It goes beyond just joining postgres to hubspot and stripe even when humans are doing it. Typos in source systems, duplicative data, unwarranted prefixes, suffi

It goes beyond just joining postgres to hubspot and stripe even when humans are doing it. Typos in source systems, duplicative data, unwarranted prefixes, suffixes, stuff you don't care about, columns named c0,c1,c2 etc. A semantic layer is just really all about defining data models in the domain of interest. It's the hardest part in dealing with data strategies, very manual, very company and process and history specific. Once it's defined, the next set of tasks is to make sure that the data in the model is correct and coherent. And only then, querying this data, applying ML etc start becoming worthwhile. We at https://syncari.com https://syncari.com take the centralized data model centric approach. https://www.definite.app/ https://www.definite.app/ also looks very cool!