Data Modeling Essentials

What you will learn

• Identify entities, relationships, and invariants for a product domain
• Choose keys and constraints that enforce integrity
• Balance normalized and denormalized designs intentionally
• Plan additive schema changes with low downtime risk
• Review data model PRs with a consistent checklist

About this course

Poor data models create silent product bugs and painful migrations. This course walks through entity design, keys, relationships, and evolution strategies that keep both application and analytics use cases healthy. We examine normalization trade-offs, naming conventions, soft deletes, historical tracking, and how to communicate model changes to engineers and analysts. Workshops ask you to critique and improve a messy schema. You finish with a checklist for reviewing pull requests that touch core tables.

Who it is for

• Backend engineers owning persistence layers
• Data engineers collaborating with product teams
• Tech leads responsible for core schema quality