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The word "model" is used a lot by data professionals. There are dbt models, machine learning models, relational models, and conceptual, logical, and physical models. My concern is we're missing the bigger picture of what data modeling was initially supposed to accomplish, which was to represent reality and structure it as data. The bigger implication is that our various "models" will become too myopic and miss the larger broader context of the reality of how we use data to serve our organizations.
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If you like this show, give it a 5-star rating on your favorite podcast platform.
Purchase Fundamentals of Data Engineering at your favorite bookseller.
Subscribe to my Substack: https://joereis.substack.com/
5
1414 ratings
The word "model" is used a lot by data professionals. There are dbt models, machine learning models, relational models, and conceptual, logical, and physical models. My concern is we're missing the bigger picture of what data modeling was initially supposed to accomplish, which was to represent reality and structure it as data. The bigger implication is that our various "models" will become too myopic and miss the larger broader context of the reality of how we use data to serve our organizations.
-----------------------
If you like this show, give it a 5-star rating on your favorite podcast platform.
Purchase Fundamentals of Data Engineering at your favorite bookseller.
Subscribe to my Substack: https://joereis.substack.com/
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