Analyze Azure Data Lake Storage Data in Cognos Analytics

Cognos Analytics, powered by IBM Watson®, empowers users to cleanse and establish connections with their data while creating visualizations. When integrated with CData Connect AI, users gain immediate, real-time connectivity between cloud-based data sources and Cognos Analytics, facilitating data management, visualization, analytics, and more. This article provides step-by-step guidance on connecting to Azure Data Lake Storage via CData Connect AI and subsequently analyzing Azure Data Lake Storage data within Cognos Analytics.

NOTE: These instructions require Cognos Analytics 11.2.4 or higher

CData Connect AI offers a dedicated cloud-to-cloud interface for Azure Data Lake Storage, enabling users to perform real-time analysis on Azure Data Lake Storage data within Cognos without the need to replicate data to a natively supported database. Equipped with built-in optimized data processing capabilities, CData Connect AI efficiently directs all supported SQL operations, including filters and JOINs, directly to Azure Data Lake Storage. This harnesses server-side processing to promptly provide the requested Azure Data Lake Storage data.

Configure Azure Data Lake Storage Connectivity for Cognos Analytics

Connectivity to Azure Data Lake Storage from Cognos Analytics is made possible through CData Connect AI. To work with Azure Data Lake Storage data from Cognos Analytics, 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
   

Add a Personal Access Token

When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. It is best practice to create a separate PAT for each service to maintain granularity of access.

1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create. 👁 Creating a new PAT
   
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, you are ready to connect to Azure Data Lake Storage data from Cognos Analytics.

Connect to Azure Data Lake Storage from Cognos Analytics

The steps below outline connecting to CData Connect AI from Cognos Analytics to analyze live Azure Data Lake Storage data.

Download and install the CData Connect AI JDBC driver

1. Open the Integrations page of CData Connect AI.
2. Search for and select JDBC.
3. Download and run the setup file.
4. When the installation is complete, copy the JAR file (cdata.jdbc.connect.jar) from the installation directory (e.g., C:\Program Files\CData\JDBC Driver for CData Connect\lib) to the "drivers" folder in your Cognos Analytics installation directory.

Configure the Connection to CData Connect AI

1. Open IBM Cognos and navigate to Manage > Data server connections.
2. Click the icon to add a data server.
3. Select CData Connect AI.
4. Set JDBC URL to the appropriate connection string. For example:

    jdbc:connect:AuthScheme=Basic;user=username;password=PAT;
    

5. Set Driver class name to "cdata.jdbc.connect.ConnectDriver"
6. Create and store authenticate credentials by selecting an authentication method
   • Set Username to your CData Connect AI username (e.g., [email protected])
   • Set Password to the PAT you previously generated.
7. Click Test connection to confirm that the connection succeeds. 👁 Connecting to CData Connect AI from Cognos Analytics
   

At this point, you are ready to analyze and visualize Azure Data Lake Storage data in Cognos Analytics. For more information about using Cognos Analytics, please refer to the Cognos Analytics documentation.

Live Access to Azure Data Lake Storage Data for Analytics

Now you have a direct, cloud-to-cloud connection to live Azure Data Lake Storage data from Cognos Analytics. You can create new visualizations, build reports, and more — without replicating Azure Data Lake Storage data.

Try CData Connect AI and get real-time data access to hundreds of SaaS, Big Data, and NoSQL sources directly from your cloud applications.