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How Information Engineering Developed since 2014 | by šŸ’”Mike Shakhomirov | Jul, 2024

admin by admin
July 29, 2024
in Artificial Intelligence
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How Information Engineering Developed since 2014 | by šŸ’”Mike Shakhomirov | Jul, 2024
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High tendencies to assist your knowledge pipelines scale with ease

šŸ’”Mike Shakhomirov

Towards Data Science

13 min learn

Ā·

22 hours in the past

AI generated picture utilizing Kandinsky

On this dialogue, I purpose to discover the evolving tendencies in knowledge orchestration and knowledge modelling, highlighting the developments in instruments and their core advantages for knowledge engineers. Whereas Airflow has been the dominant participant since 2014, the info engineering panorama has considerably remodeled, now addressing extra subtle use instances and necessities, together with assist for a number of programming languages, integrations, and enhanced scalability. I’ll look at up to date and maybe unconventional instruments that streamline my knowledge engineering processes, enabling me to effortlessly create, handle, and orchestrate strong, sturdy, and scalable knowledge pipelines.

Over the last decade we witnessed a ā€œCambrian explosionā€ of varied ETL frameworks for knowledge extraction, transformation and orchestration. It’s not a shock that lots of them are open-source and are Python-based.

The most well-liked ones:

  • Airflow, 2014
  • Luigi, 2014
  • Prefect,2018
  • Temporal, 2019
  • Flyte, 2020
  • Dagster, 2020
  • Mage, 2021
  • Orchestra, 2023
Tags: DataEngineeringEvolvedJulMikeShakhomirov
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