Low-Code Apache Airflow

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What do you do after your Spark workflow development is finished? Nowadays, data engineers dread putting their workflows in production. Apache Airflow provides the necessary scheduling primitives but writing the glue scripts, handling Airflow operators and workflow dependencies sucks! Low-Code Development & Deployment can make scheduling Spark workflows much simpler – we’ll show you how.
Additionally, we show column-level lineage for governance such as tracing your PII data, or for production issues such as understanding the downstream impact of changes to a workflow.

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