Getting Started with dbt- Transforming Data the Modern Way

dbt (data build tool) is a SQL-based transformation tool that empowers data analysts and engineers to turn raw data into clean, trusted datasets using software engineering best practices—like modular code, version control, testing, and documentation.

Unlike traditional ETL tools, dbt focuses exclusively on the ‘T’ in ELT—Transformation—operating under the assumption that raw data is already loaded into a cloud data warehouse or lakehouse. This design makes dbt an ideal tool for implementing structured transformation workflows, such as the Medallion Architecture (Bronze, Silver, Gold layers). In this pattern:

Bronze represents raw ingested data,

Silver includes cleaned and conformed data,

Gold provides business-ready, analytics-optimized datasets.

dbt allows you to build these layers as modular SQL models with clear dependencies, making the transformation pipeline more transparent, testable, and scalable.

dbt is available in two forms:

dbt Core – an open-source command-line tool that integrates with orchestration tools like Airflow, Azure Data Factory, or GitHub Actions.

dbt Cloud – a fully managed SaaS offering with features like a web-based IDE, job scheduling, CI/CD, and team collaboration.

Together, dbt Core and Cloud enable teams to manage transformations across medallion layers with confidence, speed, and reproducibility—core principles of the modern data stack.