How to Connect Google Analytics 4 to Power BI

Getting your Google Analytics 4 data into Power BI allows you to build comprehensive, custom business dashboards that go far beyond what's possible in the GA4 interface. Combining your web analytics with sales, marketing, and operational data gives you a complete picture of business performance. This tutorial will walk you through the most effective method for connecting GA4 to Power BI so you can create a single source of truth for your reporting.

Why Connect Google Analytics 4 to Power BI?

While GA4 is excellent for tracking website and app user behavior, its reporting interface has limitations. Power BI, a market-leading business intelligence tool from Microsoft, is designed for deep data exploration and visualization. Connecting them provides several powerful advantages:

• A Single Source of Truth: The main benefit is creating holistic dashboards. Imagine a report that shows GA4 user acquisition data alongside lead data from Salesforce, ad spend from Facebook Ads, and revenue from Shopify. This centralized view helps you connect the dots across the entire customer journey.
• Advanced Data Modeling: Power BI allows you to clean, transform, and model your data in ways that just aren't possible within GA4. You can create complex calculated columns, custom measures using DAX (Data Analysis Expressions), and build relationships between GA4 data and other business datasets.
• Unlimited Customization: You are no longer limited by GA4's predefined reports and widgets. In Power BI, you have total control over your visualizations. You can create anything from detailed sales funnel analyses to high-level executive KPI summaries that are fully branded and tailored to your specific needs.
• Automated & Shareable Reports: Once your dashboard is set up, you can schedule automatic data refreshes. Reports and dashboards can then be securely shared with stakeholders across your organization without needing to give everyone access to your Google Analytics account.

Understanding the Connection Methods

Unlike its predecessor, Universal Analytics, GA4 does not have a direct, native Power BI connector built by Microsoft. Let's be honest, this is a point of frustration for many analysts. However, there are established and reliable ways to get the data across. Here are the three main options:

1. Third-Party "Connector" Tools

Various third-party ETL (Extract, Transform, Load) tools like Supermetrics, Fivetran, or Stitch Data can act as a bridge. You connect GA4 to their service, and they pipe cleaned, aggregated data into Power BI.

Pros: Easy to set up, requires minimal technical expertise. The data tables are often pre-cleaned and organized for you.

Cons: A paid subscription is almost always required, and you are limited by the metrics and dimensions the service provider chooses to support.

2. The GA4 Reporting API

For those with development skills, you can use the GA4 Reporting API to pull data directly. This involves writing code (like Python) to make requests to the API and then loading that data into Power BI.

Pros: Highly flexible and customizable. You aren't paying a third-party fee for the connection itself.

Cons: Requires significant technical knowledge, coding, and ongoing maintenance. It is not a realistic option for most marketers, founders, or business analysts.

3. The Google BigQuery Route (Recommended)

This is Google’s intended and most powerful method for getting raw GA4 data into an external analysis tool. BigQuery is a serverless, highly-scalable data warehouse. You can enable a native, free connection that exports all of your raw GA4 event data directly into a BigQuery project. From there, Power BI has a built-in connector to pull data directly from BigQuery.

Pros: This gives you access to the most granular, unsampled, event-level data. It's highly scalable and reliable. Linking and exports are free, and BigQuery's free tier is sufficient for many small-to-medium-sized businesses.

Cons: It requires some initial setup and a basic understanding of how data is structured in BigQuery. The raw data needs cleaning and transformation in Power BI before it’s user-friendly.

For the remainder of this guide, we will focus on the BigQuery method as it offers the best balance of power, cost, and control.

Step-by-Step: Connecting GA4 to Power BI via BigQuery

This process has two main halves: first, linking GA4 to a BigQuery project, and second, connecting Power BI to that BigQuery project.

Part 1: Link Google Analytics 4 to BigQuery

First, we need to instruct GA4 to start sending its raw event data to a BigQuery project. If you don't have a Google Cloud (GCP) account and a BigQuery project yet, create them first - there is a generous free tier.

1. Navigate to your GA4 property and click on Admin in the bottom-left corner.
2. In the Property column, scroll down to the "Product Links" section and click on BigQuery Links.
3. Click the blue Link button. A setup wizard will appear.
4. Click Choose a BigQuery project. A list of your available projects will appear. Select the project you want to export your GA4 data to and click Confirm.
5. Select the data stream(s) you wish to export (usually your main web stream).
6. Under Frequency, you have two options:
7. Review your configuration and click Submit.

That’s it! The link is now active. It takes about 24 hours for the first daily export to complete and for you to see an events_ table appear in your BigQuery dataset.

Part 2: Connect Power BI to Google BigQuery

Once you've confirmed that data tables are appearing in your BigQuery project, it's time to open Power BI Desktop.

1. In Power BI Desktop, go to the Home tab and click on Get Data.
2. In the search box, type "BigQuery" and select Google BigQuery from the list. Click Connect.
3. A new window will pop up. You will need to sign in with the Google Account that has access to your BigQuery project.
4. Once you're authenticated, the Navigator window will appear. It shows you all of the Google Cloud projects you have access to.
5. Expand your project, then expand the dataset linked to your GA4 property (it's typically named something like analytics_PROPERTYID).
6. You will see a list of tables formatted as events_YYYYMMDD. Select one of these tables to preview its data.

Part 3: Loading and Transforming Your GA4 Data

Here’s the part that trips many people up. The raw GA4 data format is not immediately usable for reporting. It's "nested," meaning some columns contain records and lists within them. We need to use Power BI's Power Query Editor to flatten this data.

1. Instead of clicking Load, click Transform Data at the bottom of the Navigator window. This opens the Power Query Editor.
2. You'll see many columns, but the important ones are often event_name, event_params, and geo.
3. Let's say you want to build a simple report showing total sessions by country. You would first filter the event_name column to only show rows where the value is session_start.
4. Now, locate the geo column. Notice the expand icon (two arrows pointing opposite directions) in the column header. Click it.
5. Uncheck "Use original column name as prefix" and select the fields you want, like country, city, and region. Click OK. This "unnests" the data, creating new columns for country, city, and region.
6. Similarly, the event_params column contains valuable information like page title, session ID, and more. You can expand it to extract key-value pairs that are relevant to your analysis.
7. Once you have flattened the data into a usable table format, click Close & Apply in the top-left corner of the Power Query Editor.

Power BI will now load your cleaned data into its data model. You can now drag the country field and the event_name (as a count) onto your report canvas to create a map or table visual showing sessions by country. You have successfully connected GA4 to Power BI!

Tips for Success

• Start Small: The number of columns in the raw events table can be overwhelming. Start with a simple question you want to answer (like sessions by country) and focus only on the columns needed for that analysis.
• Understand Query Folding: When possible, Power BI "folds" your transformation steps in Power Query into a single native query that it sends to BigQuery. This is far more efficient than pulling a massive table into Power BI and then filtering it. Perform filtering and removal steps early in your query process.
• Manage Refresh Schedules: In the Power BI Service (the online version), you'll need to configure your data source credentials so Power BI can refresh your dataset from BigQuery automatically on a schedule you define (e.g., daily).

Final Thoughts

Connecting GA4 to Power BI via BigQuery is the most robust and scalable way to unlock deeper insights from your web analytics. It allows you to break free from GA4's native reporting environment and build comprehensive dashboards that combine web data with all your other critical business metrics in one centralized, auto-updating location.

However, as you can see, this process involves multiple platforms, technical setup, and a steep learning curve in Power Query to wrangle the raw data. At Graphed, we believe getting insights shouldn't require you to become a part-time data engineer. That's why we built our platform to handle all the complexity for you. We connect to your GA4, HubSpot, Facebook Ads, and Shopify data with one click, and you ask questions in plain English like, "show me a dashboard of my marketing funnel from ad click to purchase." Our AI builds the real-time dashboards for you in seconds, saving you from the hours typically spent on manual setup and data wrangling. If you want to skip the complexity and go straight to getting answers from your data, you should check out Graphed.