You can see the same pattern of two-step aggregation with the HLL_COUNT family of functions in BigQuery: https://cloud.google.com/bigquery/docs/reference/standard-sq...

This is really useful for this kind of metric (distinct count) that can't be trivially aggregated. It allows generating pre-aggregated tables containing the intermediate aggregation state. Now you can compute your DAUs, WAUs and MAUs from the same daily pre-aggregates.

I wish this design was generalized in SQL. For instance, getting the same family of function for variance computation would be super useful for efficient & correct computation of confidence intervals at different levels of aggregation.