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Data Source

Data source is the entry point and foundation of AI Data, used to connect external enterprise databases or data platforms with the SERVICEME platform to achieve unified data management and analysis.
By configuring data sources, the platform can recognize external table structures, field types, and metadata information, providing support for subsequent data catalog management and business domain modeling.

Connecting Data Source​

The first step of AI Data is connecting the data source, providing foundational data for subsequent analysis.

  • Supports connecting to various mainstream data platforms, including MySQL, SQL Server, Azure Databricks, etc.;
  • After adding a data source, all tables in this data source can be viewed, and users can selectively check the tables they need to use;
  • The system defaults to synchronizing only metadata (such as table structure and field information), without synchronizing actual data records, ensuring data security;
  • Provides a "Test Connection" feature to ensure data source connectivity is correct;

Data Source Configuration Items Description​

When adding a data source, the following key information needs to be filled in:

  • Data Source Type: Select the database type (such as MySQL, SQL Server, etc.);
  • Connection Address: Connection string or IP of the database server;
  • Database Name: Name of the target database;
  • Username and Password: Account information used for database authentication;
  • Port Number: Port on which the database service listens;

tip
  • After adding a data source, in addition to selecting data tables, views are also supported.
  • Views can integrate data from multiple tables into a virtual table through query logic, suitable for displaying aggregated, filtered, or calculated results, facilitating the construction of more flexible data models.

Common Causes and Troubleshooting Methods for Data Source Connection Failure​

When connecting to an external database, if the test connection fails, you can troubleshoot from the following aspects:

  1. Incorrect Connection Information

    • Check whether the hostname, port, database name, username, and password are correct.
    • Confirm that the database instance allows remote access and that the firewall does not block the corresponding port (e.g., MySQL default 3306, SQL Server default 1433).

  2. Special Characters Not Properly Escaped

    • If the database password contains special characters (such as @, #, %, &, etc.), note that these characters may be parsed as special symbols in the connection string, causing connection failure.
    • It is recommended to URL encode the password when entering it or use quotes to enclose the password field in the configuration to avoid escaping issues.

  3. Network Connectivity Issues

    • Confirm that the service environment where AI Data is located can access the network where the database resides.
    • If the database is in a private network or virtual private network (VNet), configure the correct access policies or whitelist.

  4. Insufficient Database Permissions

    • Confirm that the connection account has read permissions to access the target database and data tables.
    • For cloud databases (such as Azure SQL, Databricks), also check whether the account's Token or access key is valid.

Suggestion:
If multiple tests still fail to connect, check the detailed error logs and provide the error information to the system administrator or database administrator for further troubleshooting.