Summary

This podcast started almost exactly six years ago, and the technology landscape was much different than it is now. In that time there have been a number of generational shifts in how data engineering is done. In this episode I reflect on some of the major themes and take a brief look forward at some of the upcoming changes.

Announcements

• Hello and welcome to the Data Engineering Podcast, the show about modern data management
• Your host is Tobias Macey and today I'm reflecting on the major trends in data engineering over the past 6 years

Interview

• Introduction
• 6 years of running the Data Engineering Podcast
• Around the first time that data engineering was discussed as a role
  • Followed on from hype about "data science"
• Hadoop era
• Streaming
• Lambda and Kappa architectures
  • Not really referenced anymore
• "Big Data" era of capture everything has shifted to focusing on data that presents value
  • Regulatory environment increases risk, better tools introduce more capability to understand what data is useful
• Data catalogs
  • Amundsen and Alation
• Orchestration engine
  • Oozie, etc. -> Airflow and Luigi -> Dagster, Prefect, Lyft, etc.
  • Orchestration is now a part of most vertical tools
• Cloud data warehouses
• Data lakes
• DataOps and MLOps
• Data quality to data observability
• Metadata for everything
  • Data catalog -> data discovery -> active metadata
• Business intelligence
  • Read only reports to metric/semantic layers
  • Embedded analytics and data APIs
• Rise of ELT
  • dbt
  • Corresponding introduction of reverse ETL
• What are the most interesting, unexpected, or challenging lessons that you have learned while working on running the podcast?
• What do you have planned for the future of the podcast?

Parting Question

• From your perspective, what is the biggest gap in the tooling or technology for data management today?

Closing Announcements

• Thank you for listening! Don't forget to check out our other shows. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast helps you go from idea to production with machine learning.
• Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.
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The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

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