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name: data-modeling description: | Guide for designing database schemas, data structures, and data architectures. Use when designing tables, optimizing queries, or making decisions about data storage technologies.

Data Modeling

When to use this skill

Use this skill when:

• Designing database schemas
• Optimizing query performance
• Choosing storage technologies
• Planning schema migrations
• Balancing normalization with performance

Schema Design

Normalization

• 1NF: Atomic values, no repeating groups
• 2NF: No partial dependencies
• 3NF: No transitive dependencies
• Normalize first, then denormalize strategically

Denormalization Trade-offs

• Improves read performance
• Complicates writes and updates
• Risk of data inconsistency
• Use for read-heavy workloads

Data Store Selection

Relational (SQL)

• Strong consistency requirements
• Complex queries and joins
• ACID transactions needed
• Well-defined schema

Document (NoSQL)

• Flexible, evolving schemas
• Hierarchical data
• Horizontal scaling priority
• Read-heavy workloads

Key-Value

• Simple lookup patterns
• Extreme performance needs
• Caching layer
• Session storage

Time Series

• Temporal data patterns
• High write throughput
• Time-based queries
• Sensor and metrics data

Indexing Strategy

When to Index

• Columns in WHERE clauses
• Join columns
• ORDER BY columns
• High-cardinality columns

Index Trade-offs

• Faster reads, slower writes
• Storage overhead
• Maintenance cost
• Query planner complexity

Schema Migrations

Safe Migration Practices

• Make changes backward compatible
• Add columns before using them
• Migrate data before dropping columns
• Test migrations on production-like data

Data Modeling Checklist

• Requirements understood
• Appropriate storage technology selected
• Schema normalized appropriately
• Indexes support query patterns
• Migration plan is safe
• Backward compatibility maintained