Here are the 10 best practices for data modeling.
Understand Business Goals First
Talk to business teams. Learn what they need before you design any tables.
Pick the Right Model
Use normalized models for apps. Use star schemas or data vault for reports and warehouses.
Normalize or Denormalize
Keep OLTP tables clean and split up to avoid data errors. Combine tables in data warehouses to make queries run faster.
Use Constraints
Always add primary keys, foreign keys, and rules. They stop bad data from entering your database.
Use Clear Names
Give every table and column a simple, consistent name. Everyone should know what it means.
Track Audit Data
Add columns that show when data was loaded and where it came from. This helps you track history.
Save History Properly
Plan how to track changes over time. Do not overwrite old data unless you mean to.
Optimize for Speed
Design tables so queries run fast. Use indexes and break large tables into smaller parts by date.
Keep Good Documentation
Write down your data dictionary and draw your charts. This helps other engineers understand your work.
Design for Growth
Build your models so you can add new columns later without breaking your old system.
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