How to Connect Google Analytics to Power BI

Bringing your Google Analytics 4 data into Power BI is a great way to build powerful, customized marketing reports. By pulling GA4's rich website and app metrics into Power BI's versatile visualization canvas, you can create a dashboard that a simple GA4 exploration just can't match. This article will walk you through the primary ways to connect GA4 to Power BI and explain the pros and cons of each method.

Why Connect GA4 to Power BI Anyway?

Google Analytics 4 is a great tool for collecting data, but its built-in reporting can feel restrictive. Many marketers find themselves hitting a wall when trying to build highly specific dashboards. By connecting GA4 to Power BI, you overcome those limitations and unlock a new level of analysis.

Here's what you gain:

• Advanced Visualizations: Power BI offers a much wider and more customizable range of charts, graphs, and tables than the standard GA4 interface. You can build reports that look exactly how you want and tell a clearer story with your data.
• Data Blending: This is a big one. You can combine your GA4 data with data from other sources. Pull in your ad spend from Facebook Ads, sales data from Shopify, and lead info from Salesforce to build a single, unified view of your entire marketing and sales funnel.
• Custom Calculations with DAX: Power BI's Data Analysis Expressions (DAX) language lets you create powerful custom metrics. You can calculate things like complex conversion rates, customer lifetime value, or channel ROI that aren't readily available in GA4.
• Enhanced Sharing and Collaboration: Power BI makes it simple to securely share your dashboards with team members, clients, or stakeholders. You can publish reports to the web, embed them, or schedule automated email updates.

Method 1: Using the Native Google Analytics Connector

The easiest and most direct way to get started is by using Power BI Desktop's built-in connector for Google Analytics. It takes just a few clicks to set up, but as you'll see, it comes with some important limitations.

Step-by-Step Guide

Follow these steps to connect using the native option.

1. Get Data in Power BI Desktop

Open a new or existing Power BI file. In the Home ribbon, click the Get Data button. From the dropdown list, select More.... This will open the main data source window.

2. Find the Google Analytics Connector

In the Get Data window, use the search bar at the top-left to type "Google Analytics." You will see the Google Analytics connector appear. Select it and click Connect.

3. Choose the 2.0 API (Important!)

A dialog box will pop up asking you which implementation to use: 1.0 or 2.0 (Beta). This is a critical step.

• Implementation 1.0 is for the old Universal Analytics (UA). Do not choose this for GA4 data.
• Implementation 2.0 (Beta) is specifically for GA4. Select this option to connect to your GA4 property correctly.

Click OK to proceed.

4. Sign In and Grant Permissions

Power BI will now prompt you to sign in to your Google account. Use the email address that has access to your Google Analytics 4 property. You will then be asked to grant Microsoft Power BI permission to access your Google Analytics data. Click Allow.

5. Navigate Your GA4 Data

Once connected, the Navigator window will appear. At first glance, this part can be confusing because GA4 data isn't presented as simple, pre-built tables.

You'll see a list of your GA4 accounts and properties. Drill down into the property you want to analyze. Instead of finding a "Traffic Report" table, you'll see folders full of available Dimensions (like First User Channel Group, Session Source, Country, Page Title) and Metrics (like Active Users, Sessions, Conversions, Total Revenue).

Your job is to build your own table by selecting the dimensions and metrics you need. For example, to create a report showing sessions by country, you would check the boxes next to Country and Sessions.

Pro Tip: Start small! Avoid the temptation to select every single metric and dimension you might possibly need. The more you select, the slower the query will run, and the more likely you are to hit API limits. Start with just the essentials for one chart - for example, Date, Sessions, and Conversions.

6. Load Your Data

After selecting your desired fields, click Load. Power BI will pull the data from the GA4 API, and the fields you selected will appear in the Fields pane on the right-hand side of your screen. Now you can start dragging and dropping to build visuals!

Limitations of the Native Connector

While the native connector is great for quick analyses and simple dashboards, you will likely encounter its limitations fairly quickly.

• Data Sampling: If you are pulling data over a long time range or from a high-traffic website, Google will often return sampled data to speed up the query. This means your report is based on a subset of your data, making it less accurate and potentially misleading for precise month-end reporting.
• API Quotas: Google's API has limits on how much data you can request in a given period. If your Power BI report has many visuals and is set to refresh often, you may hit these quota limits, causing a refresh to fail.
• Awkward Data Structure: As you saw in the Navigator, you have to build your tables manually by picking from hundreds of dimensions and metrics. This can be less intuitive than connecting to a straightforward database table.
• No Raw Data Access: The native connector provides aggregated data. You cannot access the raw, unsampled, event-level data, which is essential for deep-dive behavioral analysis.

Method 2: Connecting via BigQuery (The Professional's Choice)

To overcome the limitations of the native API connector, the industry-standard best practice is to route your GA4 data through Google BigQuery first. This method gives you access to your raw, unsampled data and is far more robust for serious business intelligence needs.

Why Use BigQuery?

• No Data Sampling: BigQuery contains the raw, hit-level export of all your GA4 data. Zero sampling. Complete accuracy.
• Own Your Data: The data sits in your own Google Cloud project, giving you full control.
• Blazing Fast: BigQuery is designed to handle massive datasets, so queries inside Power BI are often much faster than those hitting the GA4 API directly.
• Avoid API Limits: Since you are querying your own data warehouse, you're no longer constrained by GA4's API quotas.

Steps to Connect Power BI to BigQuery

This process involves two main parts: linking GA4 to BigQuery and then connecting Power BI to BigQuery.

Part 1: Link GA4 to BigQuery

First, you need to set up the data export inside your Google Analytics account.

1. In your GA4 property, go to Admin (the gear icon in the bottom-left).
2. In the Product Links column, click on BigQuery Links.
3. Click the blue Link button. From here, you'll choose a BigQuery project. If you don't have one, the interface will guide you through creating one (you'll need to have a Google Cloud account with billing enabled, though there is a generous free tier).
4. Configure the export settings, choosing the data stream you want to export and how frequently (daily or streaming). Once configured, GA4 will begin sending raw event data to your BigQuery project.

Part 2: Connect Power BI to BigQuery

With data flowing into BigQuery, you can now connect Power BI to it.

1. In Power BI Desktop, go to Get Data > More...
2. Search for and select Google BigQuery.
3. You will be prompted to sign in with your Google Cloud account. Grant the necessary permissions.
4. In the Navigator, you will see a list of your Google Cloud projects. Find the project where your GA4 export resides and navigate to the analytics_####### dataset.
5. You will see tables named events_YYYYMMDD for daily exports. You can select an individual day's table or use custom SQL to query across multiple days or a date range. This gives you direct access to granular, unsampled data.
6. Click Load and start building your report.

While the BigQuery method involves more initial setup and a steeper learning curve (especially if you're new to SQL), it is the most powerful and scalable solution for professional marketing analytics in Power BI.

What About Third-Party Connectors?

If the native connector is too limited but the BigQuery method sounds too technical, a third-party data connector can be a great middle ground. Tools like Supermetrics, Stitch, or Fivetran are built to solve this exact problem.

These services act as a data pipeline. You connect them to your GA4 account, and they pull the data, handle the complexity of APIs and potential sampling, and then deliver it in a clean format to a destination of your choice, including Power BI. They are generally simpler to use than BigQuery but involve an additional subscription cost.

Final Thoughts

Connecting GA4 to Power BI unlocks a world of reporting possibilities, freeing you from the confines of the native GA4 interface. The native connector is perfect for quick, exploratory analysis, while the BigQuery method provides the depth and scalability required for serious, data-driven organizations.

All these methods still involve manually setting up connectors, navigating complex data schemas, and spending time inside a BI tool. We built Graphed because we wanted to eliminate that friction completely. With Graphed, you connect GA4 and your other marketing platforms in a few clicks, then simply describe the dashboard you want in plain English - like "Show me sessions and conversions by traffic source from Google Analytics for the last 30 days" - and the platform builds it automatically, with live data at the ready.