Integrate Azure Data Lake Storage Data into Power Automate Desktop using CData Connect

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CData Connect



CData Connect for Azure Data Lake Storage enables you to integrate Azure Data Lake Storage data into workflows built using Microsoft Power Automate Desktop.

CData Connect enables you to access live Azure Data Lake Storage data in workflow automation tools like Power Automate. This article shows how to integrate Azure Data Lake Storage data into a simple workflow, moving Azure Data Lake Storage data into a CSV file.

CData Connect provides a pure SQL interface for Azure Data Lake Storage, allowing you to easily integrate with live Azure Data Lake Storage data in Power Automate — without replicating the data. Connect looks exactly like a SQL Server database to Power Automate and uses optimized data processing out of the box to push all supported SQL operations (filters, JOINs, etc) directly to Azure Data Lake Storage, leveraging server-side processing to quickly return Azure Data Lake Storage data.

Create a Virtual SQL Database for Azure Data Lake Storage Data

CData Connect Cloud uses a straightforward, point-and-click interface to connect to data sources and generate APIs.

  1. Log into Connect Cloud and click Databases.
  2. Select "Azure Data Lake Storage" from Available Data Sources.
  3. Enter the necessary authentication properties to connect to Azure Data Lake Storage.

    Authenticating to a Gen 1 DataLakeStore Account

    Gen 1 uses OAuth 2.0 in Azure AD for authentication.

    For this, an Active Directory web application is required. You can create one as follows:

    1. Sign in to your Azure Account through the .
    2. Select "Azure Active Directory".
    3. Select "App registrations".
    4. Select "New application registration".
    5. Provide a name and URL for the application. Select Web app for the type of application you want to create.
    6. Select "Required permissions" and change the required permissions for this app. At a minimum, "Azure Data Lake" and "Windows Azure Service Management API" are required.
    7. Select "Key" and generate a new key. Add a description, a duration, and take note of the generated key. You won't be able to see it again.

    To authenticate against a Gen 1 DataLakeStore account, the following properties are required:

    • Schema: Set this to ADLSGen1.
    • Account: Set this to the name of the account.
    • OAuthClientId: Set this to the application Id of the app you created.
    • OAuthClientSecret: Set this to the key generated for the app you created.
    • TenantId: Set this to the tenant Id. See the property for more information on how to acquire this.
    • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.

    Authenticating to a Gen 2 DataLakeStore Account

    To authenticate against a Gen 2 DataLakeStore account, the following properties are required:

    • Schema: Set this to ADLSGen2.
    • Account: Set this to the name of the account.
    • FileSystem: Set this to the file system which will be used for this account.
    • AccessKey: Set this to the access key which will be used to authenticate the calls to the API. See the property for more information on how to acquire this.
    • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.
  4. Click Test Database.
  5. Click Privileges -> Add and add the new user (or an existing user) with the appropriate permissions.

Integrate Azure Data Lake Storage Data into Power Automate Workflows

After configuring CData Connect with Azure Data Lake Storage, you are ready to integrate Azure Data Lake Storage data into your Power Automate workflows. Open Microsoft Power Automate, add a new flow, and name the flow.

In the flow editor, you can add the actions to connect to Azure Data Lake Storage, query Azure Data Lake Storage using SQL, and write the query results to a CSV document.

Add an Open SQL Connection Action

Add an "Open SQL connection" action (Actions -> Database) and click the option to build the Connection string. In the Data Link Properties wizard:

  1. On the Provider tab: select Microsoft OLE DB Driver for SQL Server
  2. On the Connection tab:
    1. Select or enter a server name: set to the address and port of the SQL (TDS) endpoint of CData Connect, separated by a comma (e.g. localhost,8033)
    2. Enter information to log onto the server: select "Use a specific username and password" and use CData Connect credentials
    3. Select the database: use the database configured above (e.g. ADLS1)
  3. Click "Test Connection" to ensure the connection is configured properly
  4. Click "OK"

After building the connection string in the Data Link Properties wizard, save the action.

Add an Execute SQL Statement Action

Add an "Execute SQL statement" action (Actions -> Database) and configure the properties.

  • Get connection by: SQL connection variable
  • SQL connection: %SQLConnection% (the variable from the "Open SQL connection" action above)
  • SQL statement: SELECT * FROM Resources

After configuring the properties, save the action.

Add a Write to CSV File Action

Add a "Write to CSV file" action (Actions -> File) and configure the properties.

  • Variable to write to: %QueryResult% (the variable from the "Execute SQL statement" action above)
  • File path: set to a file on disk
  • Configure Advanced settings as needed.

After configuring the properties, save the action.

Add a Close SQL Connection Action

Add a "Close SQL connection" action (Actions -> Database) and configure the properties.

  • SQL Connection: %SQLConnection% (the variable from the "Open SQL connection" action above)

After configuring the properties, save the action.

Save & Run the Flow

Once you have configured all the actions for the flow, click the disk icon to save the flow. Click the play icon to run the flow.

Now you have a workflow to move Azure Data Lake Storage data into a CSV file.

With CData Connect, you get live connectivity to Azure Data Lake Storage data within your Microsoft Power Automate workflows.

Related Power Automate Articles

This article walks through using CData Connect Cloud with Power Automate Desktop. Check out our other articles for more ways to work with Power Automate (Desktop & Online):