i think i know the answer, but thought i would ask anyway.
I have 2 data sets, 1 is member activity the other is emails. i want to build a simple guardrail report, that checks to see that every active member received 1 email.
I can’t easily join the datasets because it becomes a many-to-many join and the whole thing is unmanageable and i would prefer not to have to maintain multiple separate datasets for individual visuals.
is there a way to compare to aggregated numbers from two separate datasets?
i.e. KPI gauge - the target is Total active members, value is total emails.
I can’t unfortunately, 1 is a sql query from a Postgres db and the other is a mongoDB backup, so I can’t join them easily without going through a whole AWS Glue ordeal upstream. This is what I’m trying to avoid, but increasingly looking like its the only option
Not sure how much of an analysis you can do without joining the datasets.
What you can try is bringing both the datasets into analysis . You can then filter both the dataset visuals on email address and see how far that gets you.
