The Joe Reis Show

Regular guest Gordon Wong joins me to chat about the impact of AI on attention and expertise, product management, and much more.

In this episode, I ramble and speculate about what the next-generation data architectures look like. Thanks for Keboola and GoodData for sponsoring this episode.Keboola: https://www.keboola.com/mcpGoodData: GoodData.com/resources

Zhamak Dehghani (creator of Data Mesh, CEO of NextData) joins me to chat about what she thinks is next in data - autonomous data products, decentralized data and AI, and much more. Zhamak is one of the people I most respect in our industry. She's a once-in-a generation phenomenon who will change the trajectory of our industry.

Matthew Scullion (CEO, Co-Founder of Matillion) joins me to chat about the future of data engineering, namely agentic data engineering teams. What does this new world look like? Matthew shares some ideas of what he's building at Matillion, and the broader context of what agentic AI means for the data ecosystem, teams, and workflows.

Wrapping up the week at Snowflake Summit. As always, the big platform ate away at their partners. If you're a partner, what can you do to shield yourself from platform cannibalization? In this episode, I give some advice from what I've seen in the data ecosystem over the years.

Svetlana Tarnagurskaja (CEO of the Dot Collective) joins me to chat about her entrepreneurial journey in the data space, building a boutique data consultancy, competing with Big Consulting, the challenges of building a team, and the importance of creating a human-centric company culture.The Dot Collective: https://www.thedotcollective.co.uk

Hannes Mühleisen shows off DuckLake and answers live questions.DuckLake: https://duckdb.org/2025/05/27/ducklake.html

Ash Smith is a data engineer based in Perth, Australia (the most remote city in the world). We chat about data products, interoperability, and the importance of collaboration and incentive structures within data teams.

Regular guest Gordon Wong and I chat about what you should think about if you want to work in data. Spoiler - it's probably not what you think.Shoutout to GoodData and MonteCarlo for sponsoring this episode.

Imagine writing SQL and getting instant results as you type? Yes, this is reality now. It's amazing!DuckDB/MotherDuck's Instant SQL made a big splash at last month's Data Council. Hamilton Ulmer gives a demo of Instant SQL at the Practical Data Community.----------------------------Instant SQL: https://motherduck.com/blog/introducing-instant-sql/Practical Data Community Discord: https://discord.gg/gNfw5AKWSK

Gaëlle Seret is a data leader based in France. We chat about how she helps large organizations drive change, especially around data architecture and strategy. We dig into her approach to upskilling teams, why data strategy matters, and how to work through the inevitable organizational challenges that come with transformation. We also discuss the AI in learning and work, and some interesting differences in education between USA and France. Enjoy!

Last week I posted about the gulf in the data industry between people in favor and opposed AI. The data industry has an atrocious track record of success over the decades. Shall we keep repeating the same mistakes with AI? I think AI denialism is holding back and AI has the potential to help us correct a lot of the sins of the past, namely quick delivery of value. Whether we get there is another question...Thanks to dbt, GoodData, and Ellie.ai for sponsoring this podcast.dbt: https://www.getdbt.comGoodData: https://www.gooddata.comEllie.ai: https://www.ellie.ai

Ryan Russon is an ML Engineer. He stopped by my house for a practical and grounded chat about ML and AI. Enjoy!---------Join dbt Labs May 28 for the dbt Launch Showcase to hear from executives and product leaders about the latest features landing in dbt. See firsthand how features will empower data practitioners and organizations in the age of AI.Thanks to dat Labs for sponsoring this episode.

Some people speculate that AI will make software and data engineers obsolete. If the only thing engineers do is write code, sure. But we do a lot more than that, and I believe we'll actually need more engineers, not fewer.In this episode, I discuss how I think AI will change the craft of software and data engineering. Spoiler - I think it will make it way more fun and productive.------------------------------Thanks to dbt and GoodData for sponsoring this episode. Please support them, as they're awesome.dbt Launch ShowcaseJoin dbt Labs May 28 for the dbt Launch Showcase to hear from executives and product leaders about the latest features landing in dbt. See firsthand how features will empower data practitioners and organizations in the age of AI.---------GoodData WebinarAnalytics and data engineering used to live in separate worlds—different teams, different tools, different goals. But the lines are blurring fast. As modern data products demand speed, scale, and seamless integration, the best teams are embracing engineering principles and best practices.In this no-BS conversation, Ryan Dolley, Matt Housley, and Joe Reis, dive into how engineering principles are transforming the way analytics is built, delivered, and scaled.

Laura McDonald is an enterprise account executive, and she walks me through navigating the complex world of enterprise sales. We chat about the sales cycle, the importance of building relationships, the challenges of navigating long complicated procurement processes, and much more. Whether you're a sales rookie, an experienced salesperson, a founder, or just interested in sales, you'll learn something new from this conversation.

I've spoken all over the world, at the biggest events, the most intimately small, and everywhere in between. In this Practical Data Community lunch and learn, I share some experiences with public speaking, give some advice on getting your first public speaking gig, how to prepare, preparing talks, dealing with stage fright, getting paid, and much more. Enjoy!From the Practical Data Lunch and Learn, May 9, 2025

Dia Adams and Gordon Wong join me for a chat about data strategy in the age of AI.

Michael Drogalis joins me to chat about building his company - Shadow Traffic - in public. We discuss sales, the psychological toll of rejection, the rollercoaster of entrepreneurship, and strategies for audience building and content creation.

John Giles joins me to discuss his new book, "The Data Elephant in the Board Room," conceptual modeling, the unreasonable effectiveness of data modeling patterns, and more.

Zhamak Dehghani joins the Practical Data Community for an open-ended Q&A about autonomous data products, Data Mesh, NextData and much more.NextData: https://www.nextdata.com/Practical Data Community: https://discord.gg/gNfw5AKWSK

I've recently spoken to several groups of students (undergrad and graduate) about the data industry, career advice, and more. Here, I distill some of my major points about careers, finding work, and more.If you're graduating this Spring 2025, congrats!This episode is brought to you by GoodData.

Jessica Talisman and I hang out at my home and chat about libraries, data, ontologies, knowledge, shitty tech jobs, and much more.

Sarah McKenna joins me to chat about all things web scraping. We discuss its applications, the evolution of alternative data, and AI's impact on the industry. We also discuss privacy concerns, the challenges of bot blocking, and the importance of data quality. Sarah shares ideas on how to get started with web scraping and the ethical considerations surrounding copyright and data collection.

I recently overheard someone say, "I Don't Need to Learn Anything Anymore" because AI would do all of this person's work. This got me thinking about the future of learning, human expertise and depth, and more.

Juan Sequeda and Jesus Barrasa are among the top experts on graphs in the world. In this episode, we chat about the definitions of semantics, ontologies, and the differences between RDF and property graphs, etc. We also talk about how AI is giving graphs a new surge of interest.

Data teams have had a rough few years. Lots of layoffs and cuts, doing more work with fewer resources, and a general sense of malaise. On top of all of this, now we're in the middle of a trade war. This is war. If you're a data team, you need to act accordingly.

Tim Berglund is the OG of DevRel. We chat about the art and craft of developer relations, hacking on hardware, and much more.

Just wrapped up a whirlwind tour, giving a workshop in Atlanta and then attending Google Cloud Next. B2b nonstop action, and I'm glad to home for a bit.While at Next, I had a conversation with another tech old timer friend. We talked about how much we're having using AI as a coding assistant. I'm having fun coming up with wild stuff and seeing if it's possible to build with code. AI's made coding fun again!------------------

Juhani Vanhatapio lives in Finland at the Arctic Circle and is studying data engineering and machine learning. Juhani shares stories about life in the Arctic, the challenges and fun of guiding tours to see the Northern Lights, his AI Assistant for Northern Lights tourism, and his journey into the tech field during the COVID pandemic. This is definitely a very interesting and left-field conversation you'll enjoy.

I'm heads down with some work right now, but here are some random rants on workshops, the tariff chaos, and more.

Vin Vashishta and I chat about the current state of AI in business, the challenges of implementation, the pervasive hype surrounding AI technologies, influencers, and more.

Vinoth Chandar (CEO at Onehouse and creator of Apache Hudi) and I chat about the creation of Apache Hudi, the future of open data lakehouses, and much more.#hudi #data #ai #datalakehouse #dataengineering

People often ask me what I'd change in Fundamentals of Data Engineering. Usually, I reply "not much", as the the Data Engineering Lifecycle still remains intact. However, I see the role of data engineers shifting both left and right. What does this mean? Have a listen.

Vaibhav Gupta and I chat about our shared love for tacos in Austin, the evolution of AI tools, and why new thinking and approaches are required for AI-first tools.BAML: https://github.com/BoundaryML/baml

Mark Freeman joins me to chat about data contracts, the crazy life of being the first employee at a hot startup, writing books and creating content, and much more.#DataEngineering #Startups #AI #DataQuality #DataContracts

I get a ton of questions from people about what their next career move should be. Given the increased turbulence in the job market and how companies are giving the middle finger to their employees, I think people are going to need to question the traditional advice (college, job, "stick it out"). This advice is outdated. Instead, you're going to have to dig deep, embrace discomfort, and figure out your next move.Nick Freund - Closing a Startup https://open.spotify.com/episode/2Iu1qbVklm7hVFniVkdCFQ?si=bcc24223758b48d3

Willis Nana and I chat about the challenges of data engineering leadership, foundational skills, and his journey to a content creator on YouTube.#dataengineering #data #ai #datateam #leadership

Salma Bakouk (CEO of Sifflet) and I discuss the evolving data and AI landscape, the rise of data observability in the age of AI, balancing personal and professional life as a founder, and much more.

Jordan Morrow and I have a lot of experience with public speaking. We get a lot of questions about tips for public speaking. In this episode, we chat about how to get started with public speaking, tips for awesome presentations and talks, and much more.

Simon Späti and I discuss various aspects of writing, data engineering, and the impact of AI on the writing process. Simon shares his journey from business intelligence to data engineering and his current focus on writing. We also discuss the future of writing in the age of AI. Enjoy!

Todd Beauchene joins me to chat about being an early employee at a tiny startup called Snowflake, modern data platforms, and much more.

In this episode, I explain how I use (and don't use) AI for writing.

The Data Cynic, aka, Matthew Kelliher-Gibson, and I chat about all things cynical about the data field, working in Dilbert-land, negotiation for data professionals, and much more.

My semi-regular co-host and bestie Carly Taylor joins me once again. This time we chat about the true cost of replacing engineers with AI. We explore the implications of mass layoffs, the importance of company culture, and the potential for burnout among tech workers.

It seems like quite a few data practitioners I talk with are miserable. Forced to deliver things ever faster, there's not enough time to THINK. Instead, the pressure is to deliver "stuff" in two-week sprints. In this episode, I rant about why not everything needs to be a sprint, and why we need to treat Deep Work versus Delivery Work differently.

John Thompson joins me to chat about his upcoming book, The Path to AGI, his book writing process, and much more.John Thompson LinkedIn: https://www.linkedin.com/in/johnkthompson/

Things aren't great in the world of data practitioners. Lots of technical debt and lack of pride in one's craft. The pressure to do more with less only compounds this problem. And AI will make it far worse.If you think the amount of poorly made data architecture and models is bad now, I think we're in for another level very soon. With AI CoPilot on the rise, right as data skills and knowledge decline, I'm increasingly worried we'll offload our critical thinking and skills to AI. The outcome will be an ever expanding Great Pacific Garbage Patch of AI Data Slop.

Eric Broda and I chat about AI Agent Ecosystems, running consultancies and why AI might be the death of consulting, and more.

Hugo Bowne-Anderson and I chat about the future of AI and automation, agents, and much more.

Ghalib Suleiman, Kevin Connolly, and I have all run data teams. In this episode, we chat about a bunch of data team "what ifs" - running a data team, hiring and firing, and executive commitments

With AI becoming engrained in nearly every product, there's still a BIG problem - AI and product teams have trouble working together. Whether it's different communication and working styles, or lack of a common language, AI teams stall because they can't align with Product.Anne-Claire Baschet & Yoann Benoit join me to chat about unifying AI and Product Development. Article: AI & Product: Two Development Cycles to Unifyhttps://craftingdataproducts.substack.com/p/ai-and-product-two-development-cycles