Do you rely heavily on GA4 data for analyzing the metrics of your website engagement? If yes, then you would face problems while collecting all the GA4 data and performing advanced analytics on it.
If you want to gain business-critical insights from your GA4 data, then you can’t simply manipulate it. You need to have access to all your marketing and website data in a centralized repository.
This article throws light on two methods for implementing GA4 BigQuery Integration. However, to increase your time to value you can definitely go through the simple two-step process for replicating data from GA4 to BigQuery.
How to set up GA4 BigQuery Integration?
Method 1: Using Hevo Data to Set up GA4 BigQuery Integration
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Hevo Data helps you directly transfer data from Google Analytics 4 and 150+ other sources to a Data Warehouse such as Google BigQuery, or a destination of your choice in a completely hassle-free & automated manner. Hevo is fully managed and completely automates the process of not only loading data from your desired source but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss.
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Hevo takes care of all your data preprocessing to set up GA4 BigQuery Integration and lets you focus on key business activities and draw a much more powerful insight on how to generate more leads, retain customers, and take your business to new heights of profitability. It provides a consistent & reliable solution to manage data in real-time and always has analysis-ready data in your desired destination.
Hevo Data focuses on two simple steps to set up GA4 BigQuery Integration:
Step 1: Configure Google Analytics 4 as a Source
- Click PIPELINES in the Navigation Bar.
- Click + CREATE in the Pipelines List View.
- In the Select Source Type page, select Google Analytics 4 as the Source.
- In the Configure your Google Analytics 4 Account page, do one of the following:
- Select a previously configured account and click CONTINUE.
- Click + ADD GOOGLE ANALYTICS 4 ACCOUNT and perform the following steps to configure an account:
- Select your linked Google account.
- Click Allow to grant Hevo access to your analytics data.
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Step 2: Integrate Data into Google BigQuery
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As can be seen, you are simply required to enter the corresponding credentials to implement this fully automated data pipeline without using any code.
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Method 2: Using Google Cloud Platform to Implement GA4 BigQuery Integration
The steps to set up GA4 Bigquery Integration are as follows:
Step 1: Create a Project in Google BigQuery
- Log in to your Google BigQuery account.
- On the menu bar, click on the arrow beside the name of the project getting displayed.
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- A pop-up window will appear with a list of existing BigQuery projects. In the top-left section of the pop-up window, click on the “New Project” option.
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- The New Project window appears. Now, you can set the name and the location of the project.
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- Then click on the “Create” button and the project will be created.
Step 2: Enable GA4 BigQuery Linking
- Log in to your Google Analytics account. For further information about Google Analytics 4, you can follow the Official Documentation.
- Click on Google Analytics 4 Admin option, found in the bottom-left corner of the window.
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- Now, after going to the GA4 Admin panel, click on “BigQuery Linking”.
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- BigQuery Linking window appears. Now, click on the “Link” button beside the search bar.
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- “Create a link with BigQuery” window appears. Now, click on the learn more link.
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- In the next window, scroll down and copy the Service Account Id of the service account given in point 5 of step 1 (firebase-measurement@system.gserviceaccount.com).
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- Now, go back to the “Create a link with BigQuery” window. Then click on the “Choose a BigQuery project” option.
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- Then select the name of the BigQuery project that you want to link with Google Analytics 4.
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- Now, select the Data Location from the drop-down menu.
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- Click on the “Next” button.
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- Now, select the type of Data streams. If you have a mobile app and want to export the user ids to Google BigQuery, you may additionally choose “Include advertising Identifiers for mobile app streams.”
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- Select the frequency of data movement accordingly i.e, either Daily (once a day) or Streaming (continuous export).
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- Now, click on the “Next” button and then review your choices and click on the “Submit” button.
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- Now, the link for the GA4 BigQuery is created.
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Until now, just the GA4 BigQuery linking is accomplished. But they are still not connected. So, you need to create an API.
Step 3: Enable Google Cloud API
- Go to the Google Cloud Console.
- Then in the left navigation pane, go to API & Services and select “Library”.
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- The API Library page appears.
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- Now, if you have not selected the project, then click on the current project name at the top. A separate window with the list of projects appears. Select the project you want to link.
- Now, in the search bar, search for BigQuery API and click on it.
- Now, make sure the BigQuery API is enabled and click on the “Manage” button.
Step 4: Add a Service Account
- From the sidebar menu, select “Credentials”.
- Go to “Create Credentials” and then select the “Service account” option.
- In the Service account name, type firebase-measurement@system.gserviceaccount.com, i.e., the Id already copied in step 2. Then in the Service account ID, write the ID where you want to give access to that account and click on “Create”.
- Now, grant the editor access to the Service account. And then click on “Continue” and select “Done”.
Step 5: Use Google BigQuery with GA4 Data
- After all the procedures, wait for 24 hours for the data set to export to your BigQuery project.
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- You’ll find 2 tables with each dataset. One for continuous export of raw events throughout the day and another for full daily export of events.
- Now, you can run SQL queries on the tables according to your requirements.
Reasons for linking failures
Linking to BigQuery can fail for either of the following two reasons:
- Your organization’s policy prohibits export to the United States. Choose a different location if you’ve chosen the United States as the location of your data.
- Modify your organization’s policy if your organization policy prohibits service accounts from the domain you want to export data from.
Reasons for export failures
There are several reasons due to which your GA4 BigQuery Schema Export may fail, such as:
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Limitations of Using Google Cloud Platform to Implement GA4 BigQuery Integration:
- Customization: There are very few customization options available in Google Cloud Platform products such as BigQuery, Spanner, and Datastore. Problems may arise in case of any difference in your workflow from the way it’s meant to be used without any means to improve performance or to find out what’s happening.
- Application Engine: Google Cloud Platform Application Engine is limited to Java, Python, PHP, and Google Go only.
- Customer Support: GCP’s support isn’t the strongest with respect to handling customer issues. Also, the support fees are quite expensive.
What can you achieve by integrating data from GA4 to BigQuery?
By migrating your data from GA4 to BigQuery, you will be able to help your business stakeholders find the answers to these questions:
- Which Demographic contributes to the highest fraction of users of a particular Product Feature?
- How are Paid Sessions and Goal Conversion Rate varying with Marketing Spend and Cash in-flow?
- How to identify your most valuable customer segments?
Why should you enable the BigQuery linking for GA4?
There are several reasons to allow BigQuery linking for GA4, such as:
- To store your data in BigQuery (Google Cloud) and/or send it to your data warehouse in other clouds like Azure or Snowflake
- To join and enrich your data with other marketing or contextual data
- To visualize your data in tools like Tableau or PowerBI
- To perform advanced analysis
- To use your data as input for (machine learning) models
Frequently Asked Questions (FAQs)
1) Is BigQuery free with GA4?
Everyone who owns a GA4 property i.e. Premium or Standard has access to BigQuery. So, unlike earlier versions of Google Analytics, with GA4, users don’t need to pay an extra fee to connect their GA4 property to their BigQuery project.
2) How to query GA4 data in BigQuery?
After setting up GA4 BigQuery integration, you can easily query your raw events data in BigQuery. You need to go to Google Data Studio and select BigQuery. You can see the list of all the Google Cloud Projects to which you have access. From there you can navigate to the tables and columns. For queries, click on SQL Workspace, and type your queries to filter and display the GA4 data according to your requirements.
Conclusion
Although GA4 provides actionable insights about digital information yet, you would need a better understanding and analysis of your data at a granular level. And also, sometimes that would be required for you to connect the data with third-party applications. This is where you can set up a GA4 BigQuery connection.
This article has touched down 2 methods for setting up GA4 BigQuery Integration. You can carry forward with the manual method if you can take all the responsibility for implementing this integration. However, to have a more seamless integration that is fully automated and completely managed then definitely you can give Hevo a try.
Hevo Data, a No-code Data Pipeline provides you with a consistent and reliable solution to manage data transfer between a variety of sources such as Google Analytics 4, and a wide variety of Desired Destinations such as Google BigQuery with a few clicks.
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Share your experience of understanding the various methods of setting up GA4 BigQuery Integration in the comment section below!
Manisha is a data analyst with experience in diverse data tools like Snowflake, Google BigQuery, SQL, and Looker. She has written more than 100 articles on diverse topics related to data industry.
With around a year of experience, Madan has demonstrated expertise in customer experience management and issue resolution. His contributions to Hevo have significantly enhanced customer satisfaction by providing detailed resolutions to queries and effectively resolving issues, thereby benefiting the company's operations and client relations.