Learning Google Analytics

Chapter 4. Data Storage

Where you store the data for your application is a critical part of your data analytics infrastructure. It can vary from a trivial concern, where you simply use GA4’s native storage systems, to complex data flows where you are ingesting multiple data sources including GA4, your CRM database, other digital marketing channel cost data, and more. Here, BigQuery as the analytics database of choice in GCP really dominates because it has been built to tackle exactly the type of issues that come up when considering working with data from an analytics perspective, which is exactly why GA4 offers it as an option to export. In general, the philosophy is to bring all your data into one location where you can run analytics queries over it with ease and make it available to whichever people or applications need it in a security-conscious but democratic way.

This chapter will go over the various decisions and strategies I have learned to consider when dealing with data storage systems. I want you to benefit from my mistakes so you can avoid them and set yourself up with a solid foundation for any of your use cases.

This chapter is the glue between the data collection and data modeling parts of your data analytics projects. Your GA4 data should be flowing in under the principles laid out in Chapter 3, and you will work with it with the tools and techniques described in this chapter with the intention of using the methods described in Chapters 5 and 6, all guided by the ...