Master Data Workload Automation: Introduction

Automating your data workloads is essential in today's mission critical data driven businesses but what is the best way to do it? There are two basic choices: job schedulers and data orchestrators. I'll explain what they are, review some examples, and explain when to use each.
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[@caydendunn8404]

great video. love when someone with many years of experience takes the time to share their knowledge

[@user-wp6di4tz4p]

Very nice explanation Bryan.. Thank you so much

[@BryanCafferky]

You're welcome!

[@kandoras.guzman6705]

Thank you for this! I literally said to myself yesterday that I'd like a video on this and now you've uploaded it.

[@BryanCafferky]

Kismet 🙂

[@jorgemercado593]

Thank you Bryan!

[@BryanCafferky]

You're Welcome!

[@DucVu-ip5pc]

Thanks sir. I understand more about these terms in data world. I learnt to use both apache airflow and dagster. Firstly, I love airflow cause flexibility of this tool and I completely hate Dagster cause the methodology is completely hard to understand. But more and more working with data, I prefer to use Dagster for some job is rarely data and Airflow for genral job.

[@oyeyemirafiuowolabi2347]

Thank you for this excellent intro. Please, i would like to hear your say about Nifi 2.0M1 which now support "full blown" python3.

[@rahulrokkam8174]

Nice video! could you please do one on what DBFS is?