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The fastest and easiest way to connect Power BI to Azure Data Lake Storage data. Includes comprehensive high-performance data access, real-time integration, extensive metadata discovery, and robust SQL-92 support.

Create Azure Data Lake Storage Dataflows on PowerBI.com



Connect to the CData Power BI Connectors from PowerBI.com to create Power BI Dataflows with real-time data.

The CData Power BI Connector for Azure Data Lake Storage seamlessly integrates with the tools and wizards in Power BI, including the real-time data workflows on PowerBI.com. Follow the steps below to pull data directly into DataFlows on PowerBI.com and use the Power BI Gateway to configure automatic refresh.

Create a DSN

Installing the Power BI Connector creates a DSN (data source name) called CData Power BI Azure Data Lake Storage. 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.

Pulling Azure Data Lake Storage Data Directly Into Your Dataflow

With the data source configured, follow the steps below to load data from Azure Data Lake Storage tables into your DataFlow.

Set Up the Power BI Gateway

Follow the steps below to configure the gateway on your machine:

  1. Run the CData Power BI Connector installer. If you have not already done so, download the Power BI Gateway.
  2. Select the on-premises data gateway (recommended) option.
  3. Sign into the gateway.
  4. Name the gateway and specify a recovery key.
  5. In the Connectors step, choose a folder where the gateway will look for the CData Power BI Connector. This article uses C:\Users\PBIEgwService\Documents\Power BI Desktop\Custom Connectors\. Copy the .pqx files for the CData Connector (found in C:\Users\USERNAME\Documents\Power BI Desktop\Custom Connectors\) to the folder you configured.

    NOTE: The account configured for the service (NT SERVICE\PBIEgwService) needs to be able to access the folder chosen for the gateway. If needed, you can change the service account in the Service Settings section of the gateway installer.

  6. Confirm that the entry CData.PowerBI.ADLS is displayed in the list in the Connectors section.

Set up Power BI Online for a Dataflow

  1. In Power BI Online, create a new workspace, which is also known as an app, if you do not already have one. Note that this is only available with Power BI Pro or higher.
  2. Set up your On-Premises Gateway. The steps for this are in the Configuring the Gateway section of this article.
  3. Go back to Power BI Online. In settings, go to 'Manage Gateways', and add a new data source to your Gateway
    • Enter the Data Source Name, the name that the data source will be referred to within Power BI Online
    • Select the Data Source Type, (e.g. CData Power BI Connector for Azure Data Lake Storage) and set the Data Source Name (e.g. CData Power BI Azure Data Lake Storage)
    • Set Authentication Method to "Anonymous"
    • Set Privacy Level as needed
  4. Click Add to finish the configuration (do not skip the test connection as it is important to know if a successful connection was made).

    If you would like to manage the users that have access to this data source, you can go to the Users tab.

Set up your Dataflow and pull the Azure Data Lake Storage data

  1. In the new workspace, go to Create > Dataflow > Add New Entities.
  2. Choose the ODBC data source and enter the correct connection properties.
    Enter your DSN name in the ODBC connection string section, dsn=CData Power BI ADLS. Choose your gateway and set the authentication type to Anonymous.
  3. Choose the table(s) you want to work with and click Transform data.
    If you want to make any changes to the query, you can right click on the query and click on Advanced Editor.

Configure Data Refresh on PowerBI.com

Refresh your dataflow to have the most up to date data.

  • To refresh manually, open the dataflow options menu from your workspace -> Dataflows and click Refresh Now.
  • To schedule refreshes, open the dataflow options menu from your workspace -> Dataflows and click Schedule Refresh. Enable the option to keep your data up to date. Specify the refresh frequency in the menus.

At this point, you will have a Dataflow built on top of live Azure Data Lake Storage data. Learn more about the CData Power BI Connectors for Azure Data Lake Storage and download a free trial from the CData Power BI Connector for Azure Data Lake Storage page. Let our Support Team know if you have any questions.