The Data Stack Show - The PRQL: From Tables to AI: The Future of Data Modeling with Best-Selling Author, Joe Reis of Ternary Data

Episode Date: December 30, 2024

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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. All right, welcome back to the Data Stack Show. We're here today with Joe Reese, a second-time guest. Joe, welcome to the show. What's up? How are you guys doing?

Good. Also, Eric is out today, and we've got the cynical data guy, Matt, here as co-host. Just sliding on over from the couch. Glad to have you here. So, Joe, yeah, catch us up a little bit on what you've been up to the last few months since we last spoke. Not traveling as much, which is good. Yeah. So I've been kind of nonstop globetrotting, which happens in the spring and fall.

So I'm just back home in Salt Lake City working on some projects right now. And that's about it. It's just been nice to just, I mean, definitely thankful to travel a lot and see some cool places and meet awesome people. But it's good to be back for a bit. Yeah, that sounds really nice. Okay, Joe, we spent a few minutes chatting before the show. I'm excited to dig into a little bit about the book you're writing and just maybe get into some cynical takes on what you're seeing out there in the data world. Yes. Well, yeah, I don't think it's any secret I'm working on a new book right now.

It's on data modeling, and I can get into why that is. But what the book is about is it's an end-to-end treatment of data modeling across different use cases, whether we're talking applications, analytics, machine learning, across different modalities of data, whether we're talking structured data, semi-structured, unstructured. The goal of the book is to really equip practitioners with an understanding of data modeling end-to-end. And so I think it's what I consider to be sort of the next phase of where data modeling is going,

is it's not just about tables anymore. It's much more than that. We're working with different types of data across many different use cases. And so the goal of this book is obviously to equip practitioners with, you know, a body of knowledge of the existing techniques as well as hopefully introducing some new ones as well. The working title is Mixed Model Arts, which is sort of a plan where it's a mixed martial arts. So I can kind of understand where the threat is coming from. And think the inspiration comes back i grew up in the 80s you know i grew up watching really trashy tv like kung fu theater and wrestling and yeah all this stuff and boxing

and you know and i think back in the day combat sports fighting was very one-dimensional you'd be a boxer or a pro wrestler and you're speedo or master in the uh mountains in china or something but there's always this notion that you know the you know the questions are always like who would win a fight like would bruce lee beat mike tyson right you know in a boxing match or you know or under some set of rules but ufc you know that came around the early 90s there are obviously other things before like valetudo in Brazil, which is early mixed martial arts. But UFC, I think, was the mainstream thing that blew the lid off the notion of being a one-dimensional martial artist. Fast forward to today, and you couldn't tell me that, you know, the best boxer in the world, if that person gets into the ring in UFC, that they would do very well.

Or any one-dimensional sport. But if you take sort of the parallels to this with data, we've been stuck in the past. We've been stuck with these notions that there's one true way to model data, there's one technique to rule them all. I think we've been, like I said, stuck in a table-centric

view of the world, and it's almost akin to thinking the universe revolves around the sun, and the world's moved on. You know, we have endless amounts of different ways of storing and querying data. We have different ways of moving data. Streaming is becoming increasingly popular and has been for a long time. Machine learning is everywhere.

Now it's AI. And so, you know, I feel like hopefully the world of data modeling and data in general starts catching up to it, to where we are. So it's part of the effort of the book. Yeah. Awesome. All right. That's a wrap for the prequel.

The full length episode will drop Wednesday morning. Subscribe now so you don't miss it. Bye.