BigQuery dashboards on live SQL
Connect Widgets PRO to any BigQuery dataset — warehouse, analytics, GA4 export. Write Standard SQL, bind parameters, the result becomes a chart, metric, or table. No semantic layer, no LookML.
Last updated June 2026 · By Widgets PRO Team
Standard SQL widgets
Paste a Standard SQL query, the result becomes a chart, metric, or table. Parameters bind safely (no string interpolation). Sub-second refresh on cached results.
Service-account auth
Connect via Google service account JSON. Scope to specific datasets, give Widgets PRO `bigquery.dataViewer` + `bigquery.jobUser` — least-privilege, audit-friendly.
Query result caching
Widget-level TTL (default 5 minutes, configurable 30s–24h). Expensive aggregations cache server-side, keeping dashboards fast and BigQuery costs predictable.
GA4 export ready
GA4 daily export to BigQuery is supported out of the box. Standard event-table queries (`events_*`, `events_intraday_*`) work without modification.
Cost guard rails
Per-widget bytes-billed estimate before each query runs. Set a workspace-wide cap (e.g., 100 GB/day) — over-limit widgets show a clear error instead of silently burning your warehouse budget.
Multiple projects
Connect prod + staging + per-customer BigQuery projects. Switch in widget config; isolate access via separate service accounts.
For analysts and ops teams who live in BigQuery
You already write SQL against BigQuery every day. The dashboard step is just "wrap that query in a widget, give it a title, drop it in the grid." No new query language, no semantic layer, no LookML to learn.
- Service account + read-only role = safe production access
- Parameter binding for dropdowns, date ranges, customer segments
- CSV export from any chart or table
- GraphQL API + CLI to script dashboards from your warehouse repo
Combine BigQuery with the live SaaS stack
Layer warehouse SQL widgets on a dashboard with Stripe revenue, GitHub deploys, Sentry errors, Plausible traffic. Warehouse data joined with live SaaS data — visually, not in another ETL pipeline.
- BigQuery + Stripe — warehouse-computed cohorts next to live MRR
- BigQuery + GitHub — product metrics next to release cadence
- BigQuery + Plausible — server-side analytics next to client-side
- TV-ready widgets — high-contrast renders for the wallboard
Related
Dashboards for analysts
SQL widgets, multiple warehouses, no BI overhead.
PostgreSQL integration
Direct SQL on managed or self-hosted Postgres — the other half of your data stack.
Plausible integration
Privacy-first analytics — pair with GA4 in BigQuery for full picture.
All integrations
GitHub, Linear, Stripe, Notion, Google Sheets, and more.
Frequently asked questions
Google service account JSON key. Create a service account with `bigquery.dataViewer` (read access to the datasets you expose) and `bigquery.jobUser` (run queries) — paste the JSON in Widgets PRO. Standard Google Cloud IAM pattern.
Two layers: per-widget cache (default 5-minute TTL) avoids re-running queries on every dashboard refresh; per-workspace bytes-billed cap stops a runaway widget from burning credits. Pre-query bytes-billed estimate shows you the cost before execution.
Yes — GA4's daily BigQuery export creates `events_*` tables in your project. Widgets PRO queries them like any other BigQuery dataset. Useful for first-party analytics without GA4 UI limitations.
Yes. BigQuery scheduled queries and materialised views are transparent to Widgets PRO — we just query the resulting table. Pair with our cache for compound speedup: scheduled query refreshes the table daily, widget caches the query result for 5 minutes.