answering-natural-language-questions-with-dbt

To answer business questions using the dbt semantic layer, query metrics and dimensions directly to retrieve data-driven insights like revenue by region or top products without writing manual SQL.

When the semantic layer cannot answer your data query, the system sequentially falls back to modifying compiled SQL, discovering dbt marts, and analyzing manifest or catalog artifacts to retrieve the required insights.

Retrieve revenue by region and perform trend analysis in dbt by asking a natural language question, which triggers a semantic layer query to automatically calculate metrics and dimensions across your models.

Yes, you can discover dbt marts and analyze manifest or catalog artifacts to answer business questions without validating or building models during development, ensuring quick and accurate data retrieval.

You need access to semantic layer tooling, dbt model discovery workflows, and manifest or catalog analysis capabilities to successfully execute semantic-layer queries and retrieve business insights.