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Engineering Craft·Intermediate

Data Modeling for Product and Analytics Systems

A practical guide to data modeling decisions that improve product velocity and analytical trust. Covers entity design, normalization tradeoffs, event modeling, and schema governance.

30 min read 2 sections 1 interview questions
Data ModelingSchema DesignNormalizationDenormalizationEvent ModelingAnalytics EngineeringData GovernanceData Contracts

Good Data Models Reduce Rework

Poor data models create hidden tax: inconsistent metrics, brittle features, and expensive migrations. Strong modeling balances correctness, query performance, and evolvability.

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