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Apache Airflow has become the dominant and ubiquitous Big Data workflow management system, leaving Oozie and other competitors miles behind in terms of features and functionality. 

In this course, you will learn the fundamentals of Apache Airflow starting with DAGs, DagRuns, Tasks and Task Instances - the building blocks of this popular technology. You’ll then move on to understanding the architecture, creating operators and sensors, and understanding XCom.

In the latter half, you’ll learn about branching, scheduling, and working with the UI. By the end of this course, you will have a new, highly coveted, and transferable skill to add to your resume.

An Introduction to Apache Airflow

If you have come this far, you should now have a working knowledge of Airflow, its architecture, and its working. We demonstrated the most used features of Airflow in this course, but Airflow is a very rich and extensive workflow framework. It isn’t possible to cover every nook and detail of the platform in an introductory course on the subject. In this regard, we encourage you to visit the official <a href="https://airflow.apache.org/docs/apache-airflow/stable/index.html" target="_blank">documentation of Airflow</a> for more complex use cases and involved features. The configuration settings are numerous and can be tweaked to alter Airflow’s behavior and are worth familiarizing yourself with.

Feedback, comments, and suggestions are most welcome!


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