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.
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[MUSIC PLAYING] 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 guest 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 show. We're here with Edward Shenard, who has had an extremely illustrious career across both large enterprise and startups and data. Edward, I have so many questions. Can't wait to dig in with you. Thanks for joining us. Well, thank you for having me. All right. Well, can you give us a quick background, just a brief overview career in what you're doing today in data? Yeah, I've spent most of my career in analytics as a market analyst. The last 13 years I have been building and running data teams that includes engineering, data science, analytics at Fortune 500 companies and startups. Currently, right now, looking for the next big thing to do. Talking to some companies right now, I think it might be getting close on so. Awesome. So before the show, Edward, we talked a little bit about P&L ownership for data team. So I'm really excited to dig on that topic. And then what kind of topics do you want to talk about? Yeah, the building of teams is really important. The change in how AI is changing the dynamics of the space, as well as areas of personalization. It's interesting. It's one of those things that every few years comes back to the surface as an important topic. Yeah. Awesome. Well, let's dig in. All right, let's do it. All right, that's a wrap for the people. The full-length episode will drop Wednesday morning. Subscribe now so you don't miss it. [MUSIC PLAYING] [MUSIC PLAYING] (upbeat music)
