Warehouse And Schema Design

Overview

Use this skill when the primary challenge is how data should be modeled for reliable analytics consumption. It helps agents choose good grain, keys, relationships, and serving patterns so downstream work stays understandable and performant.

When to Use

• designing marts, warehouse schemas, or curated serving tables
• choosing fact and dimension boundaries
• deciding grain, surrogate keys, or relationship strategy
• balancing normalization and denormalization
• restructuring analytics-facing datasets for usability

Do not reduce schema design to column naming alone. Good schema design is about behavior, meaning, and query ergonomics.

Workflow