Integrate with Live SQL Analysis Services Data in MuleSoft (via CData Connect AI)

The MuleSoft Anypoint Platform enables the building, deployment, and management of APIs and integrations, facilitating seamless connectivity across applications and systems. When combined with CData Connect AI, it provides access to SQL Analysis Services data for visualizations, dashboards, and more. 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 MuleSoft Anypoint Platform.

Prerequisites

Before configuring and using MuleSoft with CData Connect AI, you must first connect a data source to your CData Connect AI account. For more information, see the Connections section.

Additionally, you need to generate a Personal Access Token (PAT) on the Settings page. Be sure to copy it down, as it serves as your password during authentication.

Configure SQL Analysis Services Connectivity for MuleSoft

Connectivity to SQL Analysis Services from MuleSoft is made possible through CData Connect AI. To work with SQL Analysis Services data from MuleSoft, 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 Mulesoft.

Connecting to CData Connect AI

Follow these steps to establish a connection from Mulesoft to CData Connect AI through the JDBC driver:

1. Download and install the CData Connect AI JDBC driver.
   • Open the Integrations page of CData Connect AI.
   • Search for and select JDBC.
   • Download and run the setup file.
   • When the installation is complete, the JAR file can be found in the installation directory (inside the lib folder).
2. Log into Mulesoft Anypoint Studio or launch the desktop application.
3. Create a new Mulesoft project. The new project appears in a project folder.
4. In the Mule Palette located on the right, drag an HTTP Listener to the Message Flow area.
5. Click on the HTTP Listener to configure it.
6. Click the + sign on the right of Connector configuration. The HTTP Listener config dialog appears.
7. Configure the HTTP Listener, providing a Port on which to query your data, and click OK.
8. Provide a path on which to perform the actions. The HTTP Listener is now configured.
9. In the Mule Palette on the right, type database in the search bar.
10. Drag the database operation you want to perform to the Message Flow area. For this example, we choose Select.
11. Select Generic Connection from the Connection dropdown in the Database Config dialog.
12. Click the Configure button to configure the JDBC driver. Select Use local file from the drop-down list.
13. Locate the CData Connect AI JAR file from the JDBC driver installation and click OK.
14. Provide the following information:
    • URL: the URL for the connection, for example:

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

      Note: the password is the PAT created in the Prerequisites section.
    • Driver class name: Enter the Driver class name as:

       cdata.jdbc.connect.ConnectDriver

      
15. Click Test Connection.
16. If the connection is successful, provide the SQL Query Text in the editor. You can see the table metadata on the right side in the Output tab.
17. In the Mule Palette, drag Transform Message to the Message Flow area.
18. Click Transform Message to configure it. Change the Output as follows:
19. Save your project and run it. In the console, Mulesoft starts initializing the dependencies.
20. Once you see the message, "Message source 'listener' on flow your_project_name successfully started", you can start querying your data at the endpoint you provided.
21. Query to check out the data using the Postman application (as shown below).

SQL Access to SQL Analysis Services Data from Cloud Applications

Now you have a direct connection to live SQL Analysis Services data from MuleSoft Anypoint Platform. You can create more connections to ensure seamless data flow, automate business processes, and manage APIs - 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.