Welcome to the Analytics Power Hour. Analytics topics covered conversationally

and sometimes with explicit language. Hey everybody, welcome. It's the Analytics Power Hour, and this is episode 262. Hey, Happy New Year. You know, 2025, that'll probably be the year of, well, what exactly? There is a pretty steady flow of prognostications every year about the things that will define the coming year. And we're not completely immune to desire to define the future. I didn't say that very clearly, but we do want to define the future. So what will 2025 bring? It's probably the year of Tim Wilson still being frustrated with people calling stuff the year of.

That's fair. accurate yeah you could write in with tim being frustrated with people you don't really need to say there you go further qualifiers not not necessary we still like you and

2025 probably be the year of mo still liking adam Grant and Brene Brown. Hey,

Mo.

Yeah, probably, actually. That's a very good prediction.

There's going to be a huge scandal with one of them between recording and that coming out. Oh,

jeez. It's going to be. All right. And I'm Michael Helbling. Well, some attempts at categorizing the future that is coming at us awfully fast is definitely warranted. So what better time than the first episode of 2025? You know, insert Zagger and Evans pun here. And to do this right, we wanted to have a guest who has a great track record of observing our industry and seeing where the puck is going. Barb Moses is the co-founder and CEO of Monte Carlo, the data reliability company. As part of her role as CEO, she works closely with data leaders at some of the foremost AI-driven organizations like Pepsi, Roche, Fox, American Airlines, hundreds more. She's a member of the Forbes Technology Council and is a returning guest to the show. Welcome back, Barr. Thank

you so much. I am honored and pleased to be a returning member. No,

we're serious. We love the way that you take such an interest in really having, from your level, a real good, clear view of where our industry is and the data industry is going. Before we get started, let's just get a recap of what's going on with you and Monte Carlo?

Yeah, it's been a whirlwind couple of years for not only for Monte Carlo, but I'd say for the entire data industry. Like I'm just reflecting last time I was here. This was 2021. Is this just kind of, you know, coming out of COVID? I think we, you know, we're all getting comfortable behind the camera and feeling comfortable at home. And, you know, the world is obviously very different today. But maybe just kind of give a quick recap. You know, Monte Carlo was founded to solve the problem of what we call data downtime, periods of time when data is wrong or inaccurate. And, you know, five, ten years ago, that actually didn't seem important at all. Like, I think people spend some time thinking about quality of data, but, and you know, you, you guys know this better than I do, but it probably didn't get the diligence that it deserved back then. Like you could kind of like skirt around the issue. You probably, you know, it was very common at the time to just have like extra eyes on the data to make sure that a report is accurate. And if it was wrong, you'd kind of be like,

Oh, shucks. So sorry.

And kind of like move on.