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You’re correct that GA4 is fundamentally different from Universal Analytics (UA). While UA is primarily session-based, GA4 is structured around event-based data, which changes how filtering and segmenting work. Unfortunately, as of now, GA4 does not have a direct substitute for UA’s segment feature that you use extensively. While it does have a feature known as ‘Audiences’, this doesn’t yet have the same level of flexibility and depth as UA’s segments especially when used in conjunction with APIs like in your case.
Your idea about exporting GA4 data into BigQuery is a good one. In fact, this is one of the direct benefits of GA4 over UA since it allows seamless integration with BigQuery. So, you’ll essentially be pulling your GA4 data directly into BigQuery, and then from there you can use FiveTran to move the data to RedShift. It seems like the segmentation and data manipulation operations could be then handled via SQL in RedShift (which aligns more closely with your strengths) rather than fighting with GA4’s limitations.
Given the current limitations of GA4, it’s difficult to envision achieving similar effectiveness with GA4’s built-in dashboard capabilities by themselves which are significantly different from UA. Therefore, it seems the BigQuery method would not only resolve your immediate problem, but it would provide greater flexibility and scalability moving forward in terms of dealing with raw event data. While it may seem a bit more complicated initially, the increased control over data might offset this.
