# Data Modeling (DE / Analytics)

Good models reduce downstream confusion and rework.

## Start with grain

Define what one row means. Many modeling bugs are really grain bugs.

## Common approaches

- normalized models for core entities
- dimensional models for analytics

## Practical checklist

- primary keys and uniqueness
- time fields and timezone policy
- handling late arriving data
- schema evolution and compatibility