Traditionally, obtaining user data for analysis was a complex and time-consuming task. However, Google has simplified this process with the introduction of User Data Export in BigQuery. This feature allows organizations to access valuable data, including audience insights, predictive metrics, and user activity timestamps.
BigQuery is a potent tool that can be used for many reasons. In this article, we will describe the main benefits of considering BigQuery as the heart of your data analytics platform.
Although GA4 and UA are both web analytics tools used primarily for tracking website and app activity, BigQuery is mainly used for storing and analyzing large amounts of data.
One of the benefits of Google Analytics 4 is that free accounts also can export data to BigQuery. Before you can export data to BigQuery you have to create a Google Cloud Platform (GCP) which is a set of cloud computing services. In this article, we will go through the process of creating a GCP project.
Much has been written about the pros and cons of Google Analytics 4. However, in this article, we’ll take a look at one of the key features that only 360 accounts can enjoy in Google Analytics Universal. That feature is the export to BigQuery.