事件 'first_open' 的 BigQuery 到 Data Studio 差异
BigQuery to Data Studio discrepancy for event 'first_open'
我们已将数据从 Firebase Analytics（事件）导出到 BigQuery 以便在 Data Studio 中使用。
当我们尝试使用 Firebase 控制台将数据与 BigQuery/DataStudio 匹配时，字面意思是 每个 事件总数匹配，first_open 事件除外。
有什么解释吗？
这是 Firebase 支持人员的回答：
Discrepancies after linking Analytics data with BigQuery are to be expected. You can try using the following best practices to get better results:
- Instead of using user_id, make use of user_pseudo_id (which is the user identifier for Analytics reports).
- Use the table for a specific day instead of using a date comparison on the event timestamp in the WHERE clause. The event timestamp is based on client device time, which is often skewed.
- Never compare events like session_start or user_engagement that are triggered quite often.
- Always get a report past 3 days so that the data exported from GA4F to BigQuery gets normalized. Data is only exported to BigQuery once per day. And so, queries which include the most recent three days will show different results between Analytics and BigQuery.
Also, Google Analytics for Firebase is using HyperLogLog (HLL) proximation algorithm to calculate the user count. This provides more flexibility when filtering user metrics by user properties and audiences, but could cause the discrepancy in the event count.
我们已将数据从 Firebase Analytics（事件）导出到 BigQuery 以便在 Data Studio 中使用。
当我们尝试使用 Firebase 控制台将数据与 BigQuery/DataStudio 匹配时，字面意思是 每个 事件总数匹配，first_open 事件除外。
有什么解释吗？
这是 Firebase 支持人员的回答：
Discrepancies after linking Analytics data with BigQuery are to be expected. You can try using the following best practices to get better results:
- Instead of using user_id, make use of user_pseudo_id (which is the user identifier for Analytics reports).
- Use the table for a specific day instead of using a date comparison on the event timestamp in the WHERE clause. The event timestamp is based on client device time, which is often skewed.
- Never compare events like session_start or user_engagement that are triggered quite often.
- Always get a report past 3 days so that the data exported from GA4F to BigQuery gets normalized. Data is only exported to BigQuery once per day. And so, queries which include the most recent three days will show different results between Analytics and BigQuery.
Also, Google Analytics for Firebase is using HyperLogLog (HLL) proximation algorithm to calculate the user count. This provides more flexibility when filtering user metrics by user properties and audiences, but could cause the discrepancy in the event count.