dbt (data build tool) is an open-source analytics engineering framework that enables teams to transform raw data into analytics-ready datasets using SQL and version control. Instead of handling data ingestion or storage, dbt focuses on the transformation layer, allowing analysts and engineers to define models as SQL queries that are materialized in the data warehouse. It supports features like modularity, testing, documentation, and lineage tracking, making data pipelines more reliable and maintainable. dbt integrates seamlessly with modern cloud warehouses such as Snowflake, BigQuery, Redshift, and Databricks, and can be orchestrated through schedulers like Airflow or dbt Cloud. Its developer-friendly approach, emphasis on software engineering best practices, and strong community adoption have made dbt a core tool in the modern data stack for building scalable, trustworthy analytics workflows.