>> From Boston, Massachusetts, it's theCUBE, covering LiveWorx 18. Brought to you by PTC. >> Welcome back to Boston, everybody, to the LiveWorx show, hashtag LiveWorx with an "x" at the end. You're watching theCUBE, the leader in live-tech coverage. My name is Dave Vellante, and I'm with my co-host Stu Miniman. Mario Armstrong is here. He's a two-time Emmy winner, contributor to NBC today. He's the creator of the "Never Settle Show". He's an NPR contributor. >> Yep. >> And the host of LiveWorx. >> Yeah! >> Thanks so much coming on theCUBE. >> Yeah, it's a pleasure to see both of you. Good to see you too, Stu. Thanks for having me on the show. >> So yeah, this morning, a lot of action-- >> Yes. >> First of all, I tweeted out, that was like an Olympic opening, I mean-- >> That open was phenomenal. I mean, an LED-lit troop, full LED uniforms on, being acrobatic, what you can't see behind the scenes, by the way, 'cause you think it's kind of like Cirque du Soleil type of thing, with like, tech, but what you don't see are, like, these three other people that are way in the back behind the scenes, going up, scaling up and down like this truss that's like dropping them or raising them. It's just, the performance was phenomenal. >> Yeah, it was really great. And you kicked it off... 6,000 plus people here. >> Yes. >> You said the largest digital transformation conference on the planet, which of course, we were joking. Everybody says their digital-- >> Yeah. (laughs) >> But this really is digital transformation, isn't it? >> It's a lot that's taking place. I mean when you think about manufacturing, smart manufacturing, when you think about how you're trying to accelerate processes and you start looking at where things were like 20 or 30 years ago and how physical things had to be and how you actually had to, like, maybe even work on a thing then leave it, go to another place, report on it, come back to it, tweak it, and so now when you start seeing the merging of AI, VR, and so you're taking the physical and the human, and you're putting these... and the virtual, and you're putting these things together, you're seeing things like what PTC is showing us today. I mean, some of the demonstrations that I saw were absolutely mind blowing in terms of the acceleration of the process that you can actually get things done with how they're merging the different technologies and integrating them together. >> Yes, Stu and I, we're talking earlier, it's hard to get your head around this whole IOT, industrial IOT, there's just so many segments, it's so fragment that, and it's-- >> Yeah. >> It's enormous, it's almost impossible to size, I mean it's trillion dollars, this whole economy of its own. What are your takeaways on just that whole space? >> You know, a lot of what I focus on, too, when I'm doing everything from NBC or NPR and stuff like that is on the consumer impact. So I'm looking at the consumer side but I'm also an entrepreneur, so I'm thinking about what's happening on the business side. And when I see on both ends, you're absolutely right. The field is enormous when you really think about it. Whether you want to look at how we can replace old school manufacturing and how this is going to transfer... That's a whole sector just in it of itself. We haven't even now talked about, you know, AI for children or for (incoherent) or for the health and wellness sector, whole other sector that's looking at IOT and the power of that. I mean, being able to look at.. I was just in one of the other, in the deluxe lounge and I was checking out one of our fun games. It's called Sphero. It's a consumer game, but its a small ball that you control through VR and AR on your phone, but you can actually use the phone to program things in real time to make it respond in real time. So all of these things together, to me, start to paint this large ecosystem because now you have kids that are growing up using devices and using technologies that we're just starting to get our hands on but this is how they're solving problems and thinking about things already. So when this economy and this ecosystem starts to mature, you're going to have a ready-made audience that's already been exposed to 90% of this. >> Well, and Stu I wonder if you could chime into it, it makes me think that these worlds, even though consumer and industrial are so seemingly different, it seems like parts of them, anyway, adjacencies are coming together. >> Absolutely. And there's always going to be that... There's always going to be... Look, when I talk about innovation and whether you look at Dr. Hill, who's speaking here today, Dr. Linda Hill from Harvard and others, when I look at it, she calls it creative abrasion, like the difference between brainstorming and actually utilizing new ideas to create new concepts. I call it hybrid design. Normally, it's taking something that you know exists and then taking two things that don't seem to go together-- that's normally where you find creation. I don't like to say disruption, I like to say creation. >> Yeah, actually there's a good friend of mine that I work with and I worked at EMC, he called it venn diagram innovation. >> Oh, that's it! That's it! >> I take a few things and I put it together and we were talking about the consumer side-- >> Yeah! >> We've looked so many technologies, you get the scale usually from the consumer. When we look at things like flash in all of our devices-- >> That's right. >> Really enabled the enterprise to do things. The VR and AR is something that we've actually got some folks on the team that are heavy gamers that they're the ones that I go to when I want to learn, "Okay, what's the cutting-edge--" >> 'Cause they've already been in it. That's right. >> They're on their Steam, they're doing everything. >> That's right. >> They sort everything out. You leverage a lot of technology in how you really get your message out there. Talk a little about how you think of media these days. >> Oh, it's completely different. I mean, when we're looking at how media is even utilized in these new technologies, you know, our talk show is a talk show that we shoot in Nasdaq Studios, so it's shot in New York City, it's called the "Never Settle Show", it's a weekly one-hour live stream talk show, so we get and appreciate what you have to go through. These guys are pros by the way. (Dave and Stu laugh) Yeah, they're pros 'cause this is not easy to do. >> It's a minor miracle, right? Every time. >> (laughs) It's not easy to do at all. And so a lot of kudos to you and the team behind the scenes that make that happen. >> Thank you. >> With that being said, it's a great time if you have an expertise or if you have content to share especially in a live scenario because now you can start to really utilize other technologies within that. For example, we kind of claim ourselves to be one of the most interactive talk shows out there. What we do in our show is we're using other technologies, bringing them together to create real time conversations. So how that practically plays out is I'll have a guest on the show, we'll be talking, I'll put up a screen of three options and people can vote right then and there while they're watching in stream and you'll see which of what they want me to do next. I'll say something like, "Which thing is most appealing... Which topic do you want us to talk about next?" And they'll actually vote in real time and then the control room in everyone doesn't know what the answer's going to be, but we're all waiting for the answer and then when the popular vote comes out, few seconds later, we scramble and adjust to that. That's real time television, giving viewers what they really want in real time, using different technologies. So that's this hybrid approach. We can be a standard show and just do... talk and have that format, or we could really be looking at things that we could integrate in other technologies that would enhance the viewing experience and make it much more productive. >> Well you're actually affecting the, you call it "creation" as supposed to "disruption" of this new media industry, I mean, you've seen... I saw a stat the other day that cost the New York Times 200 million dollars to run a news desk. (Mario laughs) You're seeing, you know, billionaires buy up, you know, the Boston Globe, the Washington Post-- >> Yes, that's right. >> The industry is transforming in a huge way. You're seeing, you know, Facebook backlash with fake news. What's your senses as to what's going on in the media business? Obviously you're "creating", "disrupting", whatever you like to call it, sure. What do you see is the future of the media business? >> Well, I mean I think it's going to become something where the end reader, the end viewer has more control. Ultimately, that's... the problem with most systems and most structures is when people want to hold the control and not share because whether that's ego, whether they're worried about intellectual property loss, or whether they really think that the market's going to swallow them up.... Now I'm not saying, obviously you give away all your secret sauce, but what I am saying is when you start thinking from that small limiting position, you've already lost the game. And so what I think is going to happen, yes, you have big people buying a lot of media and there's a lot of discussion in politics about whether or not, you know, billionaires buying media are problems and what that's going to mean in terms of the message that's going to be reported to people, that's going to always be an issue, but I think even with that, that's why it's even more empowering that the individuals are taking more control over their own narrative. And that's why I think you've seen social media, Instagram video, Instagram talking about going to sixty minutes in it's video, not just a minute, for publishers, I think the power's now more in the person's hand to really pick and choose and so they vote with their eyeballs, they vote with their engagement, they vote with their interactivity. And so I think no matter what happens on the big end, people are going to be able to create and get the stories that they want to be able to get. >> Well we're big believers of that, Stu, and we're decentralized media and we really believe that there's got to be an incentive system to put the power back in the hands of the users to control their data. >> This is how it works. >> Right? I mean... >> Yeah. And, Mario, so we've talked about the tech and your show "Never Settle" actually won an Emmy for the interactivity nature of it? >> Yeah. It did. >> But talk to the people and passion, how that fits into "Never Settle". >> Yeah, so it's a blending. So what we try to do on our show is blend how you can leverage technology to move forward on your passion. But you can't use technology to move forward on your passion if you don't know what your passion is. So a lot of our discussions really work more around, "how do we get you to think differently"? How do we, you know... our vision for our company is to motivate people across the globe to never settle. How we do that through our mission is that we inspire the humans spirit, we want to teach lessons that matter and we want to uncover new perspectives. What that means, tangibly, is that when you watch our show, you should be having notes. You should be, like... our show is meant for you to want to take notes so that you actually know the process. What people are missing for the most part today is they see how to maybe start something or they see how someone else did and how they succeeded or how they failed, but they don't get the in between, the recipe. And so the more we can be sharing about the process about someone's success or, even better, someone's failure, 'cause that's where you learn more and you get more uncomfortable, makes you more comfortable, it's a blending of those two things of getting your mental position and getting you stronger mentally and building up your resilience so that you can actually go find your purpose, be happier in your life, but then use technology to accelerate. Like, that's the, as Jim put, like, you know, put gasoline and make it fast or make it go quicker. And so I think the blending of the two, again, a hybrid... Even how we approach our content is that. So we'll have everyone from tech luminaries on the show but also we'll just have everyday folks that have really proven success, like these people deserve attention but they're not maybe, quote on quote, big-names. >> And this idea of combinatorial innovation, you certainly heard Jim Heppelmann talking about that today with machines that are powerful and computers that are fast and can do things repetitively and then humans, which are creative. I like that theme. >> You can't do it any other way, I mean, this is why, you know, it's determination and direction. Your team needs to be determined but also have the direction. You need to have what I call the three P's. You need to have your passion in place. Like, what are you ultimately passionate about as a team? As an organization? What are you driving towards? What's your "why"? And then once you have that, then you can start to really push through on the perseverance. You're going to bump your head. You're going to fail fast. A great tech term, I love flipping that tech term because we learn in programming to fail to quick so that we can find the bugs fast and correct our course really quick. So that persistence happens. And then, the hardest part is you got to have some patience. Because then you have to kind of sit back. Let the market also play. Let the universe come around. Sometimes we're ahead. Sometimes we're behind. But we need to have a little bit of that patience to have some reflection to see where we are, so I think, you know, now is really just a great time for a lot of people that are looking to really figure out where they can make their moves... the opportunities that keep creating themselves in IOT are endless. I don't care if you're talking from someone that's a graphic designer all the way up to an engineer or a coder, to marketing and sales, like there's so many different facets of this ecosystem and opportunity now. >> I love that, Mario. Patient, passion, persistence, patience-- >> Yes. >> The three P's kind of start with why, the old-- >> Yeah. Simon Sinek. That's right. >> People don't buy what you do. They buy why you do it. >> That's right. >> Break stuff. >> (laughs) Love that. Break stuff. >> And don't give up. Don't give up. (Mario laughs) >> No, it's, you know... it's because what we're trying to do, if you really wanted to have action, you want to take complex things and you want to pull them together in a hybrid scenario and start to bang upon them. As opposed to the other idea of planning, planning, planning, planning, you actually want to practice, practice, practice, practice. That's what's going to get you there fast. So I just think that with a lot of the technologies it can be overwhelming to people 'cause they start to hear so much so that's why I say it comes back to, "What's your purpose?" If you can stay focused on why you're doing what it is you're doing, you'll know which technologies to pay more attention to. You'll know where your curiosity should veer more into. You'll study the things that you need to really study. And then you'll accelerate faster because you've identified your niche. It's like having a, you know, an Italian restaurant. You're not just, you know... somebody's going to come by and present to you... Some sales rep is going to come by and present to you, like, beer that's not a fit for like Italian restaurant, you know, like, I know that's not for me instantly. As opposed to being pulled in so many directions, which is what the danger of all this technology can do, is it can overwhelm us and pull us into so many directions that we want to go and pursue the hottest new trend or the hot thing. If we come back to our "why", we're always going to be secure. >> That's a great point, I mean there are an infinite opportunities of purposes in this world. >> Yes. >> It's sometimes hard to get a grasp on things and really focus. But you're seeing some of this successful projects really do start with a main spring and a focus and a purpose. >> Yeah. >> And a mission. >> It does. I mean, that's where it all becomes. I mean, it has to start there in order to get other people on board with your dream, whether you're the leader of the organization or the leader of a project. And, you know, I just feel that for many people, they are at an age where they have been in this business for quite some time. They've seen a lot of things evolve. Accepting change and, like Jim had said today, preparing to change is one of the best keys of information that you can take away because we all have the skill, the talent, the ability, it's just a matter or not, are we willing to adjust or are we... do we want to do status quo. >> Awesome. Hey, you're a clear thinker, articulate, you look great. Thanks so much for coming to theCUBE. >> (laughs) Aw man, Dave and Stu, it's been a pleasure. Thank you so much for having me on theCUBE. >> Our pleasure. >> This has been awesome. >> Alright, keep it right there, buddy, we'll be back from LiveWorx with our next guest right after this short break. You're watching theCUBE. We'll be right back.

>> From Boston Massachusetts, it's The Cube! Covering LiveWorx 18. Brought to you by PTC. >> Welcome to Boston everybody. You're watching The Cube, the leader in live tech coverage. And we're here with a special presentation in coverage of the LiveWorx show sponsored by PTC of Needham, soon to be of Boston. My name is Dave Vellante. I'm here with my co-host Stu Miniman. And Stu, this is quite a show. There's 6,000 people here. Jim Heppelmann this morning was up giving the keynote. PTC is a company that kind of hit the doldrums in the early 2000s. A company that as manufacturing moved offshore, its core business was CAD software for manufacturers, and it went through a pretty dramatic transformation that we're going to be talking about today. Well, fast forward 10 years, 12 years, 15 years on, this company is smokin, the stock's up 50 percent this year. They got a billion dollars plus in revenue. They're growing at 10 to 15 percent a year. They've shifted their software business from a perpetual software license to a recurring revenue model. And they're booming. And we're here at the original site of The Cube, as you remember well in 2010, the Boston Convention Center down at the seaport. And Stu, what are your initial impressions of LiveWorx? >> Yeah, it's great to be here, Dave. Good to be here with you and they dub this the largest digital transformation conference in the world. (laughing) So, I mean, Dave, you and I have been to much bigger conferences and we've been to a lot of conferences that are talking about digital transformation. But, IOT, AI, Augmented Reality, Block Chain, Robotics, all of these things really are about software, it's about digital transformation, and a really interesting space as you mentioned kind of the legacy of PTC. I have been around long enough. I remember when we used to call them Parametric Technologies. They kind of rebranded themselves as PTC. Windchill brings back some memories for me. When I worked for a high tech manufacturing company, it was that's the life cycle management tool that we used back in the early 2000s. So, I had a little bit of background in them. And, as you said, they're based in Needham, and they're moving to the Seaport. Hot area, especially, as we've said Dave, Boston has the opportunity to be the hub of IOT. And it's companies like PTC that are going to help bring those partnerships and lots of companies to an event like this. >> Well PTC has always been an inquisitive company, as you were pointing out to me off camera. They brought Prime Computer, Computer Vision. A number of acquisitions that they made back in the late 90s, which essentially didn't pan out the way they had hoped. But now again, fast forward to the modern era, Jim Heppelmann came in I think around 2010, exceeded ThingWorx, a company called Cold Light, Kept Ware is another company that they purchased. And took these really sort of independent software components and put them together and created a platform. Everybody talks about platform. We'll be talking about that a lot today, where the number of customers and partners of PTC. And we even have some folks from PTC on. But, basically, talking about digital transformation earlier, Stu, IOT is a huge tailwind for a company like PTC. But they had to really deliberately pivot to take advantage of this market. And if you think about it, yes, it's about connecting and instrumenting devices and machines, it's about reaching them, creating whatever wireless connections. But it's also about the data. We talk about that all the time. And constructing data that goes from edge to core, and even into the cloud, whether that cloud's on prem or in the data center. So you're seeing the transformation of this company. Obviously, I talked about some of the financials. We'll go into some of that. But an evolving ecosystem we heard Accenture's here, Infosys is here, Deloitte is here. As I like to say, the SI's like to eat at the trough. If the SI's are here, that means there's money here, right? >> Yeah Dave and actually a number that jumped out at me when Microsoft was up on stage, and it wasn't that Microsoft is investing five billion dollars in diode, the number that caught my ear was the 20 to 25 partners that it takes to deploy a single IOT solution. So, anybody that's been in tech for a long time, when you see these complicated stack solutions, the SIs need to be here. It takes a long time to work through them, and integration is a big challenge. How do I get all of these pieces together? It's not something that I just tit buy off the shelf. It's not shrink wrap software. This is complicated solution. It is very fragmented in how we make them up. Very specific to the industry that we're building, so really fascinating stuff that's going on. But we are still very early in the life-cycle of IOT. Huge, huge, huge opportunities but big players like Microsoft, like Google, like Amazon are going to be here making sure that they're going to simplify that environment over time. Huge, you know Dave, what's the original forecast I think we did at Wiki Bon, was a 1.2 trillion dollar opportunity, which most of that, that was actually for the industrial Internet, which is not the commercial things that we think about all the time, when we talk about the home sensors and some of the things, some of the consumer stuff, but also the industrial here. >> Well, I think a couple of key points that you're making here. First of all, the market is absolutely enormous. It's almost impossible to size. I mean you're talking about a trillion dollars in sort of spending on hardware, software, services, virtually everything. But to your point, Stu. It's highly highly fragmented, virtually every industry. And a lot of different segmented technologies. But it's also important to point out this is the mashing together of operations technology, OT with Information Technology, IT, and those four leading companies IT is actually leaning in and embracing this notion of edge, computing, and IOT. Now, I wouldn't even say that IT and OT are Hatfield and McCoy's. They're not. They're parts of the organization that don't talk to each other. So they are cultural differences. They use different languages. They think differently. One is largely engineers who make machines work. The other IT guys, which we obviously know what they do, they keep information technology systems running. They deploy a lot of new IT projects. So, really different worlds that have to start coming together. Jim Heppelmann today I thought did a really good job in his keynote. He talked about innovation. Usually you start with okay we're here at point A, we want to go here. We want to get to point B. And we're going to take a straight line and have a bunch of linear steps and milestones to get there. He pointed out that innovation today is really sort of a non-linear process. And he talked about the combinatorial effects of really three things. Machines, or the physical, computers and humans. Machines are strong, they can do heavy lifting. Computers are fast, and they can do repetitive tasks very accurately. And humans are creative. And he talked about innovation in this new world coming together by combining those three aspects, finding new ways to attack problems, to solve nature's challenges. And bringing nature into that problem solving. He gave a lot of examples of how mother nature mimicking mother nature is now possible with AI and other technologies. Pretty cool. >> Yeah, absolutely Dave. I'm sure we'll be talking a lot today about the fourth Industrial Revolution. A lot of discussion as to what jobs are Robots going to take. I look around the show floor here and there's a lot of cool robotics going on. But as Eric Manou said and Aaron McAfee, the folks from MIT that we've interviewed a couple of times talked about the second machine age. Really the marring of people and machines that are going to be powerful. And absolutely Jim Heppelmann talked about that a lot. It's humans, it's physical, and it's digital. Putting those together and then, the other thing that he talked about is we're talking a lot about voice lightly with all of these assistants, but, you're really limited as to how much input and how fast you can take information in from an auditory standpoint. I mean, I know that I listen to podcasts at 1.5 to 2 X to try to get more information in faster, but it is sight that we're going to get 80 percent of the information in, and therefore, it's the VR and AR that are huge opportunities. I know when I've been talking to some of the large manufacturers, what they used to have in written documentations and then they went digital with, they're now getting you inside to be able to configure the systems with the hollow lens, or some of the AR headsets, the VR headsets, to be able to play with that. So, we're really early but excited to see where this technology has come so far. >> Yeah, we're seeing a lot of practical applications of VR and AR. We go to a lot of these shows and they'll have the demos, and you go, okay, what will I do with this? Well, you're really seeing here at LiveWorx some of the things you actually can do. One good example I thought they did was BEA Systems up in Nashua, actually showing the folks that are doing the manufacturing, little tutorial in how to do that. We're going to see some surgical examples today. Remote surgery. There are thousands, literally thousands of examples. In the time we have remaining, I want to just do the rundown on PTC. Cause it really is quite an amazing transformation story. You're talking about a company with 1.1 billion dollars in revenue. Their aspiration is by 2021 to be a two billion dollar company. They're growing at ten percent a year, their software business has grown at 12 to 15 percent a year. 15 percent is that annual recurring revenue. So this is an example of a company that has successfully shifted from that perpetual model to that recurring model. They got 200 million dollars this year in free cash flow. Their stock, as I said, is up 50 percent this year. They got 350 million dollars in cash, but they just got a billion dollar investment from Rockwell Automation that took about 8.4 percent of the company given them an implied evaluation of almost 11 billion dollars, which has got a little uplift from the stock market there. They're selling a lot of seven figure deals. Really, the core is manufacturing product life-cycle management, CAD. That's the stuff that we know PTC well from. And I talked about some of those acquisitions that they made. They sell products like Creo, which is their 3D CAD software. I think they're on Rev five or six by now. So they've taken their sort of legacy software and sort of updated that for the digital world. >> Yep ,it is version five that they were just announced today. Talking about really the 3D effort they're doing there. Some partnerships around it, and like every other software Dave that we've been hearing about AI is getting infused in here because with so many devices and so much data, we really need the machines to help us process that and do things that humans can't keep up with. >> And the ecosystem's grown. This is a complicated marketplace. If you look at the Gartner Magic Quadrant, there is no leader, even though PTC is the leader. But there is no leader. They're all sort of in the lower right, PTC is up highest. GE is interestingly is not in there, because it doesn't have an on prem solution. I don't know why GE doesn't have an on prem solution. And I don't know why they're not in there. >> Is there another version of the magic quadrant that includes the Amazons and GEs of the world? >> I don't know. So that's kind of interesting. We'll try to unpack that as we go on here. PTC announced today a relationship with a company called Ansys, which does simulation software. Normally, simulation comes sort of after the design. They're bringing those two worlds together. The CAD design piece and the simulation piece, sort of closer to real time. So, there's a lot of stuff going on. As you said, it's data, analytics, edge computing. It's cloud, it's on prim, it's block chain for security. We haven't talked about security. A lot bigger threat metrix, so block chain comes into play. >> Yeah, Dave. I saw a great joke. Do you realize that the S in IOT stands for security? Did you know that? (laughing) Oh wait, there's no S in IOT. Well, that's the point. >> All right, good. So Stu and I will be here all day today. This is actually a three day conference. The Cube will only be there for day one. Keep right there everybody. And we'll be right back. You're watching The Cube, Live from Liveworx in Boston. (upbeat music)

>> Announcer: Live, from Orlando, Florida, it's TheCUBE, covering PentahoWorld 2017. Brought to you by Hitachi Vantara. >> Welcome back to sunny Orlando everybody. This is TheCUBE, the leader in live tech coverage. My name is Dave Vellante and this is PentahoWorld, #PWorld17. Don DeLoach here, he's the co-chair of the midwest IoT council. Thanks so much for coming on TheCUBE. >> Good to be here. >> So you've just written a new book. I got it right in my hot off the presses in my hands. The Future of IoT, leveraging the shift to a data-centric world. Can you see that okay? Alright, great, how's that, you got that? Well congratulations on getting the book done. >> Thanks. >> It's like, the closest a male can come to having a baby, I guess. But, so, it's fantastic. Let's start with sort of the premise of the book. What, why'd you write it? >> Sure, I'll give you the short version, 'cause that in and of itself could go on forever. I'm a data guy by background. And for the last five or six years, I've really been passionate about IoT. And the two converged with a focus on data, but it was kind of ahead of where most people in IoT were, because they were mostly focused on sensor technology and communications, and to a limited extent, the workflow. So I kind of developed this thesis around where I thought the market was going to go. And I would have this conversation over and over and over, but it wasn't really sticking and so I decided maybe I should write a book to talk about it and it took me forever to write the book 'cause fundamentally I didn't know what I was doing. Fortunately, I was able to eventually bring on a couple of co-authors and collectively we were able to get the book written and we published it in May of this year. >> And give us the premise, how would you summarize? >> So the central thesis of the book is that the market is going to shift from a focus on IoT enabled products like a smart refrigerator or a low-fat fryer or a turbine in a factory or a power plant or whatever. It's going to shift from the IoT enabled products to the IoT enabled enterprise. If you look at the Harvard Business Review article that Jim Heppelmann and Michael Porter did in 2014, they talked about the progression from products to smart products to smart, connected products, to product systems, to system of systems. We've largely been focused on smart, connected products, or as I would call IoT enabled products. And most of the technology vendors have focused their efforts on helping the lighting vendor or the refrigerator vendor or whatever IoT enable their product. But when that moves to mass adoption of IoT, if you're the CIO or the CEO of SeaLand or Disney or Walmart or whatever, you're not going to want to be a company that has 100,000 IoT enabled products. You're going to want to be an IoT enabled company. And the difference is really all around data primacy and how that data is treated. So, right now, most of the data goes from the IoT enabled product to the product provider. And they tell you what data you can get. But that, if you look at the progression, it's almost mathematically impossible that that is sustainable because company, organizations are going to want to take my, like let's just say we're talking about a fast food restaurant. They're going to want to take the data from the low-fat fryer and the data from the refrigerator or the shake machine or the lighting system or whatever, and they're going to want to look at it in the context of the other data. And they're going to also want to combine it with their point-of-sale or crew scheduling, or inventory and then if they're smart, they'll start to even pull in external data, like pedestrian traffic or street traffic or microweather or whatever, and they'll create a much richer signature. And then, it comes down to governance, where I want to create this enriched data set, and then propagate it to the right constituent in the right time in the right way. So you still give the product provider back the data that they want, and there's nothing that precludes you from doing that. And you give the low-fat fryer provider the data that they want, but you give your regional and corporate offices a different view of the same data, and you give the FDA or your supply chain partner, it's still the same atomic data, but what you're doing is you're separating the creation of the data from the consumption of the data, and that's where you gain maximum leverage, and that's really the thesis of the book. >> It's data, great summary by the way, so it's data in context, and the context of the low-fat fryer is going to be different than the workflow within that retail operation. >> Yeah, that's right and again, this is where, the product providers have initially kind of pushed back because they feel like they have stickiness and loyalty that's bred out of that link. But, first of all, that's going to change. So if you're Walmart or a major concern and you say, "I'm going to do a lighting RFP," and there's 10 vendors that say, "Hey, we want to compete for this," and six of 'em will allow Walmart to control the data, and four say, "No, we have to control the data," their list just went to six. They're just not going to put up with that. >> Dave: Period, the end, absolutely. >> That's right. So if the product providers are smart, they're going to get ahead of this and say, "Look, I get where the market's going. "We're going to need to give you control of the data, "but I'm going to ask for a contract that says "I'm going to get the data I'm already getting, "'cause I need to get that, and you want me to get that. "But number two, I'm going to recognize that "they can give, Walmart can give me my data back, "but enrich it and contextualize it "so I get better data back." So everybody can win, but it's all about the right architecture. >> Well and the product guys going to have the Trojan horse strategy of getting in when nobody was really looking. >> Don: That's right. >> And okay, so they've got there. Do you envision, Don, a point at which the Walmart might say, "No, that's our data "and you don't get it." >> Um, not really- >> or is there going to be a quid pro quo? >> and here's why. The argument that the product providers have made all along is, almost in a condescending way sometimes, although not intentionally condescending, it's been, look, we're selling you this low-fat fryer for your fast food restaurant. And you say you want the data, but you know, we had a team of people who are experts in this. Leave that to us, we'll analyze the data and we'll give you back what you need. Now, there's some truth to the fact that they should know their products better than anybody, and if I'm the fast food chain, I want them to get that data so that they can continually analyze and help me do my job better. They just don't have to get that data at my expense. There are ways to cooperatively work this, but again, it comes back to just the right architecture. So what we call the first receiver is in essence, setting up an abstraction close to the point of the ingestion of all this data. Upon which it's cleansed, enriched, and then propagated again to the right constituent in the right time in the right way. And by the way, I would add, with the right security considerations, and with the right data privacy considerations, 'cause like, if you look around the market now, things like GEP are in Europe and what we've seen in the US just in the wake of the elections and everything around how data is treated, privacy concerns are going to be huge. So if you don't know how to treat the data in the context of how it needs to be leveraged, you're going to lose that leverage of the data. >> Well, plus the widget guys are going to say "Look, we have to do predictive maintenance "on those devices and you want us to do that." You know, they say follow the money. Let's follow the data. So, what's the data flow look like in your mind? You got these edge devices. >> Yep, physical or virtual. Doesn't have to be a physical edge. Although, in a lot of cases, there are good reasons why you'd want a physical edge, but there's nothing technologically that says you have to have a physical edge. >> Elaborate on that, would you? What do you mean by virtual? >> Sure, so let's say I have a server inside a retail outfit. And it's collecting all of my IoT data and consolidating it and persisting it into a data store and then propagating it to a variety of constituents. That would be creating the first receiver in the physical edge. There's nothing that says that that edge device can't grab that data, but then persist it in a distributed Amazon cloud instance, or a Rackspace instance or whatever. It doesn't actually need to be persisted physically on the edge, but there's no reason it can't either. >> Okay, now I understand that now. So the guys at Wikibon, which is a sort of sister company to TheCUBE, have envisioned this three tiered data model where you've got the devices at the edge where real-time activity's going on, real-time analytics, and then you've got this sort of aggregation point, I guess call it a gateway. And then you've got, and that's as I say, aggregation of all these edge devices. And then you've got the cloud where the heavy modeling is done. It could be your private cloud or your public cloud. So does that three tier model make sense to you? >> Yeah, so what you're describing as the first tier is actually the sensor layer. The gateway layer that you're describing, in the book would be characterized as the first receiver. It's basically an edge tier that is augmented to persist and enrich the data and then apply the proper governance to it. But what I would argue is, in reality, I mean, your reference architecture is spot-on. But if you actually take that one step further, it's actually an n-tier architecture. Because there's no reason why the data doesn't go from the ten franchise stores, to the regional headquarters, to the country headquarters, to the corporate headquarters, and every step along the way, including the edge, you're going to see certain types of analytics and computational work done. I'll put a plug for my friends at Hitachi Lumada in on this, you know, there's like 700 horizontal IoT platforms out there. There aren't going to be 700 winners. There's going to be probably eight to 10, and that's only because the different specific verticals will provide for more winners than it would be if it was just one like a search engine. But, the winners are going to have to have an extensible architecture that is, will ultimately allow enterprises to do the very things I'm talking about doing. And so there are a number out there, but one of the things, and Rob Tiffany, who's the CTO of Lumada, I think has a really good handle on his team on an architecture that is really plausible for accomplishing this as the market migrates into the future. >> And that architecture's got to be very flexible, not just elastic, but sometimes we use the word plastic, plasticity, being able to go in any direction. >> Well, sure, up to and including the use of digital twins and avatars and the logic that goes along with that and the ability to spin something up and spin something down gives you that flexibility that you as an enterprise, especially the larger the enterprise, the more important that becomes, need. >> How much of the data, Don, at that edge do you think will be persisted, two part question? It's not all going to be persisted, is it? Isn't that too expensive? Is it necessary to persist all of that data? >> Well, no. So this is where, you'll hear the notion of data exhaust. What that really means is, let's just say I'm instrumenting every room in this hotel and each room has six different sensors in it and I'm taking a reading once a second. The ratio of inconsequential to consequential data is probably going to be over 99 to one. So it doesn't really make sense to persist that data and it sure as hell doesn't make sense to take that data and push it into a cloud where I spend more to reduce the value of the payload. That's just dumb. But what will happen is that, there are two things, one, I think people will see the value in locally persisting the data that has value, the consequential data, and doing that in a way that's stored at least for some period of time so you can run the type of edge analytics that might benefit from having that persisted store. The other thing that I think will happen, and this is, I don't talk much, I talk a little bit about it in the book, but there's this whole notion where when we get to the volumes of data that we really talk about where IoT will go by like 2025, it's going to push the physical limitations of how we can accommodate that. So people will begin to use techniques like developing statistical metadata models that are a highly accurate metadata representation of the entirety of the data set, but probably in about one percent of the space that's queryable and suitable for machine learning where it's going to enable you to do what you just physically couldn't do before. So that's a little bit into the future, but there are people doing some fabulous work on that right now and that'll creep into the overall lexicon over time. >> Is that a lightweight digital twin that gives you substantially the same insight? >> It could augment the digital twin in ways that allow you to stand up digital twins where you might not be able to before. The thing that, the example that most people would know about are, like in the Apache ecosystem, there are toolsets like SnappyData that are basically doing approximation, but they're doing it via sampling. And that is a step in that direction, but what you're looking for is very high value approximation that doesn't lose the outlier. So like in IoT, one of the things you normally are looking for is where am I going to pick up on anomalous behavior? Well if I'm using a sample set, and I'm only taking 15%, I by definition am going to lose a lot of that anomalous behavior. So it has to be a holistic representation of the data, but what happens is that that data is transformed into statistics that can be queryable as if it was the atomic data set, but what you're getting is a very high value approximation in a fraction of the space and time and resources. >> Ok, but that's not sampling. >> No, it's statistical metadata. There are, there's a, my last company had developed a thing that we called approximate query, and it was based on that exact set of patents around the formation of a statistical metadata model. It just so happens it's absolutely suited for where IoT is going. It's kind of, IoT isn't really there yet. People are still trying to figure out the edge in its most basic forms, but the sheer weight of the data and the progression of the market is going to force people to be innovative in how they look at some of these things. Just like, if you look at things like privacy, right now, people think in terms of anonymization. And that's, basically, I'm going to de-link data contextually where I'm going to effectively lose the linkages to the context in order to conform with data privacy. But there are techniques, like if you look at GDCAR, their techniques, within certain safe harbors, that allow you to pseudonymize the data where you can actually relink it under certain conditions. And there are some smart people out there solving these problems. That's where the market's going to go, it's just going to get there over time. And what I would also add to this equation is, at the end of the day, right now, the concepts that are in the book about the first receiver and the create, the abstraction of the creation of the data from the consumption of the data, look, it's a pretty basic thing, but it's the type of shift that is going to be required for enterprises to truly leverage the data. The things about statistical metadata and pseudonymization, pseudonymization will come before the statistical metadata. But the market forces are going to drive more and more into those areas, but you got to walk before you run. Right now, most people still have silos, which is interesting, because when you think about the whole notion of the internet of things, it infers that it's this exploitation of understanding the state of physical assets in a very broad based environment. And yet, the funny thing is, most IoT devices are silos that emulate M2M, sort of peer to peer networks just using the internet as a communication vehicle. But that'll change. >> Right, and that's really again, back to the premise of the book. We're going from these individual products, where all the data is locked into the product silo, to this digital fabric, that is an enterprise context, not a product context. >> That's right and if you go to the toolsets that Pentaho offers, the analytic toolsets. Let's just say, now that I've got this rich data set, assuming I'm following basic architectural principles so that I can leverage the maximum amount of data, that now gives me the ability to use these type of toolsets to do far better operational analytics to know what's going on, far better forensic analysis and investigative analytics to mine through the date and do root cause analysis, far better predictive analytics and prescriptive analytics to figure out what will go on, and ultimately feed the machine learning algorithms ultimately to get to in essence, the living organism, the adaptive systems that are continuously changing and adapting to circumstances. That's kind of the Holy Grail. >> You mentioned Hitachi Vantara before. I'm curious what your thoughts are on the Hitachi, you know, two years ago, we saw the acquisition, said, okay, now what? And you know, on paper it sounded good, and now it starts to come together, it starts to make more sense. You know, storage is going to the cloud. HDS says, alright, well we got this Hitachi relationship. But what do you make of that? How do you assess it, and where do you see it going? >> First of all, I actually think the moves that they've done are good. And I would not say that if I didn't think it. I'd just find a politically correct way not to say that. But I do think it's good. So they created the Hitachi Insight Group about a year and a half ago, and now that's been folded into Hitachin Vantara, alongside HDS and Pentaho and I think that it's a fairly logical set of elements coming together. I think they're going down the right path. In full disclosure, I worked for Hitachi Data Systems from '91 til '94, so it's not like I'm a recent employee of them, it's 25 years ago, but my experience with Hitachi corporate and the way they approach things has been unlike a lot of really super large companies, who may be super large, but may not be the best engineers, or may not always get everything done so well, Hitachi's a really formidable organization. And I think what they're doing with Pentaho and HDS and the Insight Group and specifically Lumada, is well thought out and I'm optimistic about where they're going. And by the way, they won't be the only winner in the equation. There's going to be eight or nine different key players, but they'll, I would not short them whatsoever. I have high hopes for them. >> The TAM is enormous. Normally, Hitachi eventually gets to where it wants to go. It's a very thoughtful company. I've been watching them for 30 years. But to a lot of people, the Pentaho and the Insight's play make a lot of sense, and then HDS, you used to work for HDS, lot of infrastructure still, lot of hardware, but a relationship with Hitachi Limited, that is quite strong, where do you see that fit, that third piece of the stool? >> So, this is where there's a few companies that have unique advantages, with Hitachi being one of them. Because if you think about IoT, IoT is the intersection of information technology and operational technology. So it's one thing to say, "I know how to build a database." or "I can build machine learning algorithms," or whatever. It's another thing to say, "I know how to build trains "or CAT scans or smart city lighting systems." And the domain expertise married with the technology delivers a set of capabilities that you can't match without that domain expertise. And, I mean, if you even just reduce it down to artificial intelligence and machine learning, you get an expert ML or AI guy, and they're only as good as the limits of their domain expertise. So that's why, and again, that's why I go back to the comparison to search engines, where there's going to be like, there's Google and maybe Yahoo. There's probably going to be more platform winners because the vertical expertise is going to be very, very important, but there's not going to be 700 of 'em. But Hitachi has an advantage that they bring to the table, 'cause they have very deep roots in energy, in medical equipment, in transportation. All of that will manifest itself in what they're doing in a big way, I think. >> Okay, so, but a lot of the things that you described, and help me understand this, are Hitachi Limited. Now of course, Hitachi Data Systems started as, National Advance Systems was a distribution arm for Hitachi IT products. >> Don: Right, good for you, not many people remember. >> I'm old. So, like I said, I had a 30 year history with this company. Do you foresee that that, and by the way, interestingly, was often criticized back when you were working for HDS, it was like, it's still a distribution hub, but in the last decade, HDS has become much more of a contributor to the innovation and the product strategy and so forth. Having said that, it seems to me advantageous if some of those things you discussed, the trains, the medical equipment, can start flowing back through HDS. I'm not sure if that's explicitly the plan. I didn't necessarily hear that, but it sort of has to, right? >> Well, I'm not privy to those discussions, so it would be conjecture on my part. >> Let's opine, but right, doesn't that make sense? >> Don: It makes perfect sense. >> Because, I mean HDS for years was just this storage silo. And then storage became a very uninteresting business, and credit to Hitachi for pivoting. But it seems to me that they could really, and they probably have a, I had Brian Householder on earlier I wish I had explored this more with him. But it just seems, the question for them is, okay, how are you going to tap those really diverse businesses. I mean, it's a business like a GE or a Siemens. I mean, it's very broad based. >> Well, again, conjecture on my part, but one way I would do it would be to start using Lumada in the various operations, the domain-specific operations right now with Hitachi. Whether they plan to do that or not, I'm not sure of. I've heard that they probably will. >> That's a data play, obviously, right? >> Well it's a platform play. And it's enabling technology that should augment what's already going on in the various elements of Hitachi. Again, I'm, this is conjecture on my part. But you asked, let's just go with this. I would say that makes a lot of sense. I'd be surprised if they don't do that. And I think in the process of doing that, you start to crosspollinate that expertise that gives you a unique advantage. It goes back to if you have unique advantages, you can choose to exploit them or not. Very few companies have the set of unique advantages that somebody like Hitachi has in terms of their engineering and massive reach into so many, you know, Hitachi, GE, Siemens, these are companies that have big reach to the extent that they exploit them or not. One of the things about Hitachi that's different than almost anybody though is they have all this domain expertise, but they've been in the technology-specific business for a long time as well, making computers. And so, they actually already have the internal expertise to crosspollinate, but you know, whether they do it or not, time will tell. >> Well, but it's interesting to watch the big whales, the horses in the track, if you will. Certainly GE has made a lot of noise, like, okay, we're a software company. And now you're seeing, wow, that's not so easy, and then again, I'm sanguine about GE. I think eventually they'll get there. And then you see IBM's got their sort of IoT division. They're bringing in people. Another company with a lot of IT expertise. Not a lot of OT expertise. And then you see Hitachi, who's actually got both. Siemens I don't know as well, but presumably, they're more OT than IT and so you would think that if you had to evaluate the companies' positions, that Hitachi's in a unique position. Certainly have a lot of software. We'll see if they can leverage that in the data play, obviously Pentaho is a key piece of that. >> One would assume, yeah for sure. No, I mean, I again, I think, I'm very optimistic about their future. I think very highly of the people I know inside that I think are playing a role here. You know, it's not like there aren't people at GE that I think highly of, but listen, you know, San Ramon was something that was spun up recently. Hitachi's been doing this for years and years and years. You know, so different players have different capabilities, but Hitachi seems to have sort of a holistic set of capabilities that they can bring together and to date, I've been very impressed with how they've been going about it. And especially with the architecture that they're bringing to bear with Lumada. >> Okay, the book is The Future of IoT, leveraging the shift to a data-centric world. Don DeLoach, and you had a co-author here as well. >> I had two co-authors. One is Wael Elrifai from Pentaho, Hitachi Vantara and the other is Emil Berthelsen, a Gartner analyst who was with Machina Research and then Gartner acquired them and Emil has stayed on with them. Both of them great guys and we wouldn't have this book if it weren't for the three of us together. I never would have pulled this off on my own, so it's a collective work. >> Don DeLoach, great having you on TheCUBE. Thanks very much for coming on. Alright, keep it right there buddy. We'll be back. This is PentahoWorld 2017, and this is TheCUBE. Be right back.