Visualize Azure Data Lake Storage Data in Sisense

Sisense lets you join, analyze, and picture data to make more intelligent business decisions and craft effective strategies. The CData JDBC Driver for Azure Data Lake Storage makes it easy to integrate with Azure Data Lake Storage data in Sisense. This article shows how to create an ElastiCube that connects to Azure Data Lake Storage data and use the ElastiCube to visualize Azure Data Lake Storage data in Sisense.

Configure the Connection to Azure Data Lake Storage

Before creating the ElastiCube, note the installation location for the JAR file for the JDBC Driver (typically C:\Program Files\CData\CData JDBC Driver for Azure Data Lake Storage 20XX\lib) or copy the jar file (cdata.jdbc.adls.ADLS.jar) to a new folder in the Sisense JDBC driver directory (typically C:\ProgramData\Sisense\DataConnectors\jdbcdrivers).

1. In the Data page of the Sisense application, create a new ElastiCube (or open an existing one).
2. In the Model Editor, click "+ Data" to open the Add Data dialog box.
3. Click Generic JDBC to open the JDBC settings. 👁 Connecting via JDBC
   
4. Set the connection string property to the JDBC URL for Azure Data Lake Storage, adding required properties.

   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.

   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.

   java -jar cdata.jdbc.adls.jar
   

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

   👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)
   

   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.

   A typical example follows:

   jdbc:adls:Schema=ADLSGen2;Account=myAccount;FileSystem=myFileSystem;AccessKey=myAccessKey;InitiateOAuth=GETANDREFRESH;
   

5. Set the JDBC JARs folder property to the location of the CData JDBC Driver JAR file (see above).
6. Set the driver's class name to the class name for the JDBC Driver: cdata.jdbc.adls.ADLSDriver
7. Leave the username and password properties blank.
8. Click Next. 👁 A configured connection in Sisense (HubSpot is shown).
   

Add Azure Data Lake Storage Data to an ElastiCube

Once you are connected to Azure Data Lake Storage, you can add views to your ElastiCubes.

1. From the Tables list, select the tables and/or views you wish to work with.
2. (Optional) Click "+" to customize the data you want to import with SQL.
3. Click Done. 👁 Selected tables to add to the ElastiCube
   
4. Click Build to build the ElastiCube for analytics.

Visualize Azure Data Lake Storage Data

With Azure Data Lake Storage tables added to your ElastiCube, you can perform analytics on your Azure Data Lake Storage data.

1. Navigate to the Analytics page of the Sisense application
2. Select a Dashboard (or create a new one)
3. Select your Data Source and click Create 👁 Selecting the newly created ElastiCube
   
4. Click "+ Select Data" and choose fields to add to your visualization. 👁 Visualizing data in Sisense (HubSpot is shown).
   

With the CData JDBC Driver for Azure Data Lake Storage, you can access Azure Data Lake Storage data right in Sisense for powerful visualization and analytics. Download a free, 30-day trial and start working with Azure Data Lake Storage data in Sisense today!