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
Gordon Wong has led data teams of all sizes, across many well-known companies. I consider him a Yoda in the data field, and this is a glimpse into the monthly chats that Gordon and I have. Unfiltered and uncut. Enjoy.
Please note - we had to cut it a bit short, as Gordon had another call at the top of the call. Again, this is literally a look at a normal chat that Gordon and I engage in.
This week I had the opportunity to give two talks to two very different groups. Earlier in the week I spoke with a group of senior and above software engineers and leaders in Utah. Yesterday I spoke with a group of data engineers and leaders in Atlanta.
The common theme? There's a big divide between dev and data, and data's often on the losing side of this divide. For data teams to be more successful, we need to close the divide and collaborate more closely with dev, and vice versa.
Vin and I chat about the challenges of writing books, how companies can mature with data science, why data scientists need to learn strategy, and much more.
(We experienced a slight internet delay around the 15:30 mark, otherwise great)
LinkedIn: https://www.linkedin.com/in/vineetvashishta/
Book: https://www.amazon.com/Data-Profit-Businesses-Leverage-Bottom/dp/1394196210
Site: https://www.datascience.vin/
-----------------------
If you like this show, give it a 5-star rating on your favorite podcast platform.
Purchase Fundamentals of Data Engineering at your favorite bookseller.
Subscribe to my Substack: https://joereis.substack.com/
We live in the golden age of data tools, yet we still lack a grasp on the basics of working with data itself - data literacy, modeling, solving problems people care about, etc. It's time to get back to basics, which I think will make data professionals way more effective at their jobs.
Scott Taylor (aka the Data Whisperer) is an OG in data content, speaking, and storytelling. He's been keynoting data events since the 1990s and keeps sharpening his game. Scott is someone I look up to, and I always enjoy our chats.
LinkedIn: https://www.linkedin.com/in/scottmztaylor/
Website: https://www.metametaconsulting.com/
YouTube: https://www.youtube.com/channel/UCVQ1YhjNqc77GVsb3Xs4tvw
(Note - there's a very slight interruption with our internet connection at the 35 minute mark)
-----------------------
If you like this show, give it a 5-star rating on your favorite podcast platform.
Purchase Fundamentals of Data Engineering at your favorite bookseller.
Subscribe to my Substack: https://joereis.substack.com/
While on a hike today with a friend, we were engrossed in a chat about something that is often overlooked by technical practitioners - the politics of data. This takes many shapes and forms, and ultimately impacts the type of work you do. The main takeaway - learn to pay attention to the broader political landscape of your company.
Kai Zenner has been working on the EI AI Act for a while, and we chat about his perspective on its evolution, challenges, and potential. Along the way, we discuss why the EU AI Act differs from GDPR, why regulating a quasi-global piece of legislation is very difficult, and much more.
I admit, politics and regulation are way outside my wheelhouse, and I learned a ton in this discussion. Given the impact the EU AI Act will affect the work of everyone involved with data, I think you'll learn a thing or two about not just the act itself, but also how the "sausage is made", so to speak. Enjoy!
LinkedIn: https://www.linkedin.com/in/kzenner/
Twitter: https://twitter.com/ZennerBXL
Site: https://www.kaizenner.eu
-----------------------
If you like this show, give it a 5-star rating on your favorite podcast platform.
Purchase Fundamentals of Data Engineering at your favorite bookseller.
Subscribe to my Substack: https://joereis.substack.com/
Ryan Boyd and I chat about the evolution and future of databases, the pendulum between single-server and distributed computing, DuckDB and Motherduck, and much more.
We also talk about developer relations, which I consider Ryan as one of the OG's in the field.
Note - this was recorded the week of Databricks Summit 2023.
-----------------------
If you like this show, give it a 5-star rating on your favorite podcast platform.
Purchase Fundamentals of Data Engineering at your favorite bookseller.
Subscribe to my Substack: https://joereis.substack.com/
Is Kimball still relevant? Or should we just throw columnar storage and unlimited compute to solve our analytical needs?
Because I like to live on the edge, I respond to a comment online that I think highlights the rot in our industry as it relates to how we view data modeling today.
Data Modeling With Joe Reis - Understanding What Data Modeling Is And Where It's Going (Seattle Data Guy): https://www.youtube.com/watch?v=NKo02ThtAto
-----------------------
If you like this show, give it a 5-star rating on your favorite podcast platform.
Purchase Fundamentals of Data Engineering at your favorite bookseller.
Subscribe to my Substack: https://joereis.substack.com/
Joshua Bowles is a linguist and data scientist turned software engineer. This is a wide-ranging chat between two old-school data scientists/ML practitioners about the past, present, and future of ML and AI.
LinkedIn: https://www.linkedin.com/in/joshua-bowles-ailgroup/
Mastadon: https://infosec.exchange/explore
-----------------------
If you like this show, give it a 5-star rating on your favorite podcast platform.
Purchase Fundamentals of Data Engineering at your favorite bookseller.
Subscribe to my Substack: https://joereis.substack.com/
Our TOPPODCAST Picks 
