Astronomer Webinars

Join us for upcoming online events!

Optimizing ML/AI Workflows with Essential Airflow Features

Hosted By

  • Kenten Danas
  • Tamara Fingerlin

In this webinar, you’ll learn best practices for using the latest Airflow features, including those recently released in Airflow 2.9, for generative AI and general machine learning use cases.

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Past Webinars

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

In this webinar, Airflow Engineering Advocate Benji Lampel will demonstrate the new features of the Great Expectations Operator, which make Great Expectations more Airflow-centric and simpler to use. The latest set of releases under the new repository hosted by Astronomer provides some dramatic changes, including a default Checkpoint feature. The webinar will feature a demo of the new operator and how to use these features.

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How to Save Money using Airflow’s asynchronous Azure operators

Many Azure users leverage Airflow for best-in-class orchestration of their Azure services. Recent updates to the Azure provider have brought greater functionality and new Airflow features to Azure operators. In this “Live with Astronomer” session, we’ll dive into the newly developed asynchronous Azure operators that offer cost savings and greater scalability. We’ll show how with only small updates to your DAGs, you can take advantage of asynchronous functionality when orchestrating services like Azure Data Factory and Azure Databricks.

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Using the new Fivetran provider

With more than 30,000 downloads per month, the Fivetran provider for Airflow is incredibly popular. Using Fivetran and Airflow together gives users the benefits of first-class orchestration, pipelines as code, and automated ELT processes.

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Organizing Your Airflow Project Code with the Astro CLI

One of the benefits of Airflow is having pipelines as Python code, which lets you treat your data pipelines like any other piece of software. In this “Live with Astronomer” session, we’ll dive into how to use the open-source Astro CLI to effectively manage your Airflow project code so you can share code with your team, test DAGs before you deploy them, keep your code organized for easy reviews, and more.

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