>> Live from Las Vegas, it's theCUBE covering AWS re:Invent 2018, brought to your by Amazon Web Services, Intel, and their ecosystem partners. (techy music) >> Hey, welcome back, everyone. It's theCUBE live here in Las Vegas for Amazon Web Services, AWS re:Invent 2018, I'm John Furrier with Lauren Cooney, the cohost of theCUBE on this set. There's two sets, and we're getting all the great interviews from the smartest people here in the ecosystem. AWS re:Invent is the industry conference that makes it all happen in the cloud. We're excited to have Lynn Lucas here, CMO of Cohesity, back on theCUBE, CUBE alumni, also the architect of the greatest party of all time. The Cohesity parties, you guys had a great party last night. I tweeted some live footage of it. Got a little bit of backlash on Twitter, but it's okay, you know. >> We don't want that. >> A lot of FOMO. >> Hopefully also the architect of some great marketing here. We're here to get the word out about Cohesity and our news with Amazon, so glad to have you here. Thanks for having me on the set again. >> You guys really hit the formula for parties at events because normally they can be kind of boring. You bring artists in, you have a great venue. You glam it up with green, the color of Cohesity. How's that working out for you guys, what's been the feedback? I was going to say people last night were jamming, great crowd. Tell us what's going on, what's the success look like, what's the vibe? >> Yeah, well it certainly is about appreciating our partners and customers that are here, but really it's all about getting the word out about Cohesity, and you know, I think you know the numbers here were somewhere between 50 and 60,000 people here, crazy, at re:Invent, and we want people to know what Cohesity can do for them in terms of their use of Amazon and making that investment even better and smarter for them, for what we call secondary data, so that was the purpose of the party, thank our customers and partners and get the word out about what we can do. >> As they say in the old marketing cliche, if you've got the sizzle you've got to have the steak. >> Absolutely. >> So, tell me, you've got some great sizzle, great marketing, congratulations, doing a great job. Love working with you and love going to your events. What is the action on the products, like where's the meat on the bone? >> Sure thing, so we had a really important announcement here yesterday extending our partnership with Amazon. We had an extension to some already great, killer features that we have. Three things, so three things you got to know. One, integration without agents to do backup of your cloud native, AWS applications, full failover and fail back to the Amazon cloud and back again for DR, and we also are now offering integration with Snowball, so a lot of customers looking at how they can get more of their data into Amazon, and now we facilitate that and of course give you the indexing that allows that to become searchable and usable for the longer term. >> I want to ask you a question. I saw a presentation this morning at Teresa Carlson's public sector breakfast, packed house, again. She's really doing an amazing job, so shout out to her and her team, but the presentation was from the deputy of the FBI counter terrorism, she talked about all the bad things that have happened and how they tried to catch up and find the bad guys, or gals, and the problem they have is that they have a data crisis, and she said that: "The FBI has a data crisis," and they can't put the puzzle together fast enough because although the data's there, they can't get it out of the databases and there are all these different fragmented systems. This is a problem, how are you guys helping clients fix this fragmentation problem? Is that an area you're solving? What's your vision, or Cohesity's vision, around this notion of how does cloudification solve this speeding up of value around data that's kind of spread out everywhere? >> Yeah, so you hit the nail on the head. We call this mass data fragmentation, and that's the problem that she's talking about. In fact, we just completed a global study of secondary data, and nine out of ten, not surprisingly, of IT organizations around the globe think that this is going to cost them somewhere between 50% and 100% more than what they're currently spending to manage their data, because it's in silos, it's in silos on-premise, but it's also then started to silo inside the cloud, and how Cohesity helps is creating a unified platform, what we call the Data Platform, and spanning the on-premise and the cloud, the multicloud environment, and providing some really unique capabilities to help organizations take that fragmentation and now remove it, bust those silos, put it in one place, give you global search, indexing, and then compression, because we all know how many copies... Excuse me, deduplication, save storage, but then also the removal of copies, because we all know how many copies there are out there. >> So, Cohesity's brand message is you guys keep pounding the frequency, get the brand message out there, is what, what's the brand promise for Cohesity? >> Great question, the brand promise is we are going to end your mass data fragmentation problems and give you web scale simplicity, right? So, why are so many organizations here, right? They love what they see with AWS and that web scale and that hyper scale simplicity, but many companies, right, still have a lot of on-premise systems, and so they're struggling with it. Well, our founder, Mohit Aron, was one of the original developers of the Google file system, knows a little bit about building distributed file systems, and so he's brought that into an affordable platform for the enterprise to give you that scalability across your on-premise, your public cloud, private cloud edge sites. >> And I think that is critical across multiple environments, especially as people are trying to develop across those multiple environments, there really needs to be that consistency for them. Some of the things that I've picked up that I hear about you guys, it's really about user experience. It seems like you care a lot about that. You've got one graphical, you know, interface that you actually use, and it makes, I think, data less scary to folks. I would say the ecosystem, I don't know... You know, I looked at your architecture and I don't know who's not in those boxes, but you make it very clear, you know, in particular, and I think also saving people money, you know, that's going to be critical because everyone is scaling out and they're spending more and more and more, and what they're spending more on is, you know, this vast amount of data that they can't control anymore, and it's, you know, just kind of churning. >> Yeah. >> And we just had this great guy on here and he was talking about, you know, the movie that he did, and he's the one-stop shop, like, IT guy at this company, and he's the... He thinks, he's like, "They saved my life," was what he told us-- >> Yeah. >> About you guys, so-- >> So, I think you hit the nail on the head, it's all about simplicity. I mean, again, in our new study, and I don't think this is going to surprise anyone, but bringing it up to date for 2018, you still have, on average, five to six systems just for backup, up to 15 if you count all secondary, which is files and objects, analytics, test dev, and think about IT trying to manage all of that complexity from a user interface, a procurement, a training enablement. So, we give them that one-stop dashboard simplicity-- >> Yeah. >> And then on top of that build a foundation for the test dev organization, analytics organization to now do more with the data, because it's not enough to just bring, bust those silos and bring the data into one place. We need to do something with that data, right? >> Absolutely, and you know, you guys were talking, before we came on camera, about storytelling, and you know, I look at the story of the cloud. I want to get your perspective on this, and Lauren, feel free to chime in because I think you've got a good input on this. If you look at what the cloud is doing to changing the game, this narrative is changing. Andy Jassy calls it the old guard, other people call it legacy systems. We've all been in a tech industry. We've kind of seen where it's been and where it's going now. More visibility now in where it's going, AI and more automation, all this greatness. The narrative's changing, who's ready, who's prepared, what is the story of the modern cloud era? What is that narrative and how should companies be talking to themselves? What's their self-talk, how do they... What's your thoughts on the story of the modern era? What's actually happening in your mind? >> Well, I think, you know, the narrative is around if you are not cloud-forward, I don't like to call it cloud native because I think that really doesn't speak to so many organizations, so it's about being cloud-forward, and having that mindset, right, that you are going to be thinking about what are the advantages of the AWS cloud for me and my business. How can I use that to gain efficiencies, and that is something that I think really does separate the old guard from the new guard. You know, if I think about Cohesity in that vein, compared to some of the legacy solutions out there, that is what Mohit Aron built in. We're cloud native from the beginning with an S3 interface, but with those interfaces back into the enterprise world so that we can help customers bring that forward, data portability and app portability. >> That's Amazon's mission, they're just forward, forward, forward progress. They're not even looking in the rear view. Although, Andy does look at Oracle, but we have to Oracle, Lauren, what's your take on the storytelling, because I'd love to get your perspective on this, too. I hate to go on a little tangent here, but I think it ties to the Cohesity brand promise. You got developers changing, you got IT experts being devops kind of, you know, culture change there, and you've got the role of opensource communities. This is a new mosh pit of action. What's your-- >> Yeah, I think it's a mosh pit of action, but it's more of a mosh pit of opportunity-- >> Yeah, absolutely. (chuckling) >> If you really want to look at it. You know, you have developers, so you know, in 2003 I was at BEA building developer communities around web servers, and then I actually went, you know, in 2008 I was at Microsoft building the web platform, which was the precursor to Azure, and you know, then skip ahead, you know, 10 years, and this is where we are and this is what we're looking at, and I think that what we've gotten to along that, you know, kind of timeline, is it has to be easy for users. Development has to be easy, it doesn't matter where in the stack people are working, it has to be accessible, people have to be able to learn it or up skill to it very, very quickly, and it's really a new, you know, shape and form that's kind of coming to the table, and as people look to study computer science and things along those lines it will be important, but it will become less important as more companies start to look at the Salesforce model where you literally can become a developer in a week, and things along those lines. >> Right. >> That's what I think the cloud is really bringing to the table. >> It's the new software methodology. Clearly Amazon announcing this cool ground station, satellite as a service, spin up, fly your own drones, whatever you want to do. You don't have to provision a satellite anymore, just turn it on. It's going to empower the edge, because the edge is where conductivity stops. So, if you've got conductivity everywhere, that now means that all data will be coming in even probably more exponentially. This is kind of in your wheelhouse. As you look forward, as you go cloud-forward and IoT edge forward more data's coming. Are you ready for that, what's the vision for you guys, how do you handle all that? >> Well, you know, I think the story about more data, with respect, is old. We all know that, right, you know. What people haven't been able to solve is as it's coming in, how are you going to keep track of it, and is it even feasible to try to put it all in one place, and I think the answer's not really, right? I mean, think about IoT-- >> Yeah. >> And all these edge sites-- >> Yeah. >> And the promise of what's going on, so this vision, which I love, is of a spanning system that gives you that operating model of one platform, but not trying to do the impossible of continually trying to put data all in physically one place, coupled with, I so agree with you, this API-first economy. If you aren't building systems that way, you know, then it really isn't built for the future because who can imagine all of the things that we do with our smartphones, and we like to think of what the Cohesity Data Platform is is the analogy to the smartphone, right? We used to carry the flip phone, the GPS, the music player, the flashlight, that device changed the world, and then we changed it again by using APIs to build new apps on it. Cohesity Data Platform is that same vision. We're going to create that unified operating environment, and then through APIs let companies build on it. >> So, it's a data platform is not so much a category of backup and recovery. It's a benefit, a lot of value there, get a magic quadrant, maybe, written up someday, but you're a data platform. >> Yeah, well I go back to that analogy of the smartphone, right? You know, so we solve, and want to solve and be the world's best at solving some of the toughest problems, and data protection is one of them. Like, I'll speak to one of our other AWS customers that's here, which is Dolby, and Dolby had a massive challenge with their on-premise data center moving their workloads to AWS since 2016, had a fire in their data center and started realizing, "Hey, there's a lot of benefits "to doing more backup in the cloud, "but also doing more archive to the cloud," both from a protection point of a view, as well as a cost saving point of view, and that is, you know, the kind of thing where we're going to solve each of those use cases. Your phone is still great as a phone, but it's also great to order your Uber here, and maybe get you a meal. >> And there's data in there, too, okay. >> Yeah. >> Question, final question for you is competition, a lot of heat in the kitchen with competition. You don't shy away from it, I love that about you. You guys are loud and proud at Cohesity, love that brand. >> Super green. >> Yeah, super green, green light, go, green is money, too. How are you different from competition, why are you winning, what's the advantage? >> Well, let me go back to, I think, a phrase, old guard, new guard. So, I think there's an old guard, and we would clearly separate ourselves from the old legacy solutions that are not hyperconverged and are not web scale, and are not web-first or cloud-forward. There's another group that are looking at, and even some of the old players now, trying to move into the new world, but I think what differentiates Cohesity is three things: A true spanning file system, web scale, that is not focused on just being a better backup. So, you just touched on backup, it's an important workload, but our vision is to consolidate all secondary workloads, so that's backup, yes, but it's also files and objects. It's also then making that data productive for test dev and analytics, and doing that across, again, the edge, the cloud, and on-premise, and that's what makes us different. >> Final, final question, because I always do this because one pops into my head when you're talking, Andy Jassy's going to talk a lot about this tomorrow, because I got a little preview on Monday last week, net new workloads, latency, all these new things. Got some of the announcements trickling out. He's seeing, and a lot of people are, we included agree with him, when you have the kind of compute that's available and the kind of data platforms and the horizontal scalability to cloud, these new net workload will be enabled. AIs been enabled by great compute. AIs been around for decades-- >> Mm-hm. >> And it's got a renaissance with compute. What new net work, net new workloads do you envision Cohesity bumping into or pioneering in the future? >> Well, actually we're going to look to the developer community, honestly, right. I think we have a strong ethos and belief that, you know, we're not the smartest people in the room, so to speak, so let's bring that out to the developers and let them in their companies or in the third parties, the great community that's here, figure out what is the next thing that we can do. When we don't have these fragmented silos of data and we can actually see in its entirety what is available to us, what might be possible? I think it could change the world. >> Developer community's a very key part of it, I would agree. Again, there's hardcore new developers emerging, IT expert developers, opensource community contributors all coming together, all here on theCUBE covering, that's our audience, that's you guys out there. Bringing the best action here at re:Invent. I'm John Furrier with Lauren Cooney, here with Lynn Lucas with Cohesity. We'll be back with more live coverage here from the two sets, double barrel shotgun of theCUBE, we call it theCUBE canons. Stay with us for more coverage after this short break. (techy music)

>> 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 Chicago, Illinois; it's theCUBE. Covering VeeamON 2018. Brought to you by Veeam. >> Welcome back to the Windy City, everybody. You're watching theCUBE, the leader in live tech coverage, where we go out to the events, we extract the signal from the noise. This is our second day at VeeamON 2018, our second year. I'm Dave Vellante with Stu Miniman, my co-host. Phil Goodwin is here, he's a research director at IDC's storage systems and software group. Phil, thanks very much for coming on theCUBE. >> Pleasure to be here today. >> So you've been to more VeeamONs than we have, so you've seen even a greater evolution, although we've been to a lot of VeeamUGs. We saw a lot of green. This company has painted Chicago in green. What's your take on the progression and ascendancy of Veeam beyond just being a virtualization specialist? >> Sure, obviously the most interesting thing about Veeam is how they really have become the high growth leader of this industry, and in many ways, kind of the darling of the industry because they've got a lot of the momentum, a lot of the attention that's going on in the data protection and recovery software space. I think what has really struck me over the years of these VeeamON conferences, and really from the very first one that I attended three years ago, is the degree to which there is an ecosystem that's been built up around the products that they have for things like disaster recovery as a service, backup as a service and so forth. Where people take the Veeam software, build it into their own products and go to market with that, and I think that's totally unique in the way they've done that compared to many of their competitors. >> Let's see, we're talking about 800 plus million dollars in bookings, mid-30% growth rates. I presume the data protection market's not growing that fast. >> No, although it's surprisingly strong. Last year it grew at about 7% rate. We don't expect it to keep going that fast but if you compare that to other stores' software, which is 1% to 2% or in some cases even negative, it's actually an area that's quite bright. >> Yeah it's grown much, much faster than the overall IT business, right? >> Oh yeah, absolutely. >> And so, why? Why is it growing faster? >> Well part of it's driven by capacity. A lot of the vendor models are associated with the capacity and so they charge upgrades every year and as data is growing at about 40% per year on a compound annual growth rate, that does cause customers to upgrade their licenses. But we're also seeing an acceleration in the deployment of applications so we expect IT organizations, according to our research, to add an additional 200 applications over the next 36 months. That's not a lot of new applications. What we find in many cases is what we would call the traditional incumbent vendors, who have their footprint within the enterprise, maintain that footprint in many cases, but those new applications have the opportunity to bring in new products and that's really where the opportunity for Veeam is. >> So part of the growth is somewhat artificial if I understand it in that it's pricing driven, and so that would suggest, given that data protection is largely insurance, that the CFOs are going to look at that line out and say, "Oh, this isn't sustainable." Unless, and I want to run this by you, research indicates that Fortune 1000 companies leave, over a three to four year period, billions of dollars each on the table because of not the most end-to-end or well-thought-out architected data protection solutions. Maybe that expands the TAM a little bit, but is that kind of growth sustainable? You've already sort of indicated it's not, but maybe talk about that a little bit. >> Right. The nature of threats has really changed a lot over the years too, so if you look back on computing, it used to be system failure, human error, and to some degree natural disaster were your biggest threats. Nowadays it's actually ransomware, malware, and other things that are much bigger threats than the traditional types of threats that organizations have dealt with. As the evolution of data protection has come about, what we've found is very much a willingness among IT organizations to not simply try and go with a single product, but to rather buy a best-in-class product for specific platforms. In the case of Veeam, I think they really did a very successful job of riding the virtual infrastructure wave when most of their competitors were architected specifically for second platform types of applications. >> Phil, one of the interesting things to watch in Veeam is their expansion beyond that virtualization. What insight can you give us about data protection and SAS and public cloud and service providers? A lot of those environments you would think that the platform or the provider might have a choice, so how does Veeam get in there? How much do customers really have choice there? >> That's really a great point because what is happening is we're moving data protection from the system level. We've moved it up to the virtualization layer and now it's really moving to the application layer, where it is the application developer whose building that data protection directly into their application. So what we're seeing is those application developers, which as you mentioned many are SAS applications on the web, building the data protection into their specific environment. But the other thing that's happening is IT organizations are suddenly realizing that much of that data that is in the web or with those SAS applications is not being protected according to the SLAs of the organization. They're using third party tools and applications like Veeam to bring that data back on site and to protect it according to what the requirements and government's requirements are. >> Okay, so let's unpack some of this. If I understood it correctly, going back to the developers, as architecting in the data protection approach, is that a result of the DeVops trend, infrastructure as code, or is it something else driving it? >> I think it's more being driven by the fact that these are discrete applications outside the data center. So if I'm inside the data center and I'm trying to protect 100 different applications, I may try and apply the same techniques to all of them, the same policies. But these are applications like Salesforce.com, or Payday, or other applications that are really, for lack of a better term, a single application. That environment really doesn't have to consider the other systems within a data center. >> So it's the SAS guy saying "one size fits all." >> Phil: For them, yes. >> Which, by the way, is an age-old problem inside the data center. Either you were not protected enough or you were paying too much. Do companies like Veeam solve that problem by providing more granularity and maybe aligning better with that? >> Yeah. They go attack the problem in a couple of different ways. First of all, they certainly have their traditional business within the data center, but they're also partnering with many of the cloud-based organizations like Azure and Amazon and others to be able to help organizations protect data they have in the cloud. Plus they're working with specific applications to be able to provide that kind of protection for a SAS app. >> I want to come back to something you were talking about with Stu about best of breeds. We do a lot of these shows. You talk to a lot of customers and a lot of technology companies. You get two ends of the spectrum. You get the best of breed guys like Veeam say, "Hey, we're best of breed, "why would you buy that old, clunky, "outdated backup capability?" And then, without naming names, you get the integrated full stack companies going, "Why would anybody buy from some tiny little company? "Oh yeah, okay they're 800 million, "but they can't do digital transformation and big data "and SAS and blah blah blah! "So why would anybody, who cares about backup?" So you have two completely counterpoised positions. How can you help us parse through that? >> I think a lot of it comes down to who is the actual consumer and buyer of the solution and that's indeed changing. What we're seeing much more is it is the application developer, the application provider, or even the line of business making the decision as to what applications are being deployed, as opposed to the central IT organization. So whereas the central IT organizations say "This is part of digital transformation," the business unit may be buying other applications. >> We talked a little earlier about money being left on the table. I don't know what your research shows but clearly there's opportunities there that's not being harvested today. From a cost-benefit analysis standpoint, I know it's one area that you focus on and spend some time there, is it a reasonable expectation that CFOs will actually look at that lost opportunity, that soft revenue that they're losing, which really is not that soft, and say, "Hey, we actually need "to increase our spending in this area?" >> Some of them, yes. What you really find is a maturity curve, of course, where you have some organizations that really have a very traditional view and have not tried to move forward. But our research is showing that about 60% of organizations have embarked on some kind of digital transformation, and that about 70% have a cloud-first perspective. Those organizations really are looking at those kinds of opportunities, both in terms of cost, opportunity cost or absolute cost, and saying, "How can we optimize this environment entirely?" >> If I were the CFO, and let's say I had the cash so I wasn't capital constrained, I would still say, "Look, this is insurance, "so figure out a way to get more value out of this data. "You got all of this data in the backup repository, "what can we do with that? "What analysis can we do? "Can we maybe be more efficient "with regard to how we do security?" It's like the US government. "Can we have this agency talk to that agency "and figure out a way we can get more leverage?" and really be putting pressure on them to do that. Is that an unreasonable expectation for CFOs? >> No, and in fact what our research has shown is that about 40% of organizations use their backup data sets for analytics. They also, about 30% of them, 33% use it for other purposes such as development and test, staging, others. So organizations really are trying to leverage that vast amount of information that they have for other purposes. One of the challenges that come out though is GDPR, the European regulation to the right to be forgotten and the way organizations have to be able to manage that data. Going into those data repositories, including backup data sets, to say "Okay, this is data "that we have to expunge by regulation." >> Phil, I wonder, we've been talking about the threats of GDPR and you might get sued or everything. The last few years, we've really been talking about how we get insights and data. Insights can transform businesses around data. Is GDPR a threat to this whole wave of getting value out of data? >> I don't think it's a threat to getting the value out of the data, I think it's a threat to how you manage that data. And the threat is much more widespread than many organizations realize. If you're doing business with anyone who is European or has traveled to Europe, and really any kind of footprint in that regard can potentially put your organization at risk if you're capturing any of that data. >> But that stat you just threw out was pretty interesting. The 40% percent of organizations that you surveyed are actually doing some types of analytics with their backup data. I would think that governance and compliance and GDPR related stuff, they're going to take, those 40% are going to take a similar approach to GDPR. Say, "Okay, guys, we got to do this. "Find some more value out of it, "or else get you in a headlock." Right? That's a huge number! >> Right, and one of the ways you do that is, and that Veeam has done is to open up APIs, application programming interfaces, to allow third party organizations to leverage that data repository and do that kind of analytics. Veaam, themselves, or any other backup vendor can't really leverage, or can't really do that, but by opening that up to third parties it increases that ecosystem and increases the value that IT organizations can get from their data and their investment. >> Some of your research. Maybe you can highlight some of the stuff you're proud of, fun stuff you've been working on, things that are current, recent, that you want to highlight to the audience. >> I think some of the interesting things, the trends in the industry really are that the kinds of things like backup and recovery and high availability and disaster recovery, we see really going into a continuum of availability. Where, if I can move data across geographies, and I can recover my application seamlessly regardless of where the data is, why do I ever need to have disaster recovery again? And in fact, that's where we believe availability is going, and in fact the theme for Veeam at this show is hyper-availability. One of the ways you do that is by placing the data in the right locations for that kind of recovery. Watching from the days of backing up once a day onto tape to continuous availability is actually a pretty interesting development. >> So who's doing a good job in this place? Sounds like Veeam is getting it done obviously, and the numbers speak for themselves. You got the startups, Cohesity, Rubrik, Zerto obviously plays in there. You have Veritas is supposedly retooling. You had Bill Coleman in there, former BEA guy who's supposedly put a lot of R and D into that. You got the leader in Dell EMC. Obviously they have a lot of resource, spend a lot of money, they're going through a retooling process. IBM has software defined everything. It seems like it's jump ball right now instead of wide open. >> It really is. You look at, you mentioned Dell EMC, they're focusing on IOT. Well IOT generates a phenomenal amount of data. What data needs to be captured, how does it need to be captured, protected, managed, is going to be a huge issue for organizations so that's a very interesting target. Veritas has been looking at their 360 data management and really taking a holistic view of data management and they're doing some very interesting things there. Commvault has done actually a pretty nice job of getting into some cloud-related kinds of things. And then finally as you mentioned, Rubrik and Cohesity, I would put them along with Veeam as probably the three companies that right now are disrupting this industry the most. There are probably certainly some other ones that are up and coming, but in terms of those that are really providing some disruption, I would probably go with those three. >> Alright, they're breaking down VeeamON 2017. Phil, thanks for coming on theCUBE. Great stuff, really good analysis. Appreciate you having on. >> Pleasure, guys, take care. >> The trains are backing up. We're trying to jam everything in before they shut down our studio, so we'll be right back right after this short break. (upbeat music)

(techno music) >> Narrator: Live from Chicago, Illinois, its theCUBE. Covering LeMon 2018. Brought to you by VeeAM. >> Welcome back to the windy city everybody. You're watching theCUBE, the leader in live tech coverage. We go out to the events. We track the signal, extract the signal from the noise. My name is Dave Vellante and I'm here with co-host Stu Miniman. This is our second year here at VeeAMON. Hashtag Veeamon, simple enough. Kate Hutchison is here, she's the CMO of VeeAm. >> Yes, thank you very much for having me. Its a pleasure to be here. >> You're very welcome, thanks so much for taking time out of your busy schedule, great show. You've painted the town in green. >> We certainly have. (laughs) >> So VeeAM obviously didn't need your expert help in creating awareness in places like this. >> Kate: Yes. >> And having a persona around around the green team. Awesome. Your background, Riverbed, Polycom, VMware, Citrix, BEA, some rockstar companies. You've got a lot of experience there. Why did you come to Veeam, and why now? >> Yes, so I was attracted to VeeAM for many reasons. We have some, as you know, some stellar attributes as a company. We've been talking about our net promoter score of 73, which is three and half times the industry average. And of course the executive team themselves, and meeting them and really wanting to be a part of that team. So that was a huge reason for me joining, but as it relates to my career and my background and what I thought I could bring to VeeAM. Very much about enterprise marketing. So I've spent about the last 20 years in the industry, as you mentioned the company names. Really helping those companies build the powerhouse brand, and so I just love being a company who is known for one thing, but is very successful that being known for something that's even broader and more strategic. And that's why I wanted to join the company. >> You mentioned the phrase powerhouse brand. What is a powerhouse brand, and how do you go about building it? >> Well everybody probably has a different definition of a powerhouse brand, but having spent a good 15 years in the Bay area, Silicon Valley, when you're walking around Silicon Valley and you say who you work for and everyone recognizes it, you're working for a powerhouse brand. That hasn't been the case with VeeAM. Now we're very strong, we do our research. We come out pretty strong it Europe, but in terms of our brand awareness in North America we have a ways to go there. Again, and I think because when it comes to building a brand and a powerhouse brand, enterprises really rely on customers to do that. To really leverage the voice of customers, to get the word out and to get the customers to go on record to talk about the power and value of VeeAM. Because when customers go on to talk about it, there really is no better marketing that you can do. >> Ya Kate, one of the things I saw. VeeAM started out with the geeks, and I say that in the most loving terms. People that did virtualization. >> Kate: Yes. >> VeeAM solved a problem, simple, huge adoption in that market, but as we've been talking about all day here, data protection is going up the stack. >> Kate: It is. >> It's hitting the seed sweep more, so. >> Kate: Yes. >> Maybe you could explain to a lot of our audience are the techies and they're like I don't understand this brand in marketing things. >> Kate: Sure. >> We just want the next little containers and things there. >> Kate: Absolutely. >> So why the brand elevation? >> So, first and foremost, we're known for one thing in the industry, as it relates to our product. It just works, and we're not leaving that behind, and certainly the enterprise cares a lot about the product, but as we go into the enterprise space, there's some things that an enterprise customer is going to look for, that an SMB may not. Enterprise is one of the assured company that they're doing business with, has long term viability. They want to make sure that there's plenty of addressable market and headroom for them to go far and above, beyond their sights of, a billion in our case. The other thing is, enterprise customers have a different way of engaging with that company, as it relates to the selling motion. So whether it's our partners, our alliance partners, our resellers, our sales teams directly, they want to be able to work with them as trusted advisors, and they want our folks to be able to anticipate their needs, well ahead of when they actually encounter them. So, we're talking a lot about a journey for our customers. We've been talking about intelligent data management, and the five stages of getting to that. So its really, its building on our core. Which has been SMB and commercial, but also now, up leveling the story, and by the way, the technologists at all companies of all sizes, want to be doing more to influence the outcomes, the business outcomes. So we're telling a story that we think will resonate with them and there's always plenty of click downs into the technology if you want it. (laughs) >> So you guys are putting a lot of emphasis on the up leveling. As Stu mentioned, CXO is becoming more aware of the data protection problem. >> Kate: Yes. >> Its becoming a board level topic. >> Kate: Yes. >> So I think I get the why now. >> Kate: Yes. >> My question is, why VeeAM? And what is the brand promise that you're going to bring to that enterprise? >> So I think, traditionally, VeeAM has been thought of as more of an S&B and commercial play. So the why now is that we have a much broader portfolio then we had a few years ago, and yet we're thought of as just back up and replication. Now, we're building on what our reputation is and back up and replication, but we want to take customers to where we know the puck is going. So for example, as enterprise customers want to take advantage of public clouds, of manage clouds, of SAS applications, they need to be able to get control of all their data. That's the one thing we hear over and over. I don't know where all my data is. Right? So they need to have a platform that can give them that visibility and that aggregated view, that single paint of glass. Then they're going to eventually want to take advantage of being able to move workloads into places where it makes more sense to have them. In cases where there needs to be tighter protection, or in the case of archive data, that they don't need to spend a lot of money on primary storage. It just depends on what our customers want to do. And, ultimately, to be able to move to more of a behavior based way of managing that data. For example, if we see malware crossing that network we can immediately respond and make sure that those workloads are secure. It could also happen as it relates to weather systems and being able to have the data be smart enough to sense and respond where it needs to move to. >> We saw some slides this morning that Peter McKay was showing, like off the platform slide, and I tweeted out that we learned years ago, working with Eric Brinyawlson and Andy McAfee that platforms beat products. >> Kate: Yes. >> So, talk about the importance of platforms through the enterprise. >> Yes, so first of all you cannot be a platform provider without an ecosystem that's embracing and extending the value, and we're working with our ecosystem through the API's, the application programming interfaces, that we make available to them so that they can integrate with our products, and actually allow our platform to be able to be the most complete platform for intelligent data management. That is not all coming from VeeAm, we are very heavily dependent on our ecosystem. >> Dave: Right. >> So that's really the crux of how important a platform is because customers have a lot of technology already in their environments. They want to make sure that if I'm buying something from you, that it'll integrate into my existing environment so I don't have to do a complete rip and replace. That's a very expensive proposition. So, we have been investing and we have thousands of technology partners that are embracing our API's and again, extending the value of our platform. >> I don't want to jump in but, I was going to ask you how you add value to those partners, and it's not just the product and the features, and doing what you say you're going to do from a product standpoint, it's having that platform that makes it easy to integrate, >> Kate: That's right. >> And creating that scale effect, that flyaway effect. >> Absolutely, and a solution that is better together. So, customers really like buying solutions that are already packaged and integrated as it might relate to Cysco and VeeAM or HPE and VeeAM or NetApp and VeeAM. That's what we've been doing with those partners in particular and really going to market together, and that is a preferred way for many customers to buy. >> Or IBM and VeeAM, or Microsoft and VeeAM, >> Yes >> Botanics and VeeAM. VMware and Veeam, we don't want to leave anybody out. >> Kate: We don't want to leave anyone out. Those three that I mentioned, we're on their price list and we are reselling. >> So that's the difference. >> Yes. That's the difference >> Okay, that's really the point. >> Yes. >> Okay. >> So my question is, as you go up the stack a bit, talk about platforms and things like orchestration, >> Kate: yes >> the swim lanes get a little bit muddy, because if you talk about those same partners, the VMware, Microsoft, the Newtanics of the world. >> Kate: Yes. >> They want to own a lot of those pieces in the multi cloud world. >> Kate: Yes. >> Maybe you can help explain that. >> I think we're all probably saying some of the same words, but defining them a little differently. So when we talk about orchestration, it's very much about allowing workloads to move seamlessly across multi-clouds. To do that while the data is secure and protected, and eventually introduce, we have partnerships today that allow us to leverage artificial intelligence. So that those workloads can move seamlessly without any disruption to the business as they're moving to the right location. So yes, I think you hear a lot of the terms, but as you drill down into it and you double click on what does that mean for, in your environment, it's a little different. >> So when VeeAM decided to expand deeper into the enterprise, it's putting its money where its mouth is. I mean Robby brought in Peter McKay, he brought in a number of folks on the sale side with enterprise, now yourself. >> Kate: Yes. >> We saw Dave Russel up on stage today. >> Kate: Yes. >> He's got some enterprise jobs. >> I'm looking forward to working with him. >> You're not just talking to talk, you're walking to walk. Which is great to see, and thinking about the total available market, its a TAM expansion move, can you address that at all? >> Kate: Yes. >> I know you guys are very research oriented, as a company. >> Kate: Yes. >> You have relationships with all the big research houses. What do you see from a taman standpoint. >> Yes, so, remember that our proposition is to have the most complete platform for intelligent data management. By virtue of saying that, it really means we have to look at adjacent markets for additional capabilities to put into our platform, to ensure that we remain ahead of the competition as it relates to intelligent data management. We're looking at various adjacent markets. Whether that be through a build buyer partner strategy. So one of the largest market opportunities in an adjacency is the cloud infrastructure as a service market. It's huge. Its about 90 billion. It's got a very fast clip in terms of its compounded annual growth rate, and we've already made some pretty great progress there, both organically, as well as through the acquisition of N2WS. When we move into fast growing market segments like that, and we have many others that are adjacent as well, it's creating an addressable market of about 30 billion for us as we look out into 2022. So we're pretty excited about that, and again, that gets back to making those investments so that an enterprise customer feels confident betting their business on us. We have that scale ability. We have that addressable market, and we are increasingly helping our folks on the front lines become trusted advisors to our customers. >> In your estimation, I know some of this is hard when you're doing the analysis >> Kate: Yes. >> I used to do that for a living so I know. In your estimation is that sort of an approximation of spend, or does it include what we look at, as the money that's left on the table by the global 2000 because they have inadequate data protection. Presume it does not include that. >> Kate: Yeah. >> Because if it did, it would probably be a trillion. >> Kate: Right >> But I wonder if you can add some color to it. >> Well I think as we get into an era of compliance, we have GDPR coming down this month, I think companies are taking a new look at what does it really mean to ensure that I know where all my data is, that I ensure it's protected, that I'm sure that it's secure, and that it's in compliance. I think you're seeing more attention, more money. You mentioned earlier that this is becoming more of a sea level issue, and I think in an era of compliance and regulations that are coming down, you're going to see that only increase. >> One of the interesting things that we saw about VeeAM when we were looking at the show here, you're almost, how do I say it, a tweener. You're still kind of a startup, but you're one of the bigger companies in the space. There's a lot of buzz and energy, and customer interest >> Yes. >> In this all market thing. How do you look at yourself compared to some of the legacy giants, >> Yeah. >> And some of the new startups? >> So we are a very fast growing company. We posted 40 percent growth in Q4. We were at 36% year over year. I mean off the very big numbers. I haven't seen these numbers since I was at VMware. So that is a rapid growth company that grows up quickly when it's growing at that clip, so I think there's a part of us that's extremely paranoid about the competition and looking at some of the new entrance to make sure that we are really staying ahead and innovating, continuing to innovate. Then we look at some being legacy companies that have been in this space, and we see in some cases, a downward trend in their revenue and in their investments in this era, in this area. Again, I think it's a healthy balance of innovative and paranoid, and recognizing that customers want the solution that VeeAM offers, and they do want to be able to migrate off of the legacy systems that are out there. We are seeing that time and again. We just showed, this morning in the general session, we showed a Royal Caribbean video and that was a case where they abandoned their legacy system to go with VeeAM. >> Well that's quite a story. Nearly a billion dollars, growing at 35 plus percent a year. You got to look to companies like Service Now, Work Day. >> Kate: Yes. >> You're in that rare-ified air. Well Kate thanks so much for coming. >> Absolutely. >> Congratulations on the new role. >> Thank you. >> Really excited to see you sort of take VeeAM up into that new stratosphere. >> I'm very excited to be here. >> It's great to be part of VeeAMON 2018. Thanks for watching everybody. We'll be right back with our next guess, right after this short break. (techno music)

>> Hi, I'm Peter Burris, Welcome to Wikibon's Action Item. (slow techno music) Once again Wikibon's research team is assembled, centered here in The Cube Studios in lovely Palo Alto, California, so I've got David Floyer and George Gilbert with me here in the studio, on the line we have Neil Raden and Jim Kobielus, thank you once again for joining us guys. This week we are going to talk about an issue that has been dominant consideration in the industry, but it's unclear exactly what direction it's going to take, and that is the role that open source is going to play in the next generation of solving problems with technology, or we could say the role that open source will play in future digital transformations. No one can argue whether or not open source has been hugely consequential, as I said it has been, it's been one of the major drivers of not only new approaches to creating value, but also new types of solutions that actually are leading to many of the most successful technology implementations that we've seen ever, that is unlikely to change, but the question is what formal open source take as we move into an era where there's new classes of individuals creating value, like data scientists, where those new problems that we're trying to solve, like problems that are mainly driven by the role that data as opposed to code plays, and that there are new classes of providers, namely service providers as opposed to product or software providers, these issues are going to come together, and have some pretty important changes on how open source behaves over the next few years, what types of challenges it's going to successfully take on, and ultimately how users are going to be able to get value out of it. So to start the conversation off George, let's start by making a quick observation, what has the history of open source been, take us through it kind of quickly. >> The definition has changed, in its first incarnation it was fixed UNIX fragmentation and the high price of UNIX system servers, meaning UNIX the proprietary UNIX's and the proprietary servers they were built, that actually rather quickly morphed into a second incarnation where it was let's take the Linux stack, Linux, Apache, MySQL, PHP, Python, and substitute that for the old incumbents, which was UNIX, BEA Web Logic, the J2E server and Oracle Database on an EMC storage device. So that was the collapse of the price of infrastructure, so really quickly then it morphed into something very, very different, which was we had the growth of the giant Internet scale vendors, and neither on pricing nor on capacity could traditional software serve their needs, so Google didn't quite do open source, but they published papers about what they did, those papers then were implemented. >> Like Map Produce. Yeah Map Produce, Big Table, Google File System, those became the basis of Hadoop which Yahoo open sourced. There is another incarnation going, that's probably getting near its end of life right now, which is sort of a hybrid, where you might take Kafka which is open source, and put sort of proprietary bits around it for management and things like that, same what Cloudera, this is called the open core model, it's not clear if you can build a big company around it, but the principle is, the principle for most of these is, the value of the software is declining, partly because it's open source, and partly because it's so easy to build new software systems now, and the hard part is helping the customer run the stuff, and that's where some of these vendors are capturing it. >> So let's David turn our attention to how that's going to turn into actual money. So in this first generation of open source, I think up until now, certainly Red Hat, Canonical have made money by packaging and putting forward distributions, that have made a lot of money, IBM has been one of the leaders in contributing open source, and then turning that into a services business, Cloudera, Horton Works, NapR, some of these other companies have not generated the same type of market presence that a Red Hat or Canonical have put forward, but that doesn't mean there aren't companies out there that have been very successful at appropriating significant returns out of open source software, mainly however they're doing it as George said, as a service, give us some examples. >> I think the key part of open source is providing a win-win environment, so that people are paid to do stuff, and what is happening now a lot is that people are putting stuff into open source in order that it becomes a standard, and also in order that it is maintained by the community as a whole. So those two functions, those two capabilities of being paid by a company often, by IBM or by whoever it is to do something on behalf of that company, so that it becomes a standard, so that it becomes accepted, that is a good business model, in the sense that it's win-win, the developer gets recognition, the person paying for it achieves their business objective of for example getting a standard recognized-- >> A volume. >> Volume, yes. >> So it's a way to get to volume for the technology that you want to build your business around. >> Yes, what I think is far more difficult in this area is application type software, so where open source has been successful, as George said is in the stacks themselves, the lower end of the stacks, there are a few, and they usually come from very very successful applications like Word, Microsoft Word, or things like that where they can be copied, and be put into open source, but even there they have around them software from a company, Red Hat or whoever it is, that will make it successful. >> Yes but open office wasn't that successful, get to the kind of, today we have Amazon, we have some of the hyper scalars that are using that open core model and putting forward some pretty powerful services, is that the new Red Hat, is that the new Canonical? >> The person who's made most money is clearly Amazon, they took open source code and made it robust, and made it in volume, those are the two key things you to have for success, it's got to be robust, it's got to be in volume, and it's very difficult for the open source community to achieve that on its own, it needs the support of a large company to do that, and it needs the value that that large company is going to get from it, for them to put those resources in. So that has been a very successful model a lot of people decry it because they're not giving back, and there's an argument-- >> They being Amazon, have not given back quite as much. >> Yes they have relatively very few commiters. I think that's more of a problem in the T&Cs of the open source contract, so those should probably be changed, to put more onus on people to give back into the pool. >> So let me stop you, so we have identified one thing that is likely going to have to be evolved as we move forward, to prevent problems, some of the terms and conditions, we try to ensure that there is that quid pro quo, that that win-win exists. So Jim Kobielus, let me ask you a question, open source has been, as David mentioned, open source has been more successful where there is a clear model, a clear target of what the community is trying to build, it hasn't been quite successful, where it is in fact is expected that the open source community is going to start with some of the original designs, so for example, there's an enormous plethora of big data tools, and yet people are starting to ask why is big data more successful, and partly it's because putting these tools together is so difficult. So are we going to see the type of artifacts and assets and technologies associated with machine learning, AI, deep learning et cetera, easily lend themselves to an open source treatment, what do you think? >> I think were going to see open source very much take off in the niches of the deep learning and machine learning AI space, where the target capabilities we've built are fairly well understood by our broad community. Machine learning clearly, we have a fair number of frameworks that are already well established, with respect to the core capabilities that need to be performed from modeling and training, and deployment of statistical models into applications. That's where we see a fair amount of takeoff for Tensor Flow, which Google built in an open source, because the core of deep learning in terms of the algorithm, in terms of the kinds of functions you perform to be able to take data and do feature engineering and algorithm selection are fairly well understood, so those are the kinds of very discreet capabilities for which open source code is becoming standard, but there's many different alternative frameworks for doing that, Tensor Flow being one of them, that are jostling for presence in the market. The term is commoditized, more of those core capabilities are being commoditized by the fact that there well understood and agreed to by a broad community. So those are the discrete areas we're seeing the open source alternatives become predominant, but when you take a Tensor Flow and combine it with a Spark, and with a Hadoop and a Kafka and broader collections of capabilities that are needed for robust infrastructure, those are disparate communities that each have their own participants committed and so forth, nobody owns that overall step, there's no equivalent of a lamp stack were all things to do with deep learning machine learning AI on an open source basis come to the fore. If some group of companies is going to own that broadening stack, that would indicate some degree of maturation for this overall ecosystem, that's not happening yet, we don't see that happening right now. >> So Jim, I want to, my bias, I hate the term commoditization, but I Want to unify what you said with something that David said, essentially what we're talking about is the agreement in a collaborative open way around the conventions of how we perform work that compute model which then turns into products and technologies that can in fact be distributed and regarded as a standard, and regarded as a commodity around which trading can take place. But what about the data side of things George, we have got, Jim's articulated I think a pretty good case, that we're going to start seeing some tools in the marketplace, it's going to be interesting to see whether that is just further layering on top of all this craziness that is happening in the big data world, and just adding to it in the ML world, but how does the data fit into this, are we going to see something that looks like open source data in the marketplace? >> Yes, yes, and a modified yes. Let me take those in two pieces. Just to be slightly technical, hopefully not being too pedantic, software used to mean algorithms and data structures, so in other words the recipe for what to do, and the buckets for where to put the data, that has changed in the data in terms of machine learning, analytic world where the algorithms and data are so tied together, the instances of the data, not the buckets, that the data changed the algorithms, the algorithms change the data, the significance of that is, when we build applications now, it's never done, and so you go, the construct we've been focusing on is the digital twin, more broadly defined than a smart device, but when you go from one vendor and you sort of partially build it, it's an evergreen thing, it's never done, then you go to the next vendor, but you need to be able to backport some core of that to the original vendor, so for all intents and purposes that's open source, but it boils down to actually the original Berkeley license for open source, not the Apache one everyone is using now. And remind me of the other question? >> The other issue is are we going to see datasets become open source like we see code bases and code fragments and algorithms becoming open source? >> Yes this is also, just the way Amazon made infrastructure commoditized and rentable, there are going to be many datasets were they used to be proprietary, like a Google web crawl, and Google knowledge graph of disambiguation people, places and things, some of these things are either becoming open source, or openly accessible by API, so when you put those resources together you're seeing a massive deflation, or a massive shrinkage in the capital intensity of building these sorts of apps. >> So Neil, if we take a look at where we are this far, we can see that there is, even though we're moving to a services oriented model, Amazon for example is a company that is able to generate commercial rents out of open source software, Jim has made a pretty compelling case that open source software can be, or will emerge out of the tooling world for some of these new applications, there are going to be some examples of datasets, or at least APIs to datasets that will look more open source like, so it's not inconceivable that we'll see some actual open source data, I think GDPR, and some other regulations, we're still early in the process of figuring out how we're going to turn data into commodity, using Jim's words. But what about the personnel, what about the people? There were reasons why developers moved to open source, some of the soft reasons that motivated them to do things, who they work with, getting the recognition, working on relevant projects, working with relevant technologies, are we going to see a similar set of soft motivators, diffuse into the data scientist world, so that these individuals, the real ones who are creating the real value, are going to have some degree of motivation to participate with each other collaborate with each other in an open source way, what do you think? >> Good question, I think the answer is absolutely true, but it's not unique to data scientists, academics, scientists in molecular biology, civil engineers, they all wannabe recognized by their peers, on some level beyond just their, just what they're doing in their organization, but there is another segment of data scientists that are just guys working for a paycheck, and generating predictive analysis and helping the company along and so forth, and that's what they're going to do. The whole open source thing, you remember object programming, you remember JavaBeans, you remember Web Services, we tried to turn developers into librarians, and when they wanted to develop something, you go to Github, I go to Github right now and I say I'm looking for a utility that can figure out why my face is so pink on this camera, I get 1000 listings of programs, and have no idea which ones work and which ones don't, so I think the whole open source thing is about to explode, it already has, in terms of piece parts. But I think managing in an organization is different, and when I say an organization, there's the Googles and the Amazons and so forth of the world, and then there's everybody else. >> Alright so we've identified an area where we can see some consequence of change where we can anticipate some change will be required to modernize the open source model, the licensing model, we see another one where the open source communities going to have to understand how to move from a product and code to a data and service orientation, can we think of any others? >> There is one other that I'd like to add to that, and that is compliance. You addressed it to some extent, but compliance brings some real-world requirements onto code and data, and you were saying earlier on that one of the options is bringing code and data so that they intermingle and change each other, I wonder whether that when you look at it from a compliance point of view will actually pass muster, because you need from a compliance point of view to prove, for example, in the health service, that it works, and it works the same way every time, and if you've got a set of code and data that doesn't work the same every time, you probably are going to get pushed back from the people who regularly health that this is not, you can't do it that way, you'll have to find another way to do it. But that again is, is at the same each time, so the point I'm making-- >> This is a bigger issue than just open source, this is an issue where the idea if continuous refinement of the code, and the data-- >> Automatic refinement. >> Automatic refinement, could in fact, we're going to have to change some compliance laws, is open source, is it possible the open source community might actually help us understand that problem? >> Absolutely, yes. >> I think that's a good point, I think that's a really interesting point, because you're right George, the idea of a continuous development, is not something that for example Serr Banes actually says I get this, Serr Banes actually says "Oh yeah, I get this." Serr Banes actually is like, yes the data, I acknowledge that this date is right, and I acknowledge the process by which it was created was read, now this is another subject, let's bring this up later, but I think it's relevant here, because in many respects it's a difference between an income statement and balance sheet right? Saying it's good now, is kind of like the income statement, but let's come back to this, because I think it's a bigger issue. You're asserting the open source community in fact may help solve this problem by coming up with new ways of conceiving say versioning of things, and stamping things and what is a distribution, what isn't a distribution, with some of these more tightly bound sets of-- >> What we find normally is that-- >> Jim: I think that we are going to-- >> Peter: Go on Jim. >> Just to elaborate on what Peter was talking about, that whole theme, I think what we're going to see is more open source governance of models and data, within distributed development environments, using technologies like block chain as a core enabler for these workflows, for these as it were general distributed hyper ledgers indicate the latest and greatest version of a given dataset, or a given model being developed somewhere around some common solution domain, I think those kinds of environments for governance will become critically important, as this pipeline for development and training and deployment of these assets, gets ever more distributed and virtual. >> By the way Jim I actually had a conversation with a very large open source distribution company a few months ago about this very point, and I agree, I think blockchain in fact could become a mechanism by which we track intellectual property, track intellectual contributions, find ways to then monetize those contributions, going back to what you were saying David, and perhaps that becomes something that looks like the basis of a new business model, for how we think about how open source goes after these looser, goosier problems. >> But also to guarantee integrity without going through necessarily a central-- >> Very important, very important because at the end of the day George-- >> It's always hard to find somebody to maintain. >> Right, big companies, one of the big challenges that companies today are having is that they do open source is that they want to be able to keep track of their intellectual property, both from a contribution standpoint, but also inside their own business, because they're very, very concerned that the stuff that they're creating that's proprietary to their business in a digital sense, might leave the building, and that's not something a lot of banks for example want to see happen. >> I want to stick one step into this logic process that it think we haven't yet discussed, which is, we're talking about now how end customers will consume this, but there still a disconnect in terms of how the open source software vendor's or even hybrid ones can get to market with this stuff, because between open source pricing models and pricing levels, we've seen a slow motion price collapse, and the problem is that, the new go to market motion is actually made up of many motions, which is discover, learn, try, buy, recommend, and within each of those, the motion was different, and you hear it's almost like a reflex, like when your doctor hit you on the knee and your leg kind of bounced, everybody says yeah we do land and expand, and land was to discover, learn, try augmented with inside sales, the recommend and standardizes still traditional enterprise software where someone's got to talk to IT and procurement about fitting into the broader architecture, and infrastructure of the firm, and to do that you still need what has always been called the most expensive migratory workforce in the world, which is an enterprise sales force. >> But I would suggest there's a big move towards standardization of stacks, true private cloud is about having a stack which is well established, and the relationship between all the different piece parts, and the stack itself is the person who is responsible for putting that stack and maintaining that stack. >> So for a moment pretend that you are a CIO, are you going to buy OpenStack or are you going to buy the Vmware stack? >> I'm going to buy Vmware stack. >> Because that's about open source? >> No, the point I'm saying is that those open source communities or pieces, would then be absorbed into the stack as an OEM supplier as opposed to a direct supplier and I think that's true for all of these stacks, if you look at the stack for example and you have code from Netapp or whatever it is that's in that code and they're contributing It You need an OEM agreement with that provider, and it doesn't necessarily have to be open source. >> Bottom line is this stuff is still really, really complicated. >> But this model of being an OEM provider is very different from growing an enterprise sales force, you're selling something that goes into the cost of goods sold of your customer, and that the cost of goods sold better be less than 15 percent, and preferably less than five percent. >> Your point is if you can't afford a sales force, an OEM agreement is a much better way of doing it. >> You have to get somebody else's sales force to do it for you. So look I'm going to do the Action Item on this, I think that this has been a great conversation again, David, George, Neil, Jim, thanks a lot. So here's the Action Item, nobody argues that open source hasn't been important, and nobody suggests that open source is not going to remain important, what we think based on our conversation today is that open source is going to go through some changes, and those changes will occur as a consequence of new folks that are going to be important to this like data scientists, to some of the new streams of value in the industry, may not have the same motivations that the old developer world had, new types of problems that are inherently more data oriented as opposed process-oriented, and it's not as clear that the whole concept of data as an artifact, data as a convention, data as standards and commodities, are going to be as easy to define as it was in the cold world. As well as ultimately IT organizations increasingly moving towards an approach that focused more on the consumption of services, as opposed to the consumption of product, so for these and many other reasons, our expectation is that the open source community is going to go through its own transformation as it tries to support future digital transformations, current and future digital transformations. Now some of the areas that we think are going to be transformed, is we expect that there's going to be some pressure on licensing, we think there's going to be some pressure in how compliance is handled, and we think the open source community may in fact be able to help in that regard, and we think very importantly that there will be some pressure on the open source community trying to rationalize how it conceives of the new compute models, the new design models, because where open source always has been very successful is when we have a target we can collaborate to replicate and replace that target or provide a substitute. I think we can all agree that in 10 years we will be talking about how open source took some time to in fact put forward that TPC stack, as opposed to define the true private cloud stack. So our expectation is that open source is going to remain relevant, we think it's going to go through some consequential changes, and we look forward to working with our clients to help them navigate what some of those changes are, both as commiters, and also as consumers. Once again guys, thank you very much for this week's Action Item, this is Peter Barris, and until next week thank you very much for participating on Wikibon's Action Item. (slow techno music)

>> Announcer: Live from Las Vegas, it's the Cube, covering Veritas Vision 2017. Brought to you by Veritas. >> Welcome back to Veritas Vision, everybody. My name is Dave Vellante, I'm here with Stu Miniman. This is the Cube, the leader in live tech coverage. This is Day One wrap of the Veritas Vision conference. Veritas, as we said earlier, is a company that has gone through a number of changes, Stu. I mean, I remember when the company launched in 1983. It was sort of, you know, it was focused on backup. It was Veritas and Legato. And they kind of grew through the PC era and the client server era, really started to take off. And then they exploded in the internet era. Their evaluation went through the roof. They ended up buying C8's backup business. They really drove that and then got purchased by Symantec for a big number. I mean, I think the number was 15 billion. I mean, it was in the teens as I recall. Really never did much under Symantec, or, Symantec never did much with Veritas. I think they had a vision of information management and that never really panned out. Spun the company back out, devested it, sale to Carlyle and some other investors for, I thought the number was 8 billion, somebody told me 7 billion today. That must be net of cash. 2.3 billion dollars in revenue. My understanding from sources is that valuation is way, way up, nearly double from 2015. Now, maybe that's an inflated number, but I'm not surprised. The market's been booming. So that's sort of the inside organizational issues. We're here at The Aria, what do you say, Stu, a couple thousand people, 2500? >> Yeah, it's about 2000, Dave, and it's interesting, I talked to some people that had gone to the old Veritas Vision, years ago, and gotten up to about 4000 or 5000 people. But, grown since last year, good energy at the show. We got to talk to the Vox community people. They've got 10,000 people online contributing to their forums, participating, launched the VIP program for some of the super users they have here. Definitely good crowd in the keynote. Good people clapping and participating, getting excited. It surprised me a little bit the number one topic of conversation is GDPR. As you said in our last interview, we're going down the deep abyss of how you're going to get litigated out of all of your money if you don't follow this. It's like way worse than Y2K, ah, some stuff's going to break and maybe turn off for a bit. >> Well, you know what I liked about the GDPR discussions though, they had answers. >> Yeah. >> Other events where I've gone to GDPR, it's been scary, scary, scary, scare you, scare you, scare you, and then call us. >> Yeah. >> And we'll give you some services. What I liked about, what I'm hearing from Veritas is, they've got at least a quasi-prescription as to what to do. So that's good. But the more interesting part to me Stu is you've got this enterprise backup legacy, I'll say it, legacy backup install base, enormous. A leader, they've mentioned many times, 15 years in a row leader in the magic quadrant. And I believe it, you talk to customers, what are you running, NetBackup, everybody's running NetBackup. But how they're transitioning into this vision of multi-cloud, data protection resilience across the Enterprise, across clouds, hyper scale. What I'm not fully clear on yet is how they get customers from point A to point B. And we heard from the keynotes this morning and Bill Campbell. We invested a bunch of dough in R&D, we're writing stuff that's cloud-native, container-based, micro services. So sort of all the right application development buzzwords and I believe that they're developing there. But I don't understand how they migrate that install base. Is there some kind of abstraction layer? Is there some kind of new UI? We heard them jokingly say today in the keynotes that, we hear you, customers, we know our UI sucked, we're working on that. I didn't see any announcements on that, but, that's something that, presumably, is a promise they're putting forth. But, I wasn't clear, maybe you could help clear it up, on how you get from point A of legacy install backup software to this nirvana of multi-cloud hyper scale micro services. >> Yeah, I mean, Dave, when we talked to Bill Coleman, his three Vs, value, vision, and that values of the company itself, clearly has got a compelling vision. He said not only ten years from now, but probably five years from now, every product I'm selling is going to be obsolete. And it's an interesting thing to hear because 15 years of experience, we're trusted, but we know that every product that you bought from Veritas in the past is going to be replaced by new things. And, right, how do we get, say okay, I've been buying that backup for a decade, do I get this visualization product, and if I'm looking at AWS, is Veritas the company I turn to? So really it gets down to, Dave, that blocking and tackling. Talked about the consultants, the partners, both on the go to market side as well as the technology side. Can Veritas get in there, can they have compelling differentiated products that solve a need in the market? We've talked to a number of companies this last year where I've looked at is this hybrid multi-cloud world. If you're software, how do you play in this market? Because isn't Microsoft, Google, Amazon, aren't they going to just do this? Information governance invisibility, absolutely. Amazon has a solution for you. Google has a solution for you. Microsoft has solutions. But, if I'm going to be across those environments, we haven't had a solution that goes across all of those environments. So, there's a hole in the ecosystem, and Veritas, along with many other companies, are trying to put that big elephant on the table and eat pieces out of it, so, it's interesting. >> And Coleman's background, from BEA, started at BEA, I think he took the thing up to half a billion dollars, sold it to Oracle for a big number. But you look at what BEA did, they were sort of the application integration glue. And that's a lot of, you hear a lot of similar messaging modernized around multi-cloud, around hyper scale, around micro services and the like. So, Coleman obviously has experience doing that. I thought he's a very clear thinker. I had not met him before. Furrier knows him pretty well, from his VC days. But I thought he laid out a pretty clear direction. So he's got street cred on this. SEEP com, done it before, I think this company has a decent balance sheet. They seem to have some patient capital in Carlyle. It doesn't appear that Carlyle's trying to suck all the money out. They don't have the 90-day shot clock. He basically, Bill Coleman basically said, look, we're fine shrinking to grow. We're shifting from a upfront license model, perpetual license model, to a ratable model. We could never do that as a public company. So it's going to be very interesting to see if and when they emerge as a public company, what that looks like and where they come from. >> Yeah, and Dave, one of the things I've been poking at is where do they sell to? If this was the backup administrator, that's not somebody that's going to help them with the transformation. It's digital transformation, it's my cloud strategy. It's things like GDPR where I'm going to need to get up the stack to the CIO, to the C-suite, prove the value that Veritas has, and therefore they can then get all these new products in where everything, the 360 data management, really at the core of what they're doing, and whole lots of other products. I mean, Dave, we didn't even dig into some of the object and file storage pieces that are in here. I know we've got their chief product officer on the Cube tomorrow. But a lot of products, pretty broad software suite. And for an infrastructure company, it's always interesting to hear them say, really, infrastructure doesn't matter. The no hardware agenda, but it's your data that matters, and we've got a vision here at Veritas Vision to bring you forward and lots of plays on the name of the company. Veritas, the show is the truth in information. >> Yeah, so, let's talk about the lineup tomorrow. A lot of product stuff tomorrow. Mike Palmer's coming on, he gave a great keynote this morning. Very funny, he gave a scenario of the world ending because basically people didn't have their data act together. They had these images of Las Vegas hotels in chaos and waterfalls running through the hotels and drones attacking and just total chaos. So we're going to get into a lot of the portfolio stuff and I think try to answer, Stu, some of those questions that I raised about how do you get customers from point A, where they are today, to point B. Are you going to, how are you going to transition them. Are there financial incentives? Is there some kind of abstraction layer that you're developing? What is that framework that brings us to that nirvana? So, give you the last word here, Stu. >> Yeah, so looking forward to digging in more with some of the customers, some of the partners. Good energy at the show. It's exciting to be here for the first time. And looking forward to Day Two. >> All right, good, good wrap, Stu. Thank you, and thank you for watching. Go to siliconangle.com for all the news. We saw some Oracle news today. Hitachi changed its name or Pentaho changed its name, we're not really sure about that. But all the news on siliconangle.com, go to wikibon.com for all the research. And of course, thecube.net to see this show, replays, youtube.com/siliconangle is where we archive all this stuff. Lot of websites. >> Yeah, and make sure to subscribe on our YouTube channel. >> Yeah, please do subscribe on that YouTube channel and follow us on Twitter, @thecube, @stuminiman, @dvellante. That's a wrap Day One, this is The Cube, we'll see you tomorrow from Veritas Vision from Vegas, take care. (techno music)

(upbeat electronic music) >> Announcer: Live from Las Vegas, it's the CUBE. Covering Veritas Vision 2017. Brought to you by Veritas. >> Welcome back to the Aria in Las Vegas everybody. This is the CUBE, the leader is live tech coverage. And we're here covering Veritas Vision, #VtasVision. I'm Dave Vellante with Stu Miniman. Bill Coleman is here. He's the CEO of Veritas. Bill, thanks for coming on the CUBE, good to see you. >> My pleasure, thank you for hosting us. >> Well, you're very welcome. And so, hot off the keynote, how do you feel, how's the show going for you so far? >> Well, I'll tell you what. I feel verit-awesome! >> (laughs) Verit-awesome is the watchword here. Get the crowd talk of Verit-awesome. I love that you started out with a little retrospective from last year. You used the term digital twin. We love that term, and you said it's sort of grown up now. I like to think the digital twins are sort of in their adolescent or even teenage years. The data is sort of out of control. We're not hearing today a message of legacy backup. We're hearing a vision of the future. Talk about that and what that vision looks like. >> Our customers obviously need data protection. They need resiliency. They need everything they've needed in the past. But that's not what they're interested in. That's assumed, that has to work. What they're interested in is the power of information. We like to say that our mission is to harness the power of information. And it's what's called digital transformation. Being able to use all that data out on the internet with all of their data, to change how they do business. To change what their products are. To change their supply chain. It's all about machine learning, predictive analytics, and the power of information. >> So I started in this business the same year that Veritas was born. And so I saw the ascendancy of Veritas and the many different forms that the company had taken. But I used to use Veritas as an example. You want to be like Veritas, with no hardware agenda. You want to be the glue that brings things together. And I saw in the conversation today a little bit of BEA-like thinking. The binder, if you will. Binding clouds together. My term, you guys didn't use that term, but to us, that's a critical value-add, and it's all around the data. You guys talked about digital business. To us, digital business means data, and it seems like we sort of share that common belief. >> Absolutely. You know, we've called this the information age for 50 years? But it's not been about information, it's been about technology. We finally have the ability to address that information, and do it over the internet, everywhere and everything. That's really what our vision is. You know, at BEA, we saw the internet emerging. And the world had to distribute, and take advantage of all that power across the whole world. And we invented that. But the key was, when I came up with the first concept of BEA in '93, I said, "You know, by the year 2000, "the network is going to be the computer." The network needs an operating system to make it all work. Well the concept here, and the reason that I actually took this job, is looking ahead ten years. Everything's going to be about information. No organization's going to be able to exist without leveraging the power of that information. Because that's the only way they'll bring their customer the value they need. That's the only way they compete, and without it, their business is just going to go down. >> Yeah, Bill, how are customers going to leverage data? You mentioned it's about the information, it's not about the technology. But you know, I look at customers. They've had storage people, they have network people. You know, "Oh, I'm excited about containers." We spent the last 15 years focused on virtualization. Is it Chief Data Officer? Or is it some other structure that customers, how are some of the leading customers that are going to be able to adopt this, how are they changing to be able to leverage that data and information? >> Well first, you have to understand, the technology has been complex, hard to use, hard to manage. As we saw earlier in the keynotes, it's like building a Rube Goldberg device. They had 27 different software products, and 14 different hardware products to sort of work together. Well, that's all disappearing. With cloud and the internet, it's becoming like a utility. You just subscribe to it. So that goes away. Now what you have to do, what we have to do, is we have to give them the tools that they can easily, visually look at that data, determine what's in that data, be maneuvering it, move it around, like in the movie, uh-- >> Stu: Minority Report? >> Minority Report. And literally, the things we talked about today, the demos we showed can lead to that. With machine learning predictive analytics, our biggest customers are already investing billions of dollars to do that. 'Cause they know if they don't jump ahead, their competition's going to do it. It's the power of information. >> So one of the things I might take away today was not only is Veritas hardware agnostic, but in many respects, you're workload agnostic. In other words, what I mean by that is, a lot of the events that Stu and I and the CUBE goes to, the enterprise companies are talking about on prem and that's where their business is, and much of your business, of course, is on prem. But we heard a message today of, "We really don't care where it lives. "We want to be the innovator "to help you get value out of your data "no matter where it lives." Now a lot of people will say that, but you really don't care where it lives. Is that true? >> And we can't. Look at, data's not just in an enterprise's data centers anymore. They're using clouds. We've surveyed our customers. Our average enterprise customer is using three public clouds already. And they have dozens of SASS applications like Salesforce, Workday, ServiceNow. Their data's in there too. That's really complex. What we've done is we've take and build the products that run in the cloud, across the cloud, to and from the cloud all by one policy orchestration. So you don't have to think about any of that. You can discover the data, categorize the data, manage the data and analyze the data all from one interface, end to end. >> So the obvious hard question follow-up is that what give you confidence that the cloud guys, once they get that workload, aren't going to just sort of usurp that agenda? What do you have to do to maintain that customer delight? >> Well, the first thing is the cloud, the public cloud providers, are our very close partners. You know, the first month we started this, Bill Voss, who heads storage for AWS, and I worked with him and Sun, came down to us and said, "Look, our customers need backup." You know, snapshots are great, but if somebody deletes a snapshot, it's gone. Your data's gone. How are you going to protect that? How are you going to analyze that data? When we want to partner with you? So we partnered with them. But the other thing he said was, "And if we do it exclusively, "the enterprises aren't going to use us." I had the CIO of one of the top five banks in the world tell me right after I started this, "We've got to be using three clouds simultaneously. "We never want to be stuck in the cloud." So the cloud service providers know that the enterprise customers want and demand that portability. And we become their, we're the premier partner for Amazon, for Microsoft, for Google, and for IBM. >> So, it's relationships. >> Right. >> But it's also innovation. >> Absolutely. >> So talk about where you are with R & D. You're purchased by a private equity company. You might have heard the narrative beforehand. A lot of the old private equity model is to suck all the cash out. Kind of the new private equity model is to invest, grow the valuation of the company. I think that's where I see you guys going. But talk about how you're able to innovate. Talk about the R & D mojo that you guys have. >> You had several questions there. >> Yeah (laughs). >> But let me start with that, with the last one. When we carved this company out 19 months ago, it became apparent that we weren't a real player in the cloud. We weren't in some of the more modern workloads. And we had to change rapidly. So, we created a strategy that led to this whole 360 data management integrated platform, software-defined storage. Integrating it with a restful API interface. And then in one year, we built seven new products from scratch that operate in the cloud, on prem, or across cloud. Automated that entire thing. We literally took the startup mentality. Now I've been a startup guy most of my life. I spent the last five and a half years before this funding early-stage startups, and the thing is being agile, and moving fast. We can move faster than anyone around now. We're a big company. Let's take Cloudpoint. We just introduced our Cloud Snapshot. That was a thought in somebody's eye in February. We defined what we needed to do, working with our customers. We put together the team. We built a micro-service end to end archistructure, and we shipped it, supporting the major, all the major cloud snapshot capability in five months, end to end. Totally new product. Now that is a startup mentality. >> Yeah, Bill, can you explain to us a little bit some of the internal plumbing of how you've managed that. On the one hand, Veritas, trusted company, strong engineering culture, product like NetBackup, you know. 15 years, leader in it's space, versus brand new stuff, whole new spaces. What staying the same, what's changing? How do you manage some of those transitions? Because you know, typical company, it's like, "We've got 7500 employees." It's like, "Well, I've got revenue streams "and product lines that I know how to do "and can keep chugging, but I've got the new stuff too." So how do you manage that internally? >> I've have a very simple philosophy of what it takes to lead a major company. You got to have a direction to go in, you have to draw higher-grade people, and you have to organize around the first two. But the key is where are you going? Where's the puck going to be in five to 10 years? And I call that the three V's. WHat's the vision of where the market's going to be? And number two, what's the value that brings to customer? The value that will justify their switching costs. And the third is, what are the values that you build your company on, that customers and partners will be able to trust and count on. So, when you start with that, we created the vision. It has to be a compelling and urgent vision. Ten years from now, all of our products are going to be obsolete. They're going to mostly be obsolete in five years. All of our traditional products. It's all going to be a microservice. Change on the fly, customers never have to upgrade kind of environment, right? There's an urgency there. And customers want to transform. There's an urgency there. The key is, based on your values, you have to develop a culture that embodies the norms to execute your strategy. And then you keep those things and balances. The cultural change has been the most profound and the most important thing we've done in this company. And this company now has a startup, win-in-the-marketplace, customer-first culture. >> So you laid out the vision. In terms of the value to customers you said, when you talk to your CIO customers and other customers, three things came out. Cut costs, deal with governance and compliance, and then help us with the digital transformation. Help us become a digital business, essentially. >> Yeah. >> So those two are pretty clear. Talk about the values that you espouse. What are they? >> So, when you start with values have to be built around what you're providing to a customer. And there's sort of three aspects of that. I'm going to give them the best possible products. I'm going to give them the lowers possible price, or I'm going to give them the best possible service that they can count on. I'm asking our customers to bet their future. So it has to be the third. So it starts with, we produce customer value, right? Then the next aspect of it is, they have to believe that what you're doing is going to be there for them, that it's going to really work. So our next one is, we're going to do that by inventing the future, to bring them the customer value. We're not going to look back and try to add features and functions where we are. We need to help them jump ahead to where they need to be. The third part of that, the pyramid there is customers are going to rely on you. So trust, accountability, ethics, integrity. Those three things come together. Then, we're all about employees, right? So, how do you empower employees to succeed, grow, and be accountable. And you put these values together, and the values will never change. The culture will evolve as strategy moves, and keeping in balance means you're going to have to reorganize on a continual basis around where you are in your strategy. I told this company, we're going to be reorganizing continuously, at least once a year. We're about to do a pretty fundamental reorganization in parts of our company. And this is second time in six months. But you have, you know, you have to be an agile organization. >> Bill, the venture community thinks that this is a hot space. There's a whole number of startups, highly focused. Obviously they're smaller than you, don't have the breadth of products. How do you look at the marketplace? What do you say about that aspect? >> Well, as I said, I spent five and a half years in early-stage venture. >> Yeah. >> We had the highest return fund for our first fund of multiple of any venture capital company. I really love that world. Venture capital is the the center of invention, the center of innovation in this country, in the world. You know, back in the 40s, 50s and 60s, you used to have these big corporate labs. You know, Bell Labs, Sarnoff Labs, et cetera. They don't exist anymore. It's all done by these. So they're inventing the future. Now the difference between the pre-dot-com era and after is, the vast majority of startups are, well, the the vast majority have failed. >> Will fail. (laughs) The vast majority of what's left are acquired, and a few go public, right? So to me, number one, they are the laboratory. They are in the areas that we that are merging, and that we don't necessarily have a core competence, we want to look on how to do that. In BEA, in six years, I did 24 acquisitions to build the company. I never acquired anything that came to us. It was all, here's part of our strategy, we need this competency, we need this time to market. How do we make it work, right? Matter of fact, there was a joke. BEA stood for Built Entirely on Acquisitions. (hosts laugh) >> Well, people used to, Larry Elison himself used to denegrate people for writing checks, not code. And then, of course, he changed the software business with (laughs) some big checks. Well, I wonder if you could talk a little bit more about the team. So when you took over here at Veritas, you mentioned off camera, you started with the team. How did you go about that? Maybe describe, add some color to the team. >> You know, like I said, one of the three pillars of my management is hire great people. And if you're going to transform a company, if you're going to do a turnaround, it has to start with the leadership team. Period, you can't start anywhere else. But you have to have a leadership team that shares the vision, shares the drive, knows how to work hard together. And when they walk in that room, there's not one thought about my organization or my career, or my compensation. Because they all know, if we make this work, all the rest can take care of itself. Now, when you're doing these sort of things, there are certain times in certain organizations, that people's skills are optimal. You know, the group that was managing this as part of Semantec, they weren't necessarily the best people to manage it as a change in culture, change in strategy. So I had to go out, and I brought in a couple of folks that I've worked with before. We brought in some real amazing people. Mike Palmer is just unbelievable at all dimensions of product development. Scott Genereux, he knows sales back, forward. He knows every customer out there by name, and he knows how to really motivate a sales force. Well, every member of my leadership team except Todd Hauschildt, the CIO, has come in with the same vision, the same, and of course that works down the organization as you're building. And that's how you change the culture. With that, here's the vision of where we're going. Here's the values, what we are going to do. This is how we're going to lead it. >> So major objectives. Obviously you want to keep moving fast. >> I presume you're going to, >> Yeah. >> You're reorganizing frequently to support that. But what are the main objectives that we should be looking for as outside observers over the next six, nine, 12, 18 months? We are changing the agenda of the information management industry. The first place is, for digital transformation, corporations have to switch. They have to get off what they're doing today ultimately and go to something new. And in an enterprise, that can only be one platform. You can't have two platforms deleting, moving data asynchronously. So, its going to be a major transformation. Now that has to be a platform. We've put the stake in the ground. We have that platform. Now, this is our battle to lose, because the incumbents in a transformation get to win if they're good enough. You know, in the disruption, only a startup can win. That's how I won at BEA, how we won at Sun. But this isn't disruption. Nobody's going to throw away all their data centers and jump into somebody before who said, "Oh, I've managed 100 terabytes. "Give me your 50 pedabytes." (Dave laughs) You know? And no customer is going to trust them. So this is our battle to win. We're changing the entire agenda with 360 data management. What we, our number one challenge is, we have to change the positioning in our own customers' minds, because they know us as the 30 years of that legacy, backup, recovery and archiving company. And it's really working. But that's number one. That's my number one objective. 'Cause the rest will take care of itself. >> And as a private company, do you feel like you're in a more advantageous position to do that, and why? >> Well, I don't think I could do this as other than a private company. Because it changes the economics dramatically. Also, at the same time, we're switching from mostly licensed revenue, to mostly rateable avenues, we move to subscription. In a public company, that's a, "Oh, our revenue's going to go down for awhile, "and so is our profits, but trust me." >> Hang with us. (laughs) >> Yeah, hang with us. There are companies like adobe that did that flawlessly, but it's not an easy thing to do. >> Yeah, it's not easy. >> And I'll tell you, I have the best partner in the world. When I, when we started this whole carveout, and I figured out, "Whoa, we don't have the right products. "We got to build this whole thing." I went to Carlisle with the strategy and the vision of what we needed to do. And I said, "Look, because pricing pressure is so high, "We're not going to be able to grow based on your plan." How you invested. "But if you want me to do that, "I can do it, and you need to invest this much more. "But I recommend that we invest as fast as we can "to get to digital transformation." They chose the third. They chose to, we're spending 99 million more dollars in R & D and go-to-market this year than was in the original plan. I wouldn't be able to do that in the public markets. >> Yeah. >> You know? But they are the perfect partner. They build for growth. They stay in two to four years after an IPO. Their return is based on multiples of growth, and that's what, so our goals are totally aligned, and aligned with what the customers are going to need. >> Bill, great story, I know you're super busy. A lot of customers to meet. So thanks very much for taking time out and joining us on the CUBE. >> Bill: This has been a pleasure. Thank you, >> You're welcome. >> Bill: you got me all stimulated. >> All right, good deal. All right, keep it right there everybody. Stu and I will be back with our next guest. This is the CUBE. We're live from Veritas Vision 2017. We'll be right back. (electronic rhythmic music)