Visualize Live Azure Data Lake Storage Data in Power BI (via CData Connect AI)

Power BI transforms your company's data into rich visuals for you to collect and organize so you can focus on what matters to you. When paired with CData Connect AI, you get access to Azure Data Lake Storage data for visualizations, dashboards, and more. This article shows how to use CData Connect to create a live connection to Azure Data Lake Storage, connect to Azure Data Lake Storage data from Power BI and then create reports on Azure Data Lake Storage data in Power BI.

Configure Azure Data Lake Storage Connectivity for Power BI

Connectivity to Azure Data Lake Storage from Power BI is made possible through CData Connect AI. To work with Azure Data Lake Storage data from Power BI, we start by creating and configuring a Azure Data Lake Storage connection.

1. Log into Connect AI, click Sources, and then click Add Connection
👁 Adding a Connection

2. Select "Azure Data Lake Storage" from the Add Connection panel
👁 Selecting a data source

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 Entra ID (formerly 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 "Entra ID" (formerly Azure AD).
   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.
   👁 Configuring a connection (Salesforce is shown)
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Azure Data Lake Storage Connection page and update the User-based permissions. 👁 Updating permissions
   

With the connection configured, you are ready to connect to Azure Data Lake Storage data from Power BI.

Query Azure Data Lake Storage Tables

Follow the steps below to build a query to pull Azure Data Lake Storage data into the report:

1. Open Power BI Desktop and click Get Data -> Online Services -> CData Connect AI and click "Connect"
2. Click "Sign in" and authenticate with your CData Connect AI account 👁 Authenticating with Connect AI
   
3. After signing in, click "Connect" 👁 Connecting to Connect AI
   
4. Select tables in the Navigator dialog 👁 The available tables. (Salesforce tables are shown)
   
5. Click Load to establish the connection to your Azure Data Lake Storage data from Power BI

Create Azure Data Lake Storage Data Visualizations

After connecting to the data into Power BI, you can create data visualizations in the Report view by dragging fields from the Fields pane onto the canvas. Select the dimensions and measures you wish to visualize along with the chart type.

Click Refresh to synchronize your report with any changes to the data.

Live Access to Azure Data Lake Storage Data from Data Applications

With CData Connect AI you have a direct connection to Azure Data Lake Storage data from Power BI. You can import more data, create new visualizations, build reports, and more — all without replicating Azure Data Lake Storage data.

To get SQL data access to hundreds of SaaS, Big Data, and NoSQL sources (including Azure Data Lake Storage) directly from your on-premise BI, reporting, ETL and other data applications, visit the CData Connect AI page and start a free trial.