从BigQuery到Data Studio的事件"first_open"差异 [英] BigQuery to Data Studio discrepancy for event 'first_open'

问题描述

我们已经将数据从Firebase Analytics(事件)导出到BigQuery，以便在Data Studio中使用.

We've exported data from Firebase Analytics (events) to BigQuery for use in Data Studio.

当我们尝试通过Firebase控制台使用BigQuery/DataStudio匹配数据时，实际上每个事件的总计数匹配，但first_open事件除外.

When we try to match data with BigQuery/DataStudio with the Firebase console, literally every event total count matches, except for the first_open event.

对此有什么解释吗?

推荐答案

这是Firebase支持的答案:

This was the answer of Firebase Support:

将Analytics(分析)数据与BigQuery链接后，会出现差异.您可以尝试使用以下最佳做法来获得更好的结果:

Discrepancies after linking Analytics data with BigQuery are to be expected. You can try using the following best practices to get better results:

1. 代替使用user_id，而要使用user_pseudo_id(这是Google Analytics(分析)报告的用户标识符).
2. 将该表用于特定的日期，而不要在WHERE子句中的事件时间戳上使用日期比较.事件时间戳基于客户端设备的时间，通常是不正确的.
3. 从不比较经常触发的诸如session_start或user_engagement之类的事件.
4. 始终会在3天后获得报告，以便对从GA4F导出到BigQuery的数据进行规范化.每天仅将数据导出到BigQuery一次.因此，最近三天的查询将显示Analytics(分析)和BigQuery之间的不同结果.

1. Instead of using user_id, make use of user_pseudo_id (which is the user identifier for Analytics reports).
2. 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.
3. Never compare events like session_start or user_engagement that are triggered quite often.
4. 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.

此外，Google Analytics for Firebase正在使用HyperLogLog(HLL)近似算法来计算用户数.当按用户属性和受众过滤用户指标时，这提供了更大的灵活性，但可能导致事件计数上的差异.

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.

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