The PRQL: Feature Stores and ML Ops with Simba Khadder of Featureform

Eric Dodds 00:06
Welcome to The Data Stack Show prequel where we replay a snippet from the show we just recorded, Kostas, are you ready to give people a sneak peek? Let’s do it. Wow, Kostas would have fascinating conversation with Simba from Featureform, I feel like the conversation spans such a larger footprint than just, you know, features and even ml ops. I mean, we talked about so many different things. But I think what I’m going to take away is that his background in trying to understand how to create a great moment for a user, it’s very clear, that influences the way that he thinks about building technology that ultimately materializes into data points, you know, of course, you know, we can call those features, you know, those they can, there’s embeddings, and there’s all sorts of technical stuff that it’s very clear that Simba is building a technology that will enable teams to use data points that create really great experiences. And I think that comes from him facing the difficulty of trying to understand why or why not, you know, of the millions of visitors, you know, the handful of people will subscribe. And that, to me was really refreshing, because ml Ops is a very difficult space, feature stores and all of this surrounding technology can be very complicated. There are a lot of players. But it’s clear that Simba just wants to help people understand how to drive a great experience using a data point that happens to be derived. That happens to rely on a lot of, you know, data sources, and that happens to he No need to be served, like in a very real time way. But to him, those are consequences.

Kostas Pardalis 02:08
Yeah, I felt was saying I mean, okay, simple. It’s like a person. First of all, it has a lot of experience, right? Like he has been through many different cars experience, like many different phases of what we call a metal or AI. And he has done that in a very, like, production environment, right. So he has seen like, how we can build actual systems and products and deliver value. And with all these technologies, which obviously, it’s something very important for him today as he’s building his own company. And I think it’s like, an incredible advantage that he has, we didn’t talk that much about, and maybe this is something that we should like, how was the topic like for another conversation with him to talk more about like the developer experience and like how, like, all these complicated infrastructure with all these different, let’s say, technologies, and all the stuff that we discussed together, how we can deliver, like an experience to developer that works with all that stuff to make him like, more productive. But what I’ll keep, like from the conversation that we had with him, I think he gave like an amazing description of what features are, what the beddings are, how they relate to each other, how we go from one to the other, and how we use them together. And how most importantly, all these will become some kind of like, let’s say, a universal API for all these ml or AI driven applications in the near future. So I am going to say more about that, because I want like everyone like to listen to him by his much, much better than nothing about. But there’s like a wealth of very interesting information around all the things that are happening today in the industry and will top in the next couple of months in the industry.

Eric Dodds 04:18
I agree. I think the I think if you want to learn about features, there’s actually way more in here. And I think you’ll learn about the future of what it looks like for ml ops, and actually operations operationalizing a lot of this stuff so definitely take a listen. If you haven’t subscribed, definitely subscribe. Tell a friend and we will catch you on the next one.