The Data Stack Show - The PRQL: What AI Founders Need to Know About Data (Before It’s Too Late) with Pete Soderling of Zero Prime Ventures

Episode Date: March 31, 2025

The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.

Welcome to the Data Stack Show prequel. This is a short bonus episode where we preview the upcoming show. You'll get to meet our guests and hear about the topics we're going to cover. If they're interesting to you, you can catch the full-length show when it drops on Wednesday. Welcome back to the Data Stack Show. We have a very exciting multi-time guest, Pete Soderling. Welcome back to the Data Stack show. We have a very exciting multi-time guest, Pete Soderling. Pete, welcome back. We're super excited to spend some more time talking with you about all things data.

Thanks. All right, Pete, you've been on the show multiple times, so a lot of our listeners know you. A lot of our listeners have met you at the Data Council conference. But for those who haven't met you, give us the brief flyover of your career and how you got into running the largest conference for data engineering and investing in data companies. Sure. Thanks, Eric. I'm Pete Soderling. I'm the founder of Data Council and I'm the founder and general partner at Zero Prime Ventures. I'm a software engineer from the first internet bubble, as I like to say, back in the 90s. And I was a self-taught hacker, programmer in high school, sort of made my way

to the East Coast to New York City and had my first jobs in tech in New York City in the first internet bubble. And so ended up sort of becoming a founder in New York City, started a couple companies there. Then in 2010, I moved to the Bay Area, started a couple companies there. But one of the companies was a data infrastructure company, and that sort of got me into the early cloud data, and got me really excited about data, and just sort of my geek mind went long on data. And ultimately, that sort of culminated in me starting Data Council, the world's first data engineering conference in 2012, which was a long time ago now, it's hard to believe. And over the years, been sort of building out the data community across multiple dimensions and ultimately culminating in starting a venture fund to invest in Day Zero engineer founders

inside the data community and beyond. That's awesome. So we were talking before the show about AI and the impact on data engineering roles, products. We're talking about people starting these AI and the impact on data engineering roles, products. We're talking about people starting these AI companies that have no idea about data engineering. So that's a bunch of topics. I'm excited about talking about all of that.

What are some things you're excited about? CB Yeah, I think that's really astute. I think there's a whole new generation of hipster hackers, quote, AI engineers, which is amazing to see, not to be pejorative because we need new fresh blood in the community. But I think there's sometimes a gap in what newer folks in the community might understand about older school, old stodgy data management techniques and architectures and data infra. And so this year's data council is actually an effort to put those two pieces together and to explain why all the new sexy AI stuff at scale

ultimately becomes and sort of demands a data engineering solution or data infrastructure solution, a data management solution. So we're excited about sort of pushing that vision forward and putting these two pieces of the community together and really explaining why data needs AI, or sorry, why AI needs data management. I should invert it and put it that way around. why AI needs data management,

I should invert it and put it that way around.