How do I use BigQuery with GA4 for advanced analysis?
Applies to: Google Analytics 4 (GA4), Google BigQuery
Last updated: May 2025
Problem
You need access to raw GA4 data for advanced queries, custom reports, or large-scale analysis beyond what GA4’s UI and Explorations can provide.
Solution
GA4 supports native integration with Google BigQuery, allowing you to export all event-level data into a warehouse environment. From there, you can write SQL queries, build dashboards, or join with other datasets.
Step-by-Step Guide
Step 1: Set Up a Google Cloud Project
- Go to https://console.cloud.google.com
- Create or select a Google Cloud project
- Enable BigQuery API under APIs & Services
- Ensure billing is enabled for the project
Step 2: Link GA4 to BigQuery
- In https://analytics.google.com, go to your GA4 property
- Click Admin > BigQuery Links
- Click Link
- Select your Cloud project
- Choose:
- Daily export (once per day)
- Streaming export (export data in near real-time; optional, adds cost)
- Review and submit
GA4 will start exporting your data to a dataset named analytics_<property_id> in BigQuery.
Step 3: Explore GA4 Data in BigQuery
Once data starts flowing, use the BigQuery console to run SQL queries.
Example: Top pages by user count
SELECT
event_params.value.string_value AS page_path,
COUNT(DISTINCT user_pseudo_id) AS users
FROM
`your_project.analytics_123456789.events_*`,
UNNEST(event_params) AS event_params
WHERE
event_name = "page_view"
AND event_params.key = "page_location"
GROUP BY page_path
ORDER BY users DESC
LIMIT 10
You can also analyze:
- User journeys
- Funnel drop-offs
- Custom conversions
- Event sequencing
- Join with CRM or ad data
Step 4: Visualize BigQuery Data (Optional)
You can connect BigQuery to tools like:
- Looker Studio
- Power BI
- Tableau
- Google Sheets
Use them to create custom dashboards or reports on top of your raw GA4 data.
Notes
- GA4’s BigQuery export includes every user interaction (event-level data)
- Data is structured by:
events_*tables (daily)- Fields like
event_name,user_pseudo_id,event_params,user_properties
- BigQuery costs are based on storage and query size—be cautious with large datasets
