Setup
Confirm prerequisites
A Google Cloud project with the BigQuery API enabled.
A service account with a JSON key file.
Grant the required permissions
Grant the service account these IAM roles on the project (or on specific datasets if you prefer tighter scoping):
- BigQuery Job User (
roles/bigquery.jobUser) — required to run query jobs - BigQuery Data Viewer (
roles/bigquery.dataViewer) — required to read table and view data
roles/datacatalog.categoryFineGrainedReader) on the relevant policy tags to read protected columns.Add the connection in Duvo
On the Connections page, open BigQuery and fill in these fields:
The full contents of your service account JSON key file. Open the downloaded
.json file in a text editor, copy everything, and paste it here. The JSON must include project_id, client_email, and private_key fields.Capabilities
- Run SQL queries — Execute standard SQL against any dataset and table your service account can access, including aggregation and filtering queries.
- Explore schemas — List available datasets, tables, and column definitions using BigQuery’s
INFORMATION_SCHEMAviews. - Export results — Query results are automatically saved as files in your workspace, optimized for efficient downstream processing by your agent.
Key Benefits
- Direct warehouse access — Query petabytes of data without manual exports or CSV downloads.
- Real-time insights — Pull current metrics and KPIs straight from your data warehouse into automated workflows.
- Secure, scoped access — Service account permissions control exactly which projects and datasets your agents can reach.
- Data-driven automation — Combine warehouse data with other connections to make intelligent decisions within a workflow.
Works Well With
Google Sheets
Query BigQuery for raw data, then write summaries or reports into a spreadsheet for stakeholders.
Slack
Pull key metrics from your warehouse and post automated updates to team channels.
Gmail
Generate data-driven reports from BigQuery and email them on a schedule.