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

service	development	master
CircleCI
AppVeyor

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.