Datasources
Manage catalog, knowledge files, and components for each datasource.
Each datasource can have its own context.
This lets Querio understand one datasource differently from another, even when the same business term appears in both places.
Catalog
The catalog is a JSON-backed map of your datasource.
Querio turns it into UI tabs so it is easier to navigate, but conceptually it is one structured catalog file.
The catalog includes:
- Schemas
- Tables
- Columns
- Joins
- Descriptions
- Agent access controls
Schemas
Schemas group tables inside a datasource.
Use schema descriptions to explain the broad purpose of a schema and when Querio should use it.
Tables
Tables are the core objects Querio queries.
Use table descriptions to explain what the table represents, what grain it has, and when it should or should not be used.
Columns
Columns describe the fields inside a table.
Use column descriptions to explain business meaning, expected values, and any caveats.
Joins
Joins explain how tables relate to each other.
Good join context helps Querio avoid incorrect joins and makes multi-table analysis more reliable.
Knowledge Files
Knowledge Files are files Querio reads as context.
They can be Markdown, SQL, or Python, but their job is to explain how your business and data work so the agent can reason better.
Examples:
- Metric definitions
- Business rules
- Data caveats
- SQL examples
- Python examples
- Team-specific analysis notes
Components
Components are reusable building blocks you can call from cells or workflows.
They are different from Knowledge Files because they are meant to be used, not just read.
Think of components like reusable functions for analysis.