Formal, intentional Data Architectures are rare in the wild and for data warehousing they're even rarer. A few textbooks describe principles for managing data in a data warehouse, and there's of course the half-baked "It's all just Kimball!" conventional wisdom. But there's not, as far as I know, a reliable cheat sheet that can help you figure out what your data architecture should look like. And no, the Medallion architecture doesn't count as "reliable."
All this is of course extremely relevant to how you implement AI, however that particular combination of machine-learning algorithms and hype is configured in the year you actually read this post.
This is looong, 8000+ words, so after the jump a table of contents:
