Episodes
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Jamie Davidson (Chief Product Officer at Omni, Former VP of Product at Looker) joins me to chat about "modern" data modeling, going from a startup to Google and back to a startup, and much more.
Omni: https://omni.co/
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Burnout is a big topic right now. Carly Taylor and Ghalib Suleiman join me to chat about burnout and ways to deal with it.
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Episodes manquant?
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Sarah Levy (CEO of Euno) joins me to chat about modern data governance for analytics.
Euno - https://euno.ai/
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Carsten Bange (Founder & CEO of BARC) joins me to chat about trends in data, analytics, and AI.
BARC website: www.barc.com
Carsten on LinkedIn: https://www.linkedin.com/in/carsten-bange/
BARC Data Culture Summit: https://barc.com/events/data-culture-summit%20/
BARC DATAfestival: https://barc.com/events/data-festival/
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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.
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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
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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/
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Simba Khadder (CEO of FeatureForm) joins me to chat about feature stores, reinforcement learning, surfing, and much more.
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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/
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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/
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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.
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Tiankai Feng joins me to chat about the people side of data, aligning on the value of data strategy, and much more.
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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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Health insurance denials are a big topic in America right now. Holden Karau joins me to talk about using AI to appeal health claim insurance denials.
Fight Health Insurance: https://fighthealthinsurance.com/
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I’ve been asked many questions about building a personal brand for the last few weeks. Perhaps it’s the uncertain job market, people wanting to branch out, or something else. I’m unsure what’s in the air right now.
In this episode, I share some thoughts on building a personal brand.
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Hannes Muhleisen is the creator of DuckDB and CEO of DuckDB Labs. We finally got a chance to meet in person at the Forward Data Conference in Paris. We hit it off immediately, and at times, I felt like I was talking with my long lost brother. Hannes is a very cool guy!
While at the conference, we recorded a chat about all things DuckDB, the challenges of data lakehouses and open table formats, local-first tech, and much more. 🦆 🐥
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Regular guest Gordon Wong joins me for a half hour to chat about tech stacks for analytics, semantic layers, and much more.
Gordon's LinkedIn: https://www.linkedin.com/in/gordonhwong/
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Bill Inmon is considered the father of the data warehouse. I just got back from spending a couple of days with Bill, and we discussed the history of the data industry and the data warehouse. On my flight back, I realized people could benefit from a short version of our conversation.
In this short chat, we discuss what a data warehouse is (and is not), Kimball and Inmon, the origins of the data warehouse, and much more.
- Montre plus
