Google BigQuery is a serverless data warehouse built for fast SQL analytics over large datasets. Connecting BigQuery to Duvo lets your assignments query your data warehouse directly, pulling metrics, running analyses, and feeding results into automated workflows.
Setup
Prerequisites
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
If your tables use column-level access control, the service account also needs the Data Catalog Fine-Grained Reader role (roles/datacatalog.categoryFineGrainedReader) on the relevant policy tags to read protected columns.
Connection Fields
| Field | Description |
|---|
| Service Account | 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. |
Treat the service account JSON key as a secret. Don’t share it or commit it to
source control, and rotate the key in Google Cloud if you suspect it has been
exposed.
Third-Party Documentation
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_SCHEMA views.
- Export results — Query results are automatically saved as files in your workspace, optimized for efficient downstream processing by your assignment.
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 assignments 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.
