Connecting BigQuery To Power BI: A Comprehensive Guide

on BI Tool, Data Integration, Tutorials • August 1st, 2020 • Write for Hevo


Do you use Google BigQuery to store data and Power BI as a BI tool? Did you invest several hours on the internet to connect these components? If yes, then this blog will answer your queries. This blog takes you through Google BigQuery, Microsoft Power BI, and steps to connect Google BigQuery to Power BI.

Power BI is a business analytics service by Microsoft. It supports in-built connectors for various sources, including Google BigQuery. We can use this connector to establish the integration. You can either get a copy of your data from BigQuery or get a live connection with your BigQuery data. For this module, you will use a copy of the public data set offered by BigQuery. 

Let’s see how this blog is structured for you:

  1. What is Google BigQuery?
  2. What is Microsoft Power BI?
  3. Prerequisites
  4. Steps to Connect Google Biguery to Power BI
  5. Limitations
  6. Conclusion

What is Google BigQuery?

Google BigQuery is a serverless and fully managed warehouse that enables scalable analysis. It is a Saas that supports querying using ANSI SQL. Petabytes of data can be processed by Google BigQuery easily. It consists of the following three parts: 

  • Storage: Data is stored in tables that can be accessed and analyzed using SQL. It automatically manages all the storage and scaling operations for you.
  • Ingestion: You can upload data from your cloud storage, or build an ETL pipeline and import data in multiple formats. 
  • Querying: ANSI SQL is used for query processing in Google BigQuery.

You can also bypass the steps of storage and ingestion by using BigQuery’s public data sets. The public data sets are third party data sets which are made public so that anyone can query it.

BigQuery offers flexible and scalable pricing based on storage and querying. Read more about the pricing here

What is Microsoft Power BI?

Power BI is a business analytics tool introduced by Microsoft. It is one of the most popular BI tools in the market. It is a collection of apps, software services, and connectors that work together to turn your unrelated data to an interactive and coherent dashboard and report. Power BI uses the Data Analysis Expression (DAX) language. DAX consists of various functions and expressions that are used to build formulas to understand data. Power BI is available as Power BI Desktop, Power BI Service, and Power BI Mobile. You can use any of the available tools for analysis.

Key features of Microsoft Power BI

  1. Customize Visualization: You can create your visualizations using custom visualize SDK.
  2. Multiple Data Sources: Power BI supports inbuilt connectors for more than 100 sources such as Oracle, Azure, SQL Server, BigQuery, etc. For data sources like MongoDB, you can use the ODBC connector as there is no in-built connector in Power BI.
  3. Real-Time: Power BI allows you to access your data in real-time. It helps us grab opportunities and solve problems.
  4. Interactive Models: Everyone in the organization can create interactive reports. To ensure that your audience gets most of your dashboards, you can add custom Q&A buttons. 

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Check out why Hevo is the Best:

  • Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
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  • Hevo Is Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
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  • Live Monitoring: Hevo allows you to monitor the data flow and check where your data is at a particular point in time.


  1. A Google BigQuery account.
  2. A dataset in BigQuery for visualizing.
  3. Power BI Desktop.
  4. You need to have basic knowledge about BigQuery and BI tools.

Let’s see the steps to connect BigQuery to Power BI.

Steps to Connect BigQuery to Power BI

You can connect your BigQuery data to Power BI using the in-built connector provided by Power BI. Follow these steps to achieve the BigQuery to Power BI integration:

  1. In Power BI, select “Get Data” in the home ribbon.
  2. In the Get Data panel, select the “Google BigQuery” and proceed by clicking “Connect”.
BigQuery to Power BI: Get Data
  1. Sign in using your Google BigQuery account and select “Connect”. 
BigQuery to Power BI: Sign In

This is how your screen looks after authentication.

BigQuery to Power BI: Click Connect
  1. In the navigator window, select your data set and click “Load”. 
BigQuery to Power BI: Select Table
  1. In the connection settings, you can select either “Import” or “DirectQuery”. Click “Load”.
BigQuery to Power BI: Select Import or DirectQery
  1. Now, your data is loaded in the Power BI and is ready to visualize.


The following limitations are encountered while connecting BigQuery to Power BI:

  1. If you are using a large data set such as a public data set offered by BigQuery, then it will take a lot of time to load it in Power BI.
  2. Security is an issue as there is no two-factor authentication. You can just sign in and load your data in Power BI.  


In this blog, you have learned about Google BigQuery, Microsoft Power BI, and steps to use the inbuilt connector to connect Google BigQuery to Power BI. You have also learned about the limitations that you will encounter while integrating these two platforms. Google BigQuery is used by various organizations to store their data. But if your data is not on a single platform, and you want to integrate it before analysis, then you can try Hevo.

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Hevo is a No-code Data Pipeline. It connects multiple data sources to Google BigQuery. You can consolidate data in Google BigQuery and then visualize it in Power BI. Hevo supports data integrations from 100+ data sources at a reasonable price.

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Share your experience of connecting BigQuery to Power BI in the comment section below.

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