Descriptions
The Descriptions tab shows the semantic metadata generated for this data source during semantic extraction. It lists all extracted tables and their columns, along with the descriptions, data types, synonyms, and other attributes the AI uses to understand and query the data.
What Is Shown
Each entry in the Descriptions tab represents a table in the datasource. Expanding a table shows its column-level details.
Table-Level Information
| Field | Description |
|---|---|
| Table name | The name of the table as it exists in the source system |
| Schema name | The schema the table belongs to (for databases that have schemas) |
| Description | A human-readable description of what the table contains. Editable. |
| Sync status | Whether the table's metadata is current — reflects the state after the last semantic extraction |
| Locked | When locked, the table's metadata is protected from being overwritten by future extractions |
| Enabled | When disabled, the table is excluded from AI query generation |
Column-Level Information
For each column in a table:
| Field | Description |
|---|---|
| Column name | The column name as it exists in the source |
| Data type | The column's data type (e.g., VARCHAR, INTEGER, TIMESTAMP) |
| Description | A human-readable description of the column's business meaning. Editable. |
| Synonyms | Alternative names for the column that the AI can recognize in natural language queries |
| Is primary key | Whether the column is a primary key |
Editing Descriptions
You can manually edit any description or synonym directly in the Descriptions tab:
- Click the description field for a table or column.
- Edit the text.
- Save the change.
Enriching descriptions is one of the most impactful ways to improve query accuracy. The AI uses these descriptions to understand what each table and column means in business terms.
Examples of useful descriptions:
- Table:
orders→ "Contains all sales orders placed by customers. Each row is one order." - Column:
order_amount→ "The total order value in EUR, excluding VAT. Negative values represent refunds." - Column:
cust_id→ "Foreign key to the customers table (customers.id). Synonym: customer_id, customer number."
Locking
When a table or column description is locked, future semantic extractions will not overwrite it. Use locking to protect descriptions you have manually crafted after confirming they are accurate.
Relationship Hints
Cross-table and cross-datasource relationship hints can be added in column descriptions or at the table level. Since the AI cannot automatically infer foreign key relationships, describing them explicitly improves join-based query generation.
Example: "orders.customer_id links to customers.customers.id"
Best Practices
- Run semantic extraction first — descriptions are generated automatically from the schema.
- After extraction, review and enrich descriptions for tables and columns that are central to your analysis.
- Lock descriptions you have carefully customized to prevent them from being reset.
- Add synonyms for columns with technical or abbreviated names (e.g.,
amt→ synonym:amount,value).