Data Products Done Right: Lessons from Capital One's Journey at Scale with Bethany Sehon

All right.

So much to unpack.

Tim, you want to go first or me?

Well, first of all, I think it resonates a lot that you're talking about, hey, it's not as simple as just, well, I guess let's just do data products.

You can't just slap a label on it, right? You're not lifting and shifting.

Otherwise, you're going to have another.

Let's call the BS on that.

How many people do you see you talk to are like, we're doing data products, and they're just slapping the label on what they've already been doing? How many people do you see this?

Oh, we still see it even in internal to Capital One.

We'd be like, actually, you got to go through the process here and we will help you with that.

We're really excited for your data.

But, you know, still seeing it internal to Capital One and especially with how quickly we can do things now with AI, it's like, why, you know, let's move faster.

And 100%, I want to move faster.

But I also don't want to just take... our legacy data where we still have sins of the past, we still have a lot of arbitrary uniqueness, et cetera, and just move that into this new environment.

We've done so much in the progress for our prioritized core data products and getting to critical mass on them that I wouldn't want to undo it by just continuing to do things the way they always were done before.

Like, why? Why even make a move in the first place? Right.

Standardization is expensive, by the way.

And so, you know, if you're going to go in, you should really just do it right.

Yeah.

So what was the the sort of business impetus that, like, started this journey? Like, was there something in particular that Capital One or that you was that you were trying to drive that kind of got this train rolling?

Yeah, I think there was actually a confluence of some really, really cool things that got me here, whether it was luck or it was, you know what I, you know, some divine providence or it was really, you know, us going out and being super, super smart about some decisions we made.

There were a number of efforts at Capital One that kind of converged.

of which is like some core modernization as well as our tech transformation and then the emerging data transformation that we went through.

So going all in on public cloud and then the data transformation that built on top of that.

But really we started with some standardization strategy where we believe that it made sense for our three core domains.