>> TheCUBE presents Ignite 22 brought to you by Palo Alto Networks. >> Welcome back to Las Vegas, everyone. We're glad you're with us. This is theCUBE live at Palo Alto Ignite 22 at the MGM Grant in Las Vegas. Lisa Martin here with Dave Vellante, day one of our coverage. We've had great conversations. The cybersecurity landscape is so interesting Dave, it's such a challenging problem to solve but it's so diverse and dynamic at the same time. >> You know, Lisa theCUBE started in May of 2010 in Boston. We called it the chowder event, chowder and Lobster. It was a EMC world, 2010. BJ Jenkins, who's here, of course, was a longtime friend of theCUBE and made the, made the transition into from, well, it's still data, data to, to cyber. So >> True. And BJ is back with us. BJ Jenkins, president Palo Alto Networks great to have you back on theCUBE. >> It is great to be here in person on theCube >> Isn't it great? >> In Vegas. It's awesome. >> And we can tell by your voice will be, will be gentle. You, you've been in Vegas typical Vegas occupational hazard of losing the voice. >> Yeah. It was one of the benefits of Covid. I didn't lose my voice at home sitting talking to a TV. You lose it when you come to Vegas. >> Exactly. >> But it's a small price to pay. >> So things kick off yesterday with the partner summit. You had a keynote then, you had a customer, a CISO on stage. You had a keynote today, which we didn't get to see. But talk to us a little bit about the lay of the land. What are you hearing from CISOs, from CIOs as we know security is a board level conversation. >> Yeah, I, you know it's been an interesting three or four months here. Let me start with that. I think, cybersecurity in general is still front and center on CIOs and CISO's minds. It has to be, if you saw Wendy's presentation today and the threats out there companies have to have it front and center. I do think it's been interesting though with the macro uncertainty. We've taken to calling this year the revenge of the CFO and you know these deals in cybersecurity are still a top priority but they're getting finance and procurements, scrutiny which I think in this environment is a necessity but it's still a, you know, number one number two imperative no matter who you talked to, in my mind >> It was interesting what Nikesh was saying in the last conference call that, hey we just have to get more approvals. We know this. We're, we're bringing more go-to-market people on board. We, we have, we're filling the pipeline 'cause we know they're going to split up deals big deals go into smaller chunks. So the question I have for you is is how are you able to successfully integrate those people so that you can get ahead of that sort of macro transition? >> Yeah I, you know, I think there's two things I'd say about uncertain macro situations and Dave, you know how old I am. I'm pretty old. I've been through a lot of cycles. And in those cycles I've always found stronger companies with stronger value proposition separate themselves actually in uncertain, economic times. And so I think there's actually an opportunity here. The message tilts a little bit though where it's been about innovation and new threat vectors to one of you have 20, 30, 40 vendors you can consolidate become more effective in your security posture and save money on your TCOs. So one of the things as we bring people on board it's training them on that business value proposition. How do you take a customer who's got 20 or 30 tools take 'em down to 5 or 10 where Palo is more central and strategic and be able to demonstrate that value. So we do that through, we're making a huge investment in our people but macroeconomic times also puts some stronger people back on the market and we're able to incorporate them into the business. >> What are the conditions that are necessary for that consolidation? Like I would imagine if you're, if you're a big customer of a big, you know, competitor of yours that that migration is going to be harder than if you're dealing with lots of little point tools. Do those, do those point tools, are they sort of is it the end of the subscription? Is it just stuff that's off the books now? What's, the condition that is ripe for that kind of consolidation? >> Look, I think the challenge coming into this year was skills. And so customers had all of these point products. It required a lot more human intervention as Nikesh was talking about to integrate them or make them work. And as all of us know finding people with cybersecurity skills over the last 12 months has been incredibly hard. That drove, if you know, if you think about that a CIO and a CISO sitting there going, I have all all this investment in tools. I don't have the people to operate 'em. What do I need to do? What we tried to do is elevate that conversation because in a customer, everybody who's bought one of those, they they bought it to solve a problem. And there's people with affinity for that tool. They're not just going to say I want to get consolidated and give up my tool. They're going to wrap their arms around it. And so what we needed to do and this changed our ecosystem strategy too how we leverage partners. We needed to get into the CIO and CISO and say look at this chaos you have here and the challenges around people that it's, it's presenting you. We can help solve that by, by standardizing, consolidating taking that integration away from you as Nikesh talked about, and making it easier for your your high skill people to work on high skill, you know high challenges in there. >> Let chaos reign, and then reign in the chaos. >> Yes. >> Andy Grove. >> I was looking at some stats that there's 26 million developers but less than 3 million cybersecurity professionals. >> Talked about that skills gap and what CISOs and CIOs are facing is do you consider from a value prop perspective Palo Alto Networks to be a, a facilitator of helping organizations deal with that skills gap? >> I think there's a short term and a long term. I think Nikesh today talked about the long term that we'll never win this battle with human beings. We're going to have to win it with automation. That, that's the long term the short term right here and now is that people need people with cybersecurity skills. Now what we're trying to do, you know, is multifaceted. We work with universities to standardize programs to develop skills that people can come into the marketplace with. We run our own programs inside the company. We have a cloud academy program now where we take people high aptitude for sales and technical aptitude and we will put them through a six month boot camp on cloud and they'll come out of that ready to really work with the leading experts in cloud security. The third angle is partners, right, there are partners in the marketplace who want to drive their business into high services areas. They have people, they know how to train. We give them, we partner with them to give them training. Hopefully that helps solve some of the short-term gaps that are out there today. >> So you made the jump from data storage to security and >> Yeah. >> You know, network security, all kinds of security. What was that like? What you must have learned a lot in the last better part of a decade? >> Yeah. >> Take us through that. >> You know, so the first jump was from EMC. I was 15 years there to be CEO of Barracuda. And you know, it was interesting because EMC was, you know large enterprise for the most part. At Barracuda we had, you know 250,000 small and mid-size enterprises. And it was, it's interesting to get into security in small and mid-size businesses because, you know Wendy today was talking about nation states. For small and mid-size business, it's common thievery right? It's ransomware, it's, and, those customers don't have, you know, the human and financial resources to keep up with the threat factor. So, you know, Nikesh talked about how it's taken 'em four and a half years to get into cybersecurity. I remember my first week at Barracuda, I was talking with a customer who had, you know, breached data shut down. There wasn't much bitcoin back then so it was just a pure ransom. And I'm like, wow, this is, you know, incredible industry. So it's been a good, you know, transition for me. I still think data is at the heart of all of this. Right? And I have always believed there's a strong connection between the things I learned growing up at EMC and what I put into practice today at Palo Alto Networks. >> And how about a culture because I, you know I know have observed the EMC culture >> Yeah. >> And you were there in really the heyday. >> Yeah. >> Right? Which was an awesome place. And it seems like Palo Alto obviously, different times but you know, similar like laser focus on solving problems, you know, obviously great, you know value sellers, you know, you guys aren't the commodity >> Yeah. For Product. But there seemed to be some similarities from afar. I don't know Palo Alto as well as I know EMC. >> I think there's a lot. When I joined EMC, it was about, it was 2 billion in in revenue and I think when I left it was over 20, 20, 21. And, you know, we're at, you know hopefully 5, 5 5 in revenue. I feel like it's this very similar, there's a sense of urgency, there's an incredible focus on the customer. you know, Near and Moche are definitely different individuals but the both same kind of disruptive, Israeli force out there driving the business. There are a lot of similarities. I, you know, the passion, I feel privileged as a, you know go to market person that I have this incredible portfolio to go, you know, work with customers on. It's a lucky position to be in, but very I feel like it is a movie I've seen before. >> Yeah. And but, and the course, the challenges from the, the target that you're disrupting is different. It was, you know, EMC had a lot of big, you know IBM obviously was, you know, bigger target whereas you got thousands of, you know, smaller companies. >> Yes. >> And, and so that's a different dynamic but that's why the consolidation play is so important. >> Look at, that's why I joined Palo Alto Networks when I was at Barracuda for nine years. It just fascinated me, that there was 3000 plus players in security and why didn't security evolve like the storage market did or the server market or network where working >> Yeah, right. >> You know, two or three big gorillas came to, to dominate those markets. And it's, I think it's what Nikesh talked about today. There was a new problem in best of breed. It was always best of breed. You can never in security go in and, you know, say, Hey it's good I saved us some money but I got the third best product in the marketplace. And there was that kind of gap between products. I, believe in why I joined here I think this is my last gig is we have a chance to change that. And this is the first company as I look from the outside in that had best of breed as, you know Nikesh said 13 categories. >> Yeah. >> And you know, we're in the leaders quadrant and it's a conversation I have with customers. You don't have to sacrifice best of breed but get the benefits of a platform. And I, think that resonates today. I think we have a chance to change the industry from that viewpoint. >> Give us a little view of the voice of the customer. You had, was it Sabre? >> Yeah. >> That was on >> Scott Moser, The CISO from Sabre. >> Give us a view, what are you hearing from the voice of the customer? Obviously they're quite a successful customer but challenges, concerns, the partnership. >> Yeah. Look, I think security is similar to industries where we come up with magic marketing phrases and, you know, things to you know, make you want to procure our solutions. You know, zero trust is one. And you know, you'll talk to customers and they're like, okay, yes. And you know, the government, right? Joe, Joe Biden's putting out zero trust executive orders. And the, the problem is if you talk to customers, it's a journey. They have legacy infrastructure they have business drivers that you know they just don't deal with us. They've got to deal with the business side who's trying to make the money that keeps the, the company going. it's really helped them draw a map from where they're at today to zero trust or to a better security architecture. Or, you know, they're moving their apps into the cloud. How am I going to migrate? Right? Again, that discussion three years ago was around lift and shift, right? Today it's about, well, no I need cloud native developed apps to service the business the way I want to, I want to service it. How do I, so I, I think there's this element of a trusted partner and relationship. And again, I think this is why you can't have 40 or 50 of those. You got to start narrowing it down if you want to be able to meet and beat the threats that are out there for you. So I, you know, the customers, I see a lot of 'em. It's, here's where I'm at help me get here to a better position. And they know it's, you know Scott said in our keynote today, you don't just, you know have layer three firewall policies and decide, okay tomorrow I'm going to go to layer seven. That, that's not how it works. Right? There's, and, and by the way these things are a mission critical type areas. So there's got to be a game plan that you help customers go through to get there. >> Definitely. Last question, my last question for you is, is security being a board level conversation I was reading some stats from a survey I think it was the what's new in Cypress survey that that Palo Alto released today that showed that while significant numbers of organizations think they've got a cyber resiliency playbook, there's a lot of disconnect or lack of alignment at the boardroom. Are you in those conversations? How can you help facilitate that alignment between the executive team and the board when it comes to security being so foundational to any business? >> Yeah, it's, I've been on three, four public company boards. I'm on, I'm on two today. I would say four years ago, this was a almost a taboo topic. It was a, put your head in the sand and pray to God nothing happened. And you know, the world has changed significantly. And because of the number of breaches the impact it's had on brand, boards have to think about this in duty of care and their fiduciary duty. Okay. So then you start with a board that may not have the technical skills. The first problem the security industry had is how do I explain your risk profile in a way you can understand it. I'm, I'm on the board of Generac that makes home generators. It's a manufacturing, you know, company but they put Wifi modules in their boxes so that the dealers could help do the maintenance on 'em. And all of a sudden these things were getting attacked. Right? And they're being used for bot attacks. >> Yeah. >> Everybody on their board had a manufacturing background. >> Ah. >> So how do you help that board understand the risk they have that's what's changed over the last four years. It's a constant discussion. It's one I have with CISOs where they're like help us put it in layman's terms so they understand they know what we're doing and they feel confident but at the same time understand the marketplace better. And that's a journey for us. >> That Generac example is a great one because, you know, think about IOT Technologies. They've historically been air gaped >> Yes. >> By design. And all of a sudden the business comes in and says, "Hey we can put wifi in there", you know >> Connect it to a home Wifi system that >> Make our lives so much easier. Next thing you know, it's being used to attack. >> Yeah. >> So that's why, as you go around the world are you discerning, I know you were just in Japan are you discerning significant differences in sort of attitudes toward, towards cyber? Whether it's public policy, you know things like regulation where you, they don't want you sharing data, but as as a cyber company, you want to share that data with you know, public and private? >> Look it, I, I think around the world we see incredible government activity first of all. And I think given the position we're in we get to have some unique conversations there. I would say worldwide security is an imperative. I, no matter where I go, you know it's in front of everybody's mind. The, on the, the governance side, it's really what do we need to adapt to make sure we meet local regulations. And I, and I would just tell you Dave there's ways when you do that, and we talk with governments that because of how they want to do it reduce our ability to give them full insight into all the threats and how we can help them. And I do think over time governments understand that we can anonymize the data. There's, but that, that's a work in process. Definitely there is a balance. We need to have privacy, we need to have, you know personal security for people. But there's ways to collect that data in an anonymous way and give better security insight back into the architectures that are out there. >> All right. A little shift the gears here. A little sports question. We've had some great Boston's sports guests on theCUBE right? I mean, Randy Seidel, we were talking about him. Peter McKay, Snyk, I guess he's a competitor now but you know, there's no question got >> He got a little funding today. I saw that. >> Down round. But they still got a lot of money. Not of a down round, but they were, but yeah, but actually, you know, he was on several years ago and it was around the time they were talking about trading Brady. He said Never trade Brady. And he got that right. We, I think we can agree Brady's the goat. >> Yes. >> The big question I have for you is, Belichick. Do you ever question Has your belief in him as the greatest coach of all time wavered, you know, now that- No. Okay. >> Never. >> Weigh in on that. >> Never, he says >> Still the Goat. >> I'll give you my best. You know, never In Bill we trust. >> Okay. Still. >> All right >> I, you know, the NFL is a unique property that's designed for parody and is designed, I mean actively designed to not let Mr. Craft and Bill Belichick do what they do every year. I feel privileged as a Boston sports fan that in our worst years we're in the seventh playoff spot. And I have a lot of family in Chicago who would kill for that position, by the way. And you know, they're in perpetual rebuilding. And so look, and I think he, you know the way he's been able to manage the cap and the skill levels, I think we have a top five defense. There's different ways to win titles. And if I, you know, remember in Brady's last title with Boston, the defense won us that Super Bowl. >> Well thanks for weighing in on that because there's a lot of crazy talk going on. Like, 'Hey, if he doesn't beat Arizona, he's got to go.' I'm like, what? So, okay, I'm sometimes it takes a good good loyal fan who's maybe, you know, has >> The good news in Boston is we're emotional fans too so I understand you got to keep the long term long term in mind. And we're, we're in a privileged position in Boston. We've got Celtics, we've got Bruins we've got the Patriots right on the edge of the playoffs and we need the Red Sox to get to work. >> Yeah, no, you know they were last, last year so maybe they're going to win it all like they usually do. So >> Fingers crossed. >> Crazy worst to first. >> Exactly. Well you said, in Bill we trust it sounds like from our conversation in BJ we trust from the customers, the partners. >> I hope so. >> Thank you so much BJ, for coming back on theCUBE giving us the lay of the land, what's new, the voice of the customer and how Palo Alto was really differentiated in the market. We always appreciate your, coming on the show you >> Honor and privilege seeing you here. Thanks. >> You may be thinking that you were watching ESPN just now but you know, we call ourselves the ESPN at Tech News. This is Lisa Martin for Dave Vellante and our guest. You're watching theCUBE, the Leader and live emerging in enterprise tech coverage. (upbeat music)

(soft techno upbeat music) >> Hi there. Welcome back to Las Vegas. This is Dave Villante with Paul Gillon. Reinvent day one and a half. We started last night, Monday, theCUBE after dark. Now we're going wall to wall. Today. Today was of course the big keynote, Adam Selipsky, kind of the baton now handing, you know, last year when he did his keynote, he was very new. He was sort of still getting his feet wet and finding his guru swing. Settling in a little bit more this year, learning a lot more, getting deeper into the tech, but of course, sharing the love with other leaders like Peter DeSantis. Tomorrow's going to be Swamy in the keynote. Adrian Cockcroft is here. Former AWS, former network Netflix CTO, currently an analyst. You got your own firm now. You're out there. Great to see you again. Thanks for coming on theCUBE. >> Yeah, thanks. >> We heard you on at Super Cloud, you gave some really good insights there back in August. So now as an outsider, you come in obviously, you got to be impressed with the size and the ecosystem and the energy. Of course. What were your thoughts on, you know what you've seen so far, today's keynotes, last night Peter DeSantis, what stood out to you? >> Yeah, I think it's great to be back at Reinvent again. We're kind of pretty much back to where we were before the pandemic sort of shut it down. This is a little, it's almost as big as the, the largest one that we had before. And everyone's turned up. It just feels like we're back. So that's really good to see. And it's a slightly different style. I think there were was more sort of video production things happening. I think in this keynote, more storytelling. I'm not sure it really all stitched together very well. Right. Some of the stories like, how does that follow that? So there were a few things there and some of there were spelling mistakes on the slides, you know that ELT instead of ETL and they spelled ZFS wrong and something. So it just seemed like there was, I'm not quite sure just maybe a few things were sort of rushed at the last minute. >> Not really AWS like, was it? It's kind of remind the Patriots Paul, you know Bill Belichick's teams are fumbling all over the place. >> That's right. That's right. >> Part of it may be, I mean the sort of the market. They have a leader in marketing right now but they're going to have a CMO. So that's sort of maybe as lack of a single threaded leader for this thing. Everything's being shared around a bit more. So maybe, I mean, it's all fixable and it's mine. This is minor stuff. I'm just sort of looking at it and going there's a few things that looked like they were not quite as good as they could have been in the way it was put together. Right? >> But I mean, you're taking a, you know a year of not doing Reinvent. Yeah. Being isolated. You know, we've certainly seen it with theCUBE. It's like, okay, it's not like riding a bike. You know, things that, you know you got to kind of relearn the muscle memories. It's more like golf than is bicycle riding. >> Well I've done AWS keynotes myself. And they are pretty much scrambled. It looks nice, but there's a lot of scrambling leading up to when it actually goes. Right? And sometimes you can, you sometimes see a little kind of the edges of that, and sometimes it's much more polished. But you know, overall it's pretty good. I think Peter DeSantis keynote yesterday was a lot of really good meat there. There was some nice presentations, and some great announcements there. And today I was, I thought I was a little disappointed with some of the, I thought they could have been more. I think the way Andy Jesse did it, he crammed more announcements into his keynote, and Adam seems to be taking sort of a bit more of a measured approach. There were a few things he picked up on and then I'm expecting more to be spread throughout the rest of the day. >> This was more poetic. Right? He took the universe as the analogy for data, the ocean for security. Right? The Antarctic was sort of. >> Yeah. It looked pretty, >> yeah. >> But I'm not sure that was like, we're not here really to watch nature videos >> As analysts and journalists, You're like, come on. >> Yeah, >> Give it the meat >> That was kind the thing, yeah, >> It has always been the AWS has always been Reinvent has always been a shock at our approach. 100, 150 announcements. And they're really, that kind of pressure seems to be off them now. Their position at the top of the market seems to be unshakeable. There's no clear competition that's creeping up behind them. So how does that affect the messaging you think that AWS brings to market when it doesn't really have to prove that it's a leader anymore? It can go after maybe more of the niche markets or fix the stuff that's a little broken more fine tuning than grandiose statements. >> I think so AWS for a long time was so far out that they basically said, "We don't think about the competition, we are listen to the customers." And that was always the statement that works as long as you're always in the lead, right? Because you are introducing the new idea to the customer. Nobody else got there first. So that was the case. But in a few areas they aren't leading. Right? You could argue in machine learning, not necessarily leading in sustainability. They're not leading and they don't want to talk about some of these areas and-- >> Database. I mean arguably, >> They're pretty strong there, but the areas when you are behind, it's like they kind of know how to play offense. But when you're playing defense, it's a different set of game. You're playing a different game and it's hard to be good at both. I think and I'm not sure that they're really used to following somebody into a market and making a success of that. So there's something, it's a little harder. Do you see what I mean? >> I get opinion on this. So when I say database, David Foyer was two years ago, predicted AWS is going to have to converge somehow. They have no choice. And they sort of touched on that today, right? Eliminating ETL, that's one thing. But Aurora to Redshift. >> Yeah. >> You know, end to end. I'm not sure it's totally, they're fully end to end >> That's a really good, that is an excellent piece of work, because there's a lot of work that it eliminates. There's are clear pain points, but then you've got sort of the competing thing, is like the MongoDB and it's like, it's just a way with one database keeps it simple. >> Snowflake, >> Or you've got on Snowflake maybe you've got all these 20 different things you're trying to integrate at AWS, but it's kind of like you have a bag of Lego bricks. It's my favorite analogy, right? You want a toy for Christmas, you want a toy formula one racing car since that seems to be the theme, right? >> Okay. Do you want the fully built model that you can play with right now? Or do you want the Lego version that you have to spend three days building. Right? And AWS is the Lego technique thing. You have to spend some time building it, but once you've built it, you can evolve it, and you'll still be playing those are still good bricks years later. Whereas that prebuilt to probably broken gathering dust, right? So there's something about having an vulnerable architecture which is harder to get into, but more durable in the long term. And so AWS tends to play the long game in many ways. And that's one of the elements that they do that and that's good, but it makes it hard to consume for enterprise buyers that are used to getting it with a bow on top. And here's the solution. You know? >> And Paul, that was always Andy Chassy's answer to when we would ask him, you know, all these primitives you're going to make it simpler. You see the primitives give us the advantage to turn on a dime in the marketplace. And that's true. >> Yeah. So you're saying, you know, you take all these things together and you wrap it up, and you put a snowflake on top, and now you've got a simple thing or a Mongo or Mongo atlas or whatever. So you've got these layered platforms now which are making it simpler to consume, but now you're kind of, you know, you're all stuck in that ecosystem, you know, so it's like what layer of abstractions do you want to tie yourself to, right? >> The data bricks coming at it from more of an open source approach. But it's similar. >> We're seeing Amazon direct more into vertical markets. They spotlighted what Goldman Sachs is doing on their platform. They've got a variety of platforms that are supposedly targeted custom built for vertical markets. How do successful do you see that play being? Is this something that the customers you think are looking for, a fully integrated Amazon solution? >> I think so. There's usually if you look at, you know the MongoDB or data stacks, or the other sort of or elastic, you know, they've got the specific solution with the people that really are developing the core technology, there's open source equivalent version. The AWS is running, and it's usually maybe they've got a price advantage or it's, you know there's some data integration in there or it's somehow easier to integrate but it's not stopping those companies from growing. And what it's doing is it's endorsing that platform. So if you look at the collection of databases that have been around over the last few years, now you've got basically Elastic Mongo and Cassandra, you know the data stacks as being endorsed by the cloud vendors. These are winners. They're going to be around for a very long time. You can build yourself on that architecture. But what happened to Couch base and you know, a few of the other ones, you know, they don't really fit. Like how you going to bait? If you are now becoming an also ran, because you didn't get cloned by the cloud vendor. So the customers are going is that a safe place to be, right? >> But isn't it, don't they want to encourage those partners though in the name of building the marketplace ecosystem? >> Yeah. >> This is huge. >> But certainly the platform, yeah, the platform encourages people to do more. And there's always room around the edge. But the mainstream customers like that really like spending the good money, are looking for something that's got a long term life to it. Right? They're looking for a long commitment to that technology and that it's going to be invested in and grow. And the fact that the cloud providers are adopting and particularly AWS is adopting some of these technologies means that is a very long term commitment. You can base, you know, you can bet your future architecture on that for a decade probably. >> So they have to pick winners. >> Yeah. So it's sort of picking winners. And then if you're the open source company that's now got AWS turning up, you have to then leverage it and use that as a way to grow the market. And I think Mongo have done an excellent job of that. I mean, they're top level sponsors of Reinvent, and they're out there messaging that and doing a good job of showing people how to layer on top of AWS and make it a win-win both sides. >> So ever since we've been in the business, you hear the narrative hardware's going to die. It's just, you know, it's commodity and there's some truth to that. But hardware's actually driving good gross margins for the Cisco's of the world. Storage companies have always made good margins. Servers maybe not so much, 'cause Intel sucked all the margin out of it. But let's face it, AWS makes most of its money. We know on compute, it's got 25 plus percent operating margins depending on the seasonality there. What do you think happens long term to the infrastructure layer discussion? Okay, commodity cloud, you know, we talk about super cloud. Do you think that AWS, and the other cloud vendors that infrastructure, IS gets commoditized and they have to go up market or you see that continuing I mean history would say that still good margins in hardware. What are your thoughts on that? >> It's not commoditizing, it's becoming more specific. We've got all these accelerators and custom chips now, and this is something, this almost goes back. I mean, I was with some micro systems 20,30 years ago and we developed our own chips and HP developed their own chips and SGI mips, right? We were like, the architectures were all squabbling of who had the best processor chips and it took years to get chips that worked. Now if you make a chip and it doesn't work immediately, you screwed up somewhere right? It's become the technology of building these immensely complicated powerful chips that has become commoditized. So the cost of building a custom chip, is now getting to the point where Apple and Amazon, your Apple laptop has got full custom chips your phone, your iPhone, whatever and you're getting Google making custom chips and we've got Nvidia now getting into CPUs as well as GPUs. So we're seeing that the ability to build a custom chip, is becoming something that everyone is leveraging. And the cost of doing that is coming down to startups are doing it. So we're going to see many, many more, much more innovation I think, and this is like Intel and AMD are, you know they've got the compatibility legacy, but of the most powerful, most interesting new things I think are going to be custom. And we're seeing that with Graviton three particular in the three E that was announced last night with like 30, 40% whatever it was, more performance for HPC workloads. And that's, you know, the HPC market is going to have to deal with cloud. I mean they are starting to, and I was at Supercomputing a few weeks ago and they are tiptoeing around the edge of cloud, but those supercomputers are water cold. They are monsters. I mean you go around supercomputing, there are plumbing vendors on the booth. >> Of course. Yeah. >> Right? And they're highly concentrated systems, and that's really the only difference, is like, is it water cooler or echo? The rest of the technology stack is pretty much off the shelf stuff with a few tweets software. >> You point about, you know, the chips and what AWS is doing. The Annapurna acquisition. >> Yeah. >> They're on a dramatically different curve now. I think it comes down to, again, David Floyd's premise, really comes down to volume. The arm wafer volumes are 10 x those of X 86, volume always wins. And the economics of semis. >> That kind of got us there. But now there's also a risk five coming along if you, in terms of licensing is becoming one of the bottlenecks. Like if the cost of building a chip is really low, then it comes down to licensing costs and do you want to pay the arm license And the risk five is an open source chip set which some people are starting to use for things. So your dis controller may have a risk five in it, for example, nowadays, those kinds of things. So I think that's kind of the the dynamic that's playing out. There's a lot of innovation in hardware to come in the next few years. There's a thing called CXL compute express link which is going to be really interesting. I think that's probably two years out, before we start seeing it for real. But it lets you put glue together entire rack in a very flexible way. So just, and that's the entire industry coming together around a single standard, the whole industry except for Amazon, in fact just about. >> Well, but maybe I think eventually they'll get there. Don't use system on a chip CXL. >> I have no idea whether I have no knowledge about whether going to do anything CXL. >> Presuming I'm not trying to tap anything confidential. It just makes sense that they would do a system on chip. It makes sense that they would do something like CXL. Why not adopt the standard, if it's going to be as the cost. >> Yeah. And so that was one of the things out of zip computing. The other thing is the low latency networking with the elastic fabric adapter EFA and the extensions to that that were announced last night. They doubled the throughput. So you get twice the capacity on the nitro chip. And then the other thing was this, this is a bit technical, but this scalable datagram protocol that they've got which basically says, if I want to send a message, a packet from one machine to another machine, instead of sending it over one wire, I consider it over 16 wires in parallel. And I will just flood the network with all the packets and they can arrive in any order. This is why it isn't done normally. TCP is in order, the packets come in order they're supposed to, but this is fully flooding them around with its own fast retry and then they get reassembled at the other end. So they're not just using this now for HPC workloads. They've turned it on for TCP for just without any change to your application. If you are trying to move a large piece of data between two machines, and you're just pushing it down a network, a single connection, it takes it from five gigabits per second to 25 gigabits per second. A five x speed up, with a protocol tweak that's run by the Nitro, this is super interesting. >> Probably want to get all that AIML that stuff is going on. >> Well, the AIML stuff is leveraging it underneath, but this is for everybody. Like you're just copying data around, right? And you're limited, "Hey this is going to get there five times faster, pushing a big enough chunk of data around." So this is turning on gradually as the nitro five comes out, and you have to enable it at the instance level. But it's a super interesting announcement from last night. >> So the bottom line bumper sticker on commoditization is what? >> I don't think so. I mean what's the APIs? Your arm compatible, your Intel X 86 compatible or your maybe risk five one day compatible in the cloud. And those are the APIs, right? That's the commodity level. And the software is now, the software ecosystem is super portable across those as we're seeing with Apple moving from Intel to it's really not an issue, right? The software and the tooling is all there to do that. But underneath that, we're going to see an arms race between the top providers as they all try and develop faster chips for doing more specific things. We've got cranium for training, that instance has they announced it last year with 800 gigabits going out of a single instance, 800 gigabits or no, but this year they doubled it. Yeah. So 1.6 terabytes out of a single machine, right? That's insane, right? But what you're doing is you're putting together hundreds or thousands of those to solve the big machine learning training problems. These super, these enormous clusters that they're being formed for doing these massive problems. And there is a market now, for these incredibly large supercomputer clusters built for doing AI. That's all bandwidth limited. >> And you think about the timeframe from design to tape out. >> Yeah. >> Is just getting compressed It's relative. >> It is. >> Six is going the other way >> The tooling is all there. Yeah. >> Fantastic. Adrian, always a pleasure to have you on. Thanks so much. >> Yeah. >> Really appreciate it. >> Yeah, thank you. >> Thank you Paul. >> Cheers. All right. Keep it right there everybody. Don't forget, go to thecube.net, you'll see all these videos. Go to siliconangle.com, We've got features with Adam Selipsky, we got my breaking analysis, we have another feature with MongoDB's, Dev Ittycheria, Ali Ghodsi, as well Frank Sluman tomorrow. So check that out. Keep it right there. You're watching theCUBE, the leader in enterprise and emerging tech, right back. (soft techno upbeat music)

>> Announcer: From around the globe, it's theCUBE. With digital coverage of VMworld 2020, brought to you by VMware and its ecosystem partners. >> Welcome back, I'm Stu Miniman. This is theCUBE's coverage of VMworld 2020 of course, happening virtually. And there are certain people that we talk to every year at theCUBE, and this guest, I believe, has been on theCUBE at VMworld more than any others. It's actually not Pat Gelsinger, Eric Herzog. He is the chief marketing officer and vice president of global storage channels at IBM. Eric, Mr. Zoginstor, welcome back to theCUBE, nice to see you. >> Thank you very much, Stu. IBM always enjoys hanging with you, John, and Dave. And again, glad to be here, although not in person this time at VMworld 2020 virtual. Thanks again for having IBM. >> Alright, so, you know, some things are the same, others, very different. Of course, Eric, IBM, a long, long partner of VMware's. Why don't you set up for us a little bit, you know, 2020, the major engagements, what's new with IBM and VMware? >> So, a couple of things, first of all, we have made our Spectrum Virtualize software, software defined block storage work in virtual machines, both in AWS and IBM Cloud. So we started with IBM Cloud and then earlier this year with AWS. So now we have two different cloud platforms where our Spectrum Virtualize software sits in a VM at the cloud provider. The other thing we've done, of course, is V7 support. In fact, I've done several VMUGs. And in fact, my session at VMworld is going to talk about both our support for V7 but also what we're doing with containers, CSI, Kubernetes overall, and how we can support that in a virtual VMware environment, and also we're doing with traditional ESX and VMware configurations as well. And of course, out to the cloud, as I just talked about. >> Yeah, that discussion of hybrid cloud, Eric, is one that we've been hearing from IBM for a long time. And VMware has had that message, but their cloud solutions have really matured. They've got a whole group going deep on cloud native. The Amazon solutions have been something that they've been partnering, making sure that, you know, data protection, it can span between, you know, the traditional data center environment where VMware is so dominant, and the public clouds. You're giving a session on some of those hybrid cloud solutions, so share with us a little bit, you know, where do the visions completely agree? What's some of the differences between what IBM is doing and maybe what people are hearing from VMware? >> Well, first of all, our solutions don't always require VMware to be installed. So for example, if you're doing it in a container environment, for example, with Red Hat OpenShift, that works slightly different. Not that you can't run Red Hat products inside of a virtual machine, which you can, but in this case, I'm talking Red Hat native. We also of course do VMware native and support what VMware has announced with their Kubernetes based solutions that they've been talking about since VMworld last year, obviously when Pat made some big announcements onstage about what they were doing in the container space. So we've been following that along as well. So from that perspective, we have agreement on a virtual machine perspective and of course, what VMware is doing with the container space. But then also a slightly different one when we're doing Red Hat OpenShift as a native configuration, without having a virtual machine involved in that configuration. So those are both the commonalities and the differences that we're doing with VMware in a hybrid cloud configuration. >> Yeah. Eric, you and I both have some of those scars from making sure that storage works in a virtual environment. It took us about a decade to get things to really work at the VM level. Containers, it's been about five years, it feels like we've made faster progress to make sure that we can have stateful environments, we can tie up with storage, but give us a little bit of a look back as to what we've learned and how we've made sure that containerized, Kubernetes environments, you know, work well with storage for customers today. >> Well, I think there's a couple of things. First of all, I think all the storage vendors learn from VMware. And then the expansion of virtual environments beyond VMware to other virtual environments as well. So I think all the storage vendors, including IBM learned through that process, okay, when the next thing comes, which of course in this case happens to be containers, both in a VMware environment, but in an open environment with the Kubernetes management framework, that you need to be able to support it. So for example, we have done several different things. We support persistent volumes in file block and object store. And we started with that almost three years ago on the block side, then we added the file side and now the object storage side. We also can back up data that's in those containers, which is an important feature, right? I am sitting there and I've got data now and persistent volume, but I got to back it up as well. So we've announced support for container based backup either with Red Hat OpenShift or in a generic Kubernetes environment, because we're realistic at IBM. We know that you have to exist in the software infrastructure milieu, and that includes VMware and competitors of VMware. It includes Red Hat OpenShift, but also competitors to Red Hat. And we've made sure that we support whatever the end user needs. So if they're going with Red Hat, great. If they're going with a generic container environment, great. If they're going to use VMware's container solutions, great. And on the virtualization engines, the same thing. We started with VMware, but also have added other virtualization engines. So you think the storage community as a whole and IBM in particular has learned, we need to be ready day one. And like I said, three years ago, we already had persistent volume support for block store. It's still the dominant storage and we had that three years ago. So for us, that would be really, I guess, two years from what you've talked about when containers started to take off. And within two years we had something going that was working at the end user level. Our sales team could sell our business partners. As you know, many of the business partners are really rallying around containers, whether it be Red Hat or in what I'll call a more generic environment as well. They're seeing the forest through the trees. I do think when you look at it from an end user perspective, though, you're going to see all three. So, particularly in the Global Fortune 1000, you're going to see Red Hat environments, generic Kubernetes environments, VMware environments, just like you often see in some instances, heterogeneous virtualization environments, and you're still going to see bare metal. So I think it's going to vary by application workload and use case. And I think all, I'd say midsize enterprise up, let's say, $5 billion company and up, probably will have at least two, if not all three of those environments, container, virtual machine, and bare metal. So we need to make sure that at IBM we support all those environments to keep those customers happy. >> Yeah, well, Eric, I think anybody, everybody in the industry knows, IBM can span those environments, you know, support through generations. And very much knows that everything in IT tends to be additive. You mentioned customers, Eric, you talk to a lot of customers. So bring us inside, give us a couple examples if you would, how are they dealing with this transition? For years we've been talking about, you know, enabling developers, having them be tied more tightly with what the enterprise is doing. So what are you seeing from some of your customers today? >> Well, I think the key thing is they'd like to use data reuse. So, in this case, think of a backup, a snap or replica dataset, which is real world data, and being able to use that and reuse that. And now the storage guys want to make sure they know who's, if you will, checked it out. We do that with our Spectrum Copy Data Management. You also have, of course, integration with the Ansible framework, which IBM supports, in fact, we'll be announcing some additional support for more features in Ansible coming at the end of October. We'll be doing a large launch, very heavily on containers. Containers and primary storage, containers in hybrid cloud environments, containers in big data and AI environments, and containers in the modern data protection and cyber resiliency space as well. So we'll be talking about some additional support in this case about Ansible as well. So you want to make sure, one of the key things, I think, if you're a storage guy, if I'm the VP of infrastructure, or I'm the CIO, even if I'm not a storage person, in fact, if you think about it, I'm almost 70 now. I have never, ever, ever, ever met a CIO who used to be a storage guy, ever. Whether I, I've been with big companies, I was at EMC, I was at Seagate Maxtor, I've been at IBM actually twice. I've also done seven startups, as you guys know at theCUBE. I have never, ever met a CIO who used to be a storage person. Ever, in all those years. So, what appeals to them is, how do I let the dev guys and the test guys use that storage? At the same time, they're smart enough to know that the software guys and the test guys could actually screw up the storage, lose the data, or if they don't lose the data, cost them hundreds of thousands to millions of dollars because they did something wrong and they have to reconfigure all the storage solutions. So you want to make sure that the CIO is comfortable, that the dev and the test teams can use that storage properly. It's a part of what Ansible's about. You want to make sure that you've got tight integration. So for example, we announced a container native version of our Spectrum Discover software, which gives you comprehensive metadata, cataloging and indexing. Not only for IBM's scale-out file, Spectrum Scale, not only for IBM object storage, IBM cloud object storage, but also for Amazon S3 and also for NetApp filers and also for EMC Isilon. And it's a container native. So you want to make sure in that case, we have an API. So the AI software guys, or the big data software guys could interface with that API to Spectrum Discover, let them do all the work. And we're talking about a piece of software that can traverse billions of objects in two seconds, billions of them. And is ideal to use in solutions that are hundreds of petabytes, up into multiple exabytes. So it's a great way that by having that API where the CIO is confident that the software guys can use the API, not mess up the storage because you know, the storage guys and the data scientists can configure Spectrum Discover and then save it as templates and run an AI workload every Monday, and then run a big data workload every Tuesday, and then Wednesday run a different AI workload and Thursday run a different big data. And so once they've set that up, everything is automated. And CIOs love automation, and they really are sensitive. Although they're all software guys, they are sensitive to software guys messing up the storage 'cause it could cost them money, right? So that's their concern. We make it easy. >> Absolutely, Eric, you know, it'd be lovely to say that storage is just invisible, I don't need to think about it, but when something goes wrong, you need those experts to be able to dig in. You spent some time talking about automation, so critically important. How about the management layer? You know, you think back, for years it was, vCenter would be the place that everything can plug in. You could have more generalists using it. The HCI waves were people kind of getting away from being storage specialists. Today VMware has, of course vCenter's their main estate, but they have Tanzu. On the IBM and Red Hat side, you know, this year you announced the Advanced Cluster Management. What's that management landscape look like? How does the storage get away from managing some of the bits and bytes and, you know, just embrace more of that automation that you talked about? >> So in the case of IBM, we make sure we can support both. We need to appeal to the storage nerd, the storage geek if you will. The same time to a more generalist environment, whether it be an infrastructure manager, whether it be some of the software guys. So for example, we support, obviously vCenter. We're going to be supporting all of the elements that are going to happen in a container environment that VMware is doing. We have hot integration and big time integration with Red Hat's management framework, both with Ansible, but also in the container space as well. We're announcing some things that are coming again at the end of October in the container space about how we interface with the Red Hat management schema. And so you don't always have to have the storage expert manage the storage. You can have the Red Hat administrator, or in some cases, the DevOps guys do it. So we're making sure that we can cover both sides of the fence. Some companies, this just my personal belief, that as containers become commonplace while the software guys are going to want to still control it, there eventually will be a Red Hat/container admin, just like all the big companies today have VMware admins. They all do. Or virtualization admins that cover VMware and VMware's competitors such as Hyper-V. They have specialized admins to run that. And you would argue, VMware is very easy to use, why aren't the software guys playing with it? 'Cause guess what? Those VMs are sitting on servers containing both apps and data. And if the software guy comes in to do something, messes it up, so what have of the big entities done? They've created basically a virtualization admin layer. I think that over time, either the virtualization admins become virtualization/container admins, or if it's a big enough for both estates, there'll be container admins at the Global Fortune 500, and they'll also be virtualization admins. And then the software guys, the devOps guys will interface with that. There will always be a level of management framework. Which is why we integrate, for example, with vCenter, what we're doing with Red Hat, what we do with generic Kubernetes, to make sure that we can integrate there. So we'll make sure that we cover all areas because a number of our customers are very large, but some of our customers are very small. In fact, we have a company that's in the software development space for autonomous driving. They have over a hundred petabytes of IBM Spectrum Scale in a container environment. So that's a small company that's gone all containers, at the same time, we have a bunch of course, Global Fortune 1000s where IBM plays exceedingly well that have our products. And they've got some stuff sitting in VMware, some such sitting in generic Kubernetes, some stuff sitting in Red Hat OpenShift and some stuff still in bare metal. And in some cases they don't want their software people to touch it, in other cases, these big accounts, they want their software people empowered. So we're going to make sure we could support both and both management frameworks. Traditional storage management framework with each one of our products and also management frameworks for virtualization, which we've already been doing. And now management frame first with container. We'll make sure we can cover all three of those bases 'cause that's what the big entities will want. And then in the smaller names, you'll have to see who wins out. I mean, they may still use three in a small company, you really don't know, so you want to make sure you've got everything covered. And it's very easy for us to do this integration because of things we've already historically done, particularly with the virtualization environment. So yes, the interstices of the integration are different, but we know here's kind of the process to do the interconnectivity between a storage management framework and a generic management framework, in, originally of course, vCenter, and now doing it for the container world as well. So at least we've learned best practices and now we're just tweaking those best practices in the difference between a container world and a virtualization world. >> Eric, VMworld is one of the biggest times of the year, where we all get together. I know how busy you are going to the show, meeting with customers, meeting with partners, you know, walking the hallways. You're one of the people that traveled more than I did pre-COVID. You know, you're always at the partner shows and meeting with people. Give us a little insight as to how you're making sure that, partners and customers, those conversations are still happening. We understand everything over video can be a little bit challenging, but, what are you seeing here in 2020? How's everybody doing? >> Well, so, a couple of things. First of all, I already did two partner meetings today. (laughs) And I have an end user meeting, two end user meetings tomorrow. So what we've done at IBM is make sure we do a couple things. One, short and to the point, okay? We have automated tools to actually show, drawing, just like the infamous walk up to the whiteboard in a face to face meeting, we've got that. We've also now tried to make sure everybody is being overly inundated with WebEx. And by the way, there's already a lot of WebEx anyway. I can think of meeting I had with a telco, one of the Fortune 300, and this was actually right before Thanksgiving. I was in their office in San Jose, but they had guys in Texas and guys in the East Coast all on. So we're still over WebEx, but it also was a two and a half hour meeting, actually almost a three hour meeting. And both myself and our Flash CTO went up to the whiteboard, which you could then see over WebEx 'cause they had a camera showing up onto the whiteboard. So now you have to take that and use integrated tools. One, but since people are now, I would argue, over WebEx. There is a different feel to doing the WebEx than when you're doing it face to face. We have to fly somewhere, or they have to fly somewhere. We have to even drive somewhere, so in between meetings, if you're going to do four customer calls, Stu, as you know, I travel all over the world. So I was in Sweden actually right before COVID. And in one day, the day after we had a launch, we launched our new Flash System products in February on the 11th, on February 12th, I was still in Stockholm and I had two partner meetings and two end user meetings. But the sales guy was driving me around. So in between the meetings, you'd be in the car for 20 minutes or half an hour. So it connects different when you can do WebEx after WebEx after WebEx with basically no break. So you have to be sensitive to that when you're talking to your partners, sensitive of that when you're talking to the customers sensitive when you're talking to the analysts, such as you guys, sensitive when you're talking to the press and all your various constituents. So we've been doing that at IBM, really, since the COVID thing got started, is coming up with some best practices so we don't overtax the end users and overtax our channel partners. >> Yeah, Eric, the joke I had on that is we're all following the Bill Belichick model now, no days off, just meeting, meeting, meeting every day, you can stack them up, right? You used to enjoy those downtimes in between where you could catch up on a call, do some things. I had to carve out some time to make sure that stack of books that normally I would read in the airports or on flights, everything, you know. I do enjoy reading a book every now and again, so. Final thing, I guess, Eric. Here at VMworld 2020, you know, give us final takeaways that you want your customers to have when it comes to IBM and VMware. >> So a couple of things, A, we were tightly integrated and have been tightly integrated for what they've been doing in their traditional virtualization environment. As they move to containers we'll be tightly integrated with them as well, as well as other container platforms, not just from IBM with Red Hat, but again, generic Kubernetes environments with open source container configurations that don't use IBM Red Hat and don't use VMware. So we want to make sure that we span that. In traditional VMware environments, like with Version 7 that came out, we make sure we support it. In fact, VMware just announced support for NVMe over Fibre Channel. Well, we've been shipping NVMe over Fibre Channel for just under two years now. It'll be almost two years, well, it will be two years in October. So we're sitting here in September, it's almost been two years since we've been shipping that. But they haven't supported it, so now of course we actually, as part of our launch, I pre say something, as part of our launch, the last week of October at IBM's TechU it'll be on October 27th, you can join for free. You don't need to attend TechU, we'll have a free registration page. So just follow Zoginstor or look at my LinkedIns 'cause I'll be posting shortly when we have the link, but we'll be talking about things that we're doing around V7, with support for VMware's announcement of NVMe over Fibre Channel, even though we've had it for two years coming next month. But they're announcing support, so we're doing that as well. So all of those sort of checkbox items, we'll continue to do as they push forward into the container world. IBM will be there right with them as well because we know it's a very large world and we need to support everybody. We support VMware. We supported their competitors in the virtualization space 'cause some customers have, in fact, some customers have both. They've got VMware and maybe one other of the virtualization elements. Usually VMware is the dominant of course, but if they've got even a little bit of it, we need to make sure our storage works with it. We're going to do the same thing in the container world. So we will continue to push forward with VMware. It's a tight relationship, not just with IBM Storage, but with the server group, clearly with the cloud team. So we need to make sure that IBM as a company stays very close to VMware, as well as, obviously, what we're doing with Red Hat. And IBM Storage makes sure we will do both. I like to say that IBM Storage is a Switzerland of the storage industry. We work with everyone. We work with all these infrastructure players from the software world. And even with our competitors, our Spectrum Virtualized software that comes on our Flash Systems Array supports over 550 different storage arrays that are not IBM's. Delivering enterprise-class data services, such as snapshot, replication data, at rest encryption, migration, all those features, but you can buy the software and use it with our competitors' storage array. So at IBM we've made a practice of making sure that we're very inclusive with our software business across the whole company and in storage in particular with things like Spectrum Virtualize, with what we've done with our backup products, of course we backup everybody's stuff, not just ours. We're making sure we do the same thing in the virtualization environment. Particularly with VMware and where they're going into the container world and what we're doing with our own, obviously sister division, Red Hat, but even in a generic Kubernetes environment. Everyone's not going to buy Red Hat or VMware. There are people going to do Kubernetes industry standard, they're going to use that, if you will, open source container environment with Kubernetes on top and not use VMware and not use Red Hat. We're going to make sure if they do it, what I'll call generically, if they use Red Hat, if they use VMware or some combo, we will support all of it and that's very important for us at VMworld to make sure everyone is aware that while we may own Red Hat, we have a very strong, powerful connection to VMware and going to continue to do that in the future as well. >> Eric Herzog, thanks so much for joining us. Always a pleasure catching up with you. >> Thank you very much. We love being with theCUBE, you guys do great work at every show and one of these days I'll see you again and we'll have a beer. In person. >> Absolutely. So, definitely, Dave Vellante and John Furrier send their best, I'm Stu Miniman, and thank you as always for watching theCUBE. (relaxed electronic music)

>> Narrator: Live from Miami, Florida, it's The Cube. Covering IBM's Data in AI Forum, brought to you by IBM. >> Welcome back to Miami, everybody. You're watching The Cube, the leader in live tech coverage. We're here covering the IBM Data and AI Forum. Scott Buckles is here to my right. He's the business unit executive at IBM and long time Cube alum, Daniel Hernandez is the Vice President of Data and AI group. Good to see you guys, thanks for coming on. >> Thanks for having us. >> Good to see you. >> You're very welcome. We're going to talk about data ops, kind of accelerating the journey to AI around data ops, but what is data ops and how does it fit into AI? Daniel, we'll start with you. >> There's no AI without data. You've got data science to help you build AI. You've got dev ops to help you build apps. You've got nothing to basically help you prepare data for AI. Data ops is the equivalent of dev ops, but for delivering AI ready data. >> So, how are you, Scott, dealing with this topic with customers, is it resonating? Are they leaning into it, or are they saying, "what?" >> No, it's absolutely resonating. We have a lot of customers that are doing a lot of good things on the data science side. But, trying to get the right data at the right people, and do it fast, is a huge problem. They're finding they're spending too much time prepping data, getting the data into the models, and they're not spending enough time failing fast with some of those models, or getting the models that they need to put in production into production fast enough. So, this absolutely resonates with them because I think it's been confusing for a long time. >> So, AI's scary to a lot of people, right? It's a complicated situation, right? And how do you make it less scary? >> Talk about problems that can be solved with it, basically. You want a better customer experience in your contact center, you want a similarly amazing experience when they're interacting with you on the web. How do you do that? AI is simply a way to get it done, and a way to get it done exceptionally well. So, that's how I like to talk about it. I don't start with here's AI, tell me what problems you can solve. Here are the problems you've got, and where appropriate, here's where AI can help. >> So what are some of your favorite problems that you guys are solving with customers. >> Customer and employee care, which, basically, is any business that does business has customers. Customer and employee care are huge a problem space. Catching bad people, financial crimes investigation is a huge one. Fraud, KYC AML as an example. >> National security, things like that, right? >> Yeah. >> You spend all your time with customers, what else? >> Well, customer experience is probably the one that we're seeing the most. The other is being more efficient. Helping businesses solve those problems quicker, faster. Try to find new avenues for revenue. How to cut costs out of their organization, out of their run time. Those are the ones that we see the most. >> So when you say customer experience, immediately chat bots jumps into my head. But I know we're talking more than, sort of a, transcends chat bots, but double click on customer experience, how are people applying machine intelligence to improve customer experience? >> Well, when I think of it, I think about if you call in to Delta, and you have one bad experience, or your airline, whatever that airline may be, that that customer experience could lead to losing that customer forever, and there used to be an old adage that you have one bad experience and you tell 10 people about it, you have a good one, and you tell one person, or two peoples. So, getting the right data to have that experience is where it becomes a challenge and we've seen instances where customers, or excuse me, organizations are literally trying to find the data on the screen while the customer is on hold. So, they're saying, "can I put you on hold?" and they're trying to go out and find it. So, being able to automate finding that data, getting it in the right hands, to the right people, at the right time, in moment's notice, is a great opportunity for AI and machine learning, and that's an example of how we do it. >> So, from a technical standpoint, Daniel, you guys have this IBM Cloud Pak for Data that's going to magic data virtualization thing. Let's take an example that Scott just gave us, think of an airline. I love my mobile app, I can do everything on my mobile app, except there are certain things I can't do, I have to go to the website. There are certain things I have to do with e-commerce that I have to go to the website that I can't do. Sometimes watching a movie, I can't order a movie from the app, I have to go to website, the URL, and order it there and put it on my watch list. So, I presume that there's some technical debt in each of those platforms, and there's no way to get the data from here, and the data from here talking to each other. Is that the kind of problem that you're solving? >> Yes, and in this particular case, you're actually touching on what we mean by customer and employee care everywhere. The interaction you have on your phone should be the same as the interaction and the kind of response on the web, which should be the same, if not better, when you're talking to a human being. How do you have the exceptional customer and employee care, all channels. Today, say the art is, I've got a specific experience for my phone, a specific experience for my website, a specific, different experience in my contact center. The whole work we're doing around Watson Assistant, and it as a virtual assistant, is to be that nervous system that underpins all channels, and with Cloud Pak for Data, we can deliver it anywhere. You want to run your contact center on an IBM Cloud? Great. You want to run it on Amazon, Azure, Google, your own private center, or everything in between, great. Cloud Pak for Data is how you get Watson Assistant, the rest of Watson and our data stack anywhere you want, so you can deliver that same consistent, amazing experience, all channels, anywhere. >> And I know the tone of my question was somewhat negative, but I'm actually optimistic, and there's a couple examples I'll give. I remember Bill Belichick one time said, "Agh, the weather, it can't ever get the weather right," this is probably five, six years ago. Actually, they do pretty well with the weather compared to 10 or 15 years ago. The other is fraud detection. In the last 10 years, fraud detection has become so much better in terms of just the time it takes to identify a fraud, and the number of false positives. Even in the last, I'd say, 12 to 18 months, false positives are way down. I think that's machine intelligence, right? >> I mean, if you're using business rules, they're not way down. They're still way up. If you're using more sophisticated techniques, that are depending upon the operational data to be trained, then they should be way down. But, there is still a lot of these systems that are based on old school business rules that can't keep up. They're producing alerts that, in many cases, are ignored, and because they're ignored, you're susceptible to bad issues. With, especially AI based techniques for fraud detection, you better have good data to train this stuff, which gets back to the whole data ops thing, and training those with good data, which data ops can help you get done. >> And a key part to data ops is the people and the process. It's not just about automating things and automating the data to get it in the right place. You have to modernize those business processes and have the right skills to be able to do that as well. Otherwise, you're not going to make the progress. You're not going to reap the benefits. >> Well, that was actually my next question. What about the people and the process? We were talking before, off camera, about our PA, and he's saying "pave the cow path." But sometimes you actually have to re-engineer the process and you might not have the skill set. So it's people and process, and then technology you lay in. And we've always talked about this, technology is always going to change. Smart technologists will figure it out. But, the people and the process, that's the hardest part. What are you seeing in the field? >> We see a lot of customers struggling with the people and process side, for a variety of reasons. The technology seems to be the focus, but when we talk to customers, we spend a lot of time saying, "well, what needs to change in your business process "when this happens? "How do those business rules need to change "so you don't get those false positives?" Because it doesn't matter at the end of the day. >> So, can we go back to the business rules thing? So, it sounds like the business rules are sort of an outdated, policy based, rigid sort of structure that's enforced no matter what. Versus machine intelligence, which can interpret situations on the fly, but can you add some color to that and explain the difference between what you call sort of business rules based versus AI based. >> So the AI based ones, in this particular case, probably classic statistical machine learning techniques, to do something like know who I am, right? My name is Danny Hernandez, if you were to Google Danny Hernandez, the number one search result is going to be a rapper. There is a rapper that actually just recently came out, he's not even that good, but he's a new one. A statistical machine learning technique would be able to say, "all right, given Daniel "and the context information I know about him, "when I look for Daniel Hernandez, "and I supplement the identity with that "contextual information, it means it's one of "the six that work at IBM." Right? >> Not the rapper. >> Not the rapper. >> Not the rapper. >> Exactly. I don't mind being matched with a rapper, but match me with a good rapper. >> All you've got to do is search Daniel Hernandez and The Cube and you'll find him. >> Ha, right. Bingo. Actually that's true. So, in any case, the AI based techniques basically allow you to isolate who I am, based on more features that you know about me, so that you get me right. Because if you can't even start there, with whom are you transacting, you're not going to have any hope of detecting fraud. Either that, or you're going to get false positives because you're going to associate me with someone that I'm not, and then it's just going to make me upset, because when you should be transacting with me, you're not because you're saying I'm someone I'm not. >> So, that ties back to what we were saying before, know you're customer and anti money laundering. Which, of course, was big, and still is, during the crypto craze. Maybe crypto is not as crazy, but that was a big deal when you had bitcoin at whatever it was. What are some practical applications for KYC AML that you're seeing in the field today? >> I think that what we see a lot of, what we're applying in my business is automating the discovery of data and learning about the lineage of that data. Where did it come from? This was a problem that was really hard to solve 18 months ago, because it took a lot of man power to do it. And as soon as you did it once, it was outdated. So, we've recently released some capabilities within Watson Knowledge Catalog that really help automate that, so that as the data continues to grow, and continues to change, as it always does, that rather than having two, three hundred business analysts or data stewards trying to go figure that out, machine learning can go do that for you. >> So, all the big banks are glomming on to this? >> Absolutely. >> So think about any customer onboarding, right? You better know who your customer is, and you better have provisions around anti money laundering. Otherwise, there's going to be some very serious downside risk. It's just one example of many, for sure. >> Let's talk about some of the data challenges because we talked a lot about digital, digital business, I've always said the difference between a business and a digital business is how they use data. So, what are some of the challenging issues that customers are facing, and particularly, incumbents, Ginni Rometty used the term a couple of events ago, and it might have even been World of Watson, incumbent disruptors, maybe that was the first think, which I thought was a very poignant term. So, what are some of the data challenges that these incumbents are facing, and how is IMB helping solve them? >> For us, one of them that we see is just understanding where their data is. There is a lot of dark data out there that they haven't discovered yet. And what impact is that having on their analytics, what opportunities aren't they taking advantage of, and what risks are they being exposed to by that being out there. Unstructured data is another big part of it as well. Structured data is sort of the easy answer to solving the data problem, >> [Daniel Hernandez] But still hard. >> But still hard. Unstructured data is something that almost feels like an afterthought a lot of times. But, the opportunities and risks there are equally, if not greater, to your business. >> So yeah, what you're saying it's an afterthought, because a lot of times people are saying, "that's too hard." >> Scott Buckles: Right. >> Forget it. >> Scott Buckles: Right. Right. Absolutely. >> Because there's gold in them there hills, right? >> Scott Buckles: Yeah, absolutely. >> So, how does IBM help solve that problem? Is it tooling, is it discovery tooling? >> Well, yeah, so we recently released a product called InstaScan, that helps you to go discover unstructured data within any cloud environment. So, that was released a couple months ago, that's a huge opportunity that we see where customers can actually go and discover that dark data, discover those risks. And then combine that with some of the capabilities that we do with structured data too, so you have a holistic view of where your data is, and start tying that together. >> If I could add, any company that has any operating history is going to have a pretty complex data environment. Any company that wants to employ AI has a fundamental choice. Either I bring my AI to the data, or I bring my data to the AI. Our competition demand that you bring your data to the AI, which is expensive, hard, often impossible. So, if you have any desire to employ this stuff, you had better take the I'm going to bring my AI to the data approach, or be prepared to deal with a multi-year deployment for this stuff. So, that principle difference in how we think about the problem, means that we can help our customers apply AI to problem sets that they otherwise couldn't because they would have to move. And in many cases, they're just abandoning projects all together because of that. >> So, now we're starting to get into sort of data strategy. So, let's talk about data strategy. So, it starts with, I guess, understanding the value of your data. >> [Daniel Hernandez] Start with understanding what you got. >> Yeah, what data do I have. What's the value of that data? How do I get to that data? You just mentioned you can't have a strategy that says, "okay, move all the data into some God box." >> Good luck. >> Yeah. That won't work. So, do customers have coherent data strategies? Are they formulating? Where are we on that maturity curve? >> Absolutely, I think the advent of the CDO role, as the Chief Data Officer role, has really helped bring the awareness that you have to have that enterprise data strategy. >> So, that's a sign. If there's a CDO in the house. >> There's someone working on enterprise, yeah, absolutely. >> So, it's really their role, the CDO's role, to construct the data strategy. >> Absolutely. And one of the challenges that we see, though, in that, is that because it is a new role, is like going back to Daniel's historical operational stuff, right? There's a lot of things you have to sort out within your data strategy of who owns the data, right? Regardless of where it sits within an enterprise, and how are you applying that strategy to those data assets across the business. And that's not an easy challenge. That goes back to the people process side of it. >> Well, right. I bet you if I asked Jim Cavanaugh what's IBM's data strategy, I bet you he'd have a really coherent answer. But I bet you if I asked Scott Hebner, the CMO of the data and AI group, I bet you I'd get a somewhat different answer. And so, there's multiple data strategies, but I guess it's (mumbles) job to make sure that they are coherent and tie in, right? >> Absolutely. >> Am I getting this? >> Absolutely. >> Quick study. >> So, what's IBM's data strategy? (laughs) >> Data is good. >> Data is good. Bring AI to the data. >> Look, I mean, data and AI, that's the name of the business, that's the name of the portfolio that represents our philosophy. No AI without data, increasingly, not a lot of value of data without AI. We have to help our customers understand this, that's a skill, education, point of view problem, and we have to deliver technology that actually works in the wild, in their environment, not as we want them to be, but as they are. Which is often messy. But I think that's our fun. It's the reason we've been here for a while. >> All right, I'll give you guys a last word, we got to run, but both Scott and Daniel, take aways from the event today, things that you're excited about, things that you learned. Just give us the bumper sticker. >> For me, you talk about whether people recognize the need for a data strategy in their role. For me, it's people being pumped about that, being excited about it, recognizing it, and wanting to solve those problems and leverage the capabilities that are out there. >> We've seen a lot of that today. >> Absolutely. And we're at a great time and place where the capabilities and the technologies with machine learning and AI are applicable and real, that they're solving those problems. So, I think that gets everybody excited, which is cool. >> Bring it home, Daniel. >> Excitement, a ton of experimentation with AI, some real issues that are getting in the way of full-scale deployments, a methodology data ops, to deal with those real hardcore data problems in the enterprise, resonating, a technology stack that allows you to implement that as a company is, through Cloud Pak for Data, no matter where they want to run is what they need, and I'm happy we're able to deliver it to them. >> Great. Great segment, guys. Thanks for coming. >> Awesome. Thank you. >> Data, applying AI to that data, scaling with the cloud, that's the innovation cocktail that we talk about all the time on The Cube. Scaling data your way, this is Dave Vellante and we're in Miami at the AI and Data Forum, brought to you by IBM. We'll be right back right after this short break. (upbeat music)

>> live from Las Vegas. It's the queue covering del Technologies. World twenty nineteen. Brought to you by Del Technologies and its ecosystem partners. >> Welcome back to the Cubes Live coverage here in Las Vegas. The Cube covering del technology World twenty nineteen. I'm John for Michael David. Want Dave? Lot of strategy being discussed. A lot of new product introductions, availability of things and beta. Michael Dell on stage of Pat Nelson, You're starting to tell a lot of great things. Jeff Clarke, master of ceremonies and here with us, Matt Baker was senior vice president's strategy and playing. Works for Jeff Clarke. Re to see you. Thanks for coming on. >> Thanks for having me. It's great to be back. >> So you're the man behind the curtain for Jeffrey. You get mall. Who's their devices? You sending all the place? He's Tom Brady. You're Bill Belichick. I >> don't have my >> so pretty strategic couple years for del sure. So take a step back because you know one of the luxuries of doing the queue for ten years. As we get some one on ones with Michael, we seem in the hallways. We get the child, then he's very approachable. We talk to him before you went private when he went private or three. Dellums buying him. See? And then when he bought the emcee. So serious conversations. But it's always had that vision of scale. Benefits of that and the numbers were off the chart. People's eyes were popping out their head. So a lot of strategy coming in with the founder with the team pretty impressive. Take us through the pieces on the board, What happened, what didn't have and what could have happened and how it all transpired. >> That's that's a long journey, and it could take a little weight. And second, I think, you know, Michael is a visionary. He's always had a vision for something bigger and certainly the history of del shows that scale matters. And, you know, we we saw display out with our competitors and our strategy versus their strategy. They got smaller, we got bigger and you know, so we're sitting here today. Following all of those moves was a vision tio become that, as Michael would say, essential infrastructure provider and in addition to that not just the physical infrastructure but the logical infrastructure of the management of all that. So vision that Michael saw through to, you know, the acquisition of the M C along with the constituent parts that were the federation inside of there being bm where an opportunity to really bring forward a solutions powerhouse that was ableto address this broad challenge that our customers were having, Which is how do you manage all of this stuff? And, you know, putting a lasso around that and figuring out how to help our customers with what is becoming increasingly complicated. It's not becoming simpler. The individual components are becoming simpler, and that's our job. To make each of those elements more automated more, you know, easy to use, more approachable for more people. But ultimately, people are trying to achieve so much with technology today that you gotta drain away the complexity of that and bring a higher order platform and a higher order operating environment to allow people to really realize their goals. >> And one of the things that you've got to do and your job is you also got not only look at that but also cut through the hype. Sure, I mean how many times we heard the PC is dead. Many times we heard that if you're not here there, you're out of business somewhat true when you have transformational markets. But then the day that the value activities that they're involved in a company is pretty simple, they have operations. They sell a product, good or service. They give it to a customer, they collect cash. At the end of the day, this workload. So you look at everything all things being equal. This is a developer operational and a workload kind of challenge to do something. Certainly pretty much. It's so operation leads a big advantage. >> Well, I think that's what our customers are struggling with is that there are very good reasons to choose different operating environments. I mean, tohave things in different localities. Simply you might want to preposition content like you guys do. I'm sure somewhere behind the Cube is a cdn right for distributing content and so that service benefits from geographic distribution. But you shouldn't have to create a diverse operating environment in order to operate a geographically diverse environment. What we're creating is the singular operational hub for your entire environment. You can run workloads in azure. You Khun, run workloads in eight of us, you Khun run workloads in the four thousand VC PP partners that that Pat mentioned during the key note. And you could do that all through a single operational framework. I don't want to stay single pane of glass, but in essence, the sink. Thank you. Single operational framework that allows you to orchestrate and manage your entirety of your operations. Which allows you to choose the best horse for the given course. >> So strategy guy? Yeah, dial back a few years, even maybe before the acquisition. How clear wasn't you? Was it to you? And what gave you the confidence that acquiring Because you guys were quiz, It'd Dell was inquisitive, and I say a lot of them didn't really pan out the way you had hoped. And you're going to bring in this giant PMC cleanup. VM wears cloud strategy, leverage it across the portfolio. Really, Dr Scale Become that sort of arms dealer, if you will. Sure. What gave you confidence at the time or was it more? Hey, this is a great asset. We'LL figure it out. Can you share with us? >> I think you need to roll the clock back much further to the fact that We were partners for a long time with the emcee, and we were certainly one of the largest. And year by year, the largest or second largest partner to VM were. So we were incredibly familiar with one another and incredibly familiar with our capabilities. We were the early company that worked on. I can't remember what it was called. It might have been Oh, my God. I can't even remember the name of a guy. Integration. No, no, I'm talking about the early visa and implementations that went to market with Dell. Right? So we have been collaborating on hyper Converged. We've been collaborating on Cloud management. We've been working with the emcee years prior. In fact, some of the folks that are appearing on you know your show today. Our people that were my partners ten years ago at that Del. So I think we had the confidence and Michael certainly had a long history with with the organization. And I think he saw on opportunity that there was sort of ah, confluence of of opportunities around, you know, the markets, you know, our ability to pull a deal like that off. But I think ultimately Michael had the confidence that this was going to create a powerhouse and those assets were undeniable. And to some degree, what you were saying about, you know, the sort of these zero some assumptions is like Okay, well, software to find it's going to disrupt traditional race. To the extent that it's going to be, there are no zero sum outcomes in it. We continue on, and those markets continue to be robust. In fact, the storage market has been growing quite robustly, so sort of like this is a set up of capabilities that people need. We need to get bigger, not smaller. >> I buy that and I buy this not a zero sum. I heard Bill Clinton at Adele World years ago talk about how it's not a zero sum game and that I thought was pretty credible. However, historically the IT business has been a winner. Take most you know the leader gets most of the the prophet the second makes does okay and the third kind of barely breaks even. And there is no fourth, fifth and sixth. So it is sort of a winner. Take All are going to take most market, isn't it? >> I think to some degree, but it depends on how you define markets and Barney we all. We all tend to participate and find opportunities. Teo to move and cross into new market areas. Market extension is a a basic of strategy, right? Like look for adjacent sees expend. So there's plenty of room in this three plus trillion dollars market for us all to really participate. The job of strategists and business leaders is what air those best opportunities and how do we get after them? And certainly Michael is proven to be the strategist to figure this out. Like what? What? You know Dell's acquiring A and C. It's like, Yeah, way are you know that >> nineteen ninety billion You grew fifty fourteen percent last year. What? Yeah, >> it's always good that the founder around always great to have that leadership in the history. But one of the things I really like about the strategy that you guys are taking is one. I love the bigger scale leverage. I think that's right on the money. We called that right out of the gate. I'm here in the Q right when it happened, but there's nothing that's emerging. I want to get your thoughts on what? I see this clearly with Google. Google has a sorry sight, reliable engineer, and they run measurement for the massive interest for themselves. They're clouds. Not yet. Translating is no one's like Google, right? There's no enterprise that actually just Google, so it's like a tailored suit for one person. Google Operational Consistency is a huge message here. This year has been for a while. This is really important. I want you to take a minute to explain why that strategy and what the impact will be for customers. >> Yeah, well, I think that you just sort of it's the analog within our customers to what you just described with our business. Achieving scale allows you to accelerate growth. Achieving scale, innit operations allows you to achieve scale and accelerate. Your digital transformation is a customer. So if you're able to create the equivalent of these sightless reliability, in other words, creating a highly scaleable environment, there is no lack of demand, for it fueled innovation in any business anywhere today. That's why we're so bullish on the future that were in the middle of this massive investment cycle of digitizing codifying business process into application and growing the footprint and sort of surface area of all businesses. So if you're able tto create this consistent operating level rather than spending all day down in the plumbing of it all, automate that layer and then focus on the business value. That's if you go look through our studies around, you know, digital transformation. What our customers air doing. It shows that to some degree they face did transformation stall right there. They're like, How do I get everybody aligned to this tea? I've got the business increasingly were like You all need to come together as an organization and focus up and helping our people free up and scale themselves to get closer to the business and really be a part of that sort of strategic discussion for the company. It's the same thing it's achieved. Scale works everywhere, achieve scale, innit Operations frees up time and investment dollars tto help the debs to help the business >> rival revenue to drive revenue well, not justa cost issue. You take away that cost, which is a cost consolidation, cost, leverage, efficiency, et cetera. But the flip side is like Bank of America was saying on the keynote. They gotta know we gotta run their business and make money. So the APP developers are critical. Well, tonight could be a part of the revenue stream, >> and I think the sort of basics of it all is that this wee keeps throwing around the term digital transformation. But at the end of the day, people are codifying business process and their customer experiences and all of that into technology. And that's how they're delivering new business products, new experiences for their customers. You know, I have a branch list bank that I use, I have. You know, I adopted them because the technology was great, right, because their experience of banking through them is amazing. If Andre never >> they know you that its data model, that actually is not an account number and >> absolutely so I think that that's the point you're asking. Why is a consistent operating model important? It helps it achieve scale. And some people say, Well, it's all about developments like them. Look, it's the It's the interplay between ops and death. There's two words there. It's not know ops. It's Dev and Ops and Achieve Scale. You need operators who can achieve scale to achieve scale, you need consistent capabilities. Tooling >> excited. So what you're saying about revenue scale is really important because most big acquisitions, they talk about synergies. That's a code word for cut. You guys grew fourteen percent last year, so I'm sure you have, you know, costs energies. But they're our revenues, energies as well to your point >> and customers as well. >> I think we've just been successful, showing the power of the full portfolio and and that's turned into will make a bigger and bigger bets with you. And during the the Post keynote press briefing, you know, it was stated. Look, you know, people I don't necessarily want more and more and more more vendors. They want fewer more strategic vendors for certain elements, and then they want to look for new innovation in in other areas on. So I think that it's sort of we're benefitting from the fact that we are the company that you could turn to to solve this broad challenge of it, and then you can work with others around your specific vertical, what you might do. We've got a huge network of partners that we work with that can help customers with the spoke applications for their specific vertical health care retail. So on and so forth. So, yeah, I think we value chain in the valley. Twenty infrastructure >> suppliers to your point about that zero sum. Um, uh, thesis is not being zero. Sum is infrastructure loves automation. Automation loves data. So if you have an end to end architecture, you have better data. Correct. You have opportunities, you know, being around automation machine learning, too. Set the standard for the next layer >> up. Well, and that consistency extends all the way across. Right? So if I can create a consistent model, that model is also four out in the data. And then I can create a consistent engine to consume that data to Dr Automation that continues to add value in value in value. So putting that loop around it is hugely important to driving value for our >> customers. Do your kids play? Would you rather you know, they say we gotta like this Really? The hot desert or freezing cold, right. So, Matt, would you rather be a fighter test pilot or a college professor? >> You know, you must have read something from my Twitter feed. I would rather >> you gotta answer. Definitely. Fighter pilot. Fighter pie. Okay. How about would you rather be a professional hunting and fishing guide or professional ocean racing skipper? >> Probably the ocean racing skipper. Although I'd like to be closer to my family. Both of those. You're out out of >> the way with your top five jobs. >> That was Those are my theoretical jobs. I love my job. I don't want a new job. I love my job. Like I don't I don't want to go anywhere. But if that was purely theoretical of it, >> Matt, thanks for coming on the Cube. I'LL give you the final word. In short, what's the core strategy of Adele Technologies? >> Well, I think it's to continue to drive value across the totality of this entity that has so much power. And I hope that's on display. An obvious to you both that we're really pulling together to create solutions that deliver a massive amount of value to our customers. And I think that's unmatched in the industry. So I appreciate you having me on toe talk through this and give me a little rip me a little about my tweets about my >> friend. Give a quick flight for your video log. The Baker's Dozen. >> Yeah, the Bakers, half dozen >> figures That doesn't give it. What's it about what he wants? The focus. >> It's It's basically a six minute spot that I go through. Six and a half things. Baker's dozens thirteen. It's hard to divide it by two way. End up with a half thing. It's sort of funny, but I just take people through a basic rundown of Hey, what's going on in the marketplace? And I try to make it simple, funny and just sort of poke fun at myself. So it's funny. >> Matt Baker, senior vice president of strategy and planning for Del Technologies. I'm Jeffrey Worry David Lantz. Stay too. From more live coverage of day One of three days of wall to wall coverage to cube sets, A lot of content. The cube cannon blowing out the content here, Del Technologies world. Stay with us. We'LL be right back

>> Narrator: From Las Vegas, it's the Cube, covering IBM Think 2018, brought to you by IBM. >> Welcome back to Las Vegas, everybody. You're watching the Cube, the leader in live tech coverage. My name is Dave Vellante, and this is day three of our wall-to-wall coverage of IBM's inaugural Think conference. Mary Glackin's here, she's the vice president of weather business solutions, public, private partnerships, IBM Watson, and she's joined by Sheri Bachstein as the global head of consumer business at the Weather Company, an IBM company. Ladies, welcome to the Cube, thanks so much for coming on. >> Thank you, you're welcome. >> Thanks. >> Alright, Mary, going to start with the Weather Company. When IBM acquired the Weather Company, a lot of people were like, "What?", and they said, "Okay, data science, I get that.", and then, there was an IoT spin on that. Obviously, you have a lot of data, but, I got to ask you, what business are you in? >> So, what we like to say is we're in, not in the weather business, we're in the decision business. We're really dedicated, everyday, to help businesses, make the best decisions possible, and Sheri works on the consumer end of the business to do exactly the same thing. >> So, talk about your respective roles. Sheri, you're on the consumer side, as Mary just said, what does that entail? >> So, the consumer side is any touchpoint where we're bringing weather and weather insights to our consumers, whether it's on our weather channel app, whether it's on our web platform, mobile web, on wearables, so, it's anywhere where we're connecting with consumers, and, as Mary said, it's really about helping consumers make decisions. In our field, the forecast and some of the weather data has become a commodity almost, and we've actually shared our weather data with a lot of partners, and, so, now, we're using machine learning and data science to really come up with weather insights to help consumers make decisions, and it could be something just as simple as what to wear today, what's going to happen for a big event, or it can be around how do I keep people safe during severe weather. >> Yeah, I mean, we all look at the weather. I mean, I look at it everyday. >> Yeah. >> Of course, when you travel, like, what do I bring, what do I wear? Living in the East Coast these days, a lot of storms that we've >> That's right. >> encountered in the East Coast. I wonder if you could talk about life at IBM. I mean, again, it was a curious acquisition to a lot of people. Have you guys assimilated, how has it changed your business? >> I would say pretty dramatically. So, coming back to IBM acquiring us, they acquired us, really, for two reasons. One is we had some underlying technology that was really of interest to them that they're leveraging today, but the other part was because weather impacts so many businesses. So, as we've come into IBM, we've had alliances with IBM research. We're working on a pretty exciting project in bringing the next generation weather model to market, using high performance computing there. We've had alliances, definitely, through Watson in bringing AI into our products, and then, our product lines marry up with a lot of IBM product lines. So, we've rolled out a really exciting offering in closed captioning, and it really works well with some of the classical media business, weather media business that we have been providing. >> So, how do you guys make money? Maybe we could talk about the consumer side and the business side. A lot of people must ask that question. >> Yeah. >> They're advertising, okay, fine, >> Yeah. >> but that's not the core of what you guys do. >> Yeah, so, on the consumer side, a big majority of our revenue is drive by advertising, but we had to look at that business as well, 'cause as programmatic advertising has kind of taken up the landscape, how did we pivot to really generate more revenue, and, so, we've done that by creating Watson advertising, and that was one of the first implementations of Watson after the acquisition on the consumer side, and what we've done is we've created an open, scalable environment that, now, we can not only sell meaningful insights on our platform, but we can now give that to our partners, that they can go off our property and use the weather insights, we can use different data around location and media to help our partners really have a better experience, not only on our platform, but on any publisher's platform. >> So, that's your customers using Watson for advertising to drive their business. >> That's right. >> It's not like IBM is getting into the advertising business, per se, directly, is that right? >> Right, well, we're leveraging the power of Watson to create these insights. One of the products we created is called Weather FX, and, really, what it's doing, it's taking predictive analytics on the retail side, which is really an underused technology for retailers, but taking our historical weather data, mixing it with their retail data' to come up with insights so we can come up with interesting things that, say, in the northeast, like right now, during the winter, soda sells tremendously during very snowy or rainy winters. We can look at, you know, strawberry Pop-Tarts sell fairly well right before a hurricane, and, so, these are insights that we can bring to retailers, but it helps them with their supply chain, it helps them with their inventory, it can actually even help them with pricing, and, so, this is one of the ways we're taking our weather technology and marrying it with the advertising world to help provide those insights. >> For real, with the strawberry Pop-Tarts? >> For real, yeah, I guess, you know, you don't have to cook 'em or something. I don't know, so, yeah. >> Right, yeah, it's simple if the lights go out, okay. I mean, we want to ask you about your title, public and private partnerships. It's interesting, what is that all about? >> So, it's really about the fact that weather has really been something that's been shared globally around the world for hundreds of years at this point, and, so, the Weather Company and IBM take it very seriously that we be good partners in that community of weather providers. So, one of the things that we feel passionately about is we have a shared safety mission with national meteorological services globally. So, here in the US, we transmit, Sheri's team does, the warnings that come from the National Weather Service unaltered with attribution to the National Weather Service. We feel that it's really important that there's a sole authoritative voice when there's really danger. So, we share that safety mission, and then, we're trying to help in other parts of the world. We've had some partnerships to try to increase the observing in Africa which is really a part of the world that's under-observed. So, some of IBM's philanthropic efforts have been helping to fill in there and work with those national met services. So, it's really one of the really fun parts of my job. >> You know, we talk a lot about digital transformation, and Ginni Rometty was talking about the incumbent disruptors, and we've been riffing on that all week. We've made the observation that companies that are digital have data at their core, and they've organized, sort of, human expertise around that data. Most companies, Fortune 1000, are built around human expertise and built around other assets, the bottling plant or the factory, et cetera. I look at the Weather Company as a data company, that's probably fair. Did you evolve into that data is clearly at your core? Has it always been, and it's very interesting that IBM has acquired this company as it changes its DNA. I wonder if you could address that. >> Go ahead (laughs). >> So, I think there's a couple aspects around our data. There's obviously the weather data which is really powerful, but then, there's also location data. We're one of the largest location data providers besides Google and some of the others, because our weather accuracy starts with location which is really important. We have 250 million users that use our application, and we want to give them the most accurate forecast, and that starts with location. Because we add value, users will opt in to give us that data which is really important to us that we do keep their data private and opt in to that to get that location data. So, that's really powerful, because, now we can deliver products based on time and location and weather, and it just makes for better weather insights for, not only our consumers, but for our businesses. >> Yeah, yeah. >> Do you use, I mean, how do you use social? I mean, you know how Waze tells you where the traffic is and you report back. Do you guys rely heavily on that, or do you more rely on machines to help you with your forecast? Is it a combination? >> So, I could talk a little bit. One of our new market areas we've been going into is ground transportation. So, we do have a partner that's providing us some transportation, traffic information, but what we bring to it is being able to do, the predictive thing, is to take the weather piece and how that's going to influence that traffic. So, as the storm comes through, we know by looking at past events what that will mean and we bring that piece to the table. So, it's an example of how we go, not just giving you a weather forecast, but really forecasting the impacts and giving you insights, so that if you're running a large trucking operation, you can reroute fleets around it and avoid weather like that and keep people safe. >> Talk about, oh, go ahead, please. >> One of the brands within our portfolio is Weather Underground, and what they brought to the table for us is a personal weather station that works. So, we have about 270,000 around the world, and these are people that just really love the weather. They have a personal weather station in their backyard and they provide that data that then goes into Mary's team in helping looking at the forecast. So, that's one of the ways that we're using kind of a social network in sensoring to influence some of the work that we're doing. >> I mean, the weather forecast, for years, have been the butt of many jokes. You guys are data science oriented, data scientists, the data doesn't lie. We just keep iterating >> Yeah. >> and make it better and better and better. What could you tell us about the improvements of the forecast over the last decade? Maybe Bill Belichick makes jokes about the weather and you hear it, you say, "You know, actually "the weather's predictions have gotten much better." You guys measure it, what can you share with us? >> Oh, it's gotten so much better over the course of my career, it's pretty dramatic and it's getting better still. You're going to see some real breakthroughs coming up. So, one of the things that we've really put a lot of bets on in IBM is the internet of things, >> Dave: Right. >> and, so, we are, today, pulling off of cellphones atmospheric pressure data and that's going into our next generation model. So, this'll be more data than anybody has powering that model. So, you're able to augment traditional data sources like, you may or may not know, we still launch weather balloons twice a day to measure through the atmosphere, but, in our technology, we take data off of airplanes, we take data off of cellphones, we'll soon be taking data off of cars which will tell us when the windshield wipers are moving, is it raining or not, when the anti-lock brakes things lock, that roads are icy, all of that. So, all of that will come in to improve forecasting. >> So, this requires partnerships with all that and amazing supply chain. >> Absolutely. >> I presume IBM helps there as well, but did you have a lot of that in motion prior to the acquisition, how does that all work? >> I think we've really been empowered by IBM. >> Yep, absolutely. >> Yeah. >> There's no question about that, and it's about finding the win-win. When we work with car manufacturers they're looking to have safe experiences for their drivers and we can help in that regard, and, as we move into autonomous vehicles, there's just going to be even more demand for very high resolution, accurate weather information. >> Am I correct at all, the weather data from all these devices actually goes back to the IBM cloud, is that right, and that's where the models are iterated and developed, is that correct, or does some of it stay out in the network? >> It's all a cloud-based operation that's here. We do do some, I mentioned before that we're working with IBM research on next generation high-performance computing which is actually, it can be cloud-based, but it's also on Prim-based, because of the very large cores we need for computing these models. We're going to run a very high-resolution model globally at a very high frequency. >> So, thinking about some of the industries that you're helping, I mean, you mentioned retail before. Obviously, government's very interested in this. I would imagine investors are interested in the weather in a big way. >> Yeah. >> Maybe you could talk about some of the more interesting industries, use cases, business models. >> Yeah, there's a lot out there, there's traditional ones we've served for years like energy traders that are very interested in, you know, because they're trying to make decisions about that. The financial services sector is also very interested. When they can get some additional insights through footfall traffic, if they know certain stores are seeing more footfall traffic, that will give them some indication, a little edge up in the marketplace for that. So, we see those kind of things, and other traditional areas as well, agriculture, what you would expect there. >> So people, you know, you hear a lot of talk in the press about artificial intelligence and Elon Musk predictions and the like, but here's an example where machine intelligence, everybody welcomes, keeps getting better and better and better. How far could we take AI and weather? Where do you see this going in the next 10 years? >> So, on the consumer side, I think it's really about transforming the way that we're delivering weather on the digital platform, the new age of the weather app will say, and, really, users want a personalized experience. They want to know how the weather's going to impact me, but they don't want to personalize, right? So, that's where machine learning is coming in, that we can be able to provide those insights. We'll know that, maybe, you're an allergy sufferer or migraine sufferer, and we're going to tell you that the conditions are right for that you might have symptoms related to that around health. So, there's a lot of ways, on the consumer side, more personalized experience, giving you more assurance that you don't have to, necessarily, go to the app to find information. We're going to send it to you more proactively, and, so, machine learning is helping us do that cognitive science as well. So, it's a pretty exciting time to be part of the weather. >> Yeah, that bum knee I have, you know, you might want to get ahead of the pain. >> That's right, with the arthritis, yes, yes, so, definitely. >> Alright, Mary, we'll give you last word on IBM Think and, you know, the whole trend of AI and weather. >> So, I think it's really exciting. I think Ginni says it really well. It's about AI and the person as well. You know, AI doesn't take over. It's really finding the way to AI to really assist decision makers and that's we're going on the business end of things is really sorting through tons and tons of data to really provide the insights that people can make, businesses can make really great decisions. >> Well, it's always been a really fascinating acquisition to me, and, now, just to see how it's evolving is really amazing. So, Sheri and Mary, thanks very much for coming on the Cube >> Thank you. >> and sharing your experiences. >> Thanks so much. >> Great, thank you. >> You're welcome, alright, keep it right there, everybody, you're watching the Cube. We're live from Think 2018 and we'll be right back. (techno beat)

>> Announcer: From Gillette Stadium in Foxborough, Massachusetts. It's theCUBE, covering VTUG Winter Warmer 2018, presented by SiliconANGLE. >> I'm Stu Miniman, and this theCUBE's coverage of VTUG Winter Warmer 2018, in addition to being an Analyst, and the host of this program, I've also been a long-time Patriot's season ticket holder. Real excited to welcome to our program, Logan Mankins, number 70. Thanks so much for joining us. >> Thanks for having me. >> Yeah so it's interesting. At this show we're talking tech, and a bunch of the IT Admins, they're people that you'd consider in the trenches. You, you know spend a lot of time in there. I wonder, a couple of your guys like Tedy Bruschi, Ty Law, Lawyer Milloy's here today, making interceptions and things like that, sometimes get a little bit more coverage out there, and they're a little bit more well known. Do you ever feel that you were faceless, you know, paying for the Pats? >> No, those guys, they made all the plays, they got all the recognition but, the linemen, we always knew that without us the offense couldn't go, the team couldn't go so... And most linemen, they don't want to be the face out there anyway. Me personally, I'd rather not be known, but it comes with the job. >> Yeah well, seven-time Pro Bowler. As a matter of fact, I was looking back, and there was this great video from Bill Belichick, and he's like, "There's tough players in the NFL, "but when I think of Logan Mankins, "he's super tough out there." When you look at the game now, Rob Gronkowski took a massive hit in the AFC Championship game. How does toughness and injuries, how did you think about that? Did you think about that when you were playing, versus now being out of the game? >> When I was playing no, you don't really think about it, but fortunately for me, I didn't have hits like that to the head, those big concussion-type hits. The stuff I always played with was just body stuff, and there's always a difference between being hurt and injured. If you're hurt you can still play, and if the injury's not too bad you can still play so, it was just a fine line of figuring out what you could do and what you couldn't. >> Patriots have had a phenomenal run. I mean you played for a great team. Bill Belichick, Tom Brady throughout them all, give us a little perspective of somebody that played for the team for awhile. How did you work through the changes, but yet there were some consistency around the core? >> Yeah, that's the main thing, the core, and they've had an unbelievable run. I don't know what's Bill been there, 18 years or something? And it's been unbelievable to see what those guys have accomplished and, it all starts at the top. You have a good owner and the best coach ever, and the best quarterback ever so, as long as you get the right guys that buy into that system, and follow those two guys, you're going to have a good team. >> Last year Deion Branch shared with us some great stories about Tom Brady, his, hyper-competitive type of guy. Give us a little color. What's it like playing in front of TB 12? >> Aw, it's great you know, you know he's always prepared. You never have to worry about him, he's going to play great the majority of the time and, just the way he competes and works. It rubs off on other guys and, he's just so dependable and can make all the right reads, throws, and he's a great guy to be around on top of that so, he's the ultimate teammate, and ultimate competitor, and that's why he's had so much success. >> You said that you didn't take, you played through some injuries, you had some, you played when you were hurt and, we know you had some rough injuries during your career, but concussions weren't a concern. Is it something that you look back now, or look at the game today, and all those things about CTE and concussions, is that, you know...? >> Oh yeah, the more you learn about it, the more you worry about it, because you're aware of it now. I think when I started playing football no one talked about it. There was no worries about it, and towards the end of my career it really started coming out, and more comes out about it every year so... Of course you worry about it. You hope you're one of the guys it's not going to affect, but there are guys that it's really affecting in bad ways, so at this stage of my life, it's too late to go back so it's, we'll see what happens I guess. >> Yeah, would you recommend young people going into football, knowing what you know now? >> I think so there's... It's a lot safer now. You're not taking those big... Well, every once in awhile a guy's just going to take one, you just saw Rob the other day. But for the most part they're trying to prevent that, and via techniques that they're teaching now with the blocking and the tackling, to not use your head as much, so it's a lot safer and look, at the end of the day, it's up to whoever's making that decision to play, and if they want to play, then they have the right to play. >> So we're obviously, everybody locally is super excited, getting ready for another Super Bowl. How does the team stay focused? You know, two weeks leading up to it, there's a lot going on. It's not New Orleans that they're going to, but how does the team stay focused on their job? >> Well, this team with the Patriots, they've been through it so many times, and they know what, they have a big job ahead of them. But they do a good job with what I was hearing when we went to Super Bowls. Like all the tickets and the hotel rooms for family and all that, they do a great job by getting that out of the way the first two days, and get that taken care of so you don't have to worry about that. And then it's on to the opponent that you're playing, and you just focus in on that, and Bill has, he's great at just, he draws a line, and follows that line so he'll have everyone in that line, and everyone will be ready, there won't be any distractions, and they'll be ready to go. >> Speaking of distractions, there's been a lot of noise in the press lately, as the relationships, everything like that. When you were in the locker room, does that hit your radar? Do you just focus and do your job? How does that impact what's going on? >> Yeah most stories, they don't bother you. They got to find stuff to write about but, the last one I guess with those guys, the story coming out that they're feuding, and this and that. I don't know if they are or they're not but, if they're not, I think that would upset me if they said I was feuding with someone that I wasn't, that has been a colleague, and most likely a friend of yours for that long. >> Well, Logan Makin, really appreciate you joining. Patriots has some phenomenal guards. You know, Hannah, in the Hall of Fame. You're definitely up there as one of the greatest guards in Patriot's history. >> I appreciate that. >> I really appreciate you joining me. >> Alright, thank you. >> Alright, so thanks again to the VTUG for bringing Logan Mankins. Love being here at the Intersection Virtualization Technology, and the Patriots. I'm Stu Miniman. Thanks for watching theCUBE. (tech music)

>> Announcer: Live from Gillette Stadium in Foxboro, Massachusetts, it's theCUBE, covering #VTUG's New England Winner Warmer 2017. Now, your host, Stu Miniman. >> And we're back, with SiliconANGLE Media's presentation of theCUBE, we're the worldwide leader in enterprise tech coverage, happy to welcome back to the program, Steve Pao, who's the CMO of Igneous Systems, Steve flew out from Seattle here to, welcome to the home of the New England Patriots. >> Oh my gosh. Number 12, number 12! >> The 12 man representing here, you've got, I have to say, I almost canceled my season tickets when Pete Carroll was our coach, so, luckily he's worked out better for you than he did for us. My wife's a Brown fan, she says the same thing about Bill Belichick. So, it's the coaching fraternity is kind of like the tech world, it's a small group, you all kind of get to know each other and move around, so, thanks for joining us. >> Yes, well thanks for having me! >> Alright, so Steve, we've been talking to you guys since you were coming out of Stealth, why don't you give our audience, what's the update on Igneous? >> Okay, well for those of you who don't know us, what Igneous really does is we offer an onsite private cloud storage service, and that's our first offering, it's part of our greater mission of providing true cloud for local data, and what we basically offer today is an unstructured data store that's completely delivered as a service, we take our own equipment, we install it, we monitor it, we manage it, we even refresh it when necessary, and all the customer has to do is really subscribe, and that's it. It's all pay-as-you-go, and it's all zero touch for the customer. We launched back in October, as you recall, and one of the things that I think that it's been really great since launching is that we've really started to see how customers that didn't know us are actually really evaluating, really, I think, the convergence of two trends, one is there's this data growth, data trend that goes on, and pretty much everybody we talk to, citing data growth rates on the order of doubling every three years, where IT budgets are growing less than 5% a year, so there's this mismatch where, basically everybody's hitting this juncture that what they used to do can't work because the data's growing faster than the budget. And at the same time, there's this data growth that's actually happening, and the data growth is not from relational databases and structured data, but rather, a lot of new applications that are logging sensor data that are supporting machine learning, AI, really, it's machine-generated data being analyzed by machines, with humans really just training the AI and the machine learning. >> Yes, Steve, I want to unpack that a little bit, let's talk it, because many of us that watch storage, it's been like, well the storage industry, it needs to change, it's not about selling boxes, it's not about capacity, and even on unstructured data, it was kind of like, okay well, what's creating data and what's actually valuable? How much is it just, do I stick it on a cheap tier, what do I actually do with it, what's interesting you guys do, some of those use cases, throughout machine learning, machine data, things like sensors, every time I hear that word, that IoT buzzword kind of pops into our head, but maybe you could talk to some of those, what's bringing customers, what's that driving challenge that they have, that you're helping to solve, that's different from the way storage has been done for many years? >> Yeah, I think, that's a great question, and I think that there's just been a real transition, and I think the transition has been largely created by the kinds of data that we want to manage and that we want to curate, and as we're seeing these sort of large unstructured data sets, it starts with the data, so as an example, you take equipment that used to exist in the past, like let's say in scientific computing. You used to have flow cytometers, which were just time-series data, and then what's now happened is is associate with ever flow cytometers, now a real-time video feed. When you look at the old world of microscopy, what you used to do is you used to flash freeze a sample, and basically take a picture of it, and now what you can do with lattice light-sheet microscopy is you can actually look at cells in vivo, while they're alive, and you can, I've personally gotten to watch a T cell move through a collagen matrix, and that's all microscopy, but generating orders of magnitude more data. That is, we're looking at these very, very different data sets, we're looking at very, very different kinds of computing, and what that requires is very, very different kind of infrastructure. And so, the infrastructure has just had to get a lot more intelligent, and the architecture has had to get a lot different, and what we've noticed is is that, that a lot of the patterns that are actually being built in the public cloud as they've taken kind of a fresh look at the computing models, have really become appropriate for this new kind of computing, and we don't see that on the premises, and that's really what we set out to go do. >> Yeah, it's interesting, it's probably the wrong term, but it sounds like we're describing kind of object storage 2.0. 1.0, I remember this healthcare use cases, everybody, when I was doing radiology, when you're doing certain healthcare and sciences, I need metadata, I need to understand that, but now there's just orders of magnitude more data, and technologies are making, it's denser, prices have come down, so the idea has been around for a little bit while, but it sounds like the technology's matured to allow kind of an explosion-- >> Well, and it's just a computing model, it's like one of these things where we're really, because of the emergence of microservices, one of the things that we've seen is applications want a restful interaction with the storage layer, and so, so it turns out that that tends to be very, very perfect for a cloud-like implementation where you can actually implement high volume, unstructured data really, really well via a restful API, where in the old world of POSIX semantics and that kind of transactional model, you just lost scalability. Either you had a lot of proprietary hardware, with that VRAM, you had proprietary interconnects data with things like InfiniBand, and nowadays, being able to loosely couple distributed systems is really the name of the game, and that's ultimately what we aim to build at Igneous, and that's all the technology, in terms of our commercial offering, the customer doesn't care what's behind it, but fundamentally, what you're looking for is the scalability and resilience that the cloud offers by doing that on premises. >> Yeah, so Steve, we had a really interesting crowd chat about a month or so ago talking about hybrid cloud, and the thing I've been saying for the last, probably year, is, as customers try to figure out what goes where in the cloud environment, you know, I've got SaaS, I've got public out of, I've got my private cloud, it's follow the data and follow the applications. In the cloud, things like mobile and even some video streaming, I think we understand how to do that, but why does on-premises make sense for your customers, your workloads, and your solution? >> Yeah, absolutely, and so, first, a little bit on hybrid cloud, there are kind of two different definitions of hybrid cloud, one is kind of the AWS VMWare scheme where what you're really looking to do is run your old stuff that you were running on-prem, in the public cloud, and you call that hybrid. But there's another way to look at it, which is to say, hey, let's take a look at the computing patterns that are being run in the public cloud, how do I bring that down to the premises? And the reason that you might want to do that is, it's really twofold, one is the gravity of the data, so it might just be that the datasets are too big to move back and forth over very thin internet pipes, and so you want to actually keep the data close to its source. The other is something that we've seen, which is really more of a preference, which is that while I think that cloud technologies actually have a lot of capability for security, there are a lot more hoops for folks to run through to ensure that they're compliant with their own internal policies, and where they've already set out a set of policies for how they run the stuff behind the firewall, sometimes it's just simpler for them to actually keep all of the data on the premises, and not actually have to worry about some of the issues in tracking, and compliance issues associated with how you move the data around. >> Yeah. One of the things we've heard from users is when they use public cloud, one of the things they really like is, sometimes the CFO's not fully onboard, but buying things as a service, so, they want to understand predictability, but they want to buy it as a service, understand, how does your solution fit into that kind of paradigm? >> That's great, I think our solution fits into both trends really, really well, because what we're really offering, we talked a little bit about technology, but really fundamentally, we're offering a service, and so when Igneous goes to a customer, our interaction is as a service. Customers interact with our service via APIs, and they get a bill for a subscription, and so it's an as-a-service model, you don't buy hardware, you don't install software, you don't have systems to manage. At the same time, there is a predictability that's a little bit of the downside of the public cloud, because there's a fee, generally, to access your data at a storage, and often, when people don't actually understand their data access and their data movement patterns, the costs of running applications in public cloud become quite unpredictable, and you actually don't run into that unpredictability with a solution like Igneous, because our data is on your local area network, and we don't charge you to access the data that's on your own network. >> So, I've come to an event like this, if I'm thinking about my storage today, the conversation in the marketplace has been, well, the new choices out there is, there's, the HCI, the hyper-convergence infrastructure, and there's flash, the AFA devices out there. And of course, even the lines between those are blurring, because I can have an all-flash configuration of hyper-converged, and some of the all-flasher a things are getting converged and put into more things, how do you help customers as the, what's the bullet point as to, well, this is for this kind of application, this is for this solution, and hey, there's this whole new category that you need to be thinking about. >> Yeah, I think that's perfect, and I think the real trick here is is that there's a difference between your hot tier and your flash tier, and your capacity tier, and fundamentally, the flash tier is really good when Time To First Byte is very important, so that might be for your relational database applications and things of that sort, where there tends to be a lot of searching through an index, and so you've got a lot of low-latency requirements. And then on the other hand, what you have is a capacity tier, they may be your video surveillance, they may be your large, unstructured documents, they may be your censor data, and in those contexts, you don't necessarily need the Time To First Byte, what you really need is capacity throughput, and so the overhead of setting up, for example, a restful connection is not significant when compared to the amount of data that actually needs to go through the system, and that's actually where restful semantics actually gets superior to positive semantics, when you have very, very large, unstructured data sets. Hyper-converge is actually a little bit of a different world, and I think that while hyper-converge has worked out pretty well, I think, for virtualization workloads, we've really found that when it comes to these very, very large unstructured data sets, hyper-converge isn't necessarily always the way to go, you tend to find a utilization issue between your compute and your storage layers, where you have to actually think about how you're balancing all this stuff, and so, really, the world that we've really seen emerge as new applications come forward, is there's really a trend to write microservices that are stateless, and to have them talk to a stateful layer, that's why in the public cloud, there's a pattern of having things like elastic container services talking to an S3, and we definitely see on premises that same type of things that's going to emerge. There's going to be some time to get there, admittedly, as I was mentioning kind of at the beginning, we've seen this really interesting set of interest patterns, one is from the folks who are developing these new applications that are utilizing unstructured data, there's a lot of interest we're getting right now from IT folks that are just getting started with object storage to do secondary workloads, to do backups, to do archives, and it's been interesting that we've been getting a lot of interest in our service as a new way to approach some of these data protection workflows. >> Alright, so Steve, last question I've got for you, came out of Stealth Q4 last year, what do we look for in 2017 from Igneous? >> Yeah, so I think that you'll see it on both of those fronts, I think that one thing that's going to be seen in 2017 is a lot more development on our side around building up a tool chain for folks to use for a data protection tier, and so, we've got a new offering coming online, we're calling it Igneous Insights, which provides information about what's currently on your primary storage tiers, we've got a whole set of replication services, they're coming up to do backup, archive, things like replication to the cloud, but what we're also really moving forward with is a lot of what's needed in the tool chain to really support hybrid and multi-clouds, so how you facilitate the data movement in and out of the cloud, as well how you do the auditing and management of the data, no matter where it lives. >> Alright, Steve Pao, really appreciate you catching up, and if you want to find out more about this category, check out cube365.net/trueprivatecloud, that's C-U-B-E, number 365.net/trueprivatecloud, which has resources from the whole industry, including from Igneous, including from Wikibon and theCUBE, as to what's happening kind of this true private cloud, hybrid cloud environment. We'll be back with lots more coverage here, thanks for watching theCUBE. (electronic music) >> Announcer: Since the dawn of the cloud, theCUBE has been there.

>> From Las Vegas. It's the cute covering knowledge sixteen Brought to you by service. Now carry your host David, Dante and Jeffrey. We're >> back. This is knowledge. Sixteen. This is the Q. We go out to the events. We extract the signal from the noise. This is day one of a three day Walter Wall coverage. The Cube has of knowledge. Sixteen Hashtag No. Sixteen like a lander is here. He's the CEO and vice chancellor of college services at Lone Star College. Longtime Cuba Lem like it's great to see again. >> Good scene again to >> another is >> great to catch up with this >> place, Another knowledge have a bigger and better than ever. You're you're speaking later on this afternoon. You've been over at the CIA event house this year going for you. You know, it's going >> great. The CIA oven, of course, is excellent lot of leadership foundations. Keynote TOC where, you know, service now is heading right now. Kind of. You know, that the shift and I always were still back to one of the themes from eons ago. Let's kill email. But the reality is emails not dead. So as we focus on it, you know, I came into this from the stance of moving the enterprise service management. So as I bring a team here, we really get the opportunity to see where we're at today in that comparison, and then how we can leverage the platform and move yourself forward >> So your role is evolving at Lone Star College, You said off camera, you're not giving up a title. A CIA, your CEO. >> Yes, I am the CEO >> and bread. That's not Teo, but your responsibilities are expanding. Talk about that side of things well, >> so well, last year actually been a year and a half. Now human resource is put underneath me. That's why the title change and all that to fit better and then analytics because, you know, analytics is not it much. People want us to think it should be buried inside of it. It never should, because it's about the business process. About the business service human resource is was just around the concept of aligning that service management what we had completed in it around service excellence. One of my right hand's basically put it as customer delight. Our focus is on customer no light. So it is about that communications piece. How do you talk to your customer? How do you move forward? How do you understand what their challenges are and help them find a solution. It may not be its instead of saying no, I can't do that for you. Sorry. You're out of luck. So in that, in that evolution, we've really moved ourselves forward on the enterprise service management platform side and early days, financial aid. We brought in student call centers. Now you've got human. Resource is were talking earlier about We're moving our legal in there. It's going to accelerate the pace it takes to get a contract illegal down TTO one day, maybe two days or some way didn't catch their approvals fast enough. So that's the big transformation from an organization >> of automated. That whole process over I actually, before going, I want to ask you questions about analytics. So you have. Ah, datas are that's working for you outside of it. Is that right or you? The days are >> well, you know, I actually have a team, >> have a data >> team s o. We're talking two different sets. Analytics too, because we're actually using service now. Analytics when it comes to the Service management analytics. Right. But for the organizational analytics, we actually have a large team that that does our analytics everything from dash boarding through, You know, in our case, core institutional reporting that's required. >> And is there a chief data officer as part of that team? >> I have a personal leading that group. >> De facto even >> factor. Yes. >> So there's a lot of discussion to about whether the CDO should report to the c. E. O. In this case, it does. But you had you had said things questions as to whether or not that Data Analytics function should be in it. It's not a night function. We kind of agree on that, but yes, but what kind of reports in to the head of, Well, >> you know, But see, when I when I sit down at that table, I sit down as the vice chancellor college services. So I have to sit down with three separate hats in front of me. Andi, I can't favor one over the other. Otherwise I wouldn't be doing my job currently. So when I look at the analytic side from a perspective, I will get on my team that provides the data, my database services and, you know, why are you not getting this done or what's happening here? So I've gotta look at it from all areas >> like Bill Belichick, GM coach way Tom Brady. You got to figure out who >> you are. At that point, I'm >> well. So is this how the role of the CEO is evolving? I mean, we've heard of this event previously. Frank's Lupin one year a couple years ago, said CEO should be a business person. Absolutely certainly seen examples of that. Now you're sort of given responsibility for you. No other services beyond just services. How was that role evolving? >> Well, rolls about for years. The question is, Is the CIA evolving? So? And that's where the challenges in the organization. So a lot of CEOs they're going through this process now where they're understanding that, Yes, I need to understand what are the business goals and objectives howto achieve those goals howto I had value to the organization. How did not become a cost center that has a target on my back? How you become an enabler enabler for the business And that's really where we came into that part of the process because we're recognized that Alcide nightie was here trying to help find solutions and provide better customer service. I myself come from a background in higher it for a long time through different institutions. And so when somebody talk to me about student services or student success, these air topics, I understand. I came to Lone Star originally because I didn't feel I had the strength in the academic side. And so when I first arrived there, I was really focused on academic understanding how the academic side operates and what they need in it. So I've had the opportunity to get well rounded in education, but it doesn't. It really is just about anybody that comes into this role. You must understand the business you're in, and then the next part is you need to be able to talk. I have an intelligent conversation around a topic area, bring value to the organization and come back with ideas. Well, you know, if we did this so the legal one was rather interesting because we had a new general counsel. Come on, and we're trying to help him, and he's like, Well, there has to be something better. You ask me. It's a better way to approach this. And we were able to dig through. Is that you know, What service? Now we've been doing this in HR. We're doing this here. So finally, we've got them into service now. And they see an opportunity the same way we see it. Which is we're improving. We're getting rid of the little stuff, the mundane work, You know that the task orientated work and we're focusing on the things that are really a challenge. And it has been there for a while because self service and all the other opportunities we've given the customer. Now we can shift that back and say, Okay, I cannot focus on what does the hard thing to get completed. How Doe I really put in effort in and a lot of a lot of staff hours into this one piece. >> So you started service management You mentioned hr Legal >> Financial Aid General Student Carlson are We're looking at scholarships right now. We tell a little bit ideas around our foundation in scholarships and what we could do for them. Grants. Grants are very big challenge because you have to really track and trend your grants. When you look at it, sm the areas that we've matured there are phenomenal, and then we're getting ready now to move and I Tom, which we didn't do because we already built a complete structure around that we were feeding that to service now. So now I'm looking at from opportunity that if I can eliminate a lot of the tools, I put in a play and get into one single tool and maximize the value of that tool. So I think you heard me many times when we talked in this. It's never about the tool. It's always about people in a process first. And then how does the tool come in? Well, this platform, we can actually adjust that because we're not We're not bound by the tool. Like the legal module. They have a great legal module. Well, it didn't fit what we needed. So it's been adjusted accordingly. T meet our needs from the platform side by keeping the core components so we haven't customized. We haven't taken it to a path where we can never upgrade. But at the same time as we looked at the process they had and how do we take that process and then actually put it into play with service now? >> And they were all inward service now do you worry about locking? >> Always. I think >> that Do you manage that risk? >> Well, the very first thing, to be honest with you is any time you enter in any cloud situation or any product situation, you want an exit strategy of some kind In case something goes wrong, something happens. You have to be at that point. So the only way to manage it really is to one. Keep a good, strong partnership. I believe that I have a strong partnership was service now. I don't believe it's a vendor relationship and I think that's critical because as we look at what we're doing each time as a partner, were were engaged with things like Where you heading? What's happening next? You know what? And then the same thing with the user group community were engaged with that group. So from a partner standpoint, we look at that first. But if the worst case scenario came, I've got to be able to get out of the solution. I've gotta have an exit strategy which we actually had designed before we went into it. Now the question becomes is we get further and further entrenched. What do we do and I'm comfortable. I'm comfortable that the company and the operations are going the right direction for me at the same time. If I'm gonna protect my organization to make sure we're safe. >> And that's a big, big part of transparency on the part of service now and your ability to communicate, you know your road map and your needs, I mean, a scale of one to ten ten being, you know, really transparent. How Where would you put service now as an organization >> who? That's a tough one, Especially when I'm sitting here. >> Uh, Frank's not around is a freaking God. He's breathing guy. Let's see. You know, >> a CZ forest transparency. I would give him good, strong seven. >> Yeah, >> I think I would. No company can be completely transparent. They've got a lot of things working in the back room or ideas that they're moving forward >> because they don't know. They don't know what they don't know. Going. Yeah, >> but there's there's ideas that they have that they're moving forward. It's gonna like today with the watch demo. I'm like, Oh, yeah, I love wearables. I you know, I live off. I could very easily now just say Oh, yeah, I just >> got an e mail. Sorry. Yeah, but, >> uh, at the same time is, you know, for them to bring that forward at this point. So they're creative and looking at these items, but they don't want to get out there too soon. >> I'm curious on the partner vendor, you know, mentioned a couple aspects of what defines that relationship of all the vendors you have. How many do you consider to be? You know, close business partners where your, you know, really sitting at the table and building a long term relationship, You gotta have an exit, but its life so much easier. If >> you're working with a partner verse a vendor right now, I would stay out of our partner strategy. We've got four. That's it. But those are four core providers for the organisation. Their leaders in the market space. That's the other key. Most my partnerships or with leaders, of course service. Now, at the time when we first engaged with them and actually I would say, from a partnership standpoint, a strong partner was service. Now, probably since about two thousand ten, we've been on the platform since two thousand eight. So we built that partnership over that first couple of years. You got past that vendor relationship and then moved on from there. But right now, just our core technology stack would be sitting in that partnership room, and I've got others than in that court Technologies. Technically, I'm not a partner there. A vendor there there were by cell. They have a great product, but they don't really want to bring us into that point. And we really haven't approached that point. >> We had a great discussion off camera about you had mentioned. You're looking at potentially expanding into this security realm with service now. And you were sharing with me like your philosophy on security. So I want to document that The premise that I'm going to put forth summarizing our conversation is, you should organizations increasingly should treat security as an ongoing part of their business continuity plans, not necessarily as a sort of separate stovepipe managed by a few security practitioners. Is that a fair summary? >> Yeah, Service continuity is what I use. I don't have >> service continuity, service continuity, that your business. Yeah, it always comes >> out to service continuity. How do you How do you continue that process and provide the same level of service in the in the event. It's very simple to me as I look at all those events as like problem management incident management, you have a response that you have to take, so it has to be inherit. It has to be natural. You just do it way we're talking about that. That response, specially for security, is what's more important is that you have everything planned out and you're ready to deal with that incident in that rock response because it's gonna happen. So how you handle that response can actually dictate your future, right? Wei had that little bit of that discussion there, too. So it does come down to that service continuity. How do you continue to move forward as and get through that threat and then afterwards make sure that you prevent that from happening again. >> Unlike many CEOs that I talked to, your discussions with the overseers at the college are not entrenched largely in the security discussion. You've earned some level of trust with regard to your capabilities. Is a business your ability to respond. Can you talk about that a little bit? How you actually achieve that, what expectations you were able to set and how you're able to execute on that? >> Well, the biggest, biggest part, especially when you look at it at that event, it's how. How is it performed overall over the history? You've gotta have some history. You've gotta have some credentials. How do you deal with these responses in these emergencies? That gives you a little bit more slack in that process, but it is about constant communications. So what the board received for me is communications. It's very straightforward. Typically, in an annual report type format, Short updates clear, concise updates. But then, when event happens, we're talking about the flood that happened in Houston, and very quickly I had an email out and my service test team was already on it. They already implemented their service continuity because while we may be shut down, we have students online taking classes. We have students that need to know what's going on, what's happening so they're calling in, and our service desk continued on through that entire process without issue. So they see that as an example on a regular basis. If we have a system down, everybody gets to see exactly. We did X, Y and Z or if we even have a like today, I should say today Monday we had a blip. We did, Nam. We have. We saw performance degradation. We immediately had a team on. We had a WebEx open with everything running. So we're preparing for a service continuity event that didn't happen. And they see those two because the business units are getting these notifications. Hey, we've gotta WebEx open. We have this issue coming up, and when they see that, they realize how fast we are to respond to what could be a potential issue that we built that trusting relations. >> So that's a good example. If I understand it correctly, the regime that you've put in place puts a heavy emphasis on the response. I mean, obviously you're trying to stop the bad guys who wouldn't go innovated on the response as well. Is that a fair assessment? >> Yes. I mean, the threats, goingto threats gonna happen. The threat happens all the time. So it is about that response. It is being quick to respond to communicate and take care of the problem. >> Do you think that's changed amongst the CEO community in the last ten years that that the shift in mindset toward that response versus so to keep him out big dig a bigger mode, Wider moat. >> Well, you can dig a big, wide moat. Doesn't matter. >> I think I've >> got these big, robust to hot data centers. Amazing firewalls. They're redundant. You tried overload him. They're going to take over. I've got next gen firewalls behind that. I've got you. Just you, layer layer. This tax of protection I have put in you still have to prepare that we're talking about it is Okay, so that's the perimeter. Well, inside my perimeter is one hundred thousand students, those hundred thousand students around my network. So how do I protect against that? So now I have inside perimeter protection. You can build all this entrenchment that you want to build. But the reality is you need we prepared Just gonna happen that you are. Somebody is going to get to that point. Or at least then the alarms up that you have to respond to >> service now is talking yesterday at the financial analyst meeting about you know, the statistic. And I've heard a range here, but it's large that that after an intrusion it takes, on average two hundred five days for the average organization toe. Realize that there's been an intrusion. I've seen numbers as high as three, three, three, fifty, etcetera. Um, first of all, does that sound consistent with what you see in there in the real world and conservative now help compress that time. >> So the interest was service. Now, of course, is tracking and trending those responses. I, tom and Service watch. There's a lot opportunities with those tools and course we have a perimeter we have a pile of tools were using. In our case, our threats are a bit different because, of course, we're not a big financial institutions. So we were not right with all those other pieces. But you're from the days to recover from a major event and my peers and what that have actually experienced a data loss event? Yeah, it easily is that it is easy. That >> and you think, feel is, though that service now could help you attack that compress that >> yes, mainly through the data collection and then the reporting and then as the events going on all of this information that's happening in the problem management side. What you're seeing from outside information coming in and technicians on the inside updating information as they go through it. You have a comprehensive log of the event from start to finish. >> Now you're speaking just right after this. I think you're just what? You're what you're talking about. >> The shift for my tea service management. Teo Enterprise Service Management. It's actually Enterprise. Wow. But I'm actually walking through the journey. But the best part about that is it's the pitfalls we learned along the way because Wei didn't know we went to Enterprise Service Management. It's kind of I think we had a discussion when we went to the cloud. I didn't know we went to cloud. Exactly. I just knew we went to this heavy virtualization, these two out data centers and I kind of realized, Wow, we really pushed into this new this new wage, this new change. >> We've got a new operating model on on, >> you know. But now yeah, it really is about how we are journey to enterprise service management and the fact that we actually started in a price servicemen before I've even heard of it. It just was around The fundamentals of Hungary. Better service provider. How can we help our customers, uh, achieve their objectives and the business units make it simpler? >> My last question is, what's exciting you these days? A CEO practitioner. What? Float your boat? True. >> What's exciting? You see, I asked if you're gonna give me any hard >> questions for you. That's exciting. >> You know, What excites me is that you're seeing the maturity level of a cloud. The platform side. It is so flexible that you can respond to a customer need quickly that you, khun dynamically spin up the capacity Your When I first started this process, trying to build this high availability was difficult. Now hie availability is really not difficult. It's just around. The process is so that the maturity of the technology and the maturity the service piece that excites me. But it also excites me when I start seeing new team, people come into the market space and they understand that already they're coming in with an idol understanding there they're coming down, understand that business mentality. So original Lighty practitioners didn't have that business background. They didn't have that communication skill you're seeing a lot more of it. The organization now. >> Well, you're a real leader in this space. You've got a lot of experience. Appreciate you sharing your knowledge. And I'm sure the service now community does as well. So good luck with your talk this afternoon. And thanks again for coming. >> Thank you. It's great being here. >> All right, Link a lender. Always a pleasure. Keep right, everybody. This is the cue. We'LL be back Live from Mandalay Bay. This is knowledge sixteen. Right back. >> Service. Now is the time.

from Las Vegas accepting the signal from the noise it's the kue coverage interconnect 2016 brought to you by IBM now your host John hurry and Dave vellante okay welcome back around we are here live in Las Vegas for IBM interconnect 2016 special presentation of the cube our flagship program would go out to the events and extract the signal from the noise I'm John forreal echoes gave a lot they are next guest pricing Kohler who's the chief information technology officer and I'm saying this for the first time on the cube the weather company and IBM business welcome back to the cube thank you very much glad to be back last time you weren't an IBM business we were just the weather company were just the weather company so congratulations on your success want to say we really big fans of it but what Papa Chiana the team have done is visionary bold and very relevant so congratulations hey how's it feel it is grateful din we are really excited the opportunity with the IBM platform and you know the reach and the capabilities I mean it it really helps accelerate what we were trying to get done as the weather company you know as our own standalone business um and you know as you try to prepare and protect the entire planet all of its people and all of its businesses prepare and protect them for tomorrow which is really what the weather is company is all about finding that intersection of consumer behavior helping prepare and protect you as a in your personal life and your family but also you as a business owner how do we prepare and protect you to do better tomorrow because of the weather and the insights that we can provide fit straight into the work the Bob picciano in team have been doing with the insights you know economy with Watson and analytics with insights as a service all of that just kind of plugs together in it it really is a natural fit it's interesting to see IBM's move we were asked to guess on from IBM earlier and Jamie Thomas said it's all open source we want to get in early so this is an early bet for IBM certainly a bold move with the weather company but it's interesting the scuttlebutt as we talk to our sources inside the company close to the company have telling us that the weather companies is infiltrating and affecting the DNA IBM in a good way and you guys have always been a large scale data company and that is what all businesses are striving to digitize everything yes and so take us through that I mean one I think it's fair to say that you guys are kind of infecting I play in a positive way the mindset of being large-scale data yeah well why is that so compelling and how did you guys get here obviously whether the big data problem share some commentary around where it all came from well i think you know it's in my DNA first of all and it's in our company's DNA it's are no teams DNA you know I'm a change agent you would not want to hire me to maintain something good if you want to hire me to you know to break something and rebuild it better that's I'm your guy so you know I think when you look at the movement from you know the kind of the movement over time of IBM and you know the constant evolution that IBM goes through time is ripe when you take the cloud capabilities and you take data and you take analytics and the whole concept and capabilities of Watson Watson gets smarter as it learns more Watson can only be as smart as the data you feed it and so for Watson to continue to learn and continue to solve new problems and continue to expand its capability set we do have to feed it more data and and so you know looking at whether whether it was the original big data problem ever since the first mainframe the first you know application ever written on a mainframe was a weather forecast and ever since then everybody's been trying to figure out how to make the forecast more accurate and a lot of that comes from more data the more data you have the more accurate your forecast is going to be so we've been trying to solve this big data problem Walt and Dave talks about it was saw earlier in the opening about digital assets and in this digital transformation companies have to create more digital assets that's just dating yeah in this new model so when you look at the data aspect you say whether also is a use case where people are familiar with we were talking before we went on camera that people can understand the geekiness of whether it's different they're familiar with it but also highlights a real-life use case and the IOT Internet of Things wearables we heard you have sports guys on here tracking sensors this brings up that digital digitizing is going to be everything not just IT right it makes it real right if I think about my parents right we've been talking about IOT hey dad you're gonna have a connected refrigerator why does he care what do I need a connected refrigerator for but as you start to bring these insights to life and you make them real and you say you know what if I actually understand the humidity levels in your house and I can get that off the sensor on the air intake of your refrigerator I can now correlate that the humidity level outside of your house and I might be able to actually tweak your HVAC and I can make that run efficiently and I can now you know cut thirty percent of your cooling costs and all of these you know examples they're integrated they become real yeah and and I think weather is great because everybody checks their weather app the weather channel app or the weather underground app every day they're always looking at it and you know we get it right seventy-eight percent of the time we'd get it wrong sometimes we're constantly working to maintain our number-one position and data accuracy on weather forecasting and you know the more data we have the more accurate we can make it and so we've got any safer to you think just think about the use cases of people's lives slippery rose you know events correct I mean it's all tied in no goes back to another you know if I understand what's going on with the anti-lock braking system of a car and I already have a communication vehicle into everybody in that car which is our appt in their pocket I can alert them if the car is up ahead are having here are their abs activated and if all of the cars up ahead are having their abs activated I could alert them two miles back and say hey get ready slow down it's real it's not forecasted it's real data I'm giving you a real alert you should really take action and you know as we move from you know weather-alerts that we're looking out forward in time many hours as we're now doing rain alerts where we tell you it's going to start raining in the next seven minutes ten minutes people love those because it's right now and I can make a decision right now lightning strikes are always fascinating oh god because I gotta see crisis so last fall at IBM insight we interviewed David Kinney death your CEO and then right after I think was the week after I was watching some you know I was in Boston watching some sports program and there's bill belichick complaining about the in accuracy of whether i'll try that whether some reporter asked him about you know you factor in the weather i don't even pay attention i look at the weather forecast they're always wrong as a wait a minute I just I just interviewed David Kennedy he was bragging on the weather is the accuracy and how much it's improved so helping you mentioned seventy-eight percent of the time it's it's gotten better over time it has it still got rooms we're not perfect so so talk about that progression it is the data but how much better are you over time where is that better is it just short term or is it longer term at so color to that it's a great question and it's a fair point I think one of the biggest changes we've made in the last three years that the weather company is we've taken our forecast from what was roughly 2 million locations where we would do a forecast two million locations around the globe and today we we create a forecast for 2.2 billion locations around the globe because the weather is different at Fenway then Boston Logan it's just different than the the start time of rain the start time of a thunderstorm you know that's gonna be different now maybe five minutes but it's different the temperature the wind it's different and so as we've increased the accuracy and granularity of ours are our locations we've also done that from a time perspective as well so we used to produce a forecast every four to six hours depending upon how fast the models ran and did they run and complete successfully we now update our forecast every 15 minutes and so we we've increased the the you know all aspects of that and when you when you now think about getting your weather forecast you can no longer just type in BOS for your airport code and say i want to know what the weather is at boston logan if you're you know if you're in cambridge the boston logan forecast is not accurate for you you know five years ago every that was fine for everybody right right and so we have to retrain people to think about and make sure that when they're looking for a forecast and they're using our apps they can get a very specific forecast for where they are whatever point on the globe they are and and don't have you know Boston you know Logan as your you know favorite for your city if you're sitting in Cambridge or your you know you know it in Andover further outside where I am now where you gonna be my guess I gotta get so different you leverage the gps capabilities get that pinpoint location it will improve what the forecast is telling so I feel like this is one of those omni headed acquisition monsters for lack of a better term because when the acquisition was first announced is huh wow really interesting remember my line Dell's by an emc IBM is buying the weather company oh how intriguing it's a contrast it's all about the data the Dane is a service and then somebody whispered in my ear well you know there's like 800 Rockstar data scientists that come along with that act like wow it's all about the data scientists and then on IBM's earnings call i hear the weather company will provide the basis for our IOT platform like okay there's another one so we're take uh uh well i think IBM made a very smart move i'm slightly biased on that opinion but I think I be made a very smart move at very forward-looking move and one built on a cloud foundation not kind of a legacy foundation and when you think about IOT data sets we ingest 100 terabytes of data a day i ingest 62 different types of data at the weather company i ingest this data and then i distributed it massive volumes so what we had fundamentally built was the world's you know largest cloud-based iot data platform and you know IBM has many capabilities of their own and as we bring these things together and create a true next-gen cloud-based IOT data engine the ability for IBM to become smarter for Watson to become smarter than all of IBM's customers and clients to to become smarter with better applications better alerts better triggers and that alerts if you think about alerting my capability to alert hundreds of millions of people weather-alerts whether that's a lightning alert a rain alert a tornado warning whatever it is that's not really any different than me being able to alert a store clerk a night stock clerk at the local you know warehouse club that they need a stock you know aisle three differently put a different in cap on because we now have a new insight we have a new insight for what demand is going to be tomorrow and how do we shift what's going on that alert going down to a handheld device on the guy driving the four club yeah it's no different skoda tato yeah the capability to ingest transform store do analytics lon provide alerting on and then distribute data at massive scale that's what we do we talk about is what happened when Home Depot gets a big truck comes in a bunch of fans and say we know where this know the weather company did for you yeah we don't understand you'll understand you'll fake it later they file a big on the top of it so I OT as well as markets where people don't can't understand that some people don't know it means being like what's IOT Internet of Things I don't get it explain to them some little use cases that you guys are involved in today and some of these new areas that you're highlighting with with learning somehow see real life examples for for businesses and users there is a smarter planet kind of you know safe society kind of angle to it but it's also there's a nuts-and-bolts kind of practical if business value saving money saving lives changing you know maintenance what are some of the things share the IOT so there's there's only two things there so one is what is IOT and IOT really is is sensor data at the end of the day computers sensors electronic equipment has a sensor in it usually that sensor is there to do its job it's there to make a decision for what if it's a thermostat it has a sensor in it what's the temperature you know and so there are sensors in everything today things have become digitized and so those sensors are there as next as those next evolutions have come online those those sensors got connected to the Internet why because it was easier than to manage and monitor you know you know here we are at the mandalay bay how many thermostat sensors do you think this hotel casino complex has thousands and so you can't walk around and look at each one to understand well how's the temperature doing they all needed to be shipped back to a central room so that the in a building manager could actually do his job more efficiently those things then got connected so you could look at it on a smartphone those things they continued to get connected to make those jobs easier that first version of all of those things it was siloed that data SAT within just this hotel but now as we move forward we have the ability to take that data and merge it with other data sets there's actually a personal a Weather Underground personal weather station on the roof of the Mandalay Bay and it's actually collecting weather data every three seconds sending it back to us we have a very accurate understanding of the state of the Earth's atmosphere right atop this building having those throws is very good for the weather data but now how does the weather data impact a business that cares about the weather that has there we understand what the Sun load is on the top of this building and so we can go ahead and pre-heat your pre cool rooms get ahead of what's changing out sign that will have an impact here inside we have sensors on aircraft today that are collecting telemetry from aircraft turbulence data that helps us understand exactly what's going on with that airplane and as that's fed in real-time back down to the earth we process that and then send it back to the plane behind it and let that plane behind it know that it needs to alter it course change its flight plan automatically and update the pilots that they need to change course to a smoother altitude so gone are the days of the pilot having to radio down and fall around his body it's bumpy to get these through there anywhere machines can can can do this in real time collected and synthesize it from hundreds of aircraft that have been flying in that same route now we can actually take that and produce a better you know in flight plan for those for those machines we do that with with advertising so you know when you think about advertising you be easy the easy example is hey we know that you're going to sell more of X product when y weather condition happens that's easy but what if I also help you know when not to run an ad how do I help save you money you know if I know that there's no way for me to actually impact demand of your product up or down because we know over the course of time looking at your skew data and weather data that no matter what what we do weathers gonna have this impact on your product save your money don't run an ad tomorrow because it doesn't matter what you do you're not going to actually move your product more that's great and it's much business intelligence it's all the above its contextual data help people get insights in subjective and prescriptive analytics all rolled into one in a tool that alerts the actual person may explain to people out they were predictive versus prescriptive means a lot people get those confused what's your how would you prescriptive is you know where we want data that just tell us what to do based upon historic looking trends so i can take ten years of weather data and I can marry that up with ten years of some other data set and I can come up with you know a trend based upon the past and with that then I could prescribe what you should do in the future hey looks like general trend bring an umbrella tomorrow it's good it might rain but if I get into predictive analytics now I can start to understand by looking at forward-looking data things that haven't happened yet or new data sets that I'm merging in in real time oh wait a minute we thought that every time it rained more people went to this gas station to fill up but wait a minute today there's an accident on the road and people no matter what we do they're not going to go to that gas station because they're not even going to drive by it so being able to predict based upon feet of our real-time data but also forward-looking data the predictive analytics is really around the insights that we want to guess I got to ask you one question about the IBM situation and I want you to kind of reflect get him get you know all right philosophical for a second what's the learning that you've had over the past few weeks months post-acquisition inside IBM is there a learning that you to kind of hit you that you didn't expect there's something you'd expect what sure what was your big takeaway from this experience personally and you had some great success in the business now integrated into IBM what's the learning that cuz that's comes out of this for you I am really proud of the team at the weather company you know I I think what we have been able to accomplish as a small company you know comparative to my four hundred and sixty-eight thousand colleagues at IBM yeah what we've been able to accomplish what we've been able to do is really you know it's impressive and I've been proud of my team I'm proud of our company I'm proud of what we were able to get done as a company and you know the reflection really is as you bring that into IBM how do you make sure that you can you can now scale that to benefit such a large organization and and so while we were great at doing it for ourselves and we built an amazing business with amazing growth you know attracted lots of people that looked at buying us and obviously IBM executing on that I think that's amazing and I'm proud of that but I think my biggest reflection is that doesn't necessarily equate to success at IBM and we now have to retool and retrans form ourselves again to be able to take what we know how to do really well which is build great capabilities build big data platforms build analytics engines and inside engines and then armed a sea of developers to use our API we can't just take what we've done and go mate rest on your laurels you gotta go reinvent so I think my biggest you know real learning and take away from the kind of integration process is well we have a lot to learn and we have a lot of change we need to do so that we can actually now adapt and and continue to be us but do it in a way that works as an IBM ER and and that's that's there's there's going to be an art to this and we've got a ways to learn so I'm going in while eyes wide open around what I have to learn but I also am very reflective on on how proud I am as a leader of the team that you know has created you know such an amazing capability acquisition is done you savor it you come in you get blue washed and I hope I had a Saturday afternoon where I say okay got all like what is this gonna think so and then okay so you you wake up in the morning and you sort of described at a high level you know what you're doing but top three things that you're focused on the next you know 12 12 months so so you know the biggest thing that I'm focused on number one is making sure that we protect the weather company culture and how we know how to do and build great things and so I've got to lead us through obviously becoming integrated with IBM but not losing who we are and IBM is very supportive of that you know Bob picciano his team have been awesome and you know John Kelly and team have been awesome everybody that we have worked with has been so supportive of Bryson please make sure you find the right way through this we don't want to break you and I think that's natural for any acquisition for any yeah but you guys aren't dogmatic you were very candid saying we're gonna transform ourselves and adapt absolutely and so and so so we've got that on wrestling on my mind how do we go find immediate wins there's there's a a million different ways for us to win there's thousands of IBM sales teams that are out in front of clients it's just today with new problems how do we quickly adapt what we've been good at doing and help solve new problems very quickly so that's on my mind and then you know wrapping that in a way that becomes self service we can't I don't want to scale my team through people to solve all these problems I want to find a way to make sure that all these capabilities new data sets new insights new capabilities that we bring the life I want to do that in a self-service way I want to make sure that our technology the way we interact with developers the developer community that we bring in to kind of work on our behalf to make this happen I don't want to solve all these problems I want to enable others to solve the problems and so we're very focused on the self service aspect which i think is very new prices thank you so much taking the time out of your busy schedule to see with us in the queue good to see you again or any congratulations IOT everything's a sensor that we're a sense are here in the cube and we sense that it's time to go to SiliconANGLE DV and check out all the videos we have a purpose our sensor is to get the data to share that out with you thanks for the commentary and insight appreciate it whether company great success weather effects of song could affect stock prices all kinds of things in the real world so we had a lot of a lot of big data thank you very much look you here live in Las Vegas right back more coverage at this short break

live from Gillette Stadium in Foxboro Massachusetts extracting the signal from the noise it's the kue covering Vitas New England winter warmer 2016 now your host Stu minimum welcome back to the cube I'm Stu miniman with Wikibon com we are here at the 2016 v tug winter warmer at Gillette Stadium home of the New England Patriots and very excited to have a patriot Hall of Famer three-time Super Bowl champion number 80 Troy brown Troy thank you so much for stopping by oh man thank you for having me on I appreciate it alright so so so Troy you know we got a bunch of geeks here and they they they we talked about you know their jobs are changing a lot and you know the question I have for you is you did so many different jobs when you're on the Patriot you know how do you manage that how do you go about that from a mindset i mean i think so many of the job you did we're so specialized never spent years doing it yet you know you excelled in a lot of different positions i think first of all i think the coach bill belichick you know I think he does a good job of evaluating is his people and his players and the people that work for them and think about him he never asked an individual to do more than they can handle and I think I was one of those individuals that he saw that could you know didn't get her out about too many different things that didn't get seemed like I was overwhelmed at any moment with the job that I was at already asked to do and if I had to do multiple jobs then I would probably be one of those guys that could handle that type of situation so it started with him and in me I guess it was just my personality and my work havoc and my work ethic and just never letting the opponent know that I was a little bit shaken a little bit weary a little bit tired at times and I just continue to chip away and be my job and not you know and I took a lot of pride in being able to manage and do a lot of different things at one time and and then really accelerate yeah so you saw the transformation in the Patriot organization I mean you know it great organization here in New England but you know we were living in a phenomenal time for the Patriots over the last 20 years it and what do you attribute that that transformation to well I think it started you know you look at when Robert crab bought the team in 94 which I was here year before he bought the team in 93 I was glad to be true Bledsoe and parcels are the first year and that really Parcells really kind of got people around here excited about football I think for the first time they were having you know capacity crowds at training camp out at Bryant college you know something they never did before I mean you're talking about a team that won two games the year prior they were two and 14 and things got so lucky winning those two games in 1992 so you bringing a guy that's you know when a couple super bowls with the Giants high-profile guy gets everybody excited about the possibility of winning and I think things started to change then and then you bring in a hands-on owner because I believe James awethu wine was the previous owner that he bought the team from and lived in st. Louis it can't be hands-on when you you know live you know half the country away from from here so he bought the team and bought the local guy and again that the enthusiasm goes through the roof and expectations in through the roof we make the playoffs in 1994 and you know the things happen they don't get along and then when you go through another coach Pete Carroll for three years and you bring in Belo check and he drives a young quarterback by the name of Tom Brady and you know those types of things those people those guys able to handle different things and different jobs as well you know and you couple that with you surround them with good people like myself david patten Antwone Smith I laws or the lawyer milloy Rodney Harrison guys that kind of embody the Patriot Way and you get what you have today and it all started with the fact that mr. Kraft and Bill Belichick now been together with 15 16 years and I think you look across the NFL across any sport you don't see the type of longevity and the type of continuity that those who have and you throw on Tom Brady into that mixers been along for that entire ride as well you just think you're not going to find out in any other sport any other team maybe a couple here you notice end Antonio Spurs no in longevity I believe it is the key and you have to build that you know see you see too many owners that throwing the town were too quick yeah you know what the young coast is trying to build a team in the system yeah so I have to ask you if you had to choose one for 15 years pray to your Belichick for 15 years yeah 15 years that maybe Brady because you know it eventually will come to an end you know Bella chikan probably coach I want to know one only known for longer than 15 years we had to choose one for 15 years I guess I'll go with Brady but you know I don't think I know if one works not the other you know so that's kind of how to be a question that people be asking for many many years to come yeah so personally for you when you look back at your career you know any favorite moments that they have that mean there's so many to so many the franchise for yourself i mean i could think of all the ones that i had the pleasure to say that was a big punt return against the pittsburgh starters yeah AFC championship no well botas me start up the scoring for us yeah that was a big moment that the strip in 06 in the superbowl that year it was a big play yeah able to get us into the AFC championship game this all the Super Bowls that we were part of and then were able to win and all those moments are just so treasured and value about me that is kind of hard to place a place one over the other but you know it was all a lot of great and fantastic moments for us all right so last question I have for you looking at the Patriots today what's your prediction for the Patriots you know going on in the playoffs here going to the AFC champ I think it a bit difficult task Denver's not been a friendly place for the Patriots over the history of this franchise not just now but it is specifics as to why it's so tough to find there I don't know I don't know what it is I mean you could say the altitude but we've been out then we played well at times even there's team this year they played well the first time they went out there had an unfortunate drop punt you know that kind of changed the complexity of the game and things just changed I mean it's that's the kind of luck that we have the last time I played out there was I think 05 I think of something in the divisional round and I fumbled Kevin Faulk fumble Tom Brady threw a pick-six basically and it was like you threw your most dependable players that turned the football over and didn't play well you know how often that would that happen so Rob Gronkowski gets hit in the knee this year so and then lose him for a couple games and his season starts to turn so just so many unfortunate things that happen out there but you have to give Denver a lot of credit as well because you know they come out and they play hard to have a really good defense quarterback that can be really good you know he's a game manager at this point in his career that's a great job of doing it you know and it seemed to rally behind his presence on the field so it'll be a tough task for the Patriots even though I think the Patriots do have the better football team overall it's just been a difficult place for the New England Patriots to get wins yeah in the past I said you have a matchup for the Super Bowl that you're picking I'm picking the Patriots for sure and from what I saw from Carolina last week I got to go with Carolina playing at home against Arizona I think the defense is just too tough and Cam Newton and that run game and that offensive line has just been been pretty remarkable and surprising after losing probably the best offensive weapon in Kelvin Benjamin so yeah well you know a little something about a Carolina versa you know New England Super Bowl so hopefully things will turn out like it did last time try really appreciate you stopping by thank you so much for trying to save the program will be right back here with a wrap-up of the cubes coverage of the V tug 2016 winter warmer thanks so much for watching you