Joe Reis Flips The Script And Interviews Tobias Macey About The Data Engineering Podcast
Data Engineering Podcast
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Data Modelling and Machine Learning
Tobias: It seems like these discussions are on data modelling that i'm seeing recently. He says there's always the problem of garbage in, garbage ou and because machine learning is such a force multiplier, it garbage in an entire, an entire trash heap out. Tying your data from point a to z within domain across domains, whatever has been very much an analytical exercise until now. But as real time comes more into vogue, he says, you can either do smart things faster or done things faster.
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Summary
Data engineering is a large and growing subject, with new technologies, specializations, and "best practices" emerging at an accelerating pace. This podcast does its best to explore this fractal ecosystem, and has been at it for the past 5+ years. In this episode Joe Reis, founder of Ternary Data and co-author of "Fundamentals of Data Engineering", turns the tables and interviews the host, Tobias Macey, about his journey into podcasting, how he runs the show behind the scenes, and the other things that occupy his time.
Announcements
- Hello and welcome to the Data Engineering Podcast, the show about modern data management
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- Your host is Tobias Macey and today we’re flipping the script. Joe Reis of Ternary Data will be interviewing me about my time as the host of this show and my perspectives on the data ecosystem
Interview
- Introduction
- How did you get involved in the area of data management?
- Now I’ll hand it off to Joe…
Joe’s Notes
- You do a lot of podcasts. Why? Podcast.init started in 2015, and your first episode of Data Engineering was published January 14, 2017. Walk us through the start of these podcasts.
- why not a data science podcast? why DE?
- You’ve published 306 of shows of the Data Engineering Podcast, plus 370 for the init podcast, then you’ve got a new ML podcast. How have you kept the motivation over the years?
- What’s the process for the show (finding guests, topics, etc….recording, publishing)? It’s a lot of work. Walk us through this process.
- You’ve done a ton of shows and have a lot of context with what’s going on in the field of both data engineering and Python. What have been some of the major evolutions of topics you’ve covered?
- What’s been the most counterintuitive show or interesting thing you’ve learned while producing the show?
- How do you keep current with the data engineering landscape?
- You’ve got a very unique perspective of data engineering, having interviewed countless top people in the field. What are the the big trends you see in data engineering over the next 3 years?
- What do you do besides podcasting? Is this your only gig, or do you do other work?
- whats next?
Contact Info
Closing Announcements
- Thank you for listening! Don’t forget to check out our other shows. The Data Engineering Podcast covers the latest on modern data management. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used.
- Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.
- If you’ve learned something or tried out a project from the show then tell us about it! Email hosts@themachinelearningpodcast.com) with your story.
- To help other people find the show please leave a review on iTunes and tell your friends and co-workers
Parting Question
- From your perspective, what is the biggest gap in the tooling or technology for data management today?
Links
- Podcast.__init__
- The Machine Learning Podcast
- Ternary Data
- Fundamentals of Data Engineering book (affiliate link)
The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA
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