Phase 1 · Data Science Foundations
TopicsData-Driven vs Model-Driven Decisions
Part of the Data Science Roadmap.
Summary
Some decisions just need clean descriptive data (data-driven); others genuinely need a predictive model's output (model-driven) — knowing which is needed prevents both under- and over-engineering a solution.
How to Learn This
- 1Recall a decision you've seen made and classify it as needing data or needing a model.
- 2Learn to ask 'could a simple dashboard answer this?' before reaching for ML.
- 3Understand that a good data scientist often talks a stakeholder OUT of needing a model.
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More topics in Data Science Foundations
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