Different processing methods for Google Analytics data in BigQuery can result in discrepancies between daily export and fresh daily. Discrepancies of less than 2% 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. |