Description
dbt is a transformation workflow that helps analytics engineers transform data in their warehouses by enabling them to write modular SQL while codifying best practices. It brings software engineering practices like version control, testing, and documentation to SQL, allowing teams to collaborate on data transformations in a structured, reliable way. dbt handles turning raw data into trusted, analytics-ready data sets without requiring complex extract-and-load processes.
Key Features
- SQL-first data transformation
- Testing and documentation built-in
- Version control integration
- Modular code organization
- Dependency management
Use Cases
- Data warehouse transformation
- Analytics engineering
- Business intelligence preparation
- Data modeling
- Metric definition and governance
Pricing Model
Open-source core with cloud offering
Integrations
Major data warehouses (Snowflake, BigQuery, Redshift), Git providers, BI tools, Airflow and other orchestrators, CI/CD pipelines
Target Audience
Analytics engineers, Data analysts, Data engineers, Business intelligence developers, Data scientists
Launch Date
2016
Available On
CLI, Cloud service, Self-hosted
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