Join us for upcoming online events!
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George YatesLead Developer Advocate
Juliana O'DonohueDirector, Product
Kenten DanasManager, Developer RelationsThis webinar will provide a comprehensive overview of the new features in the latest Astro release, complete with live demos. Whether you're already using Astro or considering it for your data orchestration needs, don't miss this opportunity to learn from the experts and have your questions answered.
A paradigm shift occurred leading to the formation of the large language model operations (LLMOps) modern data stack with Apache Airflow right at the center. Join us in this webinar to explore these providers and learn how you can leverage them to take your LLMOps to the next level.
Because Airflow is 100% code, knowing the basics of Python is all it takes to get started writing DAGs. However, writing DAGs that are efficient, secure, and scalable requires some Airflow-specific finesse. In this webinar, you’ll learn the best practices for writing DAGs that will ensure you get the most out of Airflow. We’ll include a reference repo with DAGs you can run yourself with the Astro CLI.
Data quality is an often overlooked component of data pipelines. Learn why it is a valuable part of data systems and how to get started integrating data quality checks into existing pipelines with a variety of tools.
What is Airflow? Definition: Apache Airflow is a way to programmatically author, schedule and monitor data pipelines.
The flexibility and freedom that Airflow offers you is incredible, but to really take advantage of it you need to master some concepts first, one of which has just been released in Airflow 2.2 By the end of the webinar, you will be able to define schedule intervals that you thought were impossible before.
In this informative webinar we will cover everything you need to know about Airflow 2.2. We'll go through all of the new features large and small, as well as show you how to leverage all of the new features and how you can get cleaner and more efficient DAGs as a result
Airflow, by nature, is an orchestration framework, not a data processing framework. At first sight it can be unclear how to test Airflow code. Are you triggering DAGs in the UI to validate your Airflow code? In this webinar we'll demonstrate various examples how to test Airflow code and integrate tests in a CI/CD pipeline, so that you're certain your code works before deploying to production.
More often that not, your Airflow components will have a desired order of execution particularly if you are performing a traditional ETL process—for example, before the Transform step in ETL, Extraction had to have happened in an upstream pipeline. In this webinar we will discuss how to properly setup dependencies and define an order of execution or operation for your pipelines using dependencies.
Do you use Sensors in your data pipelines? Do you need to wait for a file before executing the next step? Are you looking to execute your task after a task completes in another DAG? Would you like to wait for an import in your SQL table before executing the next task? The answer...
While Airflow and ADF (Azure Data Factory) have pros and cons, they can be used in tandem for data pipelines across your organization. In this webinar, we’ll cover how using the two together can really get you the best of both worlds!
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