The Joe Reis Show (Joe Reis)

Dave McComb (CEO of Semantic Arts) is one of the most thoughtful and original people I know in the data space, having pioneered the use of semantics and knowledge graphs in the 1990s. We talk about a wide range of topics, including interoperability at the data level, the data-centric revolution, and much more.

Note - there was a weird and unresolved connection issue that caused some static at varying points during our call.

Vishnu Vasanth (e6Data) and I chat about what's next for analytical query engines, shifting left, the Indian tech scene, and much more.

Vishnu is very wise and has a very deep technical vision for where the industry needs to go. I very much agree with his vision. Enjoy!

e6Data: https://www.e6data.com/

LinkedIn: https://www.linkedin.com/in/vishnu-vasanth-5329233/

Wendy Turner-Williams joins me to chat about her new project and communty, The Association.ai, unleashing generative AI in organizations, starting and building a community, and much more.

LinkedIn: https://www.linkedin.com/in/wendy-turner-williams-8b66039/

The Association: https://theassociation.ai/

Matt Housley hangs out at my house, and we have a random chat about all sorts of stuff - fads in data, data and ML engineering, tech hubs, and more. If you want a glimpse into the sorts of chats that Matt and I have all the time, here you go.

Whenever Kris and I chat, there's an agenda, which is totally useless. Every single time we've talked, the conversation goes into different (I'll argue better) directions. In this episode, Kris and I delve into the art and craft of programming, finding your tribe as a developer advocate, and so much more. I hope you enjoy this great and meandering conversation.

Developer Voices podcast: https://open.spotify.com/show/2gXhwz0AQRv2cvw61kobE5

Kris's LinkedIn: https://www.linkedin.com/in/krisjenkins/

Kris's Twitter: https://twitter.com/krisajenkins

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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/

In this episode, I have a chat with Antti Rask, Juha Korpella, Niko Korvenlaita, Russell Willis, and Kosti Hokkanen. We chat about data, startups, and business in Finland and Europe.

My voice is sort of working, and I chat about Tristan Handy's article that raised quite a ruckus this week, "Is the "Modern Data Stack" Still a Useful Idea?"

In the end, the Modern Data Stack won - people use the cloud for analytics. And everything ends, so I'm excited for what's next.

Article: https://roundup.getdbt.com/p/is-the-modern-data-stack-still-a?r=oc02

Jordan Tigani is back to chat about why small data is awesome, data lakehouses, DuckDB, AI, and much more.

Motherduck: https://motherduck.com/

LinkedIn: https://www.linkedin.com/in/jordantigani/

Twitter: https://twitter.com/jrdntgn?lang=en

Colleen Fotsch is one of the highest performing (and kindest/nicest) people I know. She's a former NCAA swimmer at UC Berkley, where she was a two-time national champ, American record holder, and Olympic qualifier. She's also a multiple-time Crossfit games athlete and competed on the US National Bobsled Team, where she was supposed to go to Olympic qualifiers, but got sidelined by a tragic injury which she discusses. On top of all of this, she's a data analyst! In this show, we discuss her evolution from athlete to analyst, the gory details of being a top-level competitive athlete, and much more. If you're interested in what it takes to compete at the highest levels, you'll definitely like this episode. I'm proud to call Colleen my coach, and I'm also fortunate to mentor her in her data journey. Enjoy! Instagram: https://www.instagram.com/colleenfotsch/?hl=en YouTube: https://www.youtube.com/c/ColleenFotsch LinkedIn: https://www.linkedin.com/in/colleenfotsch/

Sadie St. Lawrence chat about all sorts of stuff - mind and machines, community building, optimizing time, focus, and social capital, and much more.

Women in Data: https://www.womenindata.org/

LinkedIn: https://www.linkedin.com/in/sadiestlawrence/

Lekhana Reddy is a data content creator focusing on mindfulness. We chat about how mindfulness in technology is key, especially given the need to maintain humanity with the rise of AI.

LinkedIn: https://www.linkedin.com/in/lekhanareddy/

Instagram: https://www.instagram.com/storytellingbydata/

Paco Nathan is a national treasure. He's not only an OG in the field of AI, but he's also instrumental in early hacker and cyberpunk culture.

When I first met Paco, it suddenly clicked that I'd seen his name in various cyberpunk and alternative zines back in the 1990s. We have a chat all sorts of crazy stuff, and I feel like we only got to 5% of the stories..

Just wrapped up DEWCon, a great data engineering conference in Bangalore, India. I've participated in most data engineering events around the world this year, and I keep seeing the same things - data engineers seek guidance, mentorship, and a sense of best practices. I think we can build a global data engineering community that helps data engineers level up and share their experiences.

I've had plenty of discussions over the last couple of weeks about data teams - what are they, and how do I measure their success? I dive into a distinction I make about data teams - enterprise vs product - and some key ways to gauge them.

Ken Jee joins the show to chat about how he makes awesome content, podcasting and being authentic, jiu jitsu, maximizing your time, and adapting to AI.

#datascience #kenjee #data #ai

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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.

Check out my substack: https://joereis.substack.com/

Wes McKinney and I chat about Positron, Arrow, how he created Pandas and Arrow, and what makes him tick.

There's the interview you think you're going to have, then there's the interview you get. This is one of those, in the best way possible. I expected to chat about his time at Snowflake. We didn't even get past his early days building data warehouses because it was so fascinating. Did you know Kent is arguably one of the very first practitioners (probably an accidental inventor) of DataOps?

This is sort of a "prequel" episode. Kent Graziano and I chat about his early days as a data practitioner.

Ari Kaplan (Head of Evangelism at Databricks) joins me to chat about all things data intelligence, data lakehouses, the role of evangelism in tech companies, automation, and much more.

Jason Taylor and I chat about low-key data happy hours, getting outside of your comfort zone, finding new ideas, the divides in the data space, fighting dumpster fires, and much more. This is a wide-ranging chat about a lot of key topics in the data space. Enjoy!

LinkedIn: https://www.linkedin.com/in/jasonbennetttaylor/

Jordan Morrow has written a ton, including four books. We chat about the process of writing books, the ins and outs of working with a publisher, the role of AI in writing, and much more. If you're interested in writing a book, this is a crash course in what you should know. Enjoy!

Bill Inmon and I sat down in his home over a weekend to tell me the history of the data industry. This is a very rare and wide-ranging conversation about the dawn and evolution of the data industry, straight from the godfather himself.

Dave Langer teaches data literacy with the world's most popular data tool - Excel. We chat about why Excel is awesome, ways to teach data to the masses, and much more.

Dave Langer LinkedIn: https://www.linkedin.com/in/davelanger/

Dave on Data YouTube: https://www.youtube.com/@davidlanger8217

Website: https://www.daveondata.com/

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If you like this show, give it a 5-star rating on your favorite podcast platform.

Purchase Fundamentals of Data Engineering at your favorite book seller.

Check out my substack: https://joereis.substack.com/

What am I seeing in data engineering in 2024? Listen and find out.

Rehgan Bleile joins me to chat about the challenges and importance of AI governance and adoption. We also discuss the lack of representation of women in conferences, and efforts to create genuine opportunities for women speakers.




AlignAI: getalignai.com

LinkedIn: https://www.linkedin.com/in/rehganavon/

Women in Analytics: https://www.womeninanalytics.com/

Joseph Machado and I chat about teaching data engineering, trends in data engineering, and the state of data content and influencers.

LinkedIn: https://www.linkedin.com/in/josephmachado1991/

Website: https://www.startdataengineering.com/

Chris Tabb (LEIT Data) and I hang out at my house and chat about data monetization and business value. 

What the heck are those things? Good question. Listen and find out.

LEIT Data: https://www.leit-data.com/

Chris Tabb: https://www.linkedin.com/in/chris-tabb-datatips/

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If you like this show, give it a 5-star rating on your favorite podcast platform.

Purchase Fundamentals of Data Engineering at your favorite book seller.

Check out my substack: https://joereis.substack.com/

Gordon Wong and I chat about why most data teams aren't that valuable, and ways data teams can deliver more value.

The economic downturn is affecting the tech and data industry in a major way. Lots of layoffs, consolidation, and pain. But is this also a good thing for the industry? Listen and get my opinion in this nerdy rant about the economy, interest rates, and doing more with less.

#data #dataengineering #datascience

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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.

Check out my substack: https://joereis.substack.com/

Christian Steinart and I chat about data consulting in unsexy and niche industries (like roofing in Christian's case). We go through starting a consultancy, the mental game of running a business, getting leads, and much more.

LinkedIn: https://www.linkedin.com/in/christiansteinert96/

Ergest Xheblati is a data architect and author of Minimum Viable SQL Patterns. We chat about the opportunities and challenges of SQL, things that don't change in tech and data, writing and publishing books, and much more.

LinkedIn: https://www.linkedin.com/in/ergestx/

Other links: https://www.ergestx.com/links/

This morning, the Practical Data Modeling Community held its first group discussion (to be posted very soon). People from all sorts of organizations (biggest companies in the world, universities, small companies) discussed how the approach analytical data modeling.

My major takeaway - your mileage will vary. There's the ideal way of data modeling we're taught, and there's reality. Everyone's situation is different and there's no one-size-fits-all approach that will work for everyone.

The discussion was awesome, and we'll do it again soon. If you're not part of the Practical Data Modeling Community, please join here: https://practicaldatamodeling.substack.com/

Demetrios Brinkmann is the co-founder of the massively global MLOps Community. We chat about AI hype vs reality, building a global tech community, and ROI of AI projects, and much more.

LinkedIn: https://www.linkedin.com/in/dpbrinkm/

MLOps Community: https://mlops.community/

A question I'm asked several times a week is how to learn in a rapidly changing world. To me, this boils down to identifying your true north and mastering the fundamentals. Learn more about my approach in this 5-minute Friday. ----------------------- 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/

Venkat Subramaniam is a programmer, author, speaker, and founder of Agile Developer, Inc. I've seen him speak several times, and was always blown away by his passion and technical depth. So, I was excited to have him on the podcast.

We chat about agile development in the real world, learning to do less, and much more. Venkat is extremely wise, and I very much enjoyed our discussion. Enjoy!

LinkedIn: https://www.linkedin.com/in/vsubramaniam

Twitter: https://x.com/venkat_s

Whenever Kevin and I get together, we "nerd snipe" each other. This conversation is no different, and it's a wide-ranging conversation about how the data landscape evolves alongside LLMs, education, startup mentorship, and the possible (looming?) startup mass extinction.

Kevin's LinkedIn: https://www.linkedin.com/in/kevinzenghu/

Metaplane: https://metaplane.dev/

In my newsletter last week, I wrote "Data’s still a mess. Most data initiatives fail. Data teams are seen as a cost center and not getting the support they deserve. Same as it ever was."

Here, I unpack those four sentences. Data teams need to stop stop playing to not lose. Instead, they need to play to win!

Jarod Santo and Adam Stacoviak from The Changelog join me for 1.5 hours of free-flowing chats about planned obscelescene, old school vs new school consumer tech, the XZ Backdoor incident, the job market doldrums (plus tips for finding work and starting a biz), and being unemployable.

Jarod and Adam are two of my favorite people to talk with, since we can literally chat about anything for hours. Enjoy!

Changelog: https://changelog.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

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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/

This week I posted about how some major conferences charge a bunch of money for tickets and sponsorship, but don't pay speakers. As a speaker, I find this unethical and exploitative. Here, I unpack my thoughts on speaking at conferences. If you're a speaker, or want to become one, this is worth your time to listen.

My post: https://www.linkedin.com/posts/josephreis_this-morning-i-had-to-decline-a-speaking-activity-7252331326287011841-NPG6

John Giles is a legend in the data modeling world, having authored "Nimble Elephant" and "The Elephant in the Fridge," and written extensively on the topic. John and I discuss the power of using data model patterns, enterprise data modeling, "data town plans," and much more. It was an honor to chat with John, and I felt like I was conversing with someone who comes from a more advanced dimension than most data practitioners. You'll learn a ton from this discussion.

John's website: https://www.countrye.com.au/

Books: Nimble Elephant (https://www.amazon.com/Nimble-Elephant-Delivery-Pattern-based-Approach/dp/1935504258), The Elephant in the Fridge (https://www.amazon.com/Elephant-Fridge-Success-Building-Business-Centered/dp/1634624890)

LinkedIn: https://www.linkedin.com/in/john-giles-data/

#data #datamodeling

Is it better to make a perfect or good enough data model? It depends…

I've been told that I "say the quiet parts out loud." It might be calling out "data science" and AI as overhyped, or anything else I've ranted about online over the years.

In this episode, I unpack what that means and why I do it.

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.

I often get some questions - What happened to data modeling? Where do I learn data modeling? Where the heck is your new book?

Well, at least some of your questions will be answered in this podcast.

I'm launching a new project called Practical Data Modeling on Substack. You'll get weekly articles, early chapters of my new data modeling book, community discussions, and much more.

Subscribe to Practical Data Modeling: https://practicaldatamodeling.substack.com/

Karl "Ivo" Sokolov and I are good friends, and we chat about how he views innovation in Europe, regulations, Western and Eastern Europe, moving from services to a product, and much more. Ivo is a straight shooter, and I always enjoy chatting with him. Enjoy!

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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/

Rebecca Taylor has a ton of experience with ML, having worked as lead, and senior ML engineer, and holds a PhD in Bayesian Inference. We chat about making ML succeed in larger companies. This is a skill in itself, often requiring stakeholder management and getting buy-in. If you're in a similar situation, this episode is for you!

Rebecca's LinkedIn: https://www.linkedin.com/in/rebecca-taylor-ml-ai/

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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/

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.

I've spent the last three weeks visiting the UK, Australia, and New Zealand. Here are my observations and anecdotes about the data and ML/AI industry from countless chats with executives, practitioners, and pundits.

Nowadays, it seems like lots of people want to become data influencers and content creators. Ravit Jain and I chat about how to build an audience, the power of LinkedIn, and much more.

The Ravit Show: https://theravitshow.com/

LinkedIn: https://www.linkedin.com/in/ravitjain/

Tristan Handy and I chat about balancing competing tensions, both personally and leading dbt Labs. We also discuss the power of organizational behavior, naming problems to solve, and home remodeling.

This is different from the normal interviews you'll hear with Tristan, and I hope you enjoy it!

#dbtlabs #data #analyticsengineering

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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/

On a panel this week, we discussed the topic of career progressions. It got me thinking about the various ways people navigate their careers. Here's my advice if you're trying to move up the corporate ladder, frustrated in your current role, or want to jump ship and do your own thing.

After a whirlwind of conferences with the two "big players in the data space," I share some thoughts on how we can improve the conferences targeted at the data engineering community.

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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/

Vijay Yadav (Director of Data Science at Merck) joins me to chat about a very interesting project he launched at Merck involving LLMs in production. A big part of this discussion is how to make data ready for generative AI.

This is a great example of an LLM-native use case in production, which are rare right now. Lots to learn from here. Enjoy!

LinkedIn: https://www.linkedin.com/in/vijay-yadav-ds/

Lindsay Murphy joins me to chat about whether companies are ready for AI in their data and analytics workflows. The verdict - listen and find out more :)

Lindsay's LinkedIn: https://www.linkedin.com/in/lindsaymurphy4/

Chris Bergh joins me to chat about all things DataOps. We also discuss lean, removing waste from data processes and teams, and much more.

DataKitchen: https://datakitchen.io/

DataOps Manifesto: https://dataopsmanifesto.org/en/

Marketing is a well-established field, yet there is still a massive gulf between CEO and CMO expectations. If CMOs are still trying to get traction with their CEOs, what hope do Chief Data Officers have? I rant about this.

WSJ article: Divide Between CMOs and CEOs is Growing: https://www.wsj.com/articles/divide-between-cmos-and-ceos-is-growing-research-finds-a73374f4?st=bcayeo7wc9j18fd&reflink=desktopwebshare_permalink

I consider Steve Hoberman to be one of the original data modelers, having practiced and taught data modeling since the 1990s. He also runs the venerable Technics Publications, which I consider the foremost publishers of data-oriented books.

Steve and I discuss data modeling's past, present, and future. If you're into data modeling, this is a must-listen. Enjoy!

Technics Publications: https://technicspub.com/

Steve Hoberman LinkedIn - https://www.linkedin.com/in/stevehoberman/

I teach data at the University of Utah, and I’m also on the board of advisors for my department. What curriculum and approach do I advise universities use for teaching data and technology? Listen and find out.

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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.

Check out my substack: https://joereis.substack.com/

ChatGPT was the iPhone moment for AI, and things are moving insanely quickly. What do generative AI models mean for us, especially children, who are arguably the last of the Pre-AI generation? I dive into some thoughts this week about how we need to work alongside the machines, the impact of generative AI on kids, and so on. Buckle up. We are in for a very interesting next few years as we sort out where AI fits into our day-to-day lives.

#data #datascience #dataengineering #chatgpt #ai

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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.

Check out my substack: https://joereis.substack.com/

Just wrapped up a couple of days at the CDO/CAIO Summit in Boston. There are a lot of corporate mandates to "do AI", but also a disconnect in the support and empowerment required to succeed. I unpack some observations of this disconnect, and why it reminds of of the South Park Underpants Gnomes - "AI...?...Profit"

There's an inverse relationship between the value you add and how much you need to tell people about it. If you're adding value, you'll know - you don't need to talk about it. You're doing it. Also, the same goes with "data." If you're putting "data" as the center of the conversation, you just lost the game.

As I've ranted for a while now, I think our biggest challenge as an industry is the knowledge and skills to do our properly do our jobs. Too often, I see data professionals flounder on seemingly simple problems, even using the hottest, coolest technologies. Don't blame the tool, blame the user.

How do you sharpen your skills? I give some advice in this episode.

Most people approach their careers via 1:1 - 1 employee: 1 employer, 1 consultant: 1 client, etc.

In this rant, I discuss why you should consider 1:many as a way to level up your career and visibility.

In today's Practical Data Modeling group discussion, we chatted about how to get buy-in for data modeling. The question was intentionally vague, because context is key. I give some thoughts on this topic, and how you can generalize this to most situations where you need to get buy-in.

Practical Data Modeling: https://practicaldatamodeling.substack.com/

Jess Haberman and I chat about how to negotiate a book deal. She's been in publishing for ages and knows her stuff!

Also, I wish I had this episode handy while I was shopping around Fundamentals of Data Engineering, because Jess agreed to publish my book while she was at O'Reilly ;)

We also talk about how AI will change publishing.

Larry Burns and I chat about all things data teams—how they fail, their challenges, and how they can add value. To add value, we need to reimagine not only how we think about data but also how we manage knowledge.

Larry brings a fresh and battle-worn perspective to the data field, and if you work on or manage a data team, this conversation is worth a listen.

LinkedIn: https://www.linkedin.com/in/larryburnsdba/

I'm starting to see more and more discussions about soft skills and people skills. In this episode, I talk about why tech skills are table stakes, and soft skills are where you need to level up if you want to boost your career.

Office Space clip: https://www.youtube.com/watch?v=hNuu9CpdjIo

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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/

Alex Freberg, aka Alex The Analyst, chats with me about playing the long game with content, empathizing with his audience, how he grew a massive YouTube following, his new Analyst Builder courses, and much more.

YouTube: https://www.youtube.com/@AlexTheAnalyst

LinkedIn: https://www.linkedin.com/in/alex-freberg/

Analyst Builder: https://www.analystbuilder.com/

Sol Rashidi is one of the most experienced and decorated data executives in the world. We chat about ways for data projects to succeed and fail, being a translator between tech and the business, why she's a recovering C-Suite data executive and much more.

Data products are a very popular topic these days. The challenge is we need new thinking and approaches that differ from how we've worked with data in the past. Jon Cooke and I chat about the mindset shift needed to make data products successful.

Jon Cooke's LinkedIn: https://www.linkedin.com/in/jon-cooke-096bb0/

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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.

I’m at the Gitex Dubai conference. It’s huge, with 170k in attendance! There’s a lot of hype about AI. I unpack my thoughts on the latest AI hype cycle in my usual ranty manner. Enjoy!

Safiyy Momen and I chat about the good and bad of the Modern Data Stack, controlling cloud costs, boring engineering, and much more.

LinkedIn: https://www.linkedin.com/in/safiyy-momen/

Randy Bean and I discuss why generative AI is making companies more data-oriented, the latest Wave Stone Data and AI Leadership Executive Survey, his career and writing process and much more.

The tech and data industry needs more candor. The point of this podcast is for me (and my guests) to rant about their opinions on the tech and data industry in a very honest way. 

Juha Korpela is a world-renowned expert in conceptual data modeling. He joins me to discuss the power of conceptual data modeling, why the data modeling world is broken today, data products, and much more.

LinkedIn: https://www.linkedin.com/in/jkorpela/

Bethany Lyons and I chat about disrupting the recruitment industry, startups, and the future of work.

Matt Harrison is the author of many of the most successful Python books, including Effective Pandas, Effective XGBoost, The Machine Learning Pocket Reference, and many more. I consider him the top author of Python books and content on the planet.

He stopped by my house to chat about self-publishing technical books, the pros and cons of using a publisher, book piracy, and much more. We both talk about our experiences as best-selling technical authors, and don't hold back in this wide ranging and very candid conversation. Enjoy!

Note - my audio got a bit clippy in spots. Sorry if I blew up your speaker.

This wasn't the interview I expected to do. I thought I'd interview Nick Freund about his startup, Workstream. Between the time we scheduled our podcast and when we hit the record button, he shut down his company. That's a pretty major shift, to say the least.

What's it like to shut down a company? Nick discusses the various pivots of his startup, trying to raise capital in a brutal funding environment, the data tooling landscape, the process of shutting down a company, and much more.

This is an emotional episode, and I'm glad we got the opportunity to make it happen. I feel like stories like Nick's are all too common, yet rarely vocalized in the brutally honest way that Nick describes his story.

Nick's LinkedIn: https://www.linkedin.com/in/nick-from-workstream/

Jordan Morrow and I hung out at my house and chatted about all things data literacy, the great outdoors, and more. Enjoy!

The word "model" is used a lot by data professionals. There are dbt models, machine learning models, relational models, and conceptual, logical, and physical models. My concern is we're missing the bigger picture of what data modeling was initially supposed to accomplish, which was to represent reality and structure it as data. The bigger implication is that our various "models" will become too myopic and miss the larger broader context of the reality of how we use data to serve our organizations.

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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/

Boring is back. As technology makes the lives of data engineers easier with respect to solving classical data problems, data engineers can now move to tackle "boring" problems like data contracts, semantics, and higher-level and value-add tasks. This also sets us up to tackle the next generation of data problems, namely integrating ML and AI into every business workflow. Boring is good.

Matt Housley hangs out at my house and we chat about Data NIMBYism and gatekeeping. What is that? Listen and find out.

David Foster just published the 2nd edition of his amazing book, Generative Deep Learning (O'Reilly 2023). We chat about a lot - running a consultancy, all things writing, the impact of AI on kids, why in-person events matter more than ever, and much more.

David's LinkedIn: https://www.linkedin.com/in/davidtfoster/

Book (Amazon): https://www.amazon.com/Generative-Deep-Learning-Teaching-Machines/dp/1492041947

Applied Data Science Partners: https://adsp.ai/

Paul Blankley and Ryan Janssen are the co-founders of Zenlytic. They started a BI company with an LLM-first approach (back before LLM's were insanely cool). We talk about the future of BI, and how LLM's will change the face of data and analytics.

Zenlytic: https://www.zenlytic.com/

Paul's LinkedIn: https://www.linkedin.com/in/paulblankley/

Ryan's LinkedIn: https://www.linkedin.com/in/janssenryan/

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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/

Imagine two extremes. On one end, data modeling is done perfectly and harmoniously across the data lifecycle. On the other end, data modeling is ignored and thrown into the dustbin of history. Along this spectrum, where do you think we are as a data industry?

I'm leaving this question open-ended right for now and would appreciate your thoughts.

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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

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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/

Data can be a rough industry. Data professionals often feel alone and in need of someone to talk to. I've been hosting "data therapy" sessions for the last couple months. Here are my thoughts on them, and why I think they're critical to helping professionals feel heard and learn from others.

Join here: https://practicaldatamodeling.substack.com/

I've been spending some time in Europe, and most recently returned from Germany the other day. There are definitely some differences between the US and Europe, particularly in how each conducts business and regulation. Tune in for my thoughts on these differences.

#data #dataengineering #datascience

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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.

Check out my substack: https://joereis.substack.com/

It's not enough to know or peddle one data modeling technique these days. That's like fighting in the UFC knowing only thumb-wrestling. The world is very complicated with respect to data. To be a data practitioner, you need to be awesome in not just one, but MANY data modeling techniques. This is what I call Mixed Model Arts, which will be discussed further soon. Anyway, don't be 1-dimensional. Know a lot about a lot.

Medical data is a mess. Aaron Neiderhiser and Coco Zuloaga from Tuva Health are here (at my house) to answer why this data is insanely complex, and what can be done to fix it. They take a first-principles approach that you might find interesting.

George Park is a Czechia-based data engineer. We chat about automation, change management and culture, data modeling (Data Vault in particular), and much more. George lives on the front lines of helping customers, so this is a good discussion if you like to hear from a real practitioner.

George's LinkedIn: https://www.linkedin.com/in/george-park-599846136/

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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/

In this episode, I talk about why history matters for technology professionals. When you understand the history of technology, techniques, and approaches, you have the context to understand where they fit into your situation. Ignore history at your peril.

I've seen a TON of horror stories with tech debt and code migrations. It's estimated that 15% to 60% of every dollar in IT spend goes toward tech debt (that's a big range, I know). Regardless, most of this tech debt will not be paid down without a radical change in how we do things. Might AI be the Hail Mary we need to pay down tech debt? I don't see why not...

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/

Katharine Jarmul (Principal data scientist at Thoughtworks and author of Practical Data Privacy (O’Reilly, 2023)) and I chat about all things data privacy. She brings battle-tested experience and unique perspectives in the areas of ML/AI privacy, AI risk, regulation, and much more. I learned a ton, and I hope you do too!

LinkedIn: https://www.linkedin.com/in/katharinejarmul/

Twitter: https://twitter.com/kjam

Probably Private newsletter: https://probablyprivate.com/

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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.

Check out my substack: https://joereis.substack.com/

Christophe Blefari and I chat about why teaching data engineering is so damn hard, how generative AI will change technology and data education, and more.

Site: https://www.blef.fr/

LinkedIn: https://www.linkedin.com/in/christopheblefari

In my travels and virtual conversations with data teams and practitioners around the world, the same thing keep popping up - data teams feel misunderstood and under-appreciated. If we're going to make progress as an industry, it's time to stop playing defense, and start playing offense.

In this episode, I go through the reasons why I put a stop to most meetings going forward. I urge you to figure out how you can better control your time since it's the one thing you never get back.

Also, I've got a new weekend newsletter dropping tomorrow! Sign up at joereis.substack.com

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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/

I recap two events from this week - Matillion's Data Unlocked and the first MLOps Community event in Silicon Valley, hosted at Coactive.ai's office. Lots to unpack in 8 minutes, so let's get going.

Kishore Aradhya and I both teach, and we agree this is a very difficult landscape to determine what and how to teach. Against the backdrop of generative AI, we discuss the role of universities in teaching tech and data, the role of a teacher, how to teach data, and much more.

DSPY - https://github.com/stanfordnlp/dspy