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Visualize Azure Data Lake Storage Data from Tableau



Use the Tableau Desktop business intelligence tool to connect to Azure Data Lake Storage data.

With CData Drivers for Azure Data Lake Storage, you can use data access standards to unlock connectivity to business intelligence tools like Tableau. The CData JDBC Driver for Azure Data Lake Storage allows you to connect from Tableau on Windows and macOS. This article covers how to discover schemas and query Azure Data Lake Storage data data in real-time.

NOTE: If you are using Tableau 2020.3 or higher, you can use the CData JDBC Driver for Azure Data Lake Storage. If you wish to connect to Azure Data Lake Storage data in Tableau Cloud, you will need to use CData Connect.

Connect to Azure Data Lake Storage in Tableau

Before starting Tableau, make sure you've placed the .jar file in the correct folder:

  • Windows: C:\Program Files\Tableau\Drivers
  • MacOS: ~/Library/Tableau/Drivers

Once your .jar file is in place, establishing a connection is straightforward.

  1. Start Tableau.
  2. Under To a Server, select More.
  3. Select Other Databases (JDBC)
  4. Enter the JDBC connection string in the URL field.
  5. 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.

    Built-in Connection String Designer

    For assistance in constructing the JDBC URL, use the connection string designer built into the Azure Data Lake Storage JDBC Driver. Either double-click the .jar file or execute the .jar file from the command-line.

    From Windows:

    java -jar 'C:\Program Files\CData[product_name]\lib\cdata.jdbc.adls.jar'

    From MacOS:

    java -jar cdata.jdbc.adls.jar

    Fill in the connection properties and copy the connection string to the clipboard.

    When you configure the JDBC URL, you may also want to set the Max Rows connection property. This will limit the number of rows returned, which is especially helpful for improving performance when designing reports and visualizations.

    The following is a sample URL created in the designer:

    jdbc:adls:Schema=ADLSGen2;Account=myAccount;FileSystem=myFileSystem;AccessKey=myAccessKey;InitiateOAuth=GETANDREFRESH;
  6. Select Sign in.

Discover Schemas and Query Data

  1. Select CData from the Database pull-down menu.
  2. Select CData from the Schema pull-down menu.
  3. Drag the table onto the join area. You can include multiple tables.
  4. Select Update Now or Automatically Update. Update Now lets you preview the first 10,000 rows of the data source (or enter the number of rows you want to see in the Rows text box). Automatically Update automatically reflects the changes in the preview area.
  5. In the Connection menu, select the Live option, so that you skip loading a copy of the data into Tableau and instead work on real-time data.
  6. Click the tab for your worksheet. Columns are listed as Dimensions and Measures, depending on the data type. The CData Driver discovers data types automatically, allowing you to leverage the powerful data processing and visualization features of Tableau.
  7. Click and drag a field from the Dimensions or Measures area to Rows or Columns. Tableau creates column or row headers.
  8. Select one of the chart types from the Show Me tab. Tableau displays the chart type that you selected.

Using the CData JDBC Driver for Azure Data Lake Storage with Tableau, you can easily create robust visualizations and reports on Azure Data Lake Storage data. Download a free, 30-day trial and get started today.