Using dbt for Analytics Engineering

Core principle: Apply software engineering discipline (DRY, modularity, testing) to data transformation work through dbt's abstraction layer.

When to Use

• Building new dbt models, sources, or tests
• Modifying existing model logic or configurations
• Refactoring a dbt project structure
• Creating analytics pipelines or data transformations
• Working with warehouse data that needs modeling

Do NOT use for:

• Querying the semantic layer (use the answering-natural-language-questions-with-dbt skill)

Reference Guides

This skill includes detailed reference guides for specific techniques. Read the relevant guide when needed: