>> Announcer: Live from Madrid, Spain, it's theCUBE, covering HPE Discover Madrid 2017, brought to you by Hewlett Packard Enterprise. >> Welcome back to Madrid, everybody, this is theCUBE, the leader in live tech coverage. My name is Dave Vellante, I'm here with Peter Burris, this is day one of HPE Discover Madrid. Olivier Frank is here, he's the Worldwide Senior Sales Director for Alliances for IoT at HPE, and Kurt Bayer, otherwise known as Bager in English, in America. He's Vice President of IoT Solutions for EMEA PTC, did I get that right? >> Yeah you did it. >> Bayer? All right, well thank you for sharing that with me. Welcome to theCUBE, gentlemen. Olivier, let me start with you. The relationship between PTC and HPE is not brand new. You guys got together a while back. What catalyzed that getting together? >> Yeah, it's a great question, and thank you for inviting us, it's great pleasure to be on theCUBE, and for me the first time, so thank you for that. >> Welcome. >> Yeah, you know, the partnership is all about action and doing things together, so we did start about a year ago with, you may remember flow serve and industrial pump that we showcased, and since then we've been working very closely together to actually allow our customers to go an test the technology themselves. So I would say the partnership has matured, we now have two live environments that customer can visit, one in Europe, in Germany, in Aachen, with the RWTH University, and one in the US, near Houston, with Texmark who you know because you also came to the show. >> Right, okay, Kurt give us the update on PTC. Company's been in business for a long time, IoT is like a tailwind. >> It is, that's right. PTC is mostly known for CAD and PLM, so for 30 years they made 3D CAD software for when you design and make an aircraft or car engine. But over the last five years, PTC have moved heavily into IoT, spent a billion on acquiring and designing software platform that can connect and calculate and show in augmented reality. >> So let me build on that, because PTC as a CAD company, as a PLM company, has done a phenomenal job of using software and technology to be able to design things to a level of specificity and tolerance that just wasn't able to be done before, and it's revolutionized how people build products. But now, because technology's advanced, you can leverage that information in your drawings, in your systems to create a new kind of an artifact, a digital twin that allows a business that's working closely with you to actually render that in an IoT sense and add intelligence to it. Have I got that right? >> You got it exactly right. So making the copy. We can draw it and we can design the physical part, and we can make the digital twin of the physical part with sensors. So in that way you can loop back and see if the calculation, the design, the engineering you have made is the right fit, or you need to change things. You can optimize product with having the live digital twin of the things that you've designed physically. >> So it's like a model, except it's not a model. It's like a real world instantiation. Model is an estimate, right? A digital twin is actual real data. >> It's feeded by live data, so you have a real copy of what's going on. And we use it for not only closing the loop of designing products, but also to optimize in the industrial fold, to optimize operation and creating manufacturing of things, and we use it to connect things, so you can do predictive maintenance or you can turn products to be a service, instead of selling an asset, the company can buy by click, by use, plus the product are connected. >> I want to really amplify this, Dave, 'cause it's really important, I want to test this with you, 'cause the whole concept of using technology, IoT technology to improve the operational efficiency, to improve the serviceability, to evolve your business models, your ability to do that is tied back to the fidelity of the models you're using for things that are delivering the services, and I don't think the world fully understands the degree to which it's a natural leap from CAD and related technologies, into building the digital artifacts that are gonna be necessary to make that all work. Have I got that right? >> You got it completely right. So it is moving from having live informations from the physical object. So if you go to augmented reality, so you have the opportunity to look at things and get live information about temperature, power, streaming of water, and all these things that goes on inside the product, you also have the opportunity to understand if there's something wrong with the product, you can click on it and you can be directed on how to change and service things like when the augmented reality, all built by the CAD drawing in the beginning that is combined with sensor information and >> And simulate, and test, and all the other things that are hard, but obviously to do that, you need a whole bunch of other technology, and I guess that's where HPE comes in. >> Exactly. >> Absolutely. In fact to bounce on that thought, we talk a lot about connected operation, where you know, we are showing the digital twin, but one of the new use case that we're showing on the floor here is what we call smart product engineering. So we're basically using the CAD environment of (mumbles), running on that edge line with edge compute, you know, enterprise compute capability, manageability and security, and running on that same platform then, simulation from companies like Ensys, right, and then doing 3D printing, print prototyping, and basically instrumenting the prototype, we're using a bike, the saddle stem of a bike showcase, and they are able to connect and collect the data, we're partnering with National Instruments who are also well-known, and reinject the real data into the digital model. So again, the engineers can compare their thought and their design assumptions with the real physical prototype, and accelerate time to market. >> PTC's been a leader in starting with the CAD and then pulling it through product life cycle management, PLM. So talk about this is going to alter the way PLM becomes a design tool for digital business. If I'm right. >> You're right, it becomes industrial innovation platform from creating the product to the full life cycle of it. >> Peter: All the way up to the business model. >> All the way up to the business model. And talking about analytics, so if you have a lot of data and you want to make sure you get some decision made fast about predictive maintenance, that's an area where we are partnering with HP so we have a lot of power close in the edge, close to the products that can do the calculations from the devices, from the product, and do some fast results in order to do predictive maintenance and only send the results away from the location. >> So what are some of the things you guys are most excited about, Olivier? >> Well, really excited about making those use cases, being the smart product engineering, or the predictive maintenance, you know, work for our customers so behind the scenes we have great solutions, now we're partnering on the sales front to kind of go together to customers, we have huge install base on both sides, and picking the right customers interested in this digital transformation, and make it real for them, because we know it's a journey, we know it's kind of the crawl, walk, run, and it's really about accelerating, you know, turning insights into information and into actions, and that's really where we are very much excited to work together. >> So it's not just, so the collaboration's extending to go to market is what I'm hearing. And so what's the uptake been like, what are customers, customers must be asking you, "Where do I start?" What do you tell them? >> Before you start, it's important that you have a business case, a business value, you understand what you wanted to achieve, by integrating an IoT solution. That's important. Then you need to figure out what is the data, what is the fast solution I need to take, and then you can start deciding on the planning of your implementation of the IoT. >> Can I go back one step further, >> Yep. >> You tell me if I got that. And that one step further is, look, every... Innovation and adoption happens faster when you can take an existing asset and create new value. >> Kurt: Exactly. >> So isn't PTC actually starting by saying, hey, you've already got these designs, you've already got these models. Reuse them, create new life, give 'em new life, create new value with 'em. Do things in ways that now you can work with your customers totally differently, and isn't that kind of where it starts? >> It does, and you already have a good portion of what you need, so in order to make a fast value out of your new product or the new thing you can do with the product, connecting the products, then PTC and HP is a good platform to move on. >> Yeah but the pretesting, precertify, packaging, the software with the hardware, is allowing our customer to go faster to proof of concept and then to production. So we have a number of workshops, customers can come, again as I mentioned at the beginning, in Germany, in Aachen or in Houston at our Texmark facility, where we can basically walk the talk with customers and start those early POCs, defining the business success factors, business value they want to take out of it, and basically get the ball rolling. But it's really exciting because we have, we're touching really some of the key digital transformation of our enterprise customers. >> And don't forget that you need a partner that can do a good job in service, because you need a organization that can help you get it through, and HP are a strong service organization too. >> Well this idea of the intelligent edge has a lot of obviously executive support at Hewlett Packard Enterprise, that keeps buzzing at theCUBE today, Meg Whitman's in the house, she's right next door, and we're gonna do a quick cutaway to Meg, give her a shoutout, trying to get her over here to talk about her six-year tenure here, but you know, that top-down executive support has been so critical in terms of HPE getting early into the edge, IoT, intelligent edge you call it, Tom Bradicich obviously a leader, he's coming on. You mentioned National Instruments, PTC, you guys were first, really, from a traditional IT business to really get into that space. >> We're also the first to converge OT and IT, so we're showing on the floor what we're doing in end of line quality testing for automotive for example, taking PX higher standard, which is like instrumentation and real-time data position into our converged systems. So what I found is really amazing. You take the same architecture, and we can do it edge to core to cloud, right, that's very powerful. One software framework, one IT architecture that's pan out. >> Peter: Not some time in the future, but right now. >> Yeah, right now. >> So we talk about a three, maybe even a 3A, four-tier data model, where you've got data at the edge, real time, maybe you don't persist all of it or a lot of it. >> We call it experience data or primary data at the edge. vet data, or secondary data, and then business optimization data at the top level, that's at the cloud. >> So let's unpack that a little bit and get your perspective. So the edge, obviously you're talking about real time decision making, autonomous cars, you're not gonna go back to the cloud to make that decision. That, well you call it core, that's what did you call it? >> The hybrid IT. >> The vet, the vet. That's an aggregation point, right, to collect a lot of the data from the edge, and then cloud maybe is where you do the deep analysis and do the deep modeling. And that cloud can be on-prem, or it can be on the public cloud. Is that a reasonable data model for the flow of data for edge and IoT? >> I believe it is, because some of these products generate a lot of data, and you need to be able to handle that data, and honestly, connectivity is not for free, and sometimes it's difficult if it's in the industry floor, manufacturing floor, you need good connectivity, but you still have limitations. So if you can do the local analytics and then you only send the results to the core, then it's a perfect model. And then there's a lot of regulations around data, so for many countries, and especially in Europe, there's boundaries around the data, it's not all that you can move to a cloud, especially if it's out of the country. So the model makes a good hybrid in between speed, connectivity, analytics and the legislation problem. >> Dave: And you've both got solutions at each layer? >> Absolutely, so in fact... So PTC can run at the edge, at the core or in the cloud, and of course we are powering the three pillars. And I think what's also interesting to know is that with the advance in artificial intelligence, as was explored during the main session, there it is pivotal you need to keep a lot of data in order to learn from those data, right? So I think it's quite fascinating that we're going to store more and more data, probably make some useful right away, and maybe store some that we come back to it. That's why we're working also with companies like OSIsoft, an historian, which is collecting this time stamp data for later utilization. But I wanted also to say that what's great working with PTC is that it's kind of a workflow in media, in terms of collecting the data, contextualizing them and then visualization and then analytics. But we're developing a rich ecosystem, because in this complex world of IoT, again it's kind of an art and a science, and the ability to partner ourselves, but also our let's say friendly partners is very, very critical. >> Dave: Guys, oh good, last word. >> I will say we started with a digital twin, and for some companies they might be late to get the digital twin. The longer you have had collecting data from a live product >> The better the model gets >> The stronger you will be, >> Peter: Better fidelity. >> The better model you can do, because you have the bigger data. So it's a matter of getting the data into the twin. >> That's exactly what our research suggests. We've got a lot of examples of this. >> It's the difference between sampling and having an entire corpus of data. >> Kurt: Exactly. >> Kurt, Olivier, thanks very much for coming on the theCUBE. >> Thank you. >> Thank you so much. >> Great segment guys. Okay, keep it right there everybody, Dave Vellante for Peter Burris, we'll be back in Madrid right after this short break.