Integrate Azure Data Lake Storage Data into Automated Tasks with Power Automate

Power Automate (Microsoft Flow) is an online service that automates events (known as workflows) across the most common apps and services. When paired with CData Connect Server, you get instant, cloud-to-cloud access to Azure Data Lake Storage data for visualizations, dashboards, and more. This article shows how to connect to Connect Server from Power Automate and integrate live Azure Data Lake Storage data into your workflows and tasks.

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

1. Login to Connect Server and click Connections.
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 Save Changes
5. Click Privileges -> Add and add the new user (or an existing user) with the appropriate permissions.

Connecting to CData Connect Server

To use Connect Server to integrate Azure Data Lake Storage data into your Power Automate tasks, you need a new SQL Server connection:

1. Log in to Power Automate
2. Click Data -> Connections -> New connection
3. Select SQL Server
4. In the connection wizard:
   
   
   • Set Authentication Type to "SQL Server Authentication"
   • Set SQL server name to the address of your Connect Server instance (connect_server_url)
   • Set SQL database name to the name of the virtual Azure Data Lake Storage database you created earlier (like azuredatalakedb)
   • Set the Username and Password and click Create

Integrating Azure Data Lake Storage Data into Power Automate Tasks

With the connection to Connect Server configured, you are ready to integrate live Azure Data Lake Storage data into your Power Automate tasks.

1. Log in to Power Automate
2. Click My flows -> New and choose to create the flow from blank or template
3. Add (or configure) a SQL Server action (like Get rows) and configure the action to connect to your Connect Server connection
4. Select a Table to work with (from the drop-down menu) and configure any advanced options (like filters, orders, etc)
5. Configure any actions to follow and test, then save the flow

SQL Access to Azure Data Lake Storage Data from Applications

Now you have a direct connection to live Azure Data Lake Storage data from Power Automate tasks. You can create more connections and workflows to drive business — all without replicating Azure Data Lake Storage data.

To get SQL data access to 200+ SaaS, Big Data, and NoSQL sources directly from your applications, see the CData Connect Server.

Related Power Automate Articles

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

• Azure Data Lake Storage Data in Power Automate Desktop using CData Connect
• Azure Data Lake Storage Data in Power Automate Desktop via ODBC