Validation Checks

1. Dimension null checks

Ensure that there are no null values for registration_date, activity_date and any segment dimensions.

2. Monthly gross revenue check

Group by monthly granularity of date_activity and sum gross_revenue_primary. Check that the total values match your internal accounting and dashboards for monthly revenue.

3. Monthly marketing

spend check

Group by monthly granularity of date_activity and sum marketing_spend. Check that the total values match your internal accounting and dashboards for monthly marketing spend.

4. Daily active users check

Group by monthly granularity of date_activity and sum active_users. Check that the total values match your internal dashboards for DAU.

5. Check revenue only on active days

Check that no rows exist which have gross_revenue_primary and no active_users or active_payers (depending on which fields provided).

6. Check active_users >

active_payers

If both fields are provided, ensure that active_users >= active_payers. Check this at a segment level.

7. Check active_users

always smaller than

cohort_size

Check that active_users for all instances where registration_date != activity_date is less than active_users where registration_date = activity_date, i.e. cohort_size. Check this at a segment level.

8. Marketing spend only

provided by calendar

date

Check that marketing_spend is null when registration_date != activity_date as marketing_spend is provided as a calendar date time series and not at a cohort level by days since registration.

9. Active user value for

first day of any cohort

with data in

Check that day 0 (where activity_date = registration_date) has an active_user value if any rows exist with data for the registration_date in question. Check this at a segment level.

10. Check no activity data

before start of cohort

Check that no rows exist where activity_date < registration_date.