[Music] hi I'm Stu minimun and this is the cube conversation in Silicon angles Palo Alto office happy to welcome back to the program Lear on survival who is the co-founder and CEO of Weka IO thanks so much for joining me thank you for having me over alright so on our research side you know we've really been saying that data is at the center of everything it's in the cloud it's in the network and of course in the storage industry data has always been there but I think especially for customers it's been more front and center well you know why is data becoming more important it's not data growth and some of the other things that we've talked about for decades but you know how was it changing what are you hearing from customers today so I think the main difference is that organization they're starting to understand that the more data they have the better service they're going to provide to their customers and there will be an overall better company than their competitors so about 10 years ago we started hearing about big data and other ways that in a more simpler form just went over sieved through a lot of data and tried to get some sort of high-level meaning out of it last few years people are actually employing deep learning machine learning technique to their vast amounts of data and they're getting much higher level of intelligence out of their huge capacities of data and actually with deep learning the more data you have the better outputs you get before we go into kind of the m/l and the deep learning piece just did kind of a focus on data itself there's some that say you know digital transformation is it's this buzzword when I talk to users absolutely they're going through transformations you know we're saying everybody's becoming a software company but how does data specifically help them with that you know what what what is your viewpoint there and what are you hearing from your customers so if you look at it from the consumer perspective so people now keep track record of their lives at much higher resolution than the and I'm not talking about the images rigid listen I'm talking about the vast amount of data that they store so if I look at how many pictures I have of myself as a kid and how many pictures I have of my kids like you could fit all of my pictures into albums I can probably fit my my kids like a week's worth of time into albums so people keep a lot more data as consumers and then organization keep a lot more data of their customers in order to provide better service and better overall product you know the industry as an industry we saw a real mixed bag when it came to Big Data when I was saying great I have lots more volume of data that doesn't necessarily mean that I got more value out of it so what are the one of the trends that you're seeing why is you know where things like you deep learning machine learning AI you know is it going to be different or is this just kind of the next iteration of well we're trying and maybe we didn't hit as well with big data let's see if this does it does better so I think that Big Data had its glory days and now where they're coming to to the end of that crescendo because people realized that what they got was sort of aggregate of things that they couldn't make too much sense of and then people really understand that for you to make better use of your data you need to employ way similarly to how the brain works so look a lot of data and then you have to have some sense out of their data and once you've made some sense out of that data we can now get computers to go through way more data and make a similar amount of sense out of that and actually get much much better results so just instead of going finding anecdotes or this thing that you were able to do with big date you're actually now are able to generate intelligent systems you know what one of the other things we saw is it used to be okay I have this this huge back catalogue or I'm going to survey all the data I've collected today you know it's much more you know real times a word that's been thrown around for many years you know whether it do you say live data or you know if you're at sensors where I need to have something where I can you know train models react immediately that that kind of immediacy is much more important you know that's what I'm assuming that's something that you're seeing from customers to indeed so what we say is that customers end up collecting vast amounts of data and then they train their models on these kind of data and then they're pushing these intelligent models to the edges and then you're gonna have edges running inference and that could be a straight camera it could be a camera in the store or it could be your car and then usually you run these inference at the endpoints using all the things you've trained the models back then and you will still keep the data push it back and then you should you still run inference at the data center sort of doing QA and now the edges also know to mark where they couldn't make sense of what they saw so the the data center systems know what should we look at first how we make our models smarter for the next iteration because these are closed-loop systems you train them you push through the edges the edges tell you how well you think they think they understood your train again and things improve we're now at the infancy of a lot of these loops but I think the following probably two to five years will take us through a very very fascinating revolution where systems all around us will become way way more intelligent yeah and there's interesting architectural discussions going on if you talk about this edge environment if I'm an autonomous vehicle now from an airplane of course I need to react there I can't go back to the cloud but you know what what happens in the cloud versus what happens at the edge where do where does Weka fit into that that whole discussion so where we currently are running we're running at the data centers so at Weka we created the fastest file system that's perfect for AI and machine learning and training and we make sure that your GPU field servers that are very expensive never sit idle the second component of our system is tearing two very effective object storages that can run into exabytes so we have the system that makes sure you can have as many GPU servers churning all the time and getting the results getting the new models while having the ability to read any form of data that was collected in the several years really through hundreds of petabytes of data sets and now we have customers talking about exabytes of data sets representing a single application not throughout the organization just for that training application yeah so a I in ml you know Keita is that that the killer use case for your customers today so that's one killer application just because of the vast amount of data and the high-performance nature of the clients we actually show clients that runwa kayo finished training sessions ten times faster than how they would use traditional NFS based solutions but just based on the different way we handle data another very strong application for us is around Life Sciences and genomics where we show that we're the only storage that let these processes remain CPU bound so any other storage at some points becomes IO bound so you couldn't paralyzed paralyzed the processing anymore we actually doesn't matter how many servers you run as clients you double the amount of clients you either get the twice the result the same amount of time or you get the same result it's half the time and with genomics nowadays there are applications that are life-saving so hospitals run these things and they need results as fast as they can so faster storage means better healthcare yeah without getting too deep in it because you know the storage industry has lots of wonkiness and it's there's so many pieces there but you know I hear life scientists I think object storage I hear nvme I think block storage your file storage when it comes down to it you know why is that the right architecture you know for today and what advantages does that give you so we we are actually the only company that went through the hassles and the hurdles of utilizing nvme and nvme of the fabrics for a parallel file system all other solutions went the easier route and created the block and the reason we've created a file system is that this is what computers understand this is what the operating system understand when you go to university you learn computer science they teach you how to write programs they need a file system now if you want to run your program over to servers or ten servers what you need is a shirt file system up until we came gold standard was using NFS for sharing files across servers but NFS was actually created in the 80s when Ethernet run at 10 megabit so currently most of our customers run already 100 gigabytes which is four orders of magnitude faster so they're seeing that they cannot run a network protocol that was designed four orders of magnitude last speed with the current demanding workloads so this explains why we had to go and and pick a totally different way of pushing data to the to the clients with regarding to object storages object storages are great because they allow customers to aggregate hard drives into inexpensive large capacity solutions the problem with object storages is that the programming model is different than the standard file system that computers can understand in too thin two ways a when you write something you don't know when it's going to get actually stored it's called eventual consistency and it's very difficult for mortal programmers to actually write a system that is sound that is always correct when you're writing eventual consistency storage the second thing is that objects cannot change you cannot modify them you need to create them you get them or you can delete them they can have versions but this is also much different than how the average programmer is used to write its programs so we are actually tying between the highest performance and vme of the fabrics at the first year and these object storages that are extremely efficient but very difficult to work with at the back and tier two a single solution that is highest performance and best economics right there on I want to give you the last word give us a little bit of a long view you talked about where we've gone how parallel you know architecture helps now that we're at you know 100 Gig look out five years in the future what's gonna happen you know blockchain takes over the world cloud dominates everything but from an infrastructure application in you know storage world you know where does wek I think that the things look like so one one very strong trend that we are saying is around encryption so it doesn't matter what industry I think storing things in clear-text for many organizations just stops making sense and people will demand more and more of day of their data to be encrypted and tighter control around everything that's one very strong trend that we're seeing another very strong trend that we're seeing is enterprises would like to leverage the public cloud but in an efficient way so if you were to run economics moving all your application to the public cloud may end up being more expensive than running everything on Prem and I think a lot of organizations realized that the the trick is going to be each organisation will have to find a balance to what kind of services are run on Prem and these are going to be the services that are run around the clock and what services have the more of a bursty nature and then organization will learn how to leverage the public cloud for its elasticity because if you're just running on the cloud you're not leveraging the elasticity you're doing it wrong and we're actually helping a lot of our customers do it with our hybrid cloud ability to have local workloads and the cloud workloads and getting these whole workflows to actually run is a fascinating process they're on thank you so much for joining us great to hear the update not only on Weka but really where the industry is going dynamic times here in the industry data at the center of all cubes looking to cover it at all the locations including here and our lovely Palo Alto Studio I'm Stu minimun thanks so much for watching the cube thank you very much [Music] you

(upbeat music) [Narrator] Live from Las Vegas. It's the CUBE, covering Oracle Modern Customer Experience 2017. Brought to you by Oracle. >> Welcome back everyone. We're live in Las Vegas here at the Mandalay Bay for Oracle's Modern Customer Experience conference, their second year. This is the CUBE, Silicon ANGLES flagship program. We go out to the events and extract the signal from the noise. I'm John Furrier. My co-host Peter Burris, head of research at Wikibon.com. Our next guest is Jack Berkowitz who's the Vice President of Products and Data Science at Oracle. Well, great to have you on the CUBE. Thanks for coming on. >> Thanks a lot. >> Appreciate it. Love talking to the product guys, getting down and dirty on the products. So, AI is hot this year. It's everywhere. Everyone's got an AI in their product. What is the AI component in your product? >> Well, what we're working on is building truly adaptive experiences for people. So, we have a whole bunch of different techniques and technologies all of it comes together essentially to create a system that amplifies peoples capabilities. That's really the key thing. Two real important components. First of all, it's all about data. Everybody talks about it. Well, what we've put together is, in terms of consumers, is the largest collection of consumer data in the Oracle data cloud. So we take advantage of all that consumer data. We also have a lot of work going on with collecting business data, both Oracle originated data as well as partner data. We're bringing that all that together and it sets the context for the AI. Now on top of that we have not just the latest trends in terms of machine learning or neural networks or things like that, but we're borrowing concepts from advertising, borrowing concepts from hedge funds so that we can make a real-time system. It's all about real-time. >> You mentioned neural networks. A lot of stuff conceptually in computer science has been around literally for decades. What is, from your definition - obviously cloud creates a lot of data out there now, but what is AI these days? Because everyone now is seeing AI as a mainstream term. Even the word metadata, since Snowden's thing, is now a mainstream term. Who would have thought metadata and AI would be talked about at kitchen tables? >> Yeah. >> What is AI from your perspective? >> Yeah, from my perspective it's really about augmenting folks. It's really about helping people do things. So maybe we'll automate some very manual tasks out, right, that will free up people to have more time to do some other things. I don't think it's about replacing people. People are creative. We want to get people back to being creative and people are great at problem solving so let's get them that information. Let's get them aid so they can get back to it. >> And give them options. >> Give them options, exactly. Exactly. You know, if you can free up somebody from having to manipulate spreadsheets and all this other stuff so they can just get the answer and get on with things, people are happier. >> So Oracle is using first-person data and third-person data to build these capabilities, right? >> Jack: Yeah, exactly. >> How is that going to play out? How is Oracle going to go to a customer and say we will appropriately utilize this third-person data in a way that does not undermine your first-person rights or value proposition? >> That's a great question. So, privacy and respect has been sort of the principle we've been driving at here. So there's the mechanics of it. People can opt in. People can opt out. There's all the mechanics and the regulatory side of it but it's really about how do you use these things so that it doesn't feel creepy. How do you do this in a subtle way so that somebody accepts the fact that that's the case? And it's really about the benefit to the person as to whether or not they're willing to make that trade-off. A great example is Waze. Waze I use all the time to get around San Francisco traffic. You guys probably use it as well. Well, guess what? If you really think about it, Waze knows what time I leave the house in the morning, what time I come home. Uber knows that once a month I leave at 2:00 on a Sunday and come back a week later. So, as long as you think about that, I'm getting a benefit from Waze I'm happy to have that partnership with them in terms of my data and they respect it and so therefore it works. >> And that comes back to some of the broader concepts of modern customer experience. It is that quid pro quo that I'll take a little data from you to improve the service that I'm able to provide as measured by the increasing value customer experience that's provided. >> Yeah, that's right. I used to live in London and in London there's these stores where you can go in and that sales guy has been there for like twenty years and you just develop a relationship. He knows you. He knows your kids, and so sure enough, stationary store or whatever it is and he gives you that personal experience. That's a relationship that I've built. That really all we're trying to do with all of this. We're trying to create a situation where people can have relationships again. >> And he's prompted with history of knowing you, just give you a pleasant surprise or experience that makes you go wow. And that's data driven now. So how do you guys do that? Cause this is something that, you know, Mark Heard brought up in his keynote that every little experience in the world is a data touchpoint. >> Jack: Yeah. >> And digital, whatever you're doing, so how do you guys put that in motion for data because that means data's got to be freely available. >> Data's got to be freely available. One of the big things that we brought to bear with the Suite X is that the data is connected and the experiences are connected so really we're talking about adding that connected intelligence on top of that data. So, it's not just the data. In fact we talked about it last night. It's not just the data even from the CX systems from service, but even the feed of what inventory's going on in real-time. So I can tell somebody if something's broken, hey, tell you what. This store has it. You can go exchange it, in real-time. Instead of having to wait for a courier or things like that. So it is that data being connected and the fact that our third-party data, you know this consumer data, is actually connected as well. So we bring that in on the fly with the appropriate context so it just works. >> So one of the new things here is the adaptive intelligence positioning products. What is that and take a minute to explain the features of how that came to be and how it's different from the competition. >> Okay, great. So the products are very purposeful built apps that plug in and amplify Oracle cloud apps and you can actually put in a third-party capability if you happen to have it. So that's the capability and it's got the decision science and machine learning and the data. >> Peter: So give me an example of a product. >> So a product is adaptive intelligence offers which we were showing here. It gives product recommendations, gives promotions, gives content recommendations on websites but also in your email. If you go into the store you get the same stuff and we can then go and activate advertising campaigns to bring in more people based on those successful pick ups of products or promotions. Its a great example. Very constrained use case addressed? >> Peter: Fed by a lot of different data. >> Fed by a lot of different data. The reason why they're adaptive is because they happen in real-time. So this isn't a batch mode thing. We don't calculate it the day before. We don't calculate it a week before or every three hours. It's actually click by click for you, and for you, reacting and re-scoring and re-balancing. And so we can get a wisdom of the crowds going on and an individual reaction, click by click, interaction by interaction. >> This is an important point I think that's nuanced in the industry. You mentioned batch mode which talks about how things are processed and managed to real-time and the big data space is a huge transition whether you're looking at hadoop or in memory or at all the architectures out there from batch data lakes to data in motion they're calling it. >> Yeah, exactly. >> So now you have this free flowing scalable data layers, if you will, every where, so being adaptive means what? Being ready? Being ... >> Being ready is the fundamental principle to getting to being adaptive. Being adaptive is just like this conversation. Being able to adjust, right? And not giving you the same exact answer seven times in a row because you asked me the same question. >> Or if it's in some talking point database you'd pull up from a FAQ. >> Peter: So it adapts to context. >> It's all about adapting to context. If the concepts change, then the system will adopt that context and adapt it's response. >> That's right. And we were showing last night, even in the interaction, as more context is given, the system can then pick that up and spin and then give you what you need? >> The Omni Channel is a term that's not new but certainly is amplified by this because now you have a world certainly with multiple clouds available to customers but also data is everywhere. Data is everywhere and channels are everywhere. >> Data is everywhere. And being adaptive also means customizing something at a point and time >> Exactly. and you might not know what it is up until seconds or near real-time or actually real-time. >> Real time, right? Real human time. 100 milliseconds. 150 milliseconds, anywhere in the world, is what we're striving for. >> And that means knowing that in some database somewhere you checked into a hotel, The Four Seasons, doing a little check in the hotel and now, oh, you left your house on Uber. Oh, you're the CEO of Oracle. You're in a rental car. I'm going to give you a different experience. >> Jack: Yeah. >> Knowing you're a travel warrior, executive. That's kind of what Mark Heard was trying to get to yesterday. >> Yeah, that's what he's getting to. So it's a bit of a journey, right? This is not a sprint. So there's been all this press and you think, oh my god, if I don't have ... It's a journey. It's a bit of a marathon, but these are the experiences that are happening. >> I want to pick up on 150 milliseconds is quite the design point. I mean human beings are not able to register information faster than about 80 milliseconds. >> Jack: Yeah, yeah. So you're talking about two brain cycles coming back to that. >> Jack: Yeah. >> I mean it's an analogy but it's not a bad one. >> Jack: No. >> 150 milliseconds anywhere in the world. That is a supreme design point. >> And it is what we're shooting for. Obviously there's things about networks and everything that have to be worked through but yeah, that responsiveness, but you're seeing that responsiveness at some of the big consumer sites. You see that type of responsiveness. That's what we want to get to. >> So at the risk of getting too technical here, how does multiple cloud integration or hopping change that equation? Is this one of the reasons it's going to drive customers to a tighter relationship with Oracle because it's going to be easier to provide the 150 millisecond response inside the Oracle fabric? >> Yeah, you nailed it. And I don't want to take too many shots at my competitors, but I'm going to. We don't have to move data. I don't have to move my data from me to AWS to some place else, right, Blue Mix, whatever it happens to be. And because we don't have to move data, we can get that speed. And because it's behind the fabric, as you put it, we can get that speed. We have the ability to scale the data centers. We have the data centers located where we need them. Now your recommendations, if you happen to be here today, they're here. They may transition to Sydney if you're in Australia to be able to give you that speed but that is the notion to have that seamless experience for you, even for travelers. >> That's a gauntlet. You just threw down a gauntlet. >> Jack: I did. Yeah. >> And that's what we're going to go compete against. Because what we're competing is on the experience for people. We're not competing on who's got the better algorithm. We're competing on that experience to people and everything about that. >> So that also brings up the point of third-party data because to have that speed certainly you have advantages in your architecture but humans don't care about Oracle and on which server. They care about what's going on on their phone, on their mobile. >> Jack: That's right. >> Okay, so the user, that requires some integration. So it won't be 100 percent Oracle. There's some third-party. What's the architecture, philosophy, guiding principles around integrating third-party data for you guys. Because it's certainly part of the system. It's part of the product, but I don't think it's ... >> So there's third=party data which could be from data partners or Oracle originated data through our Oracle data cloud or the 1500 licensed data partners there and there's also third-party systems. So for example if somebody had Magento Commerce and they wanted to include that into our capability. On the third party systems, we actually have built this around an API architecture or infrastructure using REST and it's basically a challenge I gave my PMs. I said look, I want you to test against the Oracle cloud system. I want you to test against the Oracle on-prem system and I want you to find the leading third-party system. I don't care if it's sales force or anybody else and I want you to test against that and so as long as people can map to the REST APIs that we have, they can have inter-operation with their systems. >> I mean the architectural philosophy is to decouple and make highly cohesive elements and you guys are a big part of that with Oracle as a component. >> Jack: That's right. >> But I'm still going to need to get stuff from other places and so API is a strategy and microservices are all going to be involved with that. >> Yeah, and actually we deployed a full microservice architecture so behind the scenes on that offers one, 19 microservices interplaying and operating. >> But the reality is this is going to be one of the biggest challenges that answers faces is that how we bridge, or how we gateway, cloud services from a lot of different providers is a non-trivial challenge. >> Jack: That's right. >> I remember back early on in my career when we had all these mini computer companies and each one had their own proprietary network on the shop floor for doing cell controllers or finance or whatever it might be and when customers wanted to bring those things together the mini computer companies said, yeah, put a bridge in place. >> Yeah, exactly. >> And along came TCPIP and Cisco and said forget that. Throw them all out. It wasn't the microprocessor that couldn't stick to those mini computer companies. It was TCPIP. The challenge that we face here is how are we going to do something similar because we're not going to bridge these things. The latency and the speed, and you hit the key point, where is the data, is going to have an enormous impact on this. >> That's right. And again, the investments we have been making with the CX Cloud Suite will allow us to do that. Allow us to take advantage with a whole bunch of data right away and the integration with the ODCs, so we couldn't probably have done this two or three years ago because we weren't ready. We're ready now. And now we can start to build it. We can start to take it now up to the next level. >> And to his point about the road map and TCPIP was interesting. We're all historians here. We're old enough to remember those days, but TCPIP standardized the OSI model which was a fantasy of seven layers of open standards if you remember. >> Jack: Seven layers, yep, whew. >> Peter: See we still talk about it. >> What layer are you on? >> But at the time, the proprietary was IBM and DEC owned the network stacks so that essentially leveled off there so the high-water mark was operating at TCPIP. Is there an equivalent analog to that in this world because IF you can almost take what he said and say take it to the cloud and say look at some point in this whatever stack you want to call it, if it is a stack, there has to be a moment of coalescing around something for everybody. And then a point of differentiation. >> So yeah, and again I'm just going to go back - and that's a great question by the way and it's - I'm like thinking this through as I say it, but I'm going to go right back to what I said. It's about people. So if I coalesce the information around that person, whether that person is a consumer or that person's a sales guy or that person's working on inventory management or better yet disaster relief, which is all those things put together. It's about them and about what they need. So if I get that central object around people, around companies then I have something that I can coalesce and share a semantic on. So the semantic is another old seven layer word. I didn't want to say it today but I can have ... >> Disruptive enabler. >> So then what you're saying is that we need a stack, and I use that word prohibitively, but we need a way of characterizing layer seven application so that we have ... >> Or horizontal >> Either way. But the idea is that we need to get more into how the data gets handled and not just how the message gets handled. >> Jack: That's right. >> OSI's always focused on how the message got handled. Now we're focused on how the data gets handled given that messaging substraight and that is going to be the big challenge for the industry. >> Jack: Yeah. >> Well, certainly Larry Ellis is going to love this conversation, OSI, TCPIP, going old school right here. >> Jack: Like you said, we're all old and yeah, that's what we grew up in. >> Yeah, but this is definitely ... >> Hey, today's computers and today's notions are built on the shoulders of giants. >> Well the enabling that's happening is so disruptive it's going to be a 20 or 30 year innovation window and we're just at the beginning. So the final question I have for you Jack is summarize for the folks watching. What is the exciting things about the AI and the adaptive intelligence announcements and products that you guys are showing here and how does that go forward into the future without revealing any kind of secrets on Oracle like you're a public company. What's the bottom line? What's the exciting thing they should know about? >> I think the exciting thing is that they're going to be able to take advantage of these technologies, these techniques, all this stuff, without having to hire a thousand data scientists in a seven month program or seven year program to take advantage of it. They're going to be able to get up and running very, very quickly. They can experiment with it to be able to make sure that it's doing the right thing. From a CX company, they can get back to doing what they do which is building great product, building great promotions, building a great customer service experience. They don't have to worry about gee, what's our seven year plan for building AI capabilities? That's pretty exciting. It lets them get back to doing what they do which is to compete on their products. >> And I think the messaging of this show is really good because you talk about empowerment, the hero. It's kind of gimmicky but the truth is what cloud has shown in the world is you can offload some of those mundane stuff and really focus on the task at hand, being creative or building solutions, or whatever you're doing. >> Yeah. Mark was talking about it. You have this much money to spend, what's my decision to spend it on. Spend it on competing with your products. >> All right, Jack Berkowitz live here inside the CUBE here at Oracle's Modern Customer Experience, talking about the products, the data science, AI's hot. Great products. Thanks for joining us. Appreciate it. Welcome to the CUBE and good job sharing some great insight and the data here. I'm John Furrier with Peter Burris. We'll be back with more after this short break. (upbeat music)

>> Voiceover: From San Jose, California, it's The Cube, covering big data Silicon Valley 2017. >> Welcome back, everyone. Live in Silicon Valley for BigData SV, BigData Silicon Valley. This is Silicon Angles, The Cube's event in Silicon Valley, with our companion event, BigData NYC, in conjunction with O'Reilly, Strata, Hadoop, Hadoop World, our eighth year. I'm John Furrier, my co-host Jeff Frick, breaking down all the action, and our superguest, Abhi Mehta, the CEO of Tresata. He's been on every year since 2010, and the CEO of very successful Tresata, building out the vertical approach in financial net health. Welcome back, good to see you. Thank you, John, always good to see you. >> The annual pilgrimage to have you on The Cube. >> Abhi: This is literally a pilgrimage. I was exchanging messages with your co-host here, and he was pinging me, saying, "You got to come here, you got to get to this thing." I made it. The pilgrimage is successful. >> Yeah, a lot's happened, right? Data's the new oil. We've heard it over again. You had the seminal first interview in 2010, calling the oil refineries the data refineries. Turns out that was true. We always love to talk about that prediction every time you're on, but it's so much going on now. You can't believe the shift. Certainly, Hadoop has got a nice little niche position as Batch, but real time processing, you've seen the convergence of Batch, and streaming, and all that good stuff in real time, with the advances of clouds, certainly, more compute, Intel processors are getting more powerful, 5G over the top, you have connective cars, smart cities, on and on, IoT, Internet of things, all powering this new deep learning and AI trend. Man, it is game changes. I see this as a step-up function. What's your thoughts? This is going to create more data, more action. >> I agree with you. I always remind myself, John, especially when I talk to you guys, and we were chatting about this right before we went on air, which is, as smart as we as humans are, trends repeat themself. I'll be talking about AI. We all went to school, and did things in AI, you know? The whole neural networks thing has not been new. It's almost like fashion. Bell bottoms come in fashion every 20 years. I will never be seen in them again. Hopefully, neither will you. AI seems to be like that. I think the thing that hasn't changed, and yes, absolutely agree with you, that as escrows shift, as you've said, almost at this point a decade ago, there's a fundamentally new technology escrow shift under way, and escrow shifts take time. We will look back at this 10 years saying it was literally the first, second inning of this new escrow shift. I think we are entering the second innings where the conversation around Batch, real time storage, databases, the stacks, is becoming less important, and AI and deep learnings are examples of it, conversations on, how can you leverage cheaper, better, faster technology to solve and answer unanswered problems is becoming interesting. I think the basics haven't changed though. What we have spoken with you for almost eight years remain the same. The three basics around every technology trend remain the same. I think you guys will agree with me. Let me just play it by you and you can either contest it or agree with me. Data is the new competitive effort. It is unequivocally clear that the new asset, the most valuable enterprise asset has become data, and we've seen it in data companies, Facebook, Google, Uber, Airbnb, they're all fundamentally data companies. Data is the new competitive effort. The more you have of it, the better off you are. I always love people who say, "Big Data, this is a bad term." It isn't, because big data, fundamentally, in those two words, defines the very pieces of what we built Tresata on, which is, the more data you have, and if you can process and extract intelligence from it, borrowing your term, extract signal from the noise, you can make a lot of money on it. I think that fundamental basic hasn't changed. >> Big Data, to me, was always about big storage kind of a view. We coined the term Fast Data on The Cube, so that now speaks to the real time. It's interesting. I just see that the four main new areas that are being talked about outside of the Big Data world are autonomous vehicles, smart cities, smart home, and media and entertainment, and each one of those, I would say that the data is the new weaponization. There's an article that was great this month called "Weaponizing AI," and it had to do with Breitbart, and the election, and that's media and entertainment. You've got Netflix, all these new companies. Data is content, content is data. It's a digital asset. This AI component fits into autonomous vehicles, it fits into media and entertainment, fits into smart cities, and smart home. >> You also raise a very interesting point. I think that we can take comfort in the fact that we have seen this happen. This is not an idea anymore, or it's not just a wild idea anymore, which is, we have seen massive disruption happen in consumer industries. Google has created a brand new industry in how to market stuff, could be any stuff. Facebook created a brand new way of not just being in touch with your friends globally, 'cause people have thousands of friends, not true, but also, how do you monetize deep preferences, right? A twist on deep learning, but deep, deep preferences. If I know what Jeff likes, I can market to him better. I think we're about to see, the industries you just mention, is, where will success come from in enterprise software? I always ask myself that question when I come to any of these conferences, Strata, others, there's now an AI conference. What will the disruption that we have seen happen in consumer industries, we'll just mention automobiles, media entertainment, et cetera, what is going to happen to enterprise software? I think the time is ripe in the next five years to see the emergence of massive scale creation. I actually don't think it'll get disrupted. I think we will see, just like with Facebook, Google, Uber, the creation of brand new industries in enterprise software. I think that's going to be interesting. >> Mark Cuban said at South by Southwest this week, where The Cube was with the AI lounge with Intel, he was on stage saying, "The first tech trillionaire "will come out of deep learning," and deep learning is kind of the underpins for AI, if you look at all the geek stuff. To your point that a new shift of opportunity, whether it comes in from the enterprise side, or consumer, or algorithmic side, is that there's never been a trillionaire. >> Abhi: No, there hasn't. >> I want to push back a little bit, because I don't think it always was that way with data. We used to have sampling. It was all about sophistication on sampling, and data was expensive to store, expensive to collect, and expensive to manage. I think that's where the significant change is. The economics of collecting, and storing, and analyzing are such that sampling is no longer the preferred method. To your point, it's the bigness. >> Absolutely, you know exactly where I stand on that. >> Jeff: Now it's an asset. >> You know exactly where I stand on that. I said on The Cube, at this point, almost a decade ago, sampling is dead, and it's for that particular reason. I think the reality is that it has become a very tricky area to be in. Buzzwords aside, whether it's deep learning, AI, streaming, Batch, doesn't matter, Flash, all buzzwords aside, the very interesting thing is, are we seeing, as a community, the emergence of new enterprise software business models? I think ours is an example. We are now six years old. We announced Tresata on The Cube. We have celebrated our significant milestones on The Cube. We'll announce today that we are now a valuable member of society in terms of you pay tax as a company, another big milestone for a company. We have never raised venture money. We had a broad view when we started that every single thing we have learned as a industry enterprise software, the stack, databases, storage, BI, algorithms are free. Dave was talking about this earlier this week. Algorithms, analytical tools, will all become free. What is this new class of enterprise software that creates value that can then be sold as value? Buyers, corporations are becoming smart to realize and say, "Maybe I can't hire people "as smart as some of the web industries "on this side of the coast, "but I can still hire good talent, the tool set is free. "Should I build versus buy?" It fundamentally changes the conversation. Databases is a $2 trillion industry. Where does that value shift to if databases are free? I think that's what is going to be interesting to see, is, what model creates the new enterprise software industry? What is that going to be? I do agree with Mark Cuban's statement, that the answer is going to lie in, if the building blocks are free and commoditized, you guys know exactly where I stand on that one, if the building blocks are commoditized, how do you add value in the building block? It comes from the point you made, industry knowledge, data, owning data and domain knowledge. If you can combine deep domain expertise to be an advanced application that solve business problems, people don't want to know if the data is stored in a free HDFS system, or in some other system, or quantum computing, people don't care. >> I got to get your take on the data layer because this is where it's come. We had a lot of guests on saying, with the cloud, you can rent things, algorithms are free, so essentially, commoditization has happened, which is a good thing, more compute, everything else is all great, all the goodness around that. You still own your data. The data layer seems to be the LAN grab, metadata. How do you cross-connect the data layer to be consistent fabric? >> Here's how we think of it, and this is something we haven't shared publicly yet, but I believe you see us talk a lot more about this. We believe there are three new layers in the technology fabric. There is what we call the hardware operating system. The battle has been won by a company that we all like a lot, Red Hat, I think mostly won. Then there is what we call the data operating system, what you call the data layer. I think there's a new layer emerging where people like us sit. We call it the analytics operating system. The data layer will commoditize as much as the hardware operating system, what I call the layer, commoditized. The data operating system fight is moot. Metadata should not be charged for. Massive data management, draining the swamp, whatever you want to call it, every single thing in the data operating system is a commodity where you need volumes, you all are businessmen, you need volumes, in the P times V game, you need volumes to sustain a profit business model. The interesting action, in my opinion, is going to come in the analytics operating system. You are now automating hardcore, what I call, finding intelligence questions, whether it's using deep learning, AI, or whatever other buzzword the industry dreams up in the next five years, whatever the buzzwords may be, immaterial, the layer that automates the extraction of intelligence from massive amounts of data sitting in the data layer, no matter who owns it, our opinion is, Tresata, as an enterprise software player, is not interested to be a data owner. That game, I can't play anymore, right? You guys are a content company, though. You guys are data owners, and you have incredible value in the data you're building. For us, it is, I want to be the tool builder for this next gold rush. If you need the tools to extract intelligence from your data, who's going to give you those tools? I think all that value sits in what we call the analytics operating system. The world hasn't seen enough players in it yet. >> This is an interesting mind bender, if you think about it. When you said, "analytics operating system," that rings a few bells and gets the hair standing on the back of my head up because we're in a systems world now. We kind of talk about this in The Cube where operating systems concepts are very much in play. If you look at this ecosystem and who's winning, who's losing, who's struggling, who's falling away, is, the winners are nailing the integration game, and they're nailing the functional game, I think, a core functional component of an operating environment, AKA, the cloud, AKA data. >> Agreed. >> Having those functional systems, as an operating system game. What is your view of what an analytics operating system? What are some of those components? I mean, most operating systems have a linker, loader, filer, all these things going on. What's your thoughts on this analytical operating system? What is it made of? >> It's made of three core components that we have now invested six years in. The first one is exactly what you said. We don't use the word integration. We now call it the same word, we have been saying it for six years, we call it the factory, but it's very similar, which is, the ability to go to a company or enterprises with unique data assets, and enrich, I will borrow your term, integrate, enrich. We call it the data factory, the automation of 90% of the workload to make data sitting in a swamp usable data, part one. We call that creation of a data asset, a nice twist or separation from the word data warehousing we all grew up on. That's number one, the ability to make raw data usable. It's actually quite hard. If you haven't built a company squarely on data, you have to be able to buy it because building is very hard, number one. Number two is what I call the infusion of domain-centric knowledge. Can industries and industry players take expert systems and convert them into machine systems? The moment we convert expert systems into machine systems, we can do automation at very large scale. As you can imagine, the ability to add value is exponentially higher for each of those tiers, from data asset to now infusion of domain knowledge, to take an expert into a machine system, but the value trade is incredibly large as well. If you actually have the system built out, you can afford to sell it for all the value. That's number two, the ability to take expert system, go to machine systems. Number three is the most interesting, and we are very early in it. I use the term on The Cube, I'm going to be more forward-thinking over here, which is automation. Today, the best we can do with leveraging incredibly smart machines, algorithms, at scale on massive amounts of data is augmenting humans. I do fundamentally believe, just like self-driving cars, that the era where software will automate a tremendous amount of business processes in all industries is upon us. How long it takes, I think we will see it in our lifetimes too. When you and I have both a little bit more gray hair, we're saying, "Remember, we said about that? "I think automation's going to come." I do believe automation will happen. Currently, it's all about augmentation, but I do believe that business-- >> John: Cubebots are coming. We're going to have some Cubebots. >> We will have Cubebots. >> John: Automated Cube broadcasting. >> John, we'll give them your magnificent hair, and they know they'll do it. I do believe automation of complex human processes, the era of enlightenment, is upon us, where we will be able to take incredibly manual activities, like hailing a car today, to complex activities, looking at transaction information, trading information, in split second time, even quicker than real time, and making the right trading decision to make sure that Jeff's kids go to college in a robo-advisor-like mode. It's all early, but the augmentation will transform to automation, and that will take some time to do them at three tiers in the AOS. >> Then, if we are successful at converting the expert to machine system, will the value of that expert system quickly be driven to zero due to the same factors that automation has added to many other things that have been sucked in? >> You guys always blow my mind. You always push my thinking when I come here. >> I just love the concept, but then, will the same economics that have driven asumtotically approaching zero costs, then now go to these expert systems? >> You know the answer. The answer is absolutely, yes. The question then becomes, how long of an era is it? What we have learned in technology is escrow shifts take time. This era of enlightenment, what I'm calling the era of enlightenment, that enterprise software is about to enable, and leaving aside all other buzzwords, whether it's deep learning, AI, machines, chatbot, doesn't matter, the era of enlightenment is absolute. I think there'll be two things. First of all, it'll take time to mature. Yes, whether it's 50 years, 40 years, or 30 years, does it, at some point, become it's own commodity? Absolutely. The marginal value we can deliver with a machine, at some point, does go to zero, because it commoditizes it, at scale, it commoditizes it, absolutely, but does that mean the next 30 years will not be a renaissance in enterprise software? Absolutely not. I think we will see ... Let's take the enterprise IT market, what, two to three trillion dollars a year? All of it is up for grabs, and we will see in the next 20, 30, 40, 50 years that, as it is up for grabs, tremendous amount of value will be re-traded and recreated in completely new industry models. I think that's the exciting part. I won't live for 50 years, so it's okay. >> I know we got a minute or so left. I want to get your thoughts on something that we're seeing here, The Cube this year pointed out. We've kind of teased around it, but again, Batch and real time process streaming, all that's coming together. The center of that's IoT data and AI, is causing product gaps. There are some gaps that are developing, either a pure play Batch player, or your real time, some people have been one or the other, some are integrating in. When you try to blend it together, there's product gaps, organizational gaps, and then process gaps. Can you talk about how companies are solving that? Because one supplier might have a great Batch solution, data lake, some might have streaming and whatnot. Now there seems to be more of an integrated approach, bringing those worlds together, but it's causing some gaps. How do companies figure that out? >> I believe there's only one way, in the near term, and then potentially even moreso in the long term, to bridge that divide that you talk about. There absolutely is a divide. It's been very interesting for us especially. I'll use our example to answer your question. We have a very advanced health analytics application to go after diabetes. The challenge is, in order to run it, not only do you need lots and lots of data, IoT, streamed, real time from sensors you wear on your body, you need that. Not only do you need the ability and processing power to crunch all that data, not only do you need the specific algorithms to find insights that were not findable before, the unanswered questions, but the last point, you need to be able to then deliver it across all channels so you can monetize it. That is a end-to-end, what I call, business process around data monetization. Our customers don't care about it. They come to Tresata and they say, "I love your predictive diabetes outcomes application. "I have rented the system from the cloud," Amazon, Azure, I think at this point, only two players. We don't see Google much in it. I'm sure they're doing something in it. We have rented you the wheels, and the steering, and the body, so if you want to put it together to run your car on the track, you could. Everything else is containerized by us. I call them advanced analytics applications. They're fully managed. They run on any environment that is given to them because they are resource ready, whatever environment they play in, and they are completely backwards and forwards integrated. I think you will see the emergence of a class of enterprise software, what we call advanced analytics applications, that actually take away the pain from enterprises to worry about those gaps, 'cause in our case, in that example I just gave you, yes, there are gaps, but we have done it enough off a automation cycle on the business process itself, that we can title with the gaps. >> Abhi, we got to go. Glad we could squeeze you in. >> Abhi: Thank you. >> Quick 30 seconds, the show this year, what are you seeing? What's the buzz coming out of? What's the meat, what's the buzz from the show here? What's the story? >> I continue to believe that we are in an era that will redefine what we have seen humans do. The people at the show continue to surprise me because the questions they've been asking over the last eight years have slightly changed. I'm done with buzzwords. I don't pay attention to buzzwords anymore. I see a maturation. I think I said it to you before. I see more bald heads and big pates. When I see that in shows like these, it gives me hope that, when people who grew up in a different escrow have borrowed a new escrow, the pace would strengthen. As always, phenomenal show, great community. The community's changing and looking different in a good way. >> We feel your pain in the buzzword. As we proceed down this epic digital transformation, over the top, 5G, autonomous vehicles, Big Data analytics, moving the needle, all this headroom, future proofing, AI, machine learning, thanks for sharing. >> Abhi: Thank you so much, as always. >> More buzzwords, more signal from the noise here on The Cube. I'm John Furrier, Jeff Frick, and George Gilbert will be back right after this short break. (electronic music)

>> Announcer: Live from San Jose, California. It's The Cube, covering Big Data Silicon Valley 2017. (upbeat electronic music) >> California, Silicon Valley, at the heart of the big data world, this is The Cube's coverage of Big Data Silicon Valley in conjunction with Strata Hadoop, well of course we've been here for multiple years, covering Hadoop World for now our eighth year, now that's Strata Hadoop but we do our own event, Big Data SV in New York City and Silicon Valley, SV NYC. I'm John Furrier, my cohost George Gilbert, analyst at Wikibon. Our next guest is Tendü Yogurtçu with Syncsort, general manager of the big data, did I get that right? >> Yes, you got it right. It's always a pleasure to be at The Cube. >> (laughs) I love your name. That's so hard for me to get, but I think I was close enough there. Welcome back. >> Thank you. >> Great to see you. You know, one of the things I'm excited about with Syncsort is we've been following you guys, we talk to you guys every year, and it just seems to be that every year, more and more announcements happen. You guys are unstoppable. You're like what Amazon does, just more and more announcements, but the theme seems to be integration. Give us the latest update. You had an update, you bought Trillium, you got a hit deal with Hortonworks, you got integrated with Spark, you got big news here, what's the news here this year? >> Sure. Thank you for having me. Yes, it's very exciting times at Syncsort and I've probably say that every time I appear because every time it's more exciting than the previous, which is great. We bought Trillium Software and Trillium Software has been leading data quality over a decade in many of the enterprises. It's very complimentary to our data integration, data management portfolio because we are helping our customers to access all of their enterprise data, not just the new emerging sources in the connected devices and mobile and streaming. Also leveraging reference data, my main frame legacy systems and the legacy enterprise data warehouse. While we are doing that, accessing data, data lake is now actually, in some cases, turning into data swamp. That was a term Dave Vellante used a couple of years back in one of the crowd chats and it's becoming real. So, data-- >> Real being the data swamps, data lakes are turning into swamps because they're not being leveraged properly? >> Exactly, exactly. Because it's about also having access to write data, and data quality is very complimentary because dream has had trusted right data, so to enterprise customers in the traditional environments, so now we are looking forward to bring that enterprise trust of the data quality into data lake. In terms of the data integration, data integration has been always very critical to any organization. It's even more critical now that the data is shifting gravity and the amount of data organizations have. What we have been delivering in very large enterprise production environments for the last three years is we are hearing our competitors making announcements in those areas very recently, which is a validation because we are already running in very large production environments. We are offering value by saying "Create your applications for integrating your data," whether it's in the cloud or originating on the cloud or origination on the main frames, whether it's on the legacy data warehouse, you can deploy the same exact application without any recompilations, without any changes on your standalone Windows laptop or in Hadoop MapReduce, or Spark in the cloud. So this design once and deploy anywhere is becoming more and more critical with data, it's originating in many different places and cloud is definitely one of them. Our data warehouse optimization solution with Hortonworks and AtScale, it's a special package to accelerate this adoption. It's basically helping organizations to offload the workload from the existing Teradata or Netezza data warehouse and deploying in Hadoop. We provide a single button to automatically map the metadata, create the metadata in Hive or on Hadoop and also make the data accessible in the new environment and AtScale provides fast BI on top of that. >> Wow, that's amazing. I want to ask you a question, because this is a theme, so I just did a tweetup just now while you were talking saying "the theme this year is cleaning up the data lakes, or data swamps, AKA data lakes. The other theme is integration. Can you just lay out your premise on how enterprises should be looking at integration now because it's the multi-vendor world, it's the multi-cloud world, multi-data type and source with metadata world. How do you advise customers that have the plethora of action coming at them. IOT, you've got cloud, you've got big data, I've got Hadoop here, I got Spark over here, what's the integration formula? >> First thing is identify your business use cases. What's your business's challenge, what's your business goals, and the challenge, because that should be the real driver. We assist in some organizations, they start with the intention "we would like to create a data lake" without having that very clear understanding, what is it that I'm trying to solve with this data lake? Data as a service is really becoming a theme across multiple organizations, whether it's on the enterprise side or on some of the online retail organizations, for example. As part of that data as a service, organizations really need to adopt tools that are going to enable them to take advantage of the technology stack. The technology stack is evolving very rapidly. The skill sets are rare, and skill sets are rare because you need to be kind of making adjustments. Am I hiring Ph.D students who can program Scala in the most optimized way, or should I hire Java developers, or should I hire Python developers, the names of the tools in the stack, Spark one versus Spark two APIs, change. It's really evolving very rapidly. >> It's hard to find Scala developers, I mean, you go outside Silicon Valley. >> Exactly. So you need to be, as an organization, ours advises that you really need to find tools that are going to fit those business use cases and provide a single software environment, that data integration might be happening on premise now, with some of the legacy enterprise data warehouse, and it might happen in a hybrid, on premise and cloud environment in the near future and perhaps completely in the cloud. >> So standard tools, tools that have some standard software behind it, so you don't get stuck in the personnel hiring problem. Some unique domain expertise that's hard to hire. >> Yes, skill set is one problem, the second problem is the fact that the applications needs to be recompiled because the stack is evolving and the APIs are not compatible with the previous version, so that's the maintenance cost to keep up with things, to be able to catch up with the new versions of the stack, that's another area that the tools really help, because you want to be able to develop the application and deploy it anywhere in any complete platform. >> So Tendü, if I hear you properly, what you're saying is integration sounds great on paper, it's important, but there's some hidden costs there, and that is the skill set and then there's the stack recompiling, I'm making sure. Okay, that's awesome. >> The tools help with that. >> Take a step back and zoom out and talk about Syncsort's positioning, because you guys have been changing with the stacks as well, I mean you guys have been doing very well with the announcements, you've been just coming on the market all the time. What is the current value proposition for Syncsort today? >> The current value proposition is really we have organizations to create the next generation modern data architecture by accessing and liberating all enterprise data and delivering that data at the right time and the right quality data. It's liberate, integrate, with integrity. That's our value proposition. How do we do that? We provide that single software environment. You can have batch legacy data and streaming data sources integrated in the same exact environment and it enables you to adapt to Spark 2 or Flink or whichever complete framework is going to help them. That has been our value proposition and it is proven in many production deployments. >> What's interesting to is the way you guys have approached the market. You've locked down the legacy, so you have, we talk about the main frame and well beyond that now, you guys have and understand the legacy, so you kind of lock that down, protect it, make it secure, it's security-wise, but you do that too, but making sure it works because it's still data there, because legacy systems are really critical in the hybrid. >> Main frame expertise and heritage that we have is a critical part of our offering. We will continue to focus on innovation on the main frame side as well as on the distributed. One of the announcements that we made since our last conversation was we have partnership with Compuware and we now bring in more data types about application failures, it's a Band-Aid data to Splunk for operational intelligence. We will continue to also support more delivery types, we have batch delivery, we have streaming delivery, and now replication into Hadoop has been a challenge so our focus is now replication from the B2 on mainframe and ISA on mainframe to Hadoop environments. That's what we will continue to focus on, mainframe, because we have heritage there and it's also part of big enterprise data lake. You cannot make sense of the customer data that you are getting from mobile if you don't reference the critical data sets that are on the mainframe. With the Trillium acquisition, it's very exciting because now we are at a kind of pivotal point in the market, we can bring that data validation, cleansing, and matching superior capabilities we have to the big data environments. One of the things-- >> So when you get in low latency, you guys do the whole low latency thing too? You bring it in fast? >> Yes, we bring it, that's our current value proposition and as we are accessing this data and integrating this part of the data lake, now we have capabilities with Trillium that we can profile that data, get statistics and start using machine learning to automate the data steward's job. Data stewards are still spending 75% of their time trying to clean the data. So if we can-- >> Lot of manual work labor there, and modeling too, by the way, the modeling and just the cleaning, cleaning and modeling kind of go hand in hand. >> Exactly. If we can automate any of these steps to drive the business rules automatically and provide right data on the data lake, that would be very valuable. This is what we are hearing from our customers as well. >> We've heard probably five years about the data lake as the center of gravity of big data, but we're hearing at least a bifurcation, maybe more, where now we want to take that data and apply it, operationalize it in making decisions with machine learning, predictive analytics, but at the same time we're trying to square this strange circle of data, the data lake where you didn't say up front what you wanted it to look like but now we want ever richer metadata to make sense out of it, a layer that you're putting on it, the data prep layer, and others are trying to put different metadata on top of it. What do you see that metadata layer looking like over the next three to five years? >> The governance is a very key topic and social organizations who are ahead of the game in the big data and who already established that data lake, data governance and even analytics governance becomes important. What we are delivering here with Trillium, we will have generally available by end of Q1. We are basically bringing business rules to the data. Instead of bringing data to business rules, we are taking the business rules and deploying them where the data exists. That will be key because of the data gravity you mentioned because the data might be in the Hadoop environment, there might be in a, like I said, enterprise data warehouse, and it might be originating in the cloud, and you don't want to move the data to the business rules. You want to move the business rules to where the data exists. Cloud is an area that we see more and more of our customers are moving forward. Two main use cases around our integration is one, because the data is originating in cloud, and the second one is archiving data to cloud, and we announced actually, tighter integration with cloud with our director earlier this week for this event, and that we have been in cloud deployments and we have actually an offering, an elastic MapReduce already and on AC too for couple of years now, and also on the Google cloud storage, but this announcement is primarily making deployments even easier by leveraging cloud director's elasticity for increasing and reducing the deployment. Now our customers will also take advantage of integration jobs from that elasticity. >> Tendü, it's great to have you on The Cube because you have an engineering mind but you're also now general manager of the business, and your business is changing. You're in the center of the action, so I want to get your expertise and insight into enterprise readiness concept and we saw last week at Google Cloud 2017, you know, Google going down the path of being enterprise ready, or taking steps, I don't think they're fully ready, but they're certainly serious about the cloud on the enterprise, and that's clear from Diane Green, who knows the enterprise. It sparked the conversation last week, around what does enterprise readiness mean for cloud players, because there's so many details in between the lines, if you will, of what products are, that integration, certification, SLAs. What's your take on the notion of cloud readiness? Vizaviz, Google and others that are bringing cloud compute, a lot of resources, with an IOT market that's now booming, big data evolving very, very fast, lot of realtime, lot of analytics, lot of innovation happening. What's the enterprise picture look like from a readiness standpoint? How do these guys get ready? >> From a big picture, for enterprise there are couple of things that these cannot be afterthought. Security, metadata lineage is part of data governance, and being able to have flexibility in the architecture, that they will not be kind of recreating the jobs that they might have all the way to deployed and on premise environments, right? To be able to have the same application running from on premise to cloud will be critical because it gives flexibility for adaptation in the enterprise. Enterprise may have some MapReduce jobs running on premise with the Spark jobs on cloud because they are really doing some predictive analytics, graph analytics on those, they want to be able to kind of have that flexible architecture where we hear this concept of a hybrid environment. You don't want to be deploying a completely different product in the cloud and redo your jobs. That flexibility of architecture, flexibility-- >> So having different code bases in the cloud versus on prem requires two jobs to do the same thing. >> Two jobs for maintaining, two jobs for standardizing, and two different skill sets of people potentially. So security, governance, and being able to access easily and have applications move in between environments will be very critical. >> So seamless integration between clouds and on prem first, and then potentially multi-cloud. That's table stakes in your mind. >> They are absolutely table stakes. A lot of vendors are trying to focus on that, definitely Hadoop vendors are also focusing on that. Also, one of the things, like when people talk about governance, the requirements are changing. We have been talking about single view and customer 360 for a while now, right? Do we have it right yet? The enrichment is becoming a key. With Trillium we made the recent announcement, the precise enriching, it's not just the address that you want to deliver and make sure that address should be correct, it's also the email address, and the phone number, is it mobile number, is it landline? It's enriched data sets that we have to be really dealing, and there's a lot of opportunity, and we are really excited because data quality, discovery and integration are coming together and we have a good-- >> Well Tendü, thank you for joining us, and congratulations as Syncsort broadens their scope to being a modern data platform solution provider for companies, congratulations. >> Thank you. >> Thanks for coming. >> Thank you for having me. >> This is The Cube here live in Silicon Valley and San Jose, I'm John Furrier, George Gilbert, you're watching our coverage of Big Data Silicon Valley in conjunction with Strata Hadoop. This is Silicon Angles, The Cube, we'll be right back with more live coverage. We've got two days of wall to wall coverage with experts and pros talking about big data, the transformations here inside The Cube. We'll be right back. (upbeat electronic music)

>> Narrator: Live from Austin, Texas, it's the Cube, covering South by Southwest 2017. Brought to you by Intel. (electronic music) Now, here's John Furrier. >> Hello, and welcome to a special broadcast of Silicon Angles, the Cube. This is our flagship program. We go out to the events and extract the signal from the noise. We're here for a special broadcast, kicking off South by Southwest. This show is the center of the entertainment/media universe and we are here in the Intel AI Lounge, the hashtag Intel AI, and of course, hashtag The Cube, hashtag South by Southwest, and, again, South by Southwest, I call it the Burning Man for the tech industry, the music industry. It is where all the creative, the talented, and the innovators, the bomb throwers, the disrupters, and also the innovators building the next generation technologies. We're going to have wall-to-wall coverage, all day interviews here, and our theme this week at South by Southwest, is really powered by Intel AI, and that is, AI for social good. We're going to be unpacking all the cutting edge technology that's taking us into the next generation. What's this world look like with AI? What's this world look like with autonomous vehicles? These are significant shifts that we've never seen in the computer industry before. We're going to be breaking them down. And here to kickoff day one of our Cube coverage is, my friend, Brian Fanzo. iSocialFanz, is the founder. Great guy, young guy-- younger than me but, you know, still in the front lines. Brian, welcome to our kickoff. >> Thanks for having me. I like to be here. First time on the show was 2013, VM world. So, we were inside VM world, 2013, and now outside the Intel Lounge at South by. Pretty exciting. >> So, it's high noon here. We got our sunglasses on. High noon in Texas. I'm wearing my Ray Bans, but you have your Snapchat spectacles on. What's going on? Do you like them? Give us the update. >> Yeah, I'm actually a new user of them. I'm one who likes to jump on new technology, embrace the FOMO. I kind of waited a little bit on the specs. I also wanted to have something cool to release them with. After I got them, I decided to keep them in wraps until South by Southwest, but it's kind of fun. It's interactive. They are definitely-- now that you can buy them online, I think they're going to be seen a little bit more frequent, but here at South by, just walking down the streets, people are still stopping and saying, "Hey, take a picture of me," and, "How does it work?" I've been impressed. The quality's been pretty good, and it's really easy to use. I think battery life has a long way to go but we'll see. I think battery life in everything mobile has a long way to go. >> Well, that leads to our whole theme here. We're going to have Robert Scoble on, good friend, he's been doing a lot in Virtual Reality and AR, benpar, and a lot of scientists from Intel. Really, folks, talking about this kind of movement. There's a shift going on, user behavior shifting. You're seeing actually entrepreneurship, young companies coming out and changing the world, and not changing the world to go public and some of those vanity things around money, but really around social change, and that's our theme. You have been really prolific over the past couple years, this year in particular, going out, pounding the pavement. You've been at a zillion events. We see each other all the time. Of course, we do over a hundred events last year. You see a lot of stuff. What's the pattern that you're seeing out right now? In this new world order, there's certainly a couple key trends, and the big ones are autonomous vehicles, smart cities. Median entertainment's changing. The home, Alexa, Google Home, automation, but a paradigm shift is happening. What is your take on this? >> I think it comes down to, a lot of it, I think we've all realized we want an experience. Experience is extremely important. But what does an experience mean? And how do you make an experience stand out? I think that's one of the bigger problems today, is, with so much noise, so many things that are out there, I think a lot of people-- the idea of social good, people want to know that what they're working with, what they're working on, has a greater purpose. And I think, today's world, you're connected with no limitations, no silos, and not only being connected at all times, but how can you be connected at the right time and reach the right audience. I think technology like AI and some of the things-- especially cognitive, the idea that machines are learning with us, so it's not just machines learning and leaving the humans behind, but it's humans teaching machines, machines teaching humans, and then moving forward together. I think that's some exciting change. And it's from TV entertainment to enterprise tech, to even the social media space where I do a lot of work in. >> We're here in the Intel AI Lounge. We're on 77 Rainey St, so come by if you're watching here in South by Southwest. Always on Twitter. The hashtag is Intel AI at the Cube, ping us. Brian, the whole theme is here at Intel, and at South by Southwest, is real progressive thinkers, Intel's tag line is, "Your amazing starts with Intel." You start to see, even Intel, which powered the PC revolution, servers, are starting to make chips not just for machines anymore, for the Cloud, for cars. If you just think about autonomous vehicles, for instance. You think about what that does for the younger generation coming in, the computing landscape isn't about a device anymore, it's about an integrated experience, and one of the things we've been talking about on the Cube, and we're going to talk about this year, is, my vision of counterculture. >> Right. >> Every single movement, if you go look at the 60s, the computer industry was impacted by the counterculture of the 60s. You look at the PC revolution with Steve Jobs in the 80s, that was a counterculture. We're starting to see a counterculture now around new amazing new things. >> Brian: Right. >> With software, machine learning, AI-- I mean, it's mind boggling. >> Brian: It is. >> So, what is this counterculture? Do you have any thoughts on it? Do you agree, do you have any thoughts on that? >> I like to say, when Henry Ford said, that if he would've asked then what they wanted, they would have said faster horses not cars. I think today's generation has a bigger megaphone, is not afraid to say what they want, and because now, we have all of the data, they're not afraid to share that data. We're being much more transparent, allowing people to be a little bit more authentic with what they're sharing. I think we now have the opportunity to really shape new technology based on more data than we've ever had, more understanding of our consumers than we've ever had, and I like to say the consumer's no longer dumb, therefore, we have to start really pushing the boundaries. I love the tagline with awesome in it, because I think we are now creating awesome experiences and connecting things, probably in ways we would have never imagined. >> Yeah, I mean, one of the things we've been unpacking on Silicon Angle on the Cube, is this notion of all these trends that we're watching. A couple things we can talk about-- Delete Uber campaign came out of nowhere. The company's reeling because of one blog post by a woman who worked there, accusing the CEO of having a misogynistic culture. Fake news during the election. Global communication, now network, with instant sharing. We start to see these points where the voices of the internet of people is now part and disrupting traditional sacred cows, whether it's government, play, academia, so you can almost see it if you look at it and zoom out, you can say, "Woah, a new set of amazing things are happening, good and bad." >> Yeah, for sure, and I think, also, in that same realm, where now, it's kind of this idea where-- I think for the longest time, technology was taking us further away from the human condition, and we were able to be fake online, throw up a website, and really distance ourselves from the consumer and the community. And I believe now, because people are seeing through that, and the idea where people are faking profiles, we're now coming full circle where live video and a lot of these other things are saying, "Hey, we want humans, we want-- and then we want to be able to connect and come together." And I love the idea that we don't need-- a movement doesn't require a resume, doesn't require you to live in the same location. You can come together around a shared purpose, a shared passion, leveraging technology, and you can do it anywhere in the world. Especially from a mobile perspective, it's exciting to see people being able to have their voice heard, no matter where they are in the world. >> I mean, they literally-- I hate to use the phrase democratization, but that is really what's happening here, and if you look at how politics is changing and media-- the gatekeepers used to be a few parts of the world, whether it's a group of guys or a group of media companies or whatever, they were the gatekeepers. That's now leveled. You have now a leveling of that where you have these voices. So, what's happening, in my mind, is this whole AI for social good is super interesting to me because, if you think about it, the younger generation that's coming online right now and growing up into adulthood or teens is post-9/11 generation. When you think about 9/11, what that meant for our world, and now you're seeing the whole terrorist thing, these are people who are digital natives. There's a sense of, I won't say philanthropy, but societal thinking. >> And I think a part of it is, I think everyone has always wanted the ability to make a bigger impact on the world, but they also, now, I believe-- chapter three of my upcoming book is actually the future of marketing as social good, because I believe people want to know that what they're investing their money, their time in, has a greater purpose than themselves, and I think, because they're able to be connected, and we're able to expose cultures-- I mean, my daughter says good night to Alexa when she goes to bed, as if it's a human, and she's like, "Well, I got to say good night to it." It's this idea where, we're able to share, connect, and communicate-- computers are as much a part of that as humans are online, and it's an exciting movement because I think it's going to highlight and amplify the good and we're going to start to be able to drown out the noise and the bad that, before, oftentimes had a larger microphone and now, we're able to kind of equalize that. >> This is what I like about what Intel's doing. If you think about AI for social good. First of all, Intel benefits, thanks to Intel for sponsoring the Cube here, appreciate that. Plug for Intel. But if you know what they're doing under the hood, Intel makes chips. Moore's law has been one of those things that, for the folks who don't know, look it up on Google, Moore's law. Doubling the power every x-number of months, that creates really good processing power. That powers your glasses. That powers your car. The car is now a data center. The car is now an internet device. A human might have implants, chips some day. So this notion of the power, the computing power and now software's creation an amazing thing, but if you look at what you just said, it has nothing to do with computers. >> Brian: Right. >> So, computers are enabling us to do things and be connected, but if you think about that next generation of impact, it's going to come from human beings. Human beings, part of communities. And I think, if you look at the community dynamic, which has always been kind of like, oh yeah, I'm part of a community, but now, that there's intercommunication, your glasses are doing a streaming a video, we're doing a live broadcast, Twitter's out there, people can talk all over the place. You have a self-forming governance, a network. >> Which is awesome, because now, it's connecting great people no matter where you're at, you're not limited by your resume or where you grew up, and I also think there's an element here where, if you look at collaboration-- I believe collaboration is this key for the future of innovation. I think it's the idea of chips coming together with hardware and software, working together, not only in the post-product stage, but also in the innovation stage. And also, R&D Teams working together to now make things faster and smaller and able to really push the envelope. Things like, in the glasses, having sound and video, and having it connected to my phone, and transmitting with very little human input, we're now able to get perspectives that we would have never imagined, especially from just a regular person walking the streets. >> One of the things I want to get your thoughts on, because you're in the front lines, and also, I look at you, and you're not a young guy, you're an adult, but you're part of a new generation. I was talking with some folks at Stanford just last week around algorithms, and it's kind of an AI conversation, and something popped up. There is actually an issue of gender bias in algorithms. Who would have ever thought? So, now, there's kind of like algorithms for algorithms. This is kind of this AI for social good where, we don't want to actually start bringing our biases into the algorithms, so we have to always be monitoring that. But that brings up the whole point of-- Okay, we're living in a world of first time opportunities and problems and challenges. In the old days in the tech, we knew what the processes were: automated accounting software, automate this, automate some IT department, with unknown technology. And the technology would come out, like Intel and others-- now, we have unknown processes and problems, and known technology developing faster. So, what that's going to require is the human involvement, the communities to be very agile. >> Without question. Not only embrace change, but you also have to look at communities now where, I don't believe we are doing things massively different as humans today than we were years ago, we just now have more transparency and more exposure and access to all of our lives, and I think, with that becomes, as technology exposes more of our vulnerabilities, we as humans have to start to realize that people are more vulnerable and no one's perfect, and things are migrating in a different pattern. Give me that collaboration because we have to be able to trust the algorithms, there has to be that transparency there, but we also want some version of our own privacy, but I kind of live in the space where I don't think of privacy anymore. I think of things as transparently sharing, engaging, and then, hopefully, technology amplifying that and giving us the controls. >> And that's why I like how the AI for social good that Intel's doing here at South by, because it's not just the tech, it's the humanization of it, and South by Southwest represents a global culture of tech, creative tech practitioners, tech visionaries, futurists, kind of all kind of coming together. So, give us the update so far. You've been on the streets. You've been seeing folks last night. I've been on the influencers list last night on Facebook, there's a special group there, all our friends are on there. What's the update so far at South by Southwest, what's the current vibe, how do you see it going this week, what are some of the themes you see popping out of the woodwork at South by Southwest? >> I think last year was interesting. This is my third year in a row at South by, and I present and talk on a bunch of different topics, but I think last year, it was a lot about what is VR, and VR was shiny and fancy, and the conversations now seem to be, what is VR doing, what's the content look like, and where is it going and how do I get there. That's an exciting conversation because, I think, instead of it being a shiny object, it's now VR and AR and AI, how do they intertwine into our lives. The idea of interactive-- South by Southwest Interactive, really what these tools and technology are, is connecting that interactive capabilities. It's interesting to see the different car brands here. You have Intel, you have Dell, you have IBM, but then you also have some of these other brands that are trying to push the, I'd say, the startup agenda. That's exciting, because I remember, I wasn't here for Twitter when you were here for Twitter, but Meerkat, two years ago, for me, was the darling live streaming app that launched here, and it died a year later, but I'm glad to see that innovation and the startup culture is now mixing, kind of hand-in-hand with the enterprise. >> Well, I'm going to see some of my old peeps from the Web 2.0 days, and a lot of people were like, "Oh, the Web 2.0 days didn't happen," just like the bubble burst and the internet bubble, and that burst, but it all happened. Everything that was put out there, pets online, everything online went online. Everything that was promoted in Web 2.0 is happening now, so I believe that you're seeing now the absolute operationalizing, the globalization of democratization. The technology has now come with software for that democratization and now, what's exciting is, with machine learning, data sets, and all the stuff happening with the cloud technology and 5G, it's going to get faster now. >> Which is exciting, because I think real time is a powerful element, but if you're able to get multiple senses of data, interact with machines, and ultimately push that forward at the right time, I think that collaboration of machine, human, and experience at the right time is where we start pushing new innovations. AR and VR, even some of this cognitive type learning, starts hitting to mainstream, which I'm excited about because, I think, we're getting to this culture now where we look at change and we're hopefully now embracing the opportunities rather than looking and saying what you do. I think, now we're realizing no one cares what the product is, we want to know how does it impact us and why should we care. >> Brian Fanzo, new generation, a millennial, making things happen out there, checking things out. Of course, iSocialFanz is his Twitter handle, check him out. Always great content, always out there, the canary in the coalmine, poking at the new stuff and analyzing it and sharing it, oversharing, as some people would say, but not in my book. Always great to have you on. Good to see you. Thanks for spending the time, taking off our AI Lounge. >> My pleasure. Happy South by Southwest. >> Alright, we'll be back with more Intel AI Lounge after this short break. Hashtag Intel AI. I'm John Furrier with the Cube. We'll be right back. (electronic music)

why from Las Vegas Nevada it's the queue covers AWS reinvent 2016 brought to you by AWS and its ecosystem partners now here your host John Fourier and Stu Mittleman he welcome back everyone we are here live in Las Vegas for Amazon Web Services AWS reinvent 2016 their annual user developer conference I'm John furry with silicon angle Joe and Mike Coast give me a minute with boogie bond it's the cube our flagship program when we go out to the events and extract the signal noise and right now we have some really hot signal it's Andy jassie CEO of Amazon Web Services welcome back to the cube great to see you cube alumni three years in a row now you've been on the cube great to have you back keep the tradition going thanks for coming on it's great to be here and I wanted to congratulate you on your 29th birthday today I wish I'm eighteen actually you're gonna go that way I'll never get over eighteen okay appreciate that appreciate the merry Cammarata bringing the cake out for the team but what a birthday present for us to be at the cube this year because you guys have celebrate your 10 year birthday a little bit younger than I am but the world has changed in the past five years we sat down at your house and in your sports bar talked about the future and that's all on Silk'n angle comm and Forbes magazine calm but you guys have to set the agenda and 32,000 people up from 19,000 it's a significant uptick in attendance the enterprise cloud market is changing you guys are disrupting yeah your thoughts and on what's happened since Tuesday night with James Hamilton laying up a secret sauce of silicon brows back it's not being touched by anybody else efficiencies scale yeah well you know for us it's it's unbelievable to see how many people are here a reinvent I as I said in the keynote yesterday we weren't sure the first year that we could get 4,000 people to come so to have 32,000 people here and 50,000 more on our live streams for the keynotes it's just it's really inspiring and you know our teams spend most their time thinking about new new customer experiences new features new capabilities that enable our customers to build more for their customers and then operating the services and for our team to have a chance to be here with all of our customers for a week and just see how excited people are about what we're doing the platform I mean you really feel it when you're here it's a movement and it's a movement because it allows builders to build customer experiences much quicker than ever before and change their businesses you guys got a spy nose juice got some specific questions on some specific points but I want to get your thoughts on the Amazon what I call spring in your step for the first time at reinvent have seen some bravado but more you know confidence around thinking a position Vernor Vogel said a Mediate that sometimes doesn't understand things or hey why do I want to get a lower price by doubling upfront enough seeing the sales guy you mentioning a little bit of Oracle and but mainly it's the themes around the old garden and a new way so I want you to take a minute to explain your view on this new way this new environment because you're comparing interesting old ways of doing things how people buy from IP suppliers how technology is coded deployed and this new way where the game is all new ballgame everywhere scale changes in how people buy our changing it can you share your thoughts on this new way yeah well that's a I mean there's so much that we could share in that area but I you know I think that if you think about what's different about a company like Amazon and a business like AWS relative to the companies who've been providing infrastructure for the last few decades there are a lot of differences but I'll list a few you know the first is I think many companies talk about being customer focused very few walk and I think Amazon in every business including AWS is extraordinarily customer focused everything we do starts with the customer moves backwards from there 90% of our roadmap but what we build is driven by what customers tell us matters and the other 10% we try to listen to a customer's of trying to articulate and then read in between the lines and invent on their behalf I'd say most of the big technology companies the old guard our competitor focused and that could be a successful strategy they can wait and see what others are gonna do and then try to one-up them it's just not ours we tend to be customer focused second thing is we are pioneers you know we we hire builders who look at customer experiences and see what's wrong with them and then figure out how to reinvent them most of the old guard technology companies have lost their will and their DNA to invent and so they acquire most their innovation and that can work too but I think in a space as dynamic as the cloud which is the biggest technology shift in our lifetime you are much better off with the partner that has the most functionality that's iterating the fastest the most amount of customers the biggest ecosystem who's had the vision for how these things fit together from the start and then the third thing I'd say is that we are unusually long-term oriented you know I think one of the standard old guard tactics is that when a deal is to be done at the end of the quarter or the end of the year they show up at your doorstep and they harass you till you sign a deal only to be heard from again a few years from now well you actually need to sign a new deal that is not the way that we pursue our business we're trying to build a business and instead of customer relationships that lasts all of us and so we operate we treat customers we think long term and we iterate in a different way than you see the old guard do and you wrote the business case for creating AWS I think if somebody you know wrote the case study today they you talk about the flywheel you talk about the effect that scale has on your business I think many look at it is your scale and that flywheel allowed you to kind of compress margins in the industry overall well you know you know right the next business case that was scale let's kind of say if margin and you know you talked about how the race to zero wasn't it beyond kind of ancho piece of scale what is the advantage that you have with the experience and the scale and you know is there a new flywheel that goes beyond what we've been talking about well you know I think that there will be multiple successful players in this space because the market segments is something like AWS addresses are trillions of dollars worldwide but there are gonna be 30 it's gonna be a small handful and it's in part because scale really matters and in part because the amount of functionality that you need for people to choose you as their primary infrastructure technology platform is massive and we have a lot more functionality by a large amount than anybody else now I think that if you look at a couple of the key criteria and reasons that we've been successful one of them is that we just have iterated so quickly I mean I think that the rate at which we deliver new capabilities for customers is pretty unusual I mean every day on average customers wake up and they have three new capabilities they can take advantage of just by virtue of being on the platform but we're also on top of just delivering quickly we're innovating at a really rapid rate I mean look at what we did in building the no sequel database DynamoDB they would build look at what we did in building our own database engineer Aurora which is the fastest growing service in the history of AWS we just made Postgres compatible yesterday look at what we announced on the IOT side yesterday with green grass and with snowball edge look at what we did even with snowmobile where it's been impossible for companies to move large amounts of data look at how many instances we have and then look at us bringing FPGA instances to the client the pace of raw innovation on the AWS platform is very unusual and I think what that does that creates its own flywheel where because you don't have to spend a hundred million dollars upfront to buy an infrastructure platform you only pay for what you use when you make the choice of who you're gonna partner with is your primary infrastructure platform you want the platform the the most capability because it allows you not just to move your existing apps but to be able to launch new ones and any any imaginable business idea you have so one of the advantages Amazon has had both on that the dot-com side and now in the it beside it your data you've got a lot of information I think about what actually said that's part of a new flywheel that you're gonna be doing how much of that data is just what Amazon's gonna be able to drive and how much will that kind of spread to the ecosystem and your customers is there data exchanges or how do you look at data well we certainly have a lot of data and a lot of models and a lot of deep learning capabilities and we expose several of those to the AI services we housed yesterday but I think one of the significant flywheels you'll see over times that so many customers are storing their data inside of AWS because they love our storage services and our data stores that they're gonna want to use that data and they're gonna want to layer on top of it all kinds of analytics services whether it's batch whether it's you know various hadoop applications whether it's real-time processing of streaming data they're gonna want to run their data warehouse off of it and they're gonna want to run machine learning models as well as their AI models on top of it and even though I think loads and loads of companies will use the AI services that we've released yesterday I think a lot of the biggest machine learning that's gonna happen is company's own data companies have huge amounts of data that they want to get better signal from and a lot of that data lives on AWS and they're gonna use a lot of the analytics and machine learning tools that we have to get more value from it and you want to ask you specifically around the cloud competition we've said on the queue I think for you so at the first main event that we were here it's not a winner-take-all to winner take most the multi cloud conversations been going around and that's been kind of confusing people as well one of my goals this year at the reinvent was to look at the VCS dig deep once all the parties talk to entrepreneurs I wanted to find out from the canary in the coalmine the startups the developers what their their sense was they all love AWS because you you had a great service for them but now as the competition comes in Microsoft in particular spending a lot of dough trying to lure them in through their ecosystem Google mean they just have some tech not a lot of Salesforce these terms want to build their own sales forces and might not want to compete with Oracle or or Microsoft together monsters Salesforce massive commission incentives all kinds of mechanics that they're doing in the day and that product may or may not be as strong as you guys what's your message to that group of people that want to win with you what do you say to those guys on how do you look at that and what are the how do you respond to their feedback and what's the outlook for them because that's a big question of people's mind is I love Amazon I want to win with them but I might be lured by well you know I think if you look at the startup market segment the vast majority of startups continue you choose AWS as their provider and in fact you could argue an even larger share than before and the reasons are a few fold number one at the end of the day what startups want is they're trying to build incredible businesses and they're often trying to build businesses where the idea never existed before and to do that well you need the broadest functionality you can get Native US has much broader functionality with anybody else there's also a much larger ecosystem around our platform so if you actually want to use other software in your business you want to be able to use it on the infrastructure technology platform that you choose and again many more info system providers in the ad avails platform but they also are building applications where even though they're startups these security and the availability those applications are a big deal and there's just a lot more maturity in the AWS platform because we've been at it a lot longer you can't learn some of those lessons until you get two different elbows of the curve and as Gardner has said because AWS has several times the aggregate size so the next 14 providers combined we just have a different scale on a different set of lessons now we also help our startups and we go to market with our startups and we have get in front of our customers we have a lot of enterprise customers on the platform we're super interested in the new technology and the new offerings that our startups have and we continue to put them in front of saying at obviously Google obviously that's on the cube actually this morning Google doesn't really have a sales force now not known for customer engagement they're known for technology and I kind of hinted that Amazon doesn't have many sales guys but you do apparently a lot of simple you talk about the number how many sales people what's the field organization look like and he clarified that potential misconception that Amazon is just a self-service cloud well when we launched AWS in 2006 we had two sales people and in fact one of the first calls our first sales person made was to Tom McCaskill is the CEO SmugMug who has been just an incredible customer of AWS and provided so much valuable feedback and the ten and a half years we've been to the market but since then we have a very large field team I mean this is this is not a small team it's a very large field team with a lot of sellers and a lot of solutions architects and a large process yeah I mean it's it's it's you know we don't disclose the exact number but it's thousands it's it's a significant team sellers solutions architects professional services training certification it's a big team and we're continuing to grow at a very rapid rate yeah Andy you know that rapid rate is amazing to watch because you know you've spoken to us before about you look for builders you look for people that you know want challenges and keep learning I've talked to you know a few friends this week that have joined Amazon and they said the culture is different in a good way and I want you to talk about kind of that Amazon ethos there's you know a lot of companies have like mission statements you guys have leadership principles that are up on your website I hear they are you know quoted quite regularly you know in in daily life and it's you know very different can maybe there's a little bit of insight on that well 14 leadership principles and I think they've been the single most important reason that we have been able to scale as fast as we have and scale across the world the way we have without losing our culture and you know there are so many of the leadership principles that I think are really interesting you know one of them has to do with hiring and developing the best and we are really vigilant about not lowering the bar when you're trying to hire as many people as we are at Amazon and AW is a big temptation is just a lower the bar to allow you to move quickly and that's always a mistake when you're trying to build great products for customers I like you know I'll give you a couple the leadership principles I like one is the leadership principle that's being right a lot and when we first started when we rolled out the leadership principles people thought being right a lot meant that it had to be their idea they had at the start that she went with the people would get dug in and argue for their idea but being a leader and being write a lot means that you get to the right answer regardless of whose idea was at the beginning and regardless of how many times you change your mind along the way great leaders change their minds when they get new information so I really like that leadership principle I also really like have backbone disagreeing commit and so what that leadership principle is about is we don't just make it an option we expect employees if they disagree with the direction we're headed regardless of seniority of anybody in the room that they speak up and say we're going the wrong direction we're doing the wrong thing for customers even if we end up making the same decision we're gonna make before we end up with more rigor and the decision and people can argue too you know as long as they want as respectfully as they as they can in making the point and we're at the end of the day a truth-seeking culture so you know that old adage about two people look at a ceiling and one says it's ten feet and the other says it's 14 feet and they say okay let's compromise it's 12 feet what's very rarely twelve feet and so when you have a truth-seeking culture like we have it encourages people to disagree and debate with one but then once we make a decision yeah the disagreeing commit means that even if it's not the direction you were advocating everybody has to get him seeking argument you could say well if the customers not involve which version of the truth the customer has to calibrate that right I mean from here Stanfill ultimately the cut I mean we try to get customers involved the decisions we're making and we we speak to cus for input from customers yeah and we get input all the time but there are also times when you're making these decisions where you can't perfectly know we're trying to make what we think is the right decision for customers we get it right a lot of the time and sometimes we don't and if we don't then we'll learn from it sign here I gotta get this in but I gotta ask you a personal question do you get worried that you guys might get too cocky I mean right now you're on a great run rate the traction is amazing for me personally see it it's pretty stuff you know proud about you guys do this I'm a big fan as you know we're customer but you do a great work how do you guys not get too cocky what's that ethos what do you guys what do you say the customers would say it a little too big for your britches and Ian team how do you calibrate that I think that a lot of that has to do with the culture of the team and I think if you look at the culture of this team it is not a cocky team it's not an arrogant team it's a customer focused team and we I mean I think we're pretty thrilled with how things have gone the first 10 and a half years I don't think any of us would have had the audacity to predict yeah that would be where we are but I think we all know that the next 10 years are gonna have even more innovation and changed in the first 10 years so that's what we're really focused on and you know one another one of our leadership principles says that you know great leaders don't believe that their body odor doesn't stink you know and that's really intended to say that we recognize that there's all kinds of things that we can be doing better yeah and we have to be a constantly learning organization and that's the way we think about our business we have a lot of management style content on silca Daniel my third part of my three-part series with Andy final question I want you to summarize your you know really well done you had some nice clever confident in there the whole superpowers a bombastic claim with some that validated with some meat good very clever I like how you did that how would you summarize the keynote did the boy look down to what you were trying to accomplish what were you trying to convey what was the core theme of your keynote yesterday morning yeah the core theme really is that with the cloud with AWS builders have capabilities that were never before available to them on premises or elsewhere and with those capabilities or superpowers it allows them really to take on any technical challenge that they're facing and to build and implement any idea they can dream up and you know that was really the theme and then you know sprinkled in there we had a few announcements the 14 to be precise yesterday and then some customers who I think you know I think are really vivid illustrations of really reinventing their businesses and building customer experiences that weren't easily possible before doing it on top of AWS well congratulations on all your success I know it's still early I know I know you don't get to coffee knowing knowing you firstly after after the little sitting down with you and reinventing is about pioneering so you got to be humble and congratulations Andy Jesse the CEO of Amazon Web Services here in the cube I'm Sean for Ace to many are you watching Silicon angles the cube we right back with more live coverage of ABS 2016 reinvent after this short break

>> Live from Las Vegas. It's the cute covering knowledge sixteen Brought to you by service. Now here your host, Dave, Alon and Jeffrey. >> Welcome back to knowledge. Sixteen. Everybody, This is the Cube, Cuba Silicon Angles Flagship program. We go out to the events and we extract the signal from the noise We're here. This is Day two for us. Will be going wall to wall for three days. That knowledge sixteen hashtag No. Sixteen. Chris Beatty is Here's the CEO. Relatively new CEO. It's service now. Chris, Thanks for coming on the Cube. It's going to be here. So you are hosting the CEO Decisions event Yesterday >> I was an event. We had a lot of CEOs, a lot of energy in the room, you know, one of the main main themes. Wass. You know, technology change happens all the time, but really one of the leadership challenge is right and what courage is required of leaders to really break through the status quo and get to that next level. We talked a lot about the importance of getting the right culture right within it, and that's a and what it really means to have a service mindset right throughout the enterprise. And as our vocabulary becomes the same inside it and across all the departments, right, as a leader, how do you enact that change so really a lot about the human element, as opposed to, you know, the technology part of it? >> Yes. So a lot of discussions over the past several service now knowledge comes in one year, Frank said. He sort of threw down the gauntlet and CEOs. They have to be business leaders. No longer Is that just a technology roll? Others have come on. The Cuban said. Well, you know, CEOs role. They gotta choose. They're gonna choose a technical path or a business path or data path. Even Chief Date officer. What do you thoughts on the >> I mean, >> there's a >> lot of press about the role. The CEO, right? And if you go back years and anything from Seo's dead, it is a relevant right. It's going the way of the dodo bird. Teo CEOs Morse strategic than ever, disrupting and creating new business models. I think the answer is somewhere in between, and it's probably changes, you know, depending on the day of the week. Right. So CEOs have a base job which is running, you know, the technology infrastructure of any company running the applications. But I do agree with Frank in terms of CEOs up, leveling their responsibilities and taking on the responsibility for more. I could tell you what I take responsibility for, right And yes, it's I t. But the overall velocity of our business. How fast can we run with everything Hiring employees, closing our books. Every single process in the company is powered by an IT platform, right? And so high tea is really in a unique position, and it has a bird's eye view of the organization to really help. Dr Velocity and Velocity is everything. How can you outflank your competition? The other thing I see think CEOs need to take responsibility for is maximizing the productivity of every single employee in the company. Right now, if you take that on, you start to look at things a little bit differently. It's not about projects, it's really about outcomes. And you know what measurable things are we delivering? And last and certainly not least, I think, the responsibility for customer experiences again. Customer experiences are powered by platform CEOs have the ability that influence every single one of those experiences and make it great and more and more as we look towards the future with things like automated bots and augmented reality customer. Your actions are going to become human to platform, and that's going to increase its relevance in that >> so and thinking about CIA imperatives of, you know, the bromide of eighty percent of the dollars we spend is on keeping the lights on twenty percent of innovation of That's a real number, No, but nobody seems to argue with it. Yeah, you >> hear that number a lot, but I think the good organizations actually do measure that number so they actually they will know what their number is and that service. Now we've done a lot of work, so our ratio is actually sixty percent run the business forty percent on innovation, and we're driving that down. So it's uneven. Fifty fifty split. I think that where you don't want to go is spending too little time on what I call the utility computing because that's the fabric that gets work done right. It's everything from networking and email and all those basic services you still need to have. Those aren't going anywhere collaboration services. >> I'd like to split it up into a little finer grain. I wonder if you could comment run the business grow the business transformed the business. Now maybe you're maybe you're always transforming your business, I don't know. But in >> terms of have to be >> in terms of but specific spending on initiatives to transform the business is that a reasonable, reasonable way to look at your portfolio was >> absolutely right. And I think if you're not doing things that transform your business, you're you're not acting with enough urgency. So my view on it is identify the big rocks right that we need to knock down, make sure we make room for those, even if it's at the cost of the grow or run part of the budget. Because if you're not getting those things done again, back to that getting left behind things were moving too quick. You got to keep pace. So make room for the transformation somehow, and that means squeezing every bit of automation that you can. How did the run part of the business, which is something I've used service now for in my past. I used to be a customer. I bought the platform twice over before I joined the company, and we did it a lot, and I'm doing it now, now that I'm at service now, >> that's one of Frank's requirements to become a CEO. I think. How >> do you >> measure that? That split. You said you're sixty today. Like to be a fifty, a lot of CEOs going. I have no idea how to measure that. I look at my projects are, but guess how do you do it? >> And it's tough we actually use. Not surprisingly, are Ownit Financial Management module to do that. And so technology's technology would we take all of our G L data and we map it to a taxonomy of business services in certain business services we know are not transformative, but they're a run part of the business, and we do that mapping once than every month. We can look at actuals against it. We can look at our unit costs, but the other begin put his projects right, which is again also in our platform, so able to look at those two things together and data driven segmentation of our spend too many times I see ninety organizations. They do it as one time exercise as part of annual planning. Then they don't look at it again until the next year. Annual planning. But there's a lot of runway in between and decisions we're making every day, which you should be making based upon data. But instead you're doing on perhaps nine months ago information. >> So you essentially categorize the business process, the business services as run or Growler training farm and on an ongoing basis. >> Absolutely. And you do the math and the most dynamic part of it, his projects. So every one of our projects, when we look at our portfolio, we look at our project portfolio by business areas, the sales marketing HR finance so on. But then we also do categorize our portfolio by Is this just sort of keep the lights on activity? But it's a project we still need to dio, or is it growing the business in somewhere? Is it truly helping us transform the way we operate >> on reasonable people? Khun, sit down and agree on sort of what those look like and >> short, and we also adjust accordingly. Also, do a top down allocation of what percentage do we want to go into each bucket, and that's not the same for each area because different parts of our business are different maturity cars, different pressures on them. I wouldn't want to be very transfer meitiv with RGL, right? That's not an area I want to innovate on. But with our sales and marketing organization, absolutely. We want to be in high innovation. Hi, experimentation, whatever we can do to help dry. >> So that's a top down bottom up exercise with the executive team says Okay, >> sideways inputs from everywhere. You know, one of the things I think CEOs it is a coming to fund CEOs to dio is manage spend. But more importantly, where people spending their time right, that's inarguably a fixed costs. We have a set of people where they spending their time and are they spending their time on the right things? And if you get that right, the rest could get a lot easier. >> So Secretary Gates last night speaking Teo, you know, maybe roughly one hundred CEOs and your your CEO decisions Conference gave the thumbs down on consensus management, and I sense just a little bit of discomfort in the room because CEOs is a hard job. But you serve a lot of different masters if you will, and as well you've got heads of application development you got, you know, architects, you got the business to serve, and so there's a lot of consensus building. And so he got questions on How do you do it? What was your reaction to that? Your colleagues, You know, which >> one was your science? They asked him a question. And because he said Consensus building doesn't work into an outside person looking in, it would seem like by nature. Everything in the government is consensus oriented. He had a lot of examples actually, where he did things against his own team's conviction, but he felt like that change was necessary. So it's two things I think Dr Gates has dealt with monumental organizations, right? Texas A and M is the smallest organization of those the CIA and the D. O D. Department of Defense has three million people, so the scale is unlike what most enterprise CEOs are leaders have seen. So when when he talked about not being consensus oriented, he viewed it as a requirement, and I actually agree with him. If you're trying to disrupt the status quo, you can't be consensus oriented. I don't think you'LL move fast enough, and most of time you won't get very far. So I think it's incumbent upon leaders to be the ones that break the status quo and say, We've got to change. And But what? What Dr Gates did describe is that if people are informed about why, from their leader enough, even if they disagree, they can get on board. And he brought up numerous examples of where he had conversations with Congress and people within the d. O d about change. He wanted to drive, and even though they were very opposed to it, they got on board because they intellectually could understand why. And over time, he won over hearts and minds >> about your priorities. So you come in relatively new tow service now. So first of all first impressions, any any surprises, pleasant or unpleasant? And what your priorities. >> So coming in no surprises. I had had a lot of admiration for the company as a customer, and now that I'm here, I love the culture. The culture is very execution oriented, get stepped on, very customer focused. You know, when we when we talk about our go to market, we really talk a lot about what's going to be most important for our customers. What pressures are customers under what problems can be solved for him? It's really not a discussion around squeezing. You know, the maximum margin out of each customer, which I think is fantastic way drive pretty hard. But but we're also very team oriented culture, so that's been great. My priorities at service. Now, when I think about my six strategic themes that I'm focused on growth eyes hugely important that service now. Right now, it's a lot of time I spend, fails and marketing effectiveness and innovation. And what can we do to drive, help, drive growth from a night perspective? Working with our partner organization, helping our partners? I do business with us easier things like partner portals and things like that. Ah, velocity. I mentioned earlier driving velocity through every department at the Enterprise at service now and really maniacally going after business process automation. And the great thing is, we have a platform that makes it easy, right and Ivax full access to that platform. So self service catalogs and knowledge base, but really going department by department saying, How do we do that? Analytics. Obviously we want to continue to measure and improve our business. But we're starting to do a lot more with Predictive Analytics, right? And how can we use data to really predict next best actions in a variety of arenas? Uh, security is the gift that keeps on giving for every CEO never ending. It's >> just one of those things that'll Teo you got, you >> got, you got to accept it and then really focus on team, right? I think talent and team and culture hugely important. You could have the best plans, you know, on paper. But if you don't have the right talent and culture within your team to get it done, I don't think you're getting very far operational. Rigor is a big one for me and a Metrix based approach to managing our business and driving outcomes. So when I look at projects that I execute for the organization on time and on budget, that's fine. That's table stakes. Really. What I'm after is on benefit, right? Are we delivering the benefits that we said we were going to get? And last, but certainly not least a part of my job is now on now. What? What we mean by now? On now is me being our best in first customer. And that's a very strategic level, working with product management to help them, you know, with roadmap features and things like that that I think all of our CEO's would need also upgrading early. So hopefully we can iron out the bugs before all of our customers and then consuming our own your products and implement it internally, learning the lessons within our four walls that we can inform our fields they could help our customers. >> How about on benefit? What percentage of projects are on benefit? That's another one of these things. Seventy percent of the projects fail. It was a number one on the market research, even >> that even that's a problem that fail is identified as not being on time or on. But right now, I view that is interesting but not compelling. Are you delivering the outcome? And so we're early. I've only been at service now six months, but I know in the past, through rigor and even making it a metric that's important have gotten to an eighty five percent hit rate on benefit. Certainly you could do better, but some of the benefits we have realised, with our platform eighty three percent increase in productivity. Leveraging R R R R application, but examples outside of Ice D, where we've eliminated forty five hundred hours of work from our financial close by putting email and manual checklist on your platform. Eighty five percent reduction in time that we spent hours spent on on boarding new employees. I mean, the list goes on and on, but it's a requirement in my organisation. When you're doing a project, you gotta have an outcome and set an aspirational outcome. Because if you talk about ten percent improvement and anything, that's sort of easy to get it. If you tell yourself I need to get a seventy percent improvement, it forces you to really rethink things and think differently. And I think that's our job. Is leaders to set those set the bar really high and then sharp teams have the resources to go after it. >> So even if you're late and over budget, if you get that, I didn't say that I later over, but I was asked, so that's got three. So that's a that's a prerequisite to be on time and on budget, >> and we're not perfect, but our target is to be ninety five percent on time, ninety five percent on budget, knowing you're gonna have five percent, you know, wiggle room and ninety five percent on benefit. >> What is on. So when you talk to the board, switch topics about security, what should be on the CEO's checklist for communicating to the board about security? So So >> I think it's really about risk, right? And what risks do we think we have? What's the likelihood of those risks? And what's the plan to mitigate those risk? I don't think security should be talked about in a This is Donner. That's done because you're never really done right. It's risk management, and the bad guys continue to innovate faster than the good guys. So what's your current security posture? What's the state of your risks and how are you mitigating them and in what time frame you know the stuff about? You know, we have a deal. P. We have ideas. We have I ps. I mean, the list of acronyms is interesting at a more tactical level, but at a board level, I think it's really risk management. >> So I promise I wanted before Ortiz talk about mitigating risk. But is there a place for a narrative that says you'd only mitigate so much? You're going to get penetrated. It's how you respond absolutely is critical. And I can I, as the CEO can lead that response or whomever is the >> appropriate person? I think you you have to do everything you possibly can Teo secure your perimeter. But it's known that you are going to get breach. Just a fact. So then it really becomes How quickly can you identify the fact that you have anomalous activity happening on your network of data? How quickly can you mitigate it? And in the past, when I was at various sign JD issue, a lot of that was manual right You have. You know, you have a piece of bad malware on the Enterprise. You may even know what assets. Um, it's on where you think you know. Usually I think you know, and then you really find out later where it's gone. But tying those assets to risk meaning what? Business services, it is it my CFO's laptop? Or is it? You know, the the you know, the person in AP. So you treated a little bit differently. And is it the infrastructure that supports our badge reader? Or is it our ear piece system? Right, So that's the missing piece. And I do thank our security organization and our our business unit, Shawn, because they've actually built a solution. Help solve that where you can go from security incident. Piece of Alberto Asset to Business service to employ within minutes, which that used to be half a day, at least half a day is a long time in a security incident. >> Yeah, so there's that magic number of whatever it is two hundred five days to detect a penetration? Yes, very. Do you feel like your organization can compress that? Is that a viable metric to be focused on? >> It's certainly a viable metric to focus on in terms of knowledge, off again anomalous activity. I don't think we're near two hundred five days, but absolutely we are focused on it because we need to secure not only our data but the data that our customers in trust without trust, >> meaning you feel as though you could detect much in a much shorter time frame, and they have some interesting. You haven't depending >> on the wrist right? Without getting into a lot of the details. >> Yeah, So we'll see you. But implicit in that is that you have a sense of the value of your data, your assets your I p what you're saying you've got a pretty good visibility on. >> Is that right? Yeah, we d'Oh. We spent a lot of time making sure our security posture is solid again customers and trust us with their data. We take that responsibility very seriously. >> Not speaking for service now, but just general knowledge of your colleagues Do you feel as though the lack of ability to value data assets negatively affect people's ability? T appropriately spend resources >> on security? It's tough because one of the first things you need to do in security say, what do I need to secure first? And then you say, OK, well, that's my core. I pee. Where's my core I pee stored? I would argue that a lot of companies don't even know because it's scattered on different file shares and different servers, and then you don't know whether people are putting it on box or drop box or one of the many storied sites out there so keep key. First step, I think for a lot of organizations is really just getting a handle on where their I P is. >> Right? All right, Count Chris, Thank you very much. Appreciate you coming on last. Give the last word. Uh, knowledge sixteen for you. What's the kind of bumper sticker? Is the truck's pulling away from its been awesome. I mean, >> just talking with customers and fellow CEOs. You know, we're all in this journey together towards this service enabled enterprise, but it is about leadership and just courage to bust through this current status quo that were in within the enterprise to get to that next level of efficiency. >> Thanks a lot of fun. Well, congratulations on the new role on DH hosting at a hostel conference just caught the tail end of it. But it looked like great energy >> because a lot of >> had some really good discussions with some of your colleagues. So really great coming on. Thank you. Alright. Keep right there, buddy. That's the Cuba bit back from knowledge. Sixteen, Las Vegas. Right after this >> every once in a while.

>> Mine from Las Vegas. It's the cute covering knowledge sixteen brought to you by service. Now carry your host, Dave Alon and Jeff Rick. >> Welcome back to knowledge. Sixteen. Everybody, This is the Cube. Silicon Angles, flagship product. We go out to the events. We extract the signal from the noise Bart Murphy is. Here's the CTO of York Risk Services group. Mark. Good to see again. Good to see you. But thank you for having me. So what's been going on this week? Busy week. What you been doing this week has >> been busy. I've been doing a couple different things. One on the CIA decisions track, you know, collaborated on with those folks and getting some sessions in from service now and then on the partner side. You know, talking to customers, checking out and enjoying the the key notes on seeing what's new on the platform. Very exciting. >> Did you see Secretary Gates last night? We were, unfortunately, >> got pulled out for a call, So I >> think that's the >> one thing I did miss. You >> want to call me on that? One of things, he said, which I want to ask you about a former CEO. See XO now? Hey, said that consensus management don't bother now speaking to watch the CEO's as the CEO, yeah, it's a >> challenge. I think you know, there's there's one component that you have to devise, a strategy that you know a sound, and you have to have some resolve to help sell it. So I see that component of it. But the other is to sell that vision and get other people bought it. So, you know, I think there is a and consensus component from that, certainly from the executive team. And then you have to go sell it to your organization as well. And I think that truly doesn't come from just talking about the vision or the business case. It's from actually delivering the software and delivering the services and doing in an incremental basis that allows them to see and gain value from that, that that's what you build your credibility up on. And I think then that's what helps sell it. >> So you've gone through a few changes personally, your company. So take us through the care works acquisition. Sure, so >> careless family companies was required by your Chris Services Group S O. We're now part of a larger organization and national organization, Although care works itself had a few of the companies that had national footprint, a majority of them were primarily based in Ohio. So strategically great fit a great company. I moved into the corporate CTO roll about Oh, a year, year and a half after the acquisition, and I've been really trying to build out the entire enterprise strategy from a night perspective because they just they had procured a lot of acquired a lot of companies over a two to three year time span. And so we need to really invest a lot of time on what the future state of it is going to look like. >> So it's interesting gone from CEO to CTO. People talk coming to Cuba to talk about the role of the CIA. He'LL talk about all the time, and there'd been someone put forth the notion that the CEO eventually is going to have to choose a path, technical path or business path. You know, maybe both at different times. Do you subscribe to that, or do you see the CEO role is continuing on a CZ? We've known it. Yeah, >> we don't have a separate CIA and CTO I oversee the including operations. To me from a title perspective, I just want to have the organization view that that role is part of innovation. We have a chief innovation officer as well, but from a technology perspective, I think it's very difficult to run operations if you don't have a good grass for the technology in the platform. So regardless of the roller or title that they gave me, I think it's more about what are you managing on? And I don't want to ever be broken up between sort of SETI role that may be more focused on newer technology projects and then a CIA on Lee based on building our run methods. I want to make sure that those organizations are always combined because you're going to build much better software if you also have to support it. We also want to make sure that the automation is in place so that we have our support organization in mind when we actually deploy new platforms, new applications, new systems. >> So you see yourself as a software company. >> You know we do. We're in the wrist services business, so we are, ah, services provider, two carriers to large self insured Teo Large Claims organization. So we see ourselves. A lot of what we do is differentiated by our technology. Whether that's, you know, better business process, outsourcing functions or ability to do Bill review faster, more accurately. So our CEO definitely sees us as a technology company, and that's why there's a lot of investment in time being put into sort of build out what that future state of it is going to look like. >> What what do you do with service now? These days? How did the acquisition affect that and where you had it? >> Well, so we just went live with Yorker Services Group on service now is Platform on Geneva, and that's actually a separate production instance that we have with care work. So we deployed the care works instance in early two thousand eleven, late two thousand ten in that time frame, and there were, you know, there's a ton of customization a lot, you know, very solid platform for that family of companies with the York. There's a much larger scope that we wanted to address so very lucky again to be in that situation because I had an opportunity to start a redo and any time that you worked on a platform and you do it for a few years and then you get a chance to actually build again. So we really took more of an enterprise. I till out of the box type of approach s O that it could be flexible enough to manage across the entire enterprise, including all the acquired companies that we plan to pull onto the platform. And then that gives us time to figure out what was really the best out of our other platform that we want to, you know, retrofit back in. But the main reason I did that is to make sure that we could get some benefit out of the platform now and work and migrate into the business. Shared services functions within York that I think we're going to benefit very, very much from the new platform. >> So you've got a mulligan of sorts a little bit. >> Yeah, I got lucky on that on a little bit of the mulligan. And, you know, again, it's all about trying to make sure that we can come in and we just went live. You know, we're gonna have our challenges, like with any organizational change management solution, even just on the same side. But the cadence in which we're putting out releases to actually improve and bring on other shared services functions, I think, is where we will gain the majority of buying. >> So this notion here talked about a lot of this conference. The single cmd b yeah, is that something that you're able to achieve or working toward? Are you there? And absolutely, it's the goal. >> I mean, I don't know if you ever achieve it. I think it does take a lot of time. So the goal is to have everything in one platform for all of our companies across the board and to help facilitate automation, whether it's with GRC with the new security product that's coming out, which is, you know, something we're looking to get deployed in. Q three Q. Three Q For hopefully sooner rather than later. I just see there's a bunch of play on the automation orchestration side as it relates to tying in and tying an audit. Tien and Security on then also looking at business shared services and you know that's a whole different world of figuring out how can we help them? And we have ah operations service and are actually part of our next release. So I'll be very interested to see. You know, they do a lot of things manually like everybody does. He'LL be very keen to see how they see the platform and what they're going to come up with us, a strategy long term for them. >> So are you mentioned a couple times that York's made a number of acquisitions your company included, and don't give twenty four looking statements? Obviously, they're going to keep rolling up more things. But if you could speak to using service now as a vehicle to better integrate acquisitions, yeah, because for a lot of companies, that's a strategy. >> Yes, so and I actually have a strategy around that leveraging the platform is one of the main reasons that want to get it in now so that it could eventually build that. My whole goal there is the Leverage Performance Analytics on the way that I envisioned. Using that is, in many of the companies that we acquire, they will operate still, stand alone from a night perspective for some period of time. You know, whether that's six months, three months, two years until we can fully integrate him, whether it's network, you know, systems consolidation you name it. It takes a long time. It's not something that we have solved. So part of it is to be able to do modeling using Performance Analytics by pulling in the data so I can get them now onto this cloud platform because they don't need to be on network. I can have them operating their work within that platform for a period of a baseline period of time. And I could start to model that using Performance Analytics to say, How would that impact our enterprise? That's allies. Does it help our enterprise? That's always. Does it degrade our enterprise? That's the lace. Are they staffed appropriately to actually meet our enterprise? That's the lace and what our enterprises slaves. Once we start collecting all this data based on how we're staffed and how we're going to, you know, fund that transaction. So, >> Bart, if I understood it correctly, you have the dual role CEO slash CTO. Okay, is that there's the CSO report into you are he does. I saw Also he >> does. And so and that's ah, new rule that we established about a little less than a year ago. There was ah VP of corporate security. But we didn't have a chief information security officer s. So I we're not got a very season, see so and working not only as an internal what we do internally. Also within our tech company as well. We started cybersecurity practice. So everything we do, we try to make sure that we can actually support our technology investments from an enterprise perspective and be able to self serve ourselves as an enterprise. So very excited about that. That's why we're getting to the security components and some other products that we think will integrate extremely well into service. Now >> let's talk about that a little bit. I want to put forth the premise. You tell me, feel free to tell me the premise doesn't hold water. But it seems to us that there's been a shift in thinking about security from we'LL focus on you know, defense, defense, defense to one of you know we're going to get infiltrated. It's all about how we respond and I as the sea xo Whatever. See so CEO Seo, I can help lead that response. It's mechanism, but it's a team sport. Is that a valid premise? >> I think it's valid. I think you know, I think it's a little it is driving some change v f ear. But, you know, I think that, you know, is certainly from an external perspective can protect yourself pretty well. You know, a lot of the breaches were actually curve, and some of the cases were internal or through third party partners. So I think there's been a lot of additional due diligence being put on organization, especially as a service organization. We work with a lot of large insurance carriers as an example. So we are getting hit with a lot more requests and a lot more sort of assessments on what our controls are in that space. So we need to be mature, and that's based no matter what, since again, we're providing services to clients in this space, and we're collecting a good amount of claim data and bill data and medical data. So I'm not as going out staying okay, just when it's gonna happen and how we handle breach. If that's the case, I'm trying to figure out what are the ways that we can proactively manage our environment and be able to respond in a much faster fashion to isolate an issue as quickly as possible, which is why I'm really excited about the automation and security component within service now because properly integrated with similar tools that we have. There's a lot that the system conduce that a human can't get too fast enough that will actually shut down to manage that risk extremely well. >> Do you believe that the board level? There's sort of open and transparent communication that that it's not about If Wade get infiltrated, its we have been infiltrated and we will continue to be infiltrated. That discussion occur. >> I think, yeah, the board level. They're certainly more aware, and not just from their participation in our board for the companies that they run themselves, because many of these folks come from companies that their run themselves. So I think there's certainly an awareness I think they're demanding and wanting to have more concrete plans on what your corporate security strategy is going to be. So we've produced a three year plan on what that is and presented that our committee and are starting to communicate that all the way up, you know, through our CEO. So I think there's more awareness I I think that for whatever reason, people think that it hasn't been working on this for some time, but they have S o. You know, there's a lot of good things that we've already done and already put in place that people just need to be made aware of it and get up to speed if you will. And then there's. Here's what we're doing to invest in trying to stop future things or to be more proactive or tow, have better control. Is better auto practices this type of >> what's the right regime for a cyber security? In other words, who should be responsible for should be a single tech group? We Should it be a wider group. What responsibility? >> And no, it's it's it's It's by committee. So our committee included, you know, our general counsel, our CEO, our chief human resource officer, our CEO. So it it's a joint effort. Certainly there's a large component of it because many of it is about your defenses in your ability to manage and maintain and keep your data secure. But security is a company wide initiative. You know everything from training all the way down the associate level to not, you know, click on bad email links, right that no matter what you do and what type of in a virus you have and you're still going to get some of those fishing emails and some of those ransomware emails in those type of components. So there's a whole education put component that goes all the way down to the associate level. If that's not understood by the management over those groups, then you know how is it going to actually be distilled down and supported? So it's a complete company effort when it comes to corporate security. >> And how about >> the business lines? Because our research shows that a lot of organizations don't you don't even have the specifically answer for your organization. Just in your experience is the CEO and the CEO. If it seems as though a lot of businesses don't understand the value of their data or the value of their I p, and as a result, don't really know how to protect it, is that something that is challenging for organism >> Asians? I think it is least when I've talked to other clients potentially, I think less today than it was even five years ago. We certainly know the value of our data. I mean, there's been too many breaches in the large breaches in the past three years to not be aware. I have had that question asked ofyou on, even for a business perspective, understand the exposure. So you know they what is that? Hundred fifty hundred twenty five dollars per claim? Potentially on the data side. So people even put metrics around. It's you, Khun. Quickly go through and established what you think your overall exposure is from a dollar perspective and that starts toe. You know, open eyes when you have millions of claims, are even more millions of bills. >> And that's your business. So you would think you have a better understanding everything most. But so for those who don't how should they go about achieving that knowledge? That awareness, >> They should find someone that, you know, maybe some type of trusted advisor. You know, whether they need to hire a consulting company whether they need to go and just converse with another AA group like a CEO group and ask Hey, have you guys done this before? There's a ton of collaboration at that level where people are asking, Hey, how did you guys come up with your security road map on What did that >> look like? Because Because the value then drives your investment decisions, right, because that's the other thing is kind of like insurance. When is enough enough, You could always been Mohr, but at some point you're gonna have diminishing returns relative to the value. But you've gotta have a basis to set a budget. So I would imagine the value of the data, the value of the risk, whether its >> value brand right, so outside of the hard costs of potentially, you know, getting credit rating or those type of components. You know, there's there's the brand discussion, and I think that's somewhat invaluable. So, you know, budgets are just over. Go spend what you want, but there's certainly a lot of awareness that money needs to be spent that area. It needs to be spent wisely, but there hasn't been an issue as to either one. We're coming up with wild budgets for security but explaining what we're doing and why, and how cost effectively we're doing. It has been very well >> in thinking about how you communicate to the board Yeah, about cyber security. What would be the top two or three things that you would recommend that a C XO should have on his or her checklist? >> One is, you know, understanding all your end point, so understanding everything that's in your network. And it's an easy to say, but it's a very hard thing to do, especially when you have external facing applications. And you have a lot of different networks, so understanding your scope of devices and understand. You know, that way you could understand, to start to collect and fill up that C M G B and understand. Okay, if I have a patch that wasn't applied, how many devices were impacted? You know, how quickly can I get those remediated s so that you know, I think understanding the technical scope of your organization is important because it's very difficult to understand your risks, you know, rating if you will. If you don't understand the tools you have in place and where your potential holes maybe, ah, and then understanding you know your core data. So you know what is in your data that would potentially create a potential risk, even a financial risk? Certainly we go through all the insurance process, right? And even insurance now for cyber liability insurance. You know, the forms for five years ago were much different than the forms that are being filled out today. Much different. A lot more detail, a lot more drill down. So even just going through that process alone drives you to actually go and collect all this information that I'm talking about today, you know, so understanding your internal environment in understanding you know, those endpoints understanding the scope of your data management. And then I think it's around developing a sound strategy that is not just short term but short term and long term, with investments not just in tools, but also processes training those components. >> Did you look a tte security and responding to security is part of, ah, business continuity, as opposed to sort of a bespoke initiative. It is, There's business >> continuity and d are both have components of security, but it is truly what a way to ensure that you're you stay in business, right, and and And if people don't view it that way, then there's a lot of organizations that have been either crippled, not necessary put out of business but impacted extremely large. You know, financial impact with unmanaged breaches that actually went on way too long, right? And they weren't able to detect it, you know? So I think that there's a component there where you have to really think about what's the scope of the work, what the scope of the risk and how much do we need to invest? >> And you see service now. And I'm spending so much time in security this week because I'm excited about what I saw on Monday at the financial analyst meeting and who, talking to folks about this very important topic, you see, service now is playing a role in solving this problem. >> I do because we're a big user of GRC. So we already went down the audit route with service now years ago s Oh, this is just another extension I see of not just audit controls but being more proactive on the security side. And so, since all of our information is in this platform anyhow, we have a ton of opportunity toe automate and manage a lot of the things that again could have potentially gone unnoticed for a period of time simply because a manpower or logs if you ever had a review logs from some of these devices. I mean, trying to find the needle in the haystack is very difficult. So tools are extremely important in this space. Humans cannot meet this challenge alone at all. >> You just make a tad cloud. You wish, right? Awesome. Bart, this is I'LL give you the last word so that your impressions on knowledge sixteen. >> I'm excited, You know, the way it's grown again The way that they're really being purposeful about how they're building out their platform and truly trying to solve the enterprise problems to me is just it shows a very strategic, well thought out plan by service now. And as customers, you know and partners, you know, that's that's what you want to see from a company. So for me, I'm just very pleased where the platforms going. It's exciting how much they've grown. But the way that they've been able to invest in the right things, I feel and truly integrate things into the platform, even acquisitions that they had on and truly make it part of the platform versus and add on, I think, is really differentiating them from a lot of products that have grown in a similar matter but become unwieldy to manage because they're just pieced together. So I'm very, very excited, >> Fantastic. The cube securing knowledge for our audience that Bart, you have full of a lot of knowledge and really appreciate you coming on the Cuban and sharing. >> Yeah, appreciate it. Nice seeing you guys. >> All right, Keep it right there, everybody. We'LL be back with our next guests right after this. We're live knowledge. Sixteen from the Mandalay Bay Hotel in Las Vegas, right back. >> Every once in a while.

>> Las Vegas. Extensive signal from the noise. It's the Q covering interconnect 2016. Brought to you by IBM. Now your host, John Hurry and Dave Ilan. >> Okay, Welcome back, everyone. We are here live in Las Vegas for exclusive coverage of IBM interconnect 2016. This is Silicon Angles. The Q. That's our flagship program. We go out to the events and extract the signal from the noise. I'm John Ferrier with my Coast Day Volante. Our next guest, Steve Robinson News. The GM of client technical engagement before that, in the cloud doing all the blue mix now has the army of technical soldiers out there doing all the action because it's so much robust. So much demand for horizontally scale. The sluices with vertically targeted, prepackaged application development. That's horrible. First you name it big data. Welcome back. Good to see you, John. Thanks. Good to be with you again. Always, like great to have you on because you got a great perspective. You understand the executive viewpoint. A 20 mile stare in the industry. But also you got the in the nuts and bolts in under the hood. >> That's right. A >> lot of action happening under the hood. So let's get that right away. Blue, Mrs Hot Night. Now it's about the developers. What's going on under the hood right now that customers are caring about? >> I always love the Cube. You guys were like one of the first guys talking to us two years ago when we just launched a blue makes on stage. We walked off, got in front of cameras here, and it was great. Over the past year, it's been it's been outstanding. We we're writing about 20,000 folks toe blue mix right now on public, we came out with dedicated and then what people had really been warning was local blue mix as well. So we finally have full hybrid chain that goes from behind the firewall to a single client dedicated cloud all the way up to the public as well. So we've been building that out with service is as well, so have over 106 service is on top of it. You'll see things like Watson, which is unique, our Dash CB analytics, which is unique Internet of things coming in as well. So it's been a great year old building it out and getting more clients on top of it, >> it's like really trying to change the airplane engine in 30,000 feet. Or, in your case, you guys were taken off and from the runway. How has that been? It's been growing pains, of course. Unlearning What? What's going on? What have you learned? Give us the update on >> changing the engine while the plane is flying, and we've used that analogy quite a bit in the labs and way have to show relevance in this market. You know, this market is probably the fastest face technical market I think I've ever been in, and it's moving at such a rapid pace. We had to ship a lot of technology out last year is well, we have every new middleware group in IBM. Putting service is on top of blue mix, so let's get it out there. Let's get it out fast. Now, of course, this year we're gonna harden it up a little bit as well. So more architectures, more points of view. Better look on how this stuff works together hardening up our container strategy, pulling it all the way back to the virtual machine. So both continue to expand it out but let's make it enterprise grade at the same time. >> And also, some differentiation with Watts has been a big play around Catnip. Yeah, really is different because right now with the quote, um, market the way it is court monetization is on number one's mind. Start from startups to enterprises. If you're in business, you want you're top line if you're starting to get monetization. So there's a little bit of IBM in here for people to take in. Well, >> you know, if you look at Watson, you know, when we first started with it, you know, it was this very large big chunk of software that she had to buy. And and we work with Mike Rodents Team toe. Can we chop it up into a set of service is Let's really make this a set of AP eyes, and we started noticing, you know, you saw in Main stage the other day out from Otis. You know, this was a pure startup. He's started picking up the social semantics. Let's pick up the you know, some of the works to text etcetera, conversions, and all of a sudden they're starting to add it in. They said they would have never had access to this technology before way Have that a P I said. Not growing up to 28 we announced a couple cool things this morning. We even showed how would improve your dating life. Probably need some of that with my wife is well to translate between the sexes there, but what people are doing with it now, it's kind of like blowing people. His mind is far beyond what the initial exception waas. >> So your team of your niche is when they get right. It's a large team. It's, but it's a new initiative. New Justice unit, New role for you Talk about that >> way. Kinda had >> a couple pockets of this, but way clearly found that getting clients to the cloud is both a technology challenge as well as a cultural challenge as well. So he brought together some technical experts to kind of help through that entire life chain help up front. You know, many clients are trying to figure out what their overall cloud strategy is, where they truly today and where do they want to get to be? And how can we help him with a road map? That kind of helps them through the transition. Many accounts are very comfortable with the only wanting to be private and only glimpsing forward Thio Public Cloud Helping us bridge across that as well. Then we have the lab service's teams and these air the rial ninjas, the Navy seals. They go as low as you can go and what they're helping. A good way. Yeah, that's good. That's good. That's why they're helping with this very specific technical issue. Technical deployments. A lot of our dedicated local environment. These guys, they're they're really helping it wire in a cz Well, and then we have the garages, you know, we're up Thio. Five of those were going. We announced four new Blockchain garages as well. And this is where firms air coming in to kind of explore do the innovative type project as well. So I think all the way from the initial inception through rolling it out into production, having that team to be able to support him across the >> board. And so this capability existed in IBM previously, But it existed in a sort of bespoke fashion that coordinated >> couple pockets here and there. We always have supports. We had various pockets a lap service's. But we won't really wanna have the capability of seeing that client all the way through their journey, bringing it all under me. We now can easily pass the baton, Handoff says. We need to have that consistent skill there with the clients all the way through their >> journey and is the What's the life cycle of these service is? Is it Is it both pre sales in and post there? Just posted >> many times we'll get involved like our cloud advisers would get involved. Presale. They'll say a specific workload wants to go to the cloud. What are the steps we need to take to make that happen? A CZ well, with our Laps Service's teams, you know, we kind of have, you know, anywhere from a 4 to 6 week engagement. Thio do a specific technology. Let's get it in place. Let's get it wired in et cetera, and then in the garage is you know, we could just take a very novel idea and get it up to, ah, minimal viable product in about a six week period. So again, we're not doing dance lessons for life but strategically placing key skills in with accounts toe. Help him get over that next hump of their journey. >> Steve, when you look at the spectrum from from public all the way down to private and everything in between are you, I wonder if you could describe the level of capability that you are able to achieve with the best practice on Prem with regard to cloud ability. It's service is all the wonderful attributes of child that we've come to know and love. Are you able to, you know, somewhat replicate that roughly replicate that largely replicate, exactly. Replicate that. Where are we today? >> Yeah, I think >> it's a great question. I think. You know, I think most of the clients that we're dealing with have been dealing with some virtualized infrastructure, probably more VMC as they as they've been kind of progressing. That story. One of the things we did it IBM is Could we bring a true cloud infrastructure back behind the firewall? Could we bring an open stack? We bring a cloud foundry base past all the way back through because the goal, of course, is if we could have the same infrastructure private, dedicated and public as they continue to grow and got more comfortable with the public cloud that could start taking work clothes that they had built in one location and start to migrate it out with you. That that local cloud the Maur used for EJ cases. So taking that system of record and building a p i's and allowing to do extensions to that allowing you access into data records that you have today dealing with a lot of extension type cases, you know the core application still needs to be federally regulated. It needs to be under compliance domain. It's gotta be under audit. But maybe I wantto connect it in with a Fitbit or connected in with with a lot Soon are connected in with the Internet of things sensor. I gotta go public cloud for that as well. So locally we can bring that same infrastructure in and then they could doom or service. Is that extended out in the hybrid scenario >> code basis? Because this has come up. Oracle claims this is their big claim to fame. That code base is the same on premise hybrid public. Is that an issue with that? Is that just their marketing, or does it matter what's IBM take on this? >> But we've done ah lot of work with the open standard communities to let's get to a true reference implementation. So on open Stack, we've been doing a lot of work with them, and this is one of the reasons we picked up the Blue box acquisition. Could we really provide a standard open stack locally and also replicate that dedicated and, of course, have it match a reference architecture in public as well? We've also done the same thing with clout. Foundry worked with Sam Ram G to be one of the first vendors, have a certified cloud. Foundry instance is the same local dedicated in public. I think that's kind of the Holy Grail. If you could get the same infrastructural base across all, three, magic can happen. >> But management's important and integration piece becomes the new complexity. I mean, I would say it sounds easy, but it's really hard. Okay, developing in the clouds. Easy, easier ways always used to be right, right well, but not for large enterprises. The integration becomes that new kind of like criteria, right? That separates kind of the junior from the senior type players. I mean do you see the same thing and what we believe >> we do? I think there's usually two issues. We start to see that this model looks great. Let's have the same code base across all three environments. What things? We noticed that a lot of folks, when you get into Private Cloud, had tried to roll their own. You know, open Stack is an open source Project clout. Foundry is an open source project. Let's pull it down and let's see units roll it out and manage it ourselves. These air a little bit you they're very dynamic environments, and they're also a bit punishing if you don't stay current with them, both of them update on a very regular basis. And we found a lot of firms once they applied tenor well, folks to it, they just could not keep up with the right pace of change. So when the technologies we invented was a notion called relay on, this allowed us to actually to use the public cloud is our master copy and then we could provide updates to get down to the dedicated environment and down to the local. This takes the headache completely away from the firm's on trying to keep that local version current. It's not manage service, but it's kind of a new way that we can provide manage patches down to that environment. >> So one of the problems we hear in our community is and presume IBM has some visibility on this. I'm thinking about last year, John, we're at the IBM Z announcement in January, rose 1,000,000 company talked a lot about bringing transaction analytic capabilities together. But one of the problems that our community has practitioners in our community course the data for analytics. A lot of it's in the cloud and a lot of transaction data sitting, you know, on the mainframe, something. How do they bring those two together? Do I remove the data into the data center? Do I do I move pieces in how you see >> we're seeing a lot of that. A lot of it was. Bring the technology down to where the data is, and and now you know the three amount of integration you can do with public data sources, private data sources, et cetera. We're seeing a lot more of the compute want to go out to the cloud as well. You know, we've done some things like around the dash, CB Service's et cetera, where I can start to extract some of that transactional data, but maybe only need a few pieces to really make the data set. That is important to me as I move it out, so I can actually, you know, extract that record. I can actually mask it into being something brand new, and then I could minute we mix it with public data tohave. It do brand new things as well, so I think you're gonna see a lot of dynamic capability across that with or cloud computing technologies coming back behind the firewall and then more ability to release that data be intermixed with public data as well. >> What's the number one thing that you're seeing from customers that you guys were executing on? There's always the low hanging fruit for the easy winds from bringing a team of street team, if you will out. Technical service is out to clients where they really putting that gather, not their five year plans, but their one year. Of course, there's a lot of that agile going on right now. New technologies. You can't isolate one thing and break everything. Za new model. What a customer is caring about, right? What's that? What's the common thing? I think >> over there in 2015 I think the discussion changed and went from Are we going to go to the cloud or we're going to the cloud now? How are we going to do it? And the nice thing about I think a lot of enterprise architecture groups kind of took a step back to say, What do we truly have to do? What is a common platform? What is an integration layer? How do we take some of our old applications and decomposed those into a set of AP eyes? How can we then mix that with public AP eyes? So probably taking one or two projects to be proof points so they could say, this thing really has the magic associated with it. We can really build stuff fast. If we do it the right way, it's gonna be in a catalyst to have the I t. Organization now take the tough steps in what's gonna be the commonality? What common service is are we going to use and how do we start breaking up >> around things you know, we have our own data science and our backcourt operation and one of the things that we always looked at with bloom. It's way start our Amazon. But now, with blue mix, you have a couple things kind of coming together in real time. You said it's getting hard, but those hardened areas are important identity. For instance, where's the data is an instruction and structure. I want a little mongo year or something over there, but with blue mix and compose, I oh, really has a nice fit. I want to explain to the folks we talked before he came on about this new dynamic of composed Io and some of the things that are gluing around blue mix. Could you share this >> William Davis King right? And I think people look to the Cloud Data Service is air. Probably it's the most critical, the most visible, and the one we have to harden up the most is well, even though IBM has been well known for D. B two and we've been a >> wire composed right >> that we did Cognos first, and then we followed up with composed by you because recent waded about, we did compose. I know about eight months ago what we liked about it was all of your favorite flavors, you know? So your your progress, your mongo, you're you're ready. But really having it behave like Like what you would want an enterprise database to do. You can back it up. You can have multiple versions of it. We can replicate itself >> is a perfect cloud need of civic >> class. It has all the cloud properties to it and all the enterprise. Great capabilities with it. Yeah, we've got that now in public, and then you're gonna start seeing dedicated, and you want >> to go bare metal, Just go to soft layer. It's not required right on these things where this will work in the cloud, and then you get the bare metal object you want pushed up the bare metal. No problem. Well, I think >> you know it. Almost hybrid is not gonna get a new definition around it. So it's all gonna be around control and automation, more automation. You need to go all the way up to a cloud foundry where it's managing all the health, checking and keeping your apple. I've etcetera. If you want to go all the way down to bare metal so you can tune it audited et cetera. You can do that as well. I think I've got one of the broader spectrum, is there? >> I'm impressed with the composer. I got to say, Go ahead, get hotel Excited by what? I get excited by just about every way. Just love the whole Dev Ops has been just a game changer in extras. Code has been around for a while, but it's actually going totally mainstream. That's right. The benefits are just off the charts. With Mobile, we have the mobile first guys on. Earlier in the Swift, we had 10 made 12 year old kid. I mean, it's just really amazing. Now that the APS themselves aren't the discussion, it's the under the hood. That's right, so you can have an app look and feel like it's targeted for a vertical, say, retail or whatever. But the actions under the hood yeah, yeah, more than ever. Now >> it's, you know it's funny this year, you know, Dick Tino to the Devil Obsession yesterday and you're the amount of proof points we had around it last year. We were scrambling a little bit and this year it's just we always had to thin out. That's how many guys were having great success with this stuff is coming into its own. >> It totally is. And you guys are give you guys Props were running as fast as you can and you're working hard. And it's not just talk. Yeah, it's It's it's legit. I'm gonna ask you a question. What's the big learnings from last year? This year? What's happened? What do you look back and say? Wow, we really learned a lot or something that might have been Magda ified for you in this journey this past year. >> A lot of it goes back to, you know, this changing culture at IBM, you know, the amount of code we put out in two years was just just unbelievable. But I think also the IBM becoming a true cloud company. Some of that we did with our own shop some, but we did through injecting it with acquisitions. You know, like to compose Io the cloud and team, the blue box guys, et cetera. I think we got the chops now to play it play pro ball way worked very hard, Teoh. How many folks, Can we attract the blue mix? We're getting up to 20,000 week. Right now. We're starting. Get some great recognition and the successes are rolling in as well. So a lot of hard work and a lot of busted knuckles. A lot of guys are tired. Definitely, definitely straight in the game now. >> Ready for the crow bait? Taking the pro GameCube madness starts on cute madness. There were, you know, keep matched all the brackets of the Cube alumni and vote on it turns into a hack a phone because everyone stuffed the ballots. Let's talk about pro ball for next year, a CZ. You guys continue? Sure. The theme here obviously is developer. I mean, the show could be dedicated 100%. The blooming LeBlanc up there kind of going fast at the end of this booth on the clock anymore. Time >> right. Like the Star Wars trailer we had >> going up, he needed more time. So it's good props you got for this year. What's going on the road map this year? What if some of the critical goals that you guys see on your group and then just in general for the thing a >> lot of the activities were gonna be doing again is hardening the stack. I've got a brand new team now called a Solution Architecture, where we're looking at it from top to bottom, taking customer scenarios and really testing it out. How do you do? Back up. How do you do? Disaster recovery? How do you do? Multi geography, You know, things like PC I compliance. The rial enterprise problems are now coming to the class global and their global. And with security and compliance, they're changing in a very dynamic fashion. We have to show how you can do those in the cloud. You'd be amazed on how many conversations we have with Si SOS every single week. Is the cloud secure? How do we do enterprise? Great workloads. IBM is bringing that story to the cloud as well. That's the story of >> a potato that content >> Curation is unbelievable, right? That's the hardest part. And it's not that we have it fixed either. But you were doing more of aggregating it together so that we can really pull it all together. I call it the diamond Mine versus the jewelry store. You know, we always have really did you got yet? The great answers out there somewhere. But if you don't start to pull it together into a single place So one of things we did this year was launched the blue mixed garage methodology where we took all of our best practices. We took text test cases, even sample code, and brought it into a single methodology site where people start to go out, pull it down, use it, etcetera. Previously, we had it scattered all over the place, and we're gonna be doing more things like that. Bring in the assets to the programmers, things that we've tried, things we've tested being more open about it, putting in a single location. >> Well, we certainly would like to help promote that. Any kind of those kind of customer reference architectures. Happy to pump on silicon angle with the bond outlook for the vibe. I'm sorry. Five for the show things year. What's the vibe this year? You know, I think I've >> been very impressed with it, and I think, you know, I've been stepping up its game If you go down to the blue. Mixed garages are motives. A motorcycle on stage, you know, kind of getting a little more hip and happening as well. But I think the clients here and this is always about the customer stories and some of the things that we're hearing from the three guys start ups that are doing GPS logistical management 22 to the big accounts, and the big banks that you really see have embraced the cloud and doing great stories on it as well. I think people come to this show so they see what their peers were doing. And they definitely walk away with a sense that the cloud Israel it's happening and 2016. It is really going to driving it home. That has to be part of everybody. Strategy motorcycles I had put on the Harley Man. We'll take it for a spin guarantee. Come on down >> and give my wife. When I got married, it was terms of conditions. That's right. That's right. Last, Watson that Yeah, Thanks, Steve. Thanks. Taking the time and great to see you again. Congratulations. What? They get technical engagement team that you have all the work that you did that blue mix noted certainly by the cube. Congratulations and continued success with Loomis congratulating >> you guys. Well, always a pleasure. >> Okay. Cube Madness, March 15th Cube Gems go to Twitter. And speaking of jewelry, we have Cube gems hashtag Cube gems. That's the highlights of the videos up there. Real time. And, of course, we're gonna get that TV for all. All the action videos are up there right now. I'll be right back with more coverage after this short break here in Las Vegas.

>>live from San Francisco, extracting the signal from the noise. It's the cues covering Oracle OpenWorld 2015. Brought to you by Oracle. How your hosts, John Courier and Jeff Rick Wait, >>We are here. Live in Howard's treated oracle. OpenWorld for Silicon Angles, The Cube Exclusive coverage Star flagship program. We go out to the events extract the cinnamon noise. I'm John Kerry, the founder of Silicon, and Brian gracefully lead analyst on all the cloud and all the infrastructure stuff going on here. Next guess is Jeffrey Davis, Principal Gore, Oracle, global leader for Deloitte and Touche. Legend in the industry. I've been covering Oracle for a long time. Good to see you, John Bryan allegedly knew she had to get that in there. Love that. You know you guys are. The service's angle has been something that the service's business is. It's been changing radically. Now more than ever with clouds. I really want to get your take because you are an executive looking at this transformation of cloud. But the Lloyd across all the Oracle customer base, your party with customers. So you're the front lines. I gotta ask you straight up. What is the number one thing customers are looking at right now that you partner with four Cloud to figure it out. Is it a migration? All the above, And what do you think about that? So when customers are evaluating the cloud or our clients are looking at the club, you really focus on three things. One is agility. Thea other one is time and the other one is valued. So how quickly can we adopt to the changing environment? How quickly can we leverage technologies like clouds in order to be able to respond to our customers, to adapt to the changing needs of our employees, to embrace our business strategy in a new and innovative way? So I said legend, you know, talk about the eighties for women on camera. That's important point I want to bring up. Is that Is that the old way? Big growth of client server was around software middleware right year BC around you name it that created huge consultancies like Lloyd, you participated in that create a lot of wealth creation for the customers, create value, right, but their cycles were long in the deal. That'll be about 12 13 years now, months and almost a year or two, there were all these big deployments. Now the cloud is accelerating when you compare and contrast time of then share. And now with the cloud Just how much the deployments change the software, the organizations, How you guys operate a new way to do that job well, and we're all responding to the market, right? While responding to customers needs Cloud didn't come about because of technology in it of itself. But we're really all in this ecosystem responding to our customers must customers a really demanding from us is there demanding agility and speed. As I said before, if you take a look at the way we used to do things, basically you had a a large capital investment on the part of the customers. They went, they bought the software, they bought the hardware, they had to hire the expertise of an advantage, mail the eggs, and you're looking at a transformation for them that could take anywhere from 12 to 24 months or longer before they would get time to value. And, you know, these projects didn't go as planned. No, that's this is Yeah, I know the change orders came in paid more cash on DSO. We all got a really bad reputation because of the high costs in a long time to value and even if value was ever realized in some cases, now we take a look at the environment and what the cloud enables us to do is move in a much faster pace. Way used to have what we call a waterfall approach to design and implementation went into a big room and you talked about the world and I never ran that way. And then you put it into the system and then people never really embraced it, because when it came out, it didn't look like anything they thought they were gonna get. This is completely different with cloud. Now you can take an agile approach. Now you can sit and listen to the customer demands very quickly respond to what they think they need, where they really generate value. And then you can focus on those things and very quickly there, in a design session with you And at the end of the day, >>changed management is much easier because they've been a part of the process and also, you know, looking at 90 days sprints. You're looking at things that are done. You know, in >>six months, six months, time to value that can give you compress a competitive advantage. You know, that could help you retain Maur employees or customers. So it's really some timetable. Met Lavery s V p of the Cloud Gru. Gru Integration was saying they were doing provisioning on in 24 minutes. Multiple deployments like like nobody's business. What has them in the timetable that you're seeing for some of these times of value, horizons means hurdles. These milestones said days, weeks, months, hours, minutes. I mean, when you go to a customer base where their expectations of what you guys deliver, there's some insight there. Some of it depends on the environment. So remember they're still clients. We have local customers that are in a highly regulated industry or have a very complex prisons process. Those are gonna take a longer there is they're gonna take in. Technology is not necessarily on the critical path. But when you look at those other areas that frankly, you don't differentiate yourself very much or speed with a solution concave you a competitive advantage. You know, you're looking at a client expectations of anywhere from 90 days, you know, to six months, you know, manager here, very manager, but aggressive. Visa VI the old way. Well, certainly, And the other piece that we're not really talking about is, you know, it's not enough for us to put the technology out there. It's also got to be used and adopted. You know, when you had those large transformations. It's very hard for an organization to absorb all of that change. Now we're looking at the fine entry point that you could get with clouds with that fine entry point. Now we can sub select areas with greatest impact, but we're not changing the entire organization. >>Mark Hurd has the C I. O. G. On this morning and one of the comments that he made. I've heard this a number of times over the last 12 18 months. He essentially said, I have a ton of undifferentiated applications now. They're things that that Oracle thinks are fantastic. HCM and C. R. M and Air P. But in essence, everybody has those. Every business has those very undifferentiated, but they're complicated. What? You Seymour, you see more people saying you know what take those. Help me migrate those into SAS applications, you know, save costs. Where do you see more saying, You know what? Give me the other 20%. The ones that drive business differentiation, ones that are new cloud native applications. What do you see in your mix? What's pushing your customers >>to push you? You know, it depends on the geography, and it depends on the industry and some other things. If you want to talk about North America, which tends to be one of the largest markets in the world, if not the largest market in the world, when you're looking in North America, really people have gone through a lot of the major ear piece. Remember the earlier conversation? You know, they have suffered through tens of millions, hundreds of millions of dollars, and their boards were not satisfied that they got the results of the expected. Now, when you take a look at what's happening, you know, people are now being much more strategic in their investments, much more prescriptive there. Look how they spent exactly, because now the boards have different expectations. They've already gone and spent all that money on technology. They can't go back to the board. Can't say we need to redo this. What they do are willing to fund is you want to get into a new business. If you want to spin something off, you need to stand it up right away. If a customer you know, provide you a new opportunity, you want to shift to that new opportunity. Really? Well, technology is the basis of a lot of this transformation. So Cloud provides that opportunity and it's modest investment with really quick, high value. It's a great point >>you look at I t In the past decades prior to this evolution, we're seeing the cloud consolidate, consolidate, consolidate, right? I don't know the well again. I just went to the well, apparently running, you know, whatever the model was there. But now they're under a lot of pressure to drive top line revenue. Absolute. Now, the top line revenue equations, a completely different mindset. You have to go out and oh, cut the market. You gotta use a shadow I t or your authorized go out. Do legitimate stand up new platforms are Can you give me an example of that? We're seeing more of that now. A clear Mandate. Cee Io's Go take a New Hill or let's consolidate these apt and reposition for this new use case, which is not. That's experiment, but it's certainly a new market opportunity, and they gotta do their due diligence, so it's almost unparalleled. Due diligence kills your waterfall. That's one doesn't talk about that dynamic. Where examples you give go. Take that new top line revenue driver. So you know that there are customers that are looking at new partnerships in the marketplace, and those new partnerships have dynamic new business models. You know, it's not like opening up another hamburger stand. You know, they're not necessarily expanding into our core business. They're really looking at ways to amplify growth. If you're gonna take that as a strategic position, then you know customer or client of ours would focus on, you know, let's take this innovation the market. We don't want to invest a lot in it, waste a lot of time and lose the competitive advantage. Let's >>get to market first. Let's provide a new product or service to the market where we can move very quickly, and then the >>net result is we can see the benefits right away. And if it isn't way, haven't sunk a lot of time and money and something that's not necessarily gonna have the same values. We just had Shawn Price on. And I'm gonna ask this because it's a lemon that you're in because you're part of the customer right here, the strategic partner of the customer. So that idea top line revenue growth could come from a partner. When I see How do you work in that? Quick, You're cool to work with my Aunt VI's. Bring that into the table. You're absolutely so this market is changing. You know, Cloud clearly changes everything and much more so than some of the things we've seen in the past. And so now we need to position ourselves differently now for the Deloitte Business Model way. We're really in a specialized business of focusing highly on value and value creation. We weren't necessarily in other areas and we have different partnerships now. Those partnerships are shifting. Oracle provides us a complete platform. You know, we don't >>have to really get involved in a lot of the aspects of the platform that, frankly, we're in our core competency and frankly, weren't our clients what >>you talked about that customer interaction? What do you have to do to change what we've seen? Different size, trying different approaches? We've seen some that are partnering with cloud Provider, but they want to be their own flat for acquiring them. What changes in terms of the skills you have to hire the way you expect that interaction toe happen between you and customer. Because to a certain extent, like for developers, developers love self service. They do. You know, they they are shadow I because they're driving What changes in your world for that? >>So this is really kind of an interesting question. Very early on, when Oracle made cloud product available >>in HCM, we saw an opportunity. Our clients had the demand because they wanted to create a more sticky environment from customers. What better >>way than providing them better products in the HCM space? We made major investments there. Now we're a leader in HCM, and if I look back over that experience, what do we do differently? First of all, we had to change our mindset. You know, it's not enough just to say the cloud, but you gotta live the cloud because it truly is more agile. It truly is faster. You can take your old methods and tools and approaches all the things that worked for you before. A lot of them don't work anymore. There's some but some really good winds here, especially in the change management side. Also, you know, we'd have clients that had to kind of do it yourself brain surgery that have to order their own hardware that have provisional themselves. You know, that became a real mess. Now we're looking at something that's a lot different. We're not in that business anymore. You know, we do support on Prem where our clients think it's important and strategic course. But now we've got a new, agile methodology. Now we've trained our workforce. We've got 14,500 professionals around the world. We've had to move that group, and Oracle really helped us do that. They've been very collaborative in sharing I p and sharing methods and tools with us so we can make that adjustment. Not only have we had to change that when you think about our other methodologies, all of our other methodology to create value to change management, they were all thoroughly integrated. We've had to rethink those, but it's been a great story because we could go to the client. We can say we can get you there faster because where technology was a barrier world, >>it was on the critical path. We're now changing that. And by the way, this technology is not your old technology. It's much better. It's much more robust. How >>do you you know, obviously we're here It at an oracle OpenWorld. It could be called Oracle Cloud >>World if we really wanted to. I mean, >>it's a lot of it is the red stack. A lot of it is one cloud. How do you manage that against customers saying, Well, look, there's other options as well. I wanna have the ability to leverage this cloud for something. Oracles cloud for certain things. How do you do? You find your customers want multiple clouds or one cloud is good enough? >>Well, we're all teaching right? We're all teaching the world about God because you know there's still people that look at it in a variety of different ways. I think it's an excellent question, so let's think about this. >>Do you want to be your own systems integrator for your smartphone. You want to go by an operating system? Do you want to go buy a separate peace of heart? Where do you >>want to decide what APS fit? What don't. And do you want to actually try to get those abs together? I don't think we want to do that anymore. And I try to use that as an example for my clients. Tell them. Look, let's not be your own systems integrator. You is a iittie executive. You could be an officer toe, help the organization get to their business goals. You know, you're not in another yourself a business objective, but you could be an agent for change. I try to educate them so they can help their colleagues explain cloud, take the fear out and then show the art of the possible. What about the security model? I mean, I wouldn't get your take on you little bit biased because your manager Oracle really? But what would be global, critical or complementary events? How you feel about it? But the intense security message is really a game changer in my mind. Follows on incredible theory. Incredible application. Certainly the product's gonna be ready soon. If it works, it's like a car that does the key turnover. It's like it's all good on paper. Certainly a game changer. Security outside number One thing you're hearing Get some color to that because, you know, if that plays out, if you believe that end N security on the chips and software Silicon plays out the way they say it would, that's gonna change the game. For sure. It is. So none of us and you can go through a week without hearing about a major security breach. When you think about this, you step back and think about the potential here. Our stuff is starting to talkto our stuff. But our stuff isn't unless it's based on. Oracle isn't all thoroughly integrated, so somebody can break into our stuff and they can get access to our lives and they can change our lives. That's hugely powerful. So we are very concerned about security, and Lloyd is one of the largest organizations. In fact, we have a cyber practice that looks at both Proactiv reactive aspects of security. Here's the big concern we have as all this stuff starts, get interconnected. The Internet of things, security becomes a major issue. We need more breakthroughs and security. And I think oracles on the vanguard certainly as we get into what we call a hyper hybrid cloud on Prem on Cloud. Some of that's gonna be a great emotion is no. Perimeter is nothing either. Protect is the Wild West total while and, you know, despite what you believe, boards and people are not reacting fast enough to security threats. And that's why you're seeing these breaches into my knowledge. I don't think anybody has been breached with Orgel security in place. But that said, you have to be really, But still, they probably would get out. There's not that they're hiding it, but the point is, you need to be united engine system. It's hard to do that in a open source world, right? So you have a horizontally scaled open source phenomenon, and it's growing our market and a vertically integrated product requirement. You believe I want Indian security, then you gonna go vertically integrated. You do purpose built. But if you want scale a 1,000,000,000 large scale a k a cloud, you want horizontally scalable. How do you reconcile that with your customers? Well, you know so again. It's difficult for them because unless you've had a security threat, it's very difficult to really get them to take the initiative. You know, the more that we can build security in, the more that it's covered in the Red Sea. More that we get a comprehensive end to end product. I think it allows us to help the client realize you know the risk and help them. The old Fowler said. In The Cube they had they had this done in 2005. Finally took a bunch of security breaches to get people's attention to your point. It's on everyone's agenda. Number one right it is. And yet you know how much is enough? Well, we find the people are too reactive and not not proactive enough. >>What's the What's the temperature of your customers right now? I mean, you know, Tesla's out, they're disrupting Uber's out. Their Airbnb are they? Are they sort of defensive and paranoid? You know that Andy Grove, always trying to be aggressive with a saying No, no, no, no. I'm not letting these little guys into my market. I'm gonna go be aggressive and try and push back what a general feeling. There's a lot of interesting startup disruption going on really changing industry. >>There is, and you know, there's so many sort of partnerships and alliances, mergers and new innovations. You know, right now, clients are very uncomfortable. Just the transition from on Prem to Cloud is a major change in our clients have been the expert for technology for decades for their organization. They are having trouble keeping up with all of it. It can be disruptive. They're looking at what's unique in their industry. You know what is regulation driving? You know what is innovation driving in their industry? But, you know, they're always on the learning curve. They're always trying to figure out if we want to get your final thought wrapping up here to get your take for the folks that are watching here on camera that couldn't make it here were beloved world. What is this show about it? We've been here six years. You've seen that transformation. About four years ago, Larry looked like a deer in the headlights, almost stuck in his tracks and smoke coming out of his ears like he felt that the scene felt like a pivotal moment couple years ago. And then since then, just been every year. Oracle just gets more and more energy, just like dominated that march of the crowd. Almost like four years ago. Like we're gonna win that. What's your vibe? You see that same thing here and shared some color on the take is over the years, and we've been doing this a lot in various forms Over the years. There's been the promise of riel innovation. There's been the promise, real change in the industry. We saw sort of incremental change. We really see increments. Exponential change now and now. The promises fulfilled. We have real product. We're taking the market. We're doing interesting product, right? Israel product. It's very riel, and we have work to be done. But yeah, really studies and customers? Well, it's an evolution. But this is really sort of an epiphany at the moment, because we've never had, >>you know, full sweets of product in the marketplace. Not right now. I don't know that there are any other large you know. Air Pia options in the clouds away there is for Oracle and look at the host of service is that have been announced over the last year. >>This this particular show for us, you know, really isn't accelerating. All these products and service is in the cloud that are now available. They give us a lot of different options that we never had. A great quote. Put that on a cube. Jim. Thanks for joining Us. Way are here live in San Francisco's Howard Street for the Cube Special. Exclusive coverage of Oracle OpenWorld Q. Be right back with more of this short break. Thanks for watching.

>> wait. >> Okay, We're back. We are in Cambridge, Massachusetts. This is Dave Volante. I'm here with Jeff Kelly. Where with Wicked Bond. This is the Cube Silicon Angles production. We're here at the Mighty Information Quality Symposium in the heart of database design and development. We've had some great guests on Scott Hauser is here. He's the head of marketing at Adapt Company that we've introduced to our community. You know, quite some time ago, Um, really bringing multiple channels into the Duke Duke ecosystem and helping make sense out of all this data bringing insights to this data. Scott, welcome back to the Cube. >> Thanks for having me. It's good to be here. >> So this this notion of data quality, the reason why we asked you to be on here today is because first of all, you're a practitioner. Umm, you've been in the data warehousing world for a long, long time. So you've struggled with this issue? Um, people here today, uh, really from the world of Hey, we've been doing big data for a long time. This whole big data theme is nothing new to us. Sure, but there's a lot knew. Um, and so take us back to your days as a zoo. A data practitioner. Uh, data warehousing, business intelligence. What were some of the data quality issues that you faced and how did you deal with him? So >> I think a couple of points to raise in that area are no. One of things that we like to do is try and triangulate on user to engage them. And every channel we wanted to go and bring into the fold, creating unique dimension of how do we validate that this is the same person, right? Because each channel that you engage with has potentially different requirements of, um, user accreditation or, ah, guarantee of, you know, single user fuel. That's why I think the Holy Grail used to be in a lot of ways, like single sign on our way to triangulate across the spirit systems, one common identity or person to make that world simple. I don't think that's a reality in the in the sense that when you look at, um, a product provider or solution provider and a customer that's external, write those those two worlds Avery spirit and there was a lot of channels and pitch it potentially even third party means that I might want to engage this individual by. And every time I want to bring another one of those channels online, it further complicates. Validating who? That person eighty. >> Okay, so So when you were doing your data warehouse thing again as an I t practitioner, Um, you have you You try to expand the channels, but every time he did that and complex if I hide the data source So how did you deal with that problem? So just create another database and stole five Everything well, >> unfortunately, absolutely creates us this notion of islands of information throughout the enterprise. Because, as you mentioned, you know, we define a schema effectively a new place, Um, data elements into that schema of how you identified how you engage in and how you rate that person's behaviors or engagement, etcetera. And I think what you'd see is, as you'd bring on new sources that timeto actually emerge those things together wasn't in the order of days or weeks. It's on months and years. And so, with every new channel that became interesting, you further complicate the problem and effectively, What you do is, you know, creating these pools of information on you. Take extracts and you try and do something to munch the data and put in a place where you give access to an analyst to say, Okay, here's it. Another, um, Sample said a day to try and figure out of these things. Align and you try and create effectively a new schema that includes all the additional day that we just added. >> So it's interesting because again, one of the themes that we've been hearing a lot of this conference and hear it a lot in many conferences, not the technology. It's the people in process around the technology. That's certainly any person person would agree with that. But at the same time, the technology historically has been problematic, particularly data. Warehouse technology has been challenging you. So you've had toe keep databases relatively small and despair, and you had to build business processes around those that's right a basis. So you've not only got, you know, deficient technology, if you will, no offense, toe data, warehousing friends, but you've got ah, process creep that's actually fair. That's occurred, and >> I think you know what is happening is it's one of the things that's led to sort of the the revolution it's occurring in the market right now about you know, whether it's the new ecosystem or all the tangential technologies around that. Because what what's bound not some technology issues in the past has been the schema right. As important as that is because it gives people a very easy way to interact with the data. It also creates significant challenges when you want to bring on these unique sources of information. Because, you know, as you look at things that have happened over the last decade, the engagement process for either a consumer, a prospect or customer have changed pretty dramatically, and they don't all have the same stringent requirements about providing information to become engaged that way. So I think where the schema has, you know, has value you obviously, in the enterprise, it also has a lot of, um, historical challenges that brings along with >> us. So this jump movement is very disruptive to the traditional market spaces. Many folks say it isn't traditional guy, say, say it isn't but clearly is, particularly as you go Omni Channel. I threw that word out earlier on the channels of discussion that we had a dupe summit myself. John Ferrier, Hobby lobby meta and as your and this is something that you guys are doing that bringing in data to allow your customers to go Omni Channel. As you do that, you start again. Increase the complexity of the corpus of data at the same time. A lot of a lot of times into do you hear about scheme alight ski, but less so how do you reconcile the Omni Channel? The scheme of less It's their scheme alight. And the data quality >> problems, Yes, I think for, you know, particular speaking about adapt one of things that we do is we give customers the ability to take and effectively dump all that data into one common repository that is HD if s and do and leverage some of those open source tools and even their own, you know, inventions, if you will, you know, with m R code pig, whatever, and allow them to effectively normalized data through it orations and to do and then push that into tables effectively that now we can give access to the sequel interface. Right? So I think for us the abilities you're absolutely right. The more channels. You, Khun, give access to write. So this concept of anomie channel where Irrespective of what way we engaged with a customer what way? They touch us in some way. Being able to provide those dimensions of data in one common repository gives the marketeer, if you will, an incredible flexibility and insights that were previous, Who'd be discoverable >> assuming that data qualities this scene >> right of all these So so that that was gonna be my question. So what did the data quality implications of using something like HD FSB. You're essentially scheme unless you're just dumping data and essentially have a raw format and and it's raw format. So now you've gotto reconcile all these different types of data from different sources on build out that kind of single view of a customer of a product, Whatever, whatever is yours. You're right. >> So how do you go >> about doing that in that kind of scenario? So I think the repository in Hindu breach defense himself gives you that one common ground toa workin because you've got, you know, no implications of schema or any other preconceived notions about how you're going toe to toe massage weight if you will, And it's about applying logic and looking for those universal ides. There are a bunch of tools around that are focused on this, but applying those tools and it means that doesn't, um, handy captain from the start by predisposing them to some structure. And you want them to decipher or call out that through whether it's began homegrown type scripts, tools that might be upstairs here and then effectively normalizing the data and moving it into some structure where you can interact with it on in a meaningful way. So that really the kind the old way of trying to bring, you know, snippets of the data from different sources into ah, yet another database where you've got a play structure that takes time, months and years in some cases. And so Duke really allows you to speed up that process significantly by basically eliminating that that part of the equation. Yeah, I think there's and there's a bunch of dimensions we could talk about things like even like pricing exercises, right quality of triangulating on what that pricing should be per product for geography, for engagement, etcetera. I think you see that a lot of those types of work. Let's have transitioned from, you know, mainframe type environments, environments of legacy to the Duke ecosystem. And we've seen cases where people talk about they're going from eight month, you know, exercises to a week. And I think that's where the value of this ecosystem in you know, the commodity scalability really provides you with flexibility. That was just previously you unachievable. >> So could you provide some examples either >> you know, your own from your own career or from some customers you're seeing in terms of the data quality implications of the type of work they're doing. So one of our kind of *** is that you know the data quality measures required for any given, uh, use case various, in some cases, depending on the type of case. You know, in depending on the speed that you need, the analysis done, uh, the type of data quality or the level data qualities going is going to marry. Are you seeing that? And if >> so, can you give some examples of the different >> types of way data quality Gonna manifest itself in a big data were close. Sure. So I think that's absolutely fair. And you know. Obviously there's there's gonna be some trade off between accuracy and performance, right? And so you have to create some sort of confidence coefficient part, if you will, that you know, within some degree of probability this is good enough, right? And there's got to be some sort of balance between that actor Jerseyan time Um, some of the things that you know I've seen a lot of customers being interested in is it is a sort of market emerging around providing tools for authenticity of engagement. So it's an example. You know, I may be a large brand, and I have very, um, open channels that I engage somebody with my B e mail might be some Web portal, etcetera, and there's a lot of fishing that goes on out there, right? And so people fishing for whether it's brands and misrepresenting themselves etcetera. And there's a lot of, you know, desire to try and triangulate on data quality of who is effectively positioned themselves as me, who's really not me and being able to sort of, you know, take a cybersecurity spin and started to block those things down and alleviate those sort of nefarious activities. So We've seen a lot of people using our tool to effectively understand and be able to pinpoint those activities based upon behavior's based upon, um, out liars and looking at examples of where the engagement's coming from that aren't authentic if that >> makes you feel any somewhat nebulous but right. So using >> analytics essentially to determine the authenticity of a person of intensity, of an engagement rather than taking more rather than kind of looking at the data itself using pattern detection to determine. But it also taking, you know, there's a bunch of, um, there's a bunch of raw data that exists out there that needs you when you put it together again. Back to this notion of this sort of, you know, landing zone, if you will, or Data Lake or whatever you wanna call it. You know, putting all of this this data into one repository where now I can start to do you know, analytics against it without any sort of pre determined schema. And start to understand, you know, are these people who are purporting to be, you know, firm X y Z are there really from X y Z? And if they're not, where these things originating and how, when we start to put filters or things in place to alleviate those sort of and that could apply, it sounds like to certainly private industry. But, I mean, >> it sounds like >> something you know, government would be very interested in terms ofthe, you know, in the news about different foreign countries potentially being the source of attacks on U. S. Corporations are part of the, uh, part of our infrastructure and trying to determine where that's coming from and who these people are. And >> of course, people were trying to get >> complicated because they're trying to cover up their tracks, right? Certainly. But I think that the most important thing in this context is it's not necessarily about being able to look at it after the fact, but it's being able to look at a set of conditions that occur before these things happen and identify those conditions and put controls in place to alleviate the action from taking place. I think that's where when you look at what is happening from now an acceleration of these models and from an acceleration of the quality of the data gathering being able to put those things into place and put effective controls in place beforehand is changing. You know the loss prevention side of the business and in this one example. But you're absolutely right. From from what I see and from what our customers were doing, it is, you know, it's multi dimensional in that you know this cyber security. That's one example. There's pricing that could be another example. There's engagements from, ah, final analysis or conversion ratio that could be yet another example. So I think you're right in it and that it is ubiquitous. >> So when you think about the historical role of the well historical we had Stewart on earlier, he was saying, the first known chief data officer we could find was two thousand three. So I guess that gives us a decade of history. But if you look back at the hole, I mean data quality. We've been talking about that for many, many decades. So if you think about the traditional or role of an organization, trying tio achieved data quality, single version of the truth, information, quality, information value and you inject it with this destruction of a dupe that to me anyway, that whole notion of data quality is changing because in certain use, cases inference just fine. Um, in false positives are great. Who cares? That's right. Now analyzing Twitter data from some cases and others like healthcare and financial services. It's it's critical. But so how do you see the notion of data quality evolving and adapting to this >> new world? Well, I think one of these you mentioned about this, you know, this single version of the truth was something that was, you know, when I was on the other side of the table, >> they were beating you over the head waken Do this, We >> can do this, and it's It's something that it sounds great on paper. But when you look at the practical implications of trying to do it in a very finite or stringent controlled way, it's not practical for the business >> because you're saying that the portions of your data that you can give a single version of the truth on our so small because of the elapsed time That's right. I think there's that >> dimension. But there's also this element of time, right and the time that it takes to define something that could be that rigid and the structure months. It's months, and by that time a lot of the innovations that business is trying to >> accomplish. The eyes have changed. The initiatives has changed. Yeah, you lost the sale. Hey, but we got the data. It would look here. Yeah, I think that's your >> right. And I think that's what's evolving. I think there's this idea that you know what Let's fail fast and let's do a lot of it. Orations and the flexibility it's being provided out in that ecosystem today gives people an opportunity. Teo iterated failed fast, and you write that you set some sort of, you know confidence in that for this particular application. We're happy with you in a percent confidence. Go fish. You are something a little >> bit, but it's good enough. So having said that now, what can we learn from the traditional date? A quality, you know, chief data officer, practitioners, those who've been very dogmatic, particularly in certain it is what can we learn from them and take into this >> new war? I think from my point of view on what my experience has always been is that those individuals have an unparalleled command of the business and have an appreciation for the end goal that the business is trying to accomplish. And it's taking that instinct that knowledge and applying that to the emergence of what's happening in the technology world and bringing those two things together. I think it's It's not so much as you know, there's a practical application in that sense of Okay, here's the technology options that we have to do these, you know, these desired you engaged father again. It's the pricing engagement, the cyber security or whatever. It's more. How could we accelerate what the business is trying to accomplish and applying this? You know, this technology that's out there to the business problem. I think in a lot of ways, you know, in the past it's always been here. But this really need technology. How can I make it that somewhere? And now I think those folks bring a lot of relevance to the technology to say Hey, here's a problem. Trying to solve legacy methodologies haven't been effective. Haven't been timely. Haven't been, uh, scaleable. Whatever hock me. Apply what's happening. The market today to these problems. >> Um, you guys adapt in particular to me any way a good signal of the maturity model and with the maturity of a dupe, it's It's starting to grow up pretty rapidly, you know, See, due to two auto. And so where are we had? What do you see is the progression, Um, and where we're going. >> So, you know, I mentioned it it on the cue for the last time it So it and I said, I believe that you know who do busy operating system of big data. And I believe that, you know, there's a huge transition taking place that was there were some interesting response to that on Twitter and all the other channels, but I stand behind that. I think that's really what's happening. Lookit. You know what people are engaging us to do is really start to transition away from the legacy methodologies and they're looking at. He's not just lower cost alternatives, but also more flexibility. And we talked about, you know, its summit. The notion of that revenue curve right and cost takeouts great on one side of the coin, and I are one side of the defense here. But I think equally and even more importantly, is the change in the revenue curve and the insights that people they're finding because of these unique channels of the Omni Challenge you describe being able to. So look at all these dimensions have dated one. Unified place is really changing the way that they could go to market. They could engage consumers on DH that they could provide access to the analyst. Yeah. I mean, ultimately, that's the most >> we had. Stewart Madness con who's maybe got written textbooks on operating systems. We probably use them. I know I did. Maybe they were gone by the time you got there, but young, but the point being, you know, a dupe azan operating system. The notion of a platform is really it's changing dramatically. So, um, I think you're right on that. Okay. So what's what's next for you guys? Uh, we talked about, you know, customer attraction and proof points. You're working. All right on that. I know. Um, you guys got a great tech, amazing team. Um, what's next for >> you? So I think it's it's continuing toe. Look at the market in being flexible with the market around as the Hughes case is developed. So, you know, obviously is a startup We're focused in a couple of key areas where we see a lot of early adoption and a lot of pain around the problem that we can solve. But I think it's really about continuing to develop those use cases, um, and expanded the market to become more of a, you know, a holistic provider of Angelique Solutions on top of a >> house. Uh, how's Cambridge working out for you, right? I mean, the company moved up from the founders, moved up from New Haven and chose shows the East Coast shows cameras were obviously really happy about. That is East Coast people. You don't live there full time, but I might as well. So how's that working out talent pool? You know, the vibrancy of the community, the the you know, the young people that you're able to tap. So >> I see there's a bunch of dimensions around that one. It's hot. It's really, really hot >> in human, Yes, but it's been actually >> fantastic. And if you look it not just a town inside the team, but I think around the team. So if you look at our board right Jet Saxena. Chris Lynch, I've been very successful. The database community over decades of experience, you know, and getting folks like that onto the board fell. The Hardiman has been, you know, in this space as well for a long time. Having folks like that is, you know, advisors and providing guidance to the team. Absolutely incredible. Hack Reduce is a great facility where we do things like hackathons meet ups get the community together. So I think there's been a lot of positive inertia around the company just being here in Cambridge. But, you know, from AA development of resource or recruiting one of you. It's also been great because you've got some really exceptional database companies in this area, and history will show you like there's been a lot of success here, not only an incubating technology, but building real database companies. And, you know, we're on start up on the block that people are very interested in, and I think we show a lot of, you know, dynamics that are changing in the market and the way the markets moving. So the ability for us to recruit talent is exceptional, right? We've got a lot of great people to pick from. We've had a lot of people joined from no other previously very successful database companies. The team's growing, you know, significantly in the engineering space right now. Um, but I just you know, I can't say enough good things about the community. Hack, reduce and all the resource is that we get access to because we're here in Cambridge. >> Is the hacker deuces cool? So you guys are obviously leveraging that you do how to bring people into the Sohag produces essentially this. It's not an incubator. It's really more of a an idea cloud. It's a resource cloud really started by Fred Lan and Chris Lynch on DH. Essentially, people come in, they share ideas. You guys I know have hosted a number of how twos and and it's basically open. You know, we've done some stuff there. It's it's very cool. >> Yeah, you know, I think you know, it's even for us. It's also a great place to recruit, right. We made a lot of talented people there, and you know what? The university participation as well We get a lot of talent coming in, participate in these activities, and we do things that aren't just adapt related, that we've had people teach had obsessions and just sort of evangelize what's happening in the ecosystem around us. And like I said, it's just it's been a great resource pool to engage with. And, uh, I think it's been is beneficial to the community, as it has been to us. So very grateful for that. >> All right. Scott has always awesome. See, I knew you were going to have some good practitioner perspectives on data. Qualities really appreciate you stopping by. My pleasure. Thanks for having to see you. Take care. I keep right to everybody right back with our next guest. This is Dave a lot. They would. Jeff Kelly, this is the Cube. We're live here at the MIT Information Quality Symposium. We'LL be right back.

>> Wait. Okay, We're back. Live here at Stanford University Alumni Center. What a great day. Stanford loved this place. A lot of brilliant minds here. And this is the Stanford Excel Seventeenth annual symposium called Excel Enterprise. That's the hashtag falls on Twitter here with Jeff Kelly. Silicon angles. Exclusive coverage is too cute. Our flagship program about the events extract the signal from the noise. And our next guest is Amanda Richardson, the head of product. That president. Welcome to the Cube. >> Thank you. Awesome. >> So really amazing event. I'LL see a lot of big minds here, and we're also live in San Francisco at the age of us somewhere all the developers air geeking out with Amazon and all the tools you the head of product President, tell us what is President. Tell us what you're doing here. >> So, President, a collaborative presentations will. So we look forward, Teo, helping our users create idea, share ideas and really have a platform for uh, putting. Their message is out there and better sharing with the audience is So we're here because we love excel. I'm here because I'm a GSP alum and any reason to get back to the farm is a good one, and we just think it's a great place to meet people piers and share ideas and hopefully learn from each other's mistakes. >> So what? You're the new business school president? >> So I got you a job before the new business school. It's pretty awesome, but I kind of want to go back. I was joking with my husband this morning. I think it may be time for a phD. >> Yeah, Sanford's Grace, but as the head of product, you can. You still get the geek out? >> Yeah, >> And look at also the market side. You gotta look into engineering also product. So in this whole enterprise two point Oh, thank you just never happened. It's still happening. It's like going and going. But now with cloud with mobile, it's all happening right? So I got that cloud mobile social thing going on. We've been covering. So knowing it's looking angle. What are you seeing now as the market drivers for those two forces cloud and mobile and social is all that coming together? >> Um, it is all coming together, and I think you know, we call it like the consumerism ation of enterprise. Right. So, um people have one phone, one device, one presence. I think five years ago you probably tried to keep your world separated between your enterprise, professional life and your personal life, and now it really all comes together. So you've gotta solve the problems for the enterprise users in the same way you solve problems for consumers, right? What are their big needs? What are their pain points? Where do they find value, focus on those areas and make it easy to use on DH? I think that's what's finally accelerating on bringing really cool, sexy problems to the enterprise users. You just bring a consumer approach. One >> of the biggest barriers that you see in that adopts House of consumer ization of consideration of the enterprise has been talked about for many, many years and finally was seeing a ray of hope. >> Yeah, wave and making the lives the end of the tunnel >> sunrise a face. So it's there, it's there. So one of the key drivers that are helping this go faster now versus years before Oh yes, next two years next year. >> Um so I think I think mobile is actually a great point, so you can't keep pieces like Evernote, Dropbox President out of your users hands. I mean, I remember being in meetings with manager meetings five, seven years ago, talking about how we're gonna ban Facebook, and that just seems quaint now because it's all in your phone and you can't tell people not to bring their phones to work. So I think Mobil's had a huge impact and getting more of these products and tools into the hands of the consumers and out of really this kind of big brother control type situation, Thie Other thing I think that's happening is just worlds are blending together and the availability of of tools on the Internet. It sounds silly to say, but, you know, you can remember five, ten years ago, you couldn't access your perhaps it's near p program. Or perhaps this even productivity tools from home. There was a time when we all had to remote in and yeah, I mean, I'm dating myself and showing why I color my hair. But it really is. You know, the world is changing, and I think, thank goodness for the Internet, thanking us for the Web and thank goodness for >> Mo. It's interesting you mention the dating yourselves first. You look fabulous, you know, you know world. I mean, I'm older, I know how old I am. And I just had the twenty seven year old kid on drop box. So you know, that's young. But, you know, it's a lot of senior folks now. This enterprise market is shifting from consumer. You seeing some of the leaders are those experienced managers because they've lived through the right client server that lived through the that first wave. So is that just because we're more, there's more people that know that market more amusing? You're seeing a lot more cos they're not not the twenty something. It's over thirty five over forty. >> Yeah, eso no comment on age. But Thea, I think what excites me about the space I can just talk about myself is you know, I have a consumer background. So it was super fun to be in consumer five ten years ago when you know Internet was taking off. He finally have a platform on which you have millions of users to test and learn and grow. And now that you can apply that to enterprise, I mean, I think it's new challenges but similar challenges. And I really think one of the more interesting things is that it's actually solving really compelling problems. One of the you know, um, I think there are a lot of opportunities out there around photo sharing and, um, Geo location and, you know, putting together your social graph. But you know, where I find passion and energy is actually providing value and solving problems and really being a key part of someone's someone's life, That's what gets me here. Hope that keeps others here. >> So let's talk about you're solving really interesting problem. What is the mean? What is your wife? What is president about? Why are you doing what you're doing? Is it simply, you know, we've talked. We hear a lot about the concerns around power point and right death by the PowerPoint slide and that kind of thing is that really, uh, the issue you've set out to overcome our tell us a little about what you do and why you do it. >> So, um, we certainly get compared to power point a lot, but where we, uh problem we really like to solve on on a more grand scale is that we believe ideas are best shared and best collaborated about. So if you think of ideas like jeans, they can come together. They can be built on each other. A great example of president uses. There is an organization in Syria rebel organization that used President to really be the platform to explain their ideas and what the issues really were in a quick, meaningful, impactful way. I think having a platform by which you can share ideas and better understand each other can apply Teo making the world a better place but can also apply Teo helping scientists share their information around the globe, building on ideas and I know even within president, we use the tool. Teo better communicate product road maps to engineering so that we can better align. I think it's all about communication. Helping ideas grow faster and helping the world to be a more understanding place. I mean, it's a little peace, love and happiness, but it it is why we get out of bed every morning. We really think because he's a great tool for people to be the platform for them to share their ideas. And >> so I'm actually president User. I've started using recently. Actually, I downloaded. You can see here about the kind of downloaded the desktop version, and I were working on the plane that was coming out here from Boston. But, you know, it's certainly a very interesting platform. It's very different from Power. Point certainly creates much, much more compelling type of way to present information. Uh, what are some of the design principles that's had a product? What are some of the things that you really kind of court your philosophy in terms of design, find it and and implementing our should say, creating the kind of user interface and the way people interact with information? >> Yes. So I'm really proud of President of the co founders have really doubled down, if you will, on our design effort. So we have a full time user research staff. We have a full time data research that we have a full time design staff, all three different roles, all three big teams. I'm really focused on understanding our users. So we saw for key user problems in terms of design principles, specifically that we focus on, we like to, uh, help users understand structure of their ideas. So one of the challenges of President. For those who come from a power point model is everything should be linear. And one of our principles is that not all ideas are linear. There may be areas where we consume into different pieces. So helping to communicate that that is particularly important for us and how to provide simple structure. Um, I think the other ideas, uh, helping to make it beautiful. We believe that words are better. What are? Excuse me? Pictures are better. Way to communicate in words. Um, you know, death by bullet point >> thing is a common affliction, >> eh? So how can you, uh, say something with a picture that would have taken a hundred words? And that's what we try to do. >> So you know what? Your problem is? Both kind of software service, but also down with stop version. Right? Mentioned. But you know what? The software service Mom, you're able, I assume, to collect data on the way people are using your product, right. How does kind of that type of information do you incorporate that into the design process and making changes to the product come to talk about how you used data analysis really >> product. Yeah. So, you know, I believe the role of product managers to understand the user intimately have a point of view on a strategy, but then early validate through data. So not to Pripyat. We do have data about your desktop PC, which is what >> I covered. Big data for what? You have no problem with that. >> So we focus a lot on one or user stew. Do what makes them successful way try toe. Have measurable outcomes for all of our initiatives, whether its user behavior or defining what a good presidents are really helping users to solve their problems. We use data tio, on the small level, optimized and on a big level really define an objective and a goal. So how can we really push things through the funnel to get to the user to their success point, which we measure is giving a presentation. >> So both find ten of tactical issues, but also a kind of inform your larger >> are big company KP eyes. They're all based on data. >> Okay, thanks for coming on The tears. We gotta break that. Their next guest coming in lining up all of the crowd's breaking up the Silicon Angles Exclusive coverage of Stanford Excel seventeen Annual symposium. Hashtag Excel Enterprise Where it sells Doing a lot of great enterprises is Cuba's looking angles. Coverage of Stanford Excel Symposium right back with our next guest after this short break.

>> wait. >> Okay, We're back. Live a V M. World twenty twelve. I'm John for the founder's silicon angle dot com. This is the Cube silicon angle dot TV's flagship telecast. We go out to the events and extracted signal from the noise CEOs, entrepreneurs, analysts, marketing people, developers, whoever has the signal, we want extract that share that with you. We have a special guest today. Frank's Leutnant is a sea of service. Now again, I'm John Furry. I'm joined my co host >> of Dave Alonso, a wicked bond dog. Frank, Last time we saw Europe on the stage, you had these glasses on the hat. Remember that, Elwood? So, uh, welcome to the Cube. First time on Thank you. Too many of'Em worlds. I'm sure. A little different angle now. Yeah, Service now. Very exciting. Just went public solving a big problem on DH. Added again? Yes. So tell us. How do you feel? >> That's interesting. A lot of people ask me, how did you end up in, you know, in a in an application software tap a category you spent all this time in storage. The reality is that most of my life, you know, being in the application, development, dusting and system management. So this is actually close to my wheelhouse. Stories was actually a pretty good diversion for me. Careerwise >> service now, relatively, you know, not not a household name but solving that problem. Really, There's no system of record for i t. What activities air doing? Whether it's finance, it's whether it's application portfolio project portfolio. You guys were attacking that whole nut with a software service model. I mean, it used to be a lot of point tools to do that. And you guys seem to be having a lot of success bringing that all to the cloud. >> Yeah, the irony is, is that you look at all the corporate functions, you know, finance, sales, marketing HR, I sort of ranks, you know, last or near last in terms of management sophistication, right compared to the other functional areas, because the most mighty organization have to show for themselves. They helped US management system for their work. For right now, they are to keep track of what's running in their their operation, and that service model is typical of infrastructure providers. Right? You see it, you know, with tell coast like looking t you see it with power. You tell these, like PG and E their infrastructure providers first and the service model. It is not particularly compelling, right? So what we tried to dio it's really take it from a D M V style service model standing in line waiting to be helped. Do you want this more like amazon dot com, where I help myself, It's into it. If it's online, it's productive. It's where I want to go. Teo to make requests as well. Let's receive service >> So you're selling primarily to the organization. Who you sell to in the theory is that the CEO is that the project management offices all the above >> as the servicers management is a very well defined center of responsibility in i t organization. So there's always a group of people who is in charge of that that disciplined. They're easy to find, But CEOs are always involved, and the reason is these air very high profile system rollout because everybody in it is an actor or participant, the workflow as well as the broader employee population, the enterprise, touchy systems, So you better believe that people are sensitive about this being a successful practical and it looks more like a neo system. Dan. It does an infrastructure type system >> without the AARP complexity of it. >> Yes, it's it's a mixed >> metaphor, but so So here are your roughly a hundred fifty million dollar company, you know, annualized, you nice market. >> Either way, we've we've guided to about two. Thirty five, >> thirty five this year. Okay, Great. That's >> want to make sure that their investors don't get >> background. We're sorry about that. Es to thirty five, which is why your market cap about three point six billion. I think >> way had about ninety eight percent growth and buildings in the last quarter. So the high growth, obviously it's what drives >> what's driving that. So how big is the business that you guys playing? What's your tan? >> So we think that the tam just for the narrow definition around service management is a is a multi billion dollar opportunity Because of the nature ofthe work flows, we're also expanding into the operations management area. Right? This is this is where HP lives and BMC and IBM and CIA with these very large open view Tivoli Well, because their work flows between services system management are all becoming integrator that used to be suffered spheres. Not anymore. >> And that's an enormous market. >> It i d. C. Thanks. It's about a thirteen fourteen doing dollar market, and then you have the platform is a service opportunity because our customers have just gone wild, building all kinds of spoke applications on a platform just because they could. So >> you kind of betting on the intersection of systems management, operations, management >> and the platform. >> Okay, and it's kind of jump ball, really, with the dynamic of the cloud coming in, isn't it? In terms of the competitive, it's >> Ah, it's interesting because we look another assassin categories like HR marketing. You see a whole host of players you're looking in our category on the only breakout play there has been serviced now way have predominately compete against legacy vendors, people that I just mentioned. So >> you've got some experience doing that I want >> I want to ask you about the discipline side of the market. You guys are public companies, so yeah, you're out there is all exposed and then talk about some of the product directions because out yesterday they were really showcasing the vision within VM where old way a new way, a access APS infrastructure. You know the classic in the old way. New Way, Modern era. We've been calling it in your world. You're actually replacing some pretty old stuff. I mean, I remember back in the late eighties, early nineties health testing people had that's headsets on and, you know, homegrown software developers and quit a lot of this legacy kind of mindset. So first question is, Is that true? Is there still that much baggage in that services business? From an infrastructure standpoint? And the second part, the question is, what's the new stuff that's really disrupting the market? So in the new way, what is the key features that that's happening in the services industry? >> So, you know, I already started to allude to it, right. So you want to evolve that service model from that help death centric DNP style of service experience to one that's on the line looks more consumer style. You know, the way we've learned from Apple and Yahoo and Google and people like that help yourself. If you have a problem at home with your apple TV, you're really gonna try and call Apple know you're going to go online and you find years of communities you get Teo answers ten times faster, that weight and then following these needy old models the way you reference there is an awful lot of that still living in the world off because they're focuses infrastructure, not service. That's change it, right? I mean, CEOs, I read somewhere, have a shelf life of about eighteen months, right? There's incredible impatience and dissatisfaction with how that function is running. It's costing too much money in the service is not exactly to to write home about. People are really ready to move their service malls. >> The largest answer was, Just hire someone else to do it. That was the outsourcing boom, right? So that's still brought problems, right? Legacy. So how is that still in play? So if the notion is okay, outsource it, and then the outsources has some warts on it that's got to be tweaked. What's the new version? Because you know amazon dot com and you know this new environment availability, instant access, the information we don't service etcetera is that changing it >> way believed that the move to cloud computing is really going to change the role of the CIA, all right, because infrastructure is going to become something that's behind Courtney, and it's becoming less of an infrastructure centric job. CEOs and T organizations become Mohr service engineering organizations, people that understand work flows. People understand how to automate work, flows right out. And, you know, I know how to run a database or a network or, you know, all the security dimensions and so on because we're just breaking as an industry. There just isn't enough competency and skill sets for everybody to be confident at the level that we need to be at structure. It's not scaling, right. It's sort of the way telephone switching centers were in the nineteen fifties >> means one of those things to with the CIA. Attention, I'LL get to that later. But now, with big data in real time analytics is more pressure on the service delivery side. As a business driver, you seeing that pressure as well, or is it more? We just gotta fix it now. I got to do it >> Well, nighty organizations in the lift from one crisis to the next, completely event driven, you know we haven't out its were all over it. Trying to restore service on DH. You know, we sort of live that life day in, day out. But I've never changes right So waken get ahead of this game. You know, if we start structuring, you know, the interaction model that we have with our users how we communicate with them. I mean, simple things, right when you were, you haven't out it. It would be helpful if we were able to pull status. You know, every twenty minutes us to what? What we're doing, What's going on. Right? But having infrastructure be ableto push data out? No, like that. Most organizations don't do that. They live pretty much in the dark, >> so share with our audience out there. That's watching. We have a lot of professionals and data scientists and analyst type audience that we've that we've that follows. Looking angle with Yvonne on DH. Some CEOs as well on early adopters share the folks out there. The pitch, How bad is it that their environment and how easy is it to change? It is just a norther. A magnitude sense of is a turnkey. How do you guys roll in? What's he engagement look like? It's not as hard as the things that most people might have the opinion. I don't want to get just ugly. It's painful or is it not painful? Is it quick pop now? Is it like how fast a roll in and out the infrastructure that you >> the's are extraordinarily sticky systems the system that were that we replace >> your systems of the old systems. >> The old systems are on the reason that they've been around for ten, fifteen years. They're very difficult to replace. And if you look at our girls, that's certainly testament to our compelling. The value proposition has been people have said, you know, a pain is becoming unbearable and be the view of the promised Land is looking pretty good, right? So there's both an incentive to change and to move, and secondly, there is something to move towards that is this compelling inspiring. And it really is going to change my game right, because now we tell people said, Look, if you just tryingto get to a snazzier, more modern help desk, we're not your guy, okay? Because we don't find out a compelling vision of the world. We wantto wholesale transform how you deliver service just >> take us to some of those cats you were talking before you came on about your growth tripling inside. But talk about a zoo company, which is a whole nother conversation. We could talk about it yet you have expertise in, but talk more about the customer deployments. You got some fresh funding with the AIPO. You're geared up. You go out to the market place. What are the conversations like, What are some of the stats and one of the conversation with the CIA? >> Well, the CIA is obviously are interested, first and foremost of the transformation of the service model, right? I mean, we have to get Teo service experience that's more reminiscent of people experience on the consumer side. Now we typically have to do that, that an economic equation that's very similar to what they're having right now. They're not interested in spend more. They just want to get completely refreshed, you know, platform for similar amounts of money that they're already spending because Versace, you know, we're not just taking the software, not off the after after table. We're also taking the entire infrastructure, all the operating staff, everything it takes to run that environment becomes ours, right? It's no longer in the I T department, so that looks pretty compelling to them. >> How about some of the numbers in terms of uptake with customers recently? What's the growth rate was? Can you share some numbers? >> Way have about twelve hundred price customers? We had about one hundred twenty seven the last quarter. That's that is a huge number of customers. Tio Tio ad we have. Most of our focus is on global two thousand enterprises. We have about two hundred thirty global two thousand enterprises, and they're all you know who's who names that, that people recognize Starting up Ticket's been been strong. We're running very, very hard to make sure that we have two services infrastructure. Both there's people and infrastructure to be able to accommodate that. >> Well, I'm excited to interview you because I want to ask you kind of more of a personal question. And although we just met for the first time here, your name's been kicked around as kind of a maverick operational executive who knows how to scale organization. So we're in kind of living in an era where the business value focused, whether startups and has been a lot of talk about, you know, the Facebook idea, the young kids under thirty running a billion dollar market gap, companies trying to actually move from hyped to real scale. And Palmer. It's made a comment yesterday kind of dissing Facebook of in terms of the value proposition relative to say, you know, bm where. But the question I want to ask you is, um, what's your success model for scaling an organization on DH for the younger execs out there? And for people who don't know you just chairs up on the camera? What's your philosophy as the repeatable sales, lower cost leverage model? I mean variety of different kind of ingredients. What's the Franks Lukman formula for success and scaling? Bringing a product to market and growing it? >> Well, the first order of business for for a start up venture of any sort is growth. I find that a lot of people come on a business school in trying to balance girl for profitability. Um, that mentality makes no sense to me, right? It's economics. Before accounting, accounting becomes the bastardization of economics, we run our ventures cash on booking their economic concepts, not accounting constructs, right people are trying to show profit prematurely when they can invest that money to grow. We tripled our head count over the last year. We got very far over our skis. No, we're burning a hole in our gas pals but were very clear with investors that look, we are still increasing our productivity for head. Why, when we apply to resource is to grow this franchise Growth expands our multiples, expands valuation. That's what everybody is in the business for, so so sort of summarize. Knowing your question. Most people hold back on growth, and they don't really know why they're not all out trying to drive growth and the reason that growth is so important. You need to be a breakout player. Nobody wants to be the in between player. That's neither fish nor fowl and doesn't become a dominant entity into space that it wants to be in >> and have the financing in the dry powder behind you that you were a venture capital Greylock, which no something into about investing. So that's also important part right? >> Well, you don't. That's why I said to you manage on cash you managed on bookings. Those are the economics in the business essentially, >> and you've been looking up, have some really good finances behind you, trust you who get the concepts and that's key well, continue in the right >> way went public. We also explain to investors Look, this is what we're trying to do, and this is what we need you to buy into. Otherwise, find somebody else's talk. So >> what is the going public affect? You know the perception amongst the CEO's when you chose to list on the way we had them on earlier this week? But how is that affected? The brand perception? >> That was the whole reason for us to go public, right? We didn't need to cash liquidity. Obviously, it's good for employees and investors when I pose fundamentally a branding event. You know, I used the analogy. We went from playing on Saturday to playing on Sunday. You know, all of a sudden you know you're transparent, you know, all the all the thud that gets spread about you by competition. People cannot punch you up on Iand. See what the truth is around your balance sheet. You know how abot your last quarter was? It's been three. I po was tremendous for us from a branding standpoint, >> and you've been known Teo have a reputation of really getting the product in this case, the service, right? And then really getting aggressive on the sales side. Can you talk about what you've done in the sales side? I know you've aggressively hired. >> Yeah, we You know, as I said, we tripled our head count. We went from three shells. Reasons to twelve insight. One year we spread out all over Europe today. This is a ground war. You need an army to fight it. This is not Facebook. We cannot sign up annoying people in a week. It is a business that runs over the ground so you cannot scale and drive growth business unless you have two people to run it. >> And you're selling belly to belly. That right? Absolutely. So you know, >> we're going through the front door of the elevator >> way. Okay, We're getting the hook here. We're getting hooked, but I have to quit final questions. One is just put a plug out there for service's angle dot com that Silicon Angles separate publication. We launched last year, thanks to E m. C. For helping us sponsor that but really dedicated to the new era of services. And there is some disruption. We're excited to cover you guys, so I just wanted to say Go, go check out sources angle. So Franklin asked two questions. One. What's the big disruption in the services business that most people aren't getting right now? General, you know, man and tech on the street, not the insider inside the ropes. So that's the first question. The second question. What's your goals for the year? For the business? >> Well, the interesting thing about the services business is how it's one of these areas that is sort of the least automated. Write. It runs on the concept of institutional knowledge. Phone conversations, informal communications, email and the frontier in service management is that those become software automated structure processes that is not just happening in I t able sticks. It's happening everywhere, right? What do you want to request? Food. You know, from the hotel you knew what a Virgin America, right? You know, request from your seat, something that's just, you know, on an example of how >> that's the story, you know, debate about that. >> That's how it's gonna go, right? So services it's going to become, really that I call the service fabric right? Essentially how thes processes get conducted. So we're super excited because our platform sits right in the middle of that trend and we're going to try and make that trend. >> It's eleven. Platform to the economics are fantastic and no real customs agents were brought up exactly so good margins. >> And it's just >> like the stock immediately. >> It's much more scalable in the district. Disintermediation. You know, all the all the manual effort goes into this. >> Okay, so now I know your public CEO and everything now, so you really can't be as wild as you could have you a private. But what's the outlook for year? Your personal goals for the year >> Wait, given guns from or get one quarter for years. So check with your favorite analysts. >> Okay? Growth is on the horizon. Congratulations. Frank's been great to have your leadership in the Cube. Thank you. Time Cuban great to have you. This is silicon angle dot coms. The cube will be right back with our next guest, Cynthia Stoddard from Netapp CIA, Another CIA. We're gonna get into the trenches and hear about the transformation again. We'LL be right back