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Data Modeling
The Goldilocks Data Model (Too Hot, Too Cold, Never Just Right)
The Problem
Two extremes plague analytics teams: (1) Data left unmodeled or haphazardly modeled, hindering scalability and usability, or (2) Data over-engineered, slowing progress and confounding even seasoned analysts. Fresh talent joins eager to build, only to hear "our data's a hot mess—expect to spend 70% of your time wrestling with it." Both extremes leave data harder to use, not easier. You can't achieve Analytics Powerhouse status without adhering to basic data modeling principles.
The Principle
A data model has ONE job: make data easier to use for those crafting solutions with it—the BI analysts and data scientists. Ask ruthlessly: "Does this model make the data easier to use—yes or no?" If ...
Action Steps
1.Step 1 content...
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