using-dbt-for-analytics-engineering

What problem does it solve?

This skill helps analytics teams apply software engineering discipline to dbt projects, enabling structured planning, reliable builds, and robust testing of data transformations.

Core Features & Use Cases

• Guided planning and design for dbt models and tests using established references (planning-dbt-models, discovering-data).
• Systematic debugging and impact assessment for changes, including downstream effects and lineage checks.
• Practical guidelines for writing tests, documenting changes, and maintaining clean project structure across staging, intermediate, and marts.

Quick Start

• Open the references to understand the planning, data discovery, and debugging workflows.
• In your dbt project, plan changes using the planning-dbt-models guide and verify data using dbt show.
• Use the scripts/review_run_results.md workflow to check run results after executing changes.