Fabi.ai provides robust tools for managing your connected data sources, allowing you to maintain accurate, up-to-date, and well-organized access to your data. Efficient data source management ensures that your AI analyses and workflows always operate with the correct information.
Data sources evolve, and their schemas can change over time. To ensure Fabi.ai always has the most current understanding of your data structure, you can manually trigger a schema refresh. This action forces Fabi.ai to re-inspect your data source and update its internal representation of tables, columns, and data types.When to refresh:
After adding new tables or columns to your database.
After modifying existing table or column names or data types.
If you notice discrepancies between your data source and what Fabi.ai is reporting.
To improve clarity and organization, you can rename your data sources within Fabi.ai. This allows you to use more explicit and user-friendly names that better reflect the purpose or content of the data source.Benefits of renaming:
Clarity: Make it easier for all users to understand what each data source contains.
Organization: Keep your list of connected sources tidy and intuitive.
Consistency: Align data source names with your internal naming conventions.
If a data source is no longer needed or is decommissioned, you can delete it from Fabi.ai. This action removes the connection and prevents any further AI analyses or workflows from accessing that source.Important considerations: Ensure no critical Smartbooks or workflows are actively using the data source before deletion.
Modify the connection parameters and settings for an existing data source. This is useful if your database credentials change, the host address is updated, or other connection-related details need adjustment.Configurable settings may include:
