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  1. Datasource
  2. Managing Datasource
  3. Structured & Third Party Datasource

Schema Level Configuration Menus

PreviousStructured & Third Party DatasourceNextInformation

Last updated 2 months ago

The Schema-Level Configuration Menus allow users to connect, configure, and manage various data sources at the schema level. Whether working with structured databases (e.g., Redshift, BigQuery) or third-party connectors (e.g., Google Analytics), users can perform a range of actions to customize schema settings and optimize data usage.

The key menu options available for schema-level configuration include:

  • Information (Datasource Overview & Connection Details) View and edit the datasource name, description, and connection settings. Structured databases display credentials like host, port, user, and database, while third-party connectors show account details and linked services.

  • Explore Tables & Configure Schema Settings Browse available tables within a schema, enable/disable specific tables, and configure columns. Modify data types, set indexing preferences, and refine schema structures for efficient querying.

  • Define Joins Establish relationships between tables using Inner, Left, Right, or Full joins. Select tables, define linking columns, and merge data for comprehensive insights.

  • LLM Settings (AI-Powered Query Optimization) Configure LLM-based SQL's by adjusting AI model settings like temperature, top-p, and system instructions to optimize queries.

  • Manage Examples (Query Reference & Training Data) Create and store structured query examples for AI-assisted SQL generation. Improve accuracy by defining user queries and expected SQL outputs.

  • Logs (Query Execution Monitoring) Track execution history, query timestamps, and status (Success/Failure). Monitor verification status and confidence scores for troubleshooting and performance insights.

  • Suggested Questions (Predefined Queries for Quick Insights) Add and display predefined business questions for instant query generation. Enable users to explore data quickly without manually writing SQL.