It is a command line tool that enables data analysts and engineers to transform data in their warehouses more effectively.

Data Transformation

What need does dbt fulfill?

dbt (data build tool) simplifies the workflow for transforming raw data into data models consumable for analytics.

dbt makes it easy and fast for data teams to write, test, and orchestrate data pipelines. Transformations are written as templated SQL select statements and automatically orchestrated with a CLI tool. And because one only needs SQL to start with dbt, non-engineers can adopt this superpower too.

Importantly, dbt often enables data analysts to build their own analytical assets and intuitively introduces to them good software development practices (like abstraction and testing).

What are the benefits of using dbt?

  Write pipelines as quickly as writing SQL queries
  Automate tests for data as easily as querying with SQL
  Automate your DAG generation and orchestration
  Write DRY and more flexible SQL
  Centralize where you document and configure data
  Modularity, including community packages for common uses

What are the core features of dbt?

  Compiles SQL select statements into context-specific DDL
  Generates and orchestrates DAGs and offers a powerful, but simple, testing framework

Which teams does dbt cater to?


Authored By

James Peterson's profile on Data-led Academy

James Peterson

Analytics Lead at Shippit.com