dbt-skill

What problem does it solve?

This Skill provides comprehensive guidance for using dbt (data build tool) to build robust, production-ready data models, ensuring data quality, efficient deployment, and maintainable analytics engineering workflows.

Core Features & Use Cases

• Project Structure & Modeling: Guidance on Medallion and Kimball architectures, naming conventions, and materialization strategies.
• Testing & Quality: Strategies for schema tests, singular tests, generic tests, unit tests, and anomaly detection using dbt-expectations and Elementary.
• CI/CD & Deployment: Best practices for local development, Slim CI, GitHub Actions, dbt Cloud jobs, and blue/green deployments.
• Performance & Optimization: Techniques for Snowflake and BigQuery performance tuning, incremental strategies, and cost monitoring.
• Advanced Capabilities: Covers Jinja macros, essential packages, semantic layer configuration, model contracts, versioning, and dbt Mesh.

Quick Start

Use the dbt skill to create a dbt project with staging and marts layers for a Snowflake warehouse.