>> Speaker: From around the globe, it's theCube with coverage of SUSECON DIGITAL brought to you by SUSE. >> Welcome back, this is theCube's coverage of SUSECON DIGITAL '20. I'm Stu Miniman and really happy to welcome to the program. We have one of the keynote speakers, Alexander Kocher. He is president and managing director of Elektrobit, really excited to dig in and talk about autonomous vehicles. Alex, thank you so much for joining us. >> Thank you Stu Miniman, I'm really excited that you pronounced my family name correct because this is quite difficult for you. It's a German name, thank you very much. >> Well, luckily on theCube, we do have lots of global people we have on the program. I try to do my best. My [mumbles] is all I can say really [mumbles]. >> Very difficult to pronounce it. >> Alright, so Alex, obviously autonomous vehicles is one of those use cases that talk a lot about everything from edge computing, to AI, you know, software eating the world, really one of those transformative technologies. Why don't we start with first, Elektrobit, give us a little bit as to, where Elektrobit fit in kind of the global auto landscape. >> Yeah, thank you Stu. So Elektrobit was founded in the late eighties, 1988. And since then, we are really doing embedded to be a pioneer in the embedded software and, providing solutions, software technologies, for the automotive industry. Since then we are powering more than 1 billion devices in much more than 100 million vehicles worldwide. And we are serving the automotive industry since then. So software is really becoming the single biggest enabler of innovation in the car, and software creation is our passion. So we enjoy solving challenging problems, and providing solutions that drive the mobility ecosystem of the future vehicle, where mobility causes zero fatalities, produces low emissions, and is perceived as quality time. This is also our mission and with that, we are providing services, software technologies, and tools for the automotive industry. >> Yeah, it has been fascinating to watch software in the automotive world. You know, I'm old enough to remember that, when you used to take a car in, the first thing they did was put it up and look under the hood and everything. And now pretty much, they plug a cable into the computer and, go to the diagnostic screens before they do anything else. When we talk about autonomous vehicles, I think many people would be familiar. There's really that five stage model of going from helping to fully autonomous. Give us a little bit as to what you're seeing in the trends out there, and how this market has been mature. >> Yeah, I think, the trend in the autonomous vehicles, we are at the moment at level two level two plus to where you still assisting the driver's behavior with various functions. We are starting to be, to go towards a level three hands-off. In the next, couple of, yeah, hopefully just months or single years, and then going from there to a fully autonomous vehicle, where you not only have hands-off, but also eyes off and then hand over the complete control to the car. But since then, it will still be a path. We just heard recently the announcement of all the, that, not only the functionality within the car, but also then the legal environment needs to be in place, so that you also can check that all of the various functions can be approved. I think the first step, which we will see is that we have it in a kind of a clean room environment, which means highways so the hybrid pilot, where you have to have a kind of insured environment and you can predict certain use cases. And with that we are targeting at, with the next generation of the cars, which can help in one or two years. >> Yeah its really interesting stuff, because of course, you know, it would be really simple if we had nothing, but the autobahn with nothing but autonomous vehicles. I'm sure you can have that running perfectly today, but number one, you start going on different roads and number two, you add that ever unpredictable human element when you have the cars that aren't, on the same system that can cause some issues there. I'm curious, anything from a European standpoint, you know, what's the partnership between government and industry on that, and I guess anything else that's different about Europe then maybe what we'd see in North America? >> Yeah, I think the, one of the biggest differences here is as soon as authorities approve cars, then the liability goes to the authority. And America's there is a complete different behavior in that perspective, liability is taken completely by the companies and the debt, of course. Although there are authorities to control certain environment, but the main liability issue stays with the company itself. And this per se is a complete different approach for that. I think technology-wise, we are here and there, on the same level as on the same technology level. And as you can see already in today's drive assistance functions, technology-wise, we are not far ahead. You can already try certain of those functions, for at least a couple of seconds, but in order to really accept and, calculate all the use cases, you need to start step by step. A highway is one of the perfect measures for that. But when you just go, I'm living here in the in Southern Germany, when you just go to an ancient city, city center, like we do have here Nuremberg, it can be really, really tricky that you consider all the specific use cases. So, here we need to optimize algorithms. The technology are also the horsepower in terms of processing load and of course, security of the census. So here is still for full autonomy still a path to go. >> Alright, so Alex, see, you're part of the keynote, here at SUSECON, obviously, you know, innovation, is a key topic as well as open force and community is a big topic of the show overall. Tell us a little bit about the partnership between Elektrobit and SUSE. >> Yeah, thank you very much for this question. This is really an exciting thing. So two companies like SUSE and Elekrobit, by the way, we have been founded here both, very, very in recent area, so no big area. So SUSE is a leader in delivering mission critical, Linux and container technologies in several industries and Elektrobit brings in the automotive experience. And what we aim for is to really provide the future software platform for automobiles that fulfills all the key requirements around openness, about reuse and, also about a huge pool of open source methodologies, and new modules so that we have a tremendous pool of, patents as well as a tremendous pool of innovation here. So this is the key topic. The automotive industry as such is changing, changing in a way that you continue to develop the technologies along the life cycle of the car in order to really enable our customers to download new functions and new services during the life cycle of the car. This methodology is already used in several other industries. And here we introduced with this partnership exactly the basis for that, in order to really, prepare our customers to focus on their differentiating technology and differentiating features. >> Yeah, fascinating thinking, you brought up, you know, the skill set of course is a key piece. Any industry that's going through change, we wonder who can come along and who's ready for that. It sounded like you were saying that, Linux and the other technologies in this space, there is a large pool of tech of knowledge out there, and that can help really kind of the growth next generation of the automotive industry. Am I getting that right? >> Yes, I mean, for sure the development methodology in open stores and embedded is completely different, but specifically when it comes to liability. So here, there, you need to comply to certain standards of cost, but this is one topic. The other thing is that really the innovation, who the innovation span you have in open source, as well as the modules already existing and the best practices from other industries. This is a tremendous advantage. And also one thing is in terms of changing in our industry, the automotive industry, the development methodology, excuse me, the reuse of, certain platforms is limited as soon as you have to jump to new generations of processes of software modules and so on and so forth. Here, we can with the partnership also leverage the experience we have, technologies which are also for a long period of time, backward compatible and reusable in the essential lower layers of the software, which you need to have by also complying to the relevant standards for a performance as well as a safety requirement. >> Yeah, really interesting mix of balancing that, differentiation in the marketplace while still being an upgradable path. I'm curious, you talked a little bit about the open source model. One of the key things, when you talk about going through a digital transformation is data. There's obviously a lot of data if you talk about autonomous vehicles. We see everybody about, you know, how many gigabytes per hour and all the maps and everything there. What is the role of data in this entire process? Is there sharing of data between some of the different players involved? >> So, yeah, data is I would say data is one is, first of all, data is in channel independent from industry the new currency. This is one thing, also realized in the automotive industry here. Of course we need to consider, certain privacy rules independent from, whether it's the car maker itself or its project or the driver. So we need to respect it, but independent from that, car's one of the most accurate sensors we do have, in our environment. And of course creating data, are we talking about one terabyte per day roundabout? And this is already now reused amongst, common factors amongst the industry. Just think about a certain, here as an acquisition of several players in the industry where they are sharing map data, because it doesn't make a difference, for a GM car, for a Ford car, for a BMW car, for a Daimler car. When you use the same road, the road stays, of course, the brand and the car changes, but the information about the road infrastructure is exactly the same. And this is the first topic which, has to be, or will be shared and is already shared. Second thing is traffic information where you have a mobile providers, in there, and this already is considered, and there are a lot of discussion and, or any business models undergoing or, in preparation for that. >> Yeah, well, you hope the roads don't change. I live in the Boston area, there's a times if you take six months off and all of a sudden you're like, wait, this road used to go a certain way. At least it's a lot easier to update, your software than it is for older vehicles that I'm driving. You talked a little bit about privacy. I know cybersecurity is one of the aspects that Elektrobit involved. Talk to us a little bit about the security aspect and, your company's experiences there. >> The security with transferring data into the car or outside of the car, data security is a key feature. It's just a must. So, in former times as Elektrobit as we are coming from inside the car has an embedded software provider. We protected really the devices within the car, for example, the automator from manipulation and, generated certain securities in the internal bus with our customers. But this is no longer enough. You need to go outside the car. So, when you transfer data from the cloud into the car, or vice versa and therefore cyber security, to predict the whole chain inside the car communication, they're all interfaces where you can connect devices or the backend, from where you transport the information. For them, recently Elektrobit acquired a company in Israel two years ago. But also we know that in the basic technology from the SUSE distribution, there is already a lot of technology in there, which makes data transfer really, really safe, sorry, secure, so that you can trust that the data and really keep the privacy you need to have for specific regions. >> Alright, well, this is a very fast moving industry. Give us a little bit as to what you see happening both the 24 months. What are some of the kind of major opportunities as well as challenges that are being faced? >> Yeah, I think, one of the biggest opportunities we will see in the upcoming directly next generation, is the car really becoming a part of the internet. I think with that, a lot of the business models from the common effector itself, from the suppliers need to change. So that really the common effector enables their customers to continuously update their device mobile device, namely the car. It's very similar to those devices at the moment from technology which you already have then suffocate in our pocket. Of course you cannot put the car into your pocket, but you want to have the same convenience, with new services, with new functions. And I think this is the most of, and the most exciting opportunity of the car. With that you need to have new technologies on platform. You need to have data security, you enable completely new business models. And this has changed our lives completely. Also our business compete. And I think these are the most important and the most exciting changes in the near future, as the next generation already is under preparation and will be launched really, really, really soon. And of course, second topic is the autonomous driving. It goes step by step as just as is testing the beginning. And this is the second opportunity then for many other companies making business with the time when the drivers then, have quality time and, can do something different than just hearing the car. >> Excellent, so much excitement in what is happening in industry. Definitely one we want to watch. Alex wannna give you the final word, SUSECON the partnership between Elektrobit and SUSE the final takeaways that you have for the event. >> Yeah, thanks enough. It's just exciting for us to have such a great partner like SUSECON experienced partner. It brings lots of new aspects into our industry helps us to provide the right solutions. And with that, we are sure that we can generate and we will generate the basis of the next smart cars of our customer in terms of softer platform. Thank you very much. >> Alex, thank you so much for joining us. I'm Stu Miniman, I'll have more coverage here from SUSECON DIGITAL '20. Thank you for watching theCube. (bright music)

>> Announcer: From around the globe, it's theCUBE, with coverage of SUSECON Digital, brought you by SUSE. (upbeat music) >> Welcome back. I'm Stu Miniman and this is theCUBE's coverage of SUSECON Digital. And really excited to welcome to the program a first time guest, and he's relatively fresh off the keynote, Alexander Kocher, who is the President and Managing Director of Elektrobit, talking about autonomous vehicles. Alex, thanks so much or joinin' us. >> Thank you, Stu, for inviting me. >> All right, so you know, definitely really interesting technologies, and a lot of talent. So many of the ways we talk about in the IT industry, to talk about cloud computing, edge impacting things, how AI fits into the world, and the balance between people and technology. Well, your company's living it. So why don't we start a little bit. Elektrobit, at least from the research I've done and from the keynote, you are a software company if I have it right. And autonomous vehicles is really what you're driving for. But give our audience a little bit of Elektrobit where you fit in the market today. >> Yeah, Elektrobit, so you can say we are software creatrs unlocking the future of mobility. We are pioneering software in the automotive industry since more than 30 years, empowering already now more than 1 billion devices, in hundreds of millions of cars, and serving since more than 30 years the automotive industry. So as software is becoming the second biggest enabler of the innovation in the car, we are driving this with our technologies. We are focusing on software infrastructure solutions, so coming from the deep, deep layers in the car, up to the HMI, up to the user interface, and providing there specific technologies for really building the basis, and able our customers to focus on their innovations. So this is car infrastructure software. This is software for autonomous driving, as you said. And this is application software mainly in the tooling to create fancy and good-looking user interfaces in modern vehicles. >> Yeah, wow, 30 years. You know most people don't think about software that long in the automotive industry. Of course anybody that owned a car understands that a lot of times it no longer, ya know, people going under the hood, but they're plugging something in and going on a computer, understand what that is. If you could, give us a little bit, what are the trends going on? We've been talking for the last couple a years, if you talk from an autonomous vehicle stand point. Probably people have seen the five stages model that's been put out there, everything from some driver-assist technologies, to a fully autonomous vehicle. But what are you seeing, your software, the companies you supply to and the users, what's happening there? >> So, I would class the trends at the moment in our industry in three blocks. There is electrification, where software is for sure playing a role, but is more used as a supporting technology. Here dominating innovation is coming from other technologies like battery, fuel cells, charging mechanisms, and so on. But then the second trend and the third trend, automated driving and connectivity, to really make the car part of the internet, these are two mega trends where software is dominating the scene, and really also dominating the value of the car as well. And I think these are the trends. We need for all of those to develop new car connectors, similar to server infrastructures already, so that you can seamlessly integrate applications, services from the cloud into the car. And I think these are the trends. And the partnership we are the moment working with SUSE is really coming into play as well to combine experiences from other industries, from other technologies, open source technologies with the embedded world. And create added value for our customer. >> Yeah so let's dig into that SUSE partnership a little bit. Obviously community is a big thing that's talked about there, at the show and from SUSE's customers. There's what can we learn, what is the role of open source, and how do we really enable innovation? So what's important about the partnership with SUSE? >> I think, let me give a little bit of a background. So when becoming an IT device, the amount of software, the complexity is increasing like hell. What he have at the moment, round about 10% created by software in the car, we will see 30% value created by software in 10 years from now. And this is done by a disruptive change in the development model. At the moment we stopped developing functions and features at the point when we introduce the car into the market. This will completely change. Just think about a mobile device like I have it here in my hand. During the whole life cycle of this device, which is of course much shorter than the life cycle of a car, you will innovate and update functions here. This will also be introduced in the next generation, which is under development at the moment, of cars. So that you can update applications, new services during the whole life cycle of the car. And this requires new platforms. It doesn't stop at the introduction of the car. It will continue over a real, real long period of time, years it takes, even. We have a long maintenance cycles. And therefore you need to have new partnership models, and also other technologies where this is already applied with other technologies in other industries. And here our partnership really comes into play, where we need to even get other talent pools. other pools of creativity, other pools of and forces of innovation, so that we really enable with existing methods, new methods, our customers to focus on their differentiating functions to compete against their competitor. And here exactly our partnership is targeting it. >> Okay so it sounds like we're talking specifically Linux means that there's a common underlying programming model, and that there's a skill set pool out there. Am I getting that right? >> Yes, correct. At the moment, so the automotive industry stands for reliable, high performance, high quality of cars and maintaining these features and essential functions over a long, long period of time. But when using embedded technologies, you are endangered always to re-implement it again and again and reuse is not necessarily that what is implemented here from one generation to the other, completely innovated sometimes, And here with other technologies, like you're doing with Linux for example, an open source, you open up a complete new field of innovation and creativity, and of course also access to talent pools, which is very much limited at the very moment in the embedded world as well. >> Alex, I'm curious how Elektrobit thinks about data. Number one, all the training data, how AI is done. Is there any industry sharing going on with that discussion? Let's start there and then maybe we'll talk a little bit about security when we get through the basic data points. >> (laughs) Yeah so, indeed, just think about cars. One of the most accurate sensor in our environment, with all the sensors you have, camera sensors, radio sensors, liter sensors, and so on and so forth, which create a hell lot amount of data, a terabyte by day. And of course this is something which needs to be shared, because the road infrastructure, we talked about this beforehand, is the same independent, whether it's a BMW car, whether it's a GM car, whether it's a Ford car, or a Daimler car, or a Toyota. So it's for all the cars the same car infrastructure. And of course there's a lot of discussion ongoing to share this data. Although now when making business out of that, the business model needs to, as you mentioned, for sure recognize and respect the privacy of the data in order to make business out of that. >> Excellent-- >> So then--Sorry >> Please, please continue. >> So yes, I think there is discussion ongoing. And already in, for example, in map data and traffic control, there is already ongoing the share of the data amongst the manufacturers as well. >> Excellent. And of course, security is paramount. When I look at Elektrobit, cyber security is prominent in the automotive discussion. How does that play in? What's the experience that you've had there from the security side. >> Yeah, so Elektrobit, so we built up our security, but really coming from inside the car. Now three years ago we acquired a company with out mother company together which is now integrated and consolidated within Elektrobit. It's called Argus Cyber Security from Tel Aviv in Israel. And with that we are now able to really provide solutions, end to end solutions from deep inside the car up to the cloud, so that the data stream is secure to the highest standards of security, of course. And this is, on the long side, really securing remote control, maintenance of the car, but also then privacy in terms when you download new services, when you provide information into the cloud where you are. For example we talked abut this data as new currency from the sensors existing in the car. So for that reason exactly we acquired this company with their technologies we are able to provide end to end solutions also for the existing software we are providing to our customers. >> Right, Alex, I'm curious just when you talk about autonomous vehicles, anything distinct about Europe? I think about the challenge and the opportunity. Number one, you're in Germany. You've got some of the best highways in the world. Well thought-out, really well architected. But throughout Europe you also have some the oldest cities where it could be really challenging to traverse. So anything different you might be able to share with our audience about what we should look for for that journey of autonomous vehicle in Europe? >> So... basically your question, already lined it out. So yes, I think autonomous driving and it's starting with functions like hybrid pilot so that you really create a kind of a clean room, where you have a very well-defined environment, where you can start to drive autonomous, and really hands off, eyes off, so level three, level four. In old cities, the structure is yeah, grown, grown over hundreds of years. So it's for sure not foreseen for autonomous driving, at that point in time. Or let's say at that point in time you had an autonomous vehicular horse which found all the time the stable. But nowadays it's a little bit different. So the more difficult environment is for sure the center of cities. And there it will take a while. But we are on the go by going really step by step from a very well-defined environment like a highway, where you can define certain use cases. And with the evolution of sensors, with the evolution of algorithms, with the evolution of processing power, then go step by step to a more complex environment like inner cities. >> Excellent. What should people be looking for when it comes to autonomous vehicles? What can you give us on the next 12 to 24 months, what you're expecting in the industry? >> So I think at the moment, I think in the 12 to, we're still in the face when it comes to autonomous driving, we have driver assistance functions evolving from there. A level two, level two plus. Level three functions where you really then have hands off, will probably come in two, three, four years. Here it's not only the industry by itself who is the limiting factor, but also the regulations on the outside. We just recently saw the announcement of Audi that homologation related to topics at the moment not clear. This is also to be considered. Technology is already prepared, ie, I'm now, even with driver-assistance functions, able to drive. I had an experience with my car by 200km/hr around the curve, and pulling the steers a little bit off So it's still in the face. You have to be aware that you can control. So the function itself is already existing. But homologation that you really can do this for more than 10 seconds, this is the critical thing. And really be prepared techonology for all the eventual things. So here we have limiting factors also from the regulations around that. And this is basically what we have to deal with. So just recently announced by Audi A8 in the introduction. >> Excellent stuff. All right, Alex, I want to give you the final word. Just share with the audience at SUSECON, what it means for Elektrobit to participate in this partnership. >> Yeah, I think the main thing of this partnership is really that we... We are enabled to really provide and infrastructure which fulfills the complete requirements of the car industry. So long-term maintenance, enablement of secure downloads during the whole life cycle of the car, and reusabilty, backward compatibility which is very important thing as well, when you produce technologies for products which have a very long product life cycle. And with the experience SUSE brings into play from other industries, with their solutions, with their Linux distributions and container technologies, with our experience from the automotive industry, I'm really sure that with that partnership, we enable our customers to focus on their innovations, and we enable ourselves to provide the basic solutions for the industry, and for... new future intelligent vehicles. >> All right, well, thank you so much for sharing all of the updates. Fascinating stuff. Thank you so much for joining. >> Thank you, Stu, for inviting me. >> All right, lots more coverage from SUSECON Digital '20. I'm Stu Miniman and thank you for watching theCUBE. (upbeat music)

>> from Austin, Texas. It's Theo Cube, covering pure storage. Accelerate 2019. Brought to you by pure storage. >> Welcome back to the Cube, The leader and live tech coverage. I'm Lisa Martin with David Dante. We got a pretty cool guests coming up next, guys, you may have seen him here on the Q before. He has back Matt Harris, the head of I T for Mercedes AMG, Petronas Motor Sport. Matt, Welcome back. >> Often a >> way got the car over there with excitement. One of the coolest sports I've ever become involved with. Formula One is this incredible mix of technology strategy. All these crazy things you guys that Mercedes have been partners, customers a cure for about what? 45 years? >> 2015. As a customer, we became partners in 2016. >> I wonder if they like to save Mercedes AMG Petunias Motor Sport has had five consecutive years of both constructors championships driver's championships. You're a great position on both for 2019. It was a little bit of a history about the product that you put out on truck every other week and how pure storage is a facilitator of that. >> Yeah, okay, so it's an interest in a story for those that are interested in Formula One, because what you see on the track looks the same. But realistically, every time he goes out, the guarantee will be different. That level of difference could be a simple wing change or configuration, always based on data that we're learning from during a race again. But every week we also have a different car dependent on the track we're going to. So we have two different worlds that basically were to rate on a minute by minute, hour by hour and day by day at the track. But in the factory, that could be the same sort of it oration. But it could also be into weekly or monthly or year for a car. So all of that is based on data. So everything we do is that businesses revolves around data. We never make a change to the car without me now to back it up with empirical knowledge. Even if the driver turns around and tells us they feel something called, they believe something, we will always make sure we have data to back up that decision, So access to data is critical. Compute performance whether it's high performance, compute for our safety, for instance, whether it's for you as an end user, access to data is critical across everything that we do is time critical Time is our currency really as a business if we slow down your job? Generally, that probably means that you've got less time to make the correct decision. Or maybe you have to turn into a guess or a hunch, which that's never a good place to be in our sport. >> No, I would think not. >> I've I recall, from our conversation last year their rules that say, How many people you can have in your entourage like 60. I think it was yes, and at the time I think you said you got, like, 15 Allocated to data. Is that ratio kind of still holding? I >> still exactly the same in our tracks. On environment, they're still the same in the factory. We have more than that, depending on how many people on what time of day, what day of the week. So on a Friday race day, practice day, we can have a minimum. There'll be 30 people in our race support room will be looking at data along with those other 15. But you can have the whole Aargh department or design department or logistics. Whoever could still be looking at data from the track real time, so we can have as many as 4 to 500 looking at data if they want to. And if that's the right thing going on earlier in the season, you generally get more people looking As the season goes on. It's probably more aargh focused, maybe mechanically if we got something new, or maybe the engine division again in a completely separate building in the U. K 40 miles apart, they've got another set of people that will be looking and trolling through data riel time from the but looking really at the power unit rather than the chassis side. >> And you're generating, like roughly half a terabyte a weekend on a race weekend. Is that still about the same? Or is that growing a car >> perspective? It's just under half a terabyte, but we produce up to another half a terabyte of other supporting data with that GPS data, weather data, video, audio, whatever it would be other information to help with the strategy side of things So we're around 77 50 to 1 terabyte for race weekend, >> and each car has about 300 sensors. I think when we spoke with you last year, or maybe you're half ago is about 200 so that's increasing in terms of all the data being captured every race weekend. But one of the things that I love that matter sizes, you know, we're idea at Mercedes is not that unlike I t at other groups who really rely on high performance systems. But you do put out a new product every two weeks and this really extreme range of conditions, your product is extremely expensive as pretty sexy. Like the portability factor. You have to set up a tea shop, have any 20 weekends a year and set it up in what, 36 hours and take it down in six. >> And a nine year old joke about the taking it down in six is a bit like a Benny Hill sketch. It's obviously choreographed and, well, well rehearsed, but we have all the same systems as any normal business would have the tracks. That environment is very different, though we don't have air conditioning in so all the IittIe equipment has to work at the natural ambient air temperature of the country. We're in this year. Believe it or not, Germany and hungry have been our biggest challenge. We've had for the last 43 to 4 years because they had 45 degree air ambient air temperature. So forget humidity for a minute, which is Another kettle of fish probably affects us a bit more, maybe, than the systems, but we're only chucking that air as fast as we can across the components. So we're not putting any cooling into what is probably around the tolerance of most I T systems. So we have to rely basically on air throughput to terminate. Keep kit. Cool. Now the benefit with pure is actually doesn't create any heat, either. There's no riel heat generation, so it's quite tolerant, which helps us get it doesn't create Maur, but the environment we put it into is quite special. But what we're doing is what any business would want to do. Access toe email file systems. What we're trying to do is give it in a performance fashion. People need to make a decision. So in qualifying, for instance, those 300 sensors. That information that we've got from the car, we've got minutes to make a decision based on data. If it takes you too long to get the data off, you can't then look at the data to make a decision. So we have to make sure data in just from the car and then basically multi access from everybody in the factory or the track side is performance enough to make a decision before the car goes back out again. Otherwise, we're wasting track time. >> So you've always had data in this business. Early days was all analog, and it obviously progressed and thinking about what you want to do, Going forward with data. What kind of information or capabilities don't you have? Where that technology in the future could address >> s so interesting. One is technology of the future. If you know what it is, let me know with what we know right now, I think a lot of it's gonna be about having the ability to have persistent storage. But actually the dynamic of the compute resource eso looking at things like kubernetes or anything like that to turn around and have dynamic resource spin up as and when required to do high performance computer calculations based on the data, maybe to start giving us some automated information, I'm gonna be careful of the M l A. I is for our businesses, it's not quite as simple as others because our senior management very technically capable, and they just see it as advanced statistical analysis. So unless you program, it is not gonna give you an answer. Now we've started to see some things this year were actually the computer is teaching us things we didn't ask it to. So we have got some areas where we're beginning to learn that. That's not necessarily the case now, but for us that access to data moving forward, it's probably gonna be compute. Combined with that underlying storage platform, there's going to be critical onstage. You you heard Robin people talking about the ability to have that always present storage layer with the right computer. That's something for us is going to be critical, because otherwise we're gonna waste money and have resource sat doing nothing. >> Is security >> an issue for you? I mean, it's an issue for everybody, but there isn't a game of honor because you got this, you know, little community that you guys trying to hack each other systems. >> So it's an interesting one inside the sport, Actually, no. Because a few years ago there was a very high profile case where data went between two teams and there was £100 million fine's exclusion from the sport for a season. So that's that's >> too big. You don't mess with that. >> But also, if you think of that from our perspective, we've got the Daimler star on here. We cannot afford to have any of that Brenda brand reputational rubbing off on Damon's. So that's a no no other teams I can't talk for. But we're all fairly sensible between ourselves. What will be interesting moving forward is what technologies air in our sport, but actually of the whether their motor manufacturers or not, is their technology in there that they're interested in. Maybe the battery technology from the power unit side of things is that the power unit itself. So are other things actually more interesting to those other >> places. It legal for you, you know, by the rules of sports, a monitor, just data or captured data, whether it's visual, whatever from your competitors. Eso anything, >> this public? Yes, it's fair game. Okay, so we get given all the teams. Actually, we get a standard set of three or four different streams of information around GPS timing on some video feeds and audio feeds on their publicly consumable by the team's. When I say public for a second on those feeds, we can do what we like. You know that there for us to infer information, which we do a lot off, is what helps our strategy team to turn around and actually predict what we might or might not need to do as far as a pit stop or tire degradation. >> And that's where the human element must come into understanding the competent, like to football coaches who who know each other right? >> Well, yes. And now, if you think if you add to that the human element off Well, what happens if one team strategy person changes? Are they gonna make a different call based on the same data? Is their hunch different? Do they think they know better within a team? You can have that discussion. So what happens in another team where they're cars, not as performance so their mindset. Maybe they're thinking differently. Or maybe a team's got the most performance car of the moment and they think that they're going to do X. And we're like, Well, we're gonna do something different than to try and actually catch them out. So do we. Now don't do the normal thing. >> So let's hope >> Gamification I love it. >> Let's look at all. Make a prediction. 2019 is gonna be another Mercedes AMG way. So at the end of the season, all of the data that you have collected from the cars, all the sensors, all the weather data, GPS, et cetera how does pure facilitate in the off season the design of the 2020 car, for example, Where does where does things like computational fluid dynamics? >> Okay, so all of our production data is on pure, whether it's on a ray or blade somewhere, it's on pure storage across the site. So they're involved. Whether you're talking about design, whether you're talking about final element analysis for hyper a ll, the C f. D. Using high performance computer systems, everything some pure so from that point of view, is making sure we're using the right resource in the right place to get the best performance. Now, see if he's an interesting one because we're regulated by the F A a. About the amount of compute that weaken you. He's now. Because of that, you want it to be as efficient as you possibly can. It's not speed but the efficient use off CPU time. So if a CPU is waiting for data, that's wasted, Okay, so for us, it's trying to make sure that whole ecosystem is as efficient as we can. That's obviously an integral part of everything we do, so whether we're wind tunnel testing, whether we're in the dino, the simulators, but everything basically comes back to trying to understand and correlate the six or seven different places we generate data, trying to make sure that when there's a change in the simulator, we understand that change in the real world or in a diner or in safety. So all of that, what pure do is allow us to have that single place to go and look how I perform and always available. And for me, I don't have to have a story. Jasmine. Yeah, we've got a team of people that actually are thinking about that for us at Pure, You know, there is invested in us these days. Yeah, I walk around here, I'm very fortunate. I get to see all of the senior guys here and there. They are asking me what's going on and how's things with sequel Oracle Because they know exactly what we're doing and they're they're trying to say what's coming. So things like object engine Pierre So we've been talking to pure about using that over the coming months. But what? We're not having it at the moment. Go out and learn it. Actually, they coming in and they're telling us all about it. So they become a virtual extension to my team, which is just amazing. >> Yeah, far more efficient. You're able to focus on a much more things that drive value for the business. As we look at some of the things like the Evergreen business model. What were some of the big ah ha we hear is the right solution for us back in 2015. Is that >> so? Evergreen and love. Your stories were two things at the time that we're just incredible for us because love your storage was basically you could have an array and basically you could use it. And there was no commitment, no anything. But if you like that, you could keep it, obviously, paying for it. Ah, nde. When we did that in the factory, basically, within a week of being in there that the team were like, Whoa, hang on, that's going nowhere. So that was That was a nice, easy one. But Evergreen was an interesting one, which has only really, truly for me. I've always bought into it. But the last probably 18 months we've used it time and time and time again because the improvements with the speed of light x 90 coming envy Emmy drives. When we were looking at capacity, what we did was we turned round and said, Well, actually, we can buy more dense units in the next 90 so we're only buying the extra capacity, but we were getting new technology. So nations, all the innovation that you're putting into their products were getting it. So today, when they were talking about the memory based access, and if your things always sat there going, I can use that. Oh, and there's no there's no work for me, there's no effort. The only thing I gotta worry about is whether I've got capacity for that. Those modules to go in. So Evergreen has worked several times because I don't have to go back to the cap export and go. Could I have another x £1,000,000 please? Why? I need some more storage. Yeah, but you bought some of the other day. Yeah, well, that one. I need to get rid of it because I need a bigger one. And I don't have to do that. Now. I just go in. I'm telling them what the increases for which actually, they can choose Then if they want to increase, they know what the business benefit is rather than just I t has got to turn around and either replace it because of age or the new version doesn't support is not an uplift, not upgrade from the old. One >> I've seen was looking at some of your stats and the case study that's currently online on. Imagine these numbers have gone up 68% reduction in data center Rackspace and saving £100,000 a year and operating costs >> those that would have been probably two years ago. Ish roughly those figures. And the operating cost is a huge improvement for us. Cap Ex is probably the biggest one for me. They were moving forward with cost caps coming into Formula One. That type of thing is gonna be invaluable. Does not happen to do a forklift upgrade of your storage. Well, I wouldn't know what I would do if I had to upgrade what I now own from pure I can't even imagine what? I don't want to turn around town my bosses what that's >> gonna cost. Well, it sounds like you really attacked the op X side with R and D with pure r and D. I kind of like that shifting, you know, labor toe are Andy because you don't want to spend labour on managing storage a raise, make no sense for your business. Okay. What do you want? Pure toe spend? R and D are now, what problem can they saw for? You mean >> so racy is gonna help If I'm really honest, that's actually is gonna help fill a whole quite well for us because we weren't really sure what to put some of that less hot data we were like, Well, where we going to start to put this now? Because we were beginning to fill up the array and the blades. Actually, with a racy no, we can actually use that different class of storage actually, to keep it still online. Still be out to do some machine learning A. I in the future when that comes around. But actually I can now have Maur longevity out of my existing array and blades. So that's brilliant and coming, I think, having I need to be careful, I know some things that are coming. Uh, the active sinking array is brilliant, and we've been using that since it came out. Having that similar or same ability in Blade when it comes will be a very advantageous having those played enclosures. We've gone to multi chassis flash played over the last six weeks, so that for us is great. Once we can start to synchronize between those two, then that's ah, that's another big one for us, for resiliency, for fault, tolerance, but also workload movement. That thing I said about persistent stories, layer, I'm not gonna need to care where it is, and it will be worked out by the storage in the orchestration layer so it can have the storage in the computer in the right place. >> Wow. Great story, Matt, as always. And I think it's Pierre calls this the unfair advantage coming to life. Best of luck for the rest of the 2019 season. >> I'll take it. >> All right, We'll see you next time. >> Thank you. >> Keep before >> for David Dante. I am Lisa Martin. You're watching the Cube from Cure Accelerate in Austin, Texas.

>> Announcer: Live from San Jose, it's theCUBE, presenting Big Data Silicon Valley. Brought to you by SiliconANGLE Media and it's ecosystem partners. >> Welcome back to Big Data SV in San Jose. This theCUBE, the leader in live tech coverage. My name is Dave Vellante and this is day two of our wall-to-wall coverage. We've been here most of the week, had a great event last night, about 50 or 60 of our CUBE community members were here. We had a breakfast this morning where the Wikibon research team laid out it's big data forecast, the eighth big data forecast and report that we've put out, so check out that online. Jacques Nadeau is here. He is the CTO and co-founder of Dremio. Jacque, welcome to theCUBE, thanks for coming on. >> Thanks for having me here. >> So we were talking a little bit about what you guys do. Three year old company. Well, let me start. Why did you co-found Dremio? >> So, it was a very simple thing I saw, so, over the last ten years or so, we saw a regression in the ability for people to get at data, so you see all these really cool technologies that came out to store data. Data lakes, you know, SQL systems, all these different things that make developers very agile with data. But what we were also seeing was a regression in the ability for analysts and data consumers to get at that data because the systems weren't designed for analysts, they were designed for data producers and developers. And we said, you know what, there needs to be a way to solve this. We need to be able to empower people to be self-sufficient again at the data consumption layer. >> Okay, so you solved that problem how, you said, called it a self-service of a data platform. >> Yeah, yeah, so self-service data platform and the idea is pretty simple. It's that, no matter where the data is physically, people should be able to interact with a logical view of it. And so, we talk a little bit like it's Google Docs for your data. So people can go into the system, they can see the different data sets that are available to them, collaborate around those, create changes to those that they can then share with other people in the organization, always dealing with the logical layer and then, behind the scenes, we have physical capabilities to interact with all the different system we interact with. But that's something that business users shouldn't have to think as much about and so, if you think about how people interact with data today, it's very much about copies. So every time you want to do something, typically you're going to make a copy. I want to reshape the data, I make a copy. I want to make it go faster, I make a copy. And those copies are very, very difficult for people to manage and they could have mixed the business meaning of data with the physical, I'm making copies to make them faster or whatever. And so our perspective is that, if you can separate away the physical concerns from the logical, then business users have a much more, much more likelihood to be able to do something self-service. >> So you're essentially virtualizing my corpus of data, independent of location, is that right, I mean-- >> It's part of what we do, yeah. No, it's part of what we do. So, the way we look at it is, is kind of several different components to try to make something self-service. It starts with, yeah, virtualize or abstract away the details of the physical, right? But then, on top of that, expose a very, sort of a very user-friendly interface that allows people to sort of catalog and understand the different things, you know, search for things that they want to interact with, and then curate things, even if they're non-technical users, right? So the goal is that, if you talk to sort of even large internet companies in the Valley, it's very hard to even hire the amount of data engineering that you need to satisfy all the requests of your end-users of data. And so the, and so the goal of Dremio is basically to figure out different tools that can provide a non-technical experience for getting at the data. So that's sort of the start of it but then the second step is, once you've got access to this thing and people can collaborate and sort of deal with the data, then you've got these huge volumes of data, right? It's big data and so how do you make that go faster? And then we have some components that we deal with, sort of, speed and acceleration. >> So maybe talk about how people are leveraging this capability, this platform, what the business impact is, what have you seen there? >> So a lot of people have this problem, which is, they have data all over the place and they're trying to figure out "How do I expose this "to my end-users?" And those end-users might be analysts, they might be data scientists, they might be product managers that are trying to figure out how their product is working. And so, what they're doing today is they're typically trying to build systems internally that, to provide these capabilities. And so, for example, working with a large auto manufacturer. And they've got a big initiative where they're trying to make the data that they have, they have huge amounts of data across all sort of different parts of the organization and they're trying to make that available to different data consumers. Now, of course, there's a bunch of security concerns that you need to have around that, but they just want to make the data more accessible. And so, what they're doing is they're using Dremio to figure out ways to, basically, catalog all the data below, expose that to the different users, applying lots of different security rules around that, and then create a bunch of reflections, which make the things go faster as people are interacting with the things. >> Well, what about the governance factor? I mean, you heard this in the hadoop world years ago. "Ah, we're going to make, we're going to harden hadoop, "we're going to" and really, there was no governance and it became more and more important. How do you guys handle that? Do you partner with people? Is it up to the customer to figure that out? Do you provide that? >> It's several different things, right? It's a complex ecosystem, right? So it's a combination of things. You start with partnering with different systems to make sure that you integrate well with those things. So the different things that control some parts of credentials inside the systems all the way down to "What's the file system permissions?", right? "What are the permissions inside of something like Hive and the metastore there?" And then other systems on top of that, like Sentry or Ranger are also exposing different credentialing, right? And so we work hard to sort of integrate with those things. On top of that, Dremio also provides a full security model inside of the sort of virtual space that we work. And so people can control the permissions, the ability to access or edit any object inside of Dremio based on user roles and LDAP and those kinds of things. So it's, it's kind of multiple layers that have to be working together. >> And tell me more about the company. So founded three years ago, I think a couple of raises, >> Yep >> who's backing you? >> Yeah, yeah, yeah, so we founded just under three years ago. We had great initial investors, in Red Point and Lightspeed, so two great initial investors and we raised about 15 million on that round. And then we actually just closed a B round in January of this year and we added Norwest to the portfolio there. >> Awesome, so you're now in the mode of, I mean, they always say, you know, software is such a capital-efficient business but you see software companies raising, you know, 900 million dollars and so, presumably, that's to compete, to go to market and, you know, differentiate with your messaging and branding. Is that sort of what the, the phase that you're in now? You kind of developed a product, it's technically sound, it's proven in the marketspace and now you're scaling the, the go-to-market, is that right? >> That's exactly right. So, so we've had a lot of early successes, a lot of Fortune 100 companies using Dremio today. For example, we're working with TransUnion. We're working with Intel. We actually have a great relationship with OVH, which is the third-largest hosting company in the world, so a lot of great, Daimler is another one. So working with a lot of great companies, seeing sort of great early success with the product with those companies, and really looking to say "Hey, we're out here." We've got a booth for the first time at Strata here and we're sort of letting people know about, sort of, a better way, or easier way, for people to deal with data >> Yeah. >> A happier way. >> I mean, it's a crowded space, right? There's a lot of tools out there, a lot of companies. I'm interested in how you sort of differentiate. Obviously simplification is a part of that, the breadth of your capabilities. But maybe, in your words, you could share with me how you differentiate from the competition and how you break out from the noise. >> Yeah, yeah, yeah, so it's, you're absolutely right, it's a very crowded space. Everybody's using the same words and that makes it very hard for people to understand what's going on. And so, what we've found is very simple is that typically we will actually, the first meeting we deal with a customer, within the first 10 minutes we'll demo the product. Because so many technologies are technologies, not, they're not products and so you have to figure out how to use the product. You've got to figure out how you would customize it for your certain use-case. And what we've found with our product is, by making it very, very simple, people start, the light goes on in a very short amount of time and so, we also do things on our website so that you can see, in a couple of minutes, or even less than that, little animations that sort of give you a sense of what it's about. But really, it's just "Hey, this is a product "which is about", there's this light bulb that goes on, it's great. And you figure this out over the course of working with different customers, right? But there's this light bulb that goes on for people that are so confused by all the things that are going on and if we can just sit down with them, show them the product for a few minutes, all of a sudden they're like "Wait a minute, "I can use this", right? So you're frequently talking to buyers that are not the most technical parts of the organization initially, and so most of the technologies they look at are technologies that are very difficult to understand and they have to look to others to try to even understand how it would fit into their architecture. With Dremio, we have customers that can, that have installed it and gotten up, and within an hour or two, started to see real value. And that sort of excitement happens even in the demo, with most people. >> So you kind of have this bifurcated market. Since the big data meme, everybody says they're data-driven and you've got a bifurcated market in that, you've got the companies that are data-driven and you've got companies who say they're data-driven but really aren't. Who are your customers? Are they in both? Are they predominantly in the data-driven side? Are they predominantly in the trying to be data-driven? >> Well, I would say that they all would say that they're data-driven. >> Yeah, everyone, who's going to say "Well, we're not data-driven." >> Yeah, yeah, yeah. So I would say >> We're dead. >> I would say that everybody has data and they've got some ways that they're using it well and other places where they feel like they're not using it as well as they should. And so, I mean, the reason that we exist is to make it so it's easier for people to get value out of data, and so, if they were getting all the value they think they could get out of data, then we probably wouldn't exist and they would be fully data-driven. So I think that everybody, it's a journey and people are responding well to us, in part, because we're helping them down that journey. >> Well, the reason I asked that question is that we go to a lot of shows and everybody likes to throw out the digital transformation buzzword and then use Uber and Airbnb as an example, but if you dig deeper, you see that data is at the core of those companies and they're now beginning to apply machine intelligence and they're leveraging all this data that they've built up, this data architecture that they built up over the last five or 10 years. And then you've got this set of companies where all the data lives in silos and I can see you guys being able to help them. At the same time, I can see you helping the disruptors, so how do you see that? I mean, in terms of your role, in terms of affecting either digital transformations or digital disruptions. >> Well, I'd say that in either case, so we believe in a very sort of simple thing, which is that, so going back to what I said at the beginning, which is just that I see this regression in terms of data access, right? And so what happens is that, if you have a tightly-coupled system between two layers, then it becomes very difficult for people to sort of accommodate two different sets of needs. And so, the change over the last 10 years was the rise of the developer as the primary person for controlling data and that brought a huge amount of great things to it but analysis was not one of them. And there's tools that try to make that better but that's really the problem. And so our belief is very simple, which is that a new tier needs to be introduced between the consumers and the, and the producers of data. And that, and so that tier may interact with different systems, it may be more complex or whatever, for certain organizations, but the tier is necessary in all organizations because the analysts shouldn't be shaken around every time the developers change how they're doing data. >> Great. John Furrier has a saying that "Data is the new development kit", you know. He said that, I don't know, eight years ago and it's really kind of turned out to be the case. Jacques Nadeau, thanks very much for coming on theCUBE. Really appreciate your time. >> Yeah. >> Great to meet you. Good luck and keep us informed, please. >> Yes, thanks so much for your time, I've enjoyed it. >> You're welcome. Alright, thanks for watching everybody. This is theCUBE. We're live from Big Data SV. We'll be right back. (bright music)

>> Announcer: Live from Munich, Germany, it's theCUBE, covering DataWorks Summit Europe 2017. Brought to you by HORTONWORKS. (electronic music) (crowd) >> Okay, welcome back everyone, we are here live in Munich, Germany, for DataWorks 2017, formerly Hadoop Summit, the European version. Again, different kind of show than the main show in North America, in San Jose, but it's a great show, a lot of great topics. I'm John Furrier, my co-host, Dave Vellante. Our next guest is John Kreisa, Vice President of International Marketing. Great to see you emceeing the event. Great job, great event! >> John Kreisa: Great. >> Classic European event, its got the European vibe. >> Yep. >> Germany everything's tightly buttoned down, very professional. (laughing) But big IOT message-- >> Yes. >> Because in Germany a lot of industrial action-- >> That's right. >> And then Europe, in general, a lot of smart cities, a lot of mobility, and issues. >> Umm-hmm. >> So a lot of IOT, a lot of meat on the bone here. >> Yep. >> So congratulations! >> John Kreisa: Thank you. >> How's your thoughts? Are you happy with the event? Give us by the numbers, how many people, what's the focus? >> Sure, yeah, no, thanks, John, Dave. Long-time CUBE attendee, I'm really excited to be here. Always great to have you guys here-- >> Thanks. >> Thanks. >> And be participating. This is a great event this year. We did change the name as you mentioned from Hadoop Summit to DataWorks Summit. Perhaps, I'll just riff on that a little bit. I think that really was in response to the change in the community, the breadth of technologies. You mentioned IOT, machine learning, and AI, which we had some of in the keynotes. So just a real expansion of from data loading, data streaming, analytics, and machine learning and artificial intelligence, which all sit on top and use the core Hadoop platform. We felt like it was time to expand the conference itself. Open up the aperture to really bring in the other technologies that were involved, and really represent what was already starting to kind of feed into Hadoop Summit, so it's kind of a natural change, a natural evolution. >> And there's a 2-year visibility. We talk about this two years ago. >> John Kreisa: Yeah, yeah. >> That you are starting to see this aperture open up a little bit. >> Yeah. >> But it's interesting. I want to get your thoughts on this because Dave and I were talking yesterday. It's like we've been to every single Hadoop Summit. Even theCUBE's been following it all as you know. It's interesting the big data space was created by the Hadoop ecosystem. >> Umm-hmm. >> So, yeah, you rode in on the Hadoop horse. >> Yeah. >> I get that. A lot of people don't get them. They say, Oh, Hadoop's dead, but it's not. >> No. >> It's evolving to a much broader scope. >> That's right. >> And you guys saw that two years ago. Comment on your reaction to Hadoop is not dead. >> Yeah, wow (laughing). It's far from dead if you look at the momentum, largest conference ever here in Europe. I think strong interest from them. I think we had a very good customer panel, which talked about the usage, right. How they were really transforming. You had Walgreens Booth's talking about how they're redoing their shelf, shelving, and how they're redesigning their stores. Don Ske-bang talking about how they're analyzing, how they replenish their cash machines. Centrica talking about how they redo their... Or how they're driving down cost of energy by being smarter around energy consumption. So, these are real transformative use cases, and so, it's far from dead. Really what might be confusing people is probably the fact that there are so many other technologies and markets that are being enabled by this open source technologies and the breadth of the platform. And I think that's maybe people see it kind of move a little bit back as a platform play. And so, we talk more about streaming and analytics and machine learning, but all that's enabled by Hadoop. It's all riding on top of this platform. And I think people kind of just misconstrue that the fact that there's one enabling-- >> It's a fundamental element, obviously. >> John Kreisa: Yeah. >> But what's the new expansion? IOT, as I mentioned, is big here. >> Umm-hmm. >> But there's a lot more in connective tissue going on, as Shawn Connelly calls it. >> Yeah, yep. >> What are those other things? >> Yeah, so I think, as you said, smart cities, smart devices, the analytics, getting the value out of the technologies. The ability to load it and capture it in new ways with new open source technology, NyFy and some of those other things, Kafka we've heard of. And some of those technologies are enabling the broader use cases, so I don't think it's... I think it's that's really the fundamental change in shift that we see. It's why we renamed it to DataWorks Summit because it's all about the data, right. That's the thing-- >> But I think... Well, if you think about from a customer perspective, to me anyway, what's happened is we went through the adolescent phase of getting this stuff to work and-- >> Yeah. >> And figuring out, Okay, what's the relationship with my enterprise data warehouse, and then they realize, Wow, the enterprise data warehouse is critical to my big data platform. >> Umm-hmm. >> So what's customers have done as they've evolved, as Hadoop has evolved, their big data platforms internally-- >> Umm-hmm. And now they're turning to to their business saying, Okay, we have this platform. Let's now really start to go up the steep part of the S-curve and get more value out of it. >> John Kreisa: Umm-hmm. >> Do you agree with that scenario? >> I would definitely agree with that. I think that as companies have, and in particularly here in Europe, it's interesting because they kind of waited for the technology to mature and its reached that inflection point. To your point, Dave, such that they're really saying, Alright, let's really get this into production. Let's really drive value out of the data that they see and know they have. And there's sort of... We see a sense of urgency here in Europe, to get going and really start to get that value out. Yeah, and we call it a ratchet game. (laughing) The ratchet is, Okay, you get the technology to work. Okay, you still got to keep the lights on. Okay, and oh, by the way, we need some data governance. Let's ratchet it up that side. Oh, we need a CDO! >> Umm-hmm. >> And so, because if you just try to ratchet up one side of the house (laughing) (cross-talk)-- >> Well, Carlo from HPE said it great on our last segment. >> Yeah. >> And I thought this was fundamental. And this was kind of like you had a CUBE moment where it's like, Wow, that's a really amazing insight. And he said something profound, The data is now foundational to all conversations. >> Right. >> And that's from a business standpoint. It's never always been the case. Now, it's like, Okay, you can look at data as a fundamental foundation building block. >> Right. >> And then react from there. So if you get the data locked in, to Dave's point about compliance, you then can then do clever things. You can have a conversation about a dynamic edge or-- >> Right. >> Something else. So the foundational data is really now fundamental, and I think that is... Changes, it's not a database issue. It's just all data. >> Right, now all data-- >> All databases. >> You're right, it's all data. It's driving the business in all different functions. It's operational efficiency. It's new applications. It's customer intimacy. All of those different ways that all these companies are going, We've got this data. We now have the systems, and we can go ahead and move forward with it. And I think that's the momentum that we're seeing here in Europe, as evidence by the conference and those kinds of things, just I think really shows how maybe... We used to say... I'd say when I first moved over here, that Europe was maybe a year and a half behind the U.S., in terms of adoption. I'd say that's shrunk to where a lot of the conversations are the exact same conversations that we're having with big European companies, that we're having with U.S. companies. >> And, even in... >> Yeah. >> Like we were just talking to Carlo, He was like, Well, and Europe is ahead in things like certain IOT-- >> Yeah. >> And Industrial IOT. >> Yeah. >> Yeah. >> Even IOT analytics. Some of the... Tesla not withstanding some of the automated vehicles. >> John Kreisa: Correct. >> Autonomous vehicles activity that's going on. >> John Kreisa: That's right. >> Certainly with Daimler and others. So there's an advancement. It almost reminds me of the early days of mobile, so... (laughing) >> It's actually, it's a good point. If you look at... Squint through some of the perspectives, it depends on where you are in the room and what your view is. You could argue there are many things that Europe is advanced on and where we're behind. If you look at Amazon Web Services, for instance. >> Umm-hmm. >> They are clearly running as fast as they can to deploy regions. >> Umm-hmm. >> So the scoop's coming out now. I'm hearing buzz that there's another region coming out. >> Right. >> From Amazon soon (laughing). They can't go fast enough. Google is putting out regions again. >> Right. >> Data centers are now pushing global, yet, there's more industrial here than is there. So it's interesting perspective. It depends on how you look at it! >> Yeah, yeah, no, I think it's... And it's perfectly fair to say there are many places where it's more advanced. I think in this technology and open source technologies, in general, are helping drive some of those and enable some of those trends. >> Yeah. >> Because if you have the sensors, you need a place to store and analyze that data whether it's smart cars or smart cities, or energy, smart energy, all those different places. That's really where we are. >> What's different in the international theater that you're involved in because you've been on both sides. >> Yep. >> As you came from the U.S. then when we first met. What's different out here now? And I see the gaps closing? What other things that notable that you could share? >> Yeah, yeah, so I'd say, we still see customers in the U.S. that are still very much wanting to use the shiniest, new thing, like the very latest version of Spark or the very latest version of NyFy or some other technologies. They want to push and use that latest version. In Europe, now the conversations are slightly different, in terms of understanding the security and governance. I think there's a lot more consciousness, if you will, around data here. There's other rules and regulations that are coming into place. And I think they're a little bit more advanced in how they think of-- >> Yeah. >> Data, personal data, how to be treated, and so, consequently, those are where the conversations are about the platform. How do we secure it? How does it get governed? So that you need regulations-- >> John Furrier: It's not as fast, as loose as the U.S. >> Yeah, it's not as fast. And you look and see some of the regulations. (laughing) My wife asked me if we should set up a VPIN on our home WiFi because of this new rule about being able to sell the personal data. I've said, Well, we're not in the U.S., but perhaps, when we move to the U.S. >> In order to get the right to block chain (laughing). (cross-talk) >> Yeah, absolutely (cross-talk). >> John Furrier: Encrypt everything. >> (laughing) Yeah, exactly. >> Well, another topic is... Let's talk about the ecosystem a little bit. >> Umm-hmm. >> You've got now some additional public brethren, obviously Cloudera's, there's been a lot of talk here about-- >> Umm-hmm. Tow-len and Al-trex-is have gone public. >> Yeah. >> The ecosystem you've evolved that. IBM was up on stage with you guys. >> Yeah, yep. >> So that continues to be-- >> Gallium C. >> Can we talk about that a little bit? >> Gallium C >> Gallium C. >> We had a great... Partners are great. We've always been about the ecosystem. We were talking about before we came on-screen that for us it's not Marney Partnership. They're very much of substance, engineering to try to drive value for the customers. It's where we see that value in that joint value. So IBM is working with us across all of the DataWorks Summit, but, even in all of the engineering work that we're doing, participated in HDP 2.6 announcement that we just did. And I'm sure what you covered with Shawn and others, but those partnerships really help drive value for the customer. >> Umm-hmm. For us, it's all making sure the customer is successful. And to make a complete solution, it is a range of products, right. It is whether it's data warehousing, servers, networks, all of the different analytics, right. There's not one product that is the complete solution. It does take a stack, a multitude of technologies, to make somebody successful. >> Cloudera's S-1, was file, what's been part of the conversation, and we've been digging into, it's great to see the numbers. >> Umm-hmm. >> Anything surprise you in the S-1? And advice you'd give to open source companies looking to go public because, as Dave pointed out, there's a string now of comrades in arms, if you will, Mool-saw, that's doing very well. >> Yeah, yeah. >> And Al-trex-is just went public. >> Yeah. >> You guys have been public for a long time. You guys been operating the public open-- >> Yeah. >> Both open source, pure open source. But also on the public markets. You guys have experience. You got some scar tissue. >> John Kreisa: (laughing) Yeah, yeah. >> What's your advice to Cloudera or others that are... Because the risk certainly will be a rush for more public companies. >> Yeah. >> It's a fantastic trend. >> I think it is a fantastic trend. I completely agree. And I think that it shows the strength of the market. It shows both the big data market, in general, the analytics market, kind of all the different components that are represented in some of those IPOs or planned IPOs. I think that for us, we're always driving for success of the customer, and I think any of the open source companies, they have to look at their business plan and take it step-wise in approach, that keeps an eye on making the customer successful because that's ultimately what's going to drive the company success and drive revenue for it and continue to do it. But we welcome as many companies as possible to come into the public market because A: it just allows everybody to operate in an open and honest way, in terms of comparison and understanding how growth is. But B: it's shows that strength of how open source and related technologies can help-- >> Yeah. >> Drive things forward. >> And it's good for the customer, too, because now they can compare-- >> Yes! >> Apples to Apples-- >> Exactly. >> Visa V, Cloudera, and what's interesting is that they had such a head start on you guys, HORTONWORKS, but the numbers are almost identical. >> Umm-hmm, yeah. >> Really close. >> Yeah, I think it's indicative of the opportunity that they're now coming out and there's rumors of other companies coming out. And I think it's just gives that visibility. We welcome it, absolutely-- >> Yeah. >> To show because we're very proud of our performance and now are growth. And I think that's something that we stand behind and stand on top of. And we want to see others come out and show what they got. >> Let's talk about events, if we can? >> Yeah. >> We were there at the first Hadoop Summit in San Jose. Thrilled to be-- >> John Kreisa: In a few years. >> In Dublin last year. >> Yeah. >> So what's the event strategy? I love going into the local flavor. >> Umm-hmm. >> Last year we had the Irish singers. This year we had a great (laughing) locaL band. >> John Kreisa: (laughing) Yeah, yeah, yeah. >> So I don't know if you've announced where next year's going to be? Maybe you can share with us some of the roll-out strategies? >> Yeah, so first of all, DataWorks Summit is a great event as you guys know, And you guys are long participants, so it's a great partnership. We've moving them international, of course, we did a couple... We are already international, but moving a couple to Asia last year so-- >> Right. >> Those were a tremendous success, we actually exceeded our targets, in terms of how many people we thought would go. >> Dave: Where did you do those? >> We were in Melburn in Tokyo. >> Dave: That's right, yeah. >> Yeah, so in both places great community, kind of rushed to the event and kind of understanding, really showed that there is truly a global kind of data community around Hadoop and other related technologies. So from here as you guys know because you're going to be there, we're thinking about San Jose and really wanting to make sure that's a great event. It's already stacking up to be tremendous, call for papers is all done. And all that's announced so, even the sessions we're really starting build for that, We'll be later this year. We'll be in Sydney, so we're going to have to take DataWorks into Sydney, Australia, in September. So throughout the rest of this year, there's going to be continued building momentum and just really global participation in this community, which is great. >> Yeah. >> Yeah. >> Yeah, it's fantastic. >> Yeah, Sydney should be great. >> Yeah. >> Looking forward to it. We're going to expand theCUBE down under. Dave and I are are excited-- >> Dave: Yeah, let's talk about that. >> We got a lot of interest (laughing). >> Alright. >> John, great to have you-- >> Come on down. >> On theCUBE again. Great to see you. Congratulations, I'm going to see you up on stage. >> Thank you. >> Doing the emcee. Great show, a lot of great presenters and great customer testimonials. And as always the sessions are packed. And good learning, great community. >> Yeah. >> Congratulations on your ecosystem. This is theCUBE broadcasting live from Munich, Germany for DataWorks 2017, presented by HORTONWORKS and Yahoo. I'm John Furrier with Dave Vellante. Stay with us, great interviews on day two still up. Stay with us. (electronic music)

>> Male Announcer: Live from Las Vegas, it's theCUBE, covering InterConnect 2017. Brought to you by, IBM. >> Welcome back, we're live here in Las Vegas for IBM InterConnect 2017. This is theCUBE's coverage of InterConnect, I'm John Furrier with Dave Vellante my co-host. Our next guest is Deon Newman, CMO of IBM Watson IoT, and Slava Rubin, the founder and Chief Business Officer of Indiegogo, great keynote today, you're on stage. Welcome to theCUBE. Deon, great to see you. >> Thanks for having me. >> So I got to first set the context. Indiegogo, very successful crowd-funder, you guys pioneered. It's pretty obvious now looking back, this has created so much opportunity for people starting companies, whether it's a labor of love or growing into a great business, so congratulations on your success. What's the IBM connection? Because I don't want, you know, there was some stuff on the tweets, I don't want to break the news, but you guys are here. Share the connection. What's the packaging, why is IMB and Indigogo working together? >> Yeah, so back up to 2008. We launched to be able to get people access to funding. And over the last several years, we've done a pretty good job of that. Sending over a billion dollars to over half a million entrepreneurs around the world. And more recently, we've had a lot more requests of Indiegogo can you do more? And we knew that we couldn't do it all on our own. So we partnered first with Arrow to be able to bring these ideas more into reality around components and engineering and supply chain. And we knew we needed more in terms of these IoT products, so they need to be smart and they need software. So we were really excited to be able to announce today, the partnership with IBM, around everything IoT Cloud, security, and being able to provide all the block chain and any other elements that we need. >> Deon I want to ask you, get your thoughts on, we had the Watson data platform guys on earlier in the segment, and the composability is now the norm around data. This brings the hacker-maker culture to IoT. Which if you think about it as a sweet-spot for some of the innovations. They can start small and grow big. Is that part of the plan? >> Yeah, I mean, if you look at what's going on we have about 6000 clients already with us in the IoT space. They tend to be the big end of town, you know whether it be a Daimler or an Airbus or whether it be a Kone, the world's biggest elevator company. Or ISS, the world's biggest facilities management company. So we were doing a lot of work up there really around optimizing their operations, connecting products, wrapping services around them so they can create new revenue streams. But where we didn't have an offering that was being used extensively, was in the start-up space. And you know when we saw what Indiegogo had been doing in the marketplace, and when our partner Arrow, who as Slava has said, has really built up an engineering capability and a component capability to support these makers. It was just a match made in heaven. You know, for an entrepreneur who needs to find a way to capture data, make that data valuable, you know, we can do that. We have the Cloud platform, we have the AI, et cetera. >> It's interesting, we just hit the stride of dude, we have our big data Silicon Valley event just last week, and the big thing that come out of that event is finally the revelation, this is probably not new to Slava and what you're doing, it that, the production under-the-hood hard stuff that's being done is some ways stunting the creativity around some of the cooler stuff. Like whether it's data analytics or in this case, starting a company. So, Slava I want to get your thought on, your views on how the world is becoming democratized. Because if you think about the entrepreneurship trend that you're riding, is the democratization of invention. Alright, there's a democracy, this is the creative, it's the innovation, but yet it's all this hard stuff, like what's called production or under-the-hood that IBM's bringing in. What do you expect that to fuel up? What's your vision of this democratization culture? >> I mean, it's my favorite thing that's happening. I think whether it's YouTube democratizing access to content or Indiegogo democratizing access to capital. The idea of democratizing access to entrepreneurship between our partnership, just really makes me smile. I think that capital is just one of those first points and now they're starting to get the money but lots of other things are hard. When you can actually get artificial intelligence, get Cloud capabilities, get security capabilities, put it into a service so you don't need to figure all those things out on your own so you can go from a small little idea to actually start scaling pretty rapidly, that's super exciting. When you can be on Indiegogo and in four weeks get 30,000 backers of demand across 100 countries, and people are saying, we want this, you know it's good to know you don't need to start ramping up your own dev team to figure out how to create a Cloud on your own, or create your own AI, you can tap right into a server that's provided. Which is really revolutionizing how quickly a small company can scale. So it proliferates more entrepreneurs starting because they know there's more accessibility. Plus it improves their potential for success, which in the long run just means there's more swings at the bat to be able to have and entrepreneur succeed, which I think all of us want. >> Explain to the audience how it works a little bit. You got the global platform that you built up. Arrow brings it's resources and ideation. IBM brings the IoT, the cognitive platform. Talk about how that all comes together and how people take advantage of it? >> Sure, I mean you can look at it as one example, like Water Buy. So Water Buy is an actual sensor that you can deploy against your water system to be able to detect whether or not your water that you're drinking is healthy. You're getting real-time data across your system and for some reason it's telling you that you have issues, you can react accordingly. So that was an idea. You go on Indiegogo, they post that idea and they're able to get the world to start funding it. You get customer engagement. You get actual market validation. And you get funding. Well now you actually need to make these sensors, you need to make these products, so now you get the partnership with Arrow which is really helpful cause they're helping you with the engineering, the design, the components. Now you want to be able to figure out how you can store all that data. So it's not just your own house, maybe you're evaluating across an entire neighborhood. Or as a State you want to see how the water is for the whole entire State. You put all of that data up into the Cloud, you want to be able to analyze the data rapidly through AI, and similarly this is highly sensitive data so you want it to be secure. If Water Buy on their own, had to build out all of this infrastructure, we're talking about dozens, hundreds, who knows how many people they would need? But here through the partnership you get the benefit of Indiegogo to get the brilliant idea to actually get validated, Arrow to bring your idea from the back of a napkin into reality, and then you get IBM Watson to help with all the software components and Cloud that we just talked about. >> And how did this get started? How did you guys, you know, fall into this, and how did it manifest itself? >> So can I tell the story? >> Go for it. >> So I love this story, so as Slava's explained at the front end of this it was really a partnership of Arrow and Indiegogo that came out of the need of entrepreneurs to actually build their stuff. You know, you get it funded and then you say, oh boy, now I've got a bunch of orders how do I now make this stuff? And so Arrow had a capability of looking at the way you designed, you know looking at it deeply with their engineers, sourcing the components, putting it together, maybe white-boxing it even for you. So they put that together. Now, we're all seeing that IoT and the connective products are moving for disconnection, which is actually generating data and that data having value. And so Arrow didn't have that capability, we were great partners with Arrow, you know when we all looked at it, the need for AI coming into all these products, the need for security around the connection, the platform that could actually do that connection, we were a logical map here. So we're another set of components, not the physical. You know, we're the Cloud-based components and services that enable these connected devices. >> If you think about like the impact, and it's mind-boggling what the alternative is. You mentioned that the example you gave, they probably might have abandoned the project. So if you think about the scale of these opportunities what the alternative would have been without an Indiegogo, you probably have some anecdotal kind of feeling on this. But any thoughts on what data you can share around, do you have kind of reference point of, okay, we've funded all this and 90% wouldn't have been done or 70% wouldn't have been done. Do you have any flavor for? >> It's hard to know exactly. Obviously many of these folks that come to Indiegogo, if they could've gotten funded on another path earlier in the process, they would have. Indiegogo became really a great choice. Now you're seeing instead of being the last resort, Indiegogo is becoming the first resort because they're getting so much validation and market data. The incredible thing is not to think about it at scale when you think about 500 or 700 thousand entrepreneurs, or over a billion dollars, and it's in virtually every country in the world. If you really just look at it as one product. So like, Flow Hive is just one example. They've revolutionized how honey gets harvested. That product was bought in almost 170 countries around the world and it's something that hadn't been changed in over 150 years. And it's just so interesting to see that if it wasn't for Indiegogo that idea would not go from the back of a napkin to getting funded. And now through these partnerships they're able to realize so much more of their potential. >> So it's interesting, the machine learning piece is interesting to me because you take the seed-funding which is great product-market fit as they say in the entrepreneurial culture, is validated. So that's cool. But it could be in some cases, small amounts of cash before the next milestone. But if you think about the creativity impact that machine learning can give the entrepreneur, with through in their discovery process, early stage, that's an added benefit to the entrepreneur. >> Absolutely. Yeah, a great example there is against SmartPlate. SmartPlate is trying to use a combination of a weight-sensing plate as well with photo-detection, image detection software. The more data it can feed its image detection, the more qualified it can know, is that a strawberry or a cherry, or is that beef? And we take that for granted that our eyes can detect all that, but it's really remarkable to think about instead of having to journal everything by hand or make sure you pick with your finger what's the right product and how many ounces, you can take a photo of something and now you'll know what you're eating, how much you're eating and what is the food composition? And this all requires significant data, significant processing. >> I'm really pumped about that, congratulations to you on a great deal. I love the creativity and I think the impact to the globe is just phenomenal. Thinking about the game-changing things that are coming up, Slava I've got to ask you, and Deon if you could weigh in too, maybe you have some, your favorites. You're craziest thing that you've seen funded and the coolest thing you've seen funded. (laughter) >> I mean, who is hard because it's kind of like asking well who's your favorite child? I have like 700,000 children, I'm not even Wilt Chamberlain (laughter) and I like them all. But you know it's everything from an activity tracker to security devices, to being able to see what the trend is 24, 36 months ahead. Before things become mainstream today, we're seeing these things 3, 5 years ago. Things are showing up at CES, and you know these are things we get to see in advance. In terms of something crazy, it's not quite IoT but I remember when a young woman tried to raise $200,000 to be able to get enough money for her and Justin Bieber to fly to the moon. (laughter) >> That's crazy. >> That didn't quite get enough funding. But something that's fresh right now is Nimuno Loops is getting funded right now on Indiegogo live. And they just posted less than seven days ago and they have Lego-compatible tape. So it's something that you can tape onto any surface and the other side is actually Lego-compatible so you actually put Legos onto that tape. So imagine instead of only a flat surface to do Legos, you could do Legos on any surface even your jacket. It's not the most IoT-esque product right now but you just asked for something creative. >> That's the creative. >> I think once you got Wilt Chamberlain and Justin Bieber in the conversation, I'm out. (laughter) (crosstalk) >> Well now, how does Indiegogo sustain itself? Does it take a piece of the action? Does it have other funding mechanisms for? >> Yeah, and that's the beautiful thing about Indiegogo. It's a platform and it's all about supply and demand. So supply is the ideas and the entrepreneurs and the demand is the funders. It's totally free to use the website and as long as you're able to get money in your pocket, then we take a percentage. If you're not taking any money into your pocket, then we get no money. As part of the process, you might benefit from actually not receiving money. You might try to raise a hundred grand, only raise thirty-one and learn that your price-point is wrong, your target audience is wrong, your color is wrong, you're bottom cost it too high. All this feedback is super valuable. You just saved yourself a lot of pain. So really it's about building the marketplace we're a platform, we started out just with funding, we're really becoming now a springboard for entrepreneurs. We can't do it all ourselves which is why we're bringing on these great partners. >> You know we've done, just to add to that, I think it's a relevant part here too. We've actually announced a premium-based service for the entrepreneurs to get onto the Cloud, to access the AI, to access the services as a starting point to the complete premium model so they can get started very low barrier to entry and overseeing scale as they grow. >> What do you call that? Is it IBM IoT Premium or? >> It hasn't got a name specifically to the premium element of the, it's just the Watson IoT platform. Available on Blue Mist. >> So it's a Watson sort of, right. So it's like a community edition of Watson. So Deon, new chapter for you. You know I saw a good quarter for mainframes, last quarter. It's still drafting off your great work and now you've shifted to this whole new IoT role, what's that been like? Relatively new initiative for IBM, building on some historical expertise. But give us the update on your business. >> Yes, so about 15 months ago, we announced a global headquarters that we were going to open in Munich, and we announced the Watson IT business. Which brought together a lot of IBM's expertise and a lot of our experience over the years through smarter cities, through the smarter planet initiative. You know we've been working The Internet Of Things, but we made a 3-billion dollar commitment to that marketplace, that we were going to go big and go strong. We've built out a horizontal platform, the Watson IoT platform. On top of that we've got market-leading enterprise asset management software, the Maximo portfolio, TRIRIGA for facilities management. And then we have a whole set of engineering software for designing connected products as well. So we've built out a very comprehensive industry-vertical-aligned IoT business. We added last year, we went from about 4000 to about 6000 clients. So we had a very good year in terms of real enterprises getting real outcomes. We continue to bring out new industry solutions around both connected products and then operations like retail, manufacturing, building management, telco, transportation. We're building out solutions and use-cases to leverage all that software. So business is going well. We officially the Watson IoT headquarters three weeks ago in Munich. And we're jam packed with clients coming through that building, building with us. We've got a lot of clients who've actually taken space in the building. And their using it as a co-laboratory with us to work on PSE's and see the outcomes they can drive. >> Alright, Deon Newman with IoT Watson, and IoT platforms. Slava Rubin, founder of Indiegogo, collective intelligence is cultural shift happening. Congratulations outsourcing and using all that crowdfunding. It's real good data, not just getting the entrepreneur innovations funded but really using that data and your wheelhouse IoT. Thanks for joining us on theCUBE, appreciate it. >> Thank you John. >> More live coverage after this short break, with theCUBE live in Las Vegas for IBM InterConnect. We'll be right back, stay with us. (upbeat music)

>> Announcer: Live, from Las Vegas, it's theCUBE, covering InterConnect 2017, brought to you by IBM. >> OK, welcome back everyone, live here in Las Vegas for IBM InterConnect 2017. This is theCUBE's coverage of InterConnect. I'm John Furrier, Dave Vellante, my co-host. Our next guest is Deon Newman, CMO of IBM Watson IoT, and Slava Rubin, the founder and Chief Business Officer of Indiegogo. Great keynote today, you're on stage, welcome to theCUBE. Deon, great to see you. >> Thanks for havin' me. >> I got to first set the context. Indiegogo, very successful crowdfunder you guys pioneered. It's pretty obvious now, looking back, this creates so much opportunity for people starting companies, whether it's a labor of love or growing into a great business, so congratulations on your success. What's the IBM connection? Because there was some stuff on the tweets, I don't want to break the news, but you guys are here, share the connection. What's the packaging? Why is IBM and Indiegogo working together? >> Yes, so back up to 2008, we launched to be able to get people access to funding and over the last several years, we've done a pretty good job of that, sending over a billion dollars to over a half a million entrepreneurs around the world, and more recently, we've had a lot more requests of Indiegogo, can you do more? And we knew we couldn't do it all on our own, so we partnered first with Arrow, to be able to bring these ideas more into reality around components and engineering and supply chain, and we knew we needed more in terms of these IoT products, so they need to be smart and they need software, so we were really excited to be able to announce today the partnership with IBM, around everything IoT, clouds, security, and being able to provide all the block chain and any other elements that we need. >> Deon, I want to ask you or get your thoughts on, we have the Watson data platform guys on earlier in the segments, and the composability is now the normal around data, brings the hacker-maker culture to IoT, which, if you think about it, is a sweet spot for some of the innovations. They can start small and grow big. Is that part of the plan? >> I mean, if you look at what's going on, we have about 6,000 clients already working with us in the IoT space. They tend to be the big end of town, whether it be a Daimler or a Airbus, whether it be a KONE, the world's biggest elevator company, or ISS, the world's biggest facilities management company, so we were doin' a lot of work up there, really around optimizing their operations, connecting products, wrapping services around them so that they can create new revenue streams, but where we didn't have an offering that was being used extensively was in the start-ups place, and when we saw what Indiegogo had been doing in the marketplace, and when our partner, Arrow, who, as Slava said, has really built up an engineering capability and a component capability to support these makers, it was just a match made in heaven. For an entrepreneur who needs to find a way to capture data, make that data valuable, we can do that. We have the cloud platform, we have the AI, et cetera. >> It's interesting, we just had the Strata Hadoop, we have our own big data Silicon Valley event last week and the big thing that came out of that event, finally, the revelation, this is probably not new to Slava, what you're doin' is that the production under the hood hard stuff that's being done is, in some ways stunting the creativity around some of the cooler stuff, like whether it's data analytics, or in this case, the startin' a company, so, Slava, I want to get your thoughts on your views on how the world is becoming democratized, because if you think about the entrepreneurship trend that you're riding, there's a democratization of invention. This is the creative, it's the innovation, but yet, there's all this hard stuff, that's called, like, production, or under-the-hood, that IBM's bringin'. What do you expect that to feel up? What's your vision of this democratization culture? >> It's my favorite thing that's happening. I think, whether it's YouTube democratizing access to content, or Indiegogo democratizing access to capital, the idea of democratizing access to entrepreneurship between our partnership, just really makes me smile. I think that capital is just one of those first points and now they're starting to get the money, but lots of other things are hard. When you can actually get artificial intelligence, get cloud capabilities, get security capabilities, put it into a service, so you don't need to figure all those things out on your own, so you can go from a small little idea to actually start scaling pretty rapidly, that's super exciting. When you can be on Indiegogo, and in four weeks, get 30,000 backers of demand across 100 countries, and people are saying, "We want this," it's good to know that you don't need to start ramping up your own dev team to figure out how to create a cloud on your own, or create your own AI, you can tap right into a server that's provided, which has really revolutionizing how quickly a small company can scale, so it proliferates more entrepreneurs starting, 'cause they know there's more accessibility, plus it improves their potential for success, which in the long run, just means there's more swings at the bat to be able to have an entrepreneur succeed, which I think all of us want. >> Explain for the audience how it works a little bit. You got the global platform that you built out, Arrow brings its resources and ideation, IBM brings the IoT, the cognitive platform. Talk about how that all comes together and how people take advantage of it. >> Sure, I mean you can look at it as, one example like WaterBot. So WaterBot is an actual sensor that you can deploy against your water system to be able to detect whether or not your water that you're drinking is healthy. You're getting real-time data across your system and for some reason, it's telling you you have issues, you can react accordingly. So that was an idea. You go on Indiegogo, they post that idea, and they're able to get the world to start funding it. You get customer engagement, you get actual market validation, and you get funding. Well now you actually need to make these sensors, you need to make these products, so now you get the partnership with Arrow, which is really helpful, 'cause they're helping you with the engineering, the design, the components. Now you want to be able to figure out how you can store all that data, so it's not just your own house, maybe you're evaluating across an entire neighborhood, or as a state, you want to see how the water is for the whole entire state. You put all that data up into the cloud, you want to be able to analyze the data rapidly through AI, and similarly, this is highly sensitive data, so you want it to be secure. If WaterBot, on their own, had to build out all this infrastructure, we're talking about dozens, hundreds, who knows how many people they would need, but here, through the partnership, you get the benefit of Indiegogo to get the brilliant idea to actually get validated, Arrow, to bring your idea from back of the napkin into reality, and then you get IBM Watson to help with all of the software components and cloud that we just talked about. >> Great, and how did this get started? How did you guys fall into this and how did it manifest itself? >> Take it, I tell the story? >> Go for it. >> So, I love this story. So, Slava's explained that the front end of this, it was really a partnership of Arrow and Indiegogo that came out of the need of entrepreneurs to actually build their stuff. You know, you get it funded, and then you say, "Oh boy," now I've got a bunch of orders, how do I now make this stuff? And so, Arrow had a capability; of looking at the way you designed, looking deeply with their engineers, sourcing the components, putting together, maybe whiteboxing it even for you, and so, they put that together. Now, we'll all seeing that IoT and the connected products are moving for disconnection, it's actually generating data and that data having value. And so Arrow didn't have that capability, we were great partners with Arrow, you know, when we all looked at it, you know, the need for AI coming into all these products, the need for security around the connection platform, that can actually do that connection, we were a logical map here, so we're another set of components, not the physical. We're the cloud-based components and services that enable these connected devices to sync. >> If you think about the impact, it's mind-boggling with the alternative. You mentioned, the example you gave, they probably might have abandoned the project, so if you think about the scale of these opportunities, what the alternative would have been without an Indiegogo, you probably have some anecdotal feeling on this. Any thoughts on what data you can share, do you have any kind of reference point of like, OK, we funded all this and 90% wouldn't have been done, or 70% wouldn't have been done, do you have any flavor for what's... >> Hard to know exactly. Obviously, many of these folks that came to Indiegogo, if they could have gotten funded on another path, earlier in the process, they would have. Indiegogo became really a great choice. Now you're seeing, instead of being the last resort, Indiegogo's becoming the first resort because they're getting so much validation and market data. The incredible thing is not the thing that adds scale, when you think about 500 or 700,000 entrepreneurs or over a billion dollars and it's in virtually every country in the world, if you really just look at it as one product. So, like, Flow Hive is just one example. They've revolutionized how honey gets harvested. That product was bought in almost 170 countries around the world, and it's something that hasn't been changed in over 150 years, and it's just so interesting to see that, if it wasn't for Indiegogo, that idea would not go from the back of the napkin to getting funded, and now, through these partnerships, they're able to really realize so much more of their potential. >> So, it's interesting, the machine learning piece is interesting to me, because you take the seed funding, which is great, and product market fit as they say in the entrepreneurial culture, is validated, so that's cool, but it could be, in some cases, small amounts of cash before the next milestone, but if you think about the creativity impact that machine learning can give the entrepreneur. >> Slava: Right. >> On their discovery process, early stage, that's an added benefit to the entrepreneur. >> Absolutely. Yeah, a great example bears against SmartPlate. SmartPlate is trying to use the combination of weight sensing plate, as well with photo detection, image detection, and software. The more data it can feed its image detection, the more qualified it can know, "Is that a strawberry or a cherry or is that beef?" Right? And we take that for granted that our eyes can detect all that, but it's really remarkable to think about that instead of having to journal everything by hand or make sure you pick with your finger what's the right product, how many ounces, you can take a photo of something and now it'll know what you're eating, how much you're eating and what is the food composition? And this all requires significant data, significant processing. >> Well, I'm really pumped about that, congratulations, Deon, on a great deal. I love the creativity. I think the impact to the globe is just phenomenal. I mean, by what the game-changing things that are coming out. Slava, I got to ask you, and Deon, if you could weigh in, too, maybe you have some, your favorites, the craziest thing you've seen funded, and the coolest thing you've seen funded. >> Cool is hard, because it's kind of like asking, "Well, who's your favorite child?" I have like 700,000 children, not even Wilt Chamberlain, (laughing) and I like them all. But, you know, it's everything from an activity tracker to security devices, to be able to see what the trend is 24, 36 months ahead. Before things become mainstream today, we're seeing these things three, five years ago. Things are showing up at CES, and these are things we get to see in advance. In terms of something crazy, it's not quite IoT, but I remember when a young woman tried to raise $200,000 to be able to get enough money for her and Justin Bieber to fly to the moon. (laughter) >> That's crazy. >> That didn't get quite enough funding, but something's that flush right now is Nimuno Loops is getting funded right now on Indiegogo Live, and they just posted less than seven days ago and they have Lego-compatible tape, so it's something that you can tape onto any surface, and then the other side is actually Lego-compatible, so you're actually putting Legos onto that tape. So, imagine, instead of only a flat surface to do Legos, you could do Legos on any surfacing, even your jacket. It's not the most IoT-esque product right now, but you just asked for something creative, there you go. >> That's a creative. >> I think once you got Wilt Chamberlain and Justin Bieber in conversation, I am out. (laughter) >> Keepin' it fresh. (voices overlapping) >> Slava, how does Indiegogo sustain itself? Does it take a piece of the action? Does it have other funding mechanisms for... >> The beautiful thing about Indiegogo is, it's a platform and it's all about supply-and-demand, so supply is the ideas and the entrepreneurs, and demand is the funders. It's totally free to use the website and as long as you're able to get money in your pocket, then we take a percentage. If you're not taking any money into your pocket, then we get no money. As part of the process, you might benefit from actually not receiving money. You might try to raise 100 grand, only raise 31, and learn that your price point is wrong, your target audience is wrong, your color is wrong, your bond cost is too high. All this feedback is super value. You just saved yourself a lot of pain, so really it's about building the marketplace. We're a platform, we started out just with funding, we're really becoming now a springboard for entrepreneurs, we can't do it all ourselves, which is why we're bringing on these great partners. >> And you know, we've done, just to add to that, I think it's a relevant part here, too. We've actually announced a freemium-based service for the entrepreneurs to get onto the cloud access, the AI, or to access the services as a starting point, it's a complete freemium model, so that they can get started, very low barrier to entry and obviously, scale as they grow. >> What do you call that? Is it IBM IoT Freemium or is it? >> Hasn't been a name specifically to the Freemium element of it, it's what in IoT platform, available on Bluemix. >> So, it's like a community addition of lots of, so Deon, a new chapter for you, >> Yeah. >> I saw a good quarter for mainframes last quarter, still drafting off your great work, and now you've shifted to this whole new IoT role. What's that been like, relatively new initiative for IBM, building up on some historical expertise, but give us the update on your business. >> It's about 15 months ago, we announced a global headquarters that we're going to open in Munich and we announced the Watson IoT business, which brought together a lot of IBM's expertise and a lot of our experience over the years through Smarter Cities, through the Smarter Planet Initiative, we'd been working the Internet of Things. We'd made a three billion dollar commitment to that marketplace, though we were going to go big and go strong. We've built out a horizontal platform, the Watson IoT platform. On top of that, we've got market-leading enterprise SF management software, the Maximo portfolio, TRIRIGA for facilities management, and then we have a whole set of engineering software for designing connected products as well. So we've built out a very comprehensive industry, vertical-aligned IoT business. We added, last year, we went from about 4,000 to about 6,000 plants, so we had a very good year, in terms of real enterprises getting real outcomes. We continued to bring out new industry solutions around both connected products and then, operations like retail, manufacturing, building management, Tokyo, transportation. We're building out solutions and use-cases to leverage all that software, so business is going well, we officially opened the Watson IoT headquarters three weeks ago in Munich, and we're jampacked with clients coming through that building, building with us. We've got a lot of clients who've actually taken space in the building, and they're using the co-laboratory with us to work on PSEs and see the outcomes they can drive. >> Deon Newman, with Watson IoT platforms. Slava Rubin, founder of Indiegogo. Collective intelligence as cultural shift happening. Congratulations. Crowdsourcing and using all that crowdfunding. It's really good data, not just getting the entrepreneur innovations funded, but really using that data and way in your wheelhouse, IoT. >> Yeah. >> John: Thanks for joining us in theCUBE, appreciate it. More live coverage after this short break. It's theCUBE, live in Las Vegas, for IBM InterConnect. We'll be right back. Stay with us. (theCUBE jingle)