Build Pipelines with Live SQL Analysis Services Data in Google Cloud Data Fusion (via CData Connect AI)

Mohsin Turki
Mohsin Turki
Technical Marketing Engineer
Use CData Connect AI to connect to SQL Analysis Services from Google Cloud Data Fusion, enabling the integration of live SQL Analysis Services data into the building and management of effective data pipelines.

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 SQL Analysis Services data for building and managing ELT/ETL data pipelines. This article explains how to use CData Connect AI to create a live connection to SQL Analysis Services and how to connect and access live SQL Analysis Services data from the Cloud Data Fusion platform.

Configure SQL Analysis Services Connectivity for Cloud Data Fusion

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

  1. Log into Connect AI, click Sources, and then click Add Connection
  2. Select "SQL Analysis Services" from the Add Connection panel
  3. Enter the necessary authentication properties to connect to SQL Analysis Services.

    To connect, provide authentication and set the Url property to a valid SQL Server Analysis Services endpoint. You can connect to SQL Server Analysis Services instances hosted over HTTP with XMLA access. See the Microsoft documentation to configure HTTP access to SQL Server Analysis Services.

    To secure connections and authenticate, set the corresponding connection properties, below. The data provider supports the major authentication schemes, including HTTP and Windows, as well as SSL/TLS.

    • HTTP Authentication

      Set AuthScheme to "Basic" or "Digest" and set User and Password. Specify other authentication values in CustomHeaders.

    • Windows (NTLM)

      Set the Windows User and Password and set AuthScheme to "NTLM".

    • Kerberos and Kerberos Delegation

      To authenticate with Kerberos, set AuthScheme to NEGOTIATE. To use Kerberos delegation, set AuthScheme to KERBEROSDELEGATION. If needed, provide the User, Password, and KerberosSPN. By default, the data provider attempts to communicate with the SPN at the specified Url.

    • SSL/TLS:

      By default, the data provider attempts to negotiate SSL/TLS by checking the server's certificate against the system's trusted certificate store. To specify another certificate, see the SSLServerCert property for the available formats.

    You can then access any cube as a relational table: When you connect the data provider retrieves SSAS metadata and dynamically updates the table schemas. Instead of retrieving metadata every connection, you can set the CacheLocation property to automatically cache to a simple file-based store.

    See the Getting Started section of the CData documentation, under Retrieving Analysis Services Data, to execute SQL-92 queries to the cubes.

  4. Click Save & Test
  5. Navigate to the Permissions tab in the Add SQL Analysis Services Connection page and update the User-based 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.
  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 SQL Analysis Services data from Cloud Data Fusion.

Connecting to SQL Analysis Services from Cloud Data Fusion

Follow these steps to establish a connection from Cloud Data Fusion to SQL Analysis Services 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.
  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
  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.
  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.
  11. Run the pipepline created.

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 SQL Analysis Services Data from Cloud Applications

Now you have a direct connection to live SQL Analysis Services 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 SQL Analysis Services data.

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

Ready to get started?

Learn more about CData Connect AI or sign up for free trial access:

Free Trial