Differences between GA and BigQuery data

In the article “Bridging the gap between Google Analytics UI and BigQuery export” Minhaz Kazi, a developer advocate for Google Analytics, provides an explanation for why the numbers in BigQuery event export data may not match the standard reporting surfaces in Google Analytics. The article clarifies that while the intended purpose of BigQuery event export data is to provide users with more customized options for data analysis, the standard reporting surfaces use pre-processed database tables, which include Google Analytics’ value additions such as modeling and traffic attribution, and thus these two data sources are not always expected to be reconcilable.

The article then explains several specific reasons why the numbers may differ, including sampling and technical implementation, and offers ways to mitigate these differences.

Bonus: GA4SQL

GA4 SQL is a user-friendly online tool that simplifies the process of querying Google Analytics 4 data in BigQuery, allowing users to analyze reports without complex SQL coding. Sub-queries are preferred over CTEs for query building because of the flexibility and functionality they offer. The data in GA4 UI differs from BigQuery data due to several processing stages, including value additions like Google Signals, modeling, and prediction, that the former undergoes. Certain metrics or dimensions may be disabled and cannot be selected in the tool to ensure accurate results.

Panagiotis

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Panagiotis (pronounced Panayotis) is a passionate G(r)eek with experience in digital analytics projects and website implementation. Fan of clear and effective processes, automation of tasks and problem-solving technical hacks. Hands-on experience with projects ranging from small to enterprise-level companies, starting from the communication with the customers and ending with the transformation of business requirements to the final deliverable.