>> Live from New York City, it's buck you. Here is your host, Jeff Frick. >> Hey, welcome back. I'm Jeff. Rick. We're here at the Cubes. Fifth birthday party. A big date in Icy in Manhattan is part of the big Date. A week. It's got Stratos cough, a dupe world. And, of course, big Aidan. I see. So now having our party, which is always good to have, and I'm joined department X gas. Kerry McFadden from Parodi Research. Carrie. Welcome. Well, thank you very much. So last last we saw he was actually a big data and twenty thirteen, So it's lots changing the year. >> Absolutely, Absolutely. I think the whole hoodoo thing is really taken off. And the thing that interests me the most about show or or the exhibitors at the show is that Bye. You could get a lot of data into Duke, but how do you get it out? How do you make it useful? What do you do with it when you get it out? You know, I said on structure data is structured. Date. Is that a combination? Is it ski Melis? >> All the above all the above, >> right? Exactly. So I think really, that's been on and actually have been Jeff to all the shows, right? Since the beginning, when it was just a new world. Okay, Cube started back. And I think two thousand ten two thousand filling our fifth birthday. Right? So at least at least at least twenty ten. So since then, you've seen, you know, progression off vendors coming in to provide services that actually enable Duke to do more than it does started is kind of a batch oriented type of solution that now, because of these other value added solutions can to really or near real time processing, you can take the data out of it a lot more easily. You can use do basically as a as a repository, right on DH. And a lot of the solutions out there are are evolving to the point where you can, uh, you could basically make a sense of the information, and I think that's a really important rights. Dated information information inside, right? That's where we want to go with this thing. Business decisions made in real time. Which way? Define as in time to do something about it. Right? Right. Yes. Some of the players, I mean, you've got the map. Our guys. You've got the act. Aeon folks that just bought pervasive software. So they've got the Predictive Analytics piece sort of covered. Obviously. That's stone breakers. Old company, you know, a variant of ing gris, right? You've got. Obviously, IBM is a player in this space. With their blue mix and their cloud capabilities and all of their information management pieces, every major vendor is got a piece of is part of the action, if you will. Trying to build something on top of a dupe to make it more useful and make it more valuable. Yeah, the floor was filled with little companies, big companies, and everyone is certainly jumping in. So let me get your prospectus that you've been coming for a lot of years on this thing. Where are we on the journey? How? How? You know, I think we're past the P E O C stage, right? People are getting stuff into production deployments, but it's still early days. You know, the Giants are playing tonight. Go Giants, are we? First inning, third inning, seventh inning. Where are we? I think we're probably in the second or third any second. I think we got a ways to go. And what's the next big hurdle to get us to the next inning. I think one of the problems is this storage issue, right? So you've got this issue of being able to scale out theoretically, exponentially, right? The nice thing about do piss If you need Teo, if you need more space, you just add No J had storage and whatnot, But what happens when you get too much information? You're into the pedal bike, multiple PETA right range now, and most of that data, you know you're not going to access. You may access only two percent of it overtime. I think they're a lot of figures around that. But actually, a wicked bon article that I read recently is very interesting, one called Flake Flake or what they were doing. Flake. I want to make sure he gets a slave by a herd where he said it to me off camera, right? It's a f L a P. It's a combination of flash and tape on DH. Basically, there's a great article on the Wicked Bond site by Wicked Bonds CTO, David's lawyer Okay, and his premises that at some point, relatively soon a cz thie as data grows exponentially into the multiple petabytes ranges and maybe even beyond The thing is gonna get squeezed is the traditional HDD or hardening is spinning disc, right? So tape has become much more, uh, much more resilient. Uh, tape last has a meat time failure of about twenty six or thirty years versus disc, which is about five. And obviously flash is much, much faster, right? Right in some cases don't get into all the nuances of almost feet feet, but flavor going to squeeze out disks and the men think so. And what that'll offer customers is a is a much lower TCO from managing those huge petabytes scale environments and also accessing it at a relatively quick speed. So I think that's that's a piece. It's interesting that the other part that's very interesting to me, Mr Cognitive Computing face. So I was at the no SQL event last week last month in in San Jose, and with that they had a cognitive computing component on DH. I think thie idea of trying to get machines to think more like people building neuro morphing chips to two. It's kind of mimic the way synapses or electricity, electricity in the brain, you know, works how neurons fire and so forth is very interesting. And I think once you Khun Get Dupe is the repository. You've got the data there. But how do you make use of it? And I think that's the challenge. That's going to be, well, paramount the next few years. Exciting days ahead. Well, Gary, thanks for taking a few minutes. We're at the fifth birthday party at the Cube. Were at Big Data and nice jefe. Rick, we're on the ground. Thanks for watching.