joevandyk/dbt repository overview

⁠dbt

dbt (data build tool) helps analysts write reliable, modular code using a workflow that closely mirrors software development.

A dbt project primarily consists of "models". These models are SQL select statements that filter, aggregate, and otherwise transform data to facilitate analytics. Analysts use dbt to aggregate pageviews into sessions⁠, calculate ad spend ROI⁠, or report on email campaign performance⁠.

These models frequently build on top of one another. Fortunately, dbt makes it easy to manage relationships⁠ between models, test⁠ your assumptions, and visualize⁠ your projects.

Still reading? Check out the docs⁠ for more information.

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⁠Getting Started

• What is dbt⁠?
• Read the dbt viewpoint⁠
• Installation⁠
• Join the chat⁠ on Slack for live questions and support.

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⁠The dbt ecosystem

• Visualize your dbt graph here⁠
• Run your dbt projects on a schedule here⁠

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⁠Testing

Coverage⁠

⁠Code of Conduct

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