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Connect BigQuery

Point Flynt at your BigQuery project so datasets and cards have something to query. Requires the Architect tier (T6) or above; everything happens on the Connections page under Build in the sidebar.

What you need​

A Google Cloud service account with permission to run queries in your project (for example the BigQuery Job User and Data Viewer roles), and its key file -- the JSON your Google Cloud admin downloads when creating the service-account key.

Creating the connection​

  1. Open Build → Connections.
  2. Paste the full service-account JSON into the credentials field.
  3. Enter the project ID the queries should run in.
  4. Pick the location of your data (for example EU or US).
  5. Optionally set a default dataset, so SQL can reference table names without the project.dataset. prefix.
  6. Select Save.

Flynt reads the service-account email out of the JSON and shows it back to you, so you can confirm you pasted the right key. The key itself is stored server-side with restricted access and is never displayed again.

Testing it​

Use Test connection on the same page. Flynt runs a one-row test query (SELECT 1) against your project and reports success or the underlying BigQuery error, so a permissions problem surfaces immediately rather than when someone builds their first card.

Running a first query​

With the connection saved, open Build → Datasets and create a new dataset. The editor starts with sample SQL; replace it with a query against your own tables and select Run to preview the result. Saving it is the next step -- see Create a dataset.

Good to know​

  • An organisation has one BigQuery connection. Saving again replaces it.
  • To change the project, location, or default dataset later, edit those fields and save -- you only need to re-paste the JSON when the key itself changes.
  • Disconnecting removes the stored credentials, and saved queries stop working until you reconnect.
  • Spreadsheet data works differently -- it is ingested rather than queried live. See Google Sheets and files.

For result caching, row limits, and query parameters in depth, see the BigQuery reference.