data-model-design

name	data-model-design
description	Design data models for business domains using entity-relationship or domain-driven design. Use when modeling new domains or refactoring data structures.

Data Model Design

Design data models that correctly represent business domains and support required queries efficiently.

Context

You are modeling a business domain in a database. The data model must reflect business semantics and perform well.

Domain Context

Based on relational theory and domain-driven design:

• Entities: Things with identity (User, Order)
• Attributes: Properties of entities (name, email)
• Relationships: How entities connect (User has many Orders)
• Normalization: Reduce redundancy; improves write performance
• Denormalization: Intentionally duplicate data; improves read performance

Instructions

1. Identify Entities: What are the main concepts? List with primary key.
2. Identify Attributes: For each entity, list properties.
3. Define Relationships: One-to-one, one-to-many, many-to-many.
4. Normalize: Remove update anomalies through normal forms.
5. Denormalize Strategically: Add calculated columns or tables for read performance.

Anti-Patterns

• Premature Normalization: Third-normal-form everywhere. Result: slow queries. Guard: Design for reads; denormalize if needed.
• Flat Tables: No normalization; entity data scattered. Result: update anomalies. Guard: At least second-normal-form.

Further Reading

• Relational Database Design — normalization fundamentals
• Domain-Driven Design — modeling business domains