Build Pipelines with Live Azure Table Data in Google Cloud Data Fusion (via CData Connect AI)

Google Cloud Data Fusion simplifies building and managing data pipelines by offering a visual interface to connect, transform, and move data across various sources and destinations, streamlining data integration processes. When combined with CData Connect AI, it provides access to Azure Table data for building and managing ELT/ETL data pipelines. This article explains how to use CData Connect AI to create a live connection to Azure Table and how to connect and access live Azure Table data from the Cloud Data Fusion platform.

Configure Azure Table Connectivity for Cloud Data Fusion

Connectivity to Azure Table from Cloud Data Fusion is made possible through CData Connect AI. To work with Azure Table data from Cloud Data Fusion, we start by creating and configuring a Azure Table connection.

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

2. Select "Azure Table" from the Add Connection panel
👁 Selecting a data source

3. Enter the necessary authentication properties to connect to Azure Table.

   Specify your AccessKey and your Account to connect. Set the Account property to the Storage Account Name and set AccessKey to one of the Access Keys. Either the Primary or Secondary Access Keys can be used. To obtain these values, navigate to the Storage Accounts blade in the Azure portal. You can obtain the access key by selecting your account and clicking Access Keys in the Settings section.

   👁 Configuring a connection (Salesforce is shown)
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Azure Table 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 Table data from Cloud Data Fusion.

Connecting to Azure Table from Cloud Data Fusion

Follow these steps to establish a connection from Cloud Data Fusion to Azure Table through the CData Connect AI JDBC driver:

1. 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).
2. Log into Cloud Data Fusion.
3. Click the green "+" button at the top right to add an entity.
4. Under Driver, click Upload. 👁 Upload the driver JAR file
   
5. Now, upload the CData Connect AI JDBC driver (JAR file).
6. Enter the driver settings:
   • Name: Enter the name of the driver
   • Class name: Enter "cdata.jdbc.connect.ConnectDriver"
   • Version: Enter the driver version
   • Description (optional): Enter a description for the driver 👁 Enter the driver settings
     
7. Click on Finish.
8. Enter source configuration settings:
   • Label: Helps to identify the connection
   • JDBC driver name: Enter the JDBC driver name to identify the driver configured in Step 6.
   • Connection string: Enter the JDBC connection string, for example:

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

   • User: Enter your CData Connect AI username, displayed in the top-right corner of the CData Connect AI interface. For example, "[email protected]"
   • Password: Enter the PAT you generated on the Settings page. 👁 Enter the source configuration settings
     
9. Click Validate in the top right corner.
10. If the connection is successful, you can manage the pipeline by editing it through the UI. 👁 Build and manage the pipeline in the UI
    
11. Run the pipepline created. 👁 Run the pipeline
    

Troubleshooting

Please be aware that there is a known issue in Cloud Data Fusion where "int" types from source data are automatically cast as "long".

Live Access to Azure Table Data from Cloud Applications

Now you have a direct connection to live Azure Table data from from Google Cloud Data Fusion. You can create more connections to ensure a smooth movement of data across various sources and destinations, thereby streamlining data integration processes - all without replicating Azure Table data.

To get real-time data access to hundreds of SaaS, Big Data, and NoSQL sources (including Azure Table) directly from your cloud applications, explore the CData Connect AI.