How to Link GA4 to BigQuery (Step-by-Step Guide)

The Google Analytics BigQuery export allows you to send raw event-level analytics data directly into BigQuery for advanced analysis and SQL reporting.

In this guide, you’ll learn:

why analysts use BigQuery instead of only the GA4 interfaceGoogle Analytics 4 (GA4) allows you to export raw event-level data to BigQuery for in-depth analysis. Below are the steps to set up the export, along with examples.

• how GA4 BigQuery export works
• how data is stored
• daily vs intraday tables
• export limitations

Step 1: Create a Google Cloud Project

1. Go to the Google Cloud Console.
2. Click Select a project > New Project.
3. Enter a Project Name (e.g., “GA4-BigQuery-Project”).
4. Choose an organization and location, then click Create.
5. Once created, go to the project dashboard.

Example: If your company is “ABC Retail,” name the project “ABC-Retail-GA4.”

Step 2: Enable BigQuery API

1. Navigate to APIs & Services > Library.
2. Search for BigQuery API and click Enable.

Step 3: Set Up BigQuery Billing

1. Go to Billing in Google Cloud Console.
2. Link a billing account if not already linked.
3. Ensure you’re on the free tier if just testing.

Step 4: Link GA4 to BigQuery

1. Open Google Analytics Admin.
2. In Admin, go to the Property Settings of your GA4 account.
3. Under Product Links, click BigQuery Links.
4. Click Link and follow these steps:
   • Select the Google Cloud project created earlier.
   • Choose a Region for your BigQuery dataset (e.g., US or EU).
   • Select Daily Export (recommended) or Streaming Export.
   • Click Submit.

Example: If your GA4 property tracks e-commerce events, you may want to enable both daily and streaming exports to analyze real-time transactions.

Step 5: Verify Data in BigQuery

1. Go to the BigQuery Console.
2. Expand your project and look for the dataset (e.g., analytics_XXXXXXXX).
3. Click on a table (e.g., events_YYYYMMDD) and run a simple query:

SELECT event_name, COUNT(*) AS event_count
FROM `your_project.analytics_XXXXXXXX.events_YYYYMMDD`
GROUP BY event_name
ORDER BY event_count DESC;

4. Click Run to see the results.

Note: After linking Google Analytics to BigQuery, it can take approximately 24–48 hours for your first export tables and event data to appear in BigQuery.

Step 6: Automate and Optimize Data Usage

• Set up scheduled queries to extract insights regularly.
• Use BigQuery ML for predictive analytics.
• Integrate with Data Studio for visualization.

Things to Keep in Mind

• The export is NOT retroactive; it only starts from when you enable it
• If you enable it today, you only have data from today forward in BigQuery
• Historical data stays in GA4 UI only (up to 14 months)
• Action: enable the export as soon as possible, even if you’re not ready to queryData Retention: GA4 retains data for 14 months by default; adjust settings accordingly.
• Cost Considerations: BigQuery charges based on query processing and storage; monitor usage to avoid unexpected costs.
• Streaming vs. Daily Export: Streaming is useful for real-time analytics but incurs higher costs.
• Permissions: Ensure proper IAM roles are assigned for security and data access control.
• Data Transformation: GA4’s event-based model differs from Universal Analytics; plan queries accordingly.

Once your GA4 export is connected to BigQuery, you can move beyond standard GA4 reports and begin building custom attribution models, user journeys, advanced funnels, and marketing dashboards using raw event-level data.

FAQs

Is GA4 BigQuery Export Free?

Yes, GA4 standard properties can export event-level data to BigQuery.

Does GA4 Export Historical Data to BigQuery?

No. Export starts only after linking is enabled.

What Is the Difference Between Daily and Intraday Tables?

Daily tables are finalized exports while intraday tables update throughout the day.

Why Use BigQuery Instead of Only GA4 Reports?

BigQuery provides raw event-level access, SQL flexibility, and advanced analytics capabilities.

Next Step: Learn the GA4 Schema

Now that your export is connected, the next step is understanding:

• event tables
• nested fields
• event_params
• UNNEST
• user identifiers

Without understanding the schema, GA4 SQL becomes difficult quickly.