>>The cube presents HPE discover 2022 brought to you by HPE. >>Welcome back to the Cube's day one coverage of HPE discover 2022 live from Las Vegas. Lisa Martin, here with Dave ante. We've got a couple of guests here with us next, gonna be talking about industry transformation, please. Welcome, brought off director of global industry and sustainability marketing and Andy Hulk, halter senior director at worldwide industry sales programs, guys from HPE. Thanks for joining us. You bet. >>Thank you for having to >>Be here, >>Industry transformation. That's a big term. It's not a new concept, but we see so much going on. Andy, talk to you about industry transformation, from your perspective, where are customers, how are they capitalizing to really make data a true currency? >>Right? Well, underlying all this is, is the data that is becoming so complex, but at the same time, there's specialization required in each industry with the different applications that the industries are running and our ability to bring that forward and connect all those things is a big trend going on. And as we see that developing over time, um, we're getting more, um, connecting those different applications that are running is becoming more, uh, every day we're doing more of that. >>One more. >>So where do you wanna start? What's your favorite industry to, to transform? Uh, I mean, financial services is, you know, got the right, the whole blockchain thing going on, uh, industry 4.0 and manufacturing, you know, retail, everybody has, uh, you know, an Amazon war room, you know, energy now with EVs and, and solar and everything else and the price of oil. And, and now you throw in inflation and supply chain and you, I mean, it's just, every industry is getting disrupted. I, I wanna make an observation. You guys tell me what you think. Yeah. You know, think about the, the incumbent industries. They, they generally have data at the outskirts. It's all siloed and they're trying to put it at the core and that's a big challenge for them. What are you guys seeing in terms of who is having success with that? Do you have examples? What role do you play? Yeah, we have so much to talk about, right? Yeah. >>Yeah. Let me I'll jump in here. Um, I mean, I think one of the unique ideas is all this interest industries you mentioned, there are all trying to learn from each other, right? If you're a financial institution, you wanna understand what retail is doing because you wanna serve your customers better. Right. You wanna look at, you know, some of these technologies, how they're being applied. Um, you look about like sustainability industries are trying to learn how to do that better from each other. So there's this notion of industry and transformation is it's kind of twofold. It's one. How are these industries almost like entering new markets? I mean, you look at, at all the tech, tech companies out there, they're all getting in into payments, for example. Right. You know, Google pay app. Yeah. Mm-hmm <affirmative> so that's just like one example of where you're seeing the kind of, that, that blurring of lines between industries happening >>Content, uh, Amazon getting into grocery. And so in, in the premises, that data is the enabler. I mean, right. For decades, we've seen a, a, a stack, a vertical stack within an industry where, yeah. Where, whether it's, you know, research and development, manufacturing, sales, and distribute marketing, you were in that industry stuck for life. Right. And now all of a sudden data allows you to traverse industries. Yeah. This dual disruption agenda that you mentioned, right? >>Yeah. It's, it's, it's really, as it's core is because these companies have the ability to take advantage of that data even more. And they're trying to serve their customers even better that that's kind of opening up these new doors for them to, to do that because that's, you know, and again, there's so many good examples out there. Uh, automobile manufacturing are looking towards the gaming industry, you know, to how do they design controls, you know, that kind of stuff is, you know, as example. So you see, you know, all kinds of that. You mentioned also that, you know, everybody's trying to bring the data to the core. I don't, I don't think that's necessarily true. I think you heard earlier today in the keynote, you know, that that companies want to be able to, to take advantage of the data, data, wherever it is. Um, if it's the edge and a factory floor, if it's in a, you know, it's patient data sitting somewhere, you want to, you know, handle it where it is, and there's a cost to doing that, to bring it all >>Together. Yeah. So by the way, I wanna clarify you're absolutely right. The data by its very nature is distributed. Sure. When I say core, I mean, put it at the core of their business. Sure. That's >>What, I mean, >>Fair enough by data first, but your point is really, we're gonna talk about that. Yeah. Because it brings, brings so many other challenges with how you deal with that. But please jump in Lisa. Yeah. >>I was just gonna ask you, Brad, you talk about the blurred lines between industries. Yeah. And talk to us about how is HPE a facilitator of those industries learning from each other. You have such breadth in so many different industries as Dave mentioned, but how are you that enabler, if you will, of allowing them to, to be able to have data be that key. >>Yeah. Yeah. I think, I think it just comes through the experience of working with these customers, um, you know, in these various industries. And then, um, there's so many times where customers come to us and they want us brief and again, they wanna learn for these other industries. So we're an aggregator of that technology. We obviously UN understand the technology with the cloud or, you know, edge or, you know, anything we're doing in with data. So we're using those, you know, those lessons and just applying those out there, um, you know, to those industries. So it's, I think it's just us as an aggregator. >>You, you, how how's the customer experience changing any we heard from home Depot this morning, they were focused on the customer experience and, and their associate experience. Right? Yeah. Bringing those together maybe. >>Well, you know, what we also heard this morning is the different personas, right. That are out there and being that are looking to transform their business. Yeah. And each of those personas is still linked together by the data, but they want to use it in different ways with different applications and the ability to connect all those things. Again, they're learning from each industry. So what home Depot learns about their mobile apps, maybe something that we can deploy in, uh, manufacturing, um, as far as locating things on the floor and connecting the edge data in, bring it in to, and then use that to analyze, use AI models, to do predictive behavior, uh, preventative maintenance, all these things are similar uses of connecting the data, but then applying to the specific industry use case. Yeah. And that pivot of that horizontal use of the data into those specific demands by, uh, at the personas within the, the, the different industries is what we're, we're >>Focused on. Yeah. And the technology is like an accelerate, you know, here. So you're think about like something like 5g, right. 5g is gonna accelerate, you know, a lot of transformation in various industries. Um, throughout that, I mean, tech, you know, the technology alone is not really what the, the, the customer cares about it. They, they care about what do I do with that? What kind of outcome can I get? Right. >>I wanna ask you, Andy, about the customer conversations, you talked about the personas, we've been talking about data democratization for a very long time. Mm-hmm, <affirmative> obviously is a challenging thing to do, but how were you seeing customer conversations, change and evolve, especially over the last couple of years where every L B has to have access to data and be a driver of its value. >>Right. Well, the customer, you know, historically H HP's, uh, background is in infrastructure and we've served industries in the data center for a legacy, right. Mm-hmm <affirmative>, but now they're saying it's more, you know, I've gotta talk to, uh, more people in my business as a data center owner, I've gotta serve these folks, understand their business. And as a supplier, to me, you need to understand them as well. And sometimes help me with that conversation and help me see the things to make those connections that I may not know as a data, you know, as a, as an it professional. Um, and how do we challenge the business to think about different ways of doing things in the industry? So how do we, we think about, um, you know, bringing those connections from other industries in, and, and, uh, uncovering, uh, opportunities or problems anticipating problems in those deployments that they may not have seen by their staying in their swim lane. >>Yeah. You know, I'm, I'm touring on this topic because on the one hand, I think about the, the big data era and, and, and I know a, of, a lot of failures to, to return, you know, the expectations and it wasn't a fail fast. It took a decade, you know, to get there. And part of the failure domain was to your earlier point, Brett, everything was sort of shoved into this centralized location. Yeah. You have this hyper specialized data team, and everybody has to go through them, but organizations I think are now realizing it, like, like your thoughts on this, that data has to go out to the lines of business. It has to be contextualized. People are now talking about building data products and monetizing data. And yeah, that's really, to me what digital transformation is about. So, but generally speaking, most companies are not great at data. They have a lot of data. Yeah. A lot of, lot of data line around insights. I think we heard in the morning keynote are scarce. Right. So what's your vision for how this evolves? >>Yeah. I think, I think, you know, from the data perspective that again, the, at the core is how do I serve my customer better? Right. So, you know, whether that is actual, you know, customer data that you want to sort of up personalized offers for, or, you know, make decisions of, you know, medical decisions for their, you know, for their, you know, better patient outcomes. So if they keep that in mind, then, you know, as far as how it's used by the different lines of business there, you know, that's where we can help facilitate, you know, in many ways. And that's where, you know, cloud becomes a, you know, a really key technology, um, you know, having that flexibility to, to move it around as needed, create the, you know, um, deliver the workload where the customer needs it, that, you know, that sort of idea is, is where we're, we're going with this. >>I think, yeah. I'd, I'd like to give you an example, um, please, in the FSI industry, uh, out here on the floor, we've got a demo on payment systems, right. And we've been doing that, uh, with our nonstop, uh, product and supporting that, uh, in the, in the banking industry for 10 years or more. And it's evolved over time to be one of the, you know, it's a ubiquitous across the, in the support. Yeah. Um, but now we're talking about new regulations with all the global events that are going on, you know, crazy stuff that more pressure on the banks to, to comply with that, um, worries about money laundering and fraud prevention. Well, connecting those, the data from those payment systems into the AI modeling that is now being deployed to do more sophisticated fraud detection and Mon money laundering detection and all of those kinds of things, how you connect those together as an example, what we're seeing, how we get more insights by, uh, by the combination that we can bring together. >>And the insights is critical. Yes. Right. I mean, without it, the data isn't very useful. >>Right, right. Right. And I think even, you know, these, these concepts like swarm learning right. Where you're actually trying to aggregate a lot of those, you know, a lot of that data and, and provide, you know, even a broader data set to, to learn from is even, you know, more beneficial. >>I think the, when you think about the, the principles of this, this decentralized world, that's that it starts with an organization saying, look, we recognize that we can't shove it all into a data warehouse or a data hub or a single data lake. Yeah. We're gonna have all of those. And those are just kind of nodes in the mesh, like it's steel as Youma the GHI term <laugh> and, and, and, and increasingly data as product that can be monetized. We're hearing a lot more about this, and those are organizational yeah. Considerations. I mean, HPE can maybe facilitate that through whiteboard sessions, but, but the, that leads to, in order to, to democratize data, I need self-service infrastructure and I need data that can be shared and governed. I, I don't know about the last one, but you definitely are. Number three self-service infrastructure simplification. Yeah. Your version of cloud. How do you see that, uh, your, your role in that little vision that I just laid out? Do you buy that? >>You wanna take that or, >>Well, I, I think that we have, um, we definitely, because we, we see the data in all these different places and we're, we're trying to be agnostic to, um, you know, where it comes from, who owns it. It's how do you get it together and make it useful? And you don't have to capture it. You don't have to own it, but you may own some of it. You may borrow some of it. You may rent some of it. You may buy it and you may bring it together and they'll use it for the purpose. And then move on to expand into new things that you learn from that you may then monetize, um, in all those different ways. So we have a role of making that platform in a way that you can see it in different ways and use it consistently and repetitively and GRA gain more value of it, and then apply your applications and, you know, all those other things that you do. But that, that bringing together agnostically is a big part of our offering. >>And, and am I, am I not correct? I'm in my thinking on H HP's value is providing that infrastructure, uh, to be able to do just, just that that's your swim lane, if you will. And >>It is, but we're being asked to move up the stack and provide not only the infrastructure now, the platform, the ability to offer that platform, uh, in our HPE GreenLake offering where we're, we now can, you know, have cloud-like services on prem. It doesn't really matter where the data sits, um, and then plug in the applications and even manage those applications for the >>Customers. Okay. So, I mean, I see you as I, as, and Paz, which that up to stack yeah. The ability to, okay. I want whatever Python or open shift, I wanna build applications now on that. Interesting. The management piece is something I, I excluded, um, be because an organization may say, Hey, we need help managing this stuff. Right. But I see that, that I, as in pass, as infrastructure, you're not getting into applications where you're getting, you're not >>No other than letting, letting customers, you actually build on top of that. Right. Right. There's a >>Lot of customer, you're an enabler. >>Absolutely. Yeah. You look at some of the things we're doing with, you know, with our escrow platform and things like that. Right. You know, we're providing that development platform in a, in a really streamlined way of, of, you know, pushing, you know, applications out. I mean, little known fact, right. Is that most banks right now are hiring more developers right now than, than finance people. So all these, all these industries are becoming tech companies and that's, you know, that's the whole launch of the FinTech industry many years ago, and it's, you know, continued to evolve >>And they want to bring AI, they wanna bring data into their applications. And you, HPE I see is an enabler of >>That. Absolutely. Absolutely. >>Give us last question. As we wrap up here, give us the vision, like the next five years, what are some of the industry transformation elements you are forecasting if you have a crystal >>Ball. Yeah, yeah, yeah. I think number one, just an increased focus on personalization and customization. Uh, you know, you look at, you know, personalized offers when you add location based services, things like that, combined 5g, you know, like all this technologies, you're seeing a lot of that custom manufacturing, so those kind of trends are gonna continue. And we know that's, you know, those are the workloads that we gotta, you know, know know is coming, you know, down the pike and, and, and address those. Um, secondly I think AI, right, AI is gonna, is gonna be, you know, it's gonna impact every industry in a big, big way. You know, when like Andy talked right about, you know, fraud detection, uh, you know, manufacturing, robotics, those kind of things. Uh, and then I think, um, you know, lastly, just, just this more convergence, you know, of these industries, right. You know, tech is just, you know, impacting everything in such a big way. And so you're gonna see more of that, that blurring of lines between, between industries. So they jump into jump outta their normal swim lanes. Right, right. >>Be between machine learning and AI, we're gonna see efficiencies by doing things better, with less, uh, deviations and driving, uh, lower cost. And we're gonna see new capabilities come to the forefront and that's gonna be consistent across all industries. And it's gonna be based on the data. Both of those require the models, you know, the data go in and drive their models. Do >>You think any industry is more ripe for disruption? I mean, timeframe wise, you got healthcare, you know, like I always wonder, you know, how is AI gonna help doctors make better diagnoses already is yeah. Will, will AI make the diagnoses? Yeah. You know, retail, I mentioned before, you know, energy, you know, government is changing entertainment, media entertainment is, do you see any industry patterns where one is being disrupted more than the other? >>When we talk to customers, every industry thinks their industry is not going fast enough. And so it's like, you know, I think everybody is just so hyper focused on, you know, what they are involved in and then their domain that, uh, you, you, depending on who you talk to. Yeah. I, you don't, everybody needs to do it faster, you know, more economically, um, and more efficiently. Right. And so >>I think, and they're all being disrupted now, too. Absolutely. It's not only have to do faster, but they've got to, um, transform to keep up with the demands of their >>Customer. Nobody's safe. >>Yeah. And the technology's just gonna continue to accelerate that. And that's the thing. And, and, and the market's becoming, you know, less forgiving as, as we go. So people have to react really, really fast in these markets, you know, and especially with all the other changes going on around us, uh, to, to actually, you know, make that impact. >>Interesting. I'm liking what's in this crystal ball. I'm gonna have to ask you guys for some cons after we wrap here. Absolutely. Thank you so much for joining David, me talking about industry transformation, tremendous amount of, of transformation so far and so much to go. It's exciting to watch. >>Yeah. Appreciate it. >>Have an, we appreciate it for our guests and Dave ante. I, Lisa Martin, you're watching the cube, the leader in live tech coverage. You AP back after a short break.