| 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
- Identify Entities: What are the main concepts? List with primary key.
- Identify Attributes: For each entity, list properties.
- Define Relationships: One-to-one, one-to-many, many-to-many.
- Normalize: Remove update anomalies through normal forms.
- 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
