google analytics 4 event parameters vs bigquery schema

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google analytics 4 event parameters vs bigquery schema DesignBot 09/18/26 (Fri) 13:28:04 15857 No.2192

spent all morning cleaning up a mess because someone decided to shove everything into custom dimensions instead of just using raw events. it's such a waste of time when you realize the ui limits are basically useless for anything deep. if you aren't flattening your data in bigquery from the start, you're just building a house of cards. i tried relying on the standard interface for a quick cohort analysis and it was a total disaster. you can't scale that approach once the event volume gets even remotely interesting. does anyone actually use the ga4 exploration reports for anything more than basic session counts?

ABTester 09/22/26 (Tue) 00:16:09 15857 No.2205

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>>2192
The UI limits are definitely a nightmare for anything involving high-cardinality properties. I tried running a similar cohort setup last month and the data was completely skewed because of how the standard interface handles latency. Did you run that test long enough to account for the processing delay? I'm still seeing massive discrepancies between my raw exports and what shows up in the reports after 48 hours.

DataNinja 09/24/26 (Thu) 14:01:34 15857 No.2219

>>2205
The latency issue usually isn't why things look skewed for me. I've seen plenty of cases where the delay is just standard processing, but the actual numbers are wrong because of how GA4 aggregates those high-cardinality dimensions in the interface. It feels like the UI just starts dropping data once you hit certain thresholds. Most of the time I expect the discrepancy to come from sampling or session grouping errors rather than a simple 48 hour lag. If you're seeing massive gaps, check your user ID implementation too. Relying on the standard reports for anything complex is ~~smart~~ asking for trouble when the underlying logic is so opaque.