What I will show you in this article is how to use Power BI to connect to your favorite web performance monitoring service Google Analytics. It is true that this service already has its own web interface but sometime you might want to edit your data prior to visualization or create your own reports.

Connecting to Google Analytics using Power BI

First way of how to work with data is connect directly from cloud service to a Google analytics account using authentication protocol Auth2. This way, we get connected to Google API which will send us the data.

We need:

  1. Power BI account (free)
  2. Google analytics account with data history so we can analyze it


  1. Connect to Power BI account
  2. Choose “Get data”
  3. Services
  4. Choose Google analytics
  5. Log in using OAuth2 protocol
  6. Look at premade dashboard and create own graphs

google analytics power bi

This is certainly the easiest way. Reason for it is that basic Google analytics dashboard will be generated automatically if we connect directly from cloud power bi service. This is not the case for the second option. But this goes in exchange for higher variability.

There is useful info on Google analytics connector on webpage powerbi.com or exceltown.com

Connecting to Google Analytics using Power BI Desktop

Second option of data analyzing from Google analytics is connecting through Power BI desktop app. Link to download here


  1. Install and launch power BI desktop
  2. Get data
  3. Choose Google Analytics source
  4. Choose dimensions and metrics of our interest
  5. Choose visualizations

Downsides of Connecting to Google Analytics API

There is a set of restrictions (maximal number of sessions etc.) The most important restrictions concerning reporting architecture are those:

  1. High-traffic web pages can cause google analytics API to sample the data. In cases like that, only thing you can do is to shorten the observed period or to download the data daily to a data storage and follow that by reporting via Power BI or else.
  2. Restriction of dimensions (7) and metrics (10) which can be chosen in 1 API call. It is therefore important to think everything through in advance. This restriction can make reporting architecture very complicated. (you need to do more views)
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Ing. Jan Zedníček - Data Engineer & Controlling

My name is Jan Zedníček and I have been working as a freelancer for many companies for more than 10 years. I used to work as a financial controller, analyst and manager at many different companies in field of banking and manufacturing. When I am not at work, I like playing volleyball, chess, doing a workout in the gym.

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