Toby Mao started his data tooling company, SQLMesh, in 2022, when investing in data tools was unfashionable. Yet, he's managed to get traction with SQLMesh and is on a mission to simplify data transformations and make data easier to work with. We also chat about experimentation best practices, which he learned at some of the biggest tech companies in the world.

This is definitely a great episode if you're interested in startups, data tools, experiments, driving cars, and much more.

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.

Angel Narciso and I hung out at LEAP Riyadh, alongside 215K attendees (wtf?). We chat about all sorts of stuff in the data world, including some blunt convos on the modern data stack and AI, among other things.

I often get questions about how I write and advice on how one might go about becoming a "writer." In this episode, I talk a bit about my writing process and why you (yes you) should also write.

This will be the first in a few episodes and blog posts where I talk about the writing and content creation process, as I get a ton of questions about this. Thanks for your questions and support!

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.

Had a great chat with Keith Belanger yesterday (podcast dropping soon) about how conceptual data modeling fell by the wayside. All too often, people seem focused on physical data modeling. This is a shame, because conceptual is the art and lifeblood of data modeling. As an industry, we need to learn to see (again).

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/

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

Christian Bourdeau and I chat about all things data careers - getting hired, getting fired, and finding your gig. We also chat about 75 Hard, lifting weights (we're bros), hackathons, teaching, and much more.

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

Zach Zeus and I chat about trust architecture and how it can work to improve ESG impacts in supply chain. This is an incredibly important topic with massive global impact, cuz climate change.

LinkedIn: https://www.linkedin.com/in/zachary-zeus/

Recommendation 49: https://unece.org/circular-economy/news/unece-support-scaling-transparency-sustainable-value-chains

I'm chilling in Verbier, Switzerland at Skiers in Data (SKID). In this episode, I chat about the various types of debt - technical, data, and organizational debt.

Annie Nelson and I chat about her path to data analytics, writing her new book, "How to Become a Data Analyst", bad career advice, rock climbing, and more.

LinkedIn: https://www.linkedin.com/in/annie-nelson-analyst/

TikTok: https://www.tiktok.com/discover/annie-nelson-data-analytics

Book: https://www.amazon.com/How-Become-Data-Analyst-Low-Cost/dp/1394202237

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

Imagine you're dropped into the middle of a failed data project - no data team, no documentation, and other horrific things - and have to figure out a way to make it work. What would you do?

Gordon Wong and I chat about various aspects of how we'd handle this scenario.

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/

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/

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

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.

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/

Andrew Meister and I chat about removing wasted notions and bad workflows, aka "clunk."

Today's rant is a random grab bag of stuff - my thoughts on Data Day Texas, updates to Practical Data Modeling, and more.

Roy Hasson and I chat about career progressions in data and technology, open table formats (Iceberg), and more.

Are your outputs generating the right outcomes? I'm in Austin for Data Day Texas, and I reflect on this topic via a conversation I had last night with Juan Sequeda, Tim Gasper, and Santona Tuli.

In 2024, outcomes will matter more than ever. What are you doing to drive the right outcomes for your organization?

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.

I chat about my working (and evolving) definition of data modeling. In short, we need to move beyond a human-centric view of data modeling, as most data is consumed by machines.