Running dbt with Airflow

Apache Airflow is a versatile platform used for writing, scheduling, and monitoring workflows, providing a centralized way to manage and visualize tasks within a data ecosystem. It supports a wide range of "Operators" for diverse functions beyond SQL scripts, such as making HTTP requests and running Python code, which highlights its role in orchestrating comprehensive data pipelines. The integration of Airflow with dbt allows for enhanced task dependency management, centralized control, and parameterization across systems, offering a holistic view and alert system for the entire data pipeline. A detailed demo is provided, guiding users through setting up a local environment using Docker to install Postgres, dbt, and Airflow, demonstrating how to configure and run a data workflow. The demo emphasizes the use of containers for simplicity and organization, illustrating the practical steps for creating and managing data workflows in a structured and accessible manner.

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