What is Google BigQuery?
BigQuery is Google’s data warehouse. As part of the Google Cloud Platform tool suite, BigQuery allows you to host – and exploit – large databases for a very reasonable price and with very good results. In fact, BigQuery can be used for many other things, such as building Machine Learning models or analysing geospatial data.
How Does BigQuery Work with Google Analytics?
Google Analytics tools (GA360 and GA4) have a native integration with BigQuery in order to export your company’s raw analytics data to this warehouse. It is also possible to export data from other sources, such as a CRM like Salesforce or a platform like Google Ads. You can work with this raw data in each of these cases, however don’t forget that most importantly, BigQuery’s potential is not only about exploiting each database separately, but about establishing relationships between them. This is, from our point of view, one of the advantages of working with a data warehouse like BigQuery: to establish relationships between all your data sources and put an end to data silos.
How Can BigQuery Help your Company?
BigQuery can help your company understand and get the most out of your data to support marketing and business decisions. It will set you ahead of the curve in terms of finding new ways to manipulate and utilize your data.
1. Integrate Data from Different Data Sources
BigQuery allows you to enrich and combine Google Analytics data with multiple data sources such as CRM data, product usage statistics or your marketing and advertising costs. Thus, giving you the opportunity to develop a robust end-to-end analytics system, which will become a cornerstone for all data-driven decisions in your company.
2. Understand your Data
When you start using BigQuery, you will gain a better understanding of how Google Analytics data is structured and stored. For example, there is a marked difference between session-based web reports and hit-level data in the warehouse. Being aware of this difference will enable you to take full advantage of your data.
3. Improve Reporting Speed
Thanks to Google’s fast cloud-based infrastructure, BigQuery can go through billions of rows and return an accurate result in a matter of seconds. You can run queries automatically with the help of Google App Scripts, for example, and save the results to the auto-updated table and visualize them with Data Studio. This process can often yield faster and more convenient reports than the standard GA reports.
4. Use a Cost Effective Solution
In addition, BigQuery’s pay-as-you-go cost model, for storage and querying, is unlike other cloud-based data warehouse solutions. Costs are based on usage and not a fixed rate, meaning you will only get charged for what you use.
Exploring Google Analytics data through this warehouse allows for more sophisticated analysis. Exploiting your raw analytics data, calculating your own metrics, objectives, groupings by dimensions, etc. BigQuery is a cost-effective solution that makes it possible to perform detailed ad hoc analysis with your company’s data.
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In case you have questions about the setup of Google’s BigQuery, leave us a message and we will gladly get back to you to discuss your questions and requirements.