Good data models are the foundation of maintainable applications. They affect performance, scalability, and how easily you can evolve your system.
Start with the Domain
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Normalization Levels
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Strategic Denormalization
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Relationship Patterns
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Prisma Schema Example
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Schema Evolution
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Soft Deletes
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Audit Trails
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Best Practices
DO:
✓ Start with normalized design
✓ Denormalize based on measured needs
✓ Use appropriate data types
✓ Add indexes for query patterns
✓ Plan for schema evolution
✓ Document relationships
DON'T:
✗ Over-normalize (too many joins)
✗ Under-normalize (update anomalies)
✗ Use generic columns (data1, data2)
✗ Store computed values without updates
✗ Ignore NULL semantics
Conclusion
Data modeling is both art and science. Start normalized, understand your access patterns, and denormalize strategically. Plan for evolution—schemas change as requirements grow.
A well-designed data model makes the application code simpler and the database faster.