Best Practices for Effectively Running dbt in Airflow

As a popular open-source library for analytics engineering, dbt is often used in combination with Airflow. Orchestrating and executing dbt models as DAGs ensures an additional layer of control over tasks, observability, and provides a reliable, scalable environment to run dbt models.

This webinar covers a step-by-step guide to Cosmos, an open source package from Astronomer that helps you easily run your dbt Core projects as Airflow DAGs and Task Groups, all with just a few lines of code.

We’ll walk through:

• Standard ways of running dbt (and when to utilize other methods)
• How Cosmos can be used to run and visualize your dbt projects in Airflow
• Common challenges and how to address them, including performance, dependency conflicts, and more
• How running dbt projects in Airflow helps with cost optimization