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. Thanks!
