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BigQuery
Google Cloud's serverless, scalable data warehouse
Warehouse
How nao works with BigQuery
nao connects directly to BigQuery and reads your full schema on every sync, so the analytics agent always works against your live table and column structure. If you use dbt, nao ingests your manifest automatically: model documentation, lineage, and metric definitions become part of the agent's context with no manual re-documentation.
Queries run in your own BigQuery project using your credentials. Business users ask questions in plain English from the nao Chat UI, Slack, or Teams, and nao generates the SQL, runs it against BigQuery, and returns the answer with the query and data freshness shown alongside it.
What you can do with nao and BigQuery
- Let business users query BigQuery datasets in plain English without writing SQL
- Import dbt model documentation and lineage from your BigQuery project as agent context automatically
- Run nao's evaluation harness against your BigQuery question set before deploying to non-technical users
- Surface generated SQL and source tables on every answer for full transparency and governance
