Why dbt Matters
dbt (data build tool) has become a cornerstone of modern analytics engineering. It empowers teams to transform raw data into clean, tested, and documented datasets — all with version-controlled SQL and modular models.
On this page, you’ll find a curated collection of articles and guides covering both beginner and advanced dbt use cases. Topics include setting up your first project, building staging and mart layers, writing reusable macros, implementing schema enforcement with contracts, and ensuring data quality through tests.
Whether you’re working with BigQuery, Snowflake, or DuckDB, dbt provides a consistent way to manage transformations. I also share real-world lessons from projects where dbt was used at scale, along with best practices for documentation, performance optimization, and team workflows.
If you’re looking to deepen your understanding of dbt or solve specific modeling challenges, this tag is your entry point. Everything here is written by a practicing data engineer and aimed at making dbt work in production environments.