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dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.

architecture

Understanding dbt

Analysts using dbt can transform their data by simply writing select statements, while dbt handles turning these statements into tables and views in a data warehouse.

These select statements, or "models", form a dbt project. Models frequently build on top of one another – dbt makes it easy to manage relationships between models, and visualize these relationships, as well as assure the quality of your transformations through testing.

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Reporting bugs and contributing code

Code of Conduct

Everyone interacting in the dbt project's codebases, issue trackers, chat rooms, and mailing lists is expected to follow the dbt Code of Conduct.

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Key dates

PyPI data
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  • Released:
Newer release available (1.12.3)

1 maintainer

PyPI data
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Credits

Author: dbt Labs

License

Apache Software License

Requires

Python >=3.7.2

Classifiers

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