dbt (Data Build Tool) Best Practices

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So you have successfully run your dbt project. Congrats! Running dbt is just the beginning.

In order to ensure a durable and successful setup, and in order to make it possible for multiple team members to contribute to a dbt project, you are bound to adopting some best practice rules. Make it a discipline to follow those rules and stick to them throughout the life of your dbt project(s).

Use version control for your project

Version control systems such as GitHub help you manage and track changes to your dbt code over time. Managing your dbt project in a version control system helps your team members work together more efficiently and helps speed up the development process.

It is best practice to create Git branches to manage the development of new features and code fixes. Before merging into the master or main branch, a Pull Request must be created and code changes must be validated.

Set up separate development and production environments

Having separate development and production environment allows you to test your code and releases before pushing the code to the live deployment environment.