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/mcp

GoodData: 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.com GoodData: https://www.gooddata.com Ellie.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 Showcase 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.

GoodData Webinar Analytics 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. 📆 May 27, 2025🕘 9:00 AM PDT, 12:00 PM EDT, 6:00 PM CEST🔗 Register here!

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, s****y 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.