I got table of user purchases and subscriptions with various product skus
along with user attributes in a single table (~1g and 20M rows).
Due to the number of combinations for slicing and dicing the data, it takes
a while to query for churn, retention, etc. on the dataset for various time
periods and product skus selected and makes it not ideal the frontend.
Generating a precomputed table with all the combinations is pretty
exhausting, so I'm look to see if there are any best practices in designing
a schema to overcome these issues.