How to Improve Data Quality with Airflow's Great Expectations Operator

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Hosted By

  • Benji Lampel
  • Kenten Danas

This webinar provides an overview of how to use the new Great Expectations (GX) operator to implement data quality checks in your Airflow DAGs. We cover new features of the GX operator, including a default Checkpoint feature, which makes Great Expectations more Airflow-centric and simpler to use. Questions covered in this session include:

What improvements have been made to the GX operator in the latest version? How can I implement the GX operator in my Airflow DAGs? How can I scale my data quality checks to large datasets using the GX operator and Airflow? What kinds of data quality checks can I implement with the GX operator?

Learn more about the Great Expectations provider in the public repo. The example code covered in this webinar can be found on the Astronomer Registry.

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