I don't want to derail the thread, but I recently started a company (https://syndetic.co) that's working on this problem. We've been focusing on the external data dictionary use case (how does a data-as-a-service company explain a dataset to their prospective customers) but we've been encountering a number of companies that are evaluating data catalogs and other internal tools for their data science teams.
I would really appreciate getting your perspective - I'm steve (at) syndetic.co
The legacy players are a mess, the new cloud native offerings are overly Engineering focused and immature, and the few startups in this space are recreating the legacy solutions in a SAAS formats
Go forth and claim the significant checks that I and others plan to write for these mediocre offerings.
We are revamping our management of Snowplow event structures presently to make them more semantic and easier to use.
For our core data marts, we rely on naming conventions for the LookML fields, good tool tips, hold monthly training sessions for new employees, weekly office hours with analysts, and do occasional “train the trainer” sessions to try and make sure there is at least one Looker power-user in each business team.
