Analyze MySQL 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 MySQL via CData Connect AI and subsequently analyzing MySQL 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 MySQL, enabling users to perform real-time analysis on MySQL 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 MySQL. This harnesses server-side processing to promptly provide the requested MySQL data.

Configure MySQL Connectivity for Cognos Analytics

Connectivity to MySQL from Cognos Analytics is made possible through CData Connect AI. To work with MySQL data from Cognos Analytics, we start by creating and configuring a MySQL connection.

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

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

3. Enter the necessary authentication properties to connect to MySQL.

   The CData Provider supports connecting to on-premises and cloud-hosted versions of MySQL such as Amazon RDS for MySQL, Google Cloud SQL for MySQL, Azure Database for MySQL, or Oracle MySQL HeatWave. The Server and Port properties must be set to a MySQL server. If IntegratedSecurity is set to false, then User and Password must be set to valid user credentials. Optionally, Database can be set to connect to a specific database. If not set, tables from all databases will be returned.

   SSH Connectivity for MySQL

   You can use SSH (Secure Shell) to authenticate with MySQL, whether the instance is hosted on-premises or in supported cloud environments. SSH authentication ensures that access is encrypted (as compared to direct network connections).

   SSH Connections to MySQL in Password Auth Mode

   To connect to MySQL via SSH in Password Auth mode, set the following connection properties:

   • User: MySQL User name
   • Password: MySQL Password
   • Database: MySQL database name
   • Server: MySQL Server name
   • Port: MySQL port number like 3306
   • UserSSH: "true"
   • SSHAuthMode: "Password"
   • SSHPort: SSH Port number
   • SSHServer: SSH Server name
   • SSHUser: SSH User name
   • SSHPassword: SSH Password

   SSH Connections to MySQL in Public Key Auth Mode

   To connect to MySQL via SSH in Password Auth mode, set the following connection properties:

   • User: MySQL User name
   • Password: MySQL Password
   • Database: MySQL database name
   • Server: MySQL Server name
   • Port: MySQL port number like 3306
   • UserSSH: "true"
   • SSHAuthMode: "Public_Key"
   • SSHPort: SSH Port number
   • SSHServer: SSH Server name
   • SSHUser: SSH User name
   • SSHClientCret: the path for the public key certificate file
   👁 Configuring a connection (Salesforce is shown)
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add MySQL 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 MySQL data from Cognos Analytics.

Connect to MySQL from Cognos Analytics

The steps below outline connecting to CData Connect AI from Cognos Analytics to analyze live MySQL 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 MySQL data in Cognos Analytics. For more information about using Cognos Analytics, please refer to the Cognos Analytics documentation.

Live Access to MySQL Data for Analytics

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