Connecting GA4 to BigQuery – a step by step guide – Part 2

Google Analytics 4 (GA4) is a powerful tool for tracking user behavior and gaining insights into your website and app performance. However, for businesses and organizations that require more in-depth analysis and customization of their analytics data, integrating GA4 with Google BigQuery is a game-changer. In this blog post, we’ll walk you through the step-by-step process of connecting GA4 to BigQuery and explore the benefits of this integration.

Step 1: Set Up a Google Cloud Platform Project

CHECK OUT PART ONE OF OUR BLOG POST FOR A STEP BY STEP ON HOW TO DO THIS. Before you can connect GA4 to BigQuery, you need to create a Google Cloud Platform (GCP) project. If you haven’t already, sign in to the Google Cloud Console and create a new GCP project or select an existing one.

Step 2: Enable the BigQuery API

In your GCP project, navigate to the “APIs & Services” > “Library” section. Search for “BigQuery API” and enable it. This step ensures that your GCP project can communicate with BigQuery.

Step 3: Link GA4 to BigQuery

Access Your GA4 Property: Log in to your Google Analytics account and select the GA4 property that you want to link to BigQuery.

Admin Settings: In the lower-left corner, click on “Admin” to access the Admin settings for your GA4 property.

Data Streams: Under “Data Streams,” select the data stream you want to link to BigQuery. If you haven’t set up a data stream yet, you’ll need to do so.

BigQuery Linking: In the Data Stream settings, scroll down to the “BigQuery Export” section and click on the “BigQuery linking” tab.

Enable BigQuery Export: Toggle on the “BigQuery Export” option.

Choose a BigQuery Project: Select the GCP project you created or intend to use for this integration.

Dataset Name: Choose or create a BigQuery dataset where your GA4 data will be stored.

Table Name: Define a table name for your GA4 data within the selected dataset.

Export Event Data: You can choose to export both event data and user data or just event data, depending on your needs.

Schema Mapping (Optional): If you want to customize the schema of your exported data, you can use the “Schema Mapping” option to specify the fields and data types.

Save and Enable: Click “Save” to save your settings, and then toggle on the “Export to BigQuery” option to enable the integration.

Step 4: Data Transfer and Analysis

Once you’ve completed the setup, GA4 data will start flowing into BigQuery. You can use SQL queries or data visualization tools like Data Studio or Tableau to analyze the data, create custom reports, and gain deeper insights into user behavior, conversions, and other key metrics.

Benefits of GA4 and BigQuery Integration:

Advanced Analysis: BigQuery’s querying capabilities allow for more in-depth analysis of your GA4 data, including complex joins, custom calculations, and predictive modeling.

Custom Reporting: Create custom reports and dashboards tailored to your specific business needs.

Data Retention: Control data retention and archiving settings in BigQuery to store historical data for as long as necessary.

Scalability: BigQuery scales effortlessly to accommodate growing data volumes as your business expands.

Machine Learning Integration: Leverage BigQuery’s machine learning capabilities to make data-driven predictions and insights.

Conclusion

Integrating Google Analytics 4 with Google BigQuery empowers businesses to unlock the full potential of their data. By following the steps outlined in this guide, you can seamlessly connect GA4 to BigQuery and harness the power of advanced analytics, custom reporting, and data-driven decision-making. This integration is a valuable asset for any organization looking to gain a competitive edge in today’s data-driven landscape.