This has been a game changer for us. When our analysts run queries on parquets using Arrow they are orders of magnitude faster than equivalent SQL queries on databases.
Were you working off proper data warehouses, or just the transactional db?
I ask because something a lot of people miss here is how much performance you can get from the T part of ETL. Denormalizing everything into big simple inflated tables makes things orders of magnitude faster. It matters quite a bit what your comparison is against.
We saw major improvements when we simply wrote full tables from a transactional database to parquet, but also, as you say, modelling the data appropriately produced significant improvements, too.
A column oriented database is probably the bigger performance increase. Parquet and a good data warehouse (something like Clickhouse, Druid or Snowflake) will both use metadata and efficient scans to power through aggregation queries.
Parquet seems to be on a path to become the de facto standard for storing and sharing bulk data - for good reason! (discussion: https://news.ycombinator.com/item?id=34310695)