Different processing methods for Google Analytics data in BigQuery can result in discrepancies between daily export and fresh daily. Discrepancies are expected between the two export types.
Differences in event counts
| Feature | Fresh daily export | Daily export | Differences in export types |
|---|---|---|---|
| Events per user limit (typically encountered when missetting User Id) | Enforce events per user limit continuously. Events exceeding the limit may be dropped throughout the day. | Enforce events per user limit after processing all events for the day. | Different events may be dropped due to the timing of enforcement. |
| Sub and rollup property events filter | May over-filter or under-filter due to limited session context. | Has full session context for filtering. | Potential for over-filtering or under-filtering in streaming processing. Sub and rollups are not covered by the Fresh Daily SLA. |
| Spam events filter | As spam filters are deployed throughout the day, some events will be exported before the filter is deployed. | Applies spam filters after all events are collected for the day. | More spam events might be present in streaming data. |
Differences in event dimensions and metrics
| Feature | Fresh daily export | Daily export | Differences in export types |
|---|---|---|---|
| Active user ID | Determined based on partial events data due to continuous processing. | Determined based on all events for the day. | Possible discrepancies in active_user_id dimension count. |
| Audience evaluation | Evaluated without offline events and audience triggers. | Evaluated with all events, including offline events and audience triggers. | Differences in audience evaluation results. |
| Attribution results | Search Ads 360 (SA360) and app attribution results may not be present | Contains SA360 and app attribution results. | Some widening sources are not available. Discrepancies in attribution are expected given widening differences. |
| Server-side state | Partial data due to continuous processing every 30-60 minutes. | All events from the current data. | Differences in dimensions and metrics that rely on server-side state like engaged_sessions and last_purchase_date. |