Kurze prägnante Zusammenstellung
https://medium.com/write-a-catalyst/25-must-know-data-science-concepts-bb665779e4bf?sk=02d7d90f428ffbdf66a39e05e44fffd5
Begriffe, Struktur Vor- und Nachteile von Medaillon Architektur
https://medium.com/@community_md101/data-products-a-case-against-medallion-architecture-139096ceea08
Wie kommen die Daten in den See?
Grundprinzipien: https://blog.dataengineerthings.org/5-data-ingestion-methods-every-data-engineer-should-know-e527b0c819d7?sk=26bf4475e65f59c9e056bb76e23700f9
Data Pipeline Patterns: https://levelup.gitconnected.com/8-data-pipeline-patterns-exist-most-engineers-only-know-3-ad646f3b3257?sk=7cb01bc7867bb6cd0c957ae9323493ec
https://blog.gopenai.com/10-attribution-models-you-can-build-using-pure-sql-29503a648acd
https://medium.com/@Rohan_Dutt/654ed8f2d651
https://medium.com/@diogofcul/10-sql-patterns-every-data-engineer-should-know-by-heart-76b7253e0b19
interessant Artikel dazu: https://medium.com/@arthur.dc
https://medium.com/lets-code-future/70-system-design-terms-every-beginner-should-know-c8f034b44be4