Connect to Real-Time Azure Data Lake Storage Data in Power Apps Using Dataflows to Build Custom Applications

Power Apps is a suite of apps, services, and connectors that allows users to build custom applications with minimal or no coding. It empowers businesses to create tailored apps that solve specific business challenges, automate workflows, and integrate with various data sources, including Microsoft Dataverse, SQL Server, and third-party services.

Dataflows in Power Apps simplify the process of importing, transforming, and loading external data into Microsoft Dataverse or other storage systems. They allow users to connect to multiple data sources (like Salesforce, Excel, or SQL databases), clean or shape the data, and store it in Power Apps. When paired with the CData Power BI Connector for Azure Data Lake Storage, it provides access to Azure Data Lake Storage data to build custom applications and more

This article demonstrates how you can easily connect to Azure Data Lake Storage using the CData Power BI Connector for Azure Data Lake Storage and integrate your Azure Data Lake Storage data through the Power Apps on-premises data gateway.

Configure a DSN to connect to Azure Data Lake Storage data

Installing the Power BI Connector creates a DSN (data source name) called CData PBI Azure Data Lake Storage Sys. This the name of the DSN that Power BI uses to request a connection to the data source. Configure the DSN by filling in the required connection properties.

You can use the Microsoft ODBC Data Source Administrator to create a new DSN or configure (and rename) an existing DSN: From the Start menu, enter "ODBC Data Sources." Ensure that you run the version of the ODBC Administrator that corresponds to the bitness of your Power BI Desktop installation (32-bit or 64-bit).

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.

Configure the on-premises data gateway to recognize the CData Power BI Connector for Azure Data Lake Storage

In this section, we will configure the on-premises data gateway to detect the CData Power BI Connector for Azure Data Lake Storage installed on your system. If you haven't installed the data gateway yet, you can download it from Microsoft's official website.

Set Up the Power BI Gateway

Follow the given process to configure the on-premise data gateway on your machine:

1. Download and install the on-premises data gateway (recommended) option.
2. Sign into the gateway.
3. Create a name for the new gateway and specify a recovery key.
4. Open the new gateway, navigate to the Connector tab, and select the path C:\Program Files\CData\CData Power BI Connector for Azure Data Lake Storage from the folder. Click on Apply.

   NOTE: Select the folder where the gateway will search for the CData Power BI Connector.

5. Once the CData Power BI Connector for Azure Data Lake Storage is identified by the gateway, you're good to go.

Configure a dataflow connection in Power Apps

Once the on-premise data gateway is configured and a new gateway is created, follow these steps to create a dataflow that pulls in the Azure Data Lake Storage data into Power Apps:

1. Open Power Apps.
2. Select Dataflows from the left panel on the Power Apps screen and click + New Dataflow.
3. Provide a name to the dataflow and click Create.
4. Select ODBC from the list of data sources.
5. On the ODBC Connection settings screen, use the connection details you set up earlier by entering DSN=Connection name (in this case, DSN=CData PBI Azure Data Lake Storage Sys) in the connection string. The on-premise data gateway will display available gateways for connection - select the one you created. Due to the current specifications of Power Apps dataflows, authentication is required for ODBC connections. Choose Basic as the authentication type and enter the Azure Data Lake Storage Username and Password. Click Next.
6. Azure Data Lake Storage is now connected to Power Apps. Under Display options, expand CData under ODBC and Azure Data Lake Storage under CData, and a list of all the Azure Data Lake Storage tables will appear in the panel. When you select any one of these tables, a preview will appear, showing that the Azure Data Lake Storage data is correctly referenced through the Power BI connector and on-premise data gateway. Next, click on Transform Data.
7. On the query editing screen, if no column conversion is needed, you can skip this step and proceed by clicking on Next.
8. In the Choose destination settings screen, you can select how the selected table needs to be loaded by choosing options like Load to new table, Load to existing table, and Do not load. You can also change the Table display name and description as required.
9. Finally, choose how you'd like to update your data: Refresh manually or Refresh automatically. In this case, we have set it to Refresh automatically. By scheduling it to update every 45 minutes, as shown below, data will be collected and registered every 45 minutes timeframe, ensuring the most up-to-date information is always available. (You can select any timeframe based on your convenience)
10. Click on Publish. The dataflow will now be created, published, and displayed as a part of the dataflow list on the Dataflows screen.

Get Started Today

At this point, you will have created a dataflow using live Azure Data Lake Storage data and connected it to Power Apps. To learn more, explore the CData Power BI Connectors for Salesforce and download a free 30-day trial from the CData Power BI Connector for Azure Data Lake Storage page.

Feel free to reach out to our Support Team with any questions.