in an effort to fast-track a monthly comparison between Flurry and Firebase event-reporting, I wrote this simple script below to get the monthly 1) Event Count and 2) Count of Unique Users that triggered these events.
In theory the data I get from BigQuery (linked to the same Firebase account), should give the same output as the Firebase Analytics Console below. I only added a random example Screenshot to indicate which events I am talking about.
# My Standard SQL - Script
SELECT
event.name as event_name,
COUNT(event.name) as event_count,
COUNT(DISTINCT user_dim.app_info.app_instance_id) as users
FROM `project_id.com_game_example_IOS.app_events_*`,
UNNEST(event_dim) as event
WHERE (_TABLE_SUFFIX BETWEEN '20170701' AND '20170731')
------ Inclusive for both the start-date and end-date.
GROUP BY event_name
ORDER BY event_count DESC
LIMIT 10;
Results:
- The event_count from the BigQuery output is exactly the same as the output in my console, but the distinct user_count is out by about 5K-10K for most of the events. In theory, the Firebase Analytics Console's users data should line up exactly with the BigQuery-output, but it does not.
My Questions:
- Is my query not correct, or is it that the Analytics Console outputs the wrong data ?
- Can my query be even more optimised ?
- Am I perhaps not considering something like Timestamps?
Thanks!