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Google BigQuery lets any table in a Google Cloud project act as a custom data source in Adriel: its columns become candidate metrics, breakdowns, and date fields based on their BigQuery type. Connecting it brings customer-side data — orders, signups, internal events, and similar tables not available through standard ad or analytics data sources — directly into dashboards.

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Before you connect

The following are required:
  • A Google account with read access to the target BigQuery dataset. The BigQuery Data Viewer and BigQuery Job User roles are sufficient.
  • The Google Cloud project, dataset, and table to connect.
  • An optional pre-filter clause, if every query should be scoped to a fixed WHERE condition (for example, a tenant column).
  • Workspace permission to add a new data source.
Queries run live on demand each time a widget loads, and each query is billed by Google Cloud. Identical queries are served from a short result cache for 10 minutes to limit redundant scans.

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Connect Google BigQuery

1

Authorize a Google account

On the Data Sources page, search for Google BigQuery and select it. Click Sign in with Google in the pop-up and sign in with the account that has read access to the target dataset. Click Continue to grant the requested BigQuery scope. Authorization returns to the data source setup screen.
2

Choose the project, dataset, and table

On the data source settings, choose the Project, Dataset, and Table to connect. Only projects and datasets readable by the authorized Google account appear. Each table becomes its own data source.
3

Add a pre-filter (optional)

Configure a pre-filter to scope every query against this data source — either a free-form WHERE clause or a column-level filter. The two modes are mutually exclusive.
4

Submit

Click Submit to validate the connection and finalize the data source. Initial data availability can take up to one business day.

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What gets imported

Table columns become available as metrics or breakdowns depending on their type. A synthetic rowCount field returns COUNT(*) for total-row dashboards. Date-typed columns can be mapped through Blend Data settings to drive widget-level date filtering. For supported column types, query behavior, filter operators, and the full field model, see the Google BigQuery data reference.

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Troubleshooting

The OAuth refresh token has been revoked — usually because the Google account lost access, its password changed, or the connection was revoked from Google account permissions. The data source is automatically disconnected when this fires. Reconnect via Connections → Google BigQuery → Reconnect.
A pre-filter configured at connection time runs on every query. If the clause references a missing column or filters on an incorrect value, no rows match. Edit or remove the filter in the data source settings.
Each query is limited to 1,000 rows for stability and performance. Narrow the query with a pre-filter or a mapped date column so the rows that matter fall within the cap.
Every widget triggers a live query, and each query is billed by Google Cloud. Map a date column through Blend Data so queries scan less data, reduce the number of BigQuery-backed widgets, and use unfold actions sparingly. Identical queries within a 10-minute window are cached automatically.

Google BigQuery data reference

Column types, query behavior, filter operators, and the full field model.

Google BigQuery FAQs

Common questions and expected behaviors for the Google BigQuery data source.

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