IP addresses necessary for the data connector to retrieve data. Contact your IT administrator for assistance.

Primary Use Cases

Pulling data out of a Redshift data warehouse or data mart.

Primary Metrics

This depends on the data stored in the Redshift instance.

Primary Company Roles

  • BI leads

  • IT roles

Average Implementation Time

Anywhere between 5 and 40 hours, depending on configuration settings and the amount of data you are pulling.

Ease of Use (on a 1-to-10 scale with 1 being easiest)

6

## Best Practices Try to limit the results set size as much as possible. To speed the acquisition of the data, "fetch size" can be increased; however, setting it too high can cause connector run failures as well as performance problems with the Redshift instance. 10000 is a good place to start. ## Prerequisites To connect to a Redshift database and create a DataSet, you must have the following: * The username and password you use to log into your Redshift database * The host name for the database server (for example, [db.company.com](http://db.company.com) ). * The port number for the database * The database name CA certificate text or URL path is required *only* if you select **Certificate String** or **URL Path**, respectively, in the **Certificate Format** menu. ### Creating a Redshift account To create a Redshift user account, contact your Redshift Database Administrator (DBA) and have them follow these directions: By default, only the master user that you created when you launched the cluster has access to the initial database in the cluster. To grant other users access, you must create one or more user accounts. Database user accounts are global across all the databases in a cluster; they do not belong to individual databases. Use the CREATE USER command to create a new database user. When you create a new user, you specify the name of the new user and a password. A password is required. It must have between 8 and 64 characters, and it must include at least one uppercase letter, one lowercase letter, and one numeral. For example, to create a user named GUEST with password ABCd4321, issue the following command: `create user guest password 'ABCd4321';` ### Whitelisting IP addresses Before you can connect to a Redshift database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses for Connectors](/docs/s/article/360043630093 "Whitelisting IP Addresses for Connectors"). ## Connecting to Your Redshift Database This section enumerates the options in the **Credentials** and **Details** panes in the Redshift Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your database. The following table describes what is needed for each field:

Field

Description

JDBC Driver

Select the JDBC driver you want to use to connect.

Host

Enter the host string to connect to the SQL database. For example: // examplecluster.cpdbcwb2mzr4.us-east-2.redshift.amazonaws.com

Database

Enter the name of the SQL database.

Username

Enter your Redshift username.

Password

Enter your Redshift password.

Database Port

Enter the port number for the database.

Certificate Format

Select the certificate format. If you do not want to include a certificate, select No Certificate . If you select Certificate String , you must paste the text for your certificate in the Certificate field. If you select URL Path , you must enter the URL where your certificate is located in the Certificate field.

Certificate

Paste the text for your CA certificate or enter the URL where your certificate is located. This is optional. If you do not want to include a certificate, select No Certificate in the Certificate Format menu.

Once you have entered valid Redshift credentials, you can use the same account any time you go to create a new Redshift DataSet. You can manage connector accounts in the Accounts tab in the Data Center. For more information about this tab, see [Manage Connector/Adapter Accounts](https://domo-support.domo.com/s/article/360042926054?language=en_US "Manage Connector/Adapter Accounts"). ### Details Pane In this pane you create an SQL query to pull data from your database. You can also choose a specific database table and columns and specify which columns you want to appear in your report.

Menu

Description

Query

Enter the Structured Query Language (SQL) query to use in selecting the data you want. For example:

select \* from Employee.

Schema Name

Select ' With Schema Name ' option for populating the 'DATABASE SCHEMA NAMES' discovery and on the selection of the schema name it will populate the table discovery.

Database Tables

Select the database table you want to appear in your report.

Table Columns

Select all table columns you want to appear in your report.

Query Helper

Revise this query if desired.

Fetch Size

Enter the fetch size for memory performance. If the field is blank, then the default value will be 1000. If it throws out of memory for a value, then decrease the fetch size.

Boolean Format

Select the format for booleans to be represented in boolean data columns.

Boolean Format Description
1/0 true values will return '1', false values will return '0'
t/f true values will return 't', false values will return 'f'
T/F true values will return 'T', false values will return 'F'
true/false true values will return 'true', false values will return 'false'
### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Troubleshooting If you run into connection issues... * Verify the connection works using pgAdmin. * Confirm all of the necessary Domo IPs have been whitelisted (see Whitelisting IP addresses, above). * Run a profile on the SQL query. ## FAQ As often as needed. Limits depend on your server configuration. Make sure that all the words, table names and field names are correctly spelled. Refer to the Query Helper field for query help. # Amazon Redshift Unload Connector Source: https://www.domo.com/docs/s/article/360043436073 ## Intro Amazon Redshift is a fast and powerful, fully managed, petabyte-scale data warehouse service in the cloud. You connect to your Amazon Redshift Unload account in the Data Center. This topic discusses the fields and menus that are specific to the Amazon Redshift Unload connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Prerequisites To connect to Amazon Redshift so you can begin creating Amazon Redshift Unload DataSets, you must have the following: * The host name for the Redshift database * The database name for the Redshift database * Your Redshift username and password * The port number of your Redshift database * Your AWS access key * Your AWS secret access key * The name of the S3 bucket data will be unloaded into * The name of the S3 bucket region CA certificate text or URL path is required **only** if you select ****Certificate string**** or ****URL path****, respectively, in the ****Certificate type**** menu. If you do not know any of the information for Redshift, contact your Amazon Redshift Database Administrator. To find your AWS Access Key and Secret Access Key: 1. Log in to your AWS Management Console. 2. Click on your username at the top right of the page. 3. Select ****Security Credentials**** in the dropdown menu. 4. In the ****Access Credentials**** section, copy the latest Access Key ID. 5. Click on the ****Show link**** in the same row, and copy the Secret Access Key. ### Whitelisting Before you can connect to Redshift, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses for Connectors](/docs/s/article/360043630093 "Whitelisting IP Addresses for Connectors"). ## Connecting to Your Amazon Redshift Unload Account This section enumerates the options in the **Credentials** and **Details** panes in the Amazon Redshift Unload Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Amazon Redshift Unload account. The following table describes what is needed for each field:

Field

Description

Host

Enter the host name for the Redshift database you want to pull data from.

Database

Enter the database name for the Redshift database you want to pull data from.

Username

Enter the username for your Redshift account,

Password

Enter the password for your Redshift account.

Database Port

Enter the port number for the Redshift database you want to pull data from.

Certificate Format

Select a certificate format. If you do not want to include a certificate, leave the default No certificate option selected. If you select Certificate string , you must paste the text for your certificate in the Certificate field. If you select URL path , you must enter the URL where your certificate is located in the Certificate field.

Certificate

Paste the text for your CA certificate or enter the URL where your certificate is located. This is optional. If you do not want to include a certificate, select No certificate in the Certificate Format menu.

Access Key

Enter your AWS access key. For information about obtaining an access key, see "Prerequisites," above.

Secret Access Key

Enter your AWS secret key. For information about obtaining an access key, see "Prerequisites," above.

S3 Bucket

Enter the name of the S3 bucket to use in pulling in data.

S3 Bucket Region

Select the region containing the desired S3 bucket.

Once you have entered valid credentials, you can use the same account any time you go to create a new Amazon Redshift Unload DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane This pane contains various options for specifying the data you want to pull into Domo.

Menu

Description

Header Query (Optional)

Enter the SQL query to use in obtaining the correct header metadata for the query specified below (in the Query field). This is necessary because Redshift does not dump header data using UNLOAD. If you leave this blank, header data will be retrieved using the query you enter in the Query field.

Cache Last Good Header?

If you select Yes for this option, the connector caches the header so it does not create an additional query.

Query Type

Select the desired query type. If you select Query, you will be prompted to enter a regular SQL query without a parameter. If you select Query Parameter, you will be prompted to enter a SQL query with a parameter.

Query

Enter the SQL query you want to use to pull in data.

For example:

select \* from Employee

You can use the Generated Query parameter to help you write a usable SQL query. To use the Generated Query, do the following:

  1. Select your database table and table columns in the appropriate menus.

  2. Copy the SQL statement that appears in the Generated Query field.

  3. Paste the copied SQL statement into the Query field.

Fetch Size (Optional)

Enter the fetch size for memory performance. If you leave this blank, a default value of 1000 will be used. If an "Out of Memory" error is generated, try decreasing the fetch size.

Query Parameter

Enter the query parameter value. This is the initial value for the query parameter. The "Last Run" date is optional. If you do not enter this date, a default date of "02/01/1700" is used.

For example:

`!{lastvalue:_id}!=1,!{lastrundate:start_date}!=02/01/1944,!{lastmaxvalue:size}!=0`

Validation Type

Select the desired validation type. If you select Validate schema, the previous schema is validated against the current schema. If these are not the same, the validation fails. If you select this option, you are asked to select a validation case in the Validate By menu.

Validate By

Select the desired validation case option.

If you select Column case sensitive, if the previous schema and current schema are the same except for differences in letter case, the schemas are not considered the same and the validation fails.

If you select Column by order, if the previous schema and current schema are the same except for column order differences, the schemas are not considered the same and the validation fails.

Boolean Format

Select the desired Boolean format for returned data.

Database Tables (Optional)

Select the database tables you want to pull into Domo, if desired.

Table Columns (Optional)

Select the table columns you want to pull into Domo.

Generated Query (Optional)

Copy and paste the SQL statement in this field into the Query field. For more information, see Query, above.

Query Timeout (Optional)

Enter the desired query timeout value.

Use High Bandwidth Upload Select this checkbox to use high bandwidth upload transfer.

Keep Files in S3?

Select whether or not you want to keep your files in S3.

### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQs As often as needed. This depends on your server configuration. Before you can connect to a Redshift database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses](/docs/s/article/360043630093 "Whitelisting IP Addresses for Connectors"). # MySQL Connector Source: https://www.domo.com/docs/s/article/360043436193 ## Intro MySQL is a widely used open-source relational database management system. You can use Domo's MySQL Connector to pull data from your MySQL database and compile custom reports. You indicate the data you want by inputting an SQL query. For more information about the MySQL API, visit their website. ([http://dev.mysql.com/doc/refman/5.0/en/c-api.html](http://dev.mysql.com/doc/refman/5.0/en/c-api.html "http://dev.mysql.com/doc/refman/5.0/en/c-api.html") ) The MySQL connector is a "Database" connector, meaning it retrieves data from a database using a query. In the Data Center, you can access the connector page for this and other Database connectors by clicking **Database** in the toolbar at the top of the window. You connect to your MySQL database in the Data Center. This topic discusses the fields and menus that are specific to the MySQL connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). **Notes:** * This connector supports TLS IF your MySQL server supports TLS. * Non SSL connections are not supported. If no certificate is provided, the connection is still SSL but without any certificate authentication. The connection will trust all server certificates. Refer to the following link for details: [https://msdn.microsoft.com/en-us/library/bb879949%28v=sql.110%29.aspx](https://msdn.microsoft.com/en-us/library/bb879949%28v=sql.110%29.aspx "https://msdn.microsoft.com/en-us/library/bb879949%28v=sql.110%29.aspx")

Primary Use Cases

Pulling data mart and data warehouse SQL queries

Primary Metrics

N/A

Primary Company Roles

  • CIO

  • CTO

Average Implementation Time

5-40+ hours

Ease of Use (on a 1-to-10 scale with 1 being easiest)

7

## Best Practices * Limit the results set size is much as possible. * Keep the number of columns to a minimum. ## Prerequisites To connect to a MySQL database and create a DataSet, you must have the following: * The username and password you use to log into your MySQL database * The host name for the database * The port number for the database * The database name or schema name * The SQL query you will use to pull data * SSL You can also include the URL where your SSL CA Certificate is located, though this is optional. If your SSL configuration requires use of all 3.PEM certificate files, you can utilize the [MySQL Advanced Security Connector](/docs/s/article/4410071437335 "MySQL Advanced Security Connector") which has a field for each file. ### Creating MySQL Accounts You can create MySQL accounts two ways: * By using account management statements intended for creating accounts and establishing their privileges, such as CREATE USER and GRANT. These statements cause the server to make appropriate modifications to the underlying grant tables. * By manipulating the MySQL grant tables directly with statements such as INSERT, UPDATE, or DELETE. The preferred method is to use account management statements because they are more concise and less error-prone than manipulating the grant tables directly. Another option for creating accounts is to use the GUI tool MySQL Workbench. Also, several third-party programs offer capabilities for MySQL account administration, such as phpMyAdmin. ### Whitelisting Before you can connect to a MySQL database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses for Connectors](/docs/s/article/360043630093 "Whitelisting IP Addresses for Connectors"). ## Connecting to Your MySQL Database This section enumerates the options in the **Credentials** and **Details** panes in the MySQL Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). **Note:** When using the copy/paste function for your credentials, ensure there is no whitespace at the beginning or end of the string. By accidentally pasting whitespace, it will cause the connector to error when trying to connect. ### Credentials Pane This pane contains fields for entering credentials to connect to your database. The following table describes what is needed for each field:

Field

Description

Host

Enter the host name for the SQL database. For example: db.company.com

Database Name

Enter the name of the SQL database or schema.

Username

Enter your MySQL username.

Password

Enter your MySQL password.

CA Certificate

Enter the URL where the SSL Ca Certificate is located (optional).

Port

Enter the port number for the database.

Once you have entered valid MySQL credentials, you can use the same account any time you go to create a new MySQL DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing Connector Accounts](https://domo-support.domo.com/s/article/360042926054?language=en_US "Managing Connector Accounts"). ### Details Pane In this pane you create an SQL query to pull data from your database, with or without a parameter.

Menu

Description

Query Type

Select the desired MySQL query type—either with or without a parameter.

Query Type Description
Custom Query Enter the SQL query to execute.
Query Builder Select a table and fields to autogenerate your query.

Query

Enter the Structured Query Language (SQL) query to use in selecting the data you want. For example:

select \* from Employee

You can use the Query Helper parameter to help you write a usable SQL query. To use the Query Helper , do the following:

  1. Select your database table and table columns in the appropriate menus.

  2. Copy the SQL statement that appears in the Query Helper field.

  3. Paste the copied SQL statement into the Query field.

Query Parameter (checkbox)

Select this checkbox to add query parameters.

Query Parameter

Enter the query parameter value. This is the initial value for the query parameter. You can use this option to retrieve new data since the last run.

For example, if you entered the following query in the Query field...

`select * from test.lastValue where id >=!{lastvalue:id}! order by id desc`

...and then entered the following for the Query Parameter ...

`!{lastvalue:id}!=3`

...then the first run would return 3 rows, and all subsequent runs would return 1 row, and the results would be ordered from largest to smallest.

Similarly, if you entered the following in the Query field...

`select * from test.lastValue where time

...and then entered the following for the Query Parameter ...

`!{lastrundate:time}!=01/01/1990`

...then the first run would return 5 rows and all subsequent runs would return 0 rows.

Select If You Want To Compress The Data

Select True or False.

TinyInt Values Treated as BIT (Boolean) Values

Select Yes if you want TinyInt values to be treated as Boolean.

Cast Boolean Values To...

Select whether Boolean values will be cast to integers or strings.

Database Tables

Select the database table you want to import into Domo.

Table Columns

Select the table columns you want to import into Domo.

Query Helper

Copy and paste the SQL statement in this field into the Query field. For more information, see Query , above.

Select if you want to compress the data

Select how to upload the data.

Fetch Columns Description (Comment)

Toggle this option to fetch the columns description(comment) that should be imported in the current execution.

### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Troubleshooting * Verify the credentials using MySQL Workbench. * Confirm the server supports encrypted connections. * Confirm the Domo IPs are whitelisted. * To speed up your runtime, make sure the tables you are joining don't have duplicate column names and that you call each column only once. # MySQL SSH Connector Source: https://www.domo.com/docs/s/article/360043436213 ## Intro MySQL is a widely used open-source relational database management system. You can use Domo's MySQL SSH Connector to pull data from your MySQL database and compile custom reports. You indicate the data you want by inputting an SQL query. For more information about the MySQL API, visit their website. ([http://dev.mysql.com/doc/refman/5.0/en/c-api.html](http://dev.mysql.com/doc/refman/5.0/en/c-api.html)) The MySQL SSH connector is a "Database" connector, meaning it retrieves data from a database using a query. In the Data Center, you can access the connector page for this and other Database connectors by clicking **Database** in the toolbar at the top of the window. You connect to your MySQL database in the Data Center. This topic discusses the fields and menus that are specific to the MySQL SSH connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector").

Primary Use Cases

Pulling data mart and data warehouse SQL queries

Primary Metrics

N/A

Primary Company Roles

  • CIO

  • CTO

Average Implementation Time

5-40+ hours

Ease of Use (on a 1-to-10 scale with 1 being easiest)

7

## Best Practices * Limit the results set size as much as possible. * Keep the number of columns to a minimum. ## Prerequisites To connect to a MySQL database via an SSH server and create a DataSet, you must have the following: * The hostname of the UNIX server you are SSH-tunneling through * The SSH username and password for your UNIX account * The host name for the database * The SSH private key (either DES or RSA) * The database name * The username and password you use to log into your MySQL database **Note: Domo does not support the SSH keys generated using ssh-keygen. The SSH keys need to be the DES or RSA keys (in PEM format) generated by OpenSSL.** ### Creating MySQL Accounts You can create MySQL accounts two ways: * By using account management statements intended for creating accounts and establishing their privileges, such as CREATE USER and GRANT. These statements cause the server to make appropriate modifications to the underlying grant tables. * By manipulating the MySQL grant tables directly with statements such as INSERT, UPDATE, or DELETE. The preferred method is to use account management statements because they are more concise and less error-prone than manipulating the grant tables directly. Another option for creating accounts is to use the GUI tool MySQL Workbench. Also, several third-party programs offer capabilities for MySQL account administration, such as phpMyAdmin. ### Whitelisting Before you can connect to a MySQL database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses for Connectors](/docs/s/article/360043630093 "Whitelisting IP Addresses for Connectors"). ## Connecting to Your MySQL Database This section enumerates the options in the **Credentials** and **Details** panes in the MySQL Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your database. The following table describes what is needed for each field:

Field

Description

SSH Server Hostname

Enter the hostname of the UNIX server to SSH-tunnel through.

SSH Username

Enter the SSH username for your UNIX account.

SSH Password

Enter the SSH password for your UNIX account.

Database Hostname

Enter the hostname or IP address for the SQL database. For example: db.company.com

SSH Private Key

Enter the SSH private key (either DES or RSA).

Database Name

Enter the name of the SQL database or schema.

Database Username

Enter your MySQL username.

Database Password

Enter your MySQL password.

Once you have entered valid credentials, you can use the same account any time you go to create a new MySQL SSH DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane In this pane you create an SQL query to pull data from your database as well as specify a few options.

Menu

Description

Query Type

Select a query type.

Query Regular SQL query without parameter.
Query Parameter SQL query with parameter.

SQL Query

Structured Query Language (SQL) query to use in selecting the data you want. For example:

select \* from Employee

Query Parameter

Enter the query parameter value, it is the initial value for query parameter. The last run date is optional. By default, it is '02/01/1700' if is not provided.

For example: `!{lastvalue:_id}!=1,!{lastrundate:start_date}!=02/01/1944`

TINYINT Values Treated as Bit (Boolean) Values? Select Yes if you want TINYINT values to be treated as Boolean values.
Keep Connection Alive For Large Queries Select Yes if the connection should be kept running for very large queries.
Include HTML Tag Select Yes to include the html tag with the data.
### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Troubleshooting * Verify the credentials using MySQL Workbench. * Confirm the server supports encrypted connections. * Confirm the Domo IPs are whitelisted. # Snowflake Unload Connector Source: https://www.domo.com/docs/s/article/360043436313 **Note:** Snowflake will no longer support the username and password authentication mechanism as of November 2025. As a result, this connector will be retired in November 2025 and will no longer function. Please consider using one of the following connection methods instead: * [Cloud Integrations](/docs/s/article/4402322966807) * [Snowflake OAuth Unload Connector](/docs/s/article/1500010166282) * [Snowflake KeyPair Unload Connector](/docs/s/article/360059173794) ## Snowflake Connector Migration Walkthrough As Snowflake is discontinuing username and password authentication, Snowflake connectors using this authentication method will be migrated to the OAuth version. This section helps users walk through the complete process of migrating their existing username and password Snowflake datasets to utilize the OAuth authentication version. Pls refer to the migration video ([https://youtu.be/rlG\_uNZwl\_U](https://youtu.be/rlG_uNZwl_U)) to make the transition smoother and minimize disruptions. ## Intro Snowflake is a cloud-based analytic data warehouse system. The files are then downloaded from S3 into Domo. You should use this connector instead of the standard Snowflake connector if you are executing very large queries. To learn more about the Snowflake API, visit their page ([https://docs.snowflake.net/manuals](https://docs.snowflake.net/manuals)). You connect to your Snowflake account in the Data Center. This topic discusses the fields and menus that are specific to the Snowflake Unload connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). *** ## Prerequisites To connect to your Snowflake account and create a DataSet, you must have the following: * The full name of your account (provided by Snowflake). This is the portion of your Snowflake URL immediately following https\://. Note that your full account name may include additional segments that identify the region and cloud platform where your account is hosted. The following table provides account name examples by cloud platform/region. For each row, it assumes your account name is "xy12345." snowflake_account_names.png - The username and password used to connect to your Snowflake host. * Your AWS access key. This is available in the AWS Console in the **Security Credentials** section (unless you are using IAM, in which case it is under **Users**). * Your AWS secret key. This was provided when you created your access key. You can generate a new key in the AWS Console. * The name of the AWS S3 bucket in which Snowflake data will be unloaded. ## Connecting to Your Snowflake Account This section enumerates the options in the **Credentials** and **Details** panes in the Snowflake Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ### Credentials Pane This pane contains fields for entering credentials to connect to your Snowflake account. The following table describes what is needed for each field:

Field

Description

Account Name

Enter your Snowflake account name. For more information, see Prerequisites.

Username

Enter the username you use to connect to your Snowflake host.

Password

Enter the password you use to connect to your Snowflake host.

Access Key

Enter your AWS access key. For information about obtaining an access key, see "Prerequisites," above.

Secret Key

Enter your AWS secret key. For information about obtaining a secret key, see "Prerequisites," above.

Bucket

Enter the name of the AWS S3 bucket.

Once you have entered valid Snowflake credentials, you can use the same account any time you go to create a new Snowflake DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054). ### Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

Query

Enter the SQL query to use to retrieve your data. You can use the Query Helper parameter to help you write a usable SQL query. To use the Query Helper, do the following: 1. Select your desired warehouse, database, database schema, database table, and table columns in each menu. 2. Copy the SQL statement that appears in the Query Helper field. 3. Paste the copied SQL statement into the Query field.

Warehouses (Optional)

Select the warehouse containing the data you want to retrieve. The list populates with all of the warehouses you have access to based on your credentials.

Databases (Optional)

Select the database containing the data you want to retrieve. The list populates with all of the databases you have access to based on your credentials.

Database Schema (Optional)

Select the database schema containing the data you want to retrieve. The list populates with all of the schemas you have access to based on your credentials.

Database Tables (Optional)

(Optional) Select the database table you want to retrieve. The list populates with all of the tables you have access to based on your credentials. If you do not select a database table, the connector retrieves your entire database schema.

Table Columns (Optional)

(Optional) Select the table columns you want to retrieve. The list populates with all of the columns you have access to based on your credentials. If you do not select a table column, the connector retrieves your entire selected database table.

Query Helper (Optional)

(Optional) When you select warehouses, databases, schemas, tables, etc. from the above menus, a usable SQL query is built for you in this field. Copy and paste the SQL statement in this field into the Query field. For more information, see Query, above.

Use Snowflake Schema

Check this box if you want to use the schema from Snowflake instead of having Domo determine the schema automatically.

snowflake_unload_ui.png ### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQs This depends on your server configuration. DataSets can run as often as every 15 minutes. However, depending on the runtime of the query, DataSets may need to run less frequently. Make sure that all the words, table names, and field names are correctly spelled. Refer to the Query Helper field for query help. Before you can connect to a Snowflake database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses in Domo](/docs/s/article/360043439173 "Whitelisting IP Addresses in Domo"). This connector is designed for small/medium DataSets and proof of concept work for large DataSets. # Google BigQuery Service Connector Source: https://www.domo.com/docs/s/article/360043436593 ## Intro Google BigQuery is a cloud-based big data analytics web service for processing very large read-only data sets. You can use Domo's Google BigQuery Service connector to pull data from a specified project. Google BigQuery queries are written using a variation of the standard SQL SELECT statement. To learn more about the BigQuery API, go to [https://cloud.google.com/bigquery/docs/reference/v2/](https://cloud.google.com/bigquery/docs/reference/v2/). The Google BigQuery Service connector is a "Cloud App" connector, meaning it retrieves data stored in the cloud. In the Data Center, you can access the connector page for this and other Cloud App connectors by clicking **Cloud App** in the toolbar at the top of the window. This topic discusses the fields and menus that are specific to the Google BigQuery Service connector user interface. For general information about adding DataSets, setting update schedules, and editing DataSet information, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector").

Primary Use Cases

Any situations in which you need to extract data from Google BigQuery.

Primary Metrics

DFP data

Primary Company Roles

  • Marketing roles

  • Finance roles

Average Implementation Time

This depends on how many queries need to be written. Having someone who understands the BigQuery database structure and knows how to build the queries will greatly cut down on deployment time.

Ease of Use (on a 1-to-10 scale with 1 being easiest)

5

## Best Practices * Structuring your queries to be optimized so you are pre-aggregating data *before* pulling it into Domo will significantly improve performance. * Getting your data closely structured to support the visualizations prior to ingestion will save time by potentially eliminating the ETL process in Domo. ## Prerequisites To connect to a BigQuery service account, you must have a Google BigQuery service account JSON key. To generate a key, do the following: 1. In the Google Cloud Platform Console, open the IAM & Admin page. 2. Click **Service accounts** in the left-hand navigation pane. 3. Select your project and click **Open**. 4. Click **Create Service Account**. 5. Enter a name and description for the service account. 6. Click **Create**. **Note:** You may need the “BigQuery Admin” role in the service account permissions dialog. Please consult with your Google administrator for additional guidance. 7. Select **Project > Owner**. 8. Click **Continue**. 9. Click **Create key**. 10. Select **JSON** as the key type. 11. Click **Create**. A private key will be saved to your computer. ## Connecting to Your BigQuery Service Account This section enumerates the options in the Credentials and Details panes in the Google BigQuery Service Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your BigQuery service account. The following table describes what is needed for each field:

Field

Description

Service Account Key JSON

Copy and paste the JSON for your BigQuery service account key. For information about creating a key, see "Prerequisites," above.

Once you have entered a valid key, you can use the same account any time you go to create a new Google BigQuery Service DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane This pane contains a number of fields and menus you can use to configure your report. **Tip:** Use the "Table Information" report to get the DataSet ID, Project ID, table name, etc. This can help you create and form your queries.

Menu

Description

Report

Select the BigQuery report type to run. The following reports are available:

Query

Lets you enter a query and configure the parameters.

Table Data

Lets you pull data for a selected BigQuery project, dataset, and table.

Table Information

Returns the table resource that describes the structure of this table. This report does not return the data in the table. To do this, run the "Table Data" report.

SQL Dialect

Select whether your query is to be written using LegacySQL or StandardSQL. By default, Standard SQL is used.

Query

Enter a fully qualified BigQuery query. The query language you use must match what you have selected in the SQL Dialect menu.

For full documentation about writing BigQuery queries, see [https://cloud.google.com/bigquery/query-reference](https://cloud.google.com/bigquery/query-reference) . For more information about setting a query prefix, see [https://cloud.google.com/bigquery/docs/reference/standard-sql/enabling-standard-sql](https://cloud.google.com/bigquery/docs/reference/standard-sql/enabling-standard-sql) .

Query Parameter

Enter the query parameter value. This is the initial value for query parameter. You can provide multiple comma separated query parameters. The query in the above "Query" field will fetch the data according to the parameter values provided here. For more information, see "Using the Query Parameter" section below.

Example: `!{lastvalue:_id}!=1,!{lastrundate:start_date}!=02/01/1944`

Allow Large Results

Select whether you expect a large resulting DataSet from this query. If you select Yes , a temporary table will be created and then deleted when the job is finished. You will need to enter a DataSet ID in the DataSet ID field for the table to be created.

DataSet Name

Select the name of the dataset you want to pull into Domo.

Table Name

Select the table you want to pull data from.

Processing Location

Enter the location where your query will run. Queries running in a specific location may only reference data in that location.

Max Results

Enter the maximum number of results you want to return in your report. The default is 10,000 results per page. If your DataSet throws an "Out of Memory" error, decrease this number.

Use Google BigQuery Schema

Select this checkbox to use the schema received from Google BigQuery.
This is useful when a column's datatype may be perceived incorrectly to Domo.

Example: Your table may contain '123' in a String column.

Fetch Columns Description (Comment)

This field appears only when the Use Google BigQuery Schema checkbox is selected. Select this option to include column descriptions (comments) in the current execution.

### Using the Query Parameter Query parameter indicates the initial values for the query parameters. After the initial run, the query will only request the updated data from the provider on subsequent runs. You can provide multiple query parameters separated by comma. **Note:** You must use the query parameters provided here in the Query field above. The query will fetch the data according to the parameter values provided here. Example: Query_Parameters.png In this example, the values "id=1" and "start date=02/01/1944" will be used in the first run of the above query. The value for the query parameter 'last run date' is optional. By default, the last run date is '02/01/1700' if is not provided. ### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Troubleshooting * Ensure that the credentials have the proper access to the query the tables needed. * Make sure the queries are correct and calling the correctly named data sources. ## FAQs Use this connector to import small to large datasets from Google BigQuery. This connector uses a Service Account key in JSON format to connect, and only connects to the project specified in the key. Once connected, you can replace the dataset on every run, append data to the existing dataset on every run, or merge (upsert) new or updated data on every run. For very large datasets, it is recommended you use one of Domo's Google High Bandwidth or Unload connectors. The **Max Results** parameter, set in the **Details** section of the connector, is the maximum number of rows of data to return per page of results. Setting **Max Results** to a smaller value, such as 1000, then paging through results, may improve reliability when the query result set is large. In addition to Domo's **Max Results** row limit, Google imposes a byte limit of 10 MB per page of results. If your row values contain a lot of data, you may have fewer rows per page returned in order to come under the byte limit. You can specify the processing location in your Query report for storing your BigQuery data when you create a DataSet. After you create the DataSet, the location cannot be changed. Queries that run in a specific location may only reference data in that location. There are two types of locations: a regional location and a multi-regional location. For more information, visit [Dataset locations](https://cloud.google.com/bigquery/docs/locations "https://cloud.google.com/bigquery/docs/locations"). If you are expecting large results for your query, go to the **Details** section of the connector interface. Select **Yes** for **Allow large results?**, and select the DataSet in the **DataSet Name** menu. Your Google account must have Table creation permissions enabled in order to set **Allow large results** to **Yes**. As often as needed. No Yes You need the service account key JSON of your Google BigQuery Service Account. To find your service account key JSON: 1. Open the IAM & Admin page in the GCP Console. 2. In the left navigation, click **Service accounts**. 3. Select your project and click **Open**. 4. Click **Create Service Account**. 5. Enter a service account name and service account description. Click **Create**. 6. Select a role you wish to grant to the service account (Project Owner). Click **Continue**. 7. Click **Create key**. Select JSON key type. Click **Create**. Private key will be saved to your computer. 8. Close the pop up. Click **Done**. # Microsoft Azure Blob Storage Connector Source: https://www.domo.com/docs/s/article/360043436693 ## Intro Microsoft Azure Blob Storage is designed to easily and efficiently store any type of unstructured data, such as images, videos, audio, and documents. Use Domo's Microsoft Azure Blob Storage connector to pull CSV, TSV, and TXT data files from your Microsoft Azure Blob Storage account into Domo. Combine your Azure data with data from other data sources throughout your company for a comprehensive view of your business. Set up custom alerts to be notified in real-time when your key metrics change, so you can make faster, better business decisions. To learn more about the Azure Blob Storage API, visit their page ([https://docs.microsoft.com/en-us/res...rvice-rest-api](https://docs.microsoft.com/en-us/rest/api/storageservices/blob-service-rest-api "https://docs.microsoft.com/en-us/rest/api/storageservices/blob-service-rest-api")). You connect to your Microsoft Azure Blob Storage account in the Data Center. This topic discusses the fields and menus that are specific to the Azure Blob Storage connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Prerequisites To connect to your Azure Blob Storage account and create a DataSet, you must have the following: * Your Microsoft Azure Blob Storage account name * Your Microsoft Azure Blob Storage account key If you do not know your credentials, reach out to your Microsoft account representative. ## Connecting to Your Azure Blob Storage Account This section enumerates the options in the **Credentials** and **Details** panes on the Azure Blob Storage Connector page. The components of the other panes on this page, **Scheduling**, and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Credentials Pane This pane contains fields for entering credentials to connect to your Azure Blob Storage account. The following table describes what is needed for each field:

Field

Description

Account Name

Enter your Microsoft Azure Blob Storage account name.

Account Key

Enter your Microsoft Azure Blob Storage account key.

Once you have entered valid Azure Blob Storage credentials, you can use the same account any time you go to create a new Azure Blob Storage DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Manage Connector Accounts](https://domo-support.domo.com/s/article/360042926054?language=en_US "Manage Connector Accounts"). ## Details Pane This pane contains various options for selecting and configuring the file you want to import into Domo.

Menu

Description

What File Type Would You Like to Import?

Select whether you want to pull a CSV, TSV, TXT, XLS, or XLSX file into Domo.

Select File Compression Type

Select the compression type of your file.

Blob Containers

Select the desired container.

File Encoding

Select the file encoding. By default, UTF-8 is selected.

Date Format

Select the date format used in the selected file.

Blob Search Type

Select whether you want to filter the blobs with simple or advanced options.

Limit the Search To Directory

Enter the path to limit the search to a directory, subdirectory. Leave it empty if you want to search for the blob in the container root and all directories. For example directory/subdirectory/nesteddirectory/
Do not include the container name.

Blob Name

Enter partial or full name of the blob (Do not include extension).

Blob Name Match Type

Select how to match the blob names in Azure with the provided Blob Name.

Ignore Case (checkbox)

Should Domo ignore the cases while matching the provided Blob Name?

Invert Match (checkbox)

Pull the files with the provided prefix that do not match the provided criteria of Blob Name match

Advanced Filter For Blobs

The All Blobs option is selected by default and the connector pulls all the blobs for the configured dataset.

The Latest Updated Blobs option pulls all the latest updated blobs for the configured dataset.

The Recent Blob option pulls only the latest blob from all the obtained blobs for the configured dataset.

Does Your Blob Containers Have Directories?

Select 'Yes' if your blob containers have directories.

Blob Directories

Select the blob directory.

Select Block Blob

Select the desired file.

Pull All Files (checkbox)

Select this checkbox if you would like to pull all files from a directory.

How Would You Like To Choose Your Block Blob?

Specify whether you would like to select your block blob or enter it manually.

Enter Block Blob

Enter the desired file name.

Block Blob Match Type

Specify whether the block blob should start with or contain the name you have entered in Enter Block Blob .

Blobs Search Type

Select whether you want to filter the blobs with simple or advanced options.

## Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). # Amazon Redshift Writeback Connector Source: https://www.domo.com/docs/s/article/360043436893 ## Intro Use this connector to export your data from a Domo DataSet to an Amazon Redshift database. To learn more about Redshift, visit their website at [https://aws.amazon.com/redshift/](https://www.postgresql.org/ "https://www.postgresql.org/"). You export data to a Redshift database in the Data Center. This topic discusses the fields and menus that are specific to the Redshift Writeback connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). **Note:** The owner of a writeback dataset must also be an owner or co-owner of the input dataset. ## Prerequisites To configure this connector, you will need the following: * A Domo Client ID and Client Secret. Learn how to get your [Domo Client ID and Secret](/docs/s/article/000005240#create-api-clients). * The hostname or IP address of your Redshift server. * Your Redshift database name. * Your Redshift username and password. * The port number of your Redshift server. * Your AWS access key. This is available in the AWS Console in the **Security Credentials** section (or under **Users** if you are using IAM). * Your AWS secret key. This was provided when you created your access key. You can generate a new one in the AWS Console. If you don't know any of your SQL credentials, contact your SQL Database Administrator. You may also paste the text for a Redshift CA certificate (or you may input the URL where the certificate is located), but this is optional. ## Configuring the Connection This section enumerates the options in the **Credentials** and **Details** panes in the Redshift Writeback Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Domo developer account as well as the table in your Redshift database where you want your data to be copied to. The following table describes what is needed for each field:

Field

Description

Domo Client ID

Enter your Domo client ID.

Domo Client Secret

Enter your Domo client secret.

Host

Enter your Redshift database hostname.

Database

Enter the name of your Redshift database.

Username

Enter your Redshift username.

Password

Enter your Redshift password.

Database Port

Enter your Redshift database port number.

Certificate Format

Select a certificate format. This must match what you enter in the Certificate field. If you are not aware of a special certificate, select No certificate .

Certificate

Paste the text for your CA certificate, or enter the URL where your certificate is located. By default no certificate is required.

Access Key

Enter your AWS access key.

Secret Key

Enter your AWS secret key.

Region

Select the S3 region containing the bucket you want to push data to.

Bucket

Enter the name of the AWS bucket you want to push data to.

For more information about obtaining these credentials, see "Prerequisites," above. Once you have entered valid credentials, you can use the same account any time you go to set up a new Domo-Redshift connection. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane This pane contains a number of fields for specifying your data and indicating where it's going.

Menu

Description

DataSet ID

Enter the DataSet ID (GUID) for the DataSet you want to copy to Redshift. You can find the ID by opening the details view for the DataSet in the Data Center and looking at the portion of the URL following datasources/ . For example, in the URL [https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview](https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview) , the DataSet ID is 845305d8-da3d-4107-a9d6-13ef3f86d4a4.

Table Name Source

Select how you want to name the table where data will be copied.

  • DataSet ID . The table name will be the number you entered for DataSet ID .

  • DataSet Name . The table name will be the same as that of the input DataSet.

  • Custom Name . You will give the table a custom name in the Custom Table Name field.

Custom Table Name

Enter the name of the table in your Redshift database where you want your DataSet data to be copied.

Schema Name

Write dataset data to the selected schema.

Operation Type

Select an operation type to perform:

Operation Description
Create New Table Creates a new table for each execution. The table name uses the specified name followed by a numeric counter.
Update an Existing Table Updates an existing table if the table name matches a table in Amazon Redshift. If no matching table exists, a new table is created on the first run.

Append Or Overwrite

Select how you want to update the database table:

Operation Description
Append DataAppends the fetched data to the existing table.
Overwrite With New DataOverwrites the existing data with newly fetched data to the existing table.

**Note:** If the table does not exist on the first run, a new table might be created. On subsequent runs, the table is updated based on the selected option.

### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). # Google BigQuery Writeback Connector Source: https://www.domo.com/docs/s/article/360043436933 ## Intro Google BigQuery is a cloud-based big data analytics web service for processing very large read-only datasets. Use this connector to export your data from a Domo DataSet into a BigQuery table. To learn more about the BigQuery API, go to [https://cloud.google.com/bigquery/docs/reference/v2/](https://cloud.google.com/bigquery/docs/reference/v2/ "https://cloud.google.com/bigquery/docs/reference/v2/"). You export data to BigQuery in the Data Center. This topic discusses the fields and menus that are specific to the BigQuery Writeback connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). **Note:** The owner of a writeback dataset must also be an owner or co-owner of the input dataset. ## Prerequisites To configure this connector, you will need the following: * A Domo Client ID and Client Secret. Learn how to get your [Domo Client ID and Secret](/docs/s/article/000005240#create-api-clients). * A Google Service Token JSON file. ### Obtaining a Service Token JSON File To obtain a Google Service Token JSON file, do the following: 1. In the Google Developers Console, open the **Credentials** tab. 2. Click **Create credentials** then select **Service account key**. googlesheets_writeback_5.png 3. Select **New service account**. 4. Name the new service account. 5. In the **Role** dropdown, select **Project > Owner**. 6. For the **Key type**, select **JSON**. googledrive_writeback_2.png 7. Click **Create**, then **Save**. 8. Select a safe location for the file, as you will need it soon. ## Configuring the Connection This section enumerates the options in the **Credentials** and **Details** panes in the Google BigQuery Writeback Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Domo developer account as well as your destination table in BigQuery. The following table describes what is needed for each field:

Field

Description

Domo Client ID

Paste the Domo client ID you copied in Step 4: Creating a Domo Client ID and Client Secret, in the "Prerequisites" section above.

Domo Client Secret

Paste the Domo client secret you copied in Step 4: Creating a Domo Client ID and Client Secret, in the "Prerequisites" section above.

Service Token JSON

Paste the JSON Service Token you generated in Step 3: Creating a Service Account, in the "Prerequisites," above.

Once you have entered valid credentials, you can use the same account any time you go to set up a new Domo-Google BigQuery connection. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Manage Connector/Adapter Accounts](https://domo-support.domo.com/s/article/360042926054?language=en_US "Manage Connector/Adapter Accounts"). ### Details Pane This pane contains a number of fields for specifying your data and indicating where it's going.

Menu

Description

Input BigQuery Table Name

Enter the name of the BigQuery table you want to send Domo data to. The table you indicate will be deleted and recreated with each run.

Input BigQuery DataSet Name

Enter the name of the BigQuery dataset in which the table is found.

Input Domo DataSet ID

Enter the DataSet ID (GUID) for the DataSet you want to copy to a BigQuery table. You can find the ID by opening the details view for the DataSet in the Data Center and looking at the portion of the URL following datasources/ . For example, in the URL [https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview](https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview) , the DataSet ID is 845305d8-da3d-4107-a9d6-13ef3f86d4a4.

Use BigDecimal (checkbox)

Select this checkbox to use BigDecimal for all numeric values. This option is useful for preserving precision when working with large numbers. Select this option if your data contains numbers with more than 9 decimal places.

Keep Special Characters in Headers (checkbox)

Select this checkbox to keep Special Characters in headers. If this option is not selected and headers of columns contains special characters then these will get replaced with underscore in the generated BigQuery Table.

### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). # Azure Blob Storage Writeback Connector Source: https://www.domo.com/docs/s/article/360043436973 ## Intro Microsoft Azure Blob Storage is designed to easily and efficiently store any type of unstructured data, such as images, videos, audio, and documents. Use this connector to export your data from a Domo DataSet into an Azure Blob container. To learn more about the Azure Blob Storage API, visit their page ([https://docs.microsoft.com/en-us/res...rvice-rest-api](https://docs.microsoft.com/en-us/rest/api/storageservices/blob-service-rest-api "https://docs.microsoft.com/en-us/rest/api/storageservices/blob-service-rest-api") ). You export data to Azure Blob Storage in the Data Center. This topic discusses the fields and menus that are specific to the Azure Blob Storage Writeback connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274 "Adding a DataSet Using a Connector"). **Note:** The owner of a writeback dataset must also be an owner or co-owner of the input dataset. ## Prerequisites To configure this connector, you will need the following: * A Domo Client ID and Client Secret. Learn how to get your [Domo Client ID and Secret](/docs/s/article/000005240#create-api-clients). * The name and key for your Azure Blob Storage account. ## Configuring the Connection This section enumerates the options in the **Credentials** and **Details** panes in the Azure Blob Storage Writeback Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274 "Adding a DataSet Using a Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Domo developer account as well as your Azure Blob Storage container. The following table describes what is needed for each field:

Field

Description

Domo Client ID

Paste your Domo client ID. For more information, see "Prerequisites," above.

Domo Client Secret

Paste your Domo client secret. For more information, see "Prerequisites," above.

Account Name

Enter the name of the Azure Blob Storage account you want to connect to.

Account Key

Enter the account key for the Azure Blob Storage account you want to connect to.

Once you have entered valid credentials, you can use the same account any time you go to set up a new Domo-Azure Blob Storage connection. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing Connectors Accounts](https://domo-support.domo.com/s/article/360042926054 "Managing Connectors Accounts"). ### Details Pane This pane contains a number of fields for specifying your data and indicating where it's going.

Menu

Description

Blob Containers

Select the Azure Blob container you want to send your Domo data to.

Input DataSet ID

Enter the DataSet ID (GUID) for the DataSet you want to copy to the selected Azure Blob Storage container. You can find the ID by opening the details view for the DataSet in the Data Center and looking at the portion of the URL following datasources/ . For example, in the URL [https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview](https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview) , the DataSet ID is 845305d8-da3d-4107-a9d6-13ef3f86d4a4.

Select Filename

Select whether you want to reference your DataSet using the Input DataSet ID or an output file name.

Filename

Enter the output file name for your data.

### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274 "Adding a DataSet Using a Connector"). # Snowflake Writeback Connector Source: https://www.domo.com/docs/s/article/360043437093 **Note:** \*\* Snowflake will no longer support the username and password authentication mechanism as of November 2025. As a result, this connector will be retired in November 2025 and will no longer function. Please consider using one of the following connection methods instead:\*\* * [Cloud Integrations](/docs/s/article/4402322966807) * [Snowflake OAuth Writeback Connector](/docs/s/article/1500011338741) * [Snowflake Key Pair Authentication Writeback Connector](/docs/s/article/360058760154) ## Snowflake Connector Migration Walkthrough As Snowflake is discontinuing username and password authentication, Snowflake connectors using this authentication method will be migrated to the OAuth version. This section helps users walk through the complete process of migrating their existing username and password Snowflake datasets to utilize the OAuth authentication version. Pls refer to the migration video ([https://youtu.be/rlG\_uNZwl\_U](https://youtu.be/rlG_uNZwl_U)) to make the transition smoother and minimize disruptions. ## Intro Snowflake is a data warehouse that makes it easy to bring together all your data and make it available to all of the users and systems that need to analyze it. You can use Domo's Snowflake Writeback connector to push data from a Domo DataSet into a Snowflake database. For more information about the Snowflake API, go to [https://docs.snowflake.net/manuals](https://docs.snowflake.net/manuals). This topic discusses the fields and menus that are specific to the Snowflake Writeback connector user interface. For general information about adding DataSets, setting update schedules, and editing DataSet information, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). **Note:** The owner of a writeback dataset must also be an owner or co-owner of the input dataset. ## Prerequisites To connect to a Snowflake database and create a DataSet, you must have the following: * The full name of your account (provided by Snowflake). This is the portion of your Snowflake URL immediately following https\://. Note that your full account name may include additional segments that identify the region and cloud platform where your account is hosted. The following table provides account name examples by cloud platform/region. For each row, it assumes your account name is "xy12345." snowflake_account_names.png * The username and password for your Snowflake account. * A Domo Client ID and Client Secret. Learn how to [get your Client ID and Secret](/docs/s/article/000005240#create-api-clients). **Important**: You will need the following permissions on Snowflake: * CREATE TABLE * COPY INTO * PUT * CREATE FILE FORMAT * REMOVE * LIST ## Configuring the connection This section enumerates the options in the **Credentials** and **Details** panes in the Snowflake Writeback Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ### Credentials Pane This pane contains fields for entering credentials to your Domo developer account as well as your Snowflake account. The following table describes what is needed for each field:

Field

Description

Account Name

Enter the account name for your Snowflake account. For information about finding your account name, see Prerequisites.

Username

Enter the username associated with your Snowflake account.

Password

Enter the password associated with your Snowflake account.

Role

Enter your role.

Domo Client ID

Enter your Domo client ID.

Domo Client Secret

Enter your Domo client secret.

After you have entered valid credentials, you can use the same account in Domo any time you create a Snowflake Writeback DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054). ### Details Pane This pane contains a number of fields and menus for entering your SQL query and specifying the location of the data you want to retrieve.

Parameter

Description

Input DataSet ID

Enter the DataSet ID (GUID) for the DataSet you want to copy to Snowflake. You can find the ID by opening the details view for the DataSet in the Data Center and looking at the portion of the URL following datasources/. For example, in the URL [https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview](https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview), the DataSet ID is 845305d8-da3d-4107-a9d6-13ef3f86d4a4.

Select Table Name

Select how you want to name the table where data will be copied. - Use Input DataSet GUID. The table name will be the number you entered for InputDataSet ID. - Use Input DataSet Name. The table name will be the same as that of the input DataSet. - Enter Table Name. You will give the table a custom name in the Custom Table Name field.

Enter Table Name

Enter the name of the Snowflake table you want your data copied to (spaces and special characters will be replaced with underscores).

Warehouses

Select the warehouse containing the table you want to send data to.

Databases

Select the database containing the table you want to send data to.

Database Schema

Select the database schema containing the data you want to retrieve.

### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ### FAQs The Domo Snowflake Writeback connector allows you to write data from a Domo dataset to a Snowflake instance using a local username and password in your Snowflake instance. If you do not already have the connector enabled, please contact your Domo Account Executive. You need the CREATE TABLE, COPY INTO, PUT, CREATE FILE FORMAT, REMOVE, and LIST permissions on Snowflake. You need the full name of your account (provided by Snowflake), Domo client credentials (client ID and client secret), and Snowflake credentials (username and password). Learn how to get your [Domo Client ID and Secret](/docs/s/article/000005240#create-api-clients). As often as needed. Limits depend on your server configuration. Yes Before you can connect to a Snowflake database in Domo, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses](/docs/s/article/360043630093). Your Domo input dataset id is in the URL of the dataset you are exporting data from. For example: [https://customer.domo.com/datasources/aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee/details/settings](https://customer.domo.com/datasources/aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee/details/settings) # Domo Platform Tour Source: https://www.domo.com/docs/s/article/360043442453 ## Intro Welcome to Domo! Let's explore the key features and tools you'll use in your Domo instance. This guide will help you find and utilize the essential elements of Domo effectively. *** ## Dashboards You can access your dashboards in the left navigation by selecting **Features** > **Dashboards**. ### Manage Dashboards From the **Dashboards** side panel, select **Manage Dashboards** to create new dashboards or customize the order of existing dashboards. Remember, your arrangement doesn't affect other users. Screenshot #### Create a Sub-Dashboard Sub-dashboards add a layer of organization to the dashboard view. To create a sub-dashboard from the **Manage Dashboards** modal, select the arrow next to a top-level dashboard and select **Add a sub-Dashboard**. Screenshot ## Appstore Visit the [Domo Appstore](https://www.domo.com/appstore/) to find premade dashboards and apps where you can plug in your data and go. You can also access our collection of hundreds of connectors to bring your data into Domo. Screenshot ## Data After you bring your data into Domo, you can access it in the DataSets feature. From the left navigation, select **Features** > **DataSets**. Screenshot Going to DataFlows in the left navigation (**Features** > **DataFlows**) allows you to use ETL (Extract, Transform, and Load) processes, which are crucial for preparing your data. Screenshot ## Alerts You can configure Alerts to notify you about significant changes, like a 20 percent drop in sales. They can be sent via email, text, or via the Domo app.\\ Learn more about [Alerts](/docs/s/article/360043430373). Screenshot ## User Profile Choose your avatar at the bottom of the left navigation and select **Profile** to open your user profile. Screenshot ## Admin Settings Going to **Admin** in the left navigation displays the admin settings. Screenshot ## ## Help Resources There are many options to get help with Domo. ### Support Follow these steps to contact our support team: 1. Choose your avatar in the left navigation and select **Help Center**. Screenshot 2. In the Help Center, select **Support** in the top right corner. ### Community Forums The Community Forums are an excellent resource for questions, with an average response time of 30 minutes. Visit the [forums](https://community-forums.domo.com/main) . Screenshot ### Education Domo Education offers self-paced, virtual, and in-person training courses, based on your Support + Education bundle. You can also complete the Domo certification and build your resume. Visit [Domo University](https://www.domo.com/domo-central/university) or learn more about the [courses](/docs/s/article/360042935754) offered. Screenshot # Snowflake Federated Data Setup Source: https://www.domo.com/docs/s/article/360049429094 ## Intro Domo has a new streamlined Federated connection setup experience for cloud native data warehouses, starting exclusively with Snowflake. You can directly setup a Snowflake connected account from Domo's Data Center experience and use that to create Federated DataSets from your Snowflake database tables. *** ## Prerequisites To connect to your data in your Snowflake data warehouse, you need standard connection parameters such as your Snowflake account name, warehouses, databases to connect to, and the username/password. In general, you can start with a small-sized warehouse, however, we recommend a multi-cluster configuration which allows Snowflake to auto-scale to additional warehouses as needed to support your query volume. ## Setup Process 1. Start with Domo's data warehouse platter visualization and click on the **+** **Add New Data Warehouse** button. Warehouse_step_1.png 2. Select **Snowflake** Driver and click **Next**. Warehouse_step_2.png 3. Enter your connection parameters specific to the Snowflake database you need to connect to. The following fields are required: 1. Account Name (to reference within Domo.) 2. Host – This is the Snowflake account name for your Snowflake account. Note that your full account name may include additional segments that identify the region and the cloud service provider where your Snowflake account is hosted e.g. [xyz1234.us](http://xyz1234.us) -east-1, xyz1234.west-europe.azure, etc. You need to provide your full hostname, e.g. *[yourcompany.snowflakecomputing.com](http://yourcompany.snowflakecomputing.com)* 3. Warehouse – Existing Snowflake warehouse you need want to use to send queries from Domo. We recommend setting a warehouse specific to Domo. 4. Username – Snowflake username you want to connect with. We recommend creating a new user in your Snowflake account specifically to service Federated queries from Domo. 5. Password – Password for your username. 6. Role and Port are optional depending on your Snowflake account setup. Warehouse_step_3.png 4. You should have a Snowflake federate account created now. Common errors are typically due to incorrect connection parameters. Please contact Support for any help needed. Warehouse_step_4.png 5. To create a new Federated DataSet, click on **Federated** in the connect data section of the header in the Data Center. Warehouse_step_5.png 6. You will see a list of available databases in Snowflake, and you can choose the database and the specific table you want to create the Federated DataSet from. The Pane on the right shows you a preview of the data from your Snowflake table. 2.png 7. Enter the name for the DataSet (how you want to reference it in Domo), and you can optionally select a TTL for the cache. The default TTL value for cache is recommended at 900 seconds (15 minutes). If your Snowflake database table is expected to update faster than 15 minutes then you can choose a lower TTL. On the preview pane on the right, you can also toggle between viewing a preview of the data or viewing the schema of the table being used. Click the **Create** button to complete your Domo Federated DataSet creation. Warehouse_step_6.png 8. You now have a DataSet created in Domo from your Snowflake data! You can create Cards using Analyzer from this DataSet, but ETL, SQL DataFlows and DataSet Alerts are not available to operate on Federated DataSets. Warehouse_step_8.png Warehouse_step_9.png ## FAQ Domo uses native Snowflake connectivity to query data from your Snowflake tables. You can bring data into Domo by using Domo's 1000+ Connectors supporting various sources. Once your data is in Domo, and transformed as needed, you can use Domo's Snowflake Write-Back connector to push data into your Snowflake warehouse. Write-Back connectors are part of Domo's [Integration Studio](https://www.domo.com/product/integration-studio "https://www.domo.com/product/integration-studio") suite. More information on setting up Snowflake Write-Back connector can be found [here](https://domohelp.domo.com/Connect/Connecting_to_Data_with_Connectors/Configuring_Each_Connector/Writeback_Connectors/Snowflake_Writeback_Connector "https://knowledge.domo.com/Connect/Connecting_to_Data_with_Connectors/Configuring_Each_Connector/Writeback_Connectors/Snowflake_Writeback_Connector"). Specific limits on accounts and DataSets depend on your account tier. Please contact your CSM or AE for more details. Warehouse sizing depends on how many DataSets, Dashboards, and Visualizations you have in Domo. At a minimum, we recommend a medium sized warehouse (M), and Auto Resume set to ON. For the best Domo and Snowflake experience, we recommend using a Large Snowflake warehouse (L). If you want to Auto suspend your warehouse during periods of inactivity, you can set that as needed. Domo can help you with sizing your Snowflake warehouses as your Domo usage changes. Alerts are supported for Domo Cards built from Federated DataSets. However, DataSet Alerts are not supported currently. Yes, Domo's interactive, easy to use DataSet views feature can be used to explore Snowflake Federated DataSets. You can filter, group, limit, sort, and join DataSets, as well as create new calculated columns and save your transformation as new DataSet Views. These DataSet Views are virtual in Domo, and do not create Views in the customer Snowflake cata warehouse. No, currently this isn't supported, but we would love to understand your use case. Please reach out via your CSM or AE to talk to Domo's product team. The "last run" time on a Snowflake Federated DataSet indicates the last time the schema was changed. Often this is when the DataSet was created. But if you edit the schema, the "last run" value updates. Viewing data on-screen and exporting data are subject to different timeouts within Domo. These timeouts only apply to the Domo side of the action and are not issued to Snowflake. However, Domo does respect the Snowflake session timeout. Examples: * If a card cannot be rendered within the Domo timeout, an error message is displayed on-screen, but the Snowflake query is not canceled. That query is then subject to the timeout defined in Snowflake. * If a card cannot be rendered within the Snowflake timeout, and that timeout is less than the Domo timeout, an error message is displayed on-screen and the query is canceled (from the Snowflake side). Timeouts: * Cards will attempt to render on-screen for up to 1-minute. * Exports, both from cards and DataSets, will attempt to export for up to 12-hours. To change the Snowflake session timeout, adjust the STATEMENT\_TIMEOUT\_IN\_SECONDS session parameter. We recommend adjusting this setting based on the primary usage of your DataSets. For example, if they're primarily used for exporting, you may want a longer timeout than if the DataSets are primarily being used to render cards in Domo. # Amazon Redshift Partition Connector Source: https://www.domo.com/docs/s/article/360052884873 ## Intro The Amazon Redshift is a fast, scalable data warehouse that makes it simple and cost-effective to analyze all your data across your data warehouse and data lake. Domo can make your Redshift data come to life. Whether it's one Redshift datasource or a thousand different datasources, bring them all into Domo for a centralized experience to view and analyze everything at the same time. By partitioning your data, you can restrict the amount of data scanned by each query, thus improving performance and reducing cost. Use Domo's Amazon Redshift Partition Connector to connect directly to Redshift and deliver the information you need in real-time visualizations based on the number of past days provided. It make analysis easier. To learn more about the Amazon Redshift API, visit [http://docs.aws.amazon.com/redshift/latest/dg/c\_SQL\_commands.html](http://docs.aws.amazon.com/redshift/latest/dg/c_SQL_commands.html "http://docs.aws.amazon.com/redshift/latest/dg/c_SQL_commands.html"). The Amazon Redshift Partition connector is a "Database" connector, meaning it retrieves data from a database based on a query. In the Data Center, you can access the connector page for this and other Database connectors by clicking ****Database**** in the toolbar at the top of the window. You connect to your Amazon Redshift account in the Data Center. This topic discusses the fields and menus that are specific to the Amazon Redshift Partition connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). **Note:** The updated method "Append" or "Merge" needs to be used for the data to be visible.
Primary Use Cases Pulling data out of a Redshift data warehouse or data mart.
Primary Metrics This depends on the data stored in the Redshift instance.
Primary Company Roles
  • BI leads

  • IT roles

Average Implementation Time Anywhere between 5 and 40 hours, depending on configuration settings and the amount of data you are pulling.
Ease of Use (on a 1-to-10 scale with 1 being easiest) 6
## Best Practices Try to limit the results set size as much as possible. To speed the acquisition of the data, "fetch size" can be increased; however, setting it too high can cause connector run failures as well as performance problems with the Redshift instance. 400 is a good place to start. ## Prerequisites To connect to a Redshift database and create a DataSet, you must have the following: * The username and password you use to log into your Redshift database * The host name for the database server (Example: [db.company.com](http://db.company.com) ) * The port number for the database * The database name CA certificate text or URL path is required **only** if you select ****Certificate String**** or ****URL Path****, respectively, in the ****Certificate Format**** menu. ### Creating a Redshift account To create a Redshift user account, contact your Redshift Database Administrator (DBA) and have them follow these directions: By default, only the master user that you created when you launched the cluster has access to the initial database in the cluster. To grant other users access, you must create one or more user accounts. Database user accounts are global across all the databases in a cluster; they do not belong to individual databases. Use the CREATE USER command to create a new database user. When you create a new user, you specify the name of the new user and a password. A password is required. It must have between 8 and 64 characters, and it must include at least one uppercase letter, one lowercase letter, and one numeral. For example, to create a user named GUEST with password ABCd4321, use the following command: `create user guest password 'ABCd4321';` ### Whitelisting IP addresses Before you can connect to a Redshift database, you must also white list a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses for Connectors](https://domo-support.domo.com/s/article/360043439173?language=en_US "Whitelisting IP Addresses for Connectors"). ## Connecting to Your Redshift Account This section enumerates the options in the **Credentials** and **Details** panes in the Amazon Redshift Partition Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). ## Credentials Pane This pane contains fields for entering credentials to connect to your Redshift database. The following table describes what is needed for each field:

Field

Description

JDBC Driver Select the JDBC driver you want to use to connect.
Host Enter the host string to connect to the SQL database. Example: // examplecluster.cpdbcwb2mzr4.us-east-2.redshift.amazonaws.com
Database Enter the name of the database.
Username Enter your Redshift username.
Password Enter your Redshift password.
Database Port Enter the port number for the database.
Certificate Format Select the certificate format. If you do not want to include a certificate, select No Certificate . If you select Certificate String , you must paste the text for your certificate in the Certificate field. If you select URL Path , you must enter the URL where your certificate is located in the Certificate field.
Certificate Paste the text for your CA certificate or enter the URL where your certificate is located. This is optional. If you do not want to include a certificate, select No Certificate in the Certificate Format menu.
Once you have entered valid Redshift credentials, you can use the same account any time you go to create a new Amazon Redshift Partition DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](https://domo-support.domo.com/s/article/360042926054?language=en_US "Managing User Accounts for Connectors"). ## Details Pane In this pane you create an SQL query to pull data from your database. You can choose a specific database table and partition column name. You can also specify the number of past days you want to get data for.

Menu

Description

Query Enter the SQL query to execute. Example: select \* from Employee
Database Tables Select the database table you want to appear in your report.
Partition Column Name Select the partition column name.
Past Days Enter number of past days for which you want to get data. Value can be X, where X is a positive integer. Example: 30.
Date Format Select the required date format. By default yyyy-MM-dd will be used.
Custom Date Enter the custom date format you wish to apply to your data.
Fetch Size Enter fetch size for memory performance. If it is blank, default value will be 400.
## Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). ## Troubleshooting If you run into connection issues... * Verify the connection works using pgAdmin. * Confirm if all necessary Domo IPs have been white listed (see [Whitelisting IP addresses](https://domo-support.domo.com/s/article/360043439173?language=en_US "Amazon Redshift Partition Connector"), above). * Run a profile on the SQL query. # Microsoft Azure Storage Data Lake Gen2 Connector Source: https://www.domo.com/docs/s/article/360056826394 ## Intro Azure Data Lake Store is an enterprise-wide hyper-scale repository for big data analytic workloads. Use this connector to pull data files from your Data Lake Store into Domo. You can retrieve data files in any of the following file types: CSV, XLS, XLSX and JSON. For more information about Azure's API, see [https://docs.microsoft.com/en-us/azu...ta-lake-store/](https://docs.microsoft.com/en-us/azure/data-lake-store/ "https://docs.microsoft.com/en-us/azure/data-lake-store/"). You connect to your Microsoft Azure Storage Data Lake Gen2 account in the Data Center. This topic discusses the fields and menus that are specific to the Microsoft Azure Storage Data Lake Gen2 connector user interface. To add DataSets, set update schedules, and edit DataSet information, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Prerequisites To connect to your Microsoft Azure Data Lake Store Gen2 account and create a DataSet, you must have the following: * Account key * Account name To obtain credentials, please reach out to your Microsoft account representative. ## Connecting to Your Microsoft Azure Storage Data Lake Gen2 Account This section enumerates the options in the **Credentials** and **Details** panes on the Microsoft Azure Storage Data Lake Gen2 Connector page. The components of the other panes on this page, **Scheduling**, and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in great detail in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Microsoft Azure Storage Data Lake Gen2 account. The following table describes what is needed for each field:

Field

Description

Account Key Enter your Microsoft Azure Storage Data Lake Gen2 account key.
Account Name Enter your Microsoft Azure Storage Data Lake Gen2 account name.
Once you have entered valid Microsoft Azure Storage Data Lake Gen2 credentials, you can use the same account any time you go to create a new Microsoft Azure Storage Data Lake Gen2 DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Manage Connector/Adapter Accounts](https://domo-support.domo.com/s/article/360042926054?language=en_US "Manage Connector/Adapter Accounts"). ### Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

Report

Select the Microsoft Azure Storage Data Lake Gen2 report you want to run. The following reports are available:

Directory ACL Status Retrieves the access control status for a directory in Data Lake Store account.
Directory Information Retrieves the metadata for a directory in Data Lake Store account.
Download File Imports the content of a selected file into a Domo DataSet.
File ACL Status Retrieves the access control status for a file in Data Lake Store account.
File Information Retrieves the metadata for a file in Data Lake Store account.
File System Select your file system.
How Would You Like to Choose Your File Name? Select how you want to choose the file you intend to import into Domo. Select Files Discovery to choose your file from a list of files. Select Enter File Name to enter the name yourself.
File Name Enter the name of the file you want to import into Domo.
Select File Select the file you want to import into Domo.
File Format Select the format of the file you want to import. Options include CSV, XLS, XLSX, and JSON.
Delimeter Select the delimiter to use to parse your CSV file. To choose a custom delimiter, select Other , then enter your delimiter in the Custom Delimiter field.
Custom Delimiter Enter the custom delimiter you want to use to parse your CSV file. Enter tab or Unicode characters in \uxxxx form (e.g. \u005e).
Quote Character Select the desired quote character for parsing your CSV file. (A double quote is the CSV standard.) To choose a custom quote character, select Other , then enter your quote character in the Custom Quote Character field.
Custom Quote Character Enter the custom quote character you want to use to parse your CSV file. Enter tab or Unicode characters in \uxxxx form (e.g. \u005e).
Escape Character Select the escape character to use to parse your CSV file. To choose a custom escape character, select Other , then enter your delimiter in the Custom Escape Character field.
Custom Escape Character Enter the desired CSV escape character. Enter Unicode chars in \uxxxx form (e.g. \u005E).
Check this box to validate csv file Select this checkbox to validate the CSV file.
Header Start Row (Optional) Enter the header start row for your Excel file.
Data Start Row (Optional) Enter the data start row for your Excel file.
Footer Rows to Skip (Optional) Enter the number of rows to skip at the end of your Excel file, if any.
Sheet Name (Optional) If your Excel file contains more than one sheet, enter the name of the sheet you want to import. Be sure to check the sheet name for accidental spaces. If this field is left blank, the first sheet of the workbook will be used.
Data Field Key (Optional) Enter the data field key for the JSON file you want to import.
Sublist to Flatten (Optional) Enter the lists you want to flatten in your data. Separate multiple lists with commas.
### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## FAQs You need to create a Storage Account to get the account name and account key. To obtain the account name, follow the below steps: 1. Visit [Microsoft Azure Portal](https://portal.azure.com/ "Microsoft Azure Portal") and sign in using your Microsoft credentials. 2. Select **Storage accounts**. 3. Find your storage account and click on it. 4. Click the menu icon to the right of the title, and select 'Copy title to clipboard'. To obtain the account key, follow the below steps: 1. Visit Microsoft Azure Portal and sign in using your Microsoft credentials. 2. Select Storage accounts. 3. Find your storage account and click on it. 4. Open Security + networking > Access keys. 5. Click the 'Show' button on key1 or key2 and copy the value. Azure Data Lake Storage Gen2 requires that the Hierarchical namespace in the storage account be Enabled. If this is Disabled, the Connector will not be able to retrieve directory information and will not be able to retrieve the files. To Enabled, click the Disabled of the Hierarchical namespace section and follow the guidance to upgrade your storage account to Azure Data Lake Storage Gen2. # MySQL Partition Connector Source: https://www.domo.com/docs/s/article/360056826694 ## Intro MySQL is a widely used open-source relational database management system. With Domo's MySQL integration, you can easily connect your MySQL data and make faster decisions. Partitioning enables the table data to be divided across multiple storage objects (data partitions), according to the values in one or more table columns based on a set of user-defined rules. Use Domo's MySQL Partition connector to optimize the way the database engine physically stores data. You connect to your MySQL Partition account in the Data Center. This topic discusses the fields and menus that are specific to the MySQL Partition connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). **Notes:** * This connector supports TLS IF your MySQL server supports TLS. * Non SSL connections are not supported. If no certificate is provided, the connection is still SSL but without any certificate authentication. The connection will trust all server certificates. Refer to the following link for details: [https://msdn.microsoft.com/en-us/library/bb879949%28v=sql.110%29.aspx](https://msdn.microsoft.com/en-us/library/bb879949%28v=sql.110%29.aspx) Prerequisites To connect to your MySQL Partition account and create a DataSet, you must have the following: * The username and password you use to log into your MySQL database. * The host name for the database. * The port number for the database. * The database name or schema name. * SSL * You can also include the URL where your SSL CA Certificate is located, though this is optional. Before you can connect to a MySQL database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses for Connectors](/docs/s/article/360043630093 "Whitelisting IP Addresses for Connectors"). ## Connecting to Your MySQL Partition Account This section enumerates the options in the **Credentials** and **Details** panes in the MySQL Partition Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your MySQL Partition account. The following table describes what is needed for each field:

Field

Description

JDBC Driver Select the JDBC driver to use to connect to the database server.
Host Enter the host name for the MySQL database. For example: db.company.com
Port Enter the port number for the database.
Database Name Enter the name of the MySQL database or schema.
Username Enter your MySQL username.
Password Enter your MySQL password.
CA Certificate Enter the URL where the SSL CA Certificate is located (optional).
Once you have entered valid credentials, you can use the same account any time you go to create a new MySQL Partition DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane In this pane you specify the attributes and conditions to partition your data.

Menu

Description

Query Enter the SQL query to execute.
Table Name Select the database table.
Partition Column Name Select partition column name.
Past Days Enter the number of past days you want to get data for. Value can be a positive integer. For example: 30.
Date Format Select the required date format. By default yyyy-MM-dd will be used.
Select if you want to compress the data Choose the way you want the data to be uploaded. Select True, if you want the data to be compressed while uploading, else select False.
Tinyint values treated as (bit) boolean values Select Yes if you want the tiny integer values to be treated as boolean values, else select No.
Cast Boolean Values to... Select whether the String or Integer boolean values will be cast to within your dataset.
String: False/True
Integer: 0/1
### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). # Snowflake Partition Connector Source: https://www.domo.com/docs/s/article/360057013754 **Note:** Snowflake will no longer support the username and password authentication mechanism, as of November 2025. As a result, this connector will be retired in November 2025 and will no longer function. Consider using one of the following connection methods instead: * [Cloud Integrations](/docs/s/article/4402322966807) * [Snowflake KeyPair Partition Connector](/docs/s/article/1500000888261) * [Snowflake OAuth High Bandwidth With Advanced Partitions](/docs/s/article/4402638182935) ## Snowflake Connector Migration Walkthrough As Snowflake is discontinuing username and password authentication, Snowflake connectors using this authentication method will be migrated to the OAuth version. This section helps users walk through the complete process of migrating their existing username and password Snowflake datasets to utilize the OAuth authentication version. Pls refer to the migration video ([https://youtu.be/rlG\_uNZwl\_U](https://youtu.be/rlG_uNZwl_U)) to make the transition smoother and minimize disruptions. ## Intro Snowflake is a cloud-based analytic data warehouse system. The Domo Snowflake Partition Connector makes it easy to bring all your data from your Snowflake data warehouse into Domo based on the number of past days provided. If you are already using Snowflake as a data warehousing solution, this connector helps you use Domo in conjunction with it to get the most from your data. Once your Snowflake data is in Domo, you can combine it with all your other Domo data to get a centralized view of your most mission-critical data. To learn more about the Snowflake API, visit their page ([https://docs.snowflake.net/manuals](https://docs.snowflake.net/manuals)). You connect to your Snowflake account in the Data Center. This topic discusses the fields and menus that are specific to the Snowflake Partition connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). *** ## Prerequisites To connect to your Snowflake account and create a DataSet, you must have the following: * The full name of your account (provided by Snowflake). For US West Region **account\_name**, and All other regions **account\_name.region\_id**. This is the portion of your Snowflake URL immediately following https\://. Note that your full account name may include additional segments that identify the region and cloud platform where your account is hosted. The following table provides account name examples by cloud platform/region. For each row, it assumes your account name is "xy12345." Region.png - The username and password used to connect to your Snowflake host. ## Connect to Your Snowflake Account This section enumerates the options in the **Credentials** and **Details** panes in the Snowflake Partition Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Credentials Pane This pane contains fields for entering credentials to connect to your (third-party tool) account. The following table describes what is needed for each field:

Field

Description

Account Name

Enter the name of your account (provided by Snowflake). For US West Region account\_name, and All other regions account\_name.region\_id.

Username

Enter the username associated with your Snowflake host.

Password

Enter the password associated with your Snowflake host.

Role

Enter your role.

Once you have entered valid Snowflake credentials, you can use the same account any time you go to create a new Snowflake Partition DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054). ## Details Pane In this pane you create an SQL query to pull data from your database. You can choose a specific database table and partition column. You can also specify the number of past days you want to get data for.

Menu

Description

How would you like to import data into Domo?

Select whether you want to import your data by using the standard update method (replace/append), by using partition, or upsert mode.

How would you like to build your Query?

Query

Enter the query to execute. The query format must be like: select \* from "databaseName"."schemaName"."tableName"

Warehouses

Select the warehouse containing the data you want to retrieve. The list populates all warehouses you have access to based on your credentials.

Databases

Select the database containing the data you want to retrieve. The list populates all databases you have access to based on your credentials.

Schemas

Select the database schema containing the data you want to retrieve. The list populates all schemas you have access to based on your credentials.

Database Objects

Select the database object containing the data you want to retrieve. The list populates all objects you have access to based on your credentials.

Tables

Select the database table you want to retrieve. The list populates all tables you have access to based on your credentials. If you do not select a database table, the connector retrieves your entire database schema.

Views

Select the view.

Table Column Name

Select the partition column name.

Table Query Helper

A query is generated based on the selected fields. Copy and paste this text into the QUERY field. You may edit this query, if desired.

View Column Name

Select the partition column name.

View Query Helper

A query is generated based on the selected fields. Copy and paste this text into the QUERY field. You may edit this query, if desired.

Partition Criteria

Select whether you want to partition your data using the date keys, non-date keys, or meta query.

Partition Column Name

Select the partition column name. Only date fields will be shown in this discovery.

Partition Support Format

Select the partition support format.

Partition Non Date Key Column Name

Select a non-date key column name to partition the data. All fields excluding Date fields will appear in this dropdown.

Partition Query to determine partition tags

Enter the partition meta query to determine the distinct partition tags (or keys). The column containing the Date data is your partition column. Example: SELECT DISTINCT (DATE\_COLUMN\_NAME) FROM TABLENAME

Past Days

Enter the number of past days that you want to get data for. Value can be X, where X is a positive integer. Example: 30.

Past Years

Enter the number of past years that you want to get data for. Value can be X, where X is a positive integer. For example: 30.

Future Years

Enter the number of future years that you want to get data for. Value can be X, where X is a positive integer. For example: 30.

Past Months

Enter the number of past months that you want to get data for. Value can be X, where X is a positive integer. For example: 30.

Future Months

Enter the number of future months that you want to get data for. Value can be X, where X is a positive integer. For example: 30.

Date Format

Please select/enter proper date format according to the date format present in partition column. By default yyyy-MM-dd will be used.

Custom Date Format

Enter the custom date format.

Upsert Key Column(s)

Enter upsert key column name or a comma separated list of upsert key column names. Required only when Update method is Merge.

Query Tag

Optional parameter that can be used to tag connector SQL executions in Snowflake as a Query Tag.

### Selecting the Update Mode Once you decide how you want to import your data into Domo (by using the standard update method (replace/append), by using partition, or upsert mode), you need to select the relevant update mode in the **Scheduling section** in the Connector. * If you select 'Partition' in the Details section, then you need to select the 'Append' update mode in the Scheduling section. Partition-Append.png * If you select 'Upsert' in the Details section, then you need to select 'Merge' update mode in the Scheduling section. Upsert-Merge.png ## Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). # Azure DataLake Gen2 SAS Token Writeback Connector Source: https://www.domo.com/docs/s/article/360057028134 ## Intro Azure Data Lake Storage Gen2 is a set of capabilities dedicated to big data analytics, built on Azure Blob storage. Azure Data Lake Storage Gen2 is the result of converging the capabilities of the two existing storage services, Azure Blob Storage and Azure Data Lake Storage Gen1. Use Domo's Azure Data Lake Gen2 SAS Token Writeback connector to export your data from a Domo dataset to your Azure Data Lake Gen2 container. For more information about Azure Data Lake Gen2, see [https://docs.microsoft.com/en-us/azu...ta-lake-store/](https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-introduction "https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-introduction"). You export data to an Azure Data Lake Gen2 in the Data Center. This topic discusses the fields and menus that are specific to the Azure Data Lake Gen2 Writeback connector user interface. To add DataSets, set update schedules, and edit DataSet information, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). **Note:** The owner of a writeback dataset must also be an owner or co-owner of the input dataset. ## Prerequisites To configure this connector, you need the following: * Your Azure Data Lake storage account name * The Shared Access Signature (SAS) Token ## Configuring the Connection This section enumerates the options in the **Credentials** and **Details** panes on the Azure Data Lake Gen2 SAS Token Writeback Connector page. The components of the other panes on this page, **Scheduling**, and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Azure Data Lake file system (container). The following table describes what is needed for each field:

Field

Description

Account Name Enter your Azure Data Lake storage account name.
Shared Access Signature (SAS) Token Enter the shared access signature token.
Once you have entered valid credentials, you can use the same account any time you go to set up a new Domo-Azure Data Lake Storage Gen2 connection. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Manage Connector Accounts](https://domo-support.domo.com/s/article/360042926054?language=en_US "Manage Connector Accounts"). ### Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

Input DataSet ID

Enter the DataSet ID (GUID) for the DataSet you want to copy to the selected Azure Data Lake Storage file system (container). You can find the ID by opening the details view for the DataSet in the Data Center and looking at the portion of the URL following datasources/. Example, in the URL [https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview](https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview) , the DataSet ID is 845305d8-da3d-4107-a9d6-13ef3f86d4a4.

File System Name Enter the file system name where you wish to upload the file. A file system acts as a container for your files.
Select Filename Select whether you want to reference your DataSet using the Input DataSet ID or an output file name.
Filename Enter the output file name for your data.
### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). # Azure Data Lake Storage Gen2 WriteBack Source: https://www.domo.com/docs/s/article/360057028154 ## Intro Azure Data Lake Storage Gen2 is the world's most productive Data Lake. It makes Azure Storage the foundation for building enterprise data lakes on Azure. It allows you to easily manage massive amounts of data and helps to speed up your transition from proof of concept to production. Azure Data Lake Storage Gen2 is a set of capabilities dedicated to big data analytics, built on Azure Blob storage. Azure Data Lake Storage Gen2 is the result of converging the capabilities of the two existing storage services, Azure Blob storage and Azure Data Lake Storage Gen1. Use Domo's Azure Data Lake Storage Gen2 WriteBack connector to export your data from a Domo dataset to your Microsoft Azure Data Lake Gen2 container. For more information about Microsoft Azure Data Lake Gen2, see [https://docs.microsoft.com/en-us/azu...ta-lake-store/](https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-introduction "https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-introduction"). You export data to a Azure Data Lake Gen2 in the Data Center. This topic discusses the fields and menus that are specific to the Azure Data Lake Storage Gen2 WriteBack user interface. To add DataSets, set update schedules, and edit DataSet information, see [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). **Note:** The owner of a writeback dataset must also be an owner or co-owner of the input dataset. ## Prerequisites To configure this connector, you need the following: * Your Microsoft Azure Data Lake Storage account name * Your Microsoft Azure Data Lake Storage account key ## Configuring the Connection This section enumerates the options in the ****Credentials**** and ****Details**** panes in the Azure Data Lake Storage Gen2 WriteBack Connector page. The components of the other panes in this page, ****Scheduling**** and ****Name & Describe Your DataSet****, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Azure Data Lake file system (container). The following table describes what is needed for each field:

Field

Description

Account Name Enter your Microsoft Azure Data Lake storage account name.
Account Key Enter your Microsoft Azure Data Lake storage account key.
Once you have entered valid credentials, you can use the same account any time you go to set up a new Domo-Azure Data Lake Storage Gen2 connection. You can manage connector accounts in the ****Accounts**** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](https://domo-support.domo.com/s/article/360042926054?language=en_US "Managing User Accounts for Connectors"). ### Details Pane This pane contains a primary ****Reports**** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

Input DataSet ID

Enter the DataSet ID (GUID) for the DataSet you want to copy to the selected Azure Data Lake Storage file system (container). You can find the ID by opening the details view for the DataSet in the Data Center and looking at the portion of the URL following datasources/. Example, in the URL [https://mycompany.domo.com/datasourc...tails/overview](https://mycompany.domo.com/datasourc...tails/overview) , the DataSet ID is 845305d8-da3d-4107-a9d6-13ef3f86d4a4.

File System Name Enter the file system name where you wish to upload the file. A file system acts as a container for your files.
Select Filename Select whether you want to reference your DataSet using the Input DataSet ID or an output file name .
Filename Enter the output file name for your data.
### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). # Snowflake Managed Unload Connector Source: https://www.domo.com/docs/s/article/360058757134 **Note:** Snowflake will no longer support the username and password authentication mechanism as of November 2025. As a result, this connector will be retired in November 2025 and will no longer function. Please consider using one of the following connection methods instead: * [Cloud Integrations](/docs/s/article/4402322966807) * [Snowflake Key Pair Internal Managed Unload Connector](/docs/s/article/360061224493) * [Snowflake OAuth Internal Unload v2 Connector](/docs/s/article/1500010196881) ## Snowflake Connector Migration Walkthrough As Snowflake is discontinuing username and password authentication, Snowflake connectors using this authentication method will be migrated to the OAuth version. This section helps users walk through the complete process of migrating their existing username and password Snowflake datasets to utilize the OAuth authentication version. Pls refer to the migration video ([https://youtu.be/rlG\_uNZwl\_U](https://youtu.be/rlG_uNZwl_U)) to make the transition smoother and minimize disruptions. ## Intro Snowflake is a cloud-based analytic data warehouse system. Use Domo's Snowflake Managed Unload connector to unload data from your Snowflake database into internal Amazon S3. The files are then downloaded from internal S3 into Domo. This connector should be preferred over the other Snowflake connectors if you are executing very large queries. To learn more about the Snowflake API, visit their page ([https://docs.snowflake.net/manuals](https://docs.snowflake.net/manuals)). You connect to your Snowflake Managed Unload account in the Data Center. This topic discusses the fields and menus that are specific to the Snowflake Managed Unload connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Prerequisites To connect to your Snowflake Managed Unload account and create a DataSet, you must have the following: * The full name of your account (provided by Snowflake). For US West Region **account\_name**, and All other regions **account\_name.region\_id**. This is the portion of your Snowflake URL immediately following https\://. Note that your full account name may include additional segments that identify the region and cloud platform where your account is hosted. The following table provides account name examples by cloud platform/region. For each row, it assumes your account name is "xy12345." snowflake_account_names.png - The username and password used to connect to your Snowflake host. Snowflake Managed Unload Connector requires more permissions than a regular Snowflake Connector. Here is the list of commands for roles and permissions: | | | | ---------------------- | --------------------------------------------------------------------------------- | | CREATE STAGE | Creates a new stage to unload data from tables into files | | COPY INTO `` | command to unload all the rows from a table into one or more files into the stage | | CREATE FILE FORMAT | Creates a file format | | LIST | Returns a list of files that have been staged | | GET | Downloads data files from the above created Snowflake stage | | REMOVE | Removes files that have been staged - unloaded from a table | ## Connecting to Your Snowflake Managed Unload Account This section enumerates the options in the **Credentials** and **Details** panes in the Snowflake Managed Unload Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Credentials Pane This pane contains fields for entering credentials to connect to your Snowflake Managed Unload account. The following table describes what is needed for each field:

Field

Description

Account Name

Enter your Snowflake account name. For more information, see Prerequisites.

Username

Enter the username you use to connect to your Snowflake host.

Password

Enter the password you use to connect to your Snowflake host.

Role

Enter your role.

Once you have entered valid Snowflake Managed Unload credentials, you can use the same account any time you go to create a new Snowflake Managed Unload DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054). ## Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

Report

Select the Query Type. The following query types are available:

Query

Enter the SQL query to retrieve your data. You can use the Query Helper parameter to help you write a usable SQL query. To use the Query Helper, do the following: 1. Select your desired warehouse, database, database schema, database object, and table columns or views in each menu. 2. Copy the SQL statement that appears in the Query Helper field. 3. Paste the copied SQL statement into the Query field.

Warehouses

Select the warehouse containing the data you want to retrieve. The list populates with all of the warehouses you have access to based on your credentials.

Databases

Select the database containing the data you want to retrieve. The list populates with all of the databases you have access to based on your credentials.

Database Schemas

Select the database schema containing the data you want to retrieve. The list populates with all of the schemas you have access to based on your credentials.

Database Objects

Select the database object containing the data you want to retrieve. The list populates with all of the objects you have access to based on your credentials.

Database Views

Select the database view you want to retrieve. The list populates with all of the views you have access to based on your credentials. If you do not select a database view, the connector retrieves your entire database schema.

Database Tables

Select the database table you want to retrieve. The list populates with all of the tables you have access to based on your credentials. If you do not select a database table, the connector retrieves your entire database schema.

Table Columns

Select the table columns you want to retrieve. The list populates with all of the columns you have access to based on your credentials. If you do not select a table column, the connector retrieves your entire selected database table.

Query Helper

When you select warehouses, databases, schemas, tables, etc. from the above menus, a usable SQL query is built for you in this field. Copy and paste the SQL statement in this field into the Query field. For more information, see Query, above.

Partition Support

Choose whether or not to partition your data.

Past Days

Enter the number of past days that you want to get data for. Value can be X, where X is a positive integer. For example: 30.

Date Format

Select the required date format. By default, yyyy-MM-dd will be used.

Custom Date Format

Enter the custom date format.

Query Tag

Optional parameter that can be used to tag connector SQL executions in Snowflake as a Query Tag.

## Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQs The Snowflake KeyPair Internal Managed Unload connector imports data to DOmo from Snowflake by first unloading data to a user-defined S3 bucket before ingesting the data in Domo. This connector is suitable for datasets of any size and is recommended for very large datasets. To connect, you'll need a local Snowflake username and a private key. This depends on your server configuration. DataSets can run as often as every 15 minutes. However, depending on the runtime of the query, DataSets may need to run less frequently. Make sure that all the words, table names, and field names are correctly spelled. Refer to the Query Helper field for query help. Before you can connect to a Snowflake database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses in Domo](https://domo-support.domo.com/s/article/360043439173?language=en_US "Whitelisting IP Addresses in Domo"). # Snowflake Key Pair Authentication Writeback Connector Source: https://www.domo.com/docs/s/article/360058760154 ## Intro The Snowflake Key Pair Authentication Writeback Connector makes it easy to bring all your data into Domo and normalize it, then send it back to Snowflake while simultaneously making it available for queries. If you are already using Snowflake as a data warehousing solution, this connector helps you use Domo in conjunction with it to get the most from your data. To use this connector, you must have your Snowflake account name, the username used to connect to your Snowflake host, private key, passphrase, and your Domo developer account credentials (client id and client secret). Use Domo's Snowflake Key Pair Authentication Writeback connector to export your data from a Domo dataset to your Snowflake account. For more information about the Snowflake API, visit [https://docs.snowflake.net/manuals](https://docs.snowflake.net/manuals). This topic discusses the fields and menus that are specific to the Snowflake Key Pair Authentication Writeback connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Connector](/docs/s/article/360042926274). **Note:** The owner of a writeback dataset must also be an owner or co-owner of the input dataset. \-- ## Prerequisites To connect to a Snowflake database and create a DataSet, you must have the following: * The full name of your account (provided by Snowflake). This is the portion of your Snowflake URL immediately following https\://. Note that your full account name may include additional segments that identify the region and cloud platform where your account is hosted. For US West Region **account\_name** and All other regions **account\_name.region\_id**. The following table provides account name examples by cloud platform/region. For each row, it assumes your account name is "xy12345." snowflake_account_names.png * The username used to connect to your Snowflake host. * The private key. * The passphrase. If you create an encrypted private key, then OpenSSL prompts for a passphrase used to encrypt the private key file. **Important**: You need the CREATE TABLE, COPY INTO, PUT, CREATE FILE FORMAT, REMOVE, and LIST permissions on Snowflake. ### Configuring the public/private key pair To configure the public/private key pair, follow these steps: 1. From the command line in a terminal window, generate a private key. You can generate either an encrypted version of the private key or an unencrypted version of the private key. * To generate an unencrypted version, use the following command: `$ openssl genrsa -out rsa_key.pem 2048` * To generate an encrypted version, use the following command: `$ openssl genrsa 2048 | openssl pkcs8 -topk8 -inform PEM -out rsa_key.p8` It is typically safer to generate an encrypted version. If you use the second command to encrypt the private key, then OpenSSL prompts for a passphrase used to encrypt the private key file. We recommend using a strong passphrase to protect the private key. Record this passphrase in a secure location. You will input it when connecting to Snowflake. Note that the passphrase is only used for protecting the private key and will never be sent to Snowflake. The following is a sample PEM private key: `-----BEGIN ENCRYPTED PRIVATE KEY----- MIIE6TAbBgkqhkiG9w0BBQMwDgQILYPyCppzOwECAggABIIEyLiGSpeeGSe3xHP1 wHLjfCYycUPennlX2bd8yX8xOxGSGfvB+99+PmSlex0FmY9ov1J8H1H9Y3lMWXbL ... -----END ENCRYPTED PRIVATE KEY-----` 2. From the command line, generate the public key by referencing the private key. Assuming the private key is encrypted and contained in the file named “rsa\_key.p8”, use the following command: `$ openssl rsa -in rsa_key.p8 -pubout -out rsa_key.pub` The following is a sample PEM public key: `-----BEGIN PUBLIC KEY----- MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAy+Fw2qv4Roud3l6tjPH4 zxybHjmZ5rhtCz9jppCV8UTWvEXxa88IGRIHbJ/PwKW/mR8LXdfI7l/9vCMXX4mk ... -----END PUBLIC KEY-----` 3. Copy the public and private key files to a local directory for storage. Record the path to the files. Note that the private key is stored using the PKCS#8 (Public Key Cryptography Standards) format and is encrypted using the passphrase you specified in the previous step; however, the file should still be protected from unauthorized access using the file permission mechanism provided by your operating system. It is your responsibility to secure the file when it is not being used. 4. Assign the public key to the Snowflake user using ALTER USER. For example: `alter user jsmith set rsa_public_key='MIIBIjANBgkqh...';` **Notes:** * Only security administrators (i.e. users with the SECURITYADMIN role) or higher can alter a user. * Exclude the public key header and footer in the SQL statement. 5. Verify the user's public key fingerprint using DESCRIBE USER:

Property

Value

Default

Description

Name

JSMITH

null

Name

RSA\_PUBLIC\_KEY\_FP

SHA256:nvnONUsfiuycCLMXIEWG4eTp4FjhVUZQUQbNpbSHXiA=

null

Fingerprint of user's RSA public key.

RSA\_PUBLIC\_KEY\_2\_FP

null

null

Fingerprint of user's second RSA public key.

**Note:** For more information about the RSA\_PUBLIC\_KEY\_2\_FP property, see Key Rotation. 6\. Modify and execute the sample code, below. The code decrypts the private key file and passes it to the Snowflake driver to create a connection: * Update the security parameters: * `` specifies the local path to the private key file you created. * Update the session parameters: * `` specifies your Snowflake login name. * `` specifies the name of your account (provided by Snowflake). * The sample code is as follows: ```java theme={"dark"} import java.util.Properties; import java.sql.Connection; import java.sql.Statement; import java.sql.ResultSet; import java.sql.DriverManager; import java.io.File; import java.io.FileInputStream; import java.io.DataInputStream; import java.util.Base64; import java.security.spec.PKCS8EncodedKeySpec; import java.security.KeyFactory; import java.security.PrivateKey; import javax.crypto.EncryptedPrivateKeyInfo; import javax.crypto.SecretKeyFactory; import javax.crypto.spec.PBEKeySpec; public class TestJdbc { public static void main(String[] args) throws Exception { File f = new File("/rsa_key.p8"); FileInputStream fis = new FileInputStream(f); DataInputStream dis = new DataInputStream(fis); byte[] keyBytes = new byte[(int) f.length()]; dis.readFully(keyBytes); dis.close(); String encrypted = new String(keyBytes); String passphrase = System.getenv("PRIVATE_KEY_PASSPHRASE"); encrypted = encrypted.replace("-----BEGIN ENCRYPTED PRIVATE KEY-----", ""); encrypted = encrypted.replace("-----END ENCRYPTED PRIVATE KEY-----", ""); EncryptedPrivateKeyInfo pkInfo = new EncryptedPrivateKeyInfo(Base64.getMimeDecoder().decode(encrypted)); PBEKeySpec keySpec = new PBEKeySpec(passphrase.toCharArray()); SecretKeyFactory pbeKeyFactory = SecretKeyFactory.getInstance(pkInfo.getAlgName()); PKCS8EncodedKeySpec encodedKeySpec = pkInfo.getKeySpec(pbeKeyFactory.generateSecret(keySpec)); KeyFactory keyFactory = KeyFactory.getInstance("RSA"); PrivateKey encryptedPrivateKey = keyFactory.generatePrivate(encodedKeySpec); String url = "jdbc:snowflake://.snowflakecomputing.com"; Properties prop = new Properties(); prop.put("user", ""); prop.put("account", ""); prop.put("privateKey", encryptedPrivateKey); Connection conn = DriverManager.getConnection(url, prop); Statement stat = conn.createStatement(); ResultSet res = stat.executeQuery("select 1"); res.next(); System.out.println(res.getString(1)); conn.close(); } } ``` #### Key Rotation Snowflake supports multiple active keys to allow for uninterrupted rotation. Rotate and replace your public and private keys based on the expiration schedule you follow internally. Currently, you can use the RSA\_PUBLIC\_KEY and RSA\_PUBLIC\_KEY\_2 parameters for ALTER USER to associate up to 2 public keys with a single user. To rotate your keys, 1. Complete the steps in Using Key Pair Authentication to... * Generate a new private and public key set. * Assign the public key to the user. Set the public key value to either RSA\_PUBLIC\_KEY or RSA\_PUBLIC\_KEY\_2 (whichever key value is not currently in use). For example: `alter user jsmith set rsa_public_key_2='JERUEHtcve...';` 2. Update the code to connect to Snowflake. Specify the new private key. Snowflake verifies the correct active public key for authentication based on the private key submitted with your connection information. 3. Remove the old public key from the user profile. For example: `alter user jsmith unset rsa_public_key;` ## Configuring the connection This section enumerates the options in the **Credentials** and **Details** panes in the Snowflake Key Pair Authentication Writeback Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Connector](/docs/s/article/360042926274). ### Credentials Pane This pane contains fields for entering credentials to your Domo developer account as well as your Snowflake account. The following table describes what is needed for each field:

Field

Description

Account Name

Enter the full name of your account (provided by Snowflake.) For US West Region account\_name and All other regions account\_name.region\_id

Username

Enter the username used to connect to your Snowflake host.

Private Key

Enter the private key.

Passphrase

If you create an encrypted private key, then OpenSSL prompts for a passphrase used to encrypt the private key file. Enter that passphrase here.

Role

Enter your role.

Once you have entered valid credentials, you can use the same account any time you to create a new Domo-Snowflake connection. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Manage Connector Accounts](/docs/s/article/360042926054). ### Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

Input DataSet ID

Enter the DataSet ID (GUID) for the DataSet you want to copy to Snowflake. You can find the ID by opening the details view for the DataSet in the Data Center and looking at the portion of the URL following datasources/. For example, in the URL [https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview](https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview), the DataSet ID is 845305d8-da3d-4107-a9d6-13ef3f86d4a4.

Select Table Name

Select how you want to name the table where data will be copied. - Use Input DataSet GUID: The table name must be the number you entered for the InputDataSet ID. - Use Input Dataset Name: The table name must be the name used for naming the Input DataSet. - Enter Table Name: Enter a custom table name in the Enter Table Name\*\*\*\* field.

Enter Table Name

Enter the name of the Snowflake table you want your data copied to (spaces and special characters will be replaced with underscores).

Warehouses

Select the warehouse.

Databases

Select the database.

Database Schema

Select the schema.

Use All Caps for Column Names and Table Name

Write back your column names and table name in ALL CAPS, so the names are case insensitive within Snowflake.

How do you want to update your data in snowflake?

Choose the Escape character

Select the escape character for the input dataset.

### FAQs This connector allows you to write data from a Domo dataset to a Snowflake instance using a local username and a private key. You need the CREATE TABLE, COPY INTO, PUT, CREATE FILE FORMAT, REMOVE, and LIST permissions on Snowflake. You need the account name (provided by Snowflake), your Snowflake username, and private key. If you are creating an encrypted private key then you will need a passphrase used to encrypt the private key file. You can also provide your role name. As often as needed. Limits depend on your server configuration. Yes Before you can connect to a Snowflake database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses.](/docs/s/article/360043630093) Your Domo input dataset ID is in the URL of the dataset you are exporting data from. For example [https://customer.domo.com/datasources/aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee/details/settings](https://customer.domo.com/datasources/aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee/details/settings) ### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](/docs/s/article/360042926274). # Google BigQuery Enterprise Data Connector Source: https://www.domo.com/docs/s/article/360058903093 ## Intro Google BigQuery Enterprise is a cloud-based big data analytics web service for processing very large read-only data sets. You can use Domo's Google BigQuery Enterprise Data connector to pull data from a specified project and get interactive analysis of massive datasets. Google BigQuery queries are written using a variation of the standard SQL SELECT statement. To learn more about the Google API, visit [https://developer.google.com](https://developer.google.com/ "https://developer.google.com"). You connect to your Google BigQuery Enterprise Data account in the Data Center. This topic discusses the fields and menus that are specific to the Google BigQuery Enterprise Data connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ## Prerequisites To connect to your Google BigQuery Enterprise account and create a DataSet, you must have the following: * A project created in the Google Developers Console with the APIs and Services enabled * The Client ID and Client Secret associated with your Google Developers account The following steps explain in detail how to create your project and obtain the needed credentials. #### Creating a project in the Google Developers Console 1. Go to [https://console.developers.google.com](https://console.developers.google.com "https://console.developers.google.com"). 2. Click the dropdown arrow next to **My Project**. googlesheets_writeback_1.png 3. Click **New Project**. googlesheets_writeback_2.png 4. Name your project and select the parent folder. 5. Click **Create**. **Note:** You can also use an existing project if you want. #### Creating the OAuth Client ID and Client Secret 1. Login to [https://console.developers.google.com/](https://console.developers.google.com/). 2. Select your project. 3. Go to **APIs & Services > Credentials**. clipboard_e2f41627fa6f73db016bc16ff40f8b82c.png 4. Click on **+Create credentials > OAuth client ID**. clipboard_e7def711e8943bc1c4efbad251022993d.png 5. Select **OAuth client ID**. 6. Select the **Application Type** as **Web application** from the drop down. select_web_app.png 7. Enter the name for your application. 8. Click on ****+Add URI**** under ****Authorized redirect URIs****. 9. Add **[https://oauth.domo.com/api/data/v1/oauth/providers/google-bigquery-enterprise/exchange](https://oauth.domo.com/api/data/v1/oauth/providers/google-bigquery-enterprise/exchange)** as the redirect URI. redirect_URI.png 10. Click ****Create****. #### Enabling API and Services 1. Login to [https://console.developers.google.com/](https://console.developers.google.com/). 2. Go to ****APIs & Services > Dashboard****. 3. Click ****+ENABLE APIS AND SERVICES****. APIs_n_Services.png 4. Search for **Google BigQuey API**. BigQuery_api.png 5. Click the **ENABLE** button to enable the BigQuery API. BigQuery_aAPI_enabled.png ## Connecting to Your Google BigQuery Enterprise Account This section enumerates the options in the **Credentials** and **Details** panes in the Google BigQuery Enterprise Data Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Google BigQuery Enterprise account. The following table describes what is needed for each field:

Field

Description

Client ID Enter the Client ID associated with your Google Developers account. For more details, see Prerequisites .
Client Secret Enter the Client Secret associated with your Google Developers account. For more details, see Prerequisites .
Once you have entered valid credentials, you can use the same account any time you go to create a new Google BigQuery Enterprise DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

Report

Select the Google BigQuery Enterprise report you want to run. The following reports are available:

QueryReturns the data from Big Query by running legacy or standard SQL.
Table InformationReturns the information of the Table.
Table DataReturns the information about the Table data.
What Query Type would you like to use?Select whether you would like to use a Legacy SQL Query or a Standard SQL Query. By default, LegacySQL is selected.
QueryEnter a fully qualified Google BigQuery query.
Query ParameterEnter the query parameter value. It is the initial value for query parameter. The last run date is optional by default. The value for last run date is '02/01/1700' if it is not provided. Example: `!{lastvalue:_id}!=1,!{lastrundate:start_date}!=02/01/1944`
Project IDEnter the ID for the project you want to retrieve data for.
Expect Large ResultsSpecify whether you would like to get large results. Queries with large results will create a temporary table and delete it when the job is finished. A dataset ID is required to create the temporary table.
Dataset IDEnter the ID for the dataset you want to retrieve data for.
ProjectsSelect project from available list of projects.
DatasetsSelect dataset from available list of datasets.
TablesSelect table from available list of tables.
LocationEnter location. Visit Dataset Locations to find more information about Location.
Selected FieldsSelect fields.
Max ResultsMax Results is the number of results returned per page of data. By default, it returns 10,000 results per page. If your dataset throws an out of memory error, decrease Max Results.
### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). # Snowflake KeyPair Unload Connector Source: https://www.domo.com/docs/s/article/360059173794 ## Intro Snowflake KeyPair Unload is a cloud-based analytics data warehouse system. Use Domo's Snowflake KeyPair Unload connector to unload data from your Snowflake database into Amazon S3. The files are downloaded from S3 into Domo. This connector should be preferred over the Snowflake connector if you are executing very large queries. You connect to your Snowflake account in the Data Center. This topic discusses the fields and menus that are specific to the Snowflake KeyPair Unload Connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). *** ## Prerequisites To connect to a Snowflake database and create a DataSet, you must have the following: * The full name of your account (provided by Snowflake). This is the portion of your Snowflake URL immediately following https\://.\ Note that your full account name may include additional segments that identify the region and cloud platform where your account is hosted. For US West Region **account\_name** and All other regions **account\_name.region\_id**. The following table provides account name examples by cloud platform/region. For each row, it assumes your account name is "xy12345." snowflake_account_names.png * The username used to connect to your Snowflake host. * The private key. * The passphrase. If you create an encrypted private key, then OpenSSL prompts for a passphrase used to encrypt the private key file. * Your AWS access key. It is available in the AWS Console in the **Security Credentials** section or under **Users** if you are using **IAM**. * Your AWS secret key. was provided when you created your Access Key. You can generate a new one in the AWS Console. * The name of the AWS S3 bucket that your Snowflake data will be unloaded into. * You need to select the Amazon S3 Region. ### Configuring the public/private key pair To configure the public/private key pair, follow these steps: 1. From the command line in a terminal window, generate a private key.\ You can generate either an encrypted version of the private key or an unencrypted version of the private key. * To generate an unencrypted version, use the following command: `$ openssl genrsa -out rsa_key.pem 2048` * To generate an encrypted version, use the following command: `$ openssl genrsa 2048 | openssl pkcs8 -topk8 -inform PEM -out rsa_key.p8` It is typically safer to generate an encrypted version. If you use the second command to encrypt the private key, then OpenSSL prompts for a passphrase used to encrypt the private key file. We recommend using a strong passphrase to protect the private key. Record this passphrase in a secure location. You will input it when connecting to Snowflake. Note that the passphrase is only used for protecting the private key and will never be sent to Snowflake. The following is a sample PEM private key: `-----BEGIN ENCRYPTED PRIVATE KEY----- MIIE6TAbBgkqhkiG9w0BBQMwDgQILYPyCppzOwECAggABIIEyLiGSpeeGSe3xHP1 wHLjfCYycUPennlX2bd8yX8xOxGSGfvB+99+PmSlex0FmY9ov1J8H1H9Y3lMWXbL ... -----END ENCRYPTED PRIVATE KEY-----` 2. From the command line, generate the public key by referencing the private key. Assuming the private key is encrypted and contained in the file named “rsa\_key.p8”, use the following command: `$ openssl rsa -in rsa_key.p8 -pubout -out rsa_key.pub` The following is a sample PEM public key: `-----BEGIN PUBLIC KEY----- MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAy+Fw2qv4Roud3l6tjPH4 zxybHjmZ5rhtCz9jppCV8UTWvEXxa88IGRIHbJ/PwKW/mR8LXdfI7l/9vCMXX4mk ... -----END PUBLIC KEY-----` 3. Copy the public and private key files to a local directory for storage. Record the path to the files. Note that the private key is stored using the PKCS#8 (Public Key Cryptography Standards) format and is encrypted using the passphrase you specified in the previous step; however, the file should still be protected from unauthorized access using the file permission mechanism provided by your operating system. It is your responsibility to secure the file when it is not being used. 4. Assign the public key to the Snowflake user using ALTER USER. For example: `alter user jsmith set rsa_public_key='MIIBIjANBgkqh...';` **Notes:** * Only security administrators (i.e. users with the SECURITYADMIN role) or higher can alter a user. * Exclude the public key header and footer in the SQL statement. 5. Verify the user's public key fingerprint using DESCRIBE USER:

Property

Value

Default

Description

Name

JSMITH

null

Name

RSA\_PUBLIC\_KEY\_FP

SHA256:nvnONUsfiuycCLMXIEWG4eTp4FjhVUZQUQbNpbSHXiA=

null

Fingerprint of user's RSA public key.

RSA\_PUBLIC\_KEY\_2\_FP

null

null

Fingerprint of user's second RSA public key.

**Note:** For more information about the RSA\_PUBLIC\_KEY\_2\_FP property, see Key Rotation 6\. Modify and execute the sample code, below. The code decrypts the private key file and passes it to the Snowflake driver to create a connection: * Update the security parameters: * `` specifies the local path to the private key file you created. * Update the session parameters: * `` specifies your Snowflake login name. * `` specifies the name of your account (provided by Snowflake). * The sample code is as follows: ```java theme={"dark"} import java.util.Properties; import java.sql.Connection; import java.sql.Statement; import java.sql.ResultSet; import java.sql.DriverManager; import java.io.File; import java.io.FileInputStream; import java.io.DataInputStream; import java.util.Base64; import java.security.spec.PKCS8EncodedKeySpec; import java.security.KeyFactory; import java.security.PrivateKey; import javax.crypto.EncryptedPrivateKeyInfo; import javax.crypto.SecretKeyFactory; import javax.crypto.spec.PBEKeySpec; public class TestJdbc { public static void main(String[] args) throws Exception { File f = new File("/rsa_key.p8"); FileInputStream fis = new FileInputStream(f); DataInputStream dis = new DataInputStream(fis); byte[] keyBytes = new byte[(int) f.length()]; dis.readFully(keyBytes); dis.close(); String encrypted = new String(keyBytes); String passphrase = System.getenv("PRIVATE_KEY_PASSPHRASE"); encrypted = encrypted.replace("-----BEGIN ENCRYPTED PRIVATE KEY-----", ""); encrypted = encrypted.replace("-----END ENCRYPTED PRIVATE KEY-----", ""); EncryptedPrivateKeyInfo pkInfo = new EncryptedPrivateKeyInfo(Base64.getMimeDecoder().decode(encrypted)); PBEKeySpec keySpec = new PBEKeySpec(passphrase.toCharArray()); SecretKeyFactory pbeKeyFactory = SecretKeyFactory.getInstance(pkInfo.getAlgName()); PKCS8EncodedKeySpec encodedKeySpec = pkInfo.getKeySpec(pbeKeyFactory.generateSecret(keySpec)); KeyFactory keyFactory = KeyFactory.getInstance("RSA"); PrivateKey encryptedPrivateKey = keyFactory.generatePrivate(encodedKeySpec); String url = "jdbc:snowflake://.snowflakecomputing.com"; Properties prop = new Properties(); prop.put("user", ""); prop.put("account", ""); prop.put("privateKey", encryptedPrivateKey); Connection conn = DriverManager.getConnection(url, prop); Statement stat = conn.createStatement(); ResultSet res = stat.executeQuery("select 1"); res.next(); System.out.println(res.getString(1)); conn.close(); } } ``` #### Key Rotation Snowflake supports multiple active keys to allow for uninterrupted rotation. Rotate and replace your public and private keys based on the expiration schedule you follow internally. Currently, you can use the RSA\_PUBLIC\_KEY and RSA\_PUBLIC\_KEY\_2 parameters for ALTER USER to associate up to 2 public keys with a single user. To rotate your keys, 1. Complete the steps in Using Key Pair Authentication to... * Generate a new private and public key set. * Assign the public key to the user. Set the public key value to either RSA\_PUBLIC\_KEY or RSA\_PUBLIC\_KEY\_2 (whichever key value is not currently in use).\ For example: `alter user jsmith set rsa_public_key_2='JERUEHtcve...';` 2. Update the code to connect to Snowflake. Specify the new private key.\ Snowflake verifies the correct active public key for authentication based on the private key submitted with your connection information. 3. Remove the old public key from the user profile. For example: `alter user jsmith unset rsa_public_key;` ## Connecting to Your Snowflake Account This section enumerates the options in the **Credentials** and **Details** panes in the Snowflake KeyPair Unload Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ### Credentials Pane This pane contains fields for entering credentials to your Snowflake account. The following table describes what is needed for each field:

Field

Description

Account Name

Enter the full name of your account (provided by Snowflake.) For US West Region account\_name and All other regions account\_name.region\_id

Username

Enter the username used to connect to your Snowflake host.

Private Key

Enter the private key.

Passphrase

If you create an encrypted private key, then OpenSSL prompts for a passphrase used to encrypt the private key file. Enter that passphrase here.

Role

Enter your role.

Access Key

Enter your AWS access key. It is available in the AWS Console in the Security Credentials section or under Users if you are using IAM.

Secret Key

Enter your AWS secret access key. It was provided when you created your Access Key. You can generate a new one in the AWS Console.

Bucket

Enter the name of the AWS S3 bucket that your Snowflake data will be unloaded into.

Region

Select the Amazon S3 Region.

Once you have entered valid credentials, you can use the same account any time you to create a new Snowflake KayPair Unload dataset. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054). ### Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

Query

Enter the SQL query to use to retrieve your data. You can use the Query Helper parameter to help you write a usable SQL query. To use the Query Helper, do the following: 1. Select your desired warehouse, database, database schema, database table, and table columns in each menu. 2. Copy the SQL statement that appears in the Query Helper field. 3. Paste the copied SQL statement into the Query field.

Warehouses

Select the warehouse containing the data you want to retrieve. The list populates with all warehouses you have access to based on your credentials.

Databases

Select the database containing the data you want to retrieve. The list populates with all databases you have access to based on your credentials.

Database Schema

Select the database schema containing the data you want to retrieve. The list populates with all schemas you have access to based on your credentials.

Database Tables

Select the database table you want to retrieve. The list populates with all tables you have access to based on your credentials. If you do not select a database table, the connector retrieves your entire database schema.

Table Columns

Select the table columns you would like to include in your report. If you do not select any table column, the connector retrieves your entire selected database table.

Query Helper

When you select warehouses, databases, schemas, tables, etc. from the above menus, a usable SQL query is built for you in this field. Copy and paste this text into the QUERY field. You may edit this query if desired.

Use Snowflake Schema

Check this box if you wish to use the schema directly from Snowflake instead of letting Domo determine the schema.

### Other Panes For information about the remaining sections of the Connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQs The limits depend on your server configuration. DataSets can run as often as every 15 minutes. However, depending on the runtime of the query, DataSets may need to run less frequently. Make sure that all the words, table names, and field names are correctly spelled. Refer to the Query Helper field for query help. Before you can connect to a Snowflake database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses in Domo](/docs/s/article/360043439173). ## Troubleshooting * Make sure your authentication remains valid. * Review the configuration to make sure that all required items have been selected. * Review the Connector history for error messages. * In rare cases, you may be requesting too much information and reaching API limitations or timeouts. If this is the case, you can review the history of the Connector run to see the error message and duration. If this is the case, you can reduce the number of accounts that are being pulled, choose a smaller number of metrics for the report that you are pulling, or reduce the timeframe that you are trying to pull. # Google BigQuery High Bandwidth Service Connector Source: https://www.domo.com/docs/s/article/360060507713 ## Intro BigQuery is a data platform to create, manage, share, and query data. Domo's Google BigQuery High Bandwidth Service connector lets you bring in larger results from BigQuery through the assistance of the Google Cloud Storage service. To learn more about the BigQuery API, go to [https://cloud.google.com/bigquery/docs/reference/v2/](https://cloud.google.com/bigquery/docs/reference/v2/ "https://cloud.google.com/bigquery/docs/reference/v2/"). The Google BigQuery High Bandwidth Service connector is a "Cloud App" connector, meaning it retrieves data stored in the cloud. In the Data Center, you can access the connector page for this and other Cloud App connectors by clicking ********Cloud App******** in the toolbar at the top of the window. This topic discusses the fields and menus that are specific to the Google BigQuery High Bandwidth Service connector user interface. For general information about adding DataSets, setting update schedules, and editing DataSet information, see [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). ## Prerequisites To connect to BigQuery and create a DataSet, you must have the following: * A JSON BigQuery service account key * A JSON Google Cloud Storage service account key ##### To generate the necessary service account keys, do the following: 1. In the Google Cloud Platform Console, open the **IAM & Admin** page. IAM_Admin_-_Services.png 2. Click ********Service accounts********. 3. Select your project and click ********Open********. 4. Click ********Create Service Account********. Create_service_account1.png 5. Enter a name and description for the service account. 6. Click ********Create********. 7. To grant this service account access to the project, click the **Select a role** drop-down. 8. Click **Project** and then click ********Owner********. Select_Project_Owner.png 9. Owner will appear in the Role field. 10. Click ********Continue********. 11. Click the ********Create key********. Create_key1.png 12. Select ********JSON******** as the key type. Create_key_json2.png 13. Click ********Create********. A private key will be saved to your computer. ##### Include the following permissions for the Service keys: **BIGQUERY ROLES** ``` bigquery.datasets.get bigquery.jobs.create bigquery.jobs.get bigquery.jobs.list bigquery.tables.list bigquery.tables.export bigquery.tables.create bigquery.tables.delete ``` **CLOUD STORAGE ROLES** ``` storage.buckets.get storage.buckets.list storage.objects.create storage.objects.delete storage.objects.get storage.objects.list ``` ## Connecting to BigQuery This section enumerates the options in the ****Credentials**** and ****Details**** panes on the Google BigQuery High Bandwidth Service Connector page. The components of the other panes on this page, ****Scheduling****, and ****Name & Describe Your DataSet****, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). You cannot export nested and repeated data in CSV format. Nested and repeated data are supported for Avro, JSON, and Parquet exports. If the customer has a column with type as ARRAY, BigQuery doesn't support unloading that data in CSV. The customer needs to exclude the ARRAY columns or UNNEST them to run the unload successfully ## Credentials Pane This pane contains fields for entering credentials to connect to your BigQuery Unload account. The following table describes what is needed for each field:

Field

Description

Service Account Key JSON BigQuery Enter your Google BigQuery JSON service account key.
Service Account Key JSON Google Cloud Storage Enter your Google Cloud Storage JSON service account key.
Once you have entered valid credentials, you can use the same account any time you go to create a new Google BigQuery High Bandwidth Service DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](https://domo-support.domo.com/s/article/360042926054?language=en_US "Managing User Accounts for Connectors"). ## Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

Report
Report Name Description
Query Runs a BigQuery SQL query and returns results if the query completes.
Dataset ID Select the BigQuery dataset ID for your data.
For more info about BigQuery datasets, visit [https://cloud.google.com/bigquery/docs/datasets-intro](https://cloud.google.com/bigquery/docs/datasets-intro) .
Google Cloud Storage Bucket Selection Criteria Select if you want to provide a Google Cloud Storage bucket name or select from discovery.
Google Cloud Storage bucket name Select the Google Cloud Storage bucket name that will be used for temporary storage as we transfer your data into Domo.
Query Enter a query to execute. Only Standard SQL query is supported. Example: Select \* from Table\_Name.
Partition query to determine partition tags Enter partition query to determine the distinct partition tags. The column containing the Date data is your partition column. Example: Select Date from Table\_Name.
Force to string Enter a comma-separated list of fields that need to be treated as STRING in Domo.
Force to number Enter a comma-separated list of fields that need to be treated as NUMBER in Domo.
How would you like to pull your data? Choose how you would like to pull your data.
Partition column name Enter partition column name. The column containing the Date data is your partition column.
Upsert key columns Enter a comma-separated list of upsert key column names.
Partition Criteria Select if you want to partition your data using the date keys, non-date keys, or meta query.
Partition Query to determine partition tags Enter partition query to determine the distinct partition tags.
Partition Non Date Key Column Name Select the partition column name.
Partition Support Format Select the partition format.
Past Days Enter the number of past days that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Past Years Enter the number of past years that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Past Months Enter the number of past months that you want to get data for. Value can be X, where X is a positive integer. For example 30.
Future Years Enter the number of future years that you want to get data for. Value can be X, where X is a positive integer. For example 30.
Future Months Enter the number of future months that you want to get data for. Value can be X, where X is a positive integer. For example 30.
Date Format Select the proper date format according to the date format present in the partition column. By default, \yyyy-MM-dd\ will be used.
Days Back The number of days back that you would like to get data from. Example: Specify 7 to get data for the last 7 days.
Data Rolling Window The data will be retained for the number of days specified. Example: Specify 60 to retain the data for 60 days.
##### Entering the SQL Query and Partition Query clipboard_ecd64363a5df614584835f22327e84ce7.png ##### Entering the Partition column name and other parameters 2._Query___Rolling_window___Column_name.png Your data will be fetched from the number of days mentioned in the **Days Back** field and will be retained for the number of days specified in the **Data Rolling Window** field. **Note:** When using the Partition option, your DataSet must be set to **Append** and NOT Replace. ##### Using the Upsert mode 3._Upsert_method.png ## Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). **Note:** Currently this connector only supports date partitions. ## Troubleshooting #### What if no rows of data are being returned but there are rows in the run history? Google API documentation has stated that BigQuery and Cloud Storage need to follow the below rules: * If the BigQuery dataset is in a specific location then Cloud Storage should be in the same location. * If BigQuery Dataset is in a multi-region then Cloud Storage also needs to be either in the same multi-region or in a location that is contained within that multi-region. Refer to [Google Cloud Storage](https://cloud.google.com/bigquery/docs/dts-locations#cloud-storage "Google Cloud Storage") for the API documentation reference. For Bucket locations, visit [https://cloud.google.com/storage/docs/locations](https://cloud.google.com/storage/docs/locations "https://cloud.google.com/storage/docs/locations"). # Snowflake KeyPair Internal Managed Unload Connector Source: https://www.domo.com/docs/s/article/360061224493 ## Intro Snowflake is a cloud-based analytic data warehouse system. Use Domo's Snowflake KeyPair Internal Managed Unload connector to unload data from your Snowflake database into internal Amazon S3 easily and securely. The files are then downloaded from internal S3 into Domo. This connector should be preferred over the other Snowflake connectors if you are executing very large queries. Once your Snowflake data is in Domo, you can combine it with all your other Domo data to get a centralized view of your most mission-critical data. ## Prerequisites To connect to a Snowflake database and create a DataSet, you must have the following: * The full name of your account (provided by Snowflake). This is the portion of your Snowflake URL immediately following https\://. Note that your full account name may include additional segments that identify the region and cloud platform where your account is hosted. For US West Region ****account\_name**** and All other regions ****account\_name.region\_id****. The following table provides account name examples by cloud platform/region. For each row, it assumes your account name is "xy12345." snowflake_account_names.png * The username used to connect to your Snowflake host. * The private key. * The passphrase. If you create an encrypted private key, then OpenSSL prompts for a passphrase used to encrypt the private key file. * Your role name. ### Configuring the public/private key pair To configure the public/private key pair, follow these steps: 1. From the command line in a terminal window, generate a private key. You can generate either an encrypted version of the private key or an unencrypted version of the private key. * To generate an unencrypted version, use the following command: `$ openssl genrsa -out rsa_key.pem 2048` * To generate an encrypted version, use the following command: `$ openssl genrsa 2048 | openssl pkcs8 -topk8 -inform PEM -out rsa_key.p8` It is typically safer to generate an encrypted version. If you use the second command to encrypt the private key, then OpenSSL prompts for a passphrase used to encrypt the private key file. We recommend using a strong passphrase to protect the private key. Record this passphrase in a secure location. You will input it when connecting to Snowflake. Note that the passphrase is only used for protecting the private key and will never be sent to Snowflake. The following is a sample PEM private key: ``` -----BEGIN ENCRYPTED PRIVATE KEY----- MIIE6TAbBgkqhkiG9w0BBQMwDgQILYPyCppzOwECAggABIIEyLiGSpeeGSe3xHP1 wHLjfCYycUPennlX2bd8yX8xOxGSGfvB+99+PmSlex0FmY9ov1J8H1H9Y3lMWXbL ... -----END ENCRYPTED PRIVATE KEY----- ``` 2. From the command line, generate the public key by referencing the private key. Assuming the private key is encrypted and contained in the file named “rsa\_key.p8”, use the following command: `$ openssl rsa -in rsa_key.p8 -pubout -out rsa_key.pub` The following is a sample PEM public key: ``` -----BEGIN PUBLIC KEY----- MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAy+Fw2qv4Roud3l6tjPH4 zxybHjmZ5rhtCz9jppCV8UTWvEXxa88IGRIHbJ/PwKW/mR8LXdfI7l/9vCMXX4mk ... -----END PUBLIC KEY----- ``` 3. Copy the public and private key files to a local directory for storage. Record the path to the files. Note that the private key is stored using the PKCS#8 (Public Key Cryptography Standards) format and is encrypted using the passphrase you specified in the previous step; however, the file should still be protected from unauthorized access using the file permission mechanism provided by your operating system. It is your responsibility to secure the file when it is not being used. 4. Assign the public key to the Snowflake user using ALTER USER. For example: `alter user jsmith set rsa_public_key='MIIBIjANBgkqh...';` **Notes:** * Only security administrators (i.e. users with the SECURITYADMIN role) or higher can alter a user. * Exclude the public key header and footer in the SQL statement. 5. Verify the user's public key fingerprint using DESCRIBE USER:
Property Value Default Description
Name JSMITH null Name
RSA\_PUBLIC\_KEY\_FP SHA256:nvnONUsfiuycCLMXIEWG4eTp4FjhVUZQUQbNpbSHXiA= null Fingerprint of user's RSA public key.
RSA\_PUBLIC\_KEY\_2\_FP null null Fingerprint of user's second RSA public key.
**Note:** For more information about the RSA\_PUBLIC\_KEY\_2\_FP property, see Key Rotation. 6. Modify and execute the sample code, below. The code decrypts the private key file and passes it to the Snowflake driver to create a connection: * Update the security parameters: * `` specifies the local path to the private key file you created. * Update the session parameters: * `` specifies your Snowflake login name. * `` specifies the name of your account (provided by Snowflake). * The sample code is as follows: ```java theme={"dark"} import java.util.Properties; import java.sql.Connection; import java.sql.Statement; import java.sql.ResultSet; import java.sql.DriverManager; import java.io.File; import java.io.FileInputStream; import java.io.DataInputStream; import java.util.Base64; import java.security.spec.PKCS8EncodedKeySpec; import java.security.KeyFactory; import java.security.PrivateKey; import javax.crypto.EncryptedPrivateKeyInfo; import javax.crypto.SecretKeyFactory; import javax.crypto.spec.PBEKeySpec; public class TestJdbc { public static void main(String[] args) throws Exception { File f = new File("/rsa_key.p8"); FileInputStream fis = new FileInputStream(f); DataInputStream dis = new DataInputStream(fis); byte[] keyBytes = new byte[(int) f.length()]; dis.readFully(keyBytes); dis.close(); String encrypted = new String(keyBytes); String passphrase = System.getenv("PRIVATE_KEY_PASSPHRASE"); encrypted = encrypted.replace("-----BEGIN ENCRYPTED PRIVATE KEY-----", ""); encrypted = encrypted.replace("-----END ENCRYPTED PRIVATE KEY-----", ""); EncryptedPrivateKeyInfo pkInfo = new EncryptedPrivateKeyInfo(Base64.getMimeDecoder().decode(encrypted)); PBEKeySpec keySpec = new PBEKeySpec(passphrase.toCharArray()); SecretKeyFactory pbeKeyFactory = SecretKeyFactory.getInstance(pkInfo.getAlgName()); PKCS8EncodedKeySpec encodedKeySpec = pkInfo.getKeySpec(pbeKeyFactory.generateSecret(keySpec)); KeyFactory keyFactory = KeyFactory.getInstance("RSA"); PrivateKey encryptedPrivateKey = keyFactory.generatePrivate(encodedKeySpec); String url = "jdbc:snowflake://.snowflakecomputing.com"; Properties prop = new Properties(); prop.put("user", ""); prop.put("account", ""); prop.put("privateKey", encryptedPrivateKey); Connection conn = DriverManager.getConnection(url, prop); Statement stat = conn.createStatement(); ResultSet res = stat.executeQuery("select 1"); res.next(); System.out.println(res.getString(1)); conn.close(); } } ``` #### Key Rotation Snowflake supports multiple active keys to allow for uninterrupted rotation. Rotate and replace your public and private keys based on the expiration schedule you follow internally. Currently, you can use the RSA\_PUBLIC\_KEY and RSA\_PUBLIC\_KEY\_2 parameters for ALTER USER to associate up to 2 public keys with a single user. To rotate your keys, 1. Complete the steps in Using Key Pair Authentication to... * Generate a new private and public key set. * Assign the public key to the user. Set the public key value to either RSA\_PUBLIC\_KEY or RSA\_PUBLIC\_KEY\_2 (whichever key value is not currently in use). For example: `alter user jsmith set rsa_public_key_2='JERUEHtcve...';` 2. Update the code to connect to Snowflake. Specify the new private key. Snowflake verifies the correct active public key for authentication based on the private key submitted with your connection information. 3. Remove the old public key from the user profile. For example: `alter user jsmith unset rsa_public_key;` ## Connecting to Your Snowflake Account This section enumerates the options in the **Credentials** and **Details** panes in the Snowflake KeyPair Internal Managed Unload Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to your Snowflake account. The following table describes what is needed for each field:

Field

Description

Account Name Enter the full name of your account (provided by Snowflake.) For US West Region account\_name and All other regions account\_name.region\_id
Username Enter the username used to connect to your Snowflake host.
Private Key Enter the private key.
Passphrase If you create an encrypted private key, then OpenSSL prompts for a passphrase used to encrypt the private key file. Enter that passphrase here.
Role Enter the name for your role.
Once you have entered valid credentials, you can use the same account any time you want to create a new Snowflake KayPair Internal Managed Unload dataset. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

Query Type

QueryType Description
Custom Query Enter the SQL query to execute.
Query Builder Select a table and fields to autogenerate your query.
Warehouses Select the warehouse containing the data you want to retrieve. The list populates with all of the warehouses you have access to based on your credentials.
Databases Select the database containing the data you want to retrieve. The list populates with all of the databases you have access to based on your credentials.
Schemas Select the database schema containing the data you want to retrieve. The list populates with all of the schemas you have access to based on your credentials.
Database Objects Select the database object containing the data you want to retrieve.
Tables Select the table.
Database Tables Select the database table you want to retrieve. The list populates with all of the tables you have access to based on your credentials. If you do not select a database table, the connector will retrieve your entire database schema.
Table Columns Select the table columns you want to retrieve. The list populates with all of the columns you have access to based on your credentials. If you do not select a table column, the connector retrieves your entire selected database table.
Table Query Helper A query is generated based on the selected fields. Copy and paste this text into the QUERY field. You may edit this query, if desired.
Views Select the view.
View Columns Select the view columns that you would like to include in your report.
View Query Helper A query is generated based on the selected fields. Copy and paste this text into the QUERY field. You may edit this query, if desired.

Query

Enter the SQL query to retrieve your data.

Partition or Upsert Support

Specify whether you want to partition your data or need the upsert functionality.

Partition Criteria

Select whether you want to partition your data using the date keys, non-date keys, or meta query.

Partition Support Specify whether you want to partition your data.
Partition Support Format Select the partition format.
Select Partition Non Date Key Column Name Select the partition column name.
Partition Non Date Key Column Name Select a non-date key column name to partition the data. All the fields, excluding Date fields, will be shown in this discovery.
Enter Partition Non Date Key Column Name Enter the partition column name.
Partition Query to determine partition tags Enter the partition query to determine the distinct partition tags. The column contains the Date data is your partition column. For example, select Date from the Table\_Name.
Partition Column Name Select the partition column name.
Select or Enter Upsert Column You can choose whether you want to enter the column names manually or select from the list.
Upsert Columns Select the columns for upsert.
Upsert Column Names Enter the comma-separated values for upsert column names.
Past Years Enter the number of past years that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Future Years Enter the number of future years that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Past Months Enter the number of past months that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Future Months Enter the number of future months that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Past Days Enter the number of past days that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Date Format Select the required date format. By default yyyy-MM-dd will be used.
Custom Date Format Enter the custom date format.
Query Tag This is an optional parameter that can be used to tag connector SQL executions in Snowflake as a Query Tag .
Convert Columns to String Enter the column names separated by a comma to convert the columns to a string—for example, column1, column2, column3.
### Other Panes For information about the remaining sections of the Connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQs The Snowflake KeyPair Internal Managed Unload connector imports data to Domo from Snowflake by first unloading data to a Snowflake-managed S3 bucket before ingesting the data in Domo. This connector is suitable for datasets of any size and is recommended for very large datasets. To connect, you'll need a local Snowflake username and a private key. You need the account name, username, and private key associated with your Snowflake account. If you create an encrypted private key, then OpenSSL prompts for a passphrase used to encrypt the private key file. The limits depend on your server configuration. DataSets can run as often as every 15 minutes. However, depending on the runtime of the query, DataSets may need to run less frequently. Make sure that all the words, table names, and field names are correctly spelled. Before you can connect to a Snowflake database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses in Domo](/docs/s/article/360043439173 "Whitelisting IP Addresses in Domo"). ## Troubleshooting * Make sure your authentication remains valid. * Review the configuration to make sure that all required items have been selected. * Review the Connector history for error messages. * In rare cases, you may be requesting too much information and reaching API limitations or timeouts. If this is the case, you can review the history of the Connector run to see the error message and duration. If this is the case, you can reduce the number of accounts that are being pulled, choose a smaller number of metrics for the report that you are pulling, or reduce the timeframe that you are trying to pull. # Snowflake OAuth Connector Source: https://www.domo.com/docs/s/article/360061552054 ## Intro The Domo Snowflake OAuth connector makes it easy to bring your data from your Snowflake data warehouse into Domo securely. If you are already using Snowflake as a data warehousing solution, this connector helps you use Domo in conjunction with it to get the most from your data. To use this connector, you must have your Snowflake account name, and the client ID and client secret provided by Snowflake when the client is registered. Once your Snowflake data is in Domo, you can combine it with all your other Domo data to get a centralized view of your most mission-critical data. For more information about the Snowflake API, go to [https://docs.snowflake.net/manuals](https://docs.snowflake.net/manuals "https://docs.snowflake.net/manuals"). The Snowflake connector is a "Database" connector, meaning it retrieves data from a database using a query. In the Data Center, you can access the connector page for this and other Database connectors by clicking **Database** in the toolbar at the top of the window. This topic discusses the fields and menus that are specific to the Snowflake OAuth connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Best Practices **Important:** Snowflake asserts your need to manually re-connect your Domo account every time the account expires. The Snowflake integration controls how often the account will expire. If it is set to expire the refresh tokens every 90 days, then you will need to reconnect the account every 90 days. If you would like to increase the refresh timeout to more than 90 days, then you will need to contact the **Snowflake Support**, and they can increase the maximum timeout from 90 days to 1 year. ## Prerequisites To connect to your Snowflake database account and create a DataSet, you must have the following: * The full name of your account (provided by Snowflake). This is the portion of your Snowflake URL immediately following https\://. Note that your full account name may include additional segments that identify the region and cloud platform where your account is hosted. The following table provides account name examples by cloud platform/region. For each row, it assumes your account name is "xy12345." Region.png * The Client ID and Client Secret provided by Snowflake when the client is registered. ## Connecting to Your Snowflake Account This section enumerates the options in the **Credentials** and **Details** panes in the Snowflake OAuth Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ### Credentials Pane This pane contains fields for entering credentials to connect to your Snowflake account. The following table describes what is needed for each field:

Field

Description

Account Name

Enter the account name for your Snowflake account.

Client ID

Enter your Client ID provided by Snowflake when the client is registered.

Client Secret

Enter your Client Secret provided by Snowflake when the client is registered.

Role

Enter your role.

After you have entered valid Snowflake credentials, you can use the same account in Domo any time you create a Snowflake OAuth DataSet. You can manage Connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054). ### Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

Query Type Select whether you want to enter a custom query or use a query builder.
Warehouses Select the warehouse containing the data you want to retrieve. The list populates with all of the warehouses you have access to based on your credentials.
Databases Select the database containing the data you want to retrieve. The list populates with all of the databases you have access to based on your credentials.
Database Schema Select the database schema containing the data you want to retrieve. The list populates with all of the schemas you have access to based on your credentials.
Query

Enter the SQL query to use to retrieve your data. You can use the Query Helper parameter to help you write a usable SQL query. To use the Query Helper , do the following:

  1. Select your desired warehouse, database, database schema, database table, and table columns in each menu.

  2. Copy the SQL statement that appears in the Query Helper field.

  3. Paste the copied SQL statement into the Query field.

Database Objects Select the database object.
Tables Select the database table you want to retrieve. The list populates with all of the tables you have access to based on your credentials. If you do not select a database table, the connector retrieves your entire database schema.
Table Columns Select the table columns you want to retrieve. The list populates with all of the columns you have access to based on your credentials. If you do not select a table column, the connector retrieves your entire selected database table.
Table Query Helper This field shows the query that is generated based on the selected fields.
Views Select the view.
View Columns Select the view columns that you would like to include in your report.
Query Helper When you select warehouses, databases, schemas, tables, etc. from the above menus, a usable SQL query is built for you in this field. Copy and paste the SQL statement in this field into the Query field.
Fetch Size Enter a fetch size for memory performance. If this field is left blank, the default value 1000 will be used. If dataset throws an out of memory error, try decreasing the fetch size.
### Other Panes For information about the remaining sections of the Connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQs To avoid this error, you need to refresh the token. Snowflake asserts your need to manually re-connect your Domo account every time the account expires. The Snowflake integration controls how often the account will expire. If it is set to expire the refresh tokens every 90 days, then you will need to reconnect the account every 90 days. If you would like to increase the refresh timeout to more than 90 days, then you will need to contact the **Snowflake Support**, and they can increase the maximum timeout from 90 days to 1 year. This depends on your server configuration. DataSets can run as often as every 15 minutes. However, depending on the runtime of the query, DataSets may need to run less frequently. Make sure that all the words, table names, and field names are correctly spelled. Refer to the Query Helper field for query help. Before you can connect to a Snowflake database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses in Domo](/docs/s/article/360043630093 "Whitelisting IP Addresses in Domo"). You only see content that that you have access to based on the user role entered for your account in Snowflake. If you aren't seeing something you are expecting, make sure that role has access to that warehouse, database, table. etc. If you do not enter a role in Snowflake, the SYSADMIN role is used by default. ## Troubleshooting * Make sure your authentication remains valid. * Review the configuration to make sure that all required items have been selected. * Review the Connector history for error messages. * In rare cases, you may be requesting too much information and reaching API limitations or timeouts. If this is the case, you can review the history of the Connector run to see the error message and duration. If this is the case, you can reduce the number of accounts that are being pulled, choose a smaller number of metrics for the report that you are pulling, or reduce the timeframe that you are trying to pull. # Snowflake High Bandwidth With Advanced Partitions Connector Source: https://www.domo.com/docs/s/article/360061691114 **Note:** Snowflake will no longer support the username and password authentication mechanism as of November 2025. As a result, this connector will be retired in November 2025 and will no longer function. Please consider using one of the following connection methods instead: * [Cloud Integrations](/docs/s/article/4402322966807) * [Snowflake Key Pair High Bandwidth With Advanced Partitions](/docs/s/article/000005832) * [Snowflake OAuth High Bandwidth With Advanced Partitions](/docs/s/article/4402638182935) ## Snowflake Connector Migration Walkthrough As Snowflake is discontinuing username and password authentication, Snowflake connectors using this authentication method will be migrated to the OAuth version. This section helps users walk through the complete process of migrating their existing username and password Snowflake datasets to utilize the OAuth authentication version. Pls refer to the migration video ([https://youtu.be/rlG\_uNZwl\_U](https://youtu.be/rlG_uNZwl_U)) to make the transition smoother and minimize disruptions. ## Intro Snowflake is a cloud-based analytic data warehouse system. Use Domo's Snowflake High Bandwidth With Advanced Partitions connector to unload data from your Snowflake database into internal Amazon S3. The files are then downloaded from internal S3 into Domo. This connector should be preferred over the other Snowflake connectors if you are executing very large queries. It allows you to chose whether or not you want to partition your data. Unlike other partition connectors, it allows you to use partitioning on non date columns. To learn more about the Snowflake API, visit their page ([https://docs.snowflake.net/manuals](https://docs.snowflake.net/manuals)). You connect to your Snowflake account in the Data Center. This topic discusses the fields and menus that are specific to the Snowflake High Bandwidth With Advanced Partitions connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). **Note:** This connector only supports APPEND mode due to partitions. ## Prerequisites To connect to your Snowflake account and create a DataSet, you must have the following: * The full name of your account (provided by Snowflake). For US West Region **account\_name**, and All other regions **account\_name.region\_id**. This is the portion of your Snowflake URL immediately following https\://. Note that your full account name may include additional segments that identify the region and cloud platform where your account is hosted. The following table provides account name examples by cloud platform/region. For each row, it assumes your account name is "xy12345." * The username and password used to connect to your Snowflake host. ## Connecting to Your Snowflake Account This section enumerates the options in the Credentials and Details panes in the Snowflake High Bandwidth With Advanced Partitions Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Credentials Pane This pane contains fields for entering credentials to connect to your Snowflake account. The following table describes what is needed for each field:

Field

Description

Account Name

Enter your Snowflake account name. For more information, see Prerequisites.

Username

Enter the username you use to connect to your Snowflake host.

Password

Enter the password you use to connect to your Snowflake host.

Role

Enter your role.

**Note:** For any role that is used to set up the connector, the **READ**, **WRITE**, **CREATE STAGE**, and **SELECT** privileges must be turned on. For more details on each privileges, see [https://docs.snowflake.com/en/user-guide/security-access-control-privileges](https://docs.snowflake.com/en/user-guide/security-access-control-privileges#table-privileges). Once you have entered valid Snowflake credentials, you can use the same account any time you go to create a new Snowflake High Bandwidth With Advanced Partitions DataSet. You can manage Connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054). ## Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

Report

Select the Query Type. The following query types are available:

Warehouses

Select the warehouse containing the data you want to retrieve. The list populates with all of the warehouses you have access to based on your credentials.

Databases

Select the database containing the data you want to retrieve. The list populates with all of the databases you have access to based on your credentials.

Schemas

Select the database schema containing the data you want to retrieve. The list populates with all of the schemas you have access to based on your credentials.

Database Objects

Select the database object.

Tables

Select the database table you want to retrieve. The list populates with all of the tables you have access to based on your credentials. If you do not select a database table, the connector retrieves your entire database schema.

Table Columns

Select the table columns you want to retrieve. The list populates with all of the columns you have access to based on your credentials. If you do not select a table column, the connector retrieves your entire selected database table.

Table Query Helper

This field shows the query that is generated based on the selected fields.

Views

Select the view.

View Columns

Select the view columns that you would like to include in your report.

View Query Helper

This field shows the query that is generated based on the selected fields.

Query

Enter the SQL query to use to retrieve your data. You can use the Query Helper parameter to help you write a usable SQL query. To use the Query Helper, do the following: 1. Select your desired warehouse, database, database schema, database table, and table columns in each menu. 2. Copy the SQL statement that appears in the Query Helper field. 3. Paste the copied SQL statement into the Query field.

Partition Support

Choose whether or not to partition your data.

Partition Criteria

Select whether you want to partition the data using the date keys, non date keys, or meta query.

Partition Query to determine partition tags

Enter the partition meta query to determine the distinct partition tags (or keys). The column containing the Date data is your partition column. Example: SELECT DISTINCT(DATE\_COLUMN\_NAME) FROM TABLENAME

Partition Support Format

Select the partition support format.

Partition Column Name

Select the partition column name.

Past Year

Enter the number of past years that you want to get data for. Value can be X, where X is a positive integer. For example: 5.

Future Years

Enter the number of future years that you want to get data for. Value can be X, where X is a positive integer. For example:5.

Past Months

Enter the number of past months that you want to get data for. Value can be X, where X is a positive integer. For example:5

Future Months

Enter the number of future months that you want to get data for. Value can be X, where X is a positive integer. For example:5.

Past Days

Enter the number of past days that you want to get data for. Value can be X, where X is a positive integer. For example: 30.

Date Format

Select the required date format. By default yyyy-MM-dd will be used.

Custom Date Format

Enter the custom date format.

Partition Non Date Key Column Name

Select the partition column name.

## Other Panes For information about the remaining sections of the Connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQ You need the full name of your Snowflake account, and the username and password associated with your Snowflake host. You may also provide your role. Limits depend on your server configuration. Datasets can run as often as every 15 minutes. However, depending on the runtime of the query, datasets may need to run less frequently. Make sure that all the words, table names and field names are correctly spelled. Refer to the Query Helper field for query help. Before you can connect to a Snowflake database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses](/docs/s/article/360043630093). Both connectors support partitioning, but the Snowflake High Bandwidth With Advanced Partitions connector allows to select whether or not you want to use partitioning for your data. Also, unlike the other partition connectors, the Snowflake High Bandwidth With Advanced Partitions connector allows you to use partitioning on non date columns. ## Troubleshooting * Make sure your authentication remains valid. * Review the configuration to make sure that all required items have been selected. * Review the Connector history for error messages. * In rare cases, you may be requesting too much information and reaching API limitations or timeouts. If this is the case, you can review the history of the Connector run to see the error message and duration. If this is the case, you can reduce the number of accounts that are being pulled, choose a smaller number of metrics for the report that you are pulling, or reduce the timeframe that you are trying to pull. # Domo on Snowflake Source: https://www.domo.com/docs/s/article/4402322966807 ## Intro Cloud Integrations let you connect Domo directly to your Snowflake data—without moving it. Your data stays governed and secure in Snowflake, while Domo gives you powerful tools to explore, transform, and visualize it. Use this guide to set up the integration, including read/write access and OAuth configuration. **Note:** Magic ETL uses the Snowflake Cloud Integration, allowing you to transform your data directly in Snowflake. Learn about [Magic ETL on Snowflake](/docs/s/article/000005455). *** ## Architectural Overview Screenshot ## Prerequisites A Snowflake Cloud Integration setup consists of two parts: read-only or read/write. After the read-only setup is complete, you may begin using virtual tables that read from Snowflake to create cards, set up Alerts, or serve as inputs in Magic ETL flows. You can set up read-only and return later to set up the write portion. Before setting up the Snowflake connection, complete the following: 1. **Create a Snowflake service account —** Create a new Snowflake account specifically for this integration. This account must have read access to your default Snowflake environment in order to create virtual Snowflake tables in Domo. For the required permissions, see [Snowflake Minimum Permissions for Domo](/docs/s/article/Snowflake-Minimum-Permissions-for-Domo). 2. (Optional) **Create a Domo service account —** Create a new Domo account specifically for this integration. The account role must have the **Manage Cloud Accounts** and **Manage DataSet** grants enabled. For more information about roles and grants, see [Managing Custom Roles](/docs/s/article/360043438973). ### Account Creation—Write Before registering a Snowflake Cloud Integration for the write portion of the setup, you must complete the following: 1. **Create a default Snowflake database —** You need a Snowflake database that is exclusively for Domo to write Domo-managed tables. During setup, this database is the default. **Note:** Any tables not managed by Domo in this database are not seen by the Snowflake Cloud Integration. 2. (Conditional) **Place IP Addresses on an allowlist —** If your Snowflake environment restricts access based on IP address, place Domo IPs on an allowlist. For more information, see [Allow Domo IP Addresses for Network Connections](/docs/s/article/360043630093). **Important:** During the write setup process, Domo provides SQL statements to create the integration. These statements must be executed against your Snowflake environment by a Snowflake administrator with the `ACCOUNTADMIN` role. This is a Snowflake requirement that removes the need to store your Snowflake administrator credentials in Domo, which is especially important in larger organizations where your Snowflake administrator may not have Domo access. After the integration is established, you no longer need a Snowflake administrator account. ## Create or Manage Your Snowflake Integrations To access the integration management interface: 1. Navigate to **Data Warehouse**. 2. Select **Connect Data**. 3. Select **Snowflake** from the list of Cloud Integrations. Screenshot 4. The Domo on Snowflake page appears. * To create a new integration, select **Connect Snowflake** and continue to [Create a Snowflake Integration](#create-a-snowflake-integration). * To modify an existing integration, select **Manage Integrations**. The Snowflake cloud integrations list appears. Select the wrench icon next to an integration to see management options based on your access level. Screenshot Screenshot ### Create a Snowflake Integration Screenshot 1. In the **Name** field, enter a label to identify this Snowflake integration in Domo.\ The name doesn't need to match anything in Snowflake and can be changed later. 2. (Optional) In the **Description** field, enter a description to help others understand the purpose of the integration.\ This is only visible in the integration details. 3. Select an existing Snowflake service account, or select **Add account** to create a new one.\ This account authenticates to Snowflake and determines access to tables. For guidance on creating a service account, see [Create a Snowflake Account](#create-a-snowflake-account). Screenshot 4. Select the warehouse to use for querying data.\ You can assign multiple warehouses later for optimization or specific use cases. Screenshot 5. Select **Finish Setup**. When the integration is created successfully, a confirmation screen appears. Screenshot ## Create a Snowflake Account Every Snowflake integration in Domo relies on an authenticated Snowflake service account. After you create a service account, you can reuse it across multiple integrations. To create a Snowflake service account in Domo: 1. In the **Name** field, enter a name to identify the Snowflake service account within Domo.\ This name can be changed later. **Tip:** Use a clear and distinct name to differentiate between multiple service accounts and integrations. 2. In the **Account Identifier** field, enter your Snowflake account identifier. The account identifier is the subdomain that appears before `.snowflakecomputing.com` in your Snowflake URL. You can locate it in several ways: * **From the Snowflake URL** — When you're signed in to Snowsight, the browser URL takes the form `https://.snowflakecomputing.com` (for example, `xy12345.us-east-1.snowflakecomputing.com`). The portion before `.snowflakecomputing.com` is your account identifier. * **From Snowsight** — In the lower-left corner of Snowsight, hover over your account name to display the account details popover, which lists the account identifier and locator. You can also navigate to **Admin > Accounts** to view account identifiers for the accounts in your organization. * **From a SQL worksheet** — Run `SELECT CURRENT_ACCOUNT();` to return the account locator, or `SELECT CURRENT_ORGANIZATION_NAME();` together with `SELECT CURRENT_ACCOUNT_NAME();` to return the organization-qualified identifier. Snowsight account details popover showing the account identifier (FJB74201), organization (SCBPTBU), cloud, region, edition, and locator. For full details on the available identifier formats, see the [Snowflake account identifier documentation](https://docs.snowflake.com/en/user-guide/admin-account-identifier). 3. Select your authentication method: * **Key Pair (Recommended)**\ Snowflake is phasing out single-factor password sign-ins. Key-pair authentication is more secure and future-proof. See their [security MFA rollout](https://docs.snowflake.com/en/user-guide/security-mfa-rollout) and [key pair auth](https://docs.snowflake.com/en/user-guide/key-pair-auth) documentation. Add the public key to your Snowflake user: ```sql theme={"dark"} ALTER USER "" SET RSA_PUBLIC_KEY='' ``` Replace *username* and *public\_key* with your actual values. In the **Private Key** field, upload your private key file (.p8 format). Optionally, enter the passphrase if your key pair includes one. Screenshot * **Username & Password**\ Enter your Snowflake username and password. Screenshot 4. (Optional) In the **Default Role** field, enter the Snowflake role to assign to this service account.\ If left blank, Snowflake applies the default role configured for the user in Snowflake. ## Configure Write & Native Transform To write data from Domo connectors to Snowflake, or run Magic ETL DataFlows directly in Snowflake, enable one or both of the following capabilities: * **Write to Snowflake from connectors —** Allows Domo to create and update tables in Snowflake using data loaded through connectors. * **Execute Magic ETL transformations natively —** Runs Magic ETL DataFlows directly in Snowflake rather than in Domo's execution environment. Both capabilities are optional. Many integrations are read-only. Even when write or transform is enabled, access must be explicitly granted to individuals or groups. Basic access does not automatically include write or transform privileges. You can manage access levels on the accounts page by selecting **Account sharing** next to the relevant Snowflake service account. ### Prerequisites A Snowflake administrator (or someone with equivalent privileges) must be available to execute SQL queries that create a dedicated database and grant access to the service account. For the minimum permissions required and the SQL to configure them, see [Snowflake Minimum Permissions for Domo](/docs/s/article/Snowflake-Minimum-Permissions-for-Domo). ### Setup From your integration's settings page, navigate to **Write & transform** and select **Set up write & transform**. Screenshot The Configure Write & Native Transform dialog appears. 1. Toggle on the capabilities you want to enable: * **Write to Snowflake from connectors** * **Execute Magic ETL transformations natively** 2. Select the default **Database** and **Schema** where Domo writes data.\ If the schema doesn't exist, Domo creates it when selected in Magic ETL. **Tip:** You can select other databases and schemas in Magic ETL, but the service account must have the necessary grants. Screenshot 3. In the **Default Role** field, enter the Snowflake role Domo uses for write and transform operations.\ Domo uses this role to generate the SQL in the next step. Screenshot 4. Have a Snowflake user with the `ACCOUNTADMIN` role run the generated SQL to: * Create the write-back database * Grant access to the service account * Create a DOMO\_UTIL schema for Domo-managed resources **Note:** You can configure access to multiple databases if needed, either now or later. 5. In the **Temporary artifact storage** field, specify the database Domo uses for temporary storage during native transform execution.\ This can be the same database selected in step 2, or a separate database if you prefer to isolate temporary artifacts. Screenshot 6. On the **Finalize Write & Native Transform Integration** page, review the permissions Domo requires.\ Select **I understand that Domo can make changes to my Snowflake environment**, then select **Done**. Screenshot After setup is complete, the integration's settings page shows **Write** and **Native Transform** as enabled. Screenshot ## Configure OAuth OAuth allows Domo to query Snowflake data in the context of individual users rather than a shared service account, and is optional. When enabled, users accessing cards or previewing DataSets connected via OAuth are prompted to authenticate with their Snowflake credentials. **Note:** OAuth applies only to reading data from Snowflake. Other operations—including Magic ETL, write-back, and native transform—continue to use the Snowflake service account regardless of OAuth configuration. ### Prerequisites A Snowflake administrator (or someone with equivalent privileges) must first configure a security integration in Snowflake. ### Configure OAuth in Snowflake 1. In Snowflake, modify and run the following query to define the security integration.\ Replace *name\_goes\_here* with a meaningful name—this name is used in subsequent queries. ```sql theme={"dark"} create or replace security integration type = oauth enabled = true oauth_client = custom oauth_client_type = 'CONFIDENTIAL' oauth_redirect_uri = 'https://oauth.domo.com/api/data/v1/oauth/providers/snowflake-oauth/exchange' oauth_issue_refresh_tokens = true oauth_refresh_token_validity = 86400; ``` 2. Update `oauth_refresh_token_validity` to set how long refresh tokens remain valid: * 1 day = 86400 seconds * Max = 7776000 seconds (90 days) * Min = 3600 seconds (1 hour) 3. Run the following query to verify the integration: ```sql theme={"dark"} desc security integration ; ``` 4. Run the following query to retrieve the client ID and secret: ```sql theme={"dark"} select system$show_oauth_client_secrets(''); ``` 5. Copy the client ID and secret for use in Domo. ### Configure OAuth in Domo From your integration's settings page, navigate to **OAuth** and select **Set up OAuth**. Select **Add OAuth Config...** to create a new OAuth configuration. Screenshot 1. In the **Name** field, enter a name to identify this OAuth configuration within Domo. 2. In the **Account Identifier** field, enter your Snowflake account identifier.\ You can find it under **Account** > **View Account Details** in Snowflake. 3. In the **Client ID** and **Client Secret** fields, paste the values retrieved from Snowflake. 4. In the **Primary Role** field, select the Snowflake role to apply to all Domo users. Screenshot 5. Select **Connect**, then sign in using your Snowflake credentials. 6. Review the requested permissions and select **Allow** to complete the setup. ## FAQ Domo performs different activities within the Snowflake account, such as data loading, querying, and data transformation. For most use cases, a small-sized multi-cluster warehouse (multi-purpose for load, query, and transformation) set to scale up automatically is recommended. You can choose the max cluster size to put an upper bound on scaling and limit the cost envelope. When you are ready for production workloads and are considering whether to use existing functional warehouses or set up new warehouses for the Domo integration, see the [Domo blog post on optimizing a Snowflake Cloud Integration](https://www.domo.com/blog/how-to-optimize-data-warehouse-strategy-with-cloud-amplifier). With your data in Snowflake, Domo supports two different mechanisms for transforming data: 1. **DataSet Views —** DataSet Views provide the Views Explorer tool to create data transformations on your Snowflake DataSets. You can perform operations such as filtering, grouping, aggregation, `JOIN`s, `UNION`s, and creating calculated columns from a graphic user interface. DataSet Views are created as virtual DataSets, with queries sent back to the parent DataSets. **Note:** Creating a DataSet View in Domo does not create a View (normal or materialized) in Snowflake. The View definition is stored in Domo, and the resulting query is sent to Snowflake table(s) when needed. 2. **Magic ETL DataFlows —** Magic ETL is supported with Domo running on a Snowflake Cloud Integration. Using Magic ETL with Snowflake data results in data being exported from Snowflake to Magic ETL in a transient state, processed, and written back to Snowflake. Domo only operates on this data in a transient fashion and does not store DataFlow outputs in Domo. (They are sent to the Snowflake warehouse.) **Note:** Data is cached in the Magic ETL execution environment for seven days, or the two most recent data versions from that Magic ETL execution. When you connect Domo to your Snowflake account, Domo operates over two classes of databases and underlying tables. Tables you create and update directly through independent pipelines or ingestion mechanisms can be explored and registered in Domo, accessible in a read-only fashion. Domo can read and directly query these customer-managed databases. Domo recommends creating a new database for read/write access. Domo uses this Domo-managed database to write data that comes in through the Domo ingestion pipeline, using the thousands of connectors available to bring data into Snowflake. Domo also uses this Domo-managed database to create outputs of data transformations (DataFlow outputs). Permissions originating in Snowflake are not programmatically passed into Domo. However, you can use Domo's native permission model and Personalized Data Permissions (PDP) for data security to manage data access to underlying assets in Snowflake. * **Leaving data in Snowflake —** The key difference is that all Snowflake connectors copy data from Snowflake into Domo, while a Snowflake Cloud Integration leaves the data in Snowflake. * **Bulk create —** A Snowflake Cloud Integration lets you look up and bulk select multiple tables to immediately create multiple unique DataSets. To do this with connectors, you would have to configure each DataSet individually with a connector. This is the standard behavior for Snowflake views. Snowflake endpoints do not provide the number of rows unless the data is explicitly queried. Make sure that you own the user or have the `SECURITY/ADMIN` Snowflake role. Follow the instructions in the [Snowflake key pair authentication documentation](https://docs.snowflake.com/en/user-guide/key-pair-auth). Make sure that the passphrase matches the one you used to create your key pair and that you have executed the ALTER USER statement successfully. ## Troubleshoot If you experience a problem with your Snowflake Cloud Integration, the following information may help resolve the issue. You can also submit a request to [Domo Support](https://domo-support.domo.com/). ### Missing Tables If you cannot find tables that your account has access to, ensure the table is materialized. Transient or Temporary tables on the Snowflake side cannot be used to create DataSets through a Snowflake Cloud Integration. ### Setup Problems If you have problems setting up your Snowflake Cloud Integration, follow the steps below: #### Check Snowflake Service Account 1. Log in to Snowflake with the service account credentials. 2. Ensure you can view the default Snowflake Database and query the tables you expect to import. #### Assign Correct Role Ensure that a Snowflake administrator with the `ACCOUNTADMIN` role executes the SQL provided by Domo in Snowflake. #### Use the Correct URL Make sure that the Snowflake connection URL in Domo matches the Snowflake login URL. You can find the URL on the Snowflake login page. The URL is in this format: *instancename*.*region*.snowflakecomputing.com. ## Next Steps Now that you're integrated, learn how to use [Magic ETL on Snowflake](/docs/s/article/000005455) or how to [Create a Magic ETL DataFlow](/docs/s/article/360055259234). # Snowflake OAuth High Bandwidth With Advanced Partitions Connector Source: https://www.domo.com/docs/s/article/4402638182935 ## Intro Snowflake is a cloud-based analytic data warehouse system. Use Domo's Snowflake Internal Unload Advanced Partition connector to unload data from your Snowflake database into internal Amazon S3. The files are then downloaded from internal S3 into Domo. This connector should be preferred over the other Snowflake connectors if you are executing very large queries. It allows you to chose whether or not you want to partition your data. Unlike other partition connectors, it allows you to use partitioning on non date columns. To learn more about the Snowflake API, visit their page ([https://docs.snowflake.net/manuals](https://docs.snowflake.net/manuals "https://docs.snowflake.net/manuals") ). You connect to your Snowflake account in the Data Center. This topic discusses the fields and menus that are specific to the Snowflake Internal Unload Advanced Partition connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Best Practices **Important:** Snowflake asserts your need to manually re-connect your Domo account every time the account expires. The Snowflake integration controls how often the account will expire. If it is set to expire the refresh tokens every 90 days, then you will need to reconnect the account every 90 days. If you would like to increase the refresh timeout to more than 90 days, then you will need to contact the **Snowflake Support**, and they can increase the maximum timeout from 90 days to 1 year. ## Prerequisites To connect to your Snowflake account and create a DataSet, you must have the following: * The full name of your account (provided by Snowflake). For US West Region **account\_name**, and All other regions **account\_name.region\_id**. This is the portion of your Snowflake URL immediately following https\://. Note that your full account name may include additional segments that identify the region and cloud platform where your account is hosted. The following table provides account name examples by cloud platform/region. For each row, it assumes your account name is "xy12345." Region.png * The client ID and client secret provided by Snowflake when the client is registered. ## Connecting to Your Snowflake Account This section enumerates the options in the Credentials and Details panes in the Snowflake Internal Unload Advanced Partition Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ### Credentials Pane This pane contains fields for entering credentials to connect to your Snowflake account. The following table describes what is needed for each field:

Field

Description

Account Name Enter your Snowflake account name. For more information, see Prerequisites.
Client ID Enter your Client ID (provided by Snowflake when the client is registered.)
Client Secret Enter your Client secret (provided by Snowflake when the client is registered.)
Role Enter your role.
Once you have entered valid Snowflake credentials, you can use the same account any time you go to create a new Snowflake Internal Unload Advanced Partition DataSet. You can manage Connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054). ### Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

Report

Select the Query Type. The following query types are available:

Custom Query Enter the SQL query to execute.
Query Builder Select a table and fields to auto generate your query.
Warehouses Select the warehouse containing the data you want to retrieve. The list populates with all of the warehouses you have access to based on your credentials.
Databases Select the database containing the data you want to retrieve. The list populates with all of the databases you have access to based on your credentials.
Schemas Select the database schema containing the data you want to retrieve. The list populates with all of the schemas you have access to based on your credentials.
Database Objects Select the database object.
Tables Select the database table you want to retrieve. The list populates with all of the tables you have access to based on your credentials. If you do not select a database table, the connector retrieves your entire database schema.
Table Columns Select the table columns you want to retrieve. The list populates with all of the columns you have access to based on your credentials. If you do not select a table column, the connector retrieves your entire selected database table.
Table Query Helper This field shows the query that is generated based on the selected fields.
Views Select the view.
View Columns Select the view columns that you would like to include in your report.
View Query Helper This field shows the query that is generated based on the selected fields.
Query

Enter the SQL query to use to retrieve your data. You can use the Query Helper parameter to help you write a usable SQL query. To use the Query Helper , do the following:

  1. Select your desired warehouse, database, database schema, database table, and table columns in each menu.

  2. Copy the SQL statement that appears in the Query Helper field.

  3. Paste the copied SQL statement into the Query field.

Partition Support Select 'Yes' if you want to partition your data; otherwise, select 'No.'
Partition Criteria Select whether you want to partition the data using the date keys, non date keys, or meta query.
Partition Query to determine partition tags

Enter the partition meta query to determine the distinct partition tags (or keys). The column containing the Date data is your partition column.

Example: SELECT DISTINCT(DATE\_COLUMN\_NAME) FROM TABLENAME

Partition Support Format Select the partition support format.
Partition Column Name Select the partition column name.
Past Year Enter the number of past years that you want to get data for. Value can be X, where X is a positive integer. For example: 5.
Future Years Enter the number of future years that you want to get data for. Value can be X, where X is a positive integer. For example:5.
Past Months Enter the number of past months that you want to get data for. Value can be X, where X is a positive integer. For example:5
Future Months Enter the number of future months that you want to get data for. Value can be X, where X is a positive integer. For example:5.
Past Days Enter the number of past days that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Date Format Select the required date format. By default yyyy-MM-dd will be used.
Custom Date Format Enter the custom date format.
Partition Non Date Key Column Name Select the partition column name.
### Other Panes For information about the remaining sections of the Connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQs To avoid this error, you need to refresh the token. Snowflake asserts your need to manually re-connect your Domo account every time the account expires. The Snowflake integration controls how often the account will expire. If it is set to expire the refresh tokens every 90 days, then you will need to reconnect the account every 90 days. If you would like to increase the refresh timeout to more than 90 days, then you will need to contact the Snowflake Support, and they can increase the maximum timeout from 90 days to 1 year. You need the full name of your Snowflake account, and the client ID and Client secret provided by Snowflake when the client is registered. You may also provide your role. Limits depend on your server configuration. Datasets can run as often as every 15 minutes. However, depending on the runtime of the query, datasets may need to run less frequently. Make sure that all the words, table names and field names are correctly spelled. Refer to the Query Helper field for query help. Before you can connect to a Snowflake database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses](/docs/s/article/360043630093). Both connectors support partitioning, but the Snowflake Internal Unload Advanced Partition connector allows to select whether or not you want to use partitioning for your data. Also, unlike the other partition connectors, the Snowflake Internal Unload Advanced Partition connector allows you to use partitioning on non date columns. ## Troubleshooting * Make sure your authentication remains valid. * Review the configuration to make sure that all required items have been selected. * Review the Connector history for error messages. * In rare cases, you may be requesting too much information and reaching API limitations or timeouts. If this is the case, you can review the history of the Connector run to see the error message and duration. If this is the case, you can reduce the number of accounts that are being pulled, choose a smaller number of metrics for the report that you are pulling, or reduce the timeframe that you are trying to pull. # Google BigQuery Enterprise OAuth Writeback Connector Source: https://www.domo.com/docs/s/article/4403099754903 ## Intro Google BigQuery is a serverless, highly scalable, and cost-effective cloud data warehouse designed to help you make informed decisions quickly, so you can transform your business with ease. It's a cloud-based big data analytics web service for processing very large read-only data sets. Use Domo's Google BigQuery Enterprise OAuth Writeback connector to securely export your data from a Domo DataSet into a BigQuery table. To learn more about the BigQuery API, go to [https://cloud.google.com/bigquery/docs/reference/v2/](https://cloud.google.com/bigquery/docs/reference/v2/). You export data to BigQuery in the Data Center. This topic discusses the fields and menus that are specific to the Google BigQuery Enterprise OAuth Writeback connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). **Note:** The owner of a writeback dataset must also be an owner or co-owner of the input dataset. ## Prerequisites To configure this connector, you will need the client ID and client secret associated with your Google BigQuery account. ## Configuring the Connection This section enumerates the options in the **Credentials** and **Details** panes in the Domo's Google BigQuery Enterprise OAuth Writeback Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet,** are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Google BigQuery account. The following table describes what is needed for each field:
Field Description
Client ID Enter the client ID associated with your Google BigQuery account.
Client Secret Enter the client secret associated with your Google BigQuery account.
The Domo Google BigQuery Enterprise OAuth Writeback connector uses OAuth to connect, so there is no need to enter your Google credentials within Domo. After entering your client ID and client secret, click **Connect** to open the Google OAuth screen where you can enter your Google credentials. Once you have entered valid credentials, you can use the same account any time you go to set up a new Domo-Google BigQuery connection. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). **Note:** If you are already logged into Google when you connect in Domo, you are authenticated automatically when you click **Connect**. If you want to connect to an account that is different from the one you are logged into, you must first log out of the logged in Google account. ### Details Pane This pane contains a number of fields for specifying your data and indicating where it's going.

Menu

Description

BigQuery Project Select a project from the available list of projects.
BigQuery DataSet Select the BigQuery DataSet Name. Datasets are top-level containers that are used to organize and control access to your tables and views. A table or view must belong to a dataset, so you need to create at least one dataset before loading data into BigQuery.
BigQuery Table Name
Enter the BigQuery table name you want to send Domo data to. The table you indicate will be deleted and recreated with each run with the name entered here.
Input Domo DataSet ID

Enter your Domo dataset ID (GUID) located in the dataset URL.

Example: [https://customer.domo.com/datasources/](https://customer.domo.com/datasources/) aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee /details/settings

### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ## FAQs This connector will allow you to write data from Domo to BigQuery. It connects via a customer defined Google app to support OAuth connections, so you'll need a valid client id, client secret, username and password that has access to BigQuery. Once connected, you'll specify the location of the BigQuery Project and Table to write to. You need the client ID and client secret associated with your Google BigQuery account. Your Google account must have permissions to access the tables and data needed for the query. The login process uses the OAuth process, so your Google credentials are never seen or stored by Domo. This keeps your login secure. You can revoke Domo's access to your account at any time. As often as needed. None Your Domo input dataset id is in the URL of the dataset you are exporting data from. Example: `https://customer.domo.com/datasources/aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee/details/settings` Datasets are the top-level containers that are used to organize and control access to your tables and views. A table or view must belong to a dataset, so you need to create at least one dataset before loading data into BigQuery. # Google BigQuery High Bandwidth Connector Source: https://www.domo.com/docs/s/article/4403895116823 ## Intro Google BigQuery is a serverless, highly scalable, and cost-effective cloud data warehouse designed to create, manage, share, and query data. It's a cloud-based big data analytics web service for processing very large read-only data sets. With this connector you can securely pull large data from a specified project into Domo. Google BigQuery queries are written using a variation of the standard SQL SELECT statement. Once your BigQuery data is in Domo, you can combine it with other data sources, find new insights, and collaborate your data. To learn more about the BigQuery API, go to [https://cloud.google.com/bigquery/docs/reference/v2/](https://cloud.google.com/bigquery/docs/reference/v2/). The Google BigQuery High Bandwidth Connector is a "Cloud App" connector, meaning it retrieves data stored in the cloud. In the Data Center, you can access the connector page for this and other Cloud App connectors by clicking **Cloud App** in the toolbar at the top of the window. This topic discusses the fields and menus that are specific to the Google BigQuery High Bandwidth connector user interface. For general information about adding DataSets, setting update schedules, and editing DataSet information, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ## Prerequisites To connect to a BigQuery High Bandwidth account, you must have a Google BigQuery service account JSON key and Google Cloud Storage service account JSON key. To generate a Google BigQuery service account JSON key, do the following: 1. In the Google Cloud Platform Console, open the IAM & Admin page. 2. Click **Service accounts** in the left-hand navigation pane. 3. Select your project and click **Open**. 4. Click **Create Service Account**. 5. Enter a name and description for the service account. 6. Click **Create**. **Note:** You may need the “BigQuery Admin” role in the service account permissions dialog. Please consult with your Google administrator for additional guidance. 7. Select **Project > Owner**. 8. Click **Continue**. 9. Click **Create key**. 10. Select **JSON** as the key type. 11. Click **Create**. A private key will be saved to your computer. To generate a Google Cloud Storage service account JSON key, do the following: 1. In the Google Cloud Platform Console, open the IAM & Admin page. 2. Click **Service accounts** in the left-hand navigation pane. 3. Select your project and click **Open**. 4. Click **Create Service Account**. 5. Enter a name and description for the service account. 6. Click **Create**. 7. Click **Create key**. 8. Select **JSON** as the key type. 9. Click **Create**. A service account key file will be saved to your computer. ## Connecting to BigQuery This section enumerates the options in the Credentials and Details panes in the Google BigQuery Service Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your BigQuery account. The following table describes what is needed for each field:

Field

Description

Service Account Key JSON BigQuery

Copy and paste the JSON for your BigQuery service account key. For information about creating a key, see "Prerequisites," above.

Service Account Key JSON Google Cloud Storage

Copy and paste the JSON for your Google Cloud Storage account key. For information about creating a key, see "Prerequisites," above.

Once you have entered valid keys, you can use the same account any time you go to create a new Google BigQuery High Bandwidth DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane This pane contains a number of fields and menus you can use to configure your report.

Menu

Description

Report

Select the BigQuery report type to run. The following reports are available:

Query

Runs a BigQuery SQL query and returns results if the query completes.

DataSet ID

Select the BigQuery dataset id for your data. For more information about BigQuery datasets, see Introduction to DataSets .

Table ID

Select the BigQuery table id for your data. For more information about tables, see Introduction to Tables .

Google Cloud Storage Bucket Name

Select the Google Cloud Storage bucket name that will be used for temporary storage as we transfer your data into Domo.

User Query

Enter a query to execute. Only StandardSQL query is supported.

Force to String

Enter a comma separated list of fields that need to be treated as STRING in Domo.

Force to Number

E nter a comma separated list of fields that need to be treated as NUMBER in Domo.

Upsert Key Column(s)

Enter upsert key column name or a comma separated list of upsert key column names. This is Required only when the Update method is Merge .

Table Name

Select the table you want to pull data from.

Processing Location

Enter the location where your query will run. Queries running in a specific location may only reference data in that location.

Max Results

Enter the maximum number of results you want to return in your report. The default is 10,000 results per page. If your DataSet throws an "Out of Memory" error, decrease this number.

Use Google BigQuery Schema

Select this checkbox to use the schema received from Google BigQuery.
This is useful when a column's datatype may be perceived incorrectly to Domo.

Example: Your table may contain '123' in a String column.

### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Troubleshooting * Ensure that the credentials have the proper access to the query the tables needed. * Make sure the queries are correct and calling the correctly named data sources. # Google BigQuery High Bandwidth OAuth Enterprise Connector Source: https://www.domo.com/docs/s/article/4407650069527 ## Intro Google BigQuery is a serverless, highly scalable, and cost-effective cloud data warehouse designed to help you make informed decisions quickly, so you can transform your business with ease. It's a cloud-based big data analytics web service for processing very large read-only data sets. With this connector you can securely pull large data from a specified project into Domo. Google BigQuery queries are written using a variation of the standard SQL SELECT statement. Once your BigQuery data is in Domo, you can combine it with other data sources, find new insights, and collaborate your data. Use Domo's Google BigQuery High Bandwidth OAuth Connector to securely pull large data from a specified project and analyze it using SQL queries. To learn more about the BigQuery API, go to [https://cloud.google.com/bigquery/docs/reference/v2/](https://cloud.google.com/bigquery/docs/reference/v2/). The Google BigQuery High Bandwidth OAuth Enterprise Connector is a "Cloud App" connector, meaning it retrieves data stored in the cloud. In the Data Center, you can access the connector page for this and other Cloud App connectors by clicking **Cloud App** in the toolbar at the top of the window. This topic discusses the fields and menus that are specific to the Google BigQuery High Bandwidth OAuth Enterprise Connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Prerequisites To connect to BigQuery you must have your client ID and client secret associated with your OAuth client. ## Connecting to BigQuery This section enumerates the options in the **Credentials** and **Details** panes in the Google BigQuery High Bandwidth OAuth Enterprise Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ### Credentials Pane The Domo Google BigQuery High Bandwidth OAuth Enterprise Connector uses OAuth to connect. You need to enter the client ID and client secret in Domo.

Field

Description

Client ID Enter your client ID.
Client Secret Enter your client secret.
Once you have entered valid credentials, you can use the same account any time you go to create a new Google BigQuery High Bandwidth OAuth Enterprise DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054). **Note:** If you are already logged into Google when you connect in Domo, you are authenticated automatically when you click **Connect**. If you want to connect to an account that is different from the one you are logged into, you must first log out of the current Google account. ### Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

How would you like to import your data? Select the import method you want to use to update your Domo data.
Partition Criteria Select whether you want to partition your data using the date keys, non-date keys, or meta query.
Partition Column Name Select the partition column name. Only the date type columns will be available in the options.
Partition Support Format Choose how to format the values in the selected date partition columns.
Past Days Enter the number of past days that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Past Months Enter the number of past months that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Past Years Enter the number of past years that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Future Months Enter the number of future months that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Future Years Enter the number of future years that you want to get data for. Value can be X, where X is a positive integer. For example: 30.
Partition Non Date Key Column Name Select the partition column name. Values in the selected column would be used as the partition tags
Partition Query to determine partition tags Enter the partition query to determine the distinct partition tags. Example: SELECT DISTINCT(COLUMN\_NAME) FROM `DATASET_ID`.`TABLENAME`.

Report

Select the Google BigQuery High Bandwidth OAuth Enterprise report you want to run. The following reports are available:

Query Runs a BigQuery SQL query and returns results upon query completion.
Project ID Select a project from the available list of projects.

DataSet ID

Select the BigQuery dataset id for your data.

For more information about the BigQuery datasets, see [https://cloud.google.com/bigquery/docs/datasets-intro](https://cloud.google.com/bigquery/docs/datasets-intro) .

Google Cloud Storage Bucket Name Select the Google Cloud Storage bucket name that will be used for temporary storage as the connector transfers your data into Domo.
User Query Enter a query to execute. Only standard SQL query is supported.
Force To String Enter a comma separated list of fields that needs to be treated as STRING in Domo.
Force To Number Enter a comma separated list of fields that needs to be treated as NUMBER in Domo.
### Other Panes For information about the remaining sections of the Connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQs Use this connector to import any size dataset from Google BigQuery. This connector connects via OAuth using a customer-defined Google app. You'll need a client and secret, and a valid username and password that has access to both BigQuery and Google Cloud Services (GCS). Data from BigQuery is first unloaded to the specified GCS and then loaded into Domo to optimize data imports. This connector supports replace, append and upsert update modes. This connector does not support partitions. You need your client ID and client secret associated with your OAuth client. As often as needed. None ## Troubleshooting * Make sure your authentication remains valid. * Review the configuration to make sure that all required items have been selected. * Review the Connector history for error messages. # Google BigQuery Rakuten Custom Unload Connector Source: https://www.domo.com/docs/s/article/4407975319959 ## Intro Google BigQuery is a serverless, highly scalable, and cost-effective cloud data warehouse designed to create, manage, share, and query data. It's a cloud-based big data analytics web service for processing very large read-only data sets. With this connector you can unload larger results from BigQuery through the assistance of the Google Cloud Storage service. Google BigQuery queries are written using a variation of the standard SQL SELECT statement. To learn more about the BigQuery API, go to [https://cloud.google.com/bigquery/docs/reference/v2/](https://cloud.google.com/bigquery/docs/reference/v2/). The Google BigQuery Rakuten Custom Unload Connector is a "Cloud App" connector, meaning it retrieves data stored in the cloud. In the Data Center, you can access the connector page for this and other Cloud App connectors by selecting **Cloud App** in the toolbar at the top of the window. This article covers the fields and menus specific to the Google BigQuery Rakuten Custom Unload Connector interface. For general information about adding DataSets, setting update schedules, and editing DataSet information, see [Adding a DataSet Using a Connector](/docs/s/article/360042926274). *** ## Prerequisites To connect to BigQuery and create a DataSet, you must have the following: * A Google BigQuery service account JSON key * A Google Cloud Storage service account JSON key To generate a Google BigQuery service account JSON key, do the following: 1. In the [Google Cloud Platform Console](https://console.cloud.google.com/), open the **IAM & Admin** page. 2. Select **Service accounts** in the left-hand navigation pane. 3. Select your project and select **Open**. 4. Select **Create Service Account**. 5. In the Create service account pane, enter a name and description for the service account, and select **Create and continue**. 6. In the **Grant this service account access to the project** section, select **Project** > **Owner** from the **Select a role** dropdown. 7. Select **Done**. **Note:** You may need the "BigQuery Admin" role in the service account permissions dialog. Consult with your Google administrator for additional guidance. 8. To create a new JSON key, in the **Service accounts** pane, open the three-dot expansion menu and select **Manage keys**. 9. In the **Keys** section, select **Add Key** > **Create new key**. 10. Select **JSON** as the key type and select **Create**. 11. Select **Create**. A private key is saved to your computer. ## Connect to BigQuery This section enumerates the options in the Credentials and Details panes on the Google BigQuery Rakuten Custom Unload Connector page. The components of the other panes on this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Connector](/docs/s/article/360042926274). ### Credentials Pane This pane contains fields for entering credentials to connect to your BigQuery account. The following table describes what is needed for each field: | Field | Description | | --------------------------------------------- | ------------------------------------------------------------------ | | Service Account Key JSON BigQuery | Copy and paste the JSON for your BigQuery service account key. | | Service Account Key JSON Google Cloud Storage | Copy and paste the JSON for your Google Cloud Storage account key. | Once you have entered valid keys, you can use the same account any time you go to create a new Google BigQuery Rakuten Custom Unload DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Manage Connector/Adapter Accounts](/docs/s/article/360042926054). ### Details Pane This pane contains a number of fields and menus you can use to configure your report. | Menu | Description | | ------------------------------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | How would you like to import data into Domo? |
Import TypeDescription
Standard UpdateTo use standard update, select the Replace or Append mode in the scheduling section.
Use PartitionsTo use partition update, select the Append mode in the scheduling section.
Use UpsertTo use upsert update, select the Merge mode in the scheduling section.
| | Project ID | Select the Google project ID obtained from the service key. | | Google BigQuery Dataset ID | Select the BigQuery dataset ID for your data. For more information about BigQuery datasets, see [Introduction to DataSets](https://cloud.google.com/bigquery/docs/datasets-intro). | | Google Cloud Storage Bucket Name | Select the Google Cloud Storage bucket name that is used for temporary storage as we transfer your data into Domo. | | Query | Enter a query to execute. Only Standard SQL queries are supported. | | How would you like to perform your partition? | Select whether you want to perform partition by date or by meta query. | | Partition Meta Query to determine partition tags | Enter partition query to determine the distinct partition tags. | | Partition Column Name | Enter partition column name. | | Days Back | The number of days back that you would like to get data. Specify 7 to get data for the last 7 days. | | Upsert Key Column(s) | Enter upsert key column name or a comma-separated list of upsert key column names. **This is required only when the Update method is Merge.** | ### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](/docs/s/article/360042926274). ## Troubleshoot * Ensure that the credentials have the proper access to query the tables needed. * Make sure the queries are correct and calling the correctly named data sources. # Amazon Redshift Connector Source: https://www.domo.com/docs/s/article/4409682973463 ## Intro Amazon Redshift is a fast, scalable data warehouse that makes it simple and cost-effective to analyze all your data across your data warehouse and data lake. Domo can make your Redshift data come to life. Whether it's one Redshift data source or a thousand different data sources, bring them all into Domo for a centralized experience to view and analyze everything at the same time. Domo connects directly to Redshift and delivers the information you need in real-time visualizations that make analysis easier. Plus, you can see your Redshift data alongside metrics from any other system, all in a single platform. Use Domo's Amazon Redshift Connector to pull data from your Redshift database and compile custom reports. You indicate the data you want by inputting an SQL query. For more information about the Redshift API, visit their website. ([https://docs.aws.amazon.com/redshift/latest/dg/c\_redshift-sql.html](https://docs.aws.amazon.com/redshift/latest/dg/c_redshift-sql.html)) The Amazon Redshift Connector is a "Database" connector, meaning it retrieves data from a database based on a query. In the Data Center, you can access the connector page for this and other Database connectors by clicking **Database** in the toolbar at the top of the window. You connect to your Redshift database in the Data Center. This topic discusses the fields and menus that are specific to the Redshift connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). **Note:** Depending on your network's structure, you may need to whitelist any IP addresses necessary for the data connector to retrieve data. Contact your IT administrator for assistance.

Primary Use Cases

Pulling data out of a Redshift data warehouse or data mart.

Primary Metrics

This depends on the data stored in the Redshift instance.

Primary Company Roles

  • BI leads

  • IT roles

Ease of Use (on a 1-to-10 scale with 1 being easiest)

6

## Best Practices Try to limit the results set size as much as possible. To speed the acquisition of the data, "fetch size" can be increased; however, setting it too high can cause connector run failures as well as performance problems with the Redshift instance. 10000 is a good place to start. ## Prerequisites To connect to a Redshift database and create a DataSet, you must have the following: * The username and password you use to log into your Redshift database * The host name for the database server (for example, [db.company.com](http://db.company.com) ) * The port number for the database * The database name CA certificate text or URL path is required *only* if you select **Certificate String** or **URL Path**, respectively, in the **Certificate Format** menu. ### Creating a Redshift account To create a Redshift user account, contact your Redshift Database Administrator (DBA) and have them follow these directions: By default, only the master user that you created when you launched the cluster has access to the initial database in the cluster. To grant other users access, you must create one or more user accounts. Database user accounts are global across all the databases in a cluster; they do not belong to individual databases. Use the CREATE USER command to create a new database user. When you create a new user, you specify the name of the new user and a password. A password is required. It must have between 8 and 64 characters, and it must include at least one uppercase letter, one lowercase letter, and one numeral. For example, to create a user named GUEST with password ABCd4321, issue the following command: `create user guest password 'ABCd4321';` ### Whitelisting IP addresses Before you can connect to a Redshift database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses for Connectors](/docs/s/article/360043630093 "Whitelisting IP Addresses for Connectors"). ## Connecting to Your Redshift Database This section enumerates the options in the **Credentials** and **Details** panes in the Amazon Redshift Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ### Credentials Pane This pane contains fields for entering credentials to connect to your database. The following table describes what is needed for each field:

Field

Description

JDBC Driver

Select the JDBC driver you want to use to connect.

Host

Enter the host string to connect to the SQL database. For example: // examplecluster.cpdbcwb2mzr4.us-east-2.redshift.amazonaws.com

Database

Enter the name of the SQL database.

Username

Enter your Redshift username.

Password

Enter your Redshift password.

Database Port

Enter the port number for the database.

Certificate Format

Select the certificate format. If you do not want to include a certificate, select No Certificate . If you select Certificate String , you must paste the text for your certificate in the Certificate field. If you select URL Path , you must enter the URL where your certificate is located in the Certificate field.

Certificate

Paste the text for your CA certificate or enter the URL where your certificate is located. This is optional. If you do not want to include a certificate, select No Certificate in the Certificate Format menu.

Once you have entered valid Redshift credentials, you can use the same account any time you go to create a new Redshift DataSet. You can manage connector accounts in the Accounts tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane In this pane you create an SQL query to pull data from your database. You can also choose a specific database table and columns and specify which columns you want to appear in your report.

Menu

Description

Query Type

Select a query type.

Query Type Description
Query Builder Select a table and fields to autogenerate your query.
Custom Query Enter the SQL query to execute.

Query

Enter the Structured Query Language (SQL) query to use in selecting the data you want. For example:

select \* from Employee

Query Parameter Select this checkbox to add query parameters.
Query Parameter

Enter the query parameter value. It is the initial value for query parameter. The last run date is optional. By default, it is '02/01/1700 15:22:15 -0700', if is not provided.

Example: `!{lastvalue:_id}!=1,!{lastrundate:start_date}!=02/01/1944`

Database Tables

Select the database table you want to appear in your report.

Table Columns

Select all table columns you want to appear in your report.

Fetch Size Enter fetch size for memory performance. If it is blank, default value will be 1000. If it throws out of memory for a value, decrease fetch size.
Boolean Format

Select the format for booleans to be represented in boolean data columns.

Boolean Format Description
1/0 true values will return '1', false values will return '0'
t/f true values will return 't', false values will return 'f'
T/F true values will return 'T', false values will return 'F'
true/false true values will return 'true', false values will return 'false'

Query Timeout

Enter the connector timeout value in minute(s).

### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Troubleshooting If you run into connection issues... * Verify the connection works using pgAdmin. * Confirm all of the necessary Domo IPs have been whitelisted (see Whitelisting IP addresses, above). * Run a profile on the SQL query. ## FAQ You need the username, password, host name, port number, and database name of your Redshift database. As often as needed. Limits depend on your server configuration. Make sure that all the words, table names and field names are correctly spelled. The default value for the fetch size for memory performance is 1000 for this connector. If you receive an out of memory error, try decreasing the fetch size. Before you can connect to a Redshift database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses](/docs/s/article/360043630093). # MySQL Advanced Security Connector Source: https://www.domo.com/docs/s/article/4410071437335 ## Intro MySQL is a widely used open-source relational database management system. You can use Domo's MySQL Advanced Security Connector to pull data from your MySQL database and compile custom reports. You indicate the data you want by inputting an SQL query. For more information about the MySQL API, visit their website. ([http://dev.mysql.com/doc/refman/5.0/en/c-api.html](http://dev.mysql.com/doc/refman/5.0/en/c-api.html) ) The MySQL Advanced Security Connector is a "Database" connector, meaning it retrieves data from a database using a query. In the Data Center, you can access the connector page for this and other Database connectors by clicking **Database** in the toolbar at the top of the window. You connect to your MySQL database in the Data Center. This topic discusses the fields and menus that are specific to the MySQL Advanced Security C onnector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector").

Primary Use Cases

Pulling data mart and data warehouse SQL queries

Primary Metrics

N/A

Primary Company Roles

  • CIO

  • CTO

Average Implementation Time

5-40+ hours

Ease of Use (on a 1-to-10 scale with 1 being easiest)

7

## Best Practices * Limit the results set size is much as possible. * Keep the number of columns to a minimum. ## Prerequisites To connect to a MySQL database and create a DataSet, you must have the following: * The username and password you use to log into your MySQL database * The host name for the database * The port number for the database * The database name or schema name * The SQL query you will use to pull data You can also provide your SSL and CA Certificates, and the SSL key, though this is optional. ### Whitelisting Before you can connect to a MySQL database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses for Connectors](/docs/s/article/360043630093 "Whitelisting IP Addresses for Connectors"). ## Connecting to Your MySQL Database This section enumerates the options in the **Credentials** and **Details** panes in the MySQL Advanced Security Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). **Note:** When using the copy/paste function for your credentials, ensure there is no whitespace at the beginning or end of the string. By accidentally pasting whitespace, it will cause the connector to error when trying to connect. ### Credentials Pane This pane contains fields for entering credentials to connect to your database. The following table describes what is needed for each field:

Field

Description

Host

Enter the host name for the MySQL database.

For example: db.company.com

Database Name

Enter the name of the MySQL database or schema.

Username

Enter your MySQL username.

Password

Enter your MySQL password.

Port

Enter the port number for the database.

CA Certificate

Enter the URL where the CA Certificate is located (optional).

SSL Certificate

Enter the URL where the SSL Certificate is located (optional).

SSL Key

Enter the SSL key (optional).

JDBC Driver

Select the JDBC driver to use (optional). By default, the connector uses 5.1.45

Once you have entered valid MySQL credentials, you can use the same account any time you go to create a new MySQL Advanced Security DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center . For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane In this pane you create an SQL query to pull data from your database, with or without a parameter.

Menu

Description

Query Type

Select the desired MySQL query type—either with or without a parameter.

Query

Enter the SQL query to execute. The query will execute on the MySQL server and will fetch the data from it.

For example:

select \* from Employee

You can use the Query Helper to help you write a usable SQL query. To use the Query Helper , do the following:

  1. Select your database table and table columns in the appropriate menus.

  2. Copy the SQL statement that appears in the Query Helper field.

  3. Paste the copied SQL statement into the Query field.

Query Parameter

Enter the query parameter value. This is the initial value for the query parameter. You can use this option to retrieve new data since the last run.

For example: If you entered the following query in the Query field,

select \* from test.lastValue where id \<= !\{lastvalue:id}! order by id desc

and then entered the following for the Query Parameter,

!\{lastvalue:id}!=3

then the first run would return 3 rows, and all subsequent runs would return 1 row, and the results would be ordered from largest to smallest.

Similarly, if you entered the following in the Query field,

select \* from test.lastValue where time > !\{lastrundate:time}!

and then entered the following for the Query Parameter,

!\{lastrundate:time}!=01/01/1990

then the first run would return 5 rows and all subsequent runs would return 0 rows.

TinyInt Values Treated as Bit (Boolean) Values?

Select Yes if you want TinyInt values to be treated as Boolean.

Cast Boolean Values To...

Select whether Boolean values will be cast to integers or strings.

Database Tables

Select the database table you want to import into Domo.

Table Columns

Select the table columns you want to import into Domo.

Query Helper

Copy and paste the SQL statement in this field into the Query field. For more information, see Query , above.

### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Troubleshooting * Verify the credentials using MySQL Workbench. * Confirm the server supports encrypted connections. * Confirm the Domo IPs are whitelisted. * To speed up your runtime, make sure the tables you are joining don't have duplicate column names and that you call each column only once. 英語 # Cloud Integrations Overview Source: https://www.domo.com/docs/s/article/4412849158167 Cloud Integrations provides a native integration with cross-cloud systems to unlock data products at the speed your business needs them. ## Why Cloud Integrations? Cloud Integrations addresses the following common data challenges: * **IT limitations** — IT alone cannot realize the full potential of data. A broad, inclusive approach across all lines of business (LOBs) is needed, and not all valuable data is under IT control. * **Increased stress and time constraints** — Business users demand timely access to data products, increasing the pressure to deliver. * **Rigidity and friction in data processes** — Rigid processes and tooling prevent the quick building of flexible databases, requiring too much time and effort. ## Required Grants After Cloud Integrations is enabled for your Domo environment, you can assign the following Cloud Integrations grants to manage access to these features: * **Manage Cloud Accounts** — Allows you to add or remove cloud accounts, manage the tables exposed by a cloud account, and choose which cloud integration a new DataSet uses (selected from Domo or any cloud integration that has been shared with you). This grant does **not** allow you to change the instance-wide default storage cloud in **Admin** > **Features** > **Cloud Integrations**. Requires the Manage DataSet grant. * **Override Default Cloud** — Allows you to change the instance-wide default storage cloud in **Admin** > **Features** > **Cloud Integrations**. This grant does **not** allow you to change which cloud integration an individual new DataSet uses. Requires the Edit DataSet or Manage DataSet grant. ## Setup If you're on a consumption agreement, you can access Cloud Integrations from the Data Center. If not, contact your Domo account team to enable it for your instance. Once enabled, an Admin can assign the grants described above to the appropriate users before they begin connecting providers. After Cloud Integrations is enabled for your account, you can connect your existing data warehouses. Select a provider in the table below for its setup documentation. The Cloud Integrations panel in the Data Warehouse, showing connected integrations The Create a Cloud Integration modal showing all available provider tiles | Provider | Available support | | ------------------------------------------------------------------ | -------------------------------- | | [Amazon Athena](/docs/s/article/000005744) | Read-only | | [Amazon Redshift](/docs/s/article/000005312) | Read-only | | [Azure SQL Database](/docs/s/article/000005471) | Read-only | | [Databricks](/docs/s/article/000005289) | Read, Writeback, Pushdown (Beta) | | [Dremio](https://domo-support.domo.com/s/article/000005139) | Read, Writeback | | [Google BigQuery](/docs/s/article/000005237) | Read, Writeback, Pushdown (Beta) | | [Lakebase](/docs/s/article/Domo-on-Lakebase) | Read-only | | [MySQL](/docs/s/article/000005451) | Read-only | | [Oracle ADW](/docs/s/article/000005586) | Read-only | | [Oracle NetSuite](/docs/s/article/000005586) | Read-only | | [PostgreSQL](/docs/s/article/000005756) | Read-only | | [Snowflake](https://domo-support.domo.com/s/article/4402322966807) | Read, Writeback, Pushdown | ## Set a Default Storage Cloud You can specify a default storage account for all DataSets. Changing this setting does not affect existing DataSets or DataFlows — it applies only to new assets. **Before you begin:** You need the Override Default Cloud [grant](#required-grants). **Note:** We recommend setting up your Cloud Integrations connections using a service account. 1. In the Domo navigation header, select **More** > **Admin**. The **Admin Settings** page opens. 2. Under **Features**, select **Cloud Integrations**. The **Cloud Integrations** page opens. 3. Select an option from the **Select the default storage cloud** dropdown. ## Best Practices Configure all connected databases to use UTC as their time zone. When a database uses a non-UTC time zone, Domo may apply an additional time zone shift on top of the database's own offset, causing day-over-day, week-over-week, and year-over-year comparisons to return incorrect data. Databases using non-UTC time zones can also cause discrepancies between data viewed in Domo and data queried directly from the same source in other tools. ## Federated Data vs. Cloud Integrations The table below compares federated data to Cloud Integrations read and read/write configurations: | Capability | Federated-Direct Query | Cloud Integrations (Read-Adapter) | Cloud Integrations (Read/Write Adapter) | | --------------------------------------------------------------------------------- | ------------------------------ | ---------------------------------- | --------------------------------------- | | Visualize data from existing tables — Create cards, create Dashboards | ✅ | ✅ | ✅ | | Visualize on-premise data behind firewall via an agent | ✅ | ❌ | ❌ | | Get updated metadata from source tables — last updated time, updated row count | ❌ | ✅ (Every 15 minutes, Configurable) | ✅ (Every 15 minutes, Configurable) | | Card Alerts | Scheduled only | ✅ (Every 15 minutes, Configurable) | ✅ (Every 15 minutes, Configurable) | | DataSet Alerts | ❌ | ✅ (Every 15 minutes, Configurable) | ✅ (Every 15 minutes, Configurable) | | DataSet Views | ✅ | △ (See note below) | △ (See note below) | | Use data from existing tables in Magic ETL as inputs | ❌ | ✅ | ✅ | | Use data updates from existing tables to trigger other DataFlows | ❌ | ✅ | ✅ | | Custom fiscal calendar for source table data (one per instance) | ❌ | ❌ | ✅ | | Use Domo Connectors, Workbench, SDK, CLI to write to customer-owned EDW/Data Lake | Via writeback connectors | Via writeback connectors | ✅ **Native direct rewrite** | | Write Magic ETL output to customer-owned EDW/Data Lake | Via writeback connectors | Via writeback connectors | ✅ **Native direct rewrite** | | PDP \| Governance | ✅ | ✅ | ✅ | | Domo App Support | ✅ | ✅ | ✅ | | Jupyter Workspace Support | ✅ | ✅ | ✅ | | Domo auto-caching of card loads | Set static TTL on each DataSet | ✅ | ✅ | **Note:** DataSet View support for Cloud Integrations DataSets is limited: * ✅ Supported: DataSet Views (Standard Views and SQL Views) that join Cloud Integrations DataSets from the **same** cloud connection. * ❌ Not supported: DataSet Views that join a Cloud Integrations DataSet with a Domo DataSet (a standard Domo DataSet) or with a Cloud Integrations DataSet from a different cloud connection. When creating a DataSet View, make sure every DataSet in the join is a Cloud Integrations DataSet from the same cloud connection. **Note:** Custom fiscal calendars are not loaded automatically when you add a new Cloud Integration. If your instance uses a custom fiscal calendar, contact Domo Support to have it loaded on the new integration. ## Share a Cloud Integrations Account If you own a Cloud Integrations connection, you can share access to the integration and associated account so that others can help with governance of the account and underlying data. There are different levels of access available, depending on your use case. The following table can help you determine the right level of access to grant: | | | Read | Execute | Share | Write | Delete | Admin | | ----------------------- | ---------------------------------------------------------------------------------- | ---------------------------------------- | ------------------------------------------ | -------------------------------- | ---------------------------------------------------------- | -------------------------------- | ----------- | | | | Ability to register new DataSets in Domo | Ability to create new tables on the remote | Ability to share the integration | Ability to make changes to the integration and its account | Ability to delete an integration | Full access | | **Owner** | Allows read-write use, sharing, editing, and deleting of the integration. | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | **Can Edit** | Allows read-write use, sharing, and editing of the integration, but cannot delete. | ✅ | ✅ | ✅ | ✅ | | | | **Can Share** | Allows read-write use and sharing of the integration, but cannot edit or delete. | ✅ | ✅ | ✅ | | | | | **Can Write & Connect** | Allows read-write use of the integration, but cannot share, edit, or delete. | ✅ | ✅ | | | | | | **Can Write** | Allows write-only use of the integration, but cannot read, share, edit, or delete. | | ✅ | | | | | | **Can Connect** | Allows read-only use of the integration, but cannot write, share, edit, or delete. | ✅ | | | | | | | **No Access** | No access to the integration. | | | | | | | Follow these steps to share a Cloud Integrations account: 1. In the Domo navigation bar, select **Data**, then select **Accounts** from the left sidebar. The Accounts page showing the Service Accounts list 2. Find the account you want to share and select the **Wrench** icon on the right. The options menu appears. The wrench icon menu open showing Account sharing 3. Select **Account sharing**. The **Manage** *\[account name]* **access** modal opens. The Manage access modal with People with Access and People without Access sections 4. Find the person or group you want to share with and use the dropdown to choose the access level. The [table](#share-a-cloud-integrations-account) above can help you decide the appropriate level. The access level dropdown open showing all available roles 5. Select **Apply** to save your changes. ## Technical FAQ Find answers to frequently asked questions about general topics and external cloud storage. For caching and data freshness questions, see [Configure Data Freshness and Caching in Cloud Integrations](/docs/s/article/Cloud-Integrations-Data-Freshness). ### General Cloud Integrations DataSets operate the same as Domo DataSets. Additionally, Magic ETL can trigger the DataFlow to run when the data is updated in your database. By default, Domo checks the database metadata for updates every 15 minutes. Magic ETL v2 supports Cloud Integrations DataSets. You can designate DataSets created via Cloud Integrations as published DataSets to create a virtualized DataSet in a subscriber organization. You can then use the virtualized subscriber DataSet as an input to Magic ETL transformations and configure it for DataSet Alerts. You can also use DataSets created via Cloud Integrations with [Domo Everywhere Embed](https://domo-support.domo.com/s/article/360043437993). No. Not currently. Support for additional locales is planned for a future release. In the meantime, we recommend setting your locale to `en-US` when using Cloud Integrations. Old dates may shift by one hour due to daylight saving time (DST) adjustments. Domo ensures correct time zone conversions for dates on or after January 1, 1970\. For dates before that, time zone adjustments may be inaccurate depending on when daylight saving time was adopted in the relevant time zone. When a Cloud Integrations DataSet is backed by a database View (rather than a table), Domo does not display a row count or a last updated date. External cloud databases do not expose row counts or modification timestamps for Views the same way they do for tables, so Domo has no value to surface. This is expected behavior and does not affect the DataSet's ability to power cards or DataFlows. ### External Cloud Storage Find answers to frequently asked questions about using Cloud Integrations with external cloud storage accounts. Not at this time. Not at this time. Data Caching is available for Cloud Integrations DataSets. For more information, see [Configure Data Freshness and Caching in Cloud Integrations](/docs/s/article/Cloud-Integrations-Data-Freshness). Yes, Domo operates on your cloud warehouse account. The method Domo uses to access a cloud warehouse account depends on the warehouse. We recommend using a system or service account, rather than individual user accounts, to grant Domo access to all cloud warehouses. See the [provider setup guides](#setup) for details on how Domo accesses each provider. Yes. By default, you have access to both Domo's proprietary Adrenaline engine and the Cloud Integrations engine. You can configure your Domo environment so that only the Cloud Integrations DataSets are allowed to run in your Domo environment, but you need to contact [Domo Support](https://domo-support.domo.com/s/) to configure this. For existing DataSets created via a connector or Domo APIs, contact [Domo Support](https://domo-support.domo.com/s/) to move them to your cloud provider. If those DataSets were created via some other method, you need to recreate those in your cloud provider manually. Domo's APIs can be used with any DataSet in a Domo-managed database, as long as that table is in the Domo-managed database that was configured during the write integration step of your Cloud Integrations setup. Customer-managed databases that exist in the cloud, which Domo can read but not write to, cannot be updated with Domo APIs. This includes the Stream API, webhooks, custom apps that generate new data such as Form Builder, and managing a DataSet via the DataSet API (such as updating a DataSet, managing personalized data permissions (PDP) policies, changing the owner of a DataSet, exporting a DataSet). For a more comprehensive guide to using the DataSet API, see the [DataSet API reference](https://developer.domo.com/docs/dataset-api-reference/dataset). ## Related Articles * [Connect Tables in Cloud Integrations](/docs/s/article/Connect-Tables-in-Cloud-Integrations) * [Configure Data Freshness and Caching in Cloud Integrations](/docs/s/article/Cloud-Integrations-Data-Freshness) # MySQL Advanced Writeback Connector Source: https://www.domo.com/docs/s/article/4416129543063 ## Intro Use Domo's MySQL Advanced Writeback connector to export your data from a Domo DataSet to the provided MySQL database in the Data Center using Advanced Security. To learn more about MySQL, visit their website at [https://www.mysql.com/](https://www.mysql.com/ "https://www.mysql.com/"). You export data to a MySQL database in the Data Center. This topic discusses the fields and menus that are specific to the MySQL Advanced Writeback connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). **Note:** The owner of a writeback dataset must also be an owner or co-owner of the input dataset. ## Prerequisites To configure this connector, you will need the following: * Your MySQL database or schema name. * The hostname or IP address of your MySQL database server, such as [db.mycompany.com](http://db.mycompany.com). * Your MySQL Database server port number. * Your MySQL username and password. * The port number for your MySQL server. * (Optional) Your SSL client key * (Optional) Your SSL client certificate * (Optional) Your SSL CA Certificate Authority **Important**: You will need the following permissions on MySQL: * FILE * CREATE * DROP * INSERT * SELECT * UPDATE ## Configuring the Connection This section enumerates the options in the **Credentials** and **Details** panes in the MySQL Advanced Writeback Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to the table in your MySQL database where you want your data to be copied to. The following table describes what is needed for each field:

Field

Description

Database Name

Enter the name of your MySQL database.

Host

Enter your MySQL database hostname.

Username

Enter your MySQL username.

Password

Enter your MySQL password.

Port

Enter your MySQL database port number.

SSL Key

Enter the client Key for SSL.

SSL Certificate

Enter the Client Certificate for SSL.

SSL CA Certificate

Enter the MySQL CA Certificate Authority for SSL.

For more information about obtaining these credentials, see "Prerequisites," above. Once you have entered valid credentials, you can use the same account any time you go to set up a new Domo-MySQL connection. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane This pane contains a number of fields for specifying your data and indicating where it's going.

Menu

Description

DataSet ID

Enter the DataSet ID (GUID) for the DataSet you want to copy to MySQL. You can find the ID by opening the details view for the DataSet in the Data Center and looking at the portion of the URL following datasources/ . For example, in the URL [https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview\{](https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview\{)" "} , the DataSet ID is 845305d8-da3d-4107-a9d6-13ef3f86d4a4.

How Would You Like To Select Your Table?

Specify whether you would like to create a new table or select an existing table to export your DataSet data to.

Table Name

Select how you want to name the table where data will be copied.

  • DataSet ID . The table name will be the number you entered for DataSet ID .

  • Custom Name . You will give the table a custom name in the Custom Table Name field.

Custom Table Name

Enter the name of the table in your MySQL database where you want your DataSet data to be copied.

Delete Existing Table and Create New Table For The Same Name

Normally, if you provide a table name with the same name as an existing table, the connector throws an error. If instead, you want us to drop the existing table and create a new table with this name, then check this checkbox.

WARNING : This deletes the existing table, and the data cannot be recovered after it is deleted.

### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). # Databricks Using Personal Access Token Authentication Connector Source: https://www.domo.com/docs/s/article/8041126473367 ## Intro Databricks is a cloud-based collaborative data science, data engineering, and data analytics platform that combines the best of data warehouses and data lakes into a lakehouse architecture. With Databricks you can access all your data, analytics, and AI on one lake house platform. The simple, open, and collaborative environment helps reduce the infrastructure complexity, keeps control of your data, and makes it easy for your teams to partner across the entire data and workflow. For more information about the Databricks API, visit their website. ([https://docs.databricks.com/dev-tools/api/index.html](https://docs.databricks.com/dev-tools/api/index.html "https://docs.databricks.com/dev-tools/api/index.html") ) The Databricks connector is a "Database" connector, meaning it retrieves data from a database using a query. In the Data Center, you can access the connector page for this and other Database connectors by clicking **Database** in the toolbar at the top of the window. You connect to your Databricks database in the Data Center. This topic discusses the fields and menus that are specific to the Databricks connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). **Note:** Contact your AE or CSM to have it enabled in your instance. ## Prerequisites To connect to a Databricks database and create a DataSet, you must have the following: * The hostname for the database * The port number for the database * The database name or schema name * Databricks personal access token * The HTTP Path ## Connecting to Your Databricks Database This section enumerates the options in the **Credentials** and **Details** panes on the Databricks Connector page. The components of the other panes on this page, **Scheduling,** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). **Note:** When using the copy/paste function for your credentials, ensure there is no whitespace at the beginning or end of the string. By accidentally pasting whitespace, it will cause the connector to an error when trying to connect. ## Credentials Pane This pane contains fields for entering credentials to connect to your database. The following table describes what is needed for each field:

Field

Description

Host

Enter the hostname for the Databricks database.

Example: db.company.com

Port

Enter the port number for the Databricks database.

Database

Enter the name of the Databricks database.

Personal Access Token

Enter your Databricks personal access token.

HTTP Path Enter the HTTP path.
Once you have entered valid Databricks credentials, you can use the same account any time you go to create a new Databricks DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center . For more information about this tab, see [Manage Connector Accounts](https://domo-support.domo.com/s/article/360042926054?language=en_US "Manage Connector Accounts"). ## Details Pane In this pane you create an SQL query to pull data from your database, with or without a parameter.

Menu

Description

Query Type

Select the desired query type.

Query Type Description
Custom Query Enter the query to execute.
Query Builder Select a table and fields to autogenerate your query.

Query

Enter the Structured Query Language (SQL) query to use in selecting the data you want.

Example: select \* from Employee

You can use the Query Helper parameter to help you write a usable SQL query. To use the Query Helper , do the following:

  1. Select your database table and table columns in the appropriate menus.

  2. Copy the SQL statement that appears in the Query Helper field.

  3. Paste the copied SQL statement into the Query field.

Database Tables

Select the database table you want to import into Domo.

Table Columns

Select the table columns you want to import into Domo.

Query Helper

Copy and paste the SQL statement in this field into the Query field. For more information, see Query , above.

Fetch Size

Enter the fetch size for memory performance. The default value will be used if no fetch size is specified. If an " out of memory " error occurs, retry decreasing the fetch size.

Partition Support Format

Select the Year, Day and Month format of the data you would like to retrieve.

Fetch Size

Enter the fetch size for memory performance. The default value will be used if no fetch size specified. If an "out of memory" error occurs, retry decreasing the fetch size.

How you would like to import data into Domo?

You can import the data from the following:

  • Standard Update (replace/append)
  • User partition
  • Use upsert
## Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## FAQs **What kind of credentials do I need to power up this connector?** You need the host name, port number, database name of your Databricks database, HTTP path and your Databricks personal access token. **Where can I find the values that I need to enter for my credentials?** You can find the hostname, database, port number, and HTTP path by going to your cluster in Databricks and viewing the JDBC/ODBC tab in the Advanced section of the cluster details. **How frequently will my data update?** As often as needed. **Are there any API limits that I need to be aware of?** Limits depend on your server configuration. **What do I need to be aware of while writing a query?** Make sure that all the words, table names, and field names are correctly spelled. Refer to the Query Helper field for query help. **What's the Fetch Size?** The fetch size is for memory performance. The default value will be used if no fetch size is specified. If an "out of memory" error occurs, retry decreasing the fetch size. **What types of queries are supported by DataBricks Connector?** The Databricks read connector supports only read operations (if you are familiar with CRUD), and also supports where clauses, joins, group by, subselect, having, case, and so on. If you use the query builder option, it will only generate a simple "select query". If you want to use anything else in your query, you must do in the custom query field. # Amazon Redshift Domo Managed Unload Source: https://www.domo.com/docs/s/article/9030981562519 ## Intro Amazon Redshift is a fast and powerful, fully managed, petabyte-scale data warehouse service in the cloud. You connect to your Amazon Redshift Unload account in the Data Center. This topic discusses the fields and menus that are specific to the Amazon Redshift Unload connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Prerequisites To connect to Amazon Redshift so you can begin creating Amazon Redshift Unload DataSets, you must have the following: * The hostname for the Redshift database * The database name for the Redshift database * Your Redshift username and password * The port number of your Redshift database CA certificate text or URL path is required *only* if you select **Certificate string** or **URL path**, respectively, in the **Certificate type** menu. If you do not know any of the information for Redshift, contact your Amazon Redshift Database Administrator. ### Whitelisting Before you can connect to Redshift, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses for Connectors](/docs/s/article/360043630093 "Whitelisting IP Addresses for Connectors"). ## Connecting to Your Amazon Redshift Unload Account This section enumerates the options in the **Credentials** and **Details** panes on the Amazon Redshift Unload Connector page. The components of the other panes on this page, **Scheduling** **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Amazon Redshift Unload account. The following table describes what is needed for each field:

Field

Description

Host

Enter the hostname for the Redshift database you want to pull data from.

Database

Enter the database name for the Redshift database you want to pull data from.

Username

Enter the username for your Redshift account,

Password

Enter the password for your Redshift account.

Database Port

Enter the port number for the Redshift database you want to pull data from.

Certificate Format

Select a certificate format. If you do not want to include a certificate, leave the default No certificate option selected. If you select Certificate string , you must paste the text for your certificate in the Certificate field. If you select URL path , you must enter the URL where your certificate is located in the Certificate field.

Certificate

Paste the text for your CA certificate or enter the URL where your certificate is located. This is optional. If you do not want to include a certificate, select No certificate in the Certificate Format menu.

Once you have entered valid credentials, you can use the same account any time you go to create a new Amazon Redshift Unload DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane This pane contains various options for specifying the data you want to pull into Domo.

Menu

Description

Query Type

Select the desired query type. If you select Query , you will be prompted to enter a regular SQL query without a parameter. If you select Query Parameter , you will be prompted to enter a SQL query with a parameter.

Query Type Description
Custom Query Enter the SQL query to execute.
Query Builder Select schema, database table, and column names(fields) to auto-generate your query.

How would you like to import data?

Standard update (replace/append)
User partition
Use upsert

Query

Enter the SQL query you want to use to pull in data.

For example:

select \* from Employee

You can use the Generated Query parameter to help you write a usable SQL query. To use the Generated Query , do the following:

  1. Select your database table and table columns in the appropriate menus.

  2. Copy the SQL statement that appears in the Generated Query field.

  3. Paste the copied SQL statement into the Query field.

Database Tables

Select the database tables you want to pull into Domo if desired.

Table Columns

Select the table columns you want to pull into Domo.

Update Method

When Domo retrieves your data from the source, you can determine how that new data is imported into the current DataSet. We advise you to always use the Merge method, but we also offer Append and Replace if you need it.

Merge This method will replace all updated rows, while any new rows will be appended.
Append This method will take your new data and add it to your current DataSet. Using this may create duplicate data entries.
Replace This method will take your current DataSet and replace it with new data. Using this may result in some data loss.

Basic Scheduling

Choose a predefined update schedule (every day between 9 AM and 10 AM)
  • Specify a daily window of activity for 15-minute, 30-minute, and hour intervals
With a Manual schedule , you can opt-in to receive a reminder when the data needs to be updated

Advance Scheduling

Advanced Scheduling
Define a fine-grained schedule with a specific time or update frequency
  • Limit the schedule to run on specific days and months
  • Start scheduled updates on a future date with Delay Start

Note: Schedules are set from the current time in UTC

### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQs As often as needed. This depends on your server configuration. Before you can connect to a Redshift database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses](/docs/s/article/360043630093 "Whitelisting IP Addresses for Connectors"). # Configure Data Freshness and Caching in Cloud Integrations Source: https://www.domo.com/docs/s/article/Configure-Data-Freshness-and-Caching-in-Cloud-Integrations ## Intro This article explains how to open the **Data Freshness** tab for a Cloud Integration, configure scheduled data freshness checks, and configure data caching for card query results. *** ## Overview Cloud Integrations DataSets stay current through two mechanisms that you configure per integration: * **Data freshness checks —** Domo polls your source cloud warehouse on a schedule to detect when the underlying data has changed. When an update is detected, connected cards, alerts, and DataFlows reflect the new data on their next load. Domo also performs on-demand freshness checks when a query is executed and the configured cache duration (TTL) has expired, providing more responsive data without relying solely on scheduled polling. * **Data caching —** Domo stores the results of card queries temporarily. When a user opens a card, Domo returns the cached result if one exists rather than sending a new query to the warehouse. This reduces query load on your warehouse. Both settings are configured at the integration level and apply to all DataSets within that integration. ## Open the Data Freshness Tab To configure data freshness and caching for an existing integration: 1. Navigate to **Data Warehouse** > **Connect Data** > **Manage existing integrations**. 2. Select the tile for your integration type, such as BigQuery. Integration list with wrench menu open 3. Hover over the integration you want to configure and select the wrench icon that appears, then select **Edit integration**. Integration detail showing the Settings tab 4. Select the **Data Freshness** tab. By default, data freshness scheduling and caching are both disabled. Data Freshness tab in its default state, with scheduling and caching both off ## Configure Data Freshness Checks 1. Enable the **Schedule data freshness checks** toggle. 2. Select the **Basic** or **Advanced** tab to set when Domo checks for updates. ### Basic Basic mode lets you choose a preset update interval from a dropdown. Set the **Start Time** and **Time Zone** to control when within the interval checks begin. For sub-daily intervals (every 15 minutes, every 30 minutes, every hour), you can also enable **Active hours** to restrict checks to a defined time window. Basic tab with the update interval dropdown open | Update interval | Description | | ---------------- | ----------------------------------------------------------------------- | | Every 15 minutes | Checks every 15 minutes, all day or during the configured active hours. | | Every 30 minutes | Checks every 30 minutes, all day or during the configured active hours. | | Every hour | Checks every hour, all day or during the configured active hours. | | Every day | Checks once per day at the specified time, including weekends. | | Every weekday | Checks once per day at the specified time, excluding weekends. | | Every week | Checks once per week on the selected day at the specified time. | | Every month | Checks once per month on the selected date at the specified time. | ### Advanced Advanced mode gives you granular control over check frequency, day of the week, and monthly schedule. Configure all three settings to define exactly when checks run. Advanced tab with Once a day selected **How frequently?**—How often within a day checks run: * **Once a day —** Checks run once per day at the time and time zone you specify. * **More than once a day —** Checks repeat throughout the day at the interval you specify. Enable **Active hours** to restrict checks to a defined window, such as 8 AM–6 PM. Advanced tab with More than once a day selected and Active hours enabled **Day frequency**—Which days checks run: * **Every day —** Checks run every day of the week. * **Specific days of the week —** Checks run only on the days you select. * **Specific days of the month —** Checks run only on the calendar dates you select. **Month frequency**—Which months checks run: * **Every month —** Checks run every month. * **Specific months —** Checks run only in the months you select. ## Configure Data Caching 1. In the **Data Caching** section of the **Data Freshness** tab, turn on the **Enable caching** toggle. 2. Set **Cache Duration (TTL)** to control how long Domo retains cached card query results before discarding them. The maximum cache duration is 24 hours. Caching section with the Enable caching toggle being turned on ## FAQ ### Data Freshness Make sure data freshness is enabled and configured to an interval that suits your use case. If data freshness is disabled, card query results may be cached for up to 24 hours. No. Data freshness checks and caching depend on the service account used to connect your integration. These features are disabled when using OAuth. ### Caching Domo bypasses the cache and always sends a fresh query in these situations: * Viewing the DataSet preview on the DataSet's Details page * Loading a DataSet View * Loading a DataSet into Magic ETL * **Dynamic SQL functions**: Queries that include functions such as NOW(), CURRENT\_DATE(), or CURRENT\_TIMESTAMP() generate a unique SQL string on each execution. Caching is keyed on the exact SQL query, so these queries will not reuse cached results regardless of TTL setting. No. When you view a card, Domo first checks for a cached result. If one exists, Domo returns the cached data. If none exists, Domo queries the warehouse. Yes. When building or editing a card in Analyzer, each change triggers a new query if **Auto Preview** is enabled. Domo caches card query results for up to 24 hours or until the Cache Duration (TTL) expires—whichever comes first. No. There is no explicit limit on the number of cached query results. No. There is no row or data size limit on what is saved in the card cache. No. The cache duration is set at the integration level and applies to all DataSets within that integration. # Connect Tables in Cloud Integrations Source: https://www.domo.com/docs/s/article/Connect-Tables-in-Cloud-Integrations ## Intro After setting up a Cloud Integration, you can connect tables from your cloud data warehouse to make them available as DataSets in Domo. This article explains how to connect, manage, and disconnect those tables. *** ## Prerequisites Set up at least one integration before connecting tables. See [Cloud Integrations Overview](/docs/s/article/4412849158167). ## Connect Tables To open the Connect Tables panel, go to **Data > Data Warehouse**, select the integration you want to work with, then select **Connect tables** in the left navigation. Select Connect tables in the left navigation to open the Connect Tables panel **Note:** Each connect operation supports a maximum of 500 tables. To avoid exceeding this limit, select no more than 500 tables per operation. You can connect tables using the **Browse** tab or the **Manual** tab. ### Browse Use the Browse tab to navigate your warehouse hierarchy and select tables to connect. 1. In the left panel, select a database. The schemas in that database appear below it. Select a database to expand its schemas 2. Select a schema. The right panel lists each table's name, its corresponding Domo DataSet (if connected), and its status. Select a schema to load its tables in the right panel The right panel shows all tables in the schema. The donut chart in the upper right summarizes how many are connected vs. not connected. 3. Select the checkbox next to each table you want to connect. A selection bar appears at the bottom of the panel showing the number of selected tables. Select one or more tables, then select Connect in the bottom bar. 4. Select **Connect** in the bottom bar. A success message appears confirming how many tables were connected, and each table's status updates to **Connected**. A success message confirms how many tables were connected. ### Manual Use the Manual tab to connect tables by entering their location directly (**Add Table**) or by uploading a list (**Upload List**). The Manual tab lets you add individual tables or upload a list of tables. #### Add a Single Table 1. In the **Add Table** form, enter the **Database**, **Schema**, and **Table** values. 2. Select **Connect**. #### Upload a List of Tables 1. Select **Download Template** to get the CSV template. 2. Open the template and enter the **Database**, **Schema**, and **Table** values for each row. 3. Upload the file by dragging it into the **Upload List** area or selecting **Browse** to locate the file on your computer. The tables in the file are listed. Any rows that could not be matched are labeled **Needs Action**. 4. For any table labeled **Needs Action**, correct the entry in your CSV file and upload it again, or connect that table using the **Browse** tab or the **Add Table** form. ## Manage Connected Tables Use the Connect Tables panel to search, filter, and disconnect tables. ### Search and Filter Tables Use the search bar to filter the table list by name. The list updates as you type to show only tables whose names contain the search text. To filter by connection status, select **Add Filter** and choose a **Status**: * **Connected —** tables currently connected to a Domo DataSet. * **Not connected —** tables available to connect. ### Disconnect Tables **Important:** Disconnecting a table permanently deletes the corresponding DataSet from Domo. Your source table in the data warehouse remains unchanged. 1. In the left panel, select the database and schema that contain the tables you want to disconnect. 2. Select the checkbox next to each table you want to disconnect. A selection bar appears at the bottom of the panel showing the number of selected tables. Select the tables to disconnect, then select Disconnect in the bottom bar. 3. Select **Disconnect** in the bottom bar. A confirmation dialog appears. 4. Select both checkboxes in the confirmation dialog. 5. Type `CONFIRM` in the field, then select **Disconnect**. Confirm the disconnection by selecting both checkboxes and typing CONFIRM. ## Related Articles * [Cloud Integrations Overview](/docs/s/article/4412849158167) # Databricks Using OAuth M2M Authentication Connector Source: https://www.domo.com/docs/s/article/Databricks-Using-OAuth-M2M-Authentication-Connector ## Intro This article explains how to use the Databricks OAuth M2M Authentication connector to configure OAuth 2.0 client credentials, connect to your Databricks workspace, and import Databricks data into Domo. *** ## Prerequisites To configure this connector, you must have the following: * Databricks server hostname * Databricks port number * HTTP path * OAuth client ID * OAuth client secret For more information about the Databricks API, see the [Databricks API documentation](https://docs.databricks.com/aws/en/reference/api). This article covers the fields and menus specific to the Databricks using OAuth M2M Authentication connector user interface. For general information about adding DataSets, setting update schedules, and editing DataSet information, see [Add a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Configure Databricks OAuth Machine-to-Machine (M2M) Authentication To configure OAuth 2.0 client credentials (M2M) authentication for Databricks, complete the following tasks: 1. Create a Databricks service principal in your Databricks workspace, and create an OAuth secret for it. For instructions, see [Authorize service principal access to Databricks with OAuth](https://docs.databricks.com/aws/en/dev-tools/auth/oauth-m2m). Make a note of the service principal UUID (Application ID) and the secret value. 2. Grant the service principal access to the compute resources it needs. See [Compute permissions](https://docs.databricks.com/aws/en/compute/clusters-manage#cluster-level-permissions) or [Manage a SQL warehouse](https://docs.databricks.com/aws/en/compute/sql-warehouse/create#manage). Before you begin, complete the following: * Create a Databricks service principal. See [Add service principals to your account](https://docs.databricks.com/aws/en/admin/users-groups/service-principals#manage-sp-permissions). * On the service principal's **Configuration** tab, select the entitlements it needs for this workspace. * On the **Permissions** tab, grant access to any Databricks users, service principals, and groups that need to manage or use this service principal. For details, see [Who can manage and use service principals?](https://docs.databricks.com/aws/en/admin/users-groups/manage-service-principals#add-sp). ### Add a service principal to your account As an account admin, use the account console to add a service principal. 1. Sign in to the account console. 2. In the sidebar, select **User management**. 3. Select the **Service principals** tab, and then select **Add service principal**. 4. Enter a name for the service principal. 5. Select **Add**. ### Create an OAuth secret To authorize access to your Databricks resources with OAuth, create an OAuth secret. Databricks uses this secret to generate OAuth access tokens for authentication. Each service principal can have up to five OAuth secrets, and each secret can be valid for up to two years. Account admins and workspace admins can create OAuth secrets for service principals. 1. In the Databricks workspace, select your username, and then select **Settings**. 2. Select the **Identity and access** tab. 3. Next to **Service principals**, select **Manage**. 4. Select the service principal. 5. Select the **Secrets** tab. 6. Select **Generate secret**. 7. Set the secret lifetime in days (maximum 730). 8. Select **Generate**. 9. Copy the displayed secret and client ID, and then select **Done**. The secret appears only once. The client ID is the same as the service principal application ID. **Note:** Account admins can also create an OAuth secret in the account console. On the **User management** tab, select the service principal, and then go to the **Credentials & secrets** tab. ## Configure the Connection This section describes the options in the **Credentials** and **Details** panes on the Databricks using OAuth M2M Authentication connector page. The components of the **Scheduling** and **Name & Describe Your DataSet** panes are universal across most connector types and are discussed in [Add a DataSet Using a Data Connector](/docs/s/article/360042926274). ### Enter your credentials The **Credentials** pane contains fields for entering credentials to connect to your Databricks account. The following table describes what is needed for each field. | Field | Description | | ------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Host | Enter the Databricks server hostname. To find it, go to the **JDBC/ODBC** tab under the cluster's **Advanced Options**. If you do not have access to this tab, contact your Databricks administrator. | | Port | Enter the Databricks port number. For secure connections, Databricks always uses port 443. | | HTTP Path | Enter the HTTP path. To find it, go to the **JDBC/ODBC** tab under the cluster's **Advanced Options** in Databricks. If you do not have access to this tab, contact your Databricks administrator. | | OAuth Client ID | Enter the application (client) ID for your service principal. This unique identifier is used for machine-to-machine (M2M) authentication. | | OAuth Client Secret | Enter the client secret for your service principal. This confidential key is associated with the application (client) ID. | After you enter valid credentials, you can use the same account any time you set up a new Databricks using OAuth M2M Authentication connection. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Manage User Accounts for Connectors](/docs/s/article/360042926054). ### Configure the Details pane In the **Details** pane, you can configure various fields. | Field | Description | | -------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | How would you like to import data into Domo? | Select how you want to import your data. | | Catalogs | Select the catalog. | | Database Name | Select the database name. | | Query Type |
Report NameDescription
Custom QueryEnter the query to execute.
Query BuilderSelect a table and fields to automatically generate your query.
| | Query | Enter your query. | | Database Tables | Select the table. | | Table Columns | Select the columns. | | Query Helper | Generated query. | | Upsert Key Column(s) | Enter the upsert key column name. To specify multiple columns, enter a comma-separated list. This field is required only when the Import Data method is set to UPSERT. | | Partition Criteria | Select whether to partition your data by using date keys or a meta query. | | Partition Query to determine partition tags | Enter the partition meta query to return the distinct partition tags (or keys). Use the column that contains **Date** values as the partition column. For example: `SELECT DISTINCT(COLUMN_NAME) FROM TABLENAME`. | | Partition Column Name | Select the partition column name. Only date fields appear in this list. | | Partition Support Format | Select the partition format. | | Past Days | Enter how many days back you want to pull data from, such as 30 for the last 30 days. Use a number greater than zero. | | Past Years | Enter how many years back you want to pull data from, such as 10 for the last 10 years. Use a number greater than zero. | | Past Months | Enter how many months back you want to pull data from, such as 24 for the last 24 months. Use a number greater than zero. | | Future Years | Enter how many years ahead you want to retrieve data for. Enter a positive integer, such as 10. | | Future Months | Enter how many months ahead you want to retrieve data for. Enter a positive integer, such as 15. | | Date Format | Select the date format that matches the format in the partition column. By default, **yyyy-MM-dd** is used. | | Custom Date Format | Enter the custom date format. | | Partition Non Date Key Column Name | Select the partition column name. | | Fetch Size | Enter the fetch size to control memory usage. If you leave this field blank, the connector uses the default fetch size. If you get an "out of memory" error, try a smaller fetch size. | ## Configure Other Options For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Add a DataSet Using a Data Connector](/docs/s/article/360042926274). # Domo Video Library Source: https://www.domo.com/docs/s/article/Domo-Video-Library The [Domo Video Library](https://embed.domo.com/cards/2W9VW) is a searchable directory of focused videos that walk you through specific Domo features and workflows. Each card below shows a preview and a brief summary of what the video covers. Select any card to open and watch the full microlearning video. Discover why App Studio apps are becoming Domo's flagship data display tool. Learn about multiple pages, persistent filters, rich theming, and interactive components that dashboards lack. Explore the editor's layout tools, controls, and powerful actions—filter, navigation, and URL actions—that create guided analytical experiences. Perfect for polished, multi-team applications requiring persistent filters across pages. *Added June 11, 2026* Learn how OAuth2 authentication works within Domo's platform API framework. Understand the token-based authorization flow, including how to obtain and use access tokens to make authenticated API calls. Apply this pattern to enable secure programmatic access to Domo resources and data. *Added June 17, 2026* Learn how to configure triggers and schedules for Magic ETL data flows in Domo. Explore dataset update triggers with optional conditions and time-based schedules to control when data flows run. Understand how thoughtful scheduling helps manage execution credits based on your team's data freshness needs. *Added June 11, 2026* In this video we'll walk through the process of setting up a Microsoft Azure app to enable the connection between Sharepoint and Domo. *Added May 27, 2026* Learn how to combine Domo Variables with Beast Mode calculations to create dynamic what-if scenario calculators. Discover how to define and configure Variables that allow end users to adjust inputs and instantly see recalculated results in cards. *Added May 27, 2026* Discover how Massman built a purchase order verification AI agent in a single 24-hour hackathon using Domo's Pro-code framework, Workflows, AI Library, and AppDB. Learn how the agent ingests supplier PDFs, cross-references live NetSuite data, and surfaces discrepancies with severity ratings. See how human-in-the-loop design enables automated vendor outreach drafting while maintaining oversight and control. *Added July 28, 2026* Explore how to establish a Center of Excellence (CoE) for your Domo implementation, including centralized, decentralized, and hub-and-spoke organizational models. Learn how each model impacts ownership, accountability, and day-to-day operations across your Domo environment. Understand which governance responsibilities are typically managed by the CoE to drive consistency and scalability. *Added June 5, 2026* Learn how to build, manage, and deploy custom data-powered applications using Domo’s Pro-Code Editor. In this video, you’ll see how Pro-Code app designs are managed in Domo’s Asset Library and how developers can use familiar web technologies to create interactive applications directly in the browser. You’ll also learn how to: * Navigate the Pro-Code Editor workspace * Edit HTML, JavaScript, CSS, and app configuration files * Preview your application while you build * Connect apps to Domo DataSets, collections, packages, and workflows * Use resource aliases instead of hard-coding DataSet IDs * Apply Domo permissions and PDP to custom application data * Add custom layouts, interactions, and business logic * Create and manage multiple application versions * Update apps without interrupting business users * Publish Pro-Code applications as reusable Domo cards * Add custom apps to dashboards and App Studio experiences Domo’s Pro-Code Editor gives developers the flexibility of a custom web application while keeping the app, data, permissions, and deployment inside Domo’s governed environment. *Added June 18, 2026* AI is only as powerful as the systems it can securely connect to. Domo Senior Director of Consulting Ed Engalan shows how to build custom MCP servers from scratch, deploy them as embedded AI agents, and connect them to Claude Desktop to trigger external tools and run complex cross-platform workflows. Walk away with a working blueprint for multiplying your operational impact without rebuilding your existing tech stack. *Added July 28, 2026* Learn what Code Engine is, where to find it, and how it extends Domo with reusable Python or JavaScript functions. You’ll also see how those functions can add custom logic to Workflows and custom apps. *Added July 30, 2026* Bring AI directly into your Domo workflows with two powerful new capabilities (beta): Domo Essentials MCP and Conversational Agents in Domo's AI Library. Together, they let external AI assistants take action inside your Domo instance and let you deploy specialized chat agents anywhere your business needs them. In this video you'll see how to: * Use Domo Essentials MCP as a secure gateway for external AI assistants like Anthropic's Claude and Google's Gemini. * Query data, run workflows, and build content in Domo from your favorite AI assistant. * Build specialized Conversational Agents tailored to a single business domain. * Deploy agents inside App Studio apps, embedded dashboards, or your public website. * Govern every agent on a foundation of trusted, secure data. *Added May 27, 2026* Learn how to build and upload custom heat map charts in Domo using SVG vector graphics and other supported file formats such as KML, GeoJSON, TopoJSON, and Shape files. Discover how to add custom charts through Admin Settings or Analyzer so they become available in the Custom Charts menu within the Chart Picker. Explore how the Custom Regions tool provides an alternative approach for users without XML knowledge. *Added May 27, 2026* Learn how to create a new role in Domo's Role Management interface and configure specific grants to limit user access to defined job functions. Explore how grant selections control the scope of what users can see and do within the platform. Understand best practices for applying role-based access control to support organizational governance requirements. *Added June 15, 2026* Learn how to build and organize Domo dashboards—the primary way to present cards to your team. Discover how to create dashboards, arrange components with drag-and-drop, configure card interactions and drill paths, apply filters, and use filter views. Explore sharing, scheduling, and publishing options. Perfect for organizing and presenting data to your audience. *Added June 11, 2026* Learn how to use built-in documentation tools in Magic ETL to make your DataFlows easier to understand and maintain. Explore how to add notes, comments, and sections, and apply meaningful tile names to clarify the purpose and logic of each step. These practices help collaborators and your future self quickly interpret what a DataFlow does and why it was built that way. *Added June 3, 2026* This video is an introductory video about Domo Cards: what they are, how to create them and some best practices around using them. *Added June 5, 2026* This video describes the different types of Domo embed and walks through how to use Domo embed. *Added June 12, 2026* Learn how Domo's Publish feature enables controlled content distribution from a primary instance to multiple subscriber instances. Explore parent-child relationships, instance management, and publication setup in the Admin Center. Understand what transfers—dashboards, apps, datasets—and what doesn't. Master Personalized Data Permissions (PDP) for secure client-facing deployments. Perfect for companies managing data for multiple clients. *Added June 11, 2026* Learn to add Webforms--DataSets in which you enter the data manually in an Excel-like spreadsheet. *Added June 26, 2026* Learn how Domo Workflows help teams move from insight to action by automating business processes inside and outside of Domo. In this video, you’ll get a guided overview of the Workflow canvas and see how to build a simple workflow from start to finish. You’ll learn how to: * Start with a blank workflow or use a template * Add automated tasks, user tasks, flow controls, and AI agents * Create and use workflow variables * Map inputs and outputs between workflow steps * Send an email using free-form text or variable values * Add start and stop steps * Validate a workflow and review configuration warnings * Save, deploy, and manually run a workflow * Add triggers from App Studio, custom code, DataSet Alerts, and other sources Domo Workflows can notify users, collect approvals, query data, update processes, call APIs, run custom code, loop through DataSets, and route work to the right people. *Added June 18, 2026* Your Snowflake data just got an AI-powered upgrade. This demo walks through three ways to connect Domo and Snowflake's Cortex AI: building agents in Cortex Code (Coco), running natural-language queries with Snowflake Cowork, and asking Domo's AI chat to build dashboards straight from your Snowflake data. Watch data transform into governed, published apps and Cortex-powered insights in minutes, no manual dashboard-building required. This is the Intelligent Enterprise, powered by Domo and Snowflake. *Added July 30, 2026* Learn how to create Beast Mode transformations in Domo to calculate dynamic fields directly at the card level without modifying your underlying dataset. Discover how to use the Beast Mode editor to write SQL-style formulas, reference existing dataset columns, and validate your calculations. Explore how to save reusable Beast Mode calculations to a dataset and apply them across multiple cards. *Added June 11, 2026* Learn how to use Dataset Views in Domo's Data Center to build focused lenses on your existing datasets without materializing new data. Discover how to filter, group, aggregate, sort, and limit rows using the Views Explorer's Table-Based Editor. Explore how to save targeted views to share with specific users or teams while maintaining governance over the full underlying dataset. *Added June 11, 2026* Learn how to configure a Magic ETL dataflow using the tile-based editor in Domo. Discover how to configure transformation tiles, connect input and output datasets, name your data flow, and validate your results with a preview. Explore how to automate your data flow using data update triggers or schedule-based triggers, and how to manually run data flows from the Data Flows section. *Added June 11, 2026* Explore the three core data transformation tools in Domo: Magic ETL, Dataset Views, and Beast Mode. Learn the purpose of each tool, including when to use Magic ETL for complex transformations, Dataset Views for lightweight data preparation, and Beast Mode for card-level calculations. Discover where to access each tool within the Domo interface, from the Data Sets menu to the Analyzer. *Added June 11, 2026* Discover how to use Domo's AI Playground to experiment with and refine AI-powered functionality directly within the Domo platform. Learn how to configure, test, and iterate on AI models and prompts to evaluate their performance before deploying them in production. Gain hands-on experience navigating the AI Playground interface to accelerate your AI development workflow. *Added May 27, 2026* Discover the key methods for bringing data into Domo, including Connectors, Cloud Data Warehouses, Jupyter Workspaces, APIs, and Workbench. Learn how each integration approach works and when to use it based on your data environment and requirements. Walk away with a clear framework for choosing the right integration strategy for your use case. *Added June 12, 2026* Discover how to use Domo's Worksheets feature to explore and analyze data in a familiar spreadsheet-style interface. Learn how to navigate table-based views to simplify data exploration without requiring advanced technical skills. This video demonstrates how Worksheets brings accessible, intuitive data interaction directly within Domo. *Added May 22, 2026* Discover the features released at Domopalooza 2026 that are now live in your Domo instance. Explore enhancements across key areas including AI integration, data transformation, visualization, and automation. Get a comprehensive overview of what's new and how these capabilities can improve your workflows and analytics. *Added June 2, 2026* Learn how to export data from Domo cards and DataSets to Excel or CSV files for offline access. Discover the key differences between exporting a card versus a DataSet, including how filters, aggregations, and column selections affect exported data. Understand row limits, file format trade-offs, and the access permissions required to export data from Domo. *Added May 27, 2026* Flex tables are one of the most powerful ways to highlight change over time across multiple values, but they've come with limitations on user interaction and setup flexibility. This release brings a wave of new options that make Flex Table cards more interactive, more focused, and easier to read at a glance. In this video you'll see how to: * Let users change sort values on a Flex Table directly inside an App Studio App. * Use new default sort options to sort by absolute value of change and quickly spot the biggest shifts, positive or negative. * Apply scale abbreviation to data labels for cleaner, more readable values. * Control where graph data labels appear (first/last, min/max, etc.) to avoid crowded visuals. * Configure individual column settings, including hover text and the Absolute Value of change column option. *Added May 27, 2026* Learn how to create, edit, and share Alerts in Domo to stay informed when your data meets important thresholds or criteria. Explore how Alerts can automatically notify you and your team of meaningful changes in your data. Discover best practices for configuring and managing Alerts across your Domo instance. *Added May 22, 2026* Learn how to control data visibility using Personalized Data Permissions (PDP) in Domo, covering both row-based and column-based access controls. Explore the key differences between the two PDP types and how each can be configured to restrict data at a granular level. *Added June 15, 2026* Learn how to manage and govern features across multiple Domo Everywhere instances using the new scaled governance capabilities in beta. Discover how administrators can apply consistent governance policies and controls across embedded deployments. Explore tools that streamline oversight and configuration management for large-scale Domo Everywhere environments. *Added May 22, 2026* Explore the core principles of user governance in Domo and how roles, grants, and automation work together to ensure the right people have the right access. Learn how Single Sign-On integrates with your corporate directory to automate provisioning, while roles and grants define precise permissions for data stewards, analysts, and consumers. Discover how the Instance Management tool centralizes oversight across environments to enforce consistent governance at scale. *Added June 16, 2026* This video walks you though the use cases of the user management toolkit and demos how to set up a user management job to update user attributes and add custom attributes to a users profile. *Added June 19, 2026* Explore the four group types in Domo (directory, open, closed, and dynamic) and learn when to use each for optimal organization. Understand the benefits of groups for managing user access and collaboration within your Domo environment. *Added June 5, 2026* Four quick demos showing how Domo and Databricks work together — from AI agent skills to sales intelligence to warehouse optimization. 🔹 Agent Skills (Databricks + Domo) — combining Databricks' Agent Skills repo with Domo's own skills library to build sample data in Databricks, connect it to Domo via cloud integration (without the data ever leaving Databricks), and auto-generate a full dashboard with AI-powered insights in minutes. 🔹 Sales & Marketing Intelligence — a cross-sell/upsell solution shown at the Databricks conference. Databricks handles the foundational data platform, machine learning, and model serving; Domo acts as the interoperability and UX layer, running live cross-sell/upsell analysis on a customer account and returning an AI-generated executive summary, ranked product recommendations, and talking points. 🔹 Sales Ops Agent — an agent built on Databricks that aggregates Salesforce data, call transcripts, and emails into one place, summarizes deal status, flags milestones and risk (like negative sentiment), coaches reps ahead of their next call, and writes updates back to the CRM. 🔹 Warehouse Optimization App — an app that rebalances inventory across warehouse lanes using an AI-driven optimizer, auto-optimizing distribution (shown improving from 40% to 86% balanced), with manual override controls, live reporting, and move logs. *Added July 30, 2026* See how Domo and Google Cloud work together to turn any business data into a governed, AI-ready foundation for Gemini Enterprise. With 1,000+ Domo connectors, you can land data from SaaS apps, on-prem databases, files, and APIs directly into BigQuery — building a single source of truth for your AI agents. From there, Gemini Enterprise can activate that data safely and in a governed way, whether through built-in Google agents, custom agents built on Google's ADK, or Domo's own OAuth MCP server. In this demo, we walk through: 🔹 Landing business data (Salesforce, NetSuite, marketing analytics, and more) into BigQuery using Domo connectors 🔹 Adding a brand-new data source live (Meta/Facebook) in just a few clicks 🔹 A custom Domo Query Agent built on Google's ADK answering questions directly from BigQuery data 🔹 Domo's OAuth MCP server enabling governed, permissioned access to BigQuery data — with a live sales and profit analysis *Added July 30, 2026* See how to build an AI agent in Domo, from naming the agent to launching it across the business. This walkthrough follows the three steps every intelligent enterprise needs to make AI useful in production. First, build the data foundation by connecting the agent to governed business data. Second, activate that data by configuring the agent with the context, instructions, tools, and workflows it needs to answer questions and take action. Third, distribute the agent securely to the right audience so employees, teams, or customers can use it where work happens. Domo brings these steps together in one governed platform, helping companies move from AI experiments to AI-powered apps and agents that can actually run inside the business. *Added June 17, 2026* Explore how AI is built throughout the Domo platform, from preparing governed business data to building AI-powered applications. In this video, you’ll see how Domo’s AI tools work together and how organizations can use AI while maintaining their existing data permissions and governance. You’ll learn how to: * Prepare DataSets for AI by using descriptions and synonyms for AI Readiness * Control which columns AI can access and query * Ask questions about dashboards and DataSets using AI Chat * Generate Beast Modes from plain-English instructions * Test prompts and AI functionality in the AI Playground * Connect and select different AI models * Use text generation inside Magic ETL * Create structured outputs for classification, risk analysis, and summarization * Build custom data-powered apps with App Catalyst * Refine and publish AI-generated Pro-Code applications without writing code * Use AI Agents to automate workflow steps and business processes Domo’s AI platform combines conversational analytics, data preparation, generative AI, automation, and app development while continuing to respect the governance and permissions already applied to your data. *Added June 23, 2026* Explore Domo's DataSet API and learn how it enables programmatic uploading of relatively small data files into Domo. Understand the strengths and limitations of this API approach compared to other data integration methods. *Added June 17, 2026* Learn how to combine two DataSets into one using a Join tile in Magic ETL. This video walks through a simple, practical example of configuring a join to merge data from multiple sources. Viewers will gain a foundational understanding of how joins work within Magic ETL dataflows. *Added May 27, 2026* Explore the Magic ETL History and Versions tabs to monitor DataFlow run performance, diagnose failures, and identify problematic version changes. Learn how to interpret execution details including duration, input/output data volume, run initiation method, and tile-level breakdowns. Discover how to revert to a previous DataFlow version to quickly restore successful performance. *Added June 11, 2026* Learn how to create, configure, and manage Jupyter Workspaces within the Domo platform. Explore how to set up workspace environments, manage kernels, and connect to Domo DataSets for advanced analytics and custom code execution. Understand best practices for organizing and maintaining Jupyter Workspaces to support data science workflows. *Added May 22, 2026* Learn how to migrate existing NetSuite JDBC connectors to the new NetSuite JDBC OAuth connector in Domo, preserving DataSet IDs, DataFlows, and cards without rebuilding from scratch. Discover how to use Domo Stats DataSets and the Views explorer to build a mapping document for Domo Support. Understand how to manually update queries to align with the NetSuite2.com schema by replacing record and field IDs while aliasing columns to protect downstream assets. *Added June 17, 2026* Explore how to access and interpret Credit Usage Reporting in Domo to track consumption across your organization. Learn where to find usage data, understand how credits are allocated, and identify key metrics to help manage and optimize your Domo environment. This video helps administrators maintain visibility and control over platform resource usage. *Added May 22, 2026* Explore DomoStats, Domo's built-in observability layer, and learn how to use the DomoStats connector and QuickStart apps to gain instant visibility into your instance. Discover how to track user adoption, DataSet and DataFlow health, governance, and project execution using 90+ pre-built administrative reports. Install one of four QuickStart apps (Activity Log, DataSets and DataFlows, People, or Projects and Tasks) to access ready-made dashboards without building cards from scratch. *Added June 16, 2026* Discover how to use Domo's new Workspaces feature to organize and centralize your content across both web and mobile platforms. Learn how Workspaces help you group Dashboards, Cards, and other Domo assets into a single, accessible location. Explore how this May 2026 update streamlines navigation and improves team Collaboration within Domo. *Added May 22, 2026* Learn how Domo Cloud Integrations natively connects to cloud data warehouses like Snowflake, Databricks, BigQuery, and Redshift without duplicating data. Discover how to configure and manage integrations directly within Domo's Data Connection settings, enabling Magic ETL transformations, card visualizations, dashboards, and alerts on your existing data. Explore key benefits including reduced storage costs, flexible governance with OAuth pass-through, and leveraging the combined power of your warehouse and Domo's full platform. *Added August 3, 2026* Learn how Domo Connectors bring data from external systems like Salesforce, Google Ads, and MySQL into a single centralized location. Discover how to find, configure, and schedule connectors in the Domo Data Center, including setting up credentials, defining data queries, and automating refresh schedules. Explore how to access connector documentation and the Domo Knowledge Base to support your setup. *Added July 31, 2026* Explore the full range of data integration tools available in Domo, including pre-built Connectors, Cloud Data Warehouses integrations, Domo Workbench, file uploads, and API developer tools. Learn how to navigate to the Data Center, Tool Downloads, and the Domo Developer Portal to configure and manage your data connections. Discover how automated data refresh schedules create a single source of truth across your CRM, ERP, marketing platforms, and internal databases. *Added July 30, 2026* Explore how to build custom Domo apps using HTML, CSS, and JavaScript to create highly flexible visualizations beyond standard card limitations. Learn how to access the Pro Code Editor through the Asset Library and leverage AI-powered App Catalyst to generate apps with guided prompts. Discover key use cases including interactive data collection, writeback functionality, and bespoke interfaces tailored to specialized audiences. *Added July 29, 2026* This video walks you though how to set up the Governance Toolkit job for PDP automation. It covers how to use standard and custom attributes to dynamically update PDP rules based on user attributes. *Added June 19, 2026* Explore how to leverage Domo Workflow's built-in AI tools to perform text analysis directly within a Workflow. Learn how to configure AI-powered steps that process and interpret text data as part of an automated workflow process. Understand how these capabilities integrate with broader Workflow logic to enable intelligent, automated decision-making. *Added May 28, 2026* Learn how to use the Domo CLI tool to update a Magic ETL dataflow's output tile to point to an existing dataset instead of a newly created one. This video walks through extracting a dataflow definition as JSON, editing the dataset ID references, and pushing the updated definition back using CLI commands. By the end, you will have a single consolidated dataflow producing multiple outputs tied to their original dataset IDs, preserving all existing cards and content. *Added May 27, 2026* Explore the DataSet History tab to monitor update activity and statuses for your Domo DataSets. Learn how to use built-in tools to Preview, Download, Delete, or Revert individual DataSet updates. Gain confidence in managing DataSet versions to maintain data accuracy and control. *Added June 3, 2026* Learn how to set up and run Hugging Face machine learning models inside a Domo Jupyter Workspace using the Python Transformers package. Discover how to configure key settings including model selection, input and output DataSets, and batch processing for efficient text analysis. See a working example using a Twitter RoBERTa sentiment analysis model applied to a product reviews DataSet. *Added May 28, 2026* Learn how to configure scheduling options for a DataFlow in Domo to ensure your data stays current and accurate. Explore how to set up triggers and conditions that automatically run your DataFlow based on specific events or time intervals. Understand how these scheduling features fit into your broader data pipeline management strategy. *Added May 27, 2026* Learn how to use the Python scripting tile in Magic ETL to run sentiment analysis on text data such as tweets or customer reviews directly in Domo. Discover how to integrate the VADER Python package within a Python Scripting tile to score and classify text sentiment at scale. Walk away with a reusable ETL pipeline that applies machine learning-style text analysis without leaving the Domo platform. *Added May 28, 2026* Learn how to configure Alerts in Domo to monitor critical changes in your Cards and DataSets. Explore how to define alert conditions, set thresholds, and customize notification settings to stay informed when data reaches key values. Discover how to edit, share, and organize Alerts to keep your team proactively notified. *Added May 27, 2026* Learn how to automatically email dashboard snapshots to internal and external recipients using Scheduled Reports in Domo. In this video, you’ll see how to: * Send a dashboard report immediately * Schedule reports daily, weekly, or monthly * Customize the email subject and recipient list * Set an end date for report delivery * Control whether Personalized Data Permissions are applied * View scheduled reports and delivery history in Admin settings * Use an alert to trigger a dashboard report when something important happens Scheduled Reports help keep teams informed without requiring everyone to log in, locate a dashboard, and check the data manually. *Added June 18, 2026* Learn how to access and interpret the run history of a Magic ETL DataFlow to identify errors and diagnose failures. Discover how to audit DataFlow performance over time by reviewing execution logs and status details. Use this information to resolve issues and optimize your data transformation processes in Domo. *Added May 27, 2026* Learn how to identify and resolve common errors in Beast Mode calculations within Domo. Explore techniques for debugging formula syntax and validating calculation logic. Walk away with practical strategies to ensure your Beast Mode expressions return accurate and reliable results. *Added May 27, 2026* An introduction to Domo Accounts. Learn how Domo Accounts centralize credential management for connecting to external systems like Salesforce, Snowflake, and Google Analytics. Explore how accounts are used across various features in the Domo platform to securely authenticate without exposing sensitive credentials. Understand how administrators can share accounts and control permissions to enable team collaboration while maintaining strong security practices. *Added June 15, 2026* Explore the architecture behind AI in Domo, including how Models and the Domo AI Service Layer work together to power intelligent solutions. Learn how this foundation enables both traditional prompt-and-response AI interactions and advanced agentic AI workflows. Gain a clear understanding of how Domo's AI infrastructure supports scalable, flexible AI-driven experiences across the platform. Also learn best practices for when to use agentic solutions and how to get started finding good AI use cases. *Added June 11, 2026* Explore the standard files included in a Pro-Code app, including index.html, app.css, app.js, manifest.json, and thumbnail.png. Learn the purpose of each file within the Pro-Code Editor environment. Discover the different types of resources that can be attached to and managed within a Pro-Code app. *Added May 28, 2026* Explore the core components of an API request, including methods, endpoints, parameters, and body structure. Domo Connectors leverage these elements to retrieve data from third-party systems. Gain foundational knowledge to confidently work with Domo's own API endpoints for programmatic access. *Added June 17, 2026* Learn how Domo's four update methods—Replace, Append, Upsert, and Partition—control how incoming data is incorporated into your Domo DataSets. Explore the key differences between each method, including how Upsert uses primary keys for row-level merging and how Partition manages grouped data buckets. Discover where these update methods are applied across Domo tools including Connectors, Magic ETL, and Jupyter Workspaces. *Added June 12, 2026* This video walks through the Domo user attributes and how to set them up and what they are used for. *Added June 19, 2026* Explore how to access Domo's AI Service Layer using Python within Domo's Jupyter Workspaces integration. Learn how to build a sentiment analysis workflow by connecting to Domo AI capabilities directly from a Jupyter notebook environment. Walk away understanding how to leverage AI and machine learning models programmatically inside Domo. *Added May 28, 2026* Discover how to use Domo's AI Playground to test and experiment with AI tasks available through the Domo AI Service Layer. Learn how to interact with built-in AI capabilities to evaluate model outputs and understand how AI tasks can be applied within your Domo environment. Gain hands-on familiarity with the AI Playground interface before integrating AI features into your workflows. *Added May 22, 2026* Learn how to use Domo's Microsoft Office Add-Ons to access Domo data and cards directly within Excel, Word, PowerPoint, and Outlook. Discover how to embed live Domo content into your Office documents for seamless reporting and analysis. This video covers setup and practical usage of the add-on across all supported Office applications. *Added May 27, 2026* Learn how to use the Save As feature to duplicate and save existing Cards in Domo. Discover how to preserve your original Card while creating customized versions for different use cases or audiences. This video walks through the step-by-step process of saving a Card under a new name and location. *Added May 27, 2026* Stop manually handling content access requests in Domo. The new "Access Request" event trigger for Workflows kicks off a custom workflow the moment a user clicks "Request Access" on a Card, Page, or App — replacing manual follow-ups with a governed, automated process tailored to your organization. In this video you'll see how to: * Trigger a Workflow automatically when a user requests access to a Card, Page, or App. * Design multi-step approval workflows that match your governance needs. * Route notifications to the correct content owners. * Build a complete audit trail for every access request. * Ensure the right people get the right access in a timely, consistent way. *Added May 27, 2026* Learn how to use the Versioning feature in Magic ETL to document and track changes made to your DataFlows over time. Discover how to add version notes to capture the purpose of each update and maintain a clear change history. Explore how to revert a DataFlow to a previous version when needed to recover from errors or unintended modifications. *Added May 27, 2026* Learn how to use Variables in Beast Mode to build a dynamic Fahrenheit to Celsius temperature converter on a Domo dashboard. Explore how Variables enable interactive, user-driven inputs that update card calculations in real time. Walk away with a practical example of combining Beast Mode formulas and Variables to create flexible, dynamic dashboard experiences. *Added May 27, 2026* Workbench allows enterprises to access and upload on-premise data (e.g. ODBC, XML, Excel, JIRA, QuickBooks, etc.) so that it can be analyzed and assessed to help improve your business. *Added June 26, 2026* Learn how Domo handles time zone settings across your data and instance configuration. Discover best practices for ensuring your data appears in the correct time zone as defined by your Domo instance administrator. Understand the relationship between data time zones and Domo's instance-level time zone settings to avoid common display discrepancies. *Added May 27, 2026* # Domo on Lakebase Source: https://www.domo.com/docs/s/article/Domo-on-Lakebase ## Intro With Cloud Integrations, you can query and visualize Lakebase data directly in Domo without copying or duplicating data. This article explains how to set up and manage a Lakebase integration in Domo. *** ## Prerequisites * Confirm you have an account with access to Lakebase. * Ensure the Postgres user you will use for the Lakebase service account has the following Postgres privileges: * **CONNECT —** on the database—database visibility * **USAGE —** on the schemas—schema visibility * **SELECT —** on the tables—query data * If you plan to use **Username & Password** authentication: In Lakebase, go to **Advanced Settings**, enable **Postgres native role login**, and create a native username and password. Use these credentials when creating the service account. ## Access the Lakebase Integrations Page 1. Navigate to **Data Warehouse**. 2. Select **Connect Data**. 3. From the Cloud Integrations list, select **Lakebase**. The **Domo on Lakebase** page appears. Domo on Lakebase landing page ## Create a Lakebase Integration Every Lakebase integration requires a service account. You can reuse one service account across multiple integrations and run multiple integrations in the same Domo instance—use clear, descriptive names to tell them apart. Lakebase integration setup form 1. Enter a **Name** for the integration. This label identifies it within Domo—it doesn't need to match any Lakebase names and can be changed later. 2. (Optional) Enter a **Description**. The description appears only in integration details—most views show only the name. 3. In the **Lakebase service account** field, select an existing service account, or select **Add account...** to create a new one. If you select **Add account...**, the New Lakebase Service Account dialog appears—complete the steps in [Create a Lakebase service account](#create-a-lakebase-service-account) below, then return here and continue with step 4. **Important:** If you change the service account later, DataSets and DataFlows may need remapping, and access to previously connected tables may change if the new account has different privileges. 4. In the **Lakebase account database** field, enter the name of the database that contains your Lakebase tables. You can find this in your Lakebase catalog or database settings. 5. Select **Save integration**. Lakebase service account dropdown After saving, a confirmation screen appears. Integration created successfully Select **Proceed to Integration Overview** to start connecting tables and configuring the integration. ## Create a Lakebase Service Account **Important:** Anyone with access to this service account—including other account owners, Domo admins, and users you share it with—can use its credentials to access Lakebase and create connected DataSets in Domo. Passwords, tokens, and keys are never visible. 1. In the **New account name** field, enter a name to identify this service account within Domo. Use a clear, distinctive name to avoid confusion with other Lakebase accounts and integrations. 2. In the **Lakebase account server hostname** field, enter the server name or IP address of your Lakebase instance. 3. In the **Lakebase account port** field, enter the port your Lakebase instance uses for incoming connections. 4. From the **Connect with** dropdown, select your authentication method: * **Username & Password —** Authenticate using a native Postgres username and password. Requires Postgres native role login to be enabled in Lakebase Advanced Settings. * **M2M OAuth —** Authenticate using Databricks machine-to-machine OAuth credentials. New Lakebase Service Account dialog — M2M OAuth selected 5. Enter the credentials for your selected method. (Conditional) If you selected **Username & Password**: a. In the **Lakebase username** field, enter the native username you created in Lakebase. b. In the **Lakebase password** field, enter the native password you created in Lakebase. New Lakebase Service Account dialog — Username & Password (Conditional) If you selected **M2M OAuth**: a. In the **Databricks workspace hostname** field, enter the hostname of your Databricks workspace. b. In the **Client ID** field, enter the application ID of the Databricks service principal. c. In the **Client Secret** field, enter the OAuth secret for the service principal. M2M OAuth credential fields 6. Select **Create Account**. The service account is saved and available in the **Lakebase service account** dropdown when creating an integration. To view and manage existing service accounts, go to **Data Warehouse** > **Connect Data** > **Cloud Integrations** > **Lakebase**. ## Manage Existing Integrations Select **Manage Integrations** from the **Domo on Lakebase** page to view existing integrations. The Lakebase Cloud Integrations page lists each integration's name, number of connected tables, configuration type, and your access level. You can also select **+ Add New Integration** from this page. Lakebase cloud integrations page To manage a specific integration, select the wrench icon next to it. Available options vary based on your access level: * **Edit integration —** Update the integration's name, description, service account, or database settings. From the integration settings page, you can also connect tables, configure data freshness, and share the integration with other users. For details on data freshness and account sharing, see [Cloud Integrations Overview](/docs/s/article/4412849158167#cloud-integrations-overview). * **Select tables to connect —** Add or remove Lakebase tables from the integration. See [Connect Tables](/docs/s/article/Connect-Tables-in-Cloud-Integrations#connect-tables-in-cloud-integrations) for instructions. * **Delete integration —** Permanently remove the integration. Integration settings page # Getting Started for Data Consumers Source: https://www.domo.com/docs/s/article/Getting-Started-for-Data-Consumers ## Intro Get up and running with Domo faster and start seeing more insights in record time. ### Self-Guided On-Demand Course * [Start learning now](https://learndomo.domo.com/learn/course/internal/view/elearning/402/data-consumer-training) ### Popular Links and Topics * [Download the mobile app on iOS](https://apps.apple.com/us/app/domo-inc/id553997239) * [Download the mobile app on Android](https://play.google.com/store/apps/details?id=com.domo.android\&pli=1) * [Find a data connector (1,000+)](https://www.domo.com/appstore/apps?capability=Connector) * [Chart types](/docs/s/article/360042935294) * [Find a Quickstart dashboard](https://www.domo.com/appstore/apps?q=quickstart) * [Sample DataSets](/docs/s/article/360043931814) * [Domo glossary](/docs/s/article/360043427453) * [App showcase](https://www.domo.com/) * [Find an app](https://www.domo.com/appstore/apps) * [Docs & APIs](https://www.domo.com/docs/portal/Getting-Started/overview) *** ## Learn the Basics Get a quick tour of Domo, start learniing Domo terminology, and get your profile set up. * [Intro to Domo](/docs/s/article/000005874) * [The Domo interface](/docs/s/article/360043442453) * [Domo glossary](/docs/s/article/360043427453) * [Set up your profile](/docs/s/article/360042934674) * [Invite a new user](/docs/s/article/360043438893) ## Consume and Create Content in Domo Start here to learn how to create, view, and interact with data in Domo. ### Understand and Create Domo Cards Use Domo Cards to start creating individual charts, then easily use cards as building blocks for creating dashboards quickly. * [How data becomes a Domo Card](/docs/s/article/360043429873) * [Building Domo Cards in Analyzer](/docs/s/article/360042924094) * [Interacting with Domo Cards](/docs/s/article/360043428653) ### Understand and Create Dashboards Dashboards within Domo are made up of Domo Cards that you can edit, arrange, and modify as you choose. Simply drag and drop to achieve your preferred layout, and quickly filter and drill down for instant insights. * [Dashboards overview](/docs/s/article/360043428553) * [Creating a Domo Story Dashboard](/docs/s/article/360043428433) * [Managing your dashboards](/docs/s/article/360043428253) * [Filtering your dashboards](/docs/s/article/360042923914) ### Share and Collaborate Share, annotate, and have conversations with your colleagues about the insights you're seeing—all without ever leaving Domo. * [Sharing overview](/docs/s/article/360042933074) * [Alerts overview](/docs/s/article/360043430373) * [Collaborate around data with Domo Buzz](/docs/s/article/360042925574) ## Connect and Use Data in Domo Learn how to quickly connect data to Domo and make it available for analysis. * [Using the Domo Data Center](/docs/s/article/360047553253) * [Connecting to live data with connectors](/docs/s/article/360042926274) * [Explore 1,000+ cloud connectors](https://www.domo.com/appstore/apps?capability=Connector) * [Drag and drop a file](/docs/s/article/360043436573) * [Transforming data with Magic ETL](/docs/s/article/360055259234) * [Sample DataSets](/docs/s/article/360043931814) ### Popular Connectors These are just a few of the 1,000+ cloud connectors you can find in Domo's Appstore. * [Google Sheets](https://www.domo.com/appstore/connector/google-sheets-connector/overview) * [Google Analytics](https://www.domo.com/appstore/apps?q=Google%20Analytics\&capability=Connector) * [Smartsheet](https://www.domo.com/appstore/connector/smartsheet-connector/overview) * [Salesforce](https://www.domo.com/appstore/apps?q=Salesforce\&capability=Connector) * [Amazon S3](https://www.domo.com/appstore/connector/amazon-s3-connector-1/overview) * [See all connectors](https://www.domo.com/appstore/apps?capability=Connector) # Getting Started for Data Engineers Source: https://www.domo.com/docs/s/article/Getting-Started-for-Data-Engineers ## Intro Learn how to connect and transform data in Domo, orchestrate data pipelines, and manage data governance. ### Self-Guided On-Demand Course * [Start learning now](https://learndomo.domo.com/learn/course/internal/view/elearning/402/data-consumer-training) ### Popular Links and Topics * [Download the mobile app on iOS](https://apps.apple.com/us/app/domo-inc/id553997239) * [Download the mobile app on Android](https://play.google.com/store/apps/details?id=com.domo.android\&pli=1) * [Find a data connector (1,000+)](https://www.domo.com/appstore/apps?capability=Connector) * [Chart types](/docs/s/article/360042935294) * [Find a Quickstart dashboard](https://www.domo.com/appstore/apps?q=quickstart) * [Sample DataSets](/docs/s/article/360043931814) * [Domo glossary](/docs/s/article/360043427453) * [App showcase](https://www.domo.com/) * [Find an app](https://www.domo.com/appstore/apps) * [Docs & APIs](https://www.domo.com/docs/portal/Getting-Started/overview) *** ## Learn the Basics Get a quick tour of Domo, start learning Domo terminology, and get acquainted with admin settings. * [Intro to Domo](/docs/s/article/000005874) * [The Domo interface](/docs/s/article/360043442453) * [Domo glossary](/docs/s/article/360043427453) * [Using the Domo Data Center](/docs/s/article/360047553253) * [Working with DataSets in Domo](/docs/s/article/360042926154) * [Admin settings overview](/docs/s/article/360042934234) ## Consume and Create Content in Domo Learn how to quickly connect data in Domo and make it available for analysis. * [Connecting data in Domo overview](/docs/s/article/360047553253) * [Certifying Domo Cards and DataSets](/docs/s/article/360043430613) * [Using data lineage](/docs/s/article/360043428853) ### Ways to Connect to Data Connect to data from cloud, on-premises, and federated data sources. * [Drag and drop a file](/docs/s/article/360043436573) * [Connecting to live data with connectors](/docs/s/article/360042926274) * [Explore 1,000+ connectors](https://www.domo.com/appstore/apps?capability=Connector) * [Connect to on-premise data with Workbench](/docs/s/article/360056669354) * [Using the federated data solution](/docs/s/article/360042932974) * [JSON No-Code Connector](https://domo.domo.com/appstore/connectors/com.domo.connector.json.customparsing) * [DataSet via email](/docs/s/article/360042931954) * [Advanced tools](/docs/s/article/4403501587607) * [Explore other ways to connect](/docs/s/article/360052122294) ## Connect and Use Data in Domo Quickly combine data from disparate systems and optimize your existing cloud data warehouses or lakes. * [ETL overview](https://www.domo.com/data-integration/etl) * [Transforming data with Magic ETL](/docs/s/article/360055259234) * [DataSet Views](/docs/s/article/360046074774) * [Managing DataFlows](/docs/s/article/000005216) * [Creating a SQL DataFlow](/docs/s/article/360042922994) * [Viewing DataFlow details](/docs/s/article/360042923054) * [Creating an Adrenaline Dataflow](/docs/s/article/360063698733) ### Add Calculated Fields and Custom Metrics Easily create your own calculated fields. * [Adding a Beast Mode calculation to a chart](/docs/s/article/360043429913) * [Calculated fields reference guide](/docs/s/article/360043429933) ### Applying data science with Domo Use Domo to prep your data for data science. * [AutoML](/docs/s/article/360048127854) * [Magic ETL data science tiles](/docs/s/article/360045259294) # Migrate Users to the New Left Navigation Source: https://www.domo.com/docs/s/article/Migrate-Users-to-the-New-Left-Navigation ## Intro This article explains how to understand the left navigation migration banner and migrate your users to the new left navigation before Domo disables the top navigation. *** ## Required Grants To view the migration banner and transition users to the new left navigation, you must have the Admin role. Specifically, this requires the **Manage all company settings** grant, which is included in the default Admin role by default. ## Understand the Migration Banner If you are a Domo Admin, a banner will appear in your instance inviting you to enable the new navigation. We recommend migrating your users before the deadline to ensure a smooth transition. Navigation Banner ## Migrate Users to the New Left Navigation Follow these steps to migrate your users to the new left navigation: 1. Select **Learn More** in the notification banner to open the New Navigation settings. Navigation Banner **Note:** If you dismiss the banner, you can also select **More** > **Admin** in the top navigation, then select **New Navigation** under **Company Settings** to access the enablement tool. Navigation Banner Navigation Banner 2. The following options are available to help you migrate users to the new navigation: * **Not enabled in your instance —** This option disables the new navigation for all users in your instance. It is the default behavior if the new navigation has not been enabled yet. * **Enabled for everyone —** Enables the navigation for all users in your instance. * **Enabled for admins —** Enables the navigation for all admin users in your instance. This option grants all admins who can view the Company Settings page access to the navigation enablement tool. * **Enabled for a specific group —** Enables the navigation for a specific group. Navigation Banner 3. To save your changes, select **Save** in the top-right corner. A confirmation message appears. Select **Enable** to confirm. The change takes effect immediately. Navigation Banner ## Resources and Documentation Refer to the New Navigation knowledge base article, feature overview videos, and useful links in the **Resources** section. Navigation Banner # Snowflake Minimum Permissions for Domo Source: https://www.domo.com/docs/s/article/Snowflake-Minimum-Permissions-for-Domo ## Intro This article describes the minimum Snowflake permissions required to connect Domo to Snowflake, including read-only, writeback, and Native Transform (Pushdown) configurations. Use two logical permission scopes: * **Source data (read-only):** Grant Domo read-only privileges on the databases, schemas, and tables it needs to query. * **Domo-managed location (writeback + Native Transform):** Because the Domo service account needs permissions to create and manage tables, scope these elevated privileges tightly. To limit the scope of any potential issue, create a dedicated database and schema that Domo can use exclusively for write operations and intermediate objects. This location hosts: * Writeback tables * Utility objects (such as file formats) * Native Transform intermediate objects *** ## Prerequisites Before you begin, decide on the following and substitute the placeholder values in the SQL examples below: * The warehouse Domo uses for compute (`MY_WAREHOUSE`) * The source databases, schemas, and tables Domo should read (`MY_READ_DB`, `MY_READ_DB.PUBLIC`, `MY_READ_DB.PUBLIC.MY_TABLE`) * The dedicated database Domo uses for writeback operations (`MY_WRITEBACK_DB`) * The schema within that database where Domo writes tables (`WRITEBACK_SCHEMA`). Note: `DOMO_UTIL` is a fixed utility schema name used for file formats and does not need to be substituted. * The service account Domo authenticates with (`MY_SERVICE_ACCOUNT`) The following tables list all permissions required by each Domo role, the object each permission applies to, and its purpose. ### Read-Only Permissions Domo requires these permissions to query data from Snowflake. | Permission | Object type | Purpose | | ---------- | ------------ | ---------------------------------------------------------------- | | `USAGE` | Warehouse | Allows Domo to run queries using the specified warehouse | | `USAGE` | Database | Allows the role to see and reference the database | | `USAGE` | Schema | Allows the role to see and reference schemas within the database | | `SELECT` | Table / View | Allows Domo to read data from tables or views | ### Writeback Permissions Domo requires these permissions when writing data back to Snowflake. Grant them only on Domo-managed schemas or databases. | Permission | Object type | Purpose | | -------------------- | ----------- | -------------------------------------------------------------------------------------------- | | `USAGE` | Database | Allows the role to see and reference the writeback database | | `USAGE` | Schema | Allows the role to see and reference the writeback schema | | `CREATE TABLE` | Schema | Allows Domo to create and manage writeback tables in the target schema | | `CREATE FILE FORMAT` | Schema | Allows creation of file formats used during writeback operations — grant only on `DOMO_UTIL` | ### Native Transform permissions Native Transform executes transformation logic directly in Snowflake and requires the following additional permissions. | Permission | Object type | Purpose | | --------------- | ----------- | ---------------------------------------------------------------------------------- | | `CREATE SCHEMA` | Database | Allows Domo to create temporary schemas used for intermediate transform operations | ## Set Up Read-Only Permissions 1. Create the role. ```sql theme={"dark"} CREATE ROLE IF NOT EXISTS DOMO_READONLY; ``` 2. Grant warehouse usage. ```sql theme={"dark"} GRANT USAGE ON WAREHOUSE MY_WAREHOUSE TO ROLE DOMO_READONLY; ``` 3. Grant database and schema visibility. ```sql theme={"dark"} GRANT USAGE ON DATABASE MY_READ_DB TO ROLE DOMO_READONLY; GRANT USAGE ON SCHEMA MY_READ_DB.PUBLIC TO ROLE DOMO_READONLY; ``` 4. Grant table access. ```sql theme={"dark"} GRANT SELECT ON TABLE MY_READ_DB.PUBLIC.MY_TABLE TO ROLE DOMO_READONLY; ``` 5. Assign the role to the service account. ```sql theme={"dark"} GRANT ROLE DOMO_READONLY TO USER MY_SERVICE_ACCOUNT; ``` 6. (Optional) Grant access to future tables. If you need to grant SELECT access to all future tables in a schema, use a Snowflake future grant. Repeat this command for each schema that requires access. ```sql theme={"dark"} GRANT SELECT ON FUTURE TABLES IN SCHEMA MY_READ_DB.PUBLIC TO ROLE DOMO_READONLY; ``` ## Set Up Writeback Permissions **Important:** Scope writeback permissions to a dedicated Domo-managed database and schema to limit the scope of elevated privileges. 1. Create the writeback role. ```sql theme={"dark"} CREATE ROLE IF NOT EXISTS DOMO_WRITEBACK; ``` 2. Create a Domo-managed database and schema. The example below uses `WRITEBACK_SCHEMA` as the target schema for writeback tables, but you can substitute an existing schema. If you skip creating the schema, substitute your target schema name in the grant commands in steps 3 and 4. * Database: `MY_WRITEBACK_DB` * Utility schema: `DOMO_UTIL` * (Optional) A dedicated target schema for writeback tables (such as `WRITEBACK_SCHEMA`) ```sql theme={"dark"} CREATE DATABASE IF NOT EXISTS MY_WRITEBACK_DB; CREATE SCHEMA IF NOT EXISTS MY_WRITEBACK_DB.DOMO_UTIL; CREATE SCHEMA IF NOT EXISTS MY_WRITEBACK_DB.WRITEBACK_SCHEMA; ``` 3. Grant database and schema visibility. ```sql theme={"dark"} -- Database visibility/access GRANT USAGE ON DATABASE MY_WRITEBACK_DB TO ROLE DOMO_WRITEBACK; -- Schema visibility/access GRANT USAGE ON SCHEMA MY_WRITEBACK_DB.DOMO_UTIL TO ROLE DOMO_WRITEBACK; GRANT USAGE ON SCHEMA MY_WRITEBACK_DB.WRITEBACK_SCHEMA TO ROLE DOMO_WRITEBACK; ``` 4. Grant object-creation privileges only where Domo needs them. Domo creates writeback tables in the target schema and creates file formats in `DOMO_UTIL` to stage and load data during writeback operations. ```sql theme={"dark"} -- Allow Domo to create writeback tables GRANT CREATE TABLE ON SCHEMA MY_WRITEBACK_DB.WRITEBACK_SCHEMA TO ROLE DOMO_WRITEBACK; -- Allow Domo to create file formats used during writeback (grant only on DOMO_UTIL) GRANT CREATE FILE FORMAT ON SCHEMA MY_WRITEBACK_DB.DOMO_UTIL TO ROLE DOMO_WRITEBACK; ``` 5. Assign the writeback role to your service account. ```sql theme={"dark"} GRANT ROLE DOMO_WRITEBACK TO USER MY_SERVICE_ACCOUNT; ``` ## Set Up Native Transform Permissions Native Transform (also called Pushdown) extends the writeback configuration. It creates and drops temporary schemas in Snowflake during execution, so the `DOMO_WRITEBACK` role also requires `CREATE SCHEMA` on the target database. Complete [Set Up Writeback Permissions](#set-up-writeback-permissions) before proceeding. 1. (Conditional) If you use Native Transform, grant schema creation on the Domo-managed database. ```sql theme={"dark"} GRANT CREATE SCHEMA ON DATABASE MY_WRITEBACK_DB TO ROLE DOMO_WRITEBACK; ``` # Upgrade to Workbench 5.2 Source: https://www.domo.com/docs/s/article/000005103 ## Intro To experience the best performance and most up-to-date features, it's important to have the latest version of Workbench. Domo Support can always help troubleshoot issues with legacy versions, but we provide our best support when you're running the latest version. We strongly recommend that you check regularly and upgrade to the latest version if necessary. **Note:** Before proceeding with any update or migration, you should back up your jobs. If there are issues or errors during the upgrade, you may need backups. If possible, ask your IT department to take a full snapshot or backup of your VM, Server, or PC before performing an upgrade. *** ## Identify Your Current Version To determine which version of Workbench you are currently running, launch Workbench and note the version on the splash screen, as shown below. wb splash.png If you contact Domo Support, you may be asked what version of Workbench you are running to receive customized assistance. ## Download Workbench 5.2 Follow these steps to download the latest version of Workbench: 1. In the navigation header, select **More** > **Admin**. The Admin page displays. 2. Locate the **More** section, then select **Tool Downloads**. 3. In **Tool Downloads**, locate the **Workbench 5.2** section. 4. Select **Download Domo Workbench**. The installer file downloads. ## Turn Off Automatic Updates By default, automatic updates are enabled and apply to the latest major product version. Automatic updates include a restart of the Workbench service. Users who want change control and planned maintenance may want to turn off the automatic update feature. This process is described below. 1. Open the Workbench application. 2. Select **More**. 3. In the **Settings** section, locate **Updates**. 4. Uncheck **Install updates automatically**. updates.png If you choose to turn off automatic updates, we strongly recommend that you plan for regular manual maintenance and updates to ensure the best performance from your Workbench application. ## Upgrading Error If the error shown below displays in Workbench logs when upgrading a Workbench application, it is because the Microsoft.NET 4.8 Framework installer cannot make it through to the internet due to a proxy blocking it when upgrading Workbench. You can get around this by going to [https://support.microsoft.com/en-us/topic/microsoft-net-framework-4-8-offline-installer-for-windows-9d23f658-3b97-68ab-d013-aa3c3e7495e0](http://support.microsoft.com/en-us/topic/microsoft-net-framework-4-8-offline-installer-for-windows-9d23f658-3b97-68ab-d013-aa3c3e7495e0) and downloading the offline installer, then installing with it. ###### Log Error *** \[1A00:0123]\[2023-01-10T12:34:56]i123: Detect begin, 5 packages \[1A00:0123]\[2023-01-10T12:34:56]i123: Setting string variable 'NETFRAMEWORK45' to value '394802' \[1A00:0123]\[2023-01-10T12:34:56]i123: Setting string variable 'QBFC16INSTALLED' to value '' \[1A00:0123]\[2023-01-10T12:34:56]i123: Registry value not found. Key = 'SOFTWARE\Microsoft\Windows\CurrentVersion\Uninstall\{42A7A870-C6A9-4EEE-8755-2755E3C60EE4}', Value = '(null)' \[1A00:0123]\[2023-01-10T12:34:56]i125: Condition 'NETFRAMEWORK45 >= 528040' evaluates to false. *** # Workbench 5.2 Overview Source: https://www.domo.com/docs/s/article/000005138 Workbench 5.2 is an incremental upgrade from Workbench 5.1 that allows job duplication and provides support for Cloud Integrations. To move to Workbench 5.2, see our article about [Upgrading to Workbench 5.2](http://domo-support.domo.com/s/article/000005103?language=en_US). The following articles provide information unique to Workbench 5.2: * [Cloud Integrations Support in Workbench 5.2](http://domo-support.domo.com/s/article/9337403057943?language=en_US) * [Duplicating a Job in Workbench 5.2](http://domo-support.domo.com/s/article/9338871306135?language=en_US) For other information about Workbench 5.2, we refer you to the documentation for [Workbench 5.1](http://domo-support.domo.com/s/topic/0TO5w000000ZapUGAS/workbench-51?language=en_US), as it is still applicable in many cases. If you cannot find the information you need to perform a task in Workbench 5.2, please contact [Domo support](http://domo-support.domo.com/s/) or your Domo representative. # Workbench Migration Source: https://www.domo.com/docs/s/article/000005219 ## Intro Workbench Migration simplifies moving your Workbench jobs to a new server or Workbench machine. With a smoother import/export experience, you can securely move all your Workbench jobs, including the encryption keys. This allows you to restore settings and accounts as configured on any computer. ### Notes Keep the following in mind as you use Workbench Migration: * Jobs are saved in Domo, so any changes made to the jobs after backup will persist. * Any jobs scheduled to run using local time run based off the local time of the new machine after the migration. * If the new machine is on a new network, you may need to reconfigure the proxy settings. The proxy settings will be imported from the machine you are migrating from. * Make sure to turn the service OFF on the machine you are migrating from; otherwise, you will see frequent job errors. We recommend migrating to a clean machine. * Install all required ODBC drivers on the new machine. * Recreate any DSNs on the new machine that are used by Workbench jobs. * Workbench jobs that require user impersonation launch as the impersonated user. Make sure that impersonated users are in the Domo Workbench Users group. You can do this after Workbench is installed on the machine you are migrating to. ## Create Backup of Workbench Configuration 1. Navigate to **Settings** in Workbench. The **Workbench Backup** configuration section displays. 2. In the **Create backup** tab, select **Browse** and search for and select the file name for your backup. browse.jpg 3. (Conditional) Select **Generate and copy** if you want Domo to generate a secure passcode for your backup. Otherwise you can create your own passcode, following these criteria: * 20 characters or more * Includes at least one uppercase letter * Includes at least one lowercase character * Includes at least one number * Includes at least one symbol generate and copy.jpg 4. Select **Create**. create.jpg ## Import Backup **Important:** Importing a system backup while Workbench is in the middle of an operation can break Workbench and cannot be fixed in code. We strongly recommend that you turn Workbench OFF while importing the backup, then turn it back on when the backup is complete. **Note:** To migrate your Workbench jobs, you need to run the Workbench as an administrator. 1. Navigate to **Settings** in Workbench. The **Workbench Backup** configuration section displays. 2. In the **Import backup** tab, select **Browse** and select the Workbench backup file that you want to import. browse import.jpg 3. Enter the passcode that you generated in the **Passcode** field. passcode field.jpg 4. Select **Import**. import backup.jpg # Workbench Writeback to ODBC Source: https://www.domo.com/docs/s/article/000005234 ## Intro This article describes how to write a DataSet from Domo into an on-prem database using Workbench writeback. Following this process allows you to securely move your data from Domo into your on-prem system with all the same security features and benefits that come with standard Workbench. *** ## Install the ODBC Writeback Plug-in **Important:** If you don't already have Workbench installed, install the latest version of Workbench as an admin. You must install Workbench on a Windows server or laptop that has access to the database server; you do not necessarily need to install it on the database server itself. For more information, see the [Workbench installation guide](/docs/s/article/4406022964375). 1. After you have Workbench 5 or above installed, download the ODBC Writeback plug-in by selecting this link: [https://app.domo.com/workbench/plugins/beta5/OdbcWritebackDataProvider.dwp](https://app.domo.com/workbench/plugins/beta5/OdbcWritebackDataProvider.dwp "https://app.domo.com/workbench/plugins/beta5/OdbcWritebackDataProvider.dwp") 2. After downloading the plug-in, add it to Workbench. See how to do this in [Manage Plugins in Workbench 5](/docs/s/article/360043437353). 3. Restart Workbench. ## Get Client ID and Secret Please refer to [Creating a Developer Client and Auth Token](/docs/s/article/000005240#create-api-clients) for instructions on how to get your Client ID and Secret. ## Get DataSet ID 1. In your Domo instance, navigate to the Data Center and the Details view of the DataSet you want to write back to your on-prem database. 2. In the address bar of the webpage, locate and copy the DataSet ID and save it for later. It is the string between the *datasources/* and the */details*. ## Set Up DSN To use the ODBC to connect to the server, you must have a system data source name (DSN). Follow the steps below to set up the DSN. 1. On the server where Workbench is installed, select **Start** and enter ``` odbc ``` You will likely need ODBC data sources (64 bit). 2. Navigate to **System DSN** and select **Add**. 3. Select **SQL Server Native Client**. If you do not see that option, download it by selecting this link: [https://learn.microsoft.com/en-us/sql/connect/odbc/download-odbc-driver-for-sql-server?view=sql-server-ver16](https://learn.microsoft.com/en-us/sql/connect/odbc/download-odbc-driver-for-sql-server?view=sql-server-ver16) The **Microsoft SQL Server DSN Configuration** wizard displays. select sql server native client.png 4. Enter a name for this DSN in the **Name:** field. 5. Enter the name of the SQL Server in the **Server:** field. dsn config wizard.png 6. Select **Finish**. The DSN displays in the **System** tab of the **ODBC Data Source Administrator (64-bit)**. system dsn tab.png ## Add Account in Workbench 1. On this same server, open Workbench. **Note:** If you had Workbench open during DSN setup, we recommend that you restart Workbench. 2. Select **Start** and enter: ``` workbench ``` or ``` domo ``` in the search bar. 3. In the sidebar, select **Accounts**. 4. Select **Add**. add account.jpg 5. In the **Overview** tab, enter the name of your Domo instance in the **Domo domain** field. 6. Select **Authorize**. 7. Follow the authorization link in your browser and when prompted for a code, paste in the code from the **Authorization code** field in Workbench. 8. Close the browser window when prompted. 9. In Workbench, select **Save** to add your new account. ## Create Job in Workbench 1. In the sidebar, select **Jobs**. 2. Select **Add**. add job.jpg 3. In the **Job Details** section, select the Domo domain, enter a job name, select a transport type, and select a reader type. 4. In the **Domo Details** section, enter a name in the **DataSet Name** field. **Note:** The DataSet Name that you enter is NOT the DataSet that is being written back. It refers to the name of the log table that Domo creates. wb log.jpg 5. Under **Source**, select **Edit**. 6. Enter the [Client ID and secret](#get-client-id-and-secret) that you copied earlier in this process in the **Domo Client Id** and **Domo Client Secret** fields. 7. Enter the [DataSet ID](#get-dataset-id) that you copied earlier in the **Domo Dataset Id** field. We do not recommend using **Browse**. generate query.png 8. Select **Generate Dataset Query**. A query is generated that you can edit to only include the columns that you want to write back. **Note:** Make sure that the user that is logged in to Workbench has access to this DataSet. If they have an Admin security role, the DataSet does not need to be individually shared with them. Learn about sharing DataSets in [Share a DataSet](/docs/s/article/360043430713). 9. Select an **ODBC Connection Type**. odbc connection type.png 10. Select **DataBase Type**. 11. Select **Generate Writeback Query**. generate writeback query.png **Note:** By default, Domo generates a query for all columns. If you adjusted the query above, make sure to update the Writeback Query String. adjusted writeback.png **Note:** Domo does not create a table on the database. You need to create it first. Here is an example of a table created in SQL server: ```sql theme={"dark"} create table database1.dbo.domo_widgets (id numeric(18,0) , widget_id numeric (18,0) , qty numeric(18,2) , amount numeric (18,2) ) ``` This is the updated query after creating the table: updated wb query.png 12. **Processing (Edit) Section —** There is nothing you need to do in this section. Workbench initiates the data connection. It connects to the Domo DataSet and pulls it back as a CSV first and uses this CSV file to load into the SQL server. 13. **Update Method —** This is not the update method to the target database. This tells Domo whether to append or replace the log table that is created within the Domo instance. 14. Set up [impersonation](/docs/s/article/360043437173#impersonation). This allows Workbench to run as the active directory user. 15. Execute the job. ## Notes * In the **Writeback Query** section, you can only run one statement at a time. * There is a default value of 25. Domo writes back all the records from the DataSet, not only the 25. Leave that as is. * There is a limit of one million (1M) rows in Workbench Writeback due to the endpoint that is used. * Workbench writeback is designed to only run one query at a time. You cannot add more than one Data Manipulation Language (CML) command: Insert, Delete, Update, Merge. Even if you add more than one, Domo only processes one at a time. It does allow alter statements. Per product, even if you include two statements, Domo does not guarantee the integrity of the second statement. * Workbench creates a log table with the same name as the DataSet name mentioned in the **Overview** tab. * With normal writeback, you have the option to trigger a writeback when the input DataSet is refreshed. With Workbench writeback, however, you are only able to schedule it. This is a security feature and the connection is initiated from Workbench. # Use Encryption to Keep Workbench Data Secure Source: https://www.domo.com/docs/s/article/000005248 ## Intro Decision makers recognize the value of insights gained from their business data. The ability to quickly review relevant data provides better understanding of business operations and accelerates better decisions. To continually optimize business processes, companies are looking for new data sources, improved data modeling, and simpler direct access to data warehouses. With the exponential growth of data, companies have increasing concerns around data security—how can we keep data secure? With whom should we partner for IT projects and applications? How should we share data internally and externally? Increased exposure to data breaches and other data security issues are concerns that now reside on the desk of the CEO, not just the CTO or CIO. It's common to hear news about data breaches and the negative impact they have on organizations. 1 All company departments need to be concerned about inadvertently sharing their protected data with individuals and partners who do not need it while still enabling others in their ecosystem to use the data to complete their critical tasks. Protecting all data is a primary concern when selecting employees, vetting partners, and selecting vendors. You need a partner that can help you ensure that your business data is being handled correctly. ## All Data Is Not Created Equal Your organization generates and consumes different types of business data. Some of this data is publicly available and can be used and accessed by multiple users without strict control measures. Other data is sensitive, such as salaries or revenue. Finally, some data, like employee medical information, is protected by law. In each case you have the responsibility to ensure that you are compliant with different operation requirements and processes for secure data handling. Your organization is obligated to ensure that PII and PHI data is secure and/or is properly obfuscated to safeguard the identity of the individual from anyone not directly providing services to the individual. This includes a charge to control data used in third-party vendor applications. ## Data Security is a Consumption Problem As decision makers are constantly moving between meetings, locations, and critical decisions, the mobile experience demands access to information from anywhere, at any time, and on any mobile device. Questions around data security and mobility are complex and difficult to answer. Companies can no longer keep their data locked away in data centers and control access through their intranet. The successful decision maker requires access on their mobile devices to critical business information. There are many data security considerations: who can view the data, who can access it, and how the data is handled and processed. The question is not only the security of your own data architecture, but the security of the data architecture of your partners and vendors. Laws stipulate that you must have visibility to who had access to the data, when they had access to the data, and what they did with the data. 2 ## Domo Data Security For Domo, security is the number one priority. This is completed in two ways: first, with system integrity, which protects data at rest and in-transport from compromise or inadvertent exposure. Second, with the administrative control provided to users of the Domo Business Management Platform. In order to maintain a high standard of system integrity and security. Domo undergoes several measures to be compliant with regulatory and industry security standards. In addition, Domo provides periodic risk assessments designed to identify and manage risks to Domo and Domo customers' hosted data. Various methods are part of the risk identification process, including technical assessments, threat assessments, vulnerability assessments, and attack and penetration exercises. For customers of Domo. various security-related function within the platform are available for administrators. Only those users with an Admin default security role can manage inviting new users, removing users, assigning security profiles to users, and creating user groups. Domo provides integrations to single sign-on (SSO) directory services so your IT personnel can mirror your organization's policies and compliance rules in your Domo instance. ## Domo Data Encryption Domo keeps you in control of your data and data security. Our cloud-based service provides your data consumers the access they need while giving your IT administrators the confidence that the data is secure. Domo provides tools to confidently manage your data before it leaves your data center and know that it's secure while at rest until your designated users request it. ## Data in Motion Domo Workbench provides you with the ability to connect to your on-premise data sources and encrypt specific columns that contain sensitive data while it is in your data center. Before a single byte is transferred from your secure Data Center, you can encrypt sensitive information and grant access on a per user basis. This gives you granular access to both the individual columns of protected data as well asa by-user access list. to ensure that you are in full control of both data and access. When you transfer data from your data center your data remain encrypted using AES 256 encryption. The decryption is accomplished only in your user's secure browser session when they provide a unique passcode. ## Data at Rest While your business data resides on Domo servers, the data remains encrypted, completely unusable and unidentifiable. There is only a single manner in which your encrypted business data can be decrypted. This is by using the secure browser at the request of the user you designate on the access control list managed by Workbench. At no time does anyone, inside or outside of your organization, have access to read or use your encrypted data, unless you grant them access. Screenshot 2023-07-12 at 3.43.38 PM.png ## The Domo Encryption Solution Workbench provides encryption and decryption capabilities. This section describes how to maintain secure handling of sensitive data while outside of the Data Center. There are two primary actions needed to encrypt your data in Workbench: creation and consumption. The creation of your encrypted data starts with the connection of Workbench with your data source. After your data schema has been loaded, you can select the columns that you want to encrypt. Screenshot 2023-07-12 at 3.57.11 PM.png Workbench then creates a cryptographically strong 128-byte master key. Your data is then encrypted through the master key using AES 256. Each time your job runs, the previously selected data columns are encrypted at the source with the master prior to being sent to Domo. Screenshot 2023-07-12 at 3.57.25 PM.png The administrator can then select which users have access to decrypted data in the visualization stage. The administrator provides a passcode to be shared with the selected user. The passcode is used to create the user key, which is the master key that has been encrypted using the passcode and AES 256. This capability and process of selecting employees with access is done within the Workbench platform. The consumption of encrypted data is only available to the users pre-selected in Workbench. When you selected a user and granted access, they received a passcode to decrypt the user key. The authorized user can now request visualization using the encrypted data. The visualization is presented with a lock icon where the encrypted data would normally be used. The authorized user selects the **Lock** icon and receives a prompt for the user passcode. Upon successful input of the passcode, the encrypted data is revealed in the visualization. Screenshot 2023-07-12 at 3.57.47 PM.png During this process, the level of encryption and security of sensitive data remains in the admin's control. At no point is the data decrypted on the Domo server and at no time does Domo maintain the information to decrypt the keys or data. All decryption takes place within the browser; all encryption and key management takes place in Workbench prior to upload within your Data Center. ## Conclusion Data security is the responsibility of the company that creates and captures data. The Domo Business Management Platform and its features provide you the ability to share your data with the decision makers that drive your business while continuing to maintain control of your business data. *** 1. "Target says over 70 million..."; [http://www.washingtonpost.com/business/economy/target-says-70-million-customers-were-hit-by-dec-data-breach-more-than-first-reported/2014/01/10/0ada1026-79fe-11e3-8963-b4b654bcc9b2\_story.html](http://www.washingtonpost.com/business/economy/target-says-70-million-customers-were-hit-by-dec-data-breach-more-than-first-reported/2014/01/10/0ada1026-79fe-11e3-8963-b4b654bcc9b2_story.html) "Sony Pictures: The Data Breach..."; [http://www.forbes.com/sites/davelewis/2014/12/17/sony-pictures-how-the-criminal-hackers-won/](http://www.forbes.com/sites/davelewis/2014/12/17/sony-pictures-how-the-criminal-hackers-won/) "Evernote says security has been breached"; [http://www.bbc.com/news/technology-21644317](http://www.bbc.com/news/technology-21644317) "Home Depot hackers used vendor log-on..."; [http://www.usatoday.com/story/money/business/2014/11/06/home-depot-hackers-stolen-data/18613167/](http://www.usatoday.com/story/money/business/2014/11/06/home-depot-hackers-stolen-data/18613167/) 2. Table 1. Principles used by experts in the determination of the identifiability of health information." [http://www.hhs.gov/ocr/privacy/hipaa/understanding/coveredentities/De-identification/guidance.html](http://www.hhs.gov/ocr/privacy/hipaa/understanding/coveredentities/De-identification/guidance.html) # Workbench Enterprise | Implementation Guide Source: https://www.domo.com/docs/s/article/000005303 ## Intro Workbench Enterprise is a web-based alternative to our existing on-prem Workbench solution that includes some powerful new capabilities: * **Multi-user —** Multiple users can access and manage your pool of Workbench jobs. * **Web-based —** You can use different platforms/browsers to remotely access and manage Workbench jobs even though the web server remains on-prem. * **Multi-platform —** Works on Linux, Windows, and macOS. * **High availability —** Better failover logic between jobs and the capability to split up large jobs between many different worker nodes on the server. These capabilities mean managing Workbench jobs is easier, particularly in cases where you are running an exceptionally high volume of jobs, as well as tighter security around Workbench jobs and improved reliability for more complex jobs. *** ## Prerequisites You must have the following to use Workbench Enterprise: * Docker installed on your machine * (Conditional) If you want to use an existing RabbitMQ account, provide the credentials * The Workbench Enterprise grants—see below. **Note:** If used, RabbitMQ encrypts all communication between the Control Center and the nodes. Only one RabbitMQ is required. If you have hundreds of nodes, you may consider linking multiple RabbitMQ instances to avoid overloading. ## Required Grants There are three grants required to use Workbench Enterprise: * **Login to Workbench Enterprise —** Required to log in to Workbench Enterprise. All users who want to use Workbench Enterprise must have this grant enabled for their role. * **Create Jobs in Workbench Enterprise —** Allows the creation of jobs in Workbench Enterprise. * **Manage Workbench Enterprise —** Allows a user to edit all jobs and configurations in Workbench Enterprise. ## Configure Workbench Enterprise The following sections describe the different locations and required steps to configure Workbench Enterprise. ### Domo Configuration 1. From the main nav, select **More**>**Admin**.\*\*\*\*\ The Admin Settings display. 2. Under **Authentication**, select **Workbench Enterprise**.\ The **Workbench Enterprise**page displays. 3. Enter the URL(s) for your Workbench Enterprise instance so that you can use OAuth for secure access. enter urls.jpg 4. Select **Generate Key**.\ The key displays in the **Key** field. 5. Select **Copy** to copy the key to your clipboard. copy key.jpg ### Download Docker Images Download the latest Docker images by running the following commands in a terminal window such as Windows command prompt, Mac terminal, or Linux terminal. When running Docker images on an ARM architecture, you will use the tag `arm-latest`: ``` docker pull public.ecr.aws/domo/workbench/workbenchenterprise:latest docker pull rabbitmq:management ``` ### Launch the Docker Image On your local system, create a directory to store the Workbench Enterprise configuration and long-term storage. For example, on Linux, your directory could be: /usr/share/Domo Run the following Docker commands with the new file directory inserted in the highlighted section below. When running Docker images on an ARM architecture, you will use the tag `arm-latest`: ``` docker run -p 80:8080 --mount type=bind,source=/usr/share/Domo,target=/usr/share/Domo --mount type=bind,source=/usr/share/Domo,target=/app/Data public.ecr.aws/domo/workbench/workbenchenterprise:latest ``` This can run locally on any port you choose. If you want to use a reverse proxy and access it via HTTPS, use 443:8080. See how to [configure a reverse proxy](#configure-a-reverse-proxy) below. You can also use a specific port if specified in the URL. For example, -p 1337:8080 would mean the URL would be http\://\[customdomain]:1337, where \[customdomain] is the IP or domain that you would like to access the web server. ``` docker run -d -p 5672:5672 -p 15672:15672 --mount type=bind,source=/usr/share/Domo/rabbitmq,target=/var/lib/rabbitmq/mnesia/ rabbitmq:management ``` You can now open Workbench Enterprise by navigating to http\://`<>`. ### Configure a Reverse Proxy You can use a reverse proxy together with Docker to enable browsing with HTTPS instead of HTTP with a certificate that you provide. Here is an example of a Nginx reverse proxy setup that works with Workbench Enterprise: ``` # Complete Nginx Docker reverse proxy config file events { worker_connections 4096; } http{ server { listen 80; listen [::]:80; server_name {Your-server-name}; #The IP of your Workbench Enterprise location / { proxy_set_header Host $host; proxy_set_header X-Real-IP $remote_addr; proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; proxy_set_header Upgrade $http_upgrade; proxy_set_header Connection $http_connection; proxy_pass {Your-passthrough-location}; } } } ``` ### One-Time Setup On the **One-Time Setup** page, you must enter the following information: 1. Under **RabbitMQ Setup**, enter all required credentials in the appropriate fields. * If you have an existing server you want to use, you must enter an admin credential. * If you are using the RabbitMQ Server from the Docker command posted earlier, you are setting up the admin credentials and do not need existing ones. 2. Under **Domo Setup**, enter your Domo domain. 3. Paste the key you copied to your clipboard above from the Workbench Authentication. 4. Select **Submit**.\ You are redirected to the Workbench Enterprise login page and can give Workbench Enterprise access to your Domo instance. one time setup.jpg ### Log In On the Workbench Enterprise login page, select **Login With Domo**. Login.jpg ### Configure Your First Node **Note:** Nodes currently work on Windows and Linux. This section contains instructions for configuration in each. To perform these steps, you must have administrator access to your machine. 1. As an administrator for your machine, launch your web browser and navigate to your Workbench Enterprise server. 2. Log in to Workbench Enterprise. 3. Go to **Nodes**. 4. Download the Windows package. 5. Extract the ZIP file and move the folder to a known location. 6. From the **Start** menu on your machine, launch Command Prompt as an administrator. Follow the steps below depending on your system ##### Windows 1. Navigate to the folder where you placed the ZIP file and register your Workbench node as a Windows service by entering ``` EnterpriseThinClient.exe -i ``` * A protection mechanism exists to prevent the ThinClient from being run in standalone mode when it's installed as a service. The service the ThinClient creates should be set up to launch automatically and restart on failure. * After it's installed as a service, the ThinClient must be managed through the service for all subsequent use. 2. In Workbench Enterprise, go to **Nodes** >**Untrusted**. 3. Locate the node and select **Trust**to enable Workbench Enterprise to run jobs on the node. trust node.jpg ##### Linux 1. Navigate to the folder where you placed the ZIP file and register your Workbench node as a Linux daemon by completing the following steps: * Use chmod to update the ACL on EnterpriseThinClient to allow execution. * Launch the EnterpriseThinClient -i 2. In Workbench Enterprise, go to **Nodes** > **Untrusted**. 3. Locate the node you added and select **Trust** to enable Workbench Enterprise to run jobs on the node. trust node.jpg **Nodes:** * There is no limit to the number of nodes that can be connected to Workbench Enterprise. * Jobs are not tied to specific nodes. They can be tied to "clusters," which are assigned to nodes. * The job will always execute on the first available node. If the job is assigned to a cluster, it will execute on the first node available in that cluster. If a node goes down, the job will execute on the next available node. * There is no Workbench Enterprise master node. All nodes are treated the same way. ### Configure Your First Shared Credential To perform these steps, you must be logged in to Workbench Enterprise as an administrator. 1. Inside Workbench Enterprise, go to **Admin** > **Shared Credentials**. 2. Select **New Shared Credentials** > **Database** to open the creation modal. new database credentials.jpg 3. Enter the values for the shared credential in the **Database** modal. database NEW.jpg 4. Select **Save Credentials**. ### Configure Your First Job 1. Inside Workbench Enterprise, select **Jobs** in the left navigation. 2. Select **New Job**. 3. Enter a name for your job and select **Submit**. 4. In the jobs list, locate and select your job. 5. In the job details view, go to the **Configure** tab. 6. Under **Data**, change the Connection Type to Connection String Builder. 7. Select **Use a database shared credential**. 8. Select the shared credential you configured earlier. 9. Enter the query for your job. 10. Select **Save**. 11. Select **Preview**. ### Import a Job to Workbench Enterprise Follow these steps to import Workbench jobs into Workbench Enterprise: 1. In your previous Workbench installation, create a backup file that contains your job. 2. In Workbench Enterprise, go to workbench admin option.jpg **Admin** > **Workbench Import**. workbench import.jpg 3. Drop your Workbench backup file in the designated space. 4. Under **Backup file password**, enter the password for your backup file and select **Load Jobs**. 5. Select the jobs you want to import from the list and assign them a cluster. 6. When you are ready, select **Import**. ### Run Your First Job After following the steps to [configure your first job](#configure-your-first-job), do the following: 1. Inside Workbench Enterprise, select **Jobs** in the left navigation. 2. In the jobs list, locate the job you want to run. 3. Select **More** > **Execute**. ## Share Credentials Workbench Enterprise admins can share credentials. In the left navigation, go to **Admin** > **Shared Credentials**. ## Use File Watch You can use File Watch if the plugin you are using supports it. Follow these steps to configure File Watch: 1. Find and select your job in the jobs list. job.jpg 2. In the **Schedule** tab of the job details, check the box labeled **Watch for changes** in the **Basic Schedule** OR **Advanced Schedule** tab. watch for changes.jpg WBE will begin monitoring changes to your source. In the example below, WBE will watch for changes in File2.csv. If the file changes, the job will execute. Screenshot 2024-10-08 at 2.59.51 PM.jpg **Tip:** Learn how to [launch Workbench Enterprise jobs with third-party tools](/docs/s/article/000005587). ## FAQ JDBC is specific to Java-based technologies. Workbench Enterprise is not Java-based, so it can't connect to JDBC drivers. Generally, if a JDBC driver exists, an ODBC driver also exists. Yes, this is supported. ## Upgrading & Plug-Ins The Control Center needs to be updated manually because it is a docker container. The nodes, by default, update automatically to be on the same version as the Control Center. This can be disabled on a per-node basis so that they can be manually updated within the Control Center. No, plug-ins built for Workbench are specific to Workbench, and the same is true for Workbench Enterprise. Currently, every plug-in works in every environment as long as the environment supports it and is properly configured. ODBC is harder to configure on Linux. # PostgreSQL Connector Source: https://www.domo.com/docs/s/article/000005521 ## Intro PostgreSQL is a widely used open-source relational database management system. You can use Domo's PostgreSQL Connector to pull data from your PostgreSQL database and compile custom reports. To learn more about the PostgreSQL API, see ([https://www.postgresql.org/about/news/postgresql-restful-api-1616/](https://www.postgresql.org/about/news/postgresql-restful-api-1616/ "https://www.postgresql.org/about/news/postgresql-restful-api-1616/") ). You can connect to your PostgreSQL account in the Data Center. This topic discusses the fields and menus that are specific to the PostgreSQL connector user interface. To add DataSets, set update schedules, and edit DataSet information, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Prerequisites To connect to your PostgreSQL account and create a DataSet, you must have the following: * Username * Password * Host * Port * Select a Certificate Type. The certificate type must match what you enter in the **Certificate** field. If you are unaware of a special certificate, then you can select **No Certificate** from the drop-down list. * Database ## Connecting to Your PostgreSQL Account This section enumerates the options in the **Credentials** and **Details** panes on the PostgreSQL Connector page. The components of the other panes on this page, **Scheduling**, and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in great detail in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ## Credentials Pane This pane contains fields for entering credentials to connect to your PostgreSQL account. The following table describes what is needed for each field:

Field

Description

Username

Enter your PostgreSQL username. If you don't know your username, contact your PostgreSQL Database Administrator for help.

Password

Enter your PostgreSQL password. If you don't know your password, contact your PostgreSQL Database Administrator for help.

Host

Enter the host name for the SQL database. If you don't know the host name, contact your PostgreSQL Database Administrator for help.

Port

Enter the port number for the SQL database. If you don't know the port number, contact your PostgreSQL Database Administrator for help.

Certificate

Paste the text for your CA certificate or enter the URL where your certificate is located. By default no certificate is required.

Certificate Type

Select a certificate type. This must match what you enter in the Certificate field. If you are not sure of a special certificate, select No certificate from the drop-down list.

Database

Enter the name of the SQL database. If you don't know the database name, contact your SQL Database Administrator.

Once you have entered valid PostgreSQL credentials, you can use the same account any time to create a new PostgreSQL DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Manage Connector Accounts](https://domo-support.domo.com/s/article/360042926054?language=en_US "Manage Connector Accounts"). ## Details Pane
Menu Description
Query Helper Edit this query if desired.
Database Tables Select the database table that you want to view in your report.
Table Columns Select all the table columns you want to view in your report.
Query Helper Edit this query if desired.
Incremental Pull Select either Last Value or Max Value , or None from the drop-down list.
## Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). # Set Up Domo on Oracle Cloud Source: https://www.domo.com/docs/s/article/000005586 ## Intro You can connect your data from Oracle Cloud to Domo using native Cloud Integrations. Provide connection parameters and select the tables you want to see as Domo DataSets. Follow the steps in this article to configure your Oracle-Domo read and write connections with [Cloud Integrations](/docs/s/article/4412849158167). *** ## Architectural Overview The diagram below shows how Domo connects to Oracle through Cloud Integrations. Domo queries data live from your Oracle Cloud environment; no data is copied to Domo storage. Oracle architecture diagram.png ## Start and Manage Your Oracle Integrations To access the integration management interface, please follow these steps: 1. Navigate to the **Data** tab located at the top of the Domo platform. 2. Elect **Connect Data**. 3. Choose **Oracle Cloud** from the list of Cloud Integrations. Screenshot The Domo on Oracle appears. 4. Select **Connect** **Oracle Cloud** to initiate the process of creating a new integration or **Manage Integrations** to modify existing integrations.\ Available integrations display.\ To set up your integration, see [Create Your Oracle Integration](#create-your-oracle-integration). Screenshot 5. Select the **wrench icon** on your integration to access additional integration options, such as edit, select tables to connect, enable write access, and delete. Screenshot **Note:** You may see different options based on your access level. ## Create Your Oracle Integration **Important:** To create an Oracle integration, you must have an account with either NetSuite Analytics Warehouse or Oracle Autonomous Data Warehouse. **Note:** This Oracle integration setup enables Domo to read data from Oracle. You must determine which Oracle tables are connected and configure access and privileges to the integration. After you have [started your Oracle integration](#start-and-manage-your-oracle-integrations), follow these steps to get more value from your data: 1. Name your Oracle integration.\ This name helps you identify an Oracle integration within Domo and doesn't need to match any names already set in Oracle or Netsuite. You can change the name of your integration at any time. Screenshot **Tip:** Use specific naming to create more than one Oracle integration within a single Domo instance so you can connect different tables or better manage access. 2. Describe your Oracle integration.\ Adding a description to your Oracle integration helps other users understand why you created it and how it is used. **Note:** To view the description, you must inspect the details of the Oracle integration itself. 3. Select your Oracle service account within Domo or select **Add account** to create a new one. **Important:** Although the Oracle service account can be changed later, you must take care when switching the associated service account, as there is potential for DataSet and ETL remapping and Domo user access interference. **Important:** Three levels of Oracle-Domo architecture exist. This means that a many-to-one relationship can exist between Oracle service accounts, as defined by Domo and the Oracle instance, and multiple Oracle integrations can also make use of a single service account. The three levels of Oracle-Domo architecture are: * **Oracle instances**, which exist independently of Domo. * **Oracle service accounts**, which connect to the Oracle instance from inside Domo. * **Oracle integrations**, which use the service account inside Domo and add a layer of settings that specify connections between Oracle tables and Domo DataSets, define caching behavior, and determine write-back enablement. **Best Practices:** You can create multiple service accounts in Domo referencing the same Oracle instance to delineate functional differences. * **Example A:** You want to manage user access to two Oracle integrations separately. * **Example B:** You want to configure separate settings for caching TTL while preserving a shared definition for Domo user access. ## Configure Writeback Support for Oracle Cloud You can configure a Cloud Integration to write outputs from Domo into Oracle tables. Follow these instructions to add writeback capabilities to a read-only Oracle integration: 1. Navigate to the Domo Data Center. 2. (Conditional) If you're not already there, use the sidebar to go to the data warehouse.jpg **Data Warehouse**(cube icon). 3. Select **Manage Cloud Connections.** **Screenshot 2024-10-09 at 8.49.26 AM.png** 4. In the **Native Integration**section, select **See More**to see the rest of the options. see more.jpg 5. Select **Oracle** to view your existing Oracle Cloud Integrations. **Screenshot 2024-10-09 at 8.04.46 AM.png** 6. Hover over an existing integration with read-only permissions and select Screenshot 2024-10-09 at 8.57.50 AM.png (wrench icon) > **Configure write access**.If you do not have any existing integrations, follow the read-only integration steps. Screenshot 2024-10-09 at 8.57.32 AM.png 7. Enter your credential name you want to create on Oracle for the integration and select **Generate SQL**. 8. Follow the instructions; there are two sets of statements that need to be executed in Oracle: * Those with an ACCOUNTADMIN role have to execute the first set of instructions to grant the credentials in the Oracle instance. * The account user (configured when you set up your read integration) must execute the second set of instructions to create the write credentials. Screenshot 9. After successfully executing both sets of instructions in your Oracle instance, copy the ID and ARN values and select **Next.** 2.png 10. In the next step, confirm that you understand that Domo can make changes to your Oracle environment and select \*\*Next.\*\*A message confirming that your write integration was successfully configured displays. # Launch Workbench Enterprise Jobs with Third-Party Tools Using JWT Source: https://www.domo.com/docs/s/article/000005587 ## Intro Workbench Enterprise allows third-party applications to launch jobs and to get the status of a job execution. JSON web tokens (JWTs) have a limited scope. A token can only do the following: * Get the job execution status * Start an execution for a single job—to execute another job, you must generate a new JWT **Tip:** Learn how to [implement Workbench Enterprise](/docs/s/article/000005303). ## Generate a JWT 1. Find and select your job in the jobs list. job.jpg 2. Go to the **External Access** tab and select **Create New JWT**. external access.jpg 3. Copy the JWT and save it in a secure location. The JWT will never display again after you close the modal. jwt blurred.jpg ## Launch a Workbench Enterprise Job Launch a Workbench Enterprise job with a PUT request to the job execution endpoint. **Note:** In the examples below, the JWT is stored in a variable named `JWT.` Curl: ```bash theme={"dark"} curl -X PUT --header "Authorization: $JWT" -v https://WorkbenchEnterprise.internal.com/Api/Jobs/{jobId}/Execute ``` Powershell: ```powershell theme={"dark"} Invoke-Webrequest -uri https://WorkbenchEnterprise.internal.com/Api/Jobs/ {jobId} /Execute -Method PUT -Headers @{'Authorization' = $JWT} ``` ## Get the Job Execution Status Workbench Enterprise can return the job status using a GET request to the job execution endpoint. **Note:** In the examples below, the JWT is stored in a variable named `JWT.` Curl: ```bash theme={"dark"} curl -X GET --header "Authorization: $JWT" -v https://WorkbenchEnterprise.internal.com/Api/Jobs/ {jobId} /Execute ``` Powershell: ```powershell theme={"dark"} Invoke-Webrequest -uri https://WorkbenchEnterprise.internal.com/Api/Jobs/ {jobId} /Execute -Method GET -Headers @{'Authorization' = $JWT} ``` The response body will have these elements: Screenshot 2024-10-08 at 3.51.42 PM.png ## Invalidate a JWT If you want to invalidate an existing token, select **Invalidate** for the token in the job's **External Access** tab. invalidate blur.jpg # Domo on PostgreSQL Source: https://www.domo.com/docs/s/article/000005756 ## Intro This article explains how to connect Domo's Cloud Integrations to PostgreSQL, allowing you to query and visualize PostgreSQL data directly in Domo without moving or duplicating data. *** ## Prerequisites You must have an account with access to PostgreSQL to move forward. ## Create or Manage Your PostgreSQL Integrations To access the integration management interface, follow these steps: 1. Navigate to **Data Warehouse**. 2. Select **Connect Data**. 3. From the list of Cloud Integrations, choose **PostgreSQL**.\ The **Domo on PostgreSQL** page appears. 4. Select **Connect PostgreSQL** to start creating a new integration (see the [integration setup instructions](#create-a-postgresql-integration-in-domo)). 5. Select **Manage Integrations** to modify existing integrations.\ A list of available integrations displays. 6. Select the wrench icon next to an integration to view available options.\ The options shown depend on your access level. Screenshot ## Create a PostgreSQL Integration in Domo Every PostgreSQL integration in Domo requires an authenticated service account. Once created, a single service account can be reused across multiple integrations. Follow these steps to create a PostgreSQL Integration in Domo. 1. Provide a name for the integration. This is simply a label to help you identify the integration within Domo. It does not need to match any names in PostgreSQL and can be changed later if needed. **Tip:** Multiple PostgreSQL integrations can exist in the same Domo instance, created by you or your colleagues. Clear naming helps users select the correct integration later. For example, separate integrations might be created to connect different tables or manage access levels. 2\. Add a description to explain the purpose of this integration and who created it. Most users will only see the integration name in menus and lists. The description is visible only when viewing integration details. 3\. Select an existing PostgreSQL service account from the drop-down menu or select **Add account** to create a new one.\ You can change the service account later, but switching accounts may require remapping DataSets and ETLs if the new account lacks access to previously used tables. User access may also be affected unless privileges are identical. 4\. Enter the name of the Database that contains your PostgreSQL tables. **Understand the Architecture** There are three levels in this setup: * PostgreSQL instance – Exists independently of Domo. * PostgreSQL service account – Defined in Domo and connects to the PostgreSQL instance. * PostgreSQL integration – Uses the service account and adds settings such as connected tables and caching behavior. **Note:** Multiple service accounts can connect to the same PostgreSQL instance. Multiple integrations can share a single service account. **Access and Sharing** * Initially, only the owner of the service account has access. * The owner can share access with individuals or groups. * If multiple integrations use the same service account, they inherit the same user privileges. * Changes to privileges affect all integrations tied to that account. To review access settings, go to the Accounts Page and select Account sharing next to the relevant PostgreSQL service account. **Tip:** You can create multiple service accounts for the same PostgreSQL instance.\ Reasons for doing this include:\ Example A: Managing user access separately for different integrations.\ Example B: Applying different caching TTL settings while sharing user access. Screenshot ## Create a PostgreSQL Service Account in Domo Every PostgreSQL integration in Domo relies on an authenticated PostgreSQL service account. Once created, this account can be reused across multiple PostgreSQL integrations. Domo provides a dedicated Accounts Page where you can create and manage service accounts for various external services, including PostgreSQL. After creation, your PostgreSQL service account will appear on this page. **Important:** Creating a PostgreSQL service account in Domo allows you, other account owners, Domo admins, and anyone with whom the account is shared, to use its credentials to access PostgreSQL and create connected DataSets in Domo. Users will not have access to sensitive values such as passwords, tokens, or keys used by the service account to connect to PostgreSQL. Follow these steps to create a PostgreSQL service account in Domo. 1. Choose a name to identify this PostgreSQL service account within Domo. * The name can be changed later * Use clear, distinctive names to avoid confusion between PostgreSQL accounts and integrations * You can create multiple service accounts, even if they all point to the same PostgreSQL instance 2. Enter the name of your server or its IP address. 3. Enter the port that your PostgreSQL instance is using for incoming connections. 4. Enter your PostgreSQL Username. 5. Enter your PostgreSQL Password. Screenshot # Connecting to SAP HANA Data in Workbench 5 Source: https://www.domo.com/docs/s/article/1500000285042 ## Intro The Domo SAP HANA Plugin allows you to create jobs in Workbench 5 to get the Data from your SAP HANA database in Domo. The SAP HANA plugin uses SAP HANA ODBC driver for connecting to your database. Thus, you will need to install the SAP HANA ODBC driver for using this plugin. The SAP HANA plugin also supports end-to-end trace. For more info please see End-to-end tracing section. This tutorial teaches you how to use the Domo SAP HANA ODBC Plugin to connect to your SAP HANA data. ## Prerequisites * Windows 10 64-bit operating system * Domo Workbench * SAP HANA ODBC Driver * SAP HANA Plugin ## Installing the SAP HANA ODBC Driver You can download the SAP HANA ODBC driver from SAP Support Package Stack. 1. Launch hdbsetup.exe in HDB\_CLIENT\_WINDOWS\_X86\_64. The **Install new SAP HANA Database Client** option is automatically selected. clipboard_e52f242b7f83114904a870a4ceb08ca85.png 2. Click **Install** and wait for the installation to finish. clipboard_e43201196b8dddebc921ba9e81e9ed7ae.png 3. Click **Finish**. ## Installing the SAP HANA Data Provider Plugin in Domo Workbench All Workbench plugins are contained within Dynamic Link Libraries (DLLs). You can add plugins to Workbench by selecting the desired DLL on your machine or network. ### Adding SAP HANA plugin to Workbench **Note:** Your SAP HANA plugin must be located in a subdirectory of the chosen directory. 1. Click in the left-hand icon bar. 2. Click **Plugins** in the **More** pane. (If you do not see this pane, click to expand it.) The **Plugin Manager** opens. 3. Under **Register new plugins** click the ellipsis (**...**) next to the **Search path** field. clipboard_e4efaf33bb01785ea914d5012fba1ea4e.png 4. On your machine or network, locate and open the folder that contains a folder with all DLLs of SAP HANA Plugin. 5. Click **Add** after you have chosen your directory. ## Connecting to the SAP HANA Data ### Creating a SAP HANA DataSet job in Workbench 5 1. Click the icon in the left-hand icon bar. 2. Click the **+** button in the top right corner of the jobs listing pane. 3. Select the desired account (Domo instance) in the **Domo Domain** dropdown menu. If you have only one account set up, that account is already chosen for you and the menu is unavailable. 4. In the **Name** field, enter a name for the DataSet Job. This is the name of the job as it appears in Workbench, *not* the name of the uploaded DataSet in Domo. 5. In the **Transport Type** menu, select **SAP HANA Data Provider**. 6. In the **Reader Type** menu, select **Database Query**. 7. In the **DataSet Name** field, enter the name of the DataSet. This is the name of the uploaded DataSet in Domo. This is the *only* setting you can change after saving the new job. 8. In the **DataSet Type** field, select the type of DataSet in the dropdown. The DataSet type you select or enter here is reflected as the connector type in Domo after you execute the job. 9. Enter a description for the DataSet if desired. This is the description of the DataSet as it appears in Domo. 10. Click **Create**. A new SAP HANA DataSet Job is added to the list of jobs for the currently authenticated account. Note that after creating the job, you cannot edit any of the settings you just configured except for the DataSet name. If you want to change any of the other settings, you must create a new job. 11. Click the **Configure** subtab. 12. Click the **Edit** button under "Source." A panel opens with options for configuring your SAP HANA connection and defining your query. 13. In the **Connection Type** field, select a connection option. The following table describes the available options:
Option Description
System DSN Select your SAP HANA DSN.
Connection Builder Enter details for your SAP HANA connection, such as login credentials, server URL, database name, and port.
Connection String Enter a single string for your connection.
14. (Conditional) Do one of the following: * If you selected **System DSN** as your **Connection Type**... 1. In the **System DSN** menu, select the desired system DSN from those available in your system. Please note that only the DSNs created for SAP HANA ODBC driver will be listed in the options. 2. (Conditional) If this DSN connection requires credentials to connect, set **Required Credentials** to **On**, then enter your username and password in the appropriate fields. Otherwise set **Required Credentials** to **Off**. * If you selected **Connection Builder** as your **Connection Type**... 1. Enter the appropriate information in the fields. Some parameters may or may not be required, depending on your connection. You can use the following table for reference:
Field Description
Server Specify the server name or URL for your database.
Database Specify the name of your database to access.
Port Enter the port number where your database is found. The default port in the SAP HANA plugin is 30015
Username Specify the username you use to connect to your database.
Password Specify the password you use to connect to your database.
Requires 32-bit Execution Select this check box if you want to use 32-bit SAP HANA Driver for connection. Please note that you will need a 32-bit SAP HANA Driver already installed on the system.
* If you selected **Connection String** as your **Connection Type...** 1. Enter a connection string to connect to the data source. 2. Select this check box **Requires 32-bit Execution** if you want to use the 32-bit SAP HANA Driver. 15. Click **Apply**. ## End-to-end tracing The SAP HANA plugin support end-to-end trace functionality of SAP HANA database. Every connection made using the plugin with the SAP HANA Database has 2 session variables: APPLICATION and APPLICATIONUSER. By default, SAP HANA plugin sets the **APPLICATION** session variable as **DOMO** and **APPLICATIONUSER** session variable as- a. **Windows user**, if the workbench Job is set to use impersonation b. **Domo user** otherwise If you want to explicitly specify the values for the session variables (APPLICATION and APPLICATIONUSER session variables), you can use any of the following approaches: * ### Adding the session variables to the connection string You can select the connection type as Connection String, and add the required session variables to the connection string. More information on setting a session variable in HANA connection strings can be found at the SAP Help Portal as [Setting Session-Specific Client Information](https://help.sap.com/viewer/0eec0d68141541d1b07893a39944924e/2.0.04/en-US/e90fa1f0e06e4840aa3ee2278afae16b.html). Example connection string: DSN=HANADataSource;UID=myUser;PWD=myPassword;sessionVariable:APPLICATION=myapp;sessionVariable:APPLICATIONUSER=user1 * ### Setting up the DSNs with the session variable DOMO Workbench relies on an ODBC Data Source Name (DSN) when connecting to a database. The data source is defined by the end user in the ODBC Administrator, which in turn calls the SAP HANA ODBC driver. 1. From your Windows 10 desktop, click the **Start** Button and search for ODBC Data Sources. Click ODBC Data Sources (64-bit). **Note:** An ODBC Data Source is NOT the same thing as a Domo DataSet. 2. From the **ODBC Source Administrator** window, select **HANA Service** and click **Add….** clipboard_ec65dd5c45eb58621e40f2fa69002dda3.png 3. Select the SAP HANA ODBC driver **(HDODBC)** and click **Finish**. clipboard_e8c62705a464c3bad59f705c39136ad91.png 4. Enter a name for the data source, host IP, instance number or port number for your SAP HANA database. clipboard_e143f0b24469f94e0e03e55ee383d2922.png 5. Click the **Test Connection** button to check if the configurations are correct. You will see a success message as below if the DSN is configured correctly. clipboard_ece3c74911b01da5bfab2af08502a2cae.png 6. Once it is configured, Click on **Advanced**. 7. Click **Add**. 8. In the **Add/Modify Connection** window, enter the **SessionVariable:APPLICATION** connection property. **Note:** SessionVariable is case insensitive. clipboard_ea56a76340c29b89d55907e6734e8820e.png 9. Similarly, add **SessionVariable:APPLICATIONUSER** connection property. **Note:** The APPLICATIONUSER can be the Domo user you are logged in as. It is not necessary to be the database user. 10. Your session variables will appear like this. clipboard_e19747a8ad88f3a58d97d3f5467219f15.png # MySQL SSH Writeback Connector Source: https://www.domo.com/docs/s/article/1500000974662 ## Intro MySQL is an open-source relational database management system. The MySQL SSH Writeback connector supports a secure connection to export your data from a Domo DataSet to the provided MySQL database. You export data to a MySQL database in the Data Center. You configure your Domo-MySQL connection in the Data Center. This topic discusses the fields and menus that are specific to the MySQL SSH Writeback Connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). **Note:** The owner of a writeback dataset must also be an owner or co-owner of the input dataset. ## Prerequisites To configure this connector, you must have the following: * The hostname of the server you are SSH-tunneling through * Your SSH server port number, username, password, private key, and private key passphrase * The hostname or IP address of your database server * Your MySQL port number, username, password, and database name **Note: Domo does not support the SSH keys generated using ssh-keygen. The SSH keys need to be the DES or RSA keys generated by OpenSSL.** **Important**: You will need the following permissions on MySQL: * FILE * CREATE * DROP * INSERT * SELECT * UPDATE ## Configuring the Connection This section enumerates the options in the **Credentials** and **Details** panes in the MySQL SSH Writeback Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most Connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ### Credentials Pane This pane contains fields for entering credentials to connect to your MySQL account where you want your data to be copied to. The following table describes what is needed for each field:

Field

Description

SSH Server Host Name Enter your SSH server host name.
SSH Port Number Enter your SSH server port number.
SSH Username Enter your SSH sever username.
SSH Password Enter your SSH server password.
SSH Private Key Enter the SSH private key in PEM format (either DES or RSA).
SSH Private Key Passphrase Enter your SSH server private key passphrase.
MySQL JDBC Driver Select the MySQL JDBC driver to use.
Host Enter your hostname or IP address of your database server.
Port Enter your MySQL port number.
Username Enter your MySQL username.
Password Enter your MySQL password.
Database Enter your MySQL database name.
Once you have entered valid credentials, you can use the same account any time you go to set up a new Domo-MySQL connection. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane This pane contains a number of fields for specifying your data and indicating where it's going.

Menu

Description

DataSet ID

Enter your Domo dataset ID(GUID) located in the dataset URL.

For example, in the URL [https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview\{](https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview\{)" "} , the DataSet ID is 845305d8-da3d-4107-a9d6-13ef3f86d4a4.

How would you like to select your table? Specify whether you would like to create a new table or select an existing table to export your DataSet data to.
Table Name

Select whether you would like to use the dataset ID or a custom name for the table name.

Custom Table Name Enter the name for the SQL table to write the dataset data to.
Delete existing table and create a new table with the same name

Select this checkbox if you want Domo to delete the existing table and create a new one with the same name.

WARNING : This deletes the existing table and the data cannot be recovered once deleted.

Existing Table Select the table to write the dataset data to.
Update Operation Type

Select whether you want to append data, overwrite new data, or upsert data while updating it.

Use Column Mapping Select the checkbox if you wish to provide Dataset Column Name and Table Column Name mapping. If this option is selected, only those columns that are provided in the Text Areas will be updated/inserted.
Dataset Column Names Enter the comma separated list of Dataset Column Names.
Table Column Names Enter the comma separated list of Table Column Names. Table Column Names should correspond to the Dataset Column Names in the same sequence. The Number of Dataset Column Names should be equal to Table Column Names for proper mapping.
Primary Column Select the column name that should be primary key column.
### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQs You need the following: * The hostname of the server you are SSH-tunneling through * Your SSH server port number, username, password, private key, and private key passphrase * The hostname or IP address of your database server * Your MySQL port number, username, password, and database name * You also need to s elect the MySQL JDBC driver to use No Your Domo input dataset id is in the URL of the dataset you are exporting data from. For example: `https://customer.domo.com/datasources/aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee/details/settings` ## Troubleshooting * Make sure your authentication remains valid. * Review the configuration to make sure that all required items have been selected. * Review the Connector history for error messages. * In rare cases, you may be requesting too much information and reaching API limitations or timeouts. If this is the case, you can review the history of the Connector run to see the error message and duration. If this is the case, you can reduce the number of accounts that are being pulled, choose a smaller number of metrics for the report that you are pulling, or reduce the timeframe that you are trying to pull. # On-Premise SharePoint Data Provider Plugin Source: https://www.domo.com/docs/s/article/1500008535702 ## Intro The Domo SharePoint Plugin allows you to create jobs in Workbench 5 to get the data from SharePoint into Domo. Domo Workbench provides a secure, client-side solution for uploading your on-premise data to Domo. The Domo SharePoint Data Provider links Domo Workbench to operational SharePoint data. You can build datasets from SharePoint data in Workbench and then create real-time visualizations of SharePoint data in the Domo service. This tutorial teaches you how to use the Domo SharePoint Plugin to connect to your SharePoint data. #### Getting Started * Windows 10 64-bit operating system * Domo Workbench * SharePoint plugin: [https://app.domo.com/workbench/plugins/stable/DomoSharePointDataProvider.dwp](https://app.domo.com/workbench/plugins/stable/DomoSharePointDataProvider.dwp) ## Install the SharePoint Plugin in Domo Workbench All Workbench plugins are contained within Dynamic Link Libraries (DLLs). You can add plugins to Workbench by selecting the desired DLL on your machine or network. #### Add SharePoint Plugin to Workbench: **Note:** Your SharePoint Plugin must be located in a subdirectory of the chosen directory. 1. In Domo Workbench, Click in the left-hand icon bar. 2. Click **Plugins** in the **More** pane. (If you do not see this pane, click to expand it.) The **Plugin Manager** opens. 3. Under **Register new plugins** click the ellipsis (**...**) next to the **Search path** field. 3.png 4. On your machine or network, locate and open the folder that contains a folder with all DLLs of SharePoint Plugin. 5. Click **Add** after you have chosen your DLL. # Connect to the SharePoint Data #### Create a SharePoint DataSet Job in Workbench 5 1. Click the icon in the left-hand icon bar. 2. Click the **+** button in the top right corner of the jobs listing pane. 3. An **Overview** tab for a new job will appear. 4. Enter the following details in **Job Details** section.
Field Description
Domo Domain

Select the desired account (Domo instance) in the Domo Domain dropdown menu.

If you have only one account set up, that account is already chosen for you and the menu is unavailable.

Job Name

Enter a name for the DataSet Job.

This is the job name that appears in Workbench, not the name of the uploaded DataSet in Domo.

Transport Type Select Domo SharePoint Data Provider .
Reader Type Select the file type that you want to read from SharePoint in Workbench.
5.png 5. In the **Domo Details** section, provide the information for your DataSet.
Field Description
DataSet Name Enter the name of the DataSet. This is the name of the uploaded DataSet in Domo.
DataSet Type Select the type of DataSet from the dropdown. The DataSet type you select or enter here is reflected as the Connector type in Domo after you execute the job.
DataSet Description

Enter a description for the DataSet, if desired.

This is the description of the DataSet as it appears in Domo.

6. Click **Create**. A new SharePoint DataSet Job is created and added to the list of jobs for the currently authenticated account. **Note:** After creating a job, you cannot edit any of the settings you just configured except for the DataSet name. If you want to change any of the other settings, you must create another new job. #### Configure Your Job Once a job is created, you need to provide the configuration details for the job. #### Configure the Source 1. Provide the details for the SharePoint data in the **Source** menu. 2. Click **Edit**. 3. A **Domo SharePoint Data Provider Editor** window will appear. Here, you need to provide the Credentials and Report details required to connect to your SharePoint data.

Field

Description
Connection Type Select the connection type as SharePoint On-Premise .
SharePoint URL Enter URL for the SharePoint site.
Username Enter your SharePoint username.
Password Enter your SharePoint password.
Domain

Enter your SharePoint Windows domain name.

Example: If your SharePoint site was located at [https://sample.sharepoint.com](https://sample.sharepoint.com) , your domain name would be “sample”.

Report Select the report from the dropdown.
Server Relative URL Enter the name of the data file you want to connect with this DataSet in SharePoint.
4. Click **Apply**. 6.png #### Configure Data Processing 1. Provide the details about data processing for the SharePoint data in the **Processing** menu. 2. Click **Edit**. 3. An **Editor** window will appear for the selected Reader type. Here, you can provide the properties and details for your data to define how your data will be handled in the DataSet. 4. Click **Apply**. #### Configure Data Update Method 1. Select **Replace** if you want newly uploaded data to replace the existing data in the DataSet. 2. Select **Append** if you want the newly added data to be appended (added) to the existing data 3. Select **Partition** if you want to apply partitioning on your data. Partitioning uses a grain (like day or week) to create groups in your data. Data can then be processed as a group, and added or replaced as it changes. 4. Select the **Partition column** and **Date grain** in the respective drop downs for your data. #### Applying Transforms to Your Data Transforms modify your data locally before uploading it to Domo. They are faster, and process on your computer or server without a queue. Choose from a variety of options to transform your data so it's ready when it hits Domo. 1. Select the desired transform from the drop down and click the **+** button next to it. 2. Mention the transform properties for the selected transform and click **Apply**. 3. You can add multiple transforms to your data. 4. Click to update the transform properties for a specific transform. 5. Click to remove a specific transform. 6. Click the (up and down arrows) to interchange the positions of the transforms. #### Impersonate Your Job Use of impersonation allows the Domo Workbench to run your job as a specific Active Directory user. **Note:** The user profile in job impersonation needs to be a role that has access to the source data needed to run the job. 1. Select the **Requires impersonations** check box. 2. Your Active Directory domain name and username will appear. 3. Enter your Active Directory password and click **Validate**. #### Additional Settings for Your Job Set the advanced options for how your job uploads data in Domo in the **Additional Settings**. You can specify the Error handling method, and the job run duration and conditions here. #### Schedule Your Job You can schedule a DataSet job to routinely upload data from external DataSets to Domo. You mention this frequency in the Schedule tab. ##### Basic Schedule The **Basic Schedule** section allows you to update the data manually, update when file is changed, or update on a schedule. If you chose to update on a schedule, you can select the time interval and a specific time window to run the job. ##### Advanced Schedule In the **Advanced Scheduling** section, you can opt to run the job once a day, more than once a day, every day, specific days of the week/month, every month, or specific months. Click the (**Save**) button to save your changes. #### Schema Protection for Your Job Domo Workbench 5 offers three different schema protection types. You can control the schema changes by allowing the schema changes safely or permitting the unprotected schema changes, or completely blocking all schema changes. Domo Workbench supports a Protect feature that enables you to control these schema changes in a way. It is available for the “Allow safe schema changes” and “Allow unprotected schema changes” views. ##### Protect Column The Protect column indicates whether your column (data field) is protected while you apply the schema changes to your job. * If the **Protect** checkbox is selected for a column, it means that column is protected, and no schema changes can be made. If you try to remove the protection for any column (by unchecking it) while allowing either the safe schema changes or unprotected schema changes, the Domo Workbench will give you the following warning: **Warning:** Unprotected columns can be changed and deleted, which may break content in Domo. 11.png * The Protect column provides you a control to protect or unprotect all columns with a single click. Select the checkbox next to the column header (Protect) to protect all your columns at once. Similarly, you can unprotect your columns at the same time by deselecting this checkbox. * The column header also provides the control to get a filtered view of protected, unprotected, or both type of entries with a single click. * When you click to select the regular select view , the Protect column will display all protected entries. * When you click to select the unchecked view , the Protect column will display the unprotected entries. * When you click to select the mixed view , the Protect column displays both protected and unprotected entries together. * You cannot change the name of a protected source column. Domo Workbench does not allow the edit operation on a protected source column name. However, you can change the names or properties for other columns. 17.png * Similarly, you cannot delete a protected column. * If you want to allow the schema change, uncheck the column and re-run the job. #### Allow Safe Schema Changes If you select this option, the unprotected columns will accept the changes during the next execution, and will automatically be protected after. New columns will be added, and will automatically be protected in future runs. The **Allow safe schema changes** option is the default setting for new jobs. #### Allow Unprotected Schema Changes If you choose to allow unprotected schema changes, you will be able to change and delete the unprotected columns, and they will remain unprotected. #### Block All Schema Changes If you choose to block all schema changes, you will not see the Protect option for your columns. If you attempt to make changes to any column and run the job, you will receive an error stating about your forceful change. #### Set Notifications for Your Job You can set notify other users upon your job success or failure by simply selecting the respective checkbox in front of their names under the respective columns. 1. Once you are done with the job specifications, click the (**Save**) button to save your changes. 2. Click the (**Execute**) button to run your job. # Oracle Sales Cloud Connector Source: https://www.domo.com/docs/s/article/1500011014942 ## Intro Oracle Sales Cloud is a customer relationship management solution that offers capabilities and features enabling companies to significantly grow through accelerated sales, improved customer engagement, and more. It enables modern selling with tools that are easy to deploy and use, completely mobile, packed with powerful analytics, and built for collaborative selling and revenue generation.Use this connector to get data about your opportunities like- your team's opportunities, territories opportunities, subordinate opportunities, and so on. You connect to your Oracle Sales Cloud account in the Data Center. This topic discusses the fields and menus that are specific to the Oracle Sales Cloud connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Prerequisites To connect to your Oracle Sales Cloud account and create a DataSet, you must have the following: * Your Oracle Sales Cloud username and password * Your Oracle Sales Cloud REST Server URL. It's the URL of your Oracle Cloud service. Example: [https://servername.fa.us2.oraclecloud.com](https://servername.fa.us2.oraclecloud.com) ## Connecting to Your Oracle Sales Cloud Account This section enumerates the options in the Credentials and Details panes in the Oracle Sales Cloud Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ### Credentials Pane This pane contains fields for entering credentials to connect to your Oracle Sales Cloud account. The following table describes what is needed for each field:

Field

Description

Username Enter your Oracle Sales Cloud username.
Password Enter your Oracle Sales Cloud password.
API URL Enter your Oracle Sales Cloud REST Server URL. It's the URL of your Oracle Cloud service. Example: [https://servername.fa.us2.oraclecloud.com](https://servername.fa.us2.oraclecloud.com)
Once you have entered valid Oracle Sales Cloud credentials, you can use the same account any time you go to create a new Oracle Sales Cloud DataSet. You can manage Connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054). ### Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

Report

Select the Oracle Sales Cloud report you want to run. The following reports are available:

Opportunities Returns all the opportunities like sales, revenue for all the products.
Record Set Select the record set you want to retrieve the opportunities data for.
Status Code Enter the status code.
Date Selection Select the date format for your data.
Single Date Select whether the report data is for a specific date or for a relative number of days back from today.
Specific Date Select the specific date using the date selector.
Relative Date Enter the number of days back that you would like to get data for in the Days Back field. Specify either today or 0, yesterday or 1, or today-7 or 7 to get data for 7 days into the past.
Date Range Select the specific or relative date range.
Start Date - Specific Select the first date in your date range using the date selector.
End Date - Specific Select the last date in your date range using the date selector.
Start Date - Relative

Enter the number of days back that you would like to get data from (start day). Combine with End Date to create a range of represented days.

For example, if you entered 10 for Start Date and 5 for End Date , the report would contain data for 10 days ago up until 5 days ago.

End Date - Relative

Enter the number of days back that you would like to get data to (end day). Combine with Start Date to create a range of represented days.

For example, if you entered 10 for Start Date and 5 for End Date , the report would contain data for 10 days ago up until 5 days ago.

### Other Panes For information about the remaining sections of the Connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQs
Report Name Endpoint URL(s)
Opportunities /crmRestApi/resources/11.13.18.05/opportunities
You need the username and password associated with your Oracle Sales Cloud account, and the URL of your Oracle Cloud service (Example: `https://{servername}.fa.us2.oraclecloud.com.`) Yes No As often as needed.
## Troubleshooting * Make sure your authentication remains valid. * Review the configuration to make sure that all required items have been selected. * Review the Connector history for error messages. * In rare cases, you may be requesting too much information and reaching API limitations or timeouts. If this is the case, you can review the history of the Connector run to see the error message and duration. If this is the case, you can reduce the number of accounts that are being pulled, choose a smaller number of metrics for the report that you are pulling, or reduce the timeframe that you are trying to pull. # Oracle Database Connector Source: https://www.domo.com/docs/s/article/1500012178021 ## Intro Oracle Database is an object-relational database management system produced and marketed by Oracle Corporation. You can use Domo's Oracle Database Connector to pull data from your Oracle database and compile custom reports. You indicate the data you want by inputting an SQL query. You connect to Oracle Database in the Data Center. This topic discusses the fields and menus that are specific to the Oracle Database connector user interface. To add DataSets, set update schedules, and edit DataSet information, see [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). ## Prerequisites To connect to Oracle Database and create a DataSet, you must have the following: * Your Oracle database server username and password * The hostname or IP address of your Oracle database server * Your Oracle port number * Your Oracle database service name Before you can connect to Oracle Database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses for Connectors](https://domo-support.domo.com/s/article/360043630093?language=en_US "Whitelisting IP Addresses for Connectors"). ## Connecting to Your Oracle Account This section enumerates the options in the Credentials and Details panes in the Oracle Database Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in great detail in [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Oracle Database account. The following table describes what is needed for each field:

Field

Description

Username

Enter the username for your Oracle database.

Password

Enter the password for your Oracle database.

Host

Enter the hostname or IP address of your Oracle server. Example db.company.com

Port

Enter your Oracle database port number.

Service Name

Enter your Oracle database service name.

Once you have entered valid Oracle database credentials, you can use the same account any time you go to create a new Oracle Database DataSet. You can manage Connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](https://domo-support.domo.com/s/article/360042926054?language=en_US "Managing User Accounts for Connectors"). ### Details Pane This pane contains a primary **Reports** menu, along with various other menus which may or may not appear depending on the report type you select.

Menu

Description

Query Type

Select a query type.

Query Type Description
Query Regular SQL query without parameter.
Query Parameter SQL query with parameter.
Query Enter the SQL query to execute.
Query Parameter Enter the query parameter value. It is the initial value for query parameter. The last run date is optional. By default, it is '02/01/1700' if is not provided. Example: `!{lastvalue:_id}!=1,!{lastrundate:start_date}!=02/01/1944`
Database Tables
Select the database table.
Table Columns
Select the table columns.
Query Helper
This query is automatically generated when you select a table and columns in the Database Table and Table Columns fields, respectively. Copy and paste this query into the Query field if you need help building a query.
### Other Panes For information about the remaining sections of the Connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). # Oracle Autonomous Data Warehouse Cloud Connector Source: https://www.domo.com/docs/s/article/360042928934 ## Intro Oracle Autonomous Data Warehouse Cloud (Oracle ADWC) is a fully-managed, high-performance, and elastic data warehouse service. You can use Domo's Oracle ADWC connector to pull data from your Oracle data warehouse and compile custom reports. To learn more about the Oracle ADWC, visit their website ([https://cloud.oracle.com/en\_US/datawarehouse](https://cloud.oracle.com/en_US/datawarehouse "https://cloud.oracle.com/en_US/datawarehouse") ). You connect to your Oracle ADWC account in the Data Center. This topic discusses the fields and menus that are specific to the Oracle ADWC connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## Prerequisites To connect to your Oracle ADWC account and create a DataSet, you must have the following: * The name of the service you want to connect to. Your service names are found in the tnsnames.ora file inside your connection wallet. Each service name is the text on the left of the '=' in each entry in tnsnames.ora. **Note:** The entries may contain a field named **service\_name**. This is *not* the Oracle service that needs to be provided. For example, the Oracle service of the following entry is adw\_high. `adw_high = (description= (address=(protocol=tcps)(port=1522)(host= adb.us-phoenix-1.oraclecloud.com ))(connect_data=(service_name=qfd8c2d8u4sdf_adw_high. adwc.oraclecloud.com )))` * Your Oracle database username and password * A Base64-encoded wallet file. You can download this file from the Oracle ADWC console. To encode the wallet file, use the command line to navigate to the directory of your zipped wallet file. Run the command corresponding to your operating system, replacing wallet.zip with the name of your wallet file: Windows: `certutil -encode wallet.zip encoded\_wallet.txt` Mac/Linux: `base64 -i wallet.zip -o encoded\_wallet.txt` This will generate a text file named encoded\_wallet.txt. Open this file and copy ALL of the text. Paste the text into the **Base64 Encoded Wallet** field. ### Whitelisting Before you can connect to an Oracle database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses for Connectors](/docs/s/article/360043630093 "Whitelisting IP Addresses for Connectors"). ## Connecting to Your Oracle ADWC Database This section enumerates the options in the **Credentials** and **Details** panes in the Oracle ADWC Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Oracle ADWC database. The following table describes what is needed for each field:

Field

Description

Oracle Service

Enter the name of the Oracle service you want to connect to. For more information about locating your service, see "Prerequisites," above.

Database Username

Enter your Oracle database username.

Database Password

Enter your Oracle database password.

Base64 Encoded Wallet

Enter the copied text from the encoded\_wallet.txt file. For more information about generating this file, see "Prerequisites," above.

Once you have entered valid credentials, you can use the same account any time you go to create a new Oracle ADWC DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane In this pane you input the SQL query you want to use to pull data from your Oracle database. Optionally, you can also indicate the specific table and columns from that table to bring into Domo.

Menu

Description

Query

Enter the SQL query to use to retrieve your data. You can use the Query Helper parameter to help you write a usable SQL query. To use the Query Helper , do the following:

  1. Select your database table and table columns in the appropriate menus.

  2. Copy the SQL statement that appears in the Query Helper field.

  3. Paste the copied SQL statement into the Query field.

Database Tables

Select the database tables you want to pull into Domo, if desired.

Table Columns

Select the table columns you want to pull into Domo.

Query Helper

(Optional) Copy and paste the SQL statement in this field into the Query field. For more information, see Query , above.

### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274). ## FAQ See "Prerequisites" near the top of this page. See "Prerequisites" near the top of this page. # Oracle CRM on Demand Connector Source: https://www.domo.com/docs/s/article/360042929634 ## Intro Oracle's CRM On Demand solutions help organizations drive sales, marketing, loyalty, and service effectiveness through a CRM that integrates with other Oracle products and services. You connect to your Oracle CRM On Demand account in the Data Center. This topic discusses the fields and menus that are specific to the Oracle CRM On Demand connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ## Prerequisites To connect to your Oracle CRM On Demand account and create a DataSet, you must have the following: * The user host where your Oracle CRM On Demand account is located * Your Oracle CRM On Demand username and password ## Connecting to Your Oracle CRM On Demand Account This section enumerates the options in the **Credentials** and **Details** panes in the Oracle CRM On Demand Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your Oracle CRM On Demand account. The following table describes what is needed for each field:

Field

Description

Host

Enter the host name where the Oracle CRM On Demand account is found.

Username

Enter the username for the Oracle CRM On Demand account.

Password

Enter the username for the Oracle CRM On Demand account.

Once you have entered valid Oracle CRM On Demand credentials, you can use the same account any time you go to create a new Oracle CRM On Demand DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](/docs/s/article/360042926054 "Managing User Accounts for Connectors"). ### Details Pane This pane contains two primary menus from which you select your resource and the attributes (columns) for the resource you want to appear in the DataSet. You can also add an optional query expression to filter resources.

Menu

Description

Resources

Select the Oracle CRM On Demand resource (record) you want to pull into Domo as a DataSet.

Attributes Select all the attributes (columns) of the selected resource you want to appear in your DataSet.
Advanced Options Check this box to reveal the optional Query Expression field.
Query Expression (Optional)

Enter a query expression to filter resources in a collection. A query expression is comprised of one or more "field expressions." The maximum supported query expression length is 4096 characters.

The following is the query expression syntax:

QUERY EXPRESSION = FIELD EXPRESSION \[; FIELD EXPRESSION]

\[FIELD EXPRESSION] = \ \ \ \[ANDOR CLAUSE]

\[ANDOR CLAUSE] = \ \ \ \[ ANDOR CLAUSE]


The following example shows a query expression with two field expressions separated by a semicolon:

AccountName='PSKDemo02' OR = 'A. C. Networks'; Reference = false

Tips:
  • Use single quotes around values.
  • Use the same date format as exists in the field you are writing the expression for.
### Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [a DataSet Using a Data Connector](/docs/s/article/360042926274 "Adding a DataSet Using a Data Connector"). # PostgreSQL SSH Connector Source: https://www.domo.com/docs/s/article/360042931754 ## Intro PostgreSQL is a widely used open-source relational database management system. You can use Domo's PostgreSQL SSH Connector to pull data from your PostgreSQL database via an SSH tunnel and compile custom reports. You indicate the data you want by inputting an SQL query. For more information about the PostgreSQL API, visit their website. ([https://www.postgresql.org/docs/](https://www.postgresql.org/docs/ "https://www.postgresql.org/docs/") ) The PostgreSQL SSH connector is a "Database" connector, meaning it retrieves data from databases using a query. In the Data Center, you can access the connector page for this and other Database connectors by clicking **Database** in the toolbar at the top of the window. You connect to your PostgreSQL database in the Data Center. This topic discusses the fields and menus that are specific to the PostgreSQL SSH connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). **Note:** Depending on your network's structure, your IT administrator may need to whitelist any IP addresses necessary for the data connector to retrieve data. Contact your IT administrator for assistance.

Primary Use Cases

This connector is appropriate for pulling database information into Domo.

Primary Metrics

N/A

Primary Company Roles

  • IT

  • Project management

Average Implementation Time

\~10 hours

Ease of Use (on a 1-to-10 scale with 1 being easiest)

9

## Best Practices * Use read-only queries only. * Use "Replace" instead of "Append." ## Prerequisites To connect to a PostgreSQL database via an SSH tunnel and create a DataSet, you must have the following: * The username and password you use to log into your PostgreSQL database * The name of the PostgreSQL database * The port number for the PostgreSQL database * The PostgreSQL database hostname or IP address * The UNIX server to SSH-tunnel through * The username and password for the UNIX account * The SSH port number * The SSH private key (either DES or RSA) Before you can connect to a PostgreSQL database, you must also whitelist a number of IP addresses on your database server on the port you want to connect to. For the full list of IP addresses, see [Whitelisting IP Addresses for Connectors](/docs/s/article/360043630093 "Whitelisting IP Addresses for Connectors"). **Note: Domo does not support the SSH keys generated using ssh-keygen. The SSH keys need to be the DES or RSA keys generated by OpenSSL**. ## Connecting to Your PostgreSQL Database This section enumerates the options in the **Credentials** and **Details** panes in the PostgreSQL SSH Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Connector"). ### Credentials Pane This pane contains fields for entering credentials to connect to your database and SSH server. The following table describes what is needed for each field:

Field

Description

SSH Server Hostname

Enter the hostname of the UNIX server to SSH-tunnel through.

SSH Username

Enter the SSH username for your UNIX account.

SSH Password

Enter the SSH password username for your UNIX account.

SSH Port

Enter the port number for your UNIX account.

Database Hostname

Enter the host name for the PostgreSQL database. For example: db.company.com

SSH Private Key

Enter the SSH private key (either DES or RSA).

Database Name

Enter the PostgreSQL database name.

Database Username

Enter your PostgreSQL username.

Database Password

Enter your PostgreSQL password.

Database Port

Enter your PostgreSQL port number.

Once you have entered valid credentials, you can use the same account any time you go to create a new PostgreSQL SSH DataSet. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Manage Connector Accounts](https://domo-support.domo.com/s/article/360042926054?language=en_US "Manage Connector Accounts"). ### Details Pane In this pane you create an SQL query to pull data from your database.

Menu

Description

Query Type

Custom Query Enter a customized SQL query with or without parameter to run.
Query Builder Build an SQL query by selecting the database table and table columns.

Database Tables

Select the database table you want to view in your report. This field appears when you select Query Builder as the Query Type .

Table Columns

Select all the table columns you want to view in your report.

Query Helper

Edit the query if required.

SQL Query

Enter the Structured Query Language (SQL) query to select the data you want.

Incremental Pull

The incremental pull option enables smaller dataset to be pulled from a database table as per variable tag!! and a last value or max value logic option. Dates should include single quotes around the variable tag such as '!!', while integers and decimals can remain without a single quote.

Last value : populate the variable in the query with the last value for the column to be pulled into Domo.

Max value : populates the variable in the query with the max value for that column from the last time the dataset ran.

The syntax for the variable is!!, column being the dataset column to be queried and the incremental pull logic acted against.

Default Value is used in the!! for only the first run of the dataset.

For example query: Select \* from table where date > '!!' and the max value incremental pull option is selected. The connector uses the max date saved from the previous run for the date column, inserts that date into the query, and then runs the query against the database. All the data with a date greater than the max date would be pulled into Domo.

Default Value

Replaces the!! macro for the first run of the dataset. This field appears when you select Max value or Last value from the Incremental Pull drop-down list.

Fetch Size

Enter the fetch size for the memory performance. If the field is blank, then the default value becomes 400. If it throws out of memory for a value, then decrease the fetch size.

Keep big ints as integers

Select this checkbox to keep big ints as integers. Otherwise, big ints will be converted to floating decimals.

## Troubleshooting * Make sure the appropriate IP addresses are whitelisted (see Prerequisites for a list of IP addresses). * Try decreasing fetch size or leave it empty. # Oracle Database Writeback Connector Source: https://www.domo.com/docs/s/article/360042932434 ## Intro To learn more about Oracle, visit their website at [https://www.oracle.com/index.html](https://en.wikipedia.org/wiki/SSH_File_Transfer_Protocol "https://www.oracle.com/index.html"). You export data to an Oracle database in the Data Center. This topic discusses the fields and menus that are specific to the Oracle Database Writeback connector user interface. General information for adding DataSets, setting update schedules, and editing DataSet information is discussed in [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). **Note:** * The Oracle Database Writeback Connector does not allow full replace. * The owner of a writeback dataset must also be an owner or co-owner of the input dataset. ## Prerequisites To configure this connector, you will need the following: * A Domo Client ID and Client Secret. Learn how to get your [Domo Client ID and Secret](/docs/s/article/000005240#create-api-clients). * Your Oracle Databaseserver hostname. * Your Oracle Databaseserver port number. * Your Oracle Databaseserver username and password. * An Oracle SID. This is a unique identifier for a specific Oracle database. For more information about finding the SID for your database, see [https://asktom.oracle.com/pls/asktom...D:318216852435](https://asktom.oracle.com/pls/asktom/f?p=100:11:0::NO::P11_QUESTION_ID:318216852435 "https://asktom.oracle.com/pls/asktom/f?p=100:11:0::NO::P11_QUESTION_ID:318216852435"). ## Configuring the Connection This section enumerates the options in the **Credentials** and **Details** panes in the Oracle Database Writeback Connector page. The components of the other panes in this page, **Scheduling** and **Name & Describe Your DataSet**, are universal across most connector types and are discussed in greater length in [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926274?language=en_US "Adding a DataSet Using a Data Connector"). ## Credentials Pane This pane contains fields for entering credentials to connect to your Domo developer account as well as the table in your Oracle database where you want your data to be copied to. The following table describes what is needed for each field:

Field

Description

Domo Client ID

Enter your Domo client ID.

Domo Client Secret

Enter your Domo client secret.

Host

Enter your Oracle database hostname.

Port

Enter your Oracle database port number.

Username

Enter your Oracle database username.

Password

Enter your Oracle database password.

SID Enter your Oracle SID.
For more information about obtaining these credentials, see "Prerequisites," above. Once you have entered valid credentials, you can use the same account any time you go to set up a new Domo-Oracle connection. You can manage connector accounts in the **Accounts** tab in the Data Center. For more information about this tab, see [Managing User Accounts for Connectors](https://domo-support.domo.com/s/article/360042926054?language=en_US "Managing User Accounts for Connectors"). ## Details Pane This pane contains a number of fields for specifying your data and indicating where it's going.

Menu

Description

Input DataSet ID

Enter the DataSet ID (GUID) for the DataSet you want to copy to S3. You can find the ID by opening the details view for the DataSet in the Data Center and looking at the portion of the URL following datasources/ . For example, in the URL [https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview](https://mycompany.domo.com/datasources/845305d8-da3d-4107-a9d6-13ef3f86d4a4/details/overview) , the DataSet ID is 845305d8-da3d-4107-a9d6-13ef3f86d4a4.

Select Table Name

Select how you want to name the table where data will be copied.

  • Use Input DataSet Name as Table Name . The table name will be the same as that of the input DataSet.

  • Enter Table Name . You will give the table a custom name in the Table Name field.

Table Name Enter the name of the table in your Oracle database where you want your DataSet data to be copied.
Update Type Select how you like to update the database table.
Truncate Table if Input Dataset is empty? Select this checkbox to truncate the table, if the input datset is empty.
Note: It will remove all the rows from the table, only if the provided dataset is empty. Please do not select the checkbox if table does not exist in oracle database. Only select the checkbox when truncating the exisiting database tables.
Alter Schema Select if you want to alter the database table schema.
Note : It may change/alter the table schema completely. If selected with Truncate Table if Input Dataset is empty? checkbox, then it will only alter schema if input dataset has some schema/columns.
## Other Panes For information about the remaining sections of the connector interface, including how to configure scheduling, retry, and update options, see [Adding a DataSet Using a Data Connector](https://domo-support.domo.com/s/article/360042926054?language=en_US "Adding a DataSet Using a Data Connector"). # Workbench 5 Overview Source: https://www.domo.com/docs/s/article/360042932554 ## Intro Workbench is a Windows-based application and one way to securely bring your data into Domo. You can bring data in manually or automatically on a schedule. * ou can upload data from databases via data queries in ODBC/OLAP System DSNs, CSV and delimted text files, Microsoft Excel spreadsheets, Jira, QuickBooks, JSON and XML namespaces. * You can upload data manually or through scheduled jobs. Workbench validates the data and securely transfers it to Domo. Workbench allows you to import/export files of the following types: * CSV * Excel * JSON * ODBC * OLAP * Quickbooks * XML * Create groups of DataSet jobs that run on the same schedule * Import and export job files * Preview and validate jobs before you run them * Add, create, save, and delete accounts * Add, create, save, delete, open, preview, and cancel jobs * Revert back to a previous version of a job you saved * Add/delete transforms to/from jobs, which includes the following: * Add new columns * Change date format * Encrypt sensitive data in specific columns * Filter columns in the DataSet * Set the time zone for the DataSet job * Replace column values in the DataSet * Combine the DataSet with another DataSet * View logs * Send logs as a zip file * Run logs from the command line * Add and manage plugins for using Workbench * Set up notifications for DataSet jobs that can email you if DataSets are uploaded successfully or if it experiences an error To read a white paper about making your Workbench data more secure in Domo by means of encryption, click here: [Whitepaper\_Domo+Data+Security+and+Encryption+Draft.pdf](https://domosoftware.sharepoint.com/:b:/s/CS-Edu-PublicFiles/Ec5lAMNCHyxIrujDa7ZAXFIBo5jv7_53HWgO7lQJdSsbbA?e=pS17jG) Workbench also allows you to do some transformations on your data: calculations, custom dates, filtering, search and replace. If you need to perform encryptions on data files, Workbench is the only place in Domo to do that. *** This article provides information about Workbench in the following topics: * Available languages * Security settings * Install latest version of Workbench * Run Workbench 5 *** ## Available Languages Workbench 5 is available in the same languages as the rest of the Domo product, listed below: * English * Japanese * French * German * Spanish * Chinese Workbench 5 automatically syncs with the configured user language on your machine. If the language of your machine is not available for Workbench, the default language for the tool is English. If you would like Workbench in a language not shown in the list above, contact [Domo Support](https://domo-support.domo.com/s/). ## Security Settings Access the security settings for Workbench 5 from the sidebar by selecting **More** > **Settings**. security settings.png Under **Security**, you can check boxes to enable the following options, described below: * **Only run locally managed jobs —** When enabled, this option only allows jobs to be run that are created on this specific machine. Jobs created through the API or any other sources do not run. This prevents hacking of your Workbench API. * **Limit concurrent jobs —** When enabled, this option causes Workbench to request non-default credentials for all DataSet jobs. This means that no jobs can be run as the local system. Because users are forced to enter non-default credentials, jobs are run at the proper security level. This option is only available if you have administrator privileges. ## **Can Workbench update or make any changes to our original data?** No, Workbench does not modify your original data. It is designed to read and transmit data to Domo. Workbench does let you modify the data going in to Domo through transforms, calculations, and joins. **Note:** For database connections only, if your ODBC driver supports read/write, any queries you pass into your database can be considered a “write.” For example, temp tables, inserts, or deletes are entirely possible with Workbench and database connections. Consider using read-only credentials for your database connections if there is cause for concern. **What type of encryption does Workbench use to transmit data?** All data transferred from Workbench into Domo's production systems is sent using encrypted HTTPS sessions, the same technology you typically use to conduct online banking and online purchases. No data is sent from Workbench to Domo in an unencrypted manner. **If access credentials cannot be stored as part of the Windows DSN, how are those credentials stored?** Workbench stores access credentials for ODBC DataSets. To properly protect these credentials, Workbench uses industry standard AES-256 bit encryption or RSA encryption with a key stored locally on your computer (depending on the length of data being encrypted) . Workbench enforces encryption automatically so users do not have the opportunity of mistakenly storing their passwords or other credentials inappropriately. **How are access controls configured for Workbench?** Workbench is configured by the client from an access control perspective. Workbench allows users to upload DataSets into Domo to enable KPI card creation and automated updates. Users select DataSets (System DSNs, flat files, Microsoft Excel spreadsheets, JIRA, QuickBooks, JSON, XML namespaces) to which they already have access. Workbench can connect to DataSets only if the Microsoft Windows system running the software can reach the DataSet, and if the machine has access to read the DataSet files or databases. **Is any of the data transmitted by Workbench cached on the local machine?** Workbench uses a temp directory (%PROGRAMDATA%\Domo\Workbench\DomoCache) to stage incoming data. If you have many DataSet Jobs with a large number of rows, this temp directory can fill up with a large amount of data. Make sure the C:\ drive has a reasonable amount of free space for these files. These files are cleared when the job is complete and are not permanently stored. **Are 32-bit ODBC connections supported?** Yes. Workbench concurrently supports both 32- and 64-bit ODBC drivers. **What is the maximum size of a DataSet that Workbench supports?** Workbench has no row limit for a single upload job. You can use a `lastvalue` variable to upload rows incrementally. For more information about query parameters, see [Understanding the Workbench 5 User Interface.](/docs/s/article/360042932654) **Can Workbench run from a command line?** Yes, Workbench can be executed directly from a command line and/or added as a task in an ETL package. For more information about running Workbench from the command line, see [Running Workbench from the command line](/docs/s/article/360042932594). **How can I improve the performance of a MySQL driver?** When using a MySQL driver, you can decrease its memory usage and improve its performance by configuring parameters for the DSN. Follow these steps to configure your MySQL DSN: 1. Open the the Windows ODBC Data Source Administrator by entering "ODBC" in the Start Menu search, then selecting "Data Sources (ODBC)". 2. Select your DSN, then click **Configure**. 3. Click **Details** to display additional settings. 1. In the **Connection** tab, mark the **Allow big result sets** box.\ When selected, the driver does not set packet limits for results. 2. In the **Cursors/Results** tab, mark the **Don't cache results of forward-only cursors** box and the **Force use of forward-only cursors** box.\ When selected, the driver does not cache results and uses forward-only cursors. **Note:** Workbench does not need anything other than "forward only" cursors and the MySQL ODBC driver performs better using the "forward only" cursors option. **How do I get access to network files to run a scheduled job?** When running a job on a schedule, if the file is not located on the local machine Workbench is running on, you must set up impersonation for access rights. Follow these steps to set up impersonation: 1. Click the wb5_jobs_icon.png icon in the left-hand icon bar. 2. Double-click the name of the job you want to set up impersonation for. 3. Select **Configure**. 4. Click **Impersonation** to expand that section. 5. Check the **Requires Impersonation** box. 6. Enter your domain, username, and password in the boxes. 7. Click **Validate**. If you are connecting to a file on a domain file share that the Workbench computer is not on, the domain impersonation will not work if you are not on the domain computer. You will have to give domain access to it. Follow these steps to give domain access: 1. Click the wb5_jobs_icon.png icon in the left-hand icon bar. 2. Double-click the name of the job you want to provide domain access for. 3. Click **Edit** under "Source." 4. Enter the network file path in the **File Path** field. 5. Check the **File on an external network** box. 6. Enter your credentials. 7. Click **Apply**. **How do I clear the queue in Workbench?** Say you have a dataset set up to update every hour, and you keep getting an error when you're trying to run the job in Workbench. More specifically, you're not able to add that job to the queue because it is either already queued or currently executing. There are a few reasons why this error can occur and ways to avoid it: * The current job could be in a non-responsive state. If a job is running longer than expected, open a case with Domo Support to investigate the issue further ([support@domo.com](mailto:support@domo.com)). * You can also restart the Workbench service, which will flush the queue. Normal workflow of Workbench jobs should return after restarting. If restarting the service does not return your Workbench to normal operation, please open a case with Domo Support ([support@domo.com](mailto:support@domo.com)). **How do I change data capture using Workbench?** You can create a new job that will append the data that has changes in the RDBMS (Relational database management system) since the last load. Follow the steps below to do it. 1. Perform the initial load of the data using **Create New Data Source**. Screenshot 2. The two key setup lines in the SQL that are very important are as follows: * Where "ReportDate" > '!\{lastvalue:ReportDate}!'\ Ensure the Where clause contains the field that holds the value that indicate the changes since last load. The '!\{lastvalue:ReportDate}!' contains the last value for the **Query Variable** as shown (see the Query Variable Setup section below). Call the **Query Variable** the same name as the field in the query that indicates the changes since the last Load. * Order by\ Ensure you have an **Order By** clause in the SQL statement, since it will be the value from the last row that will be saved in the Lastvalue variable. If you don't order by the column that contains the change data capture field, then you might not get the changed rows in the query. 3. After the initial load change, the job will start appending data to the existing dataset, as shown in the example below: Screenshot ## Query Variable Setup Steps 1. Perform the Query Variable setup on the separate 'Edit Query Variables' screen. Note that you have the option of setting a Job Variable or a Global Variable. 2. Create a Job Variable that matches the 'Name' of the field that contains the data that controls the Changed data. Screenshot 3. The 'Current Value' will indicate the last value the job loaded. The initial value must be less than the first record you want to import. **What proxy settings does Workbench use?** When you first connect to Domo via Workbench, Workbench leverages your Windows system proxy settings. You can open your proxy settings for editing by clicking wb5_more_icon.png and selecting **Proxy**. **Can I save Workbench jobs to a shared folder? I want multiple users to be able to access and edit the jobs, but I can't figure out where jobs are saved on the drive.** All Workbench jobs are saved in the cloud and tied to a specific login, *not* saved locally. Therefore, the recommended solution to this problem is to install Workbench on a common server then create an admin user to be used by all users who need to modify jobs. Thus, all these users will be able to access the jobs, and you will not need to worry about saving copies of the job on a physical drive. Although multiple users can use Workbench simultaneously, only the first opened instance will get the live updates from the Workbench service. We generally do not recommend having multiple instances of Workbench open because of multiple people have the same job open and are making changes, the last person to save will overwrite all other changes. **Can I share Workbench jobs?** Jobs are tied to the Workbench installation in which they were created. If you wanted to share a job, you would need to export that job on the Workbench installation in which it was created then import it into the second installation of Workbench. **Note:** It is not recommended to have the same job running on two different instances of Workbench at the same time. If you do export a job from one and import it into another, be sure to remove it from its original Workbench instance after successfully importing it into another. **Is multi-factor authentication available for Workbench?** Not at this time. **Can I do a mass export of all my job files?** Yes. Workbench 5 allows the mass import/export of job files. Click wb5_more_icon.png and select **Export**. You can then choose a save folder and select all of the jobs you want to export. wb5_mass_export1.png **What are the recommended specifications to run Workbench?** * Operating system: Any version of Windows still supported by Microsoft * CPU: A modern 4- or 8-core processor * Memory: 8-16 GB * Hard drive: 250 MB of space minimum, 2 GB recommended (though more may be required depending on the amount of data in your jobs) **Important:** If you have space issues with C: Drive, then contact your IT team to investigate what else is taking up space on that drive. **How many refresh tokens are available per client?** Due to OAuth 2.0, each user is allowed 50 refresh tokens per client. This means that only 50 Workbench machines can be running at a time per user. If you set up more machines using the same set of credentials, you will likely run into problems while executing jobs. **Will changing my password cause my OAuth tokens to expire in Workbench?** Yes. Changing your password causes your OAuth tokens to expire, and Workbench is no longer authenticated. **What firewall rules or ports need to be open for Workbench?** Port 443 bi-directional **Does Workbench throttle CPU usage?** Not by default, but Workbench does have this as a configurable option. **Where does Workbench store staging data by default? And can I move this staging data?** The data is stored in %PROGRAMDATA\Domo\Workbench\DomoCache. Currently you cannot move the staging folder. **How do I get the list of table names or stored procedures on my database?** The query builder is in the **Source** pane. This may give you a list of tables, views, and procedures. Be aware this is not compatible with all database types. **I am unable to add a user to the Domo Workbench users group. Why is this?** Ensure your Windows username is not the same as the PC name. Windows 10 appears to enforce this. Older versions of Windows may also be impacted. **Workbench failed to install. Where can I find the logs?** You can find the logs in the following directory: C:\Users\NAME\_OF\_USER\AppData\Local\Temp The file names are Domo\_Workbench\_\.log and Domo\_Workbench\_\\_001\_DomoWorkbench64.log **My QuickBooks Workbench jobs will not run on schedule. What do I do?** You must be logged into Windows with an active session for QuickBooks integrated applications to run unattended. **What do I do if the Unsafe Save dialog appears?** The "Unsafe Save" dialog is displayed when your local job configuration and the remote job configuration stored in Domo do not match up or the job is currently running. To prevent the loss of data, you must first wait for the job to finish if it's running, then re-sync your local configuration with Domo. This can be done by either clicking **Revert** or pressing F5 on your keyboard to refresh your entire job list. Unfortunately you will lose any changes that you have made when you take either of these actions. If your job runs long enough or frequently enough that you constantly see this dialog when attempting to make changes, you likely need to temporarily turn off the Workbench service, make your changes, then re-enable the service to start running your newly modified job. **My IT department requires a whitelist for all outgoing internet traffic from our network. Does Domo have an IP whitelist for purposes of running Workbench?** Domo Support can provide you with an IP to whitelist. Note that although unlikely, the IP can change at any moment and without notice, resulting in Workbench job failures. It is advised that you whitelist by DNS name if possible. (e.g. instance.domo.com). **Is there a way to move my DomoCache directory to a different disk drive?** The current version of Workbench doesn't allow you to separate the operating system from the application data, but you can work around this issue using hard-coded symbolic links. The following example shows how a user moved his DomoCache directory to the E: drive: `mklink /J "C:\ProgramData\Domo\Workbench\DomoCache" "E:\Domo\Workbench\DomoCache"` What does it mean when Workbench says "Live updates are not available"? This could mean a few different things. If another person is running Workbench on the same computer, this message will appear. This could also appear if there are port conflicts with other applications on the computer. To fix this, go to **Workbench Settings**, and in the **Notifications** section you will be able to update the **Port**. **Can I run jobs more frequently than every 15 minutes?** Yes, if you need this ability, please reach out to your account team for evaluation. ## Install the Latest Version of Workbench You can only download and use Workbench on a Windows OS. It does work on a virtual machine.\ Follow these steps to install the latest version of Workbench: 1. From the navigation header, select **More** > **Admin**. The Admin Settings display. 2. In the **More** menu, select **Tool Downloads**. 3. On the **Tool Downloads** page, locate the section for the latest version of Workbench and select **Download** **Domo Workbench**. download domo workbench.jpg 4. Locate the file in the downloads area of your machine. 4. Open the file and follow the steps --- **Video - Workbench 5 Overview**