The Data Stack Show - The PRQL: From Databases to Customer Data Platforms with Tasso Argyros of ActionIQ

Episode Date: December 18, 2023

In this bonus episode, Eric and Kostas preview their upcoming conversation with Tasso Argyros of ActionIQ.

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. We are here on the Data Stack Show with Tasso Argyros. Welcome to the show, Tasso. We're so excited to have you. Great to be here.

I've been looking forward to it. Thank you for having me. All right. Well, give us an abbreviated background. So you're the CEO of Action IQ, but you've done lots of database stuff. So just give us a brief background. Yeah. So I've been a database guy my whole life, more or less my whole professional life. I was, you know, grew up in Greece where I studied engineering.

And then I came to the U S I started at PhD at Stanford to study databases and distributed systems. And about a couple of years into that, I dropped out and just started one of the first, third nothing massively scalable database companies at the time. I mean, that was back in the 2000s. It was called Aster Data. And Aster was one of the first companies that could deploy very large databases on commodity hardware, right?

So much lower cost to store and analyze big amounts of data. That was, you know, pre-Hadoop. It was around the same time that MapReduce and that stuff was coming out. I sold that to Teradata, which is one of the, you know, a big data warehouse company at the time. I was the largest enterprise data warehouse company and spent a few years there. Definitely a great school in databases

and the business of databases. And then, you know, I wanted to do something slightly different. So I left and I started ActionIQ. We're a customer data platform. So there's definitely a bunch of database technology involved. But at the end of the day, we have a UI, and our goal is to empower the business users along with the data engineers.

So databases were a technical product, and Action IQ serves a dual purpose, as I like to think about it, which kind of brings us to today. CDP is a big, exciting market, and I'm sure we'll talk about it. You know, which kind of brings us to today, you know, CDP is a big, exciting market and I'm sure we'll talk about it in the show. Yeah, 100%. And by the way,

it's also like one of the things that like really excites me in like the conversation that we are going to have today is like this connection between like the data systems, like in, you know, like at scale especially and the business use case.

And you chose, I think, kind of an extreme use case here because you have a problem that, from my experience at least, when we are dealing with customer data at scale, it can be hard for the data platform that you are using and how to interact with it. But at the same time, you have one of the most demanding, in a way, customers out there, which is marketing people who have to use this. And they have to use it in a way that it's very provable, that brings value to the company. So I'd love to get more into connecting the con connecting, like the dots there, how like data systems and like the evolution of them, like led like to today

to support this kind of use cases and also how you solve like this very hard product problem, right? It's one thing like to build a database with terminal, like SQL. It's another thing to build something that someone needs to slice and dice data for marketing campaigns. Right? So that's something that like, I'm really excited about. That's right. What's in your mind?

Like what you would love to get deeper into like today? Yeah. So I think, of course, what you say is spot on right so i think with the cdp you know we had our work cut out for us because first of all for the business user you need to abstract things enough so that they can do stuff without understanding all the underlying you know data you know they shouldn't know sql and they shouldn't be able to know what every table column means, right? To do work. So you need to abstract things enough for the business user to do the work, but not so much that they can really do that much anymore, right? Because you've abstracted

things to the point of elimination. And the other thing that I think is interesting is that it's not just the business users, right? So we have the business user persona, but we also have the data engineer and analyst persona. So database, you have the database users or engineers or analysts that are using it, right? Everybody knows at least SQL, right? And people understand data structures and what the data means. And in our world, some of our users do, but some of our users don't, right?

So you also have like this multitude of users. So it was definitely an interesting problem, which is kind of what I was looking for. But beyond that, I think it's interesting to think how the CDP and the database world have been kind of intertwined, right? And, you know, some of the latest trends in the CDP world, like composability, are enabled and were created

because of how the cloud databases, right, have evolved in the past few years. So I think database architecture evolution and CDP evolution kind of go hand in hand, even though they're separate spaces. So I think it'd be very interesting to talk about that and, you know, what is a CDP, right? And we're still, you know, hours of debate, right?

How it can take place in that, what is a composable CDP, all the stuff is fascinating to discuss. Yep, that's super interesting. I can't wait to get into the details here. Yeah, let's dig in. Let's do it. All right, that's a wrap for the prequel.

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