Stay ConnectedI’m Joe Reis, co-author of Fundamentals of Data Engineering, creator of Mixed Model Arts, international speaker, and long-time observer of the tech industry’s favorite recurring mistakes.
Weekly broadcasts from somewhere on the road. Expect raw solo rants and long-form conversations with the engineers and leaders actually building things. I dive into data, AI, architecture, and career survival.
This podcast is invitation-only. Unsolicited guest pitches and PR outreach are not considered.
Copyright: © Joe Reis
Will AI chatbots replace old school BI dashboards and reports? Or can they co-exist with one another? Will AI help the often poor adoption by the business of dashboards and reporting? I rant about this and more in this latest episode.
Dave Colls and David Tan join me to chat about building effective machine learning teams, the challenges they face, the 7 deadly wastes in data and ML, writing a book, and much more.
Get their book here: https://amzn.to/3DS2OMp
It's 2025! We made it! ;)
In this podcast, I rant about why data modeling matters more than ever, AI, and why humans will seek out "human" things in 2025 and beyond.
❤️ Your support means a lot. Please like and rate this podcast on your favorite podcast platform.
🤓 My works:
📕Fundamentals of Data Engineering: https://www.oreilly.com/library/view/fundamentals-of-data/9781098108298/
🎥 Deeplearning.ai Data Engineering Certificate: https://www.coursera.org/professional-certificates/data-engineering
🔥Practical Data Modeling: https://practicaldatamodeling.substack.com/
🤓 My SubStack: https://joereis.substack.com/
Simba Khadder (CEO of FeatureForm) joins me to chat about feature stores, reinforcement learning, surfing, and much more.
It's December 31, 2024. Gordon Wong and I wrap up 2024 and chat about what we're excited about in 2025 in data and otherwise.
❤️ If you like my podcasts, please like and rate it on your favorite podcast platform.
🤓 My works:
📕Fundamentals of Data Engineering: https://www.oreilly.com/library/view/fundamentals-of-data/9781098108298/
🎥 Deeplearning.ai Data Engineering Certificate: https://www.coursera.org/professional-certificates/data-engineering
🔥Practical Data Modeling: https://practicaldatamodeling.substack.com/
🤓 My SubStack: https://joereis.substack.com/
Matt Housley and I have a LONG chat about working in consulting, leaving your job, AI, the job market, our thoughts on what's coming in 2025, and much more.
❤️ If you like my podcasts, please like and rate it on your favorite podcast platform.
🤓 My works:
📕Fundamentals of Data Engineering: https://www.oreilly.com/library/view/fundamentals-of-data/9781098108298/
🎥 Deeplearning.ai Data Engineering Certificate: https://www.coursera.org/professional-certificates/data-engineering
🔥Practical Data Modeling: https://practicaldatamodeling.substack.com/
🤓 My SubStack: https://joereis.substack.com/
The first time I met Amr Awadallah, he struck me as a rare person genuinely curious about the world and how technology and AI impact it.
We discuss his early roots as an entrepreneur, the founding of Cloudera and Vectara, the challenges of AI in enterprises, what makes humans unique, and much more.
I had an interesting conversation yesterday with a young gentleman upgrading my Google Fiber. While he was originally pursuing a career as a software developer, he and his friends decided against it after seeing the progress of ChatGPT over the last couple of years.
As a father of two teenage boys, I often think about the nature of work, including whether writing code will be relevant for future generations. Here, I rant at least part (not all) of what's on my mind. This is a big topic, and you'll see me ranting more about it.
Tiankai Feng joins me to chat about the people side of data, aligning on the value of data strategy, and much more.
This morning, a great article came across my feed that gave me PTSD, asking if Iceberg is the Hadoop of the Modern Data Stack?
In this rant, I bring the discussion back to a central question you should ask with any hot technology - do you need it at all? Do you need a tool built for the top 1% of companies at a sufficient data scale? Or is a spreadsheet good enough?
Link: https://blog.det.life/apache-iceberg-the-hadoop-of-the-modern-data-stack-c83f63a4ebb9
❤️ If you like my podcasts, please like and rate it on your favorite podcast platform.
🤓 My works:
📕Fundamentals of Data Engineering: https://www.oreilly.com/library/view/fundamentals-of-data/9781098108298/
🎥 Deeplearning.ai Data Engineering Certificate: https://www.coursera.org/professional-certificates/data-engineering
🔥Practical Data Modeling: https://practicaldatamodeling.substack.com/
🤓 My SubStack: https://joereis.substack.com/
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