I speak at a lot of conferences, and I've lost track of how many questions I've answered. Since conferences are top of mind for me right now, here are some tips for asking good (and bad) questions of speakers.

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/

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

Ilya Reznik has been in the ML game for ages, having worked at Adobe and Twitter and led teams at Meta, among others.

We chat about leading ML teams, AI today, creating content, and much more.

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

What happens when AI can generate content about whatever - or whoever - whether it's true or not? Welcome to 2023 and beyond.

I think the Internet is about to become a sea of complete sh*t of uninteresting and inaccurate content. The value of most content on the Internet will be less than worthless.

What can content creators and authors do? I provide some ideas...

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"

Eleanor Thompson is the most knowledgeable person I know on the topic of vendor partnerships. We dive into the details of what makes a great partnership, tips on starting a partner program, certifications, and much more.

Are you a technology or data vendor looking to start a partnership program, or improve your existing one? Or a consulting company looking to partner with a vendor? Having worked with many partners, I can tell you that partnerships have always had ups and downs. I wish I'd listened to this episode several years ago. Enjoy!

Ben Rogojan, aka Seattle Data Guy, needs no introduction. He's a force of nature in the data engineering content world.

We chat about his origin story (sort of like a superhero), content creation, consulting, cooking, and much more.

You may have heard of Live Action Role Playing (LARP), where people dress up like fantasy characters and sword fight in a park or a Wal Mart parking lot. Some data teams LARP too...

Data LARPs are a real thing, often identified by pretending to do "data stuff", while never actually pushing anything into production. Are you Data LARPing? If so, what can you do? Listen and find out.

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.

Karin Wolok and I chat about all things devrel - what it is, why it matters, the good the bad, and everything in between. We also talk about her time in the music industry, which is a fascinating side thread. Karin is amazingly smart, energetic, and fun to talk with. Enjoy!

Note - this was recorded right after the awesome DEWCon, the premier data engineering conference in Bangalore, India. Shoutout to everyone there!

Like most of you, I spent last weekend and the earlier part of this week following the OpenAI drama. Plot-twists galore! Every minute seemed like a new adventure. In the midst of the plot twists and turns, I noticed quite a few people saying, "This was all predictable", and then offering prognostications, most of which turned out to be very wrong. If even the OpenAI insiders couldn't figure out what was going on, how would the person on the street?

It's a good reminder that you need to approach the world with a sense of humility and try not to be a know-it-all. Don't be afraid to say "I don't know."

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.

Peggy Tsai joins me to chat about a ton of hard topics. We chat about how to set up Chief Data Officers for success (not easy), data maturity, data and ESG, and a ton more. Enjoy this very wide-ranging chat.

As I travel this Fall, I'm reminded that most people don't work at fancy tech companies. Most people work at traditional companies with "boring" data and tech stacks. And that's OK. Boring is good.

Katharine Jarmul and I chat about the Biden AI Executive Order. Enjoy!

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.

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

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.

In my global travels, I've spoken to countless practitioners and leaders in the data field. I discuss two common themes of questions I get - "How do I work with the business?" and "What tools should I use?"

Matt Sharp and Chris Brousseau join me to chat about writing their new book "LLMs in Production" (Manning). What's it like to write a book in a field that's changing at light speed? How do two people write a book together? We dive into this and much more.

Note - we recorded this outside at the Utah State Capitol. There's a bit of background noise, but it hopefully doesn't distract from the conversation. It was too nice of a day to be stuck inside :)

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!

Johnny Graettinger (CTO of Estuary) joins the show to give a clinic on streaming and immutable logs. We cover a lot of ground in this technical deep dive. Enjoy!

Estuary: https://estuary.dev/

Gazette: https://gazette.readthedocs.io/en/latest/

Github (Estuary Flow): https://github.com/estuary/flow

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

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.

Bob Muglia joins the show to talk about why we need to move beyond SQL, semantic models, the power of knowledge graphs, the past, present, and future of databases, and much more.

Bob has a storied history in the data space, having significant involvement with Microsoft Office, SQL Server, Snowflake (former CEO), and much more. It's rare to meet someone with such a deep involvement in the creation of our industry, and this was a fascinating conversation.

Also, check out Bob's book, "The Datapreneurs." One of the best books about the data industry I've read in ages.

LinkedIn: https://www.linkedin.com/in/bob-muglia/

X: https://twitter.com/Bob_Muglia

Book: https://www.amazon.com/Datapreneurs-Promise-Creators-Building-Future-ebook/dp/B0BZQFJ5RP

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!

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.

Egor Gryaznov joins me to chat about the "Non-Modern Data Stack", getting out of our data bubble, and much more. If you like a refreshing conversation talking about the past, present, and future of our industry, this is for you.

BigEye: https://webflow.bigeye.com/

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

Vendors are an integral part of conferences (they pay for them, for one). But what happens when vendors face a tough market? Between higher interest rates, a tough funding environment, and a lukewarm market for what vendors are selling, what happens? I unpack some thoughts on what I think 2024 will look like for vendors at conferences.

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/

Michel Tricot (CEO of Airbyte) joins me to chat about the impact of AI on the modern data stack, ETL for AI, the challenges of moving from open source to a paid product, and much more.

Airbyte & Pinecone - https://airbyte.com/tutorials/chat-with-your-data-using-openai-pinecone-airbyte-and-langchain

Note from Joe - I had audio issues cuz he got a new computer and didn't use the correct mic :(

Juan Sequeda and I chat about knowledge graphs (he's an OG in this area), the potential of LLMs on structured datasets, and much more. This is an honest, no-BS chat about the transition from a data-first world to a knowledge-first world. Enjoy!

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

data.world: https://data.world/product/

website: https://www.juansequeda.com/

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/

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.

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.

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.

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

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/

The massive attention on AI means the data industry has a shot at finally succeeding with the things we've been struggling with for decades - "adding value", data quality and modeling, governance, etc. For AI to work, these things need to properly function. But are we up for the task? And if we can't get it right NOW, when?

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/

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

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/

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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.

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)

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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/

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.

Uncle Rico is a character in the movie Napoleon Dynamite, who is stuck in the past, reminiscing about his days as a high school football star. If only he'd won the game and went to the state championship. Some of the data industry reminds me of Uncle Rico.

During a recent panel, there was a question about whether AI can help with data management (governance, modeling, etc).

Some people were quick to dismiss this, saying that machines are no substitute for humans in their understanding and translating of "the business" to data.

Yet why are we still perpetually stuck in the mode of "80% of data projects fail"? Might AI/ML help data management move out of its rut? Or will it stay stuck in the past?

Also, please check out my new data engineering course on Coursera!

https://www.coursera.org/learn/intro-to-data-engineering

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

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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/

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.

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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/

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/