(upbeat music) >> Okay, welcome back everyone to theCUBE's coverage of AWS re:Invent 2021. We're here live in Las Vegas for an in-person event. Of course, it's a hybrid event, virtual online. Many people online. A lot of people here on the event, a lot of action. cloud going next generation, mainframe transformation, more analytics, more chips, everything's faster and cheaper and getting better and better in the cloud. We've got the great coverage. We've got two great guests. We got Justin Hooper vice president of Global Operations Infrastructure Ingram Micro and JP Perot, EVP of Telecom Media and Technology and AWS executive sponsor for Atos. Gentlemen, thank you for joining me on theCUBE. >> Thank you. >> Thank you, glad to be here. >> So what is it about the conference so far? Pretty good, like a lot of people here? >> Super exciting. >> 27,000 people showing up. >> It's amazing. >> Real people not workers. >> Yeah, it feels almost normal. >> Yeah I can't believe the turnout. >> Got a great topic, you guys working together you got mainframe, you got analytics, transformation. Let's get into it. Let's start by introducing what you guys do, your company, and why you are here. JP, we'll start with you. >> Yeah, I can start. Okay, so yeah, so I'm leading, you know, in Atos all the cloud business and telecom media technology, Atos is a big company is a service and technology company, 11 billion Euro business, and we are leading all the transformation to cloud and also, all what is related to hybrid cloud transformation. Also with security. We are number two in the world in terms of security and cybersecurity. We have developed for so long lasting relationship with AWS. We have been an advanced technology partner of AWS for now many years, since 2013. And we have developed a specific program, you know, regarding manufacturing transformation and mega trends. So this is why we are super excited to be here with you Justin today, thank you, by the way having Ingram Micro with us, Justin. >> I appreciate it, it's good talking to you. Good to be here. >> And I'm Justin Hooper, I work for a Ingram Micro. I run their Global Infrastructure and IT operations. Ingram Micro is one of the world's largest technology suppliers, technology solutions, and cloud platform and services. >> Well, great for the intro. Thanks for that set up, a lot of action going on. You guys have recently purchased, you guys got the transformation in the cloud. What is the movement to the cloud? Take us through the current situation. >> Yeah, we see, a big acceleration and especially due to COVID situation. We have seen acceleration of transformation to cloud. There is a lot to do, a lot to do because many business critical application, which have not been transformed. And also, especially all the applications which are sitting on top of mainframe that is why executive discussion we are with Ingram at the moment is how we can help Ingram with some of the applications that are on mainframe to transform and design the future. >> Justin, take us through the transformation that they're helping you with, what's the key challenge? What problem are they solving? Take us through the specifics. >> Yeah, it's interesting because I'm actually a lover of the mainframe, I think most of the people at AWS would think, the mainframes, didn`t they put the rockets on the moon. That's old technology, but mainframes are still fantastic platforms. We, have great success, great resiliency with Atos . We are on the most modern chips, but there are a lot of restrictions. You know, you really have to size your mainframe for your peak workloads. You don't have the ability to separate segments, scale horizontally, and then there are really nuanced. Like it's hard to get resources that know mainframes, to be honest with you, it is just, there's a people issue there industry-wide, and we're not different than any other company and compete for resources, both on the system side and on the programming side. And we really want to look at how we can make a massive leave, if we're going to leave the mainframe, how do we start a journey where we can end up really being able to take advantage of horizontal scalability, the ability to have a utility compute model where we're really paying as we go, because that is the opposite how the mainframe model works today. >> Talk about the refactor 'cause I know I've covered a lot of mainframe stuff with IBM in the past and how banks are still using it. Everyone is they're real applications. They're mission critical. How are they integrating into the digital transformation. Containers, kubernetes are hot right now. You're starting to see a lot more integration. How do your customers and how do you guys see refactoring happening? I can see the integration, but that as the refactoring come in. >> There's really what we've learned with our partnership is there are really a couple of ways to do the refactoring. You can convert your old Cobalt code to something else like Java. And there are tools and companies out there that do that. Or you can really build a plan where you can effectively emulate your mainframe on commodity computing and through a relatively deep analysis with Atos, the recommendation that we're looking at is that ability to first get off of the hardware, get off of that reliance on the platform, but not jump all the way to modify your code to Java. There's not a lot of value in going from Cobalt to Java, for example, if you're not making improvements in your programs, adding business capabilities. So the journey starts with get off the hardware, but then it allows you to go and say, we are going to break up those complex programs. We are going to separate the data differently. And once you do that, you can start to take advantage of containers and start to separate yourself even more and really get into the cloud. But, there are ways to piece your way through that. >> You know that's really good insight, JP, I'd love to get your reaction on this too, because what Justin's getting at is what we hear a lot from experienced CIOs of large companies that have a lot of existing stuff. And the theme is and the word they use is you don't want to touch the white hot core. Meaning it's so mission critical that if you mangle it too hard, touch it too hard a lot of bad things happen. So this idea of push things out to the cloud that around the edges, and then work your way slowly in is a risk management and practical approach. >> Not exactly, you said it right, its exactly a risk management So, and Justin explain it different factors, which come to the end point in terms of decision there is one issue regarding competencies, because their lack of competency in the markets. There is what kind of business critical apps you have. There is a transformation as such, you know, as Justin explain you can record, or you can move, you know, to a different platform. So, each time it's a program, it's a program and analysis that we do with our customer advising the customer about, hey, based on your critical application, what is the right journey, what is the right transformation to do the right risk management? >> Justin you're taking the hot core I saw you nodding your head. You're like, yeah, what's your take on that? >> Well, yeah, I agree with you. And that fear, uncertainty and doubt it's kept people on the mainframe for a really long time. The technology has caught up and the expertise where just as JP said, you've got to be really careful in the way you plan it, and you've got to make sure that you can always get back. And so the approach that we're looking at taking is, you're able to accommodate more risk if there's an easy roll back plan, and some of the new new technologies and processes are going to allow that, so, you know, if I screw this up, I get to go find a job someplace else. So I'm aware of the white hot core, but I am confident it can be done. >> Yeah, and then technology, if you don't have to kill the old to bring in the new, you can do both, and I like your approach. I think that's a success path that people are talking about it's well documented. But at the end of the day, we're back in distributed computing, I mean, I want to get this at the end, but I want to give you guys some time to think about it. As cloud becomes everywhere as Adam Selipsky talks about, it's not just about mainframes, this it's a distributed computing paradigm. So we're going to come back to that, but let's get into the SAP Redshift `cause I think that's something that you guys are working on I think that's worth calling out here. Analytics is huge, tell us what's going on there, how you guys are working together on that. >> Yeah, so we have designed a high level of competency around SAP, and especially the migration and the SAP Redshift. So we have designed this program also with AWS and is something we are discussing at the moment also with Ingram. So we see an acceleration of this trajectory. It has been also highly pushed by SAP as well. And also we are one of the strongest partner of SAP and we see many many customers engage into this transformation at the moment. >> The cloud really gives you a lot of advantages when you're doing migration, especially around a pre-existing software, like SAP was pretty big, complex mission critical So you can throw compute at it, a lot of cool capabilities. >> Yeah, that's true, but you need, you still need to configure a lot of things as well, because it's, you need to customize and you have to really fine tune, you know, what is it, what is going to be available to the customer needs and to what you need in your company as well. >> Okay, lets get back to what Justin was saying about emulation, I mean, I can run SAP (laughs) on Amazon. I mean, we've talked about it, I wrote a story about this prior to the event called Superclouds. You can build these super applications that combine things that you never would have thought was possible. SAP running on Amazon or Ford can come to Redshift when you need it, so you have a lot more flexibility. This is now the new normal. >> Correct. >> Correct. Or Justin maybe you want also to comment on that, you know? >> You know, the great thing about being on Redshift is we pick that as a platform for our data warehouse a number of years ago, and there were basically analytics capabilities, but what we're seeing a lot here at re:Invent is as Amazon is catching up with their out of the box ML and AI capabilities in Redshift. So it feels good that we pick the platform that they're growing the capabilities in right, as we're advancing out of more of the traditional analytics and trying to go to that machine learning. And one of the things that we work at the Atos on is migrating off of SAPBW and saying, maybe we don't need that as a data and reporting platform, if we're solid with Redshift and we certainly don't need both. So we're working with them to look at the case to move all the way to Redshift, and then we can run our analytics and build the ML in that. >> And you know, that was a big theme in the keynote. This purpose-built capabilities, it's almost like having, you know, if you're building a building, you got iron steel girders made for you. You got this now better value in the platform to build on. This brings up the notion of distributed computing. >> JP: Yeah. >> In a way there's the same game, different generation. I mean, isn't it? You've got to integrate this still transformations inflection points, this is current. I feel like this now more than ever is a time where you can actually roll it all together with a little help from your friends or if Amazon's got somebody, you know, who want to reinvent the wheel. What's your reaction to that? 'Cause we've seen the movie before, when it's hard. Now, it seems easier, maybe its not. >> Yeah, we see three layers co-existing in more more. We see that, see application on data will be spread over three dimensions there will be edge computing there will be private cloud and there will be public cloud. And we see more more pressure in the direction that many customers are saying, hey, where should I put my data? This spot will go on and be processed at the edge, this spot will be process in the public cloud. There is also one of the capability where we in Atos we are able to advise customers about what is the best way to process your data if you have a lot of latency, you can process at the edge. You know, there's less equipment, you can process the public cloud. So, we see this coexistence of model. >> Justin what's your take on this distributed computing throwback concept, because look at the rise of companies like Snowflake. Where'd they come from? They're on Amazon, they pick the cloud. Now they're on going to other clouds. You can build a supercloud. You can actually build this out now faster. What's your take? >> Yeah, I, my take is that it's a pendulum and it swings back and forth, and like you said, there was client server and then everything was web-based. And a lot of things look a lot like the mainframe, put everything in the cloud and then attached to it. And then all of a sudden, you know what? We need edge computing, pull some stuff back out of the cloud and put it where we need it. So, it's going to continue to evolve. What I have noticed that I like more is, the major home one swings and statements like I want to get out of the data center business and go to the cloud, I hear those less. And people are realizing there's there's hybrid. There's purpose build computing like you said, and we need to make sure that we're putting our data where it needs to be, putting our compute where it needs to be. And that's going to change on our customer base and evolving technologies 5G is changing the whole world around edge computing. So I'm enjoying the ride, I'm glad I'm in technology because I get to move with the ebbs and flows, but I don't think we're ever going to land. I think it's going to keep moving. >> Yeah that's a totally fair point where it's fun as a technologist, but you're right. If you're operating with cloud, it doesn't matter if you're on premises or edge or public cloud, it's the same thing (laughs). >> Justin: Yeah. >> It's just pick your, pick, your use case. >> Justin: Right, your use case- >> I want a low latency at the edge. I'm not going to move my data, send it to cloud. Of course, we're going to leave it there. >> Yeah. >> If you're on premise before- >> We've already move workloads back and forth. And a lot of companies are doing that too, you know? >> I think that's what they're getting at when they talk about cloud everywhere. I think that's their way of saying, okay, hybrid is real. They won't ever say multicloud though. (all laughing) Not yet. (all laughing) >> Won't hear that here. >> All right, quick summary. What do you guys do? And what's the future hold for the relationship. You guys got a good thing going on? Take us through what's the future look like. >> Yeah, for me it's a big thank you for the partnership with Ingram. So we are extremely excited by what we can do for you. And in terms of advising your transformation and, you know, I hope that you get the right service and the right advice, you know, from Atos. >> Yeah, it's been great. We, we've appreciated. We've been, we started as a mainframe customer and now they're helping to advise on how we could get off the mainframe. I mean really cannibalizing one of the other areas there in the spirit of evolving and partnership, and you guys are bringing a ton of expertise and the way you guys attack the account and we centralized through our account team is very helpful. You're very aware of what's going on on all sides of the business. >> Well, congratulations. >> That's a big part of the theme, the keynote today on, on ad about mainframe transmission. But at the end of the day, it's about modern infrastructure, modern application development. >> Justin: Absolutely. >> Getting out, having set the table for the next generation. >> JP: Yeah. >> Thanks for coming on theCUBE and you guys want to get a quick plug in real quick for the company talk about Atos and Ingram. Give a quick plug for what you guys are working on. >> Sorry- >> Give a quick plug about what you`re working on. Give a quick commercial one minute about the company. >> One minute. >> Yeah. >> At Atos we're really transforming or leading the industry in terms of secured transformation to cloud security will be more and more important as data is everything about where is the value. So we are really making sure that our customers, they get to maximize, they can maximize the value around data transformation to cloud in a secured way. >> Justin, JP, thanks for coming on theCUBE. Really appreciate the insights. Don't touch the hot core and make, take your time. Have a good time, you're watching theCUBE, the official broadcasting of AWS re:Invent leader in tech coverage, theCUBE. Thanks for watching. (upbeat music)

>>Welcome to the cubes, continuing coverage of AWS reinvent 2021 find Lisa Martin and we are running one of the industry's most important and largest hybrid tech events with AWS in this ecosystem partners. This year, we have two live sets, two remote sites over 100 guests talking about the next decade in cloud innovation. And we're excited to be joined by Patrick Jeanne, the CTO of OutSystems Patrick. Welcome to the program. >>Thank you. I appreciate being one of those 100 guests, >>One of the 100, one of the elite, 100, we'll say it like that. Right? So, so OutSystems has some revolutionary news. You guys are saying, you know, what developer experience needs to change? Tell us more. >>It does. I mean, it needs to change. And I've been in the industry developing applications for too many years dimensions basically since I was 12 years old writing software and, you know, going over that time and thinking about it, doing the traditional software development route. So many applications that take too long was, you know, costly to build so much risk involved in it. Eventually it didn't meet all the requirements. And if you look at the investment we make in software, which is important, I mean, software is a, is a unique differentiator for, for businesses. That investment has such a high risk and a high cost, and that needs to change and it needs to change just because of the complexity that is in that process inherent in it that's. And that is what we are doing and OutSystems is tackling that problem. And, um, from a business standpoint, it must change. >>It must change that that is strong words there. So talk to me about what you're announcing, what, what were the gaps in the market customer feedback? Was it, or were there any catalysts from the pandemic going we've got to change this developer experience and this is the time >>For sure. I mean, if you think about from the pandemic and I mean, we were on a journey for digital transformation. We've been on this journey for a number of years and it really accelerated that the experiences that we have with each other, with you and me, we're not the same studio today. I mean, there's there reasons that we have used this experience remote, we have a technology that can do it, the pandemic accelerated that. And so, so much of the experiences we have are digital experiences. And if you think about it, there's a device in between us. There's going to be a device in between all the people viewing what we're looking at, that experience that, uh, that they will have with us will be basically surfaced through an application on that device. And the pandemic has really accelerated that. And that's an area that we play in, obviously for what's considered low code application development. >>And if you just think about application development in general, that's what powers all of these experiences. And going back to that, you know, statement about that, it needs to change if we need these experiences to be diverse, if we need these experiences to be meaningful, if we need them to make sure that when people engage, as far as what that device is, something that brings, you know, delight and pleasure to them, we need developers across the board. Investing in that today, there is a very constrained market for professional developers, but because of the inherent complexity in software development. And so if you think about how that's almost almost you're limiting access to the people who can create those experiences, that's not a good situation. There's about 25 million developers in the world that would consider themselves developers today, 7, 8, 9, 10 billion devices out there. Think of that disparity between those two numbers. >>And so we need a larger number of people to actually develop applications. So that experience can be much more diverse. We need to expose development to many more people. That is the problem today with software development is that it is complex. It is too specialized. It's too inherit as far as with failure when you get it together. And so either you shy away from that as an organization or as an individual to do development, or you go on these very long development as far as cycles to actually create these applications. What we do is we take the approach of let's make it very simple to get into, you know, some terms and call it citizen developer, low code, basically all they're saying is let's, let's reduce the risk of development. Let's go into a process where we make it accessible to more and more people. You can go through and develop applications with the lower risk. You can build change into that process and you can get value into end users as rapidly as possible. So that's, that is the value proposition. That is what needs to change >>Strong value proposition well said, Patrick, talking about reducing the complexity, uh, the risk as well. So, so go ahead and crack crack open what you guys are actually announcing today. >>Yeah, for sure. So with, we we've been doing this for many years, we have, um, software development, we have 14 million plus as far as end-users using applications that have been developed with the Al systems platform, what we're announcing is taking some of the great benefits that we have to what you'd consider as the first part of that low code process, where you have a, you have a developer that has an idea, and there's a canvas in front of you. You know, you're, you're an artist, right? But again, this is what you are as a developer. And so you go in and you create that application. We've been doing this for many years and it works really well. But thing that we're improving upon now is the ability to do that and scale that out to millions of end-users 10 millions of end-users. So if you think about that inherent speed of developing an application, using a platform like OutSystems, we're taking that same concept and rolling that into an internet scale application, hosting architecture. >>So any developer that uses our systems, basically like it would be comparable to a traditional development team that has application architects, cloud architects, security, engineers, database engineers, a whole team of very smart individuals that generally the, the biggest technology companies in the world can put together. Most companies can't do that. You don't have access to that type of that type of skillset. And so we're providing that with project Neo, which is what we're announcing today in our, um, at our user conference and customer conference, is this brand new as far as platform that allows you to build these applications at scale. And this is initially built on AWS using all the great AWS technologies. If you look at what AWS has done and provided to developers today, it's amazing. It is absolutely amazing. The amount of technologies that you can leverage. It's also daunting because as a traditional developer, you have to go in and choose, you know, what do you do? It's like, there's just massive cognitive load as far as upfront when you're going to design and application and what type of messaging what's at the data store. Well, how do I host my application? What type of network, you know, as far as security do I use, we're taking all that heavy lifting, all that undifferentiated, heavy lifting off of the developers, putting it into the project, Neo platform, allowing a single developer or a small group of developers to actually leverage that best in class architecture on AWS today. >>So when you're talking to developers, what are some of the things that you described as the unique differentiators of project Neo? It sounds like this was really apt and apt time for change, but when you're talking to those folks, what do you say? You know, 1, 2, 3, these are the things that make project Neo unique. >>Yeah. So you're the first is don't worry about the application architecture. Like I mentioned, don't when you go in that, the idea, the concept of that application and what it means to, to deliver some value, whether it's into a business or a hobby or whatever. I mean, however, you're developing application, you're doing it for a reason. You want that value to come out as quickly as possible. You want that experience. And so that first thing is you don't have to worry about the architecture anymore. So in the past, you know, you'd have to think about if it's a very large application, it's millions and millions of end-users. How do you structure that? How do you put it together? That concern is removed from you in that process? The other thing is we solve the problem of software disintegration. So with traditional development, when you develop an application and you get it into the hands of end, users get immediately starts to disintegrate. >>So there will be bugs that will appear. There will be, as far as, um, security flaws that will come up services that you use will become deprecated. We'll swap out cloud services, you know, AWS or Azure or Google, we'll swap out cloud services with different services behind the scenes version that we new versions of those that is software disintegration. As soon as you develop software today and all of these beautiful cloud services that you use and components, they often something will become outdated almost by the time you release it. A lot of times with software development projects, it literally is you start with some version or some component before you can get that out in a traditional mode. Something becomes outdated. We solve that issue. What I like to call software disintegration, we, as far as our systems, ensure we invest in that platform. And so when we need to change out those components, so services, those versions fix is for a security flaws, fixed bugs. >>We do that and it seamless. And so your application, you do not have to rewrite your application. You do not have to go through that process as a tradition, as a developer on our systems like you would, as your traditional developer, we solve that software disintegration issue. So it is it's, it's very empowering to developers to not have to worry about that. There are many, you look at the numbers today about how much is invested in innovation versus maintenance. You know, a lot of companies start out at 70% innovation, 30% as far as maintenance. And then over time that flips and you'll get to 30% of your time spent on innovations development, 70% maintenance, that burden we removed that burden. >>Those are some really powerful statements protect that you mean, I really liked the way that you described software disintegration. I've actually never heard that term before. And it kind of reminded me of, you know, when you buy a brand new car, you drive it off. The lot the value goes down right away, then before you even get things out. And on the consumer side, we know that as soon as we buy the newest iPhone, the next one's going to be out, or there's some part of it, that's going to be outdated in terms of technical debt. I was reading a stat that technical debt is expected to reach and costs businesses 5 trillion us dollars over the next 10 years. How does OutSystems helps customers address the challenges with technical debt and even reduce it? >>Yeah. If you think about the guy, the truest sense of technical debt, it's a, it's a decision that you make in the development process to basically, you know, load up the future with some work that you don't want to do right now. And so we're solving that issue where number one, we, you don't even have to make that decision. So you can go back to that concept of removing that cognitive load of, do I get the software out right now or do I get it out in the right way? And that's really what technical debt technical debt is saying. I need to get it out now. And there are some things I want to do that it'd be better if I did them now, but I'm going to go ahead and push that out into the future. You don't have to do that today with us. >>And so what happens with our systems? We invest in that platform, and this is hard. I mean, this is not an easy thing to do. This is why we have some of the best and brightest engineers focusing on this process at the heart of this, not to get too technical, but the heart of this is what we call the true change engine. But then, um, within our platform, we go through and we look at all of the changes that you need to make. So if you think of that concept of technical debt of like, oh, I want to get this into the hands of man users, but I don't want to invest in the time to do something right. It's always done right. As far as with the OutSystems platform. So we take that, we look at the intent of your change. So it's like a, it's like a process where you tell us the intent. >>When you, as a application developer, you're designing an application, you tell us the intent of the application is to look and feel. It could be some business processes can be some integrations. We determine what's the best way to do that. And then once again, from a software disintegration standpoint, we continue to invest in all the right ways to do that the best way possible. And so, I mean, we have customers that have written applications. That's 10, 15 years ago, they're still using our platform with those same applications they've added to them, but they actually have not rewritten those applications. And so if you think about the normal traditional development process, the technical debt incurred over that type of lifetime would be enormous with us. There's no technical debt. They're still using the same application. They have simply added capabilities to it. We invest in that platform. So they don't have to >>So big business outcomes there, obviously from a developer productivity perspective, but from the company wide perspective, the ability to eliminate technical debt, some significant opportunities there. Talk to me about the existing OutSystems customers. When are they going to be able to take advantage of this? What is the migration or upgrade path that they can take? >>Yeah. And so it's, it was very important to me and, and, uh, and the team, as far as our systems, to be able to integrate, to innovate as far as for customers, without disrupting customers. And we've probably all been through this path of great new technology is awesome. But then to actually utilize that technology when you're a current customer, it creates pain. And so we've invested heavily in making sure that the process is pain-free so you can use project Niamh. So we are announcing it as it was in public preview, as far as now, and then we will release it from GA as far as in the first quarter of next year. So over this timeframe, you'll be able to get in and try it out and all that continue to use your current version, which is OutSystems 11. So what we, what we affectionately call it 11, as far as Alice systems, Al systems, 11 version, and continued to use, and you can continue to use that today. >>Side-by-side and coexistence with the project, Neo and project Neo is a code name. So we will, we will have an official product name is for as at launch, but it's our it's. Our affectionate is kind of a unofficial mascot as Neo. So we call it project Neo bit of a fun thing, and you can use it side by side. And then in the future, you'll be able to migrate applications over, or you can just continue to coexist. I mean, we see a very long lifetime for OutSystems 11, it's a different platform, different technology behind the scenes project, Neos, Kubernetes base, Lennox containers. Based once again on the bill, we went in with the, just looked at it and said, rearchitect re-imagined, how would you do this? If you had the best and brightest, as far as engineers, architects, um, you know, we have, which we do, you know, very smart in those people. >>And we did that. And so we did that for our customers. And so Neo is that how systems 11 still a great choice. If you have applications on it, you can use it. And we have, we anticipate that customers will actually side by side, develop on both in which we have some customers in preview today. And that's the process that they have. They will develop on 11, they will develop on the Neo and they will continue to do that. And there's no, we, we are dedicated to making sure that there's no disruption and no pain in that process. And then when customers are ready to migrate over, if that's what they choose, we'll help them migrate over. >>You make it sound easy. And I was wondering if project Neo had anything to do with the new matrix movie, I just saw the trailer for it the other day. >>It was a happy coincidence. It is not easy. Let me, let me be clear. It is something we have been working on for three years and really this last year really kicked into high gear. And, um, you know, a lot of behind the scenes work, obviously for us, but once again, that's our value proposition. It's we do the hard work. So developers and customers don't have to do that hard work, uh, but no relations in the L I love, I do love the matrix movies. So it's a, it's a nice coincidence. >>It is a nice coincidence. Last question, Patrick, for you, you know, as we wrap up the calendar year 2021, we head into 20, 22. I think we're all very hopeful that 2022 will be a better year than the last two. What are some of the things that you see as absolutely critical for enterprises? What are they most concerned about right now? >>Yeah, I think it's look, I mean, it's, obviously it has been a crazy couple of years. And, um, and if you think about what enterprises want, I mean, they want to provide, uh, a great experiences for their customers, a great experience for their employees. Once again, digital transformation, we're where you don't even kind of talk about digital transformation more because we're in it. And I think that customers need to make sure that the experiences they provide these digital experiences are the best possible experiences. And these are differentiators. These are differentiators for employees is, are differentiators for customers. I believe that software is one of the big differentiators for businesses today and going forward, and that will continue to be so we're where businesses may be invested in supply chains and invested in certain types of technologies. Business will continue to invest in software because software is that differentiator. >>And if you look at where we fit, you can go, you can go buy, you know, some great satisfied where my software as a service off the shelf in the end, you're just like every other business you bought the same thing that everybody else has bought. You can go the traditional development route, where you invest a bunch of money. It's a high risk, takes a long time. And once again, you may not get what you want. We believe what is most important to businesses. Get that unique software that fits like a glove that is great for employees is great for their customers. And it is a unique differentiator for them. And I really see that in 2022, that's going to be big and, and going forward. They're the legs for that type of investment that companies make and their return on that is huge. >>I agree with you on that in terms of software as a differentiator. No, we're seeing every company become a software company in every industry these days to be first to survive in the last 20 months and now to be competitive, it's really kind of a must have. So Patrick, thank you for joining me on the program, talking about project Neo GA in quarter of calendar year 22 exciting stuff. We appreciate your feedback and your insights and congratulations on project Neil. Thanks, Lisa. Appreciate it for Patrick Jean I'm Lisa Martin, and you're watching the cubes continuous coverage of re-invent 2021.

(Upbeat intro music) >> Welcome to theCUBE's continuing coverage of AWS re:Invent 2021. I'm Lisa Martin and we are running one of the industry's most important and largest hybrid tech events with AWS in this ecosystem partners this year. We have two live sets, two remote sets over 100 guests talking about the next decade in cloud innovation. And we're excited to be joined by Patrick Jean the CTO of OutSystems, Patrick welcome to the program. >> Thank you, I appreciate being one of those 100 guests. >> One of the 100, one of the elite 100, we'll say it like that, right? >> Yes. >> So OutSystems has some revolutionary news. You guys are saying, you know what, developer experience needs to change, tell us more. >> It does I mean, it needs to change. And I've been in the industry developing applications for too many years to mention, basically since I was 12 years old writing software and going over that time and thinking about it, doing the traditional software development route. So many applications that take too long was costly to build, so much risk involved in it. Eventually it didn't meet all the requirements. And if you look at the investment we make in software, which is important, I mean, software is a unique differentiator for businesses. That investment has such a high-risk and a high cost and that needs to change. And it needs to change just because of the complexity that is in that process inherent in it. That's and that is what we are doing in OutSystems is tackling that problem. And from a business standpoint, it must change. >> It must change that is strong words there. So talk to me about what you're announcing what were the gaps in the market, customer feedback, were there any catalysts from the pandemic going we've got to change this developer experience and this is the time. >> For sure. I mean, if you think about from the pandemic and I mean, we were on a journey for digital transformation. We've been on this journey for a number of years the pandemic really accelerated that the experiences that we have with each other, you and me are not in the same studio today. I mean, there reasons that we use this experience remotely. We have a technology that can do it. The pandemic accelerated that. And so, so much of the experiences we have are digital experiences. And if you think about it, there's a device in between us. There's going to be a device in between all the people viewing what we're looking at. That experience that they will have with us will be basically surfaced through an application on that device. And the pandemic has really accelerated that. And that's an area that we play in, obviously for what's considered low-code application development. And if you just think about application development in general, that's what powers all of these experiences. And going back to that statement about that it needs to change. If we need these experiences to be diverse, if we need these experiences to be meaningful, if we need them to make sure that when people engage as far as what that device is something that brings, delight and pleasure to them. We need developers across the board investing in that. Today there is a very constrained market for professional developers because of the inherent complexity in software development. And so if you think about how that's almost, almost here limiting access to the people who can create those experiences, that's not a good situation. There's about 25 million developers in the world that would consider themselves developers today, seven, eight, nine, 10 billion devices out there. Think of that disparity between those two numbers. And so we need a larger number of people to actually develop applications so that experience can be much more diverse. We need to expose development to many more people. That is the problem today with software development is that it is complex, it is too specialized. It's too inherent as far with failure when you get it together. And so either you shy away from that as an organization or as an individual. To do development are you going on these very long development as far as cycles to actually create these applications? What we do is we take the approach of let's make it very simple to get into. Sometimes we call it citizen developer, low-code, basically all they're saying is let's reduce the risk of development. Let's go into a process where we make it accessible to more and more people. You can go through and develop applications with the lower risk. You can build change into that process. You can get value into end users as rapidly as possible. So that is the value proposition, that is what needs to change. >> Strong value proposition well said, Patrick. Talking about reducing the complexity, the risk as well. So go ahead and crack open what you guys are actually announcing today. >> Yeah, for sure. So we've been doing this for many years. We have software development, we have 14 million plus as far as end-users using applications that have been developed with the Allo systems platform. What we're announcing is taking some of the great benefits that we have to what you'd consider as the first part of that low-code process. Where you have a developer that has an idea, and there's a canvas in front of you. You're an artist, right, with a canvas that's what you are as a developer. And so you go in and you create that application. We've been doing this for many years and it worked really well. The thing that we're improving upon now is the ability to do that and scale that out to millions of end-users, 10 millions of end-users. So if you think about that inherent speed of developing an application, using a platform like OutSystems, we're taking that same concept and rolling that into an internet scale application, hosting architecture. So any developer that uses OutSystems, basically like it would be comparable to a traditional development team that has application architects, cloud architects, security engineers, database engineers, a whole team of very smart individuals that generally the biggest technology companies in the world can put together. Most companies can't do that, you don't have access to that type of skillset. And so we're providing that with Project Neo, which is what we're announcing today in our, at our user conference and customer conference. Is this brand new as far as platform that allows you to build these applications at scale. And this is initially built on AWS using all the great AWS technologies. If you look at what AWS has done and provided to developers today, it's amazing. It is absolutely amazing. The amount of technologies that you can leverage. It's also daunting because as a traditional developer, you have to go in and choose what do you do? It's like, there's just massive cognitive load. As far as upfront when you go in to design an application. What's up in messaging, what's up at data store, well, how do I host my application? What type of network as far as security do I use? We're taking all that heavy lifting, all that undifferentiated heavy lifting off of the developers, putting it into the Project Neo platform. Allowing a single developer or a small group of developers to actually leverage that best in class architecture on AWS today. >> So when you're talking to developers, what are some of the things that you describe as the unique differentiators of Project Neo? It sounds like this was really apt and apt time for change. But when you're talking to those folks, what do you say you know, one, two three, these are the things that make Project Neo unique. >> Yeah, so the first is don't worry about the application architecture. Like I mentioned when you go in, the idea, the concept of that application and what it means to deliver some value, whether it's into a business or a hobby or whatever. I mean, however you're developing application, you're doing it for a reason. You want that value to come out as quick as possible. You want that experience. And so that first thing is, you don't have to worry about the architecture anymore. So in the past you'd have to think about if it's a very large application, it's millions and millions of end-users. How do you structure that? How do you put it together? That concern is removed from you in that process. The other thing is we solve the problem of software disintegration. So with traditional development, when you develop an application and you get it into the hands of end users it immediately starts to disintegrate. So there will be bugs that will appear. There will be as far as security flaws that will come up services that you use will become deprecated. We'll swap out cloud services by AWS or Azure or Google. swap out cloud services with different services behind the scenes. Version, there'll be new versions of those that is software disintegration. As soon as you develop software today and all of these beautiful cloud services that you use and components. Something will become outdated almost by the time you release it. A lot of times with software development projects, it literally is you start with some version or some component before you can get that out in a traditional mode, something becomes outdated. We solved that issue. What I like to call software disintegration. We, as far as OutSystems, ensure we invest in that platform. And so when we may need to change out those components, those services, those versions fix is for security flaws, fixed bugs, we do that and it's seamless. And so your application, you do not have to rewrite your application. You do not have to go through that process as a tradition, as a developer on OutSystems like you would, as your traditional developer. We solve that software disintegration issue. So it's very empowering to developers to not have to worry about that. There are many, you look at the numbers today about how much is invested in innovation versus maintenance. A lot of companies start out at 70% innovation, 30% as far as maintenance, and then overtime that flips. And you'll get to 30% of your time spent on innovations development, 70% maintenance, that burden, we remove that burden. >> Those were some really powerful statements Patrick that you made and I really liked the way that you described software disintegration. I've actually never heard that term before. And it kind of reminded me of when you buy a brand new car, you drive it off the lot, the value goes down right away then before you even get things out. And on the consumer side, we know that as soon as we buy the newest iPhone, the next one's going to be out, or there's some part of it, that's going to be outdated. In terms of technical debt, I was reading a stat that technical debt is expected to reach in costs of businesses, 5 trillion, US dollars over the next 10 years. How does OutSystems help customers address the challenges with technical debt and even reduce it? >> Yeah, I mean if you think about in the kind of the truest sense of technical debt, it's a decision that you make in the development process to basically load up the future with some work that you don't want to do right now. And so we're solving that issue where not only, you don't even have to make that decision. So you can go back to that concept of removing that cognitive load of, do I get the software out right now or do I get it out in the right way? And that's really what technical debt, technical debt is saying I need to get it out now. And there are some things I want to do that it'd be better if I did them now, but I'm going to go ahead and push that out into the future. You don't have to do that today with us. And so what happens with OutSystems is we invest in that platform. And this is hard. I mean, this is not an easy thing to do. This is why we have some of the best and brightest engineers focusing on this process at the heart of this, not to get too technical, but the heart of this is what we call the true change engine within our platform. We go through and we look at all of the changes that you need to make. So you think of that concept of technical debt of like, ah, I want to get this in the hands of end users, but I don't want to invest in the time to do something right. It's always done right, as far as with the OutSystems platform. So we take that, we look at the intent of your change. So it's like a process where you tell us the intent. When you as a application developer, you're designing an application, you tell us the intent of the application is to look and feel. It could be some business processes this could be some integrations. We determine what's the best way to do that and then once again, from a software disintegration standpoint, we continue to invest in all the right ways to do that the best way possible. And so, I mean, we have customers that have written applications that's 10, 15 years ago. They're still using our platform with those same applications they've added to them, but they have not rewritten those applications. And so if you think about the normal traditional development process, the technical debt incurred over that type of lifetime would be enormous. With us there's no technical debt. They're still using the same application they've simply added capabilities to it. We invest in that platform so they don't have to. >> So big business outcomes down, obviously from a developer productivity perspective, but from the company wide perspective, the ability to eliminate technical debt, some significant opportunities there. Talk to me about the existing OutSystems customers. When are they going to be able to take advantage of this? What is the migration or upgrade path that they can take and when? >> Yeah and so it is very important to me and the team as far as OutSystems to be able to integrate, to innovate as far as for customers, without disrupting customers. And we've probably all been through this path of great new technology is awesome. But then to actually utilize that technology when you're a current customer, it creates pain. And so we've invested heavily in making sure that the process is pain-free. So you can use Project Neo. So we are announcing it as in, it was in public preview as far as now, and then we will release it from GA as far as in the first quarter of next year. So over this timeframe, you'll be able to get in and try it out and all that. Continue to use your current version, which is OutSystems 11. So what we affectionately call O-11, as far as Allo systems. The Allo systems 11 version continue to use, and you can continue to use that today side-by-side and coexistence with the Project Neo. And Project Neo is a code name. So we will have an official product name as for as at launch but it's our affectionate it's kind of a unofficial mascot as Neo. So we call the Project Neo is a little bit of a fun name and you can use it side by side and then in the future, you'll be able to migrate applications over. Or you can just continue to co-exist. I mean, we see a very long lifetime for OutSystems 11, it's a different platform, different technology behind the scenes. Project Neo's Kubernetes-base Linux containers. Based once again, on the ability, we went in with the gist and looked at it and said, re-architect, re-imagine, how would you do this if you had the best and brightest as far as engineers, architects, we have, which we do. Various market and those people and we did that. And so we did that for our customers. And so Neo is that OutSystems 11 still a great choice. If you have applications on it, you can use it. And we have, we anticipate the customers will actually side by side develop on both in which we have some customers in preview today. And that's the process that they have. They will develop on 11, they will develop on Neo and they will continue to do that. And there's no, we are dedicated to making sure that there's no disruption and no pain in that process. And then when customers are ready to migrate over, if that's what they choose, we'll help them migrate over. >> You make it sound easy. And I was wondering if Project Neo had anything to do with the new matrix movie I just saw the trailer for it the other day, I wonder if this is related. >> It was a happy coincidence. It is not easy let me, let me be clear. It is something we have been working on for three years and really this last year really kicked into high gear. And a lot of behind the scenes work, obviously for us, but once again, that's our value proposition. It's we do the hard work. So developers and the customers don't have to do that hard work. But no relations to Neo, I love, I do love the matrix movies. So it's a nice coincidence. (Lisa laughs) >> It is a nice coincidence. Last question, Patrick, for you, as we wrap up the calendar year 2021, we heading into 2022. I think we're all very hopeful that 2022 will be a better year than the last two. What are some of the things that you see as absolutely critical for enterprises? What are they most concerned about right now? >> Yeah, I think it's, look I mean, it's obviously it has been a crazy a couple of years. And if you think about what enterprises want, I mean, they want to provide a great experiences for their customers, a great experience for their employees. Once again, digital transformation, where you don't even kind of talk about digital transformation more because we're in it. And I think that customers need to make sure that the experiences they provide these digital experiences are the best possible experiences. And these are differentiators. These are differentiators for employees. These are differentiators for customers. I believe that software is one of the big differentiators for businesses today and going forward. And that will continue to be so where businesses may be invested in supply chains, invested in certain types of technologies. Business will continue to invest in software because software is that differentiator. And if you look at where we fit, you can go, you can go buy, some great set of software, my software as a service off the shelf. In the end, you're just like every other business you bought the same thing that everybody else had bought. You can go the traditional development route, where you invest a bunch of money, it's a high risk, takes a long time. And once again, you may not get what you want. We believe what is most important to businesses. Get that unique software that fits like a glove that is great for employees, it's great for their customers. And it is a unique differentiator for them. And I really see that in 2022, that's going to be big and going forward. They're the legs for that type of investment that companies make and they return on that is huge. >> I agree with you on that in terms of software as a differentiator. Now we're seeing every company become a software company in every industry these days to be, first to survive in the last 20 months and now to be competitive, it's really kind of a must have. So, Patrick thank you for joining me on the program, talking about Project Neo, GA in the first quarter of calendar year 22. Exciting stuff we appreciate your feedback and your insights and congratulations on Project Neo. >> Thanks, Lisa, appreciate it. >> For Patrick Jean, I'm Lisa Martin, and you're watching theCUBEs continuous coverage of re:Invent 2021. (Outro music)

>> Live, from Las Vegas, it's theCUBE covering UiPath Forward Americas 2019. Brought to you by UiPath. >> Welcome back to the Bellagio in Las Vegas, everybody. You're watching theCUBE, the leader in live tech coverage. My name is Dave Vellante. Day one of UiPath Forward III, hashtag UiPathForward. Elena Christopher is here. She's the senior vice president at HFS Research, and Elena, I'm going to recruit you to be my co-host here. >> Co-host! >> On this power panel. Jean Youngers here, CUBE alum, VP, a Six Sigma Leader at Security Benefit. Great to see you again. >> Thank you. >> Dave: And Amy Chandler, who is the Assistant Vice President and Director of Internal Controls, also from Security Benefit. >> Hello. >> Dave: Thanks for coming on theCUBE. >> Thank you. >> Alright Elena, let's start off with you. You follow this market, you have for some time, you know HFS is sort of anointed as formulating this market place, right? >> Elena: We like to think of ourselves as the voice-- >> You guys were early on. >> The voice of the automation industry. >> So, what are you seeing? I mean, process automation has been around forever, RPA is a hot recent trend, but what are you seeing the last year or two? What are the big trends and rip currents that you see in the market place? >> I mean, I think one of the big trends that's out there, I mean, RPA's come on to the scene. I like how you phrase it Dave, because you refer to it as, rightly so, automation is not new, and so we sort of say the big question out there is, "Is RPA just flavor of the month?" RPA is definitely not, and I come from a firm, we put out a blog earlier this year called "RPA is dead. Long live automation." And that's because, when we look at RPA, and when we think about what it's impact is in the market place, to us the whole point of automation in any form, regardless of whether it's RPA, whether it be good old old school BPM, whatever it may be, it's mission is to drive transformation, and so the HFS perspective, and what all of our research shows and sort of justifies that the goal is, what everyone is striving towards, is to get to that transformation. And so, the reason we put out that piece, the "RPA is dead. Long live integrated automation platforms" is to make the point that if you're not- 'cause what does RPA allow? It affords an opportunity for change to drive transformation so, if you're not actually looking at your processes within your company and taking this opportunity to say, "What can I change, what processes are just bad, "and we've been doing them, I'm not even sure why, "for so long. What can we transform, "what can we optimize, what can we invent?" If you're not taking that opportunity as an enterprise to truly embrace the change and move towards transformation, that's a missed opportunity. So I always say, RPA, you can kind of couch it as one of many technologies, but what RPA has really done for the market place today, it's given business users and business leaders the realization that they can have a role in their own transformation. And that's one of the reasons why it's actually become very important, but a single tool in it's own right will never be the holistic answer. >> So Jean, Elena's bringing up a point about transformation. We, Stew Bennett and I interviewed you last year and we've played those clips a number of times, where you sort of were explaining to us that it didn't make sense before RPA to try to drive Six Sigma into business processes; you couldn't get the return. >> Jean: Right. >> Now you can do it very cheaply. And for Six Sigma or better, is what you use for airplane engines, right? >> Right. >> So, now you're bringing up the business process. So, you're a year in, how's it going? What kind of results are you seeing? Is it meeting your expectations? >> It's been wonderful. It has been the best, it's been probably the most fun I've had in the last fifteen years of work. I have enjoyed, partly because I get to work with this great person here, and she's my COE, and helps stand up the whole RPA solution, but you know, we have gone from finance into investment operations, into operations, you know we've got one sitting right now that we're going to be looking at statements that it's going to be fourteen thousand hours out of both time out as well as staff hours saved, and it's going to touch our customer directly, that they're not going to get a bad statement anymore. And so, you know, it has just been an incredible journey for us over the past year, it really has. >> And so okay Amy, your role is, you're the hardcore practitioner here right? >> Amy: That's right. >> You run the COE. Tell us more about your role, and I'm really interested in how you're bringing it out, RPA to the organization. Is that led by your team, or is it kind of this top-down approach? >> Yeah, this last year, we spent a lot of time trying to educate the lower levels and go from a bottom-up perspective. Pretty much, we implemented our infrastructure, we had a nice solid change management process, we built in logical access, we built in good processes around that so that we'd be able to scale easily over this last year, which kind of sets us up for next year, and everything that we want to accomplish then. >> So Elena, we were talking earlier on theCUBE about you know, RPA, in many ways, I called it cleaning up the crime scene, where stuff is kind of really sort of a mass and huge opportunities to improve. So, my question to you is, it seems like RPA is, in some regards, successful because you can drop it into existing processes, you're not changing things, but in a way, this concerns that, oh well, I'm just kind of paving the cow path. So how much process reinvention should have to occur in order to take advantage of RPA? >> I love that you use that phrase, "paving the cow path." As a New Englander, as you know the roads in Boston are in fact paved cow paths, so we know that can lead to some dodgy roads, and that's part of, and I say it because that's part of what the answer is, because the reinvention, and honestly the optimization has to be part of what the answer is. I said it just a little bit earlier in my comments, you're missing an opportunity with RPA and broader automation if you don't take that step to actually look at your processes and figure out if there's just essentially deadwood that you need to get rid of, things that need to be improved. One of the sort of guidelines, because not all processes are created equal, because you don't want to spend the time and effort, and you guys should chime in on this, you don't want to spend the time and effort to optimize a process if it's not critical to your business, if you're not going to get lift from it, or from some ROI. It's a bit of a continuum, so one of the things that I always encourage enterprises to think about, is this idea of, well what's the, obviously, what business problem are you trying to solve? But as you're going through the process optimization, what kind of user experience do you want out of this? And your users, by the way, you tend to think of your user as, it could be your end customer, it could be your employee, it could even be your partner, but trying to figure out what the experience is that you actually want to have, and then you can actually then look at the process and figure out, do we need to do something different? Do we need to do something completely new to actually optimize that? And then again, line it with what you're trying to solve and what kind of lift you want to get from it. But I'd love to, I mean, hopping over to you guys, you live and breathe this, right? And so I think you have a slightly different opinion than me, but-- >> We do live and breathe it, and every process we look at, we take into consideration. But you've also got to, you have a continuum right? If it's a simple process and we can put it up very quickly, we do, but we've also got ones where one process'll come into us, and a perfect example is our rate changes. >> Amy: Rate changes. >> It came in and there was one process at the very end and they ended up, we did a wing to wing of the whole thing, followed the data all the way back through the process, and I think it hit, what, seven or eight-- >> Yeah. >> Different areas-- >> Areas. >> Of the business, and once we got done with that whole wing to wing to see what we could optimize, it turned into what, sixty? >> Amy: Yeah, sixty plus. Yeah. >> Dave: Sixty plus what? >> Bot processes from one entry. >> Yeah. >> And so, right now, we've got 189 to 200 processes in the back log. And so if you take that, and exponentially increase it, we know that there's probably actually 1,000 to 2,000 more processes, at minimum, that we can hit for the company, and we need to look at those. >> Yeah, and I will say, the wing to wing approach is very important because you're following the data as it's moving along. So if you don't do that, if you only focus on a small little piece of it, you don't what's happening to the data before it gets to you and you don't know what's going to happen to it when it leaves you, so you really do have to take that wing to wing approach. >> So, internal controls is in your title, so talking about scale, it's a big theme here at UiPath, and these days, things scale really fast, and boo-boos can happen really fast. So how are you ensuring, you know that the edicts of the organization are met, whether it's security, compliance, governance? Is that part of your role? >> Yeah, we've actually kept internal audit and internal controls, and in fact, our external auditors, EY. We've kept them all at the table when we've gone through processes, when we've built out our change management process, our logical access. When we built our whole process from beginning to end they kind of sat at the table with us and kind of went over everything to make sure that we were hitting all the controls that we needed to do. >> And actually, I'd like to piggyback on that comment, because just that inclusion of the various roles, that's what we found as an emerging best practice, and in all of our research and all of the qualitative conversations that we have with enterprises and service providers, is because if you do things, I mean it applies on multiple levels, because if you do things in a silo, you'll have siloed impact. If you bring the appropriate constituents to the table, you're going to understand their perspective, but it's going to have broader reach. So it helps alleviate the silos but it also supports the point that you just made Amy, about looking at the processes end to end, because you've got the necessary constituents involved so you know the context, and then, I believe, I mean I think you guys shared this with me, that particularly when audit's involved, you're perhaps helping cultivate an understanding of how even their processes can improve as well. >> Right. >> That is true, and from an overall standpoint with controls, I think a lot of people don't realize that a huge benefit is your controls, cause if you're automating your controls, from an internal standpoint, you're not going to have to test as much, just from an associate process owner paying attention to their process to the internal auditors, they're not going to have to test as much either, and then your external auditors, which that's revenue. I mean, that's savings. >> You lower your auditing bill? >> Yeah. Yeah. >> Well we'll see right? >> Yeah. (laughter) >> That's always the hope. >> Don't tell EY. (laughter) So I got to ask you, so you're in a little over a year So I don't know if you golf, but you know a mulligan in golf. If you had a mulligan, a do over, what would you do over? >> The first process we put in place. At least for me, it breaks a lot, and we did it because at the time, we were going through decoupling and trying to just get something up to make sure that what we stood up was going to work and everything, and so we kind of slammed it in, and we pay for that every quarter, and so actually it's on our list to redo. >> Yeah, we automated a bad process. >> Yeah, we automated a bad process. >> That's a really good point. >> So we pay for it in maintenance every quarter, we pay for it, cause it breaks inevitably. >> Yes. >> Okay so what has to happen? You have to reinvent the process, to Elena's? >> Yes, you know, we relied on a process that somebody else had put in place, and in looking at it, it was kind of a up and down and through the hoop and around this way to get what they needed, and you know there's much easier ways to get the data now. And that's what we're doing. In fact, we've built our own, we call it a bot mart. That's where all our data goes, they won't let us touch the other data marts and so forth so they created us a bot mart, and anything that we need data for, they dump in there for us and then that's where our bot can hit, and our bot can hit it at anytime of the day or night when we need the data, and so it's worked out really well for us, and so the bot mart kind of came out of that project of there's got to be a better way. How can we do this better instead of relying on these systems that change and upgrade and then we run the bot and its working one day and the next day, somebody has gone in and tweaked something, and when all's I really need out of that system is data, that's all I need. I don't need, you know, a report. I don't need anything like that, cause the reports change and they get messed up. I just want the raw data, and so that's what we're starting to do. >> How do you ensure that the data is synchronized with your other marts and warehouses, is that a problem? >> Not yet. >> No not yet! (laughter) >> I'm wondering cause I was thinking the exact same question Dave, because on one hand its a nice I think step from a governance standpoint. You have what you need, perhaps IT or whomever your data curators are, they're not going to have a heart attack that you're touching stuff that they don't want you to, but then there is that potential for synchronization issues, cause that whole concept of golden source implies one copy if you will. >> Well, and it is. It's all coming through, we have a central data repository that the data's going to come through, and it's all sitting there, and then it'll move over, and to me, what I most worry about, like I mentioned on the statement once, okay, I get my data in, is it the same data that got used to create those statements? And as we're doing the testing and as we're looking at going live, that's one of our huge test cases. We need to understand what time that data comes in, when will it be into our bot mart, so when can I run those bots? You know, cause they're all going to be unattended on those, so you know, the timing is critical, and so that's why I said not yet. >> Dave: (chuckle) >> But you want to know what, we can build the bot to do that compare of the data for us. >> Haha all right. I love that. >> I saw a stat the other day. I don't know where it was, on Twitter or maybe it was your data, that more money by whatever, 2023 is going to be spent on chat bots than mobile development. >> Jean: I can imagine, yes. >> What are you doing with chat bots? And how are you using them? >> Do you want to answer that one or do you want me to? >> Go ahead. >> Okay so, part of the reason I'm so enthralled by the chat bot or personal assistant or anything, is because the unattended robots that we have, we have problems making sure that people are doing what they're supposed to be doing in prep. We have some in finance, and you know, finance you have a very fine line of what you can automate and what you need the user to still understand what they're doing, right? And so we felt like we had a really good, you know, combination of that, but in some instances, they forget to do things, so things aren't there and we get the phone call the bot broke, right? So part of the thing I'd like to do is I'd like to move that back to an unattended bot, and I'm going to put a chat bot in front of it, and then all's they have to do is type in "run my bot" and it'll come up if they have more than one bot, it'll say "which one do you want to run?" They'll click it and it'll go. Instead of having to go out on their machine, figure out where to go, figure out which button to do, and in the chat I can also send them a little message, "Did you run your other reports? Did you do this?" You know, so, I can use it for the end user, to make that experience for them better. And plus, we've got a lot of IT, we've got a lot of HR stuff that can fold into that, and then RPA all in behind it, kind of the engine on a lot of it. >> I mean you've child proofed the bot. >> Exactly! There you go. There you go. >> Exactly. Exactly. And it also provides a means to be able to answer those commonly asked questions for HR for example. You know, how much vacation time do I have? When can I change my benefits? Examples of those that they answer frequently every day. So that provides another avenue for utilization of the chat bot. >> And if I may, Dave, it supports a concept that I know we were talking about yesterday. At HFS it's our "Triple-A Trifecta", but it's taking the baseline of automation, it intersects with components of AI, and then potentially with analytics. This is starting to touch on some of the opportunities to look at other technologies. You say chat bots. At HFS we don't use the term chat bot, just because we like to focus and emphasize the cognitive capability if you will. But in any case, you guys essentially are saying, well RPA is doing great for what we're using RPA for, but we need a little bit of extension of functionality, so we're layering in the chat bot or cognitive assistant. So it's a nice example of some of that extension of really seeing how it's, I always call it the power of and if you will. Are you going to layer these things in to get what you need out of it? What best solves your business problems? Just a very practical approach I think. >> So Elena, Guy has a session tomorrow on predictions. So we're going to end with some predictions. So our RPA is dead, (chuckle) will it be resuscitated? What's the future of RPA look like? Will it live up to the hype? I mean so many initiatives in our industry haven't. I always criticize enterprise data warehousing and ETL and big data is not living up to the hype. Will RPA? >> It's got a hell of a lot of hype to live up to, I'll tell you that. So, back to some of our causality about why we even said it's dead. As a discrete software category, RPA is clearly not dead at all. But unless it's helping to drive forward with transformation, and even some of the strategies that these fine ladies from Security Benefit are utilizing, which is layering in additional technology. That's part of the path there. But honestly, the biggest challenge that you have to go through to get there and cannot be underestimated, is the change that your organization has to go through. Cause think about it, if we look at the grand big vision of where RPA and broader intelligent automation takes us, the concept of creating a hybrid workforce, right? So what's a hybrid workforce? It's literally our humans complemented by digital workers. So it still sounds like science fiction. To think that any enterprise could try and achieve some version of that and that it would be A, fast or B, not take a lot of change management, is absolutely ludicrous. So it's just a very practical approach to be eyes wide open, recognize that you're solving problems but you have to want to drive change. So to me, and sort of the HFS perspective, continues to be that if RPA is not going to die a terrible death, it needs to really support that vision of transformation. And I mean honestly, we're here at a UiPath event, they had many announcements today that they're doing a couple of things. Supporting core functionality of RPA, literally adding in process discovery and mining capabilities, adding in analytics to help enterprises actually track what your benefit is. >> Jean: Yes. >> These are very practical cases that help RPA live another day. But they're also extending functionality, adding in their whole announcement around AI fabric, adding in some of the cognitive capability to extend the functionality. And so prediction-wise, RPA as we know it three years from now is not going to look like RPA at all. I'm not going to call it AI, but it's going to become a hybrid, and it's honestly going to look a lot like that Triple-A Trifecta I mentioned. >> Well, and UiPath, and I presume other suppliers as well, are expanding their markets. They're reaching, you hear about citizens developers and 100% of the workforce. Obviously you guys are excited and you see a long-run way for RPA. >> Jean: Yeah, we do. >> I'll give you the last word. >> It's been a wonderful journey thus far. After this morning's event where they showed us everything, I saw a sneak peek yesterday during the CAB, and I had a list of things I wanted to talk to her about already when I came out of there. And then she saw more of 'em today, and I've got a pocketful of notes of stuff that we're going to take back and do. I really, truly believe this is the future and we can do so much. Six Sigma has kind of gotten a rebirth. You go in and look at your processes and we can get those to perfect. I mean, that's what's so cool. It is so cool that you can actually tell somebody, I can do something perfect for you. And how many people get to do that? >> It's back to the user experience, right? We can make this wildly functional to meet the need. >> Right, right. And I don't think RPA is the end all solution, I think it's just a great tool to add to your toolkit and utilize moving forward. >> Right. All right we'll have to leave it there. Thanks ladies for coming on, it was a great segment. Really appreciate your time. >> Thanks. >> Thank you. >> Thank you for watching, everybody. This is Dave Vellante with theCUBE. We'll be right back from UiPath Forward III from Las Vegas, right after this short break. (technical music)

>> Live, from Las Vegas, it's theCUBE covering UiPath Forward Americas 2019. Brought to you by UiPath. >> Welcome back to the Bellagio in Las Vegas, everybody. You're watching theCUBE, the leader in live tech coverage. My name is Dave Vellante. Day one of UiPath Forward III, hashtag UiPathForward. Elena Christopher is here. She's the senior vice president at HFS Research, and Elena, I'm going to recruit you to be my co-host here. >> Co-host! >> On this power panel. Jean Youngers here, CUBE alum, VP, a Six Sigma Leader at Security Benefit. Great to see you again. >> Thank you. >> Dave: And Amy Chandler, who is the Assistant Vice President and Director of Internal Controls, also from Security Benefit. >> Hello. >> Dave: Thanks for coming on theCUBE. >> Thank you. >> Alright Elena, let's start off with you. You follow this market, you have for some time, you know HFS is sort of anointed as formulating this market place, right? >> Elena: We like to think of ourselves as the voice-- >> You guys were early on. >> The voice of the automation industry. >> So, what are you seeing? I mean, process automation has been around forever, RPA is a hot recent trend, but what are you seeing the last year or two? What are the big trends and rip currents that you see in the market place? >> I mean, I think one of the big trends that's out there, I mean, RPA's come on to the scene. I like how you phrase it Dave, because you refer to it as, rightly so, automation is not new, and so we sort of say the big question out there is, "Is RPA just flavor of the month?" RPA is definitely not, and I come from a firm, we put out a blog earlier this year called "RPA is dead. Long live automation." And that's because, when we look at RPA, and when we think about what it's impact is in the market place, to us the whole point of automation in any form, regardless of whether it's RPA, whether it be good old old school BPM, whatever it may be, it's mission is to drive transformation, and so the HFS perspective, and what all of our research shows and sort of justifies that the goal is, what everyone is striving towards, is to get to that transformation. And so, the reason we put out that piece, the "RPA is dead. Long live integrated automation platforms" is to make the point that if you're not- 'cause what does RPA allow? It affords an opportunity for change to drive transformation so, if you're not actually looking at your processes within your company and taking this opportunity to say, "What can I change, what processes are just bad, "and we've been doing them, I'm not even sure why, "for so long. What can we transform, "what can we optimize, what can we invent?" If you're not taking that opportunity as an enterprise to truly embrace the change and move towards transformation, that's a missed opportunity. So I always say, RPA, you can kind of couch it as one of many technologies, but what RPA has really done for the market place today, it's given business users and business leaders the realization that they can have a role in their own transformation. And that's one of the reasons why it's actually become very important, but a single tool in it's own right will never be the holistic answer. >> So Jean, Elena's bringing up a point about transformation. We, Stew Bennett and I interviewed you last year and we've played those clips a number of times, where you sort of were explaining to us that it didn't make sense before RPA to try to drive Six Sigma into business processes; you couldn't get the return. >> Jean: Right. >> Now you can do it very cheaply. And for Six Sigma or better, is what you use for airplane engines, right? >> Right. >> So, now you're bringing up the business process. So, you're a year in, how's it going? What kind of results are you seeing? Is it meeting your expectations? >> It's been wonderful. It has been the best, it's been probably the most fun I've had in the last fifteen years of work. I have enjoyed, partly because I get to work with this great person here, and she's my COE, and helps stand up the whole RPA solution, but you know, we have gone from finance into investment operations, into operations, you know we've got one sitting right now that we're going to be looking at statements that it's going to be fourteen thousand hours out of both time out as well as staff hours saved, and it's going to touch our customer directly, that they're not going to get a bad statement anymore. And so, you know, it has just been an incredible journey for us over the past year, it really has. >> And so okay Amy, your role is, you're the hardcore practitioner here right? >> Amy: That's right. >> You run the COE. Tell us more about your role, and I'm really interested in how you're bringing it out, RPA to the organization. Is that led by your team, or is it kind of this top-down approach? >> Yeah, this last year, we spent a lot of time trying to educate the lower levels and go from a bottom-up perspective. Pretty much, we implemented our infrastructure, we had a nice solid change management process, we built in logical access, we built in good processes around that so that we'd be able to scale easily over this last year, which kind of sets us up for next year, and everything that we want to accomplish then. >> So Elena, we were talking earlier on theCUBE about you know, RPA, in many ways, I called it cleaning up the crime scene, where stuff is kind of really sort of a mass and huge opportunities to improve. So, my question to you is, it seems like RPA is, in some regards, successful because you can drop it into existing processes, you're not changing things, but in a way, this concerns that, oh well, I'm just kind of paving the cow path. So how much process reinvention should have to occur in order to take advantage of RPA? >> I love that you use that phrase, "paving the cow path." As a New Englander, as you know the roads in Boston are in fact paved cow paths, so we know that can lead to some dodgy roads, and that's part of, and I say it because that's part of what the answer is, because the reinvention, and honestly the optimization has to be part of what the answer is. I said it just a little bit earlier in my comments, you're missing an opportunity with RPA and broader automation if you don't take that step to actually look at your processes and figure out if there's just essentially deadwood that you need to get rid of, things that need to be improved. One of the sort of guidelines, because not all processes are created equal, because you don't want to spend the time and effort, and you guys should chime in on this, you don't want to spend the time and effort to optimize a process if it's not critical to your business, if you're not going to get lift from it, or from some ROI. It's a bit of a continuum, so one of the things that I always encourage enterprises to think about, is this idea of, well what's the, obviously, what business problem are you trying to solve? But as you're going through the process optimization, what kind of user experience do you want out of this? And your users, by the way, you tend to think of your user as, it could be your end customer, it could be your employee, it could even be your partner, but trying to figure out what the experience is that you actually want to have, and then you can actually then look at the process and figure out, do we need to do something different? Do we need to do something completely new to actually optimize that? And then again, line it with what you're trying to solve and what kind of lift you want to get from it. But I'd love to, I mean, hopping over to you guys, you live and breathe this, right? And so I think you have a slightly different opinion than me, but-- >> We do live and breathe it, and every process we look at, we take into consideration. But you've also got to, you have a continuum right? If it's a simple process and we can put it up very quickly, we do, but we've also got ones where one process'll come into us, and a perfect example is our rate changes. >> Amy: Rate changes. >> It came in and there was one process at the very end and they ended up, we did a wing to wing of the whole thing, followed the data all the way back through the process, and I think it hit, what, seven or eight-- >> Yeah. >> Different areas-- >> Areas. >> Of the business, and once we got done with that whole wing to wing to see what we could optimize, it turned into what, sixty? >> Amy: Yeah, sixty plus. Yeah. >> Dave: Sixty plus what? >> Bot processes from one entry. >> Yeah. >> And so, right now, we've got 189 to 200 processes in the back log. And so if you take that, and exponentially increase it, we know that there's probably actually 1,000 to 2,000 more processes, at minimum, that we can hit for the company, and we need to look at those. >> Yeah, and I will say, the wing to wing approach is very important because you're following the data as it's moving along. So if you don't do that, if you only focus on a small little piece of it, you don't what's happening to the data before it gets to you and you don't know what's going to happen to it when it leaves you, so you really do have to take that wing to wing approach. >> So, internal controls is in your title, so talking about scale, it's a big theme here at UiPath, and these days, things scale really fast, and boo-boos can happen really fast. So how are you ensuring, you know that the edicts of the organization are met, whether it's security, compliance, governance? Is that part of your role? >> Yeah, we've actually kept internal audit and internal controls, and in fact, our external auditors, EY. We've kept them all at the table when we've gone through processes, when we've built out our change management process, our logical access. When we built our whole process from beginning to end they kind of sat at the table with us and kind of went over everything to make sure that we were hitting all the controls that we needed to do. >> And actually, I'd like to piggyback on that comment, because just that inclusion of the various roles, that's what we found as an emerging best practice, and in all of our research and all of the qualitative conversations that we have with enterprises and service providers, is because if you do things, I mean it applies on multiple levels, because if you do things in a silo, you'll have siloed impact. If you bring the appropriate constituents to the table, you're going to understand their perspective, but it's going to have broader reach. So it helps alleviate the silos but it also supports the point that you just made Amy, about looking at the processes end to end, because you've got the necessary constituents involved so you know the context, and then, I believe, I mean I think you guys shared this with me, that particularly when audit's involved, you're perhaps helping cultivate an understanding of how even their processes can improve as well. >> Right. >> That is true, and from an overall standpoint with controls, I think a lot of people don't realize that a huge benefit is your controls, cause if you're automating your controls, from an internal standpoint, you're not going to have to test as much, just from an associate process owner paying attention to their process to the internal auditors, they're not going to have to test as much either, and then your external auditors, which that's revenue. I mean, that's savings. >> You lower your auditing bill? >> Yeah. Yeah. >> Well we'll see right? >> Yeah. (laughter) >> That's always the hope. >> Don't tell EY. (laughter) So I got to ask you, so you're in a little over a year So I don't know if you golf, but you know a mulligan in golf. If you had a mulligan, a do over, what would you do over? >> The first process we put in place. At least for me, it breaks a lot, and we did it because at the time, we were going through decoupling and trying to just get something up to make sure that what we stood up was going to work and everything, and so we kind of slammed it in, and we pay for that every quarter, and so actually it's on our list to redo. >> Yeah, we automated a bad process. >> Yeah, we automated a bad process. >> That's a really good point. >> So we pay for it in maintenance every quarter, we pay for it, cause it breaks inevitably. >> Yes. >> Okay so what has to happen? You have to reinvent the process, to Elena's? >> Yes, you know, we relied on a process that somebody else had put in place, and in looking at it, it was kind of a up and down and through the hoop and around this way to get what they needed, and you know there's much easier ways to get the data now. And that's what we're doing. In fact, we've built our own, we call it a bot mart. That's where all our data goes, they won't let us touch the other data marts and so forth so they created us a bot mart, and anything that we need data for, they dump in there for us and then that's where our bot can hit, and our bot can hit it at anytime of the day or night when we need the data, and so it's worked out really well for us, and so the bot mart kind of came out of that project of there's got to be a better way. How can we do this better instead of relying on these systems that change and upgrade and then we run the bot and its working one day and the next day, somebody has gone in and tweaked something, and when all's I really need out of that system is data, that's all I need. I don't need, you know, a report. I don't need anything like that, cause the reports change and they get messed up. I just want the raw data, and so that's what we're starting to do. >> How do you ensure that the data is synchronized with your other marts and warehouses, is that a problem? >> Not yet. >> No not yet! (laughter) >> I'm wondering cause I was thinking the exact same question Dave, because on one hand its a nice I think step from a governance standpoint. You have what you need, perhaps IT or whomever your data curators are, they're not going to have a heart attack that you're touching stuff that they don't want you to, but then there is that potential for synchronization issues, cause that whole concept of golden source implies one copy if you will. >> Well, and it is. It's all coming through, we have a central data repository that the data's going to come through, and it's all sitting there, and then it'll move over, and to me, what I most worry about, like I mentioned on the statement once, okay, I get my data in, is it the same data that got used to create those statements? And as we're doing the testing and as we're looking at going live, that's one of our huge test cases. We need to understand what time that data comes in, when will it be into our bot mart, so when can I run those bots? You know, cause they're all going to be unattended on those, so you know, the timing is critical, and so that's why I said not yet. >> Dave: (chuckle) >> But you want to know what, we can build the bot to do that compare of the data for us. >> Haha all right. I love that. >> I saw a stat the other day. I don't know where it was, on Twitter or maybe it was your data, that more money by whatever, 2023 is going to be spent on chat bots than mobile development. >> Jean: I can imagine, yes. >> What are you doing with chat bots? And how are you using them? >> Do you want to answer that one or do you want me to? >> Go ahead. >> Okay so, part of the reason I'm so enthralled by the chat bot or personal assistant or anything, is because the unattended robots that we have, we have problems making sure that people are doing what they're supposed to be doing in prep. We have some in finance, and you know, finance you have a very fine line of what you can automate and what you need the user to still understand what they're doing, right? And so we felt like we had a really good, you know, combination of that, but in some instances, they forget to do things, so things aren't there and we get the phone call the bot broke, right? So part of the thing I'd like to do is I'd like to move that back to an unattended bot, and I'm going to put a chat bot in front of it, and then all's they have to do is type in "run my bot" and it'll come up if they have more than one bot, it'll say "which one do you want to run?" They'll click it and it'll go. Instead of having to go out on their machine, figure out where to go, figure out which button to do, and in the chat I can also send them a little message, "Did you run your other reports? Did you do this?" You know, so, I can use it for the end user, to make that experience for them better. And plus, we've got a lot of IT, we've got a lot of HR stuff that can fold into that, and then RPA all in behind it, kind of the engine on a lot of it. >> I mean you've child proofed the bot. >> Exactly! There you go. There you go. >> Exactly. Exactly. And it also provides a means to be able to answer those commonly asked questions for HR for example. You know, how much vacation time do I have? When can I change my benefits? Examples of those that they answer frequently every day. So that provides another avenue for utilization of the chat bot. >> And if I may, Dave, it supports a concept that I know we were talking about yesterday. At HFS it's our "Triple-A Trifecta", but it's taking the baseline of automation, it intersects with components of AI, and then potentially with analytics. This is starting to touch on some of the opportunities to look at other technologies. You say chat bots. At HFS we don't use the term chat bot, just because we like to focus and emphasize the cognitive capability if you will. But in any case, you guys essentially are saying, well RPA is doing great for what we're using RPA for, but we need a little bit of extension of functionality, so we're layering in the chat bot or cognitive assistant. So it's a nice example of some of that extension of really seeing how it's, I always call it the power of and if you will. Are you going to layer these things in to get what you need out of it? What best solves your business problems? Just a very practical approach I think. >> So Elena, Guy has a session tomorrow on predictions. So we're going to end with some predictions. So our RPA is dead, (chuckle) will it be resuscitated? What's the future of RPA look like? Will it live up to the hype? I mean so many initiatives in our industry haven't. I always criticize enterprise data warehousing and ETL and big data is not living up to the hype. Will RPA? >> It's got a hell of a lot of hype to live up to, I'll tell you that. So, back to some of our causality about why we even said it's dead. As a discrete software category, RPA is clearly not dead at all. But unless it's helping to drive forward with transformation, and even some of the strategies that these fine ladies from Security Benefit are utilizing, which is layering in additional technology. That's part of the path there. But honestly, the biggest challenge that you have to go through to get there and cannot be underestimated, is the change that your organization has to go through. Cause think about it, if we look at the grand big vision of where RPA and broader intelligent automation takes us, the concept of creating a hybrid workforce, right? So what's a hybrid workforce? It's literally our humans complemented by digital workers. So it still sounds like science fiction. To think that any enterprise could try and achieve some version of that and that it would be A, fast or B, not take a lot of change management, is absolutely ludicrous. So it's just a very practical approach to be eyes wide open, recognize that you're solving problems but you have to want to drive change. So to me, and sort of the HFS perspective, continues to be that if RPA is not going to die a terrible death, it needs to really support that vision of transformation. And I mean honestly, we're here at a UiPath event, they had many announcements today that they're doing a couple of things. Supporting core functionality of RPA, literally adding in process discovery and mining capabilities, adding in analytics to help enterprises actually track what your benefit is. >> Jean: Yes. >> These are very practical cases that help RPA live another day. But they're also extending functionality, adding in their whole announcement around AI fabric, adding in some of the cognitive capability to extend the functionality. And so prediction-wise, RPA as we know it three years from now is not going to look like RPA at all. I'm not going to call it AI, but it's going to become a hybrid, and it's honestly going to look a lot like that Triple-A Trifecta I mentioned. >> Well, and UiPath, and I presume other suppliers as well, are expanding their markets. They're reaching, you hear about citizens developers and 100% of the workforce. Obviously you guys are excited and you see a long-run way for RPA. >> Jean: Yeah, we do. >> I'll give you the last word. >> It's been a wonderful journey thus far. After this morning's event where they showed us everything, I saw a sneak peek yesterday during the CAB, and I had a list of things I wanted to talk to her about already when I came out of there. And then she saw more of 'em today, and I've got a pocketful of notes of stuff that we're going to take back and do. I really, truly believe this is the future and we can do so much. Six Sigma has kind of gotten a rebirth. You go in and look at your processes and we can get those to perfect. I mean, that's what's so cool. It is so cool that you can actually tell somebody, I can do something perfect for you. And how many people get to do that? >> It's back to the user experience, right? We can make this wildly functional to meet the need. >> Right, right. And I don't think RPA is the end all solution, I think it's just a great tool to add to your toolkit and utilize moving forward. >> Right. All right we'll have to leave it there. Thanks ladies for coming on, it was a great segment. Really appreciate your time. >> Thanks. >> Thank you. >> Thank you for watching, everybody. This is Dave Vellante with theCUBE. We'll be right back from UiPath Forward III from Las Vegas, right after this short break. (technical music)

(funky music) >> Live from Las Vegas, its theCUBE, covering Dell Technologies World 2019, brought to you by Dell Technologies and its ecosystem partners. >> Welcome to theCUBE. Day three of our live coverage from Dell Technologies World 2019 continues. Lisa Martin with my co-host Stu Miniman and we're welcoming to theCUBE for the first time Michael St-Jean, Principal Marketing Manager for Red Hat Storage. Michael welcome. >> Thanks Lisa. Hi Stu. >> So day three this event is still pretty loud around us. This has about we're hearing upwards of fifteen thousand people. A lot of partners. Give us your perspective on Dell Technologies World 2019. >> I got to tell you this is an awesome show. I got to tell you the energy, and not just in the sessions but out on the show floor as well. It's amazing. And some of the conversations that we've been having out there around things like emerging technologies, emerging workflows around artificial intelligence, machine learning things like that. And the whole adoption around hybrid cloud, it really speaks to all of the things that we're doing, the initiatives that we're leading at Red Hat. So it's a great validation of all of the things that we've been working on for the past 10, 15, 20 years. >> And you had a long-standing relationship with Dell. >> Oh yeah, absolutely. >> 18 years or so? >> Yeah, yeah we've had not just a long relationship but very collaborative relationship with Dell over the past 18 years. It's something like If you take a look at some of the initiatives that we've been working on, we have ready architectures around open stack, around open shift. We have just, we have highlighting a few things here around Microsoft sequel server, around SAP HANA. And actually, we're really talking a lot around open shift and a ready architecture that we've developed, that we have architecture guides, deployment guides all around open shift and open shift container storage for Dell hardware. And actually, next week at our Red Hat Summit event, you should really take a look on Wednesday morning our keynote, our EVP Paul Cormier will be talking about some great, new, very interesting initiatives that we've been working with Dell on. >> Alright well Michael I'm excited we're going to have theCUBE at Red Hat Summit in Boston. It's our sixth year there. I'll be one of the hosts there. John Walls will be there with me. We're going to have Paul Cormier on the program. (laughs) Jim Whitehurst hacking the keynote. It's actually not a secret Satya Nadella and Ginni Rometty will both be up on the main stage there. And just my perspective you were talking about hybrid cloud. As you said, Red Hat Summit, I've been for many years. That hybrid cloud, that adoption. They're both open stack at the infrastructure layer and up to the application with open chip. Something we've been hearing for years and you're right. The general themes seem to echo and resonate here as to what I've been hearing at Red Hat. Can you help expand a little bit those conversations you're having here? I love you talking about some of that app modernization analytics that are going on there. How does that fit into the ready architectures that Dell's offering? >> Sure. Well I represent our storage business unit. So a lot of times, the conversations I'm having over there at the booth are kind of revolving around storage and storage growth. How data is expanding, how do we deal with the scalability of that? How do we deal with persistence of storage and containers for staple applications, things of that nature. But really, at the end of the day as I'm listening to some of the other conversations that my colleagues are having over there, it's really about how do we get work done? How do we now move into these areas where we need that cloud like experience not just in a public cloud or even in a private cloud but everywhere that we touch infrastructure. We need to have that simplified cloud-like experience. >> So just point on your subject area. Talk about the containerization and what's happening with storage pieces. Give us that layer between the infrastructure layer because let me say I believe the t shirt I saw was Linux is container, containers are Linux. So Linux has lived on Dell hardware for a long time. But anything that users should understand about the differentiation between whether they were bare metal or virtualized in the past and containerized environments today? >> Yeah well I like to say that you can't spell Red Hat without storage. (laughs) I don't know that that's particularly true but (laughing) >> It sells good. >> It sells good. Yeah so storage is near and dear to my heart but really at the end of the day, you can't have storage sitting in an island, it has to integrate and be collaborative with the rest of the portfolio that we're expanding out for our customers solving real issues, real problems. And so we've been watching industry trends and certainly these are things like that from an industry we've been looking at over the past five, 10 years so nothing new but we see the evolution of certain things like for example developers and data analysts, data scientists, these people are really charged with going out there and making dramatic differences, transforming their companies, their organizations. And as that transformational application, service development or bringing back insights on data is really integral to a company's ability to transform or differentiate in the industry. They have to be much, much more agile. And it seems that they are more and more taking over a lot of the role that we would normally see traditional I.T. managers making a lot of the purchasing decisions. A lot of the industry trends show that these folks, developers, data analysts are actually making some of those I.T. decisions now. And of course, everything is really being developed as cloud native. So we see cloud native as being more of the new norm. And if you kind of look at the expansion of data, Lisa Spellman a couple of days ago said "Hey look. "We've seen data double in the past two years "but we're only using two percent of that data." >> Two percent? >> Two percent. >> Wow, it's not very much. >> Yeah. And if you look at IDC mentioned that the data sphere has now grown to over 33 Zettabytes. A zettabyte is a billion gigabytes. So put that into perspective. Alright. 33 Zettabytes. By 2025, they project that we're going to grow to 175 Zetabytes. How can we make better use of that data? A lot of that data is coming from IOT type applications. You look at trends, traffic trends and how that might be correlated to weather activities or other events that are going on or archeological digs or all sorts of just information that is brought back. How do we make best use of that information? And so the need for scalability in a hybrid cloud environment, has become more and more of a key industry trend as the data sphere continues to grow. And I think across all three of those, that's really driving this need for hyper convergence and not just hyper convergence in the traditional sense. we've seen hyper convergence in the field for probably about five, 10 years now. But initially it was kind of a niche play and it was based on appliances. Well the past two years, you've seen the Gardner reports on hyper convergence really talking about how it is moving and evolving to more of a software defined nature. And in fact, in the past Magic Quadrant around hyper convergence, you see Red Hat show up. Something that is probably not known that Red Hat has hyper converged offerings. It's something that actually we didn't get into it just because the analysts were suggesting it. We had customers come to us and they were trying to put together Red Hat Enterprise Linux, Red Hat virtualization, storage, et cetera et cetera with varying degrees of success with that because they were doing it more or less as a project. And so we took upon ourselves to develop that, put it into a product and start to develop it with things like Ansible for deployment management. We have dedupe and compression with our virtual data optimization products, virtual GPUs, et cetera. So we're really in that space now too. >> Yeah Michael I mean it really from our standpoint it was a natural extension of what happens if you look at what hyper converged was, it was simplification and it had to be tight integration down at the OS level or the virtualization level. As a matter of fact, when we first wrote our research on it, we called it server SAN because it was the benefits of storage area network but built at the server level. So we said those OS manufacturers. Now I have to admit, I called out VMware and Microsoft are the ones that I considered the biggest ones. But as a natural fit that Red Hat would look out of that environment and if you look at the leaders in the marketplace today, we're here, VMware is here, their softwares piece. Techtonic has transitioned to be a software company. So yeah, welcome to the party. It's been a fun ride to watch that over the last five years. >> Yeah absolutely. >> So let's talk about customers and this spirit of collaboration. You just mentioned sort of the entrance into HCIs being really driven by the voice and the actions and the needs of Red Hat customers. You guys have three major pillars, themes that you have been delivering at Dell Technologies World. Talk to us a little bit about this and how your customers are helping to drive what you're delivering here and what you'll be delivering in the future. >> Yes certainly. I mean that's the whole open source model. And we don't we don't just contribute to the open source community but we develop enterprise grade infrastructure solutions for customers based on the open source way. And so essentially, as I think of it these market trends that I was talking about. It's not that we're leading them or that we're following them. It's we're tightly integrated with them because all of these industry trends are being formulated as we're in progress. It's a great opportunity for Red Hat to really express what we can do with our customers, with our partners, our developers, the folks that we have on our staff that are working directly in the community. Most products that we work on, we're the number one contributor for. So it's all very special opportunity for us. I would say from a storage perspective, what we've really focused on this year is around three main pillars. One is around data portability for those application portability projects that we see in open shift. So being able to offer an enterprise grade persistent storage for stateful applications that are running in these containerized environments. Another area is around that hybrid cloud scalable storage. And this is something that being able to scale that storage to hundreds of petabytes is kind of a big deal (laughs) and especially as we see a lot of the workloads that we've been working with customers on around data analytics and now artificial intelligence, machine learning. Those types of data lakes type projects where we're able to, by using open stack or open shift, we're able to do multi-tenant workforce workload isolation of the work that all of these people are doing while having a shared data context underneath with Red Hat storage. And then the third is around hyper convergence. I think we've touched on that already. >> Yeah so Michael before letting you go I have to touch on the hot thing that everybody needs to understand what's going. The ripple that will be felt throughout the industry. And I'm not talking about a certain 34 billion dollar pending acquisition. (laughs) Constant in the last, most of my career there has been a certain logo that I would see at every conference and that Red Hat that I got my first one, I don't know, 15, 16 years ago. So the shadow man has been deprecated. There's a new Red Hat logo. >> Oh yeah yeah. And we just brought out the new logo today. So a great segue into actually, it was last night, they pulled down the old logos, they put the new logos on the buildings, pretty much around the world. I think it's May Day in Europe. So maybe some of that will happen tomorrow or. Trying to think of what time it is, probably tonight. So yeah it's a great new logo and it's, our old logo has been over, it was around for 19 years since 2000. And it came back from a lot of feedback from customers but also from people who didn't know Red Hat, didn't know what we did. And quite honestly, some of them said that shadow man looked a little sneaky. (laughing) >> I guess on the rise of all those cyber challenges, maybe they're right. >> (laughs) so we have a new logo just launched today. Very proud of it, we're looking forward to working with everybody in the industry and go forward with all these new, wonderful opportunities that we have. >> I look forward to pointing out to all the vendors that they're now using the old Red Hat logo just like they do for every other vendor in this space when it changes. >> As of how many hours ago. (laughing) >> Well it'll be interesting to see and hear what Stu and team uncover at the summit next week in terms of the impact of this brand. We thank you so much for your time Michael, >> Absolutely. >> joining Stu and me on theCUBE. I guess it is just after day of day three. It's hard to tell right it's all blending in together. (laughs) Well we thank you for your time and your insight. >> Thank you very much and see you next week Stu. >> Exactly. For Stu Miniman, I am Lisa Martin, you're watching theCUBE live from day three of our coverage of Dell technologies world 2019. Thanks for watching. (light music)

(upbeat music) >> From Washington, DC, it's theCUBE, covering ScienceLogic Symposium 2019. Brought to you by ScienceLogic. >> I'm Stu Miniman, and this is theCUBE's coverage of ScienceLogic Symposium 2019, here at the Ritz-Carlton, in Washington, DC. Have about 460 people, it's a good mix of enterprise users, of course there's government agencies, as well as a lot of service providers, which is really where ScienceLogic started and has, many of their customers are in that space. And happy to welcome to the program, coming to us from Europe, a first time guest on the program, Luc Horee, who's RCloud and innovation Manager at Realdolmen, who's, as I said, a service provider. Thanks so much for joining me. >> Thank you, no problem. >> So, you're based in Belgium, you're a service provider, tell us a little bit about Realdolmen, a little bit about the size, scope, number of users, and we'll take it from there. >> Realdolmen is an Belgium company, around 1,500 people in an country that is small compared to the U.S. So we have an total of 11 million people. One of the biggest service providers in Belgium, but we also do reselling, and we also do service integration. Our customers it's Belgium, it's what we call SMB market. But we have around, in total, I think three thousand customers in Belgium. Some only are buying products or licenses, others are in fact in full manage service operations. >> Okay great, yeah, the SMB market, as you call it, we understand, especially for service providers, really important market, help them, I don't want to have to manage my IT, I want to be able to go to experts that can do this. >> That's one of the reasons, yeah. >> RCloud and Innovation Manager, it's an interesting title, tell us a little bit about your role inside the company. >> I already worked for more than 36 years in the company, so I had a lot of jobs within the company. In the previous job I was a Operations Manager, and now I am RCloud and Innovation Manager. RCloud is our private cloud that we are using for hosting customers and serving customers. It's and active-active data center where we can do disaster recovery, set up, and so on. So for customers that are no longer interested in building their own data centers, that's what we doing. And it's for some of them also an in between on-premise data center and public clouds. So we have customers moving to Azure and AWS, and sometimes they just stay for specific reasons in our RCloud. Innovation Manger is about how do we set up, how do we improve our tooling, and how do we improve our processes in helping and unburdening our customers. >> You mentioned the public clouds like Azure and AWS, do you have relationships with them, do you have connections into some of those public clouds? >> We are Microsoft partner, so most of our customers are going to Azure, but it's also building up in Amazon, and we did receive some questions also about Google. >> Okay, great. So when we talk about operations, service providers, very rapid change environment, typically you have a lot of customers to be able to deal with, give us a little bit about what's changing in your business, the infrastructure management and the tooling space. >> In the tooling space, IT is moving, IT in motion is what we heard in the keynote this morning. Customers are expecting a lot, about dashboarding, they want to see how their business is behaving not about what is a device doing. We need to monitor more and more applications, and the business lines. So that's why we are implementing ScienceLogic, or had an implementation of ScienceLogic, and now we doing the second phase in building more runbook automations, more dashboarding, more experience levels instead of SLS or XLS. >> Great, I want to get to the automation, but first, you've only been using ScienceLogic for a couple of years now, bring us back to, was it a bunch of in-house tooling that you had created for managing before that drove us there, paint us a picture of kind of the before and how you ended up with ScienceLogic. >> We had Microsoft Systems Center Operations Manager, we had Nagios, we had some plugs-in on this tooling, so it was I think in total six or seven tools, and we did some interfacing about it. But yeah, seven tools interfacing, not easy to run, a lot of management, a lot of people involved, a lot of skills required, so the reason was simplify it. >> So did you completely eliminate those seven previous tools? >> Yup, as of the 1st of April this year they are gone. >> All right, so there was a little bit of a journey, can you walk us through a little bit about there, was it prying it away from certain people, was it maturity from your side or from a product standpoint, what were some of those points that took a little while to get there. >> It took a while just to convince everybody in the company, set up an organization, it's not only the tooling it's also the organization need to be involved, a lot of communication, there's a change process going on, and we implemented, the first customers were in November 2017 on the system, and since then every month we added sometimes two, sometimes five, sometimes seven, sometimes one, as customer, so the people internally and externally need to get used to the product, so that's step-by-step, keep it simple, do it slowly but fast, and with a deadline. >> So, you talk a little bit about your organization operationally, what's the impact then to your ultimate end user, do they see anything, has it changed how, has it improved cost? >> It's changed certainly for the customers, because the old tools, there was no multi tenancy, there was not easy logon, so they had no access to the dashboards, they were just waiting for the monthly reporting and say, okay, it was up, okay we were, now they can have access, we use single sign-on to do that, so the customers are happy that they can see, they can see line of business dashboarding, and so on. And certainly internally it did improve a lot of cost savings, because a lot of the things we are doing now is automation, and we started the integration with our ITSM tool, and that will go live, normally next week. >> Okay, what ITSM tool are you-- >> It's a German tool, it's from a company called OMNINET, and the tool is called OMNITRACKER. >> Great, talk now about that automation, where have you come so far, where do you see it progressing in the future? >> We started first with some task automation, we have an 24/7 operation team, first-line, and they were doing a lot of manual tasks, so where we can, and what we first did was automate some manual tasks. And now we are progressing with ITSM integration, bi-directional integration, and then we will start with removing from old mailboxes, where we can do some restart automatically, so we will take a look at the incidents, see what we can do, see if we can do some automation with that, and we will certainly progress very far, as far as possible to do more and more automation and less manual work. >> Great, tell us, you've attended this event before, what brings you back to the event? >> First of all I want to see a lot of the demos, what's coming, because we are today, 8.12 version was announced, we are on 8.9, we will move next week to 8.10, so what is coming, so I have to talk internally to people, okay, what's coming, I need to convince all program managers, service delivery managers, I can talk to customers what is coming, what they can expect, so that's one of the reasons. The other reason is to talk to other customers of ScienceLogic, what are you doing, what's helping you, what's not, and so on. >> Yeah, I noticed one of the things they talked about is making it easier to upgrade from versions, when you think about the cloud world, as we talk about it, is, if your customers are in Azure, you don't ask them what version of Azure they're running, you're running whatever version Microsoft has it, they patch it, they update it, if security fix happens it goes there, when you talk about moving from 8.9 to 10 to 12, that process of when do I do it, how do I do it, how's ScienceLogic doing it, keeping things easy to upgrade, were there things in the keynote that you were ready to jump on? >> We started with, the first version 8.3 or 4 I think, and we always try to be in good shape in the newer releases. So we already had some experience with upgrading, and it's going smooth. And whatever I heard from the system engineers, it's going better and better and better. So normally we have only a very small outage to do that, in fact it should be minimal, sometimes they switch over or something like that, when a database is changed, but normally operations is always running 24/7, and there is no interruption for operations. >> Has there been anything at the show that you've seen so far, either through the demos, talking to some of the experts, or in the keynote, that you want to highlight? >> One of the things that I have seen is the connection with the application, with the APM tools, that's what our customers also are requesting more and more, the integration of infrastructure and application, and the multi cloud of course. >> Yeah, that's definitely something we've heard. All right Luc, I want to give you the final word, things to take away, for people that haven't come to a ScienceLogic event, what you think that they should take away from an event like this. >> For me the greatest take-away is come here to learn. Come here to see what is possible, what the future is, what AIOps will mean in the future, prepare yourself for the next three to five years, that's the main reason. >> Great, well thank you so much, preparing for the next three to five years, we know the pace of change isn't slowing down at all, so it's great to be able to talk to a practitioner that's helping to manage and deal with so many of those environments, thanks so much for joining me. >> Thank you. >> All right, and we'll be back with more coverage here, be sure to check out thecube.net for all interviews, I'm Stu Miniman, and thanks so much for watching. (upbeat music)

(techno music) >> At Ducati, we create racing bikes and road bikes, and unique experiences for our bikers. The Ducati teams participate in 19 races, in 15 countries, on five continents, as part of Moto GP Championship around the world. When you own a bike, you are part of a new family, the Ducatisti. (engine revving) We have a DNA racing, that we bring into everyday's bike, you can be a racer, or you can be someone who want to go down downtown Bologna, or San Francisco, or Bangkok. Data is at the heart of the Ducati digital strategy, in racing we know how to analyze data, the experience is directly moved to our road bikes. In race bikes and road bikes we have physical sensors, now thanks to machine learning, artificial intelligence, we can bring to data together to create Bitron sensors, that give us information that were not available before. We are looking for a partner that truly understands the value and the power of data, and this happened to be NetAPP. We want to arrange data in new ways, to transform the sport of Moto GP racing, and the road bike experience. NetAPP has controlled data to make experimentation more quickly, the bike we race on Sunday, is the bike we sell on Monday, and we can test the riders sensation through data. I'm Piergiorgio Grossi, and I'm data driven. (techno music) >> Narrator: Live from Las Vegas, it's the Cube, covering NetAPP Insight 2018, brought to you by NetAPP. >> Welcome back the the Cube our continuing coverage today, from the Mandalay Bay of NetAPP Insight 2018, I'm Lisa Martin with Stu Miniman and we have a couple of guests joining us. If you're a Motorsport fan, turn the volume up. First we have, welcoming back to the Cube, Jean English, the SVP and CMO at NetAPP, great to have you back Jean!. >> Oh thank you very much, excited to be here. >> And we have Konstantin Kostenarov, CTO of Ducati Motor, wow Ducati, there is by the way, I encourage you to go to the NetAPP.com web site after the segment here there's a very cool video about how Ducati is working with NetAPP on the racing side, these bikes are like flying IOT devices, as well as the consumer side. So Jean let's kick of things with you, this is day one, record breaking attendance for NetAPP, 5000 attendees, we were in the Keynote this morning, standing room only, talk to us about NetAPP as a Data authority, what's some of the feedback that you're hearing from your wealth of partners and customers that are here this week? >> Absolutely, well we're thrilled to have so many partners and customers and employees here with us, record breaking attendance, more customers and partners that have ever joined us before here at Insight a Data authority, people are asking us what do I need to do to maximize the value of that data, whether it's integrating the data, simplifying the data, they're trying to figure it out, and most of the time it's in a Hybrid role, it's in a multiclout world, and so we're just excited about where we are with our strategy, we're bringing it to life, more and more customers, like Ducati everyday are helping us to see this vision come true and we just can't wait to get started with everyone else. >> And this is a really interesting example, NetAPP has, in it's 26 year history, a massive install base, probably every industry, but when you look at something like Ducati, which probably every guy knows about, I have some Motorsport experience myself, it's much more of a, oh as a consumer, as a fan of the sport, so Konstantin, tell us about Ducati's decision to work with NetAPP, because you guys aim to not only utilize, all of the data, tons of data coming off the two bikes, every race weekend, to improve performance, but you're also wanting to use that speed, which is the new scale as George Curion said this morning, to even improve the consumer experience, and talk to us about Ducati's partnership with NetAPP. >> So we start to work with NetAPP about two years ago, more over, and in these, nowadays, every people around us talk about job thinking, extreme improvement, extreme increase of customer experience so in this world this will be Ducatis very excited challenge and this challenge requires us to respond with the best technology. The best technology that help us to collect the best information from our motorbikes, from our racing teams that we know how to collect the data, how to transformate this data into usable information, and how to generate the opportunity to have data sensors that we can transform in in information but also in knowledge that we hear before, and put all this information inside our fabric, and inside our shop floor, inside our R and D department, in order to be able to extremely increase the experience of our customers. >> I love that we get to work with one of the most innovative companies in the entire world of Motorsports, and I think really from the inception of Ducati, you guys have been really focused on how do you keep innovating through technology, and we talk about transforming the world of racing with data and how are we doing that together, so together with Ducati and NetAPP, how do we help enable them to have the best motors in the whole world, we're really excited! >> Jean, it's a great discussion, we've loved watching from just talking about the storage industry to where we're talking about data, and transformations so maybe explain to our audience that maybe not understand, you know, what's different about the industry today, and what's enabling this, NetAPP to be able to work with companies like Ducati, to help them through these transformations today, that they might not have been able to do a few years ago. >> Absolutely, I think there's just more and more data that we're finding every day, whether it's Ducati, Motorsports, if it happens to be in health care, and thinking about the millions and billions of genomes types of research that they're doing. We know even from banking how they're trying to connect the dots across an entire customer experience. Sure they're using technology like storage, absolutely, they're thinking about computers, they're thinking more and more though about services, and the cloud, APIs, how are they going to gain all this innovation through AI, analytics, but it's about making the customer experience better. What I love about the partnership we have with Ducati is it's not just about the bikes themselves, it's about the community that they have and that they're building and that community is yes, based on data from the bike, it's about the data coming from the riders, and it's about the data they collect so they all become a stronger community as a whole. >> Yeah, Konstantin maybe explain a little bit more to your audience the role of data as Ducati see's it, and how that drives innovation in your company. >> In the world like motorbike racing team, where every millisecond counts and the difference, in how we can collect in, very quickly mode the data, and to transform the information becomes determinate if you win or not because as you know, in Qatar we win with 29 milliseconds, and this is the work that we've done, days before, analyzing data, and set up the motorcycle, in the best way, because for us, the collaboration with NetAPP is not only storage, and is not only data, but is data management, and extremely short time to respond to our business requests and work to transform the paradigm of time, and money the paradigm of data and information, and we talk about performance with our line of business, not from the technical point of view but from the extremely business oriented, the customer oriented point of view, and we collect the data from the more than 60 sensors, from the racing motorbikes and transform it with artificial intelligence and deep machine learning, in vector sensors that give us information that we cannot reach from the normal road bikes, and this improves extremely our competitiveness, and we are able to give this, experience to our riders that becomes our families, because a good thing, a good product to all our customers, and with attention of environment in the behavior of the riders we would think that the good people in the good universe act in a good way. >> And we're happy to be part of that too. >> Before we get into that, the consumer side, so your riders, Andrea Dovizioso, and Jorge Lorenzo, how has their performance improved because you're able to take data, gigs per quali day, race day, analyze it in real time, how has their performance improved as a result of your NetAPP partnership? >> As you know, the racing motorbike is not able to stop in real time during the race, not like in Formula One so you need to use the best technology to connect the bikes to our minidata center inside the box during the race. Make our strategy to set up the bike as better as we can, and the speed which we can reach the, and collect the data, put it in the telemetry software, calibrate it, make the strategy decision is very very important. And with the HCI technology we can do it. >> How are you taking the transformation that you're making on the racing side and applying it to the consumer side so that, as I think I heard on the video, Ducati wants to deliver the bike that a guy or gal rides on a Sunday by Monday, that speed, speed is the new scale as George Curion mentioned this morning, how is the consumer side of Ducati Motorsport being influenced positively to enable those consumers to have exactly what they want? >> If you see our new creation, the Dopra, the Panigale V4, this is the right example how we transform racing motorbikes to the road bikes, and we give to our customers this kind of experience because all information we manage during the Sunday we are able to put in on Monday and sell the bike that have the same performance, safety, and pleasure of riding for the final customers and we have a racing that we bring to everydays motorbike, so when you buy a bike we give you experience that before you're riding, during the riding, and after your riding when you are at your home, with our uplink connection, we use the NetAPP technology to give the best experience of connected bikes. >> So when you think about customers, especially our partnership with Ducati, in order to be customer centric, or rider centric, we really have to be data driven, and so as we think about what are all the connections and the dots of data that happen, whether it's on the bike, the rider, the community itself, how does that bike that's driven or ridden on a Sunday, how is then really performed and given to customer that next day, it's all about the data. >> I'm curious, cause how have you been able to improve that speed of scale meta HCI as part of your data driven foundation, what's kind of a before and after, are you able to deliver bikes faster? Have you transformed the customer experience like Jean was saying? >> So before NetAPP, our production plan is more difficult to be connected to all other line of business and we are not able to collect the information from our final user, our customer. And give this information to our R and D department or the shop floor, in order to be able to transform in real time our production process, and to give the best experience for everyday bikers. >> So significant business impact? >> Exactly, and with our connected bike, this has become a reality. >> Jean, just want to bring it back to NetAPP for a minute here you've been on board for about two years, George Curion talked about the transformation that NetAPP is going through itself, can you speak a little bit to the culture, you know I think back for years and NetAPP has been known for one of the top places to work, it's talking about that transformation, what can you say about what's happening inside NetAPP? >> Sure, so I think the transformation has gone through a couple of different cycles. I mean one was really around the operational efficiency we needed to be as a company to really be focused on what were the customers caring about? What were the technologies and innovations that we needed to shift to that mattered to the customer? Cloud being one of those, whether it was a private cloud, or a public cloud, we also started to think through, is the right leadership that we needed to have in the company to start making those shifts? A big part of it is the culture though and that culture is ground up, it definitely starts across the leadership team we have today, but it is infused across all of NetAPP. It is one of the reason why I joined the company, when I first started interviewing with George, he wanted me to come help him write the new story, but so much a part of a story of a company is the people themselves, and so if you think about any kind of transformation, it is definitely strategy, it's technology, it's around what you do from processes, but culture and people are the biggest part of that, and we think of the brand inside of NetAPP, the people are the biggest part of it. And who we are and what we stand for, really always leaning in to the latest technology, because it's what customers care about, if I think about the history over the last 10 to 15 years, what could have broken NetAPP, moving from Linux to Windows, moving in to virtualization, now with the cloud, we've always leaned in, because we want to care about what the customer cares about. And that's every single person inside of NetAPP that makes that happen. So I love being at NetAPP and it's an exciting place to be! >> Cultural transformation is hard to do, it's essential for IT transformation, digital transformation, security transformation, I'm curious Jean, NetAPP has such a big install base of a lot of enterprise incumbents that weren't born in digital of course you've got some amazing customers like Ducati, talk to us about how your customers, you mentioned NetAPP is good at leaning in, how do you leverage that voice of the customer to help the sustain the cultural transformation you need to really put cloud at the heart of your strategy? >> Absolutely, even with the example of Dreamworks, we just started working with Dreamworks as one of our partners to start co-engineering with them, to help them on their own transformation. And so that's taking right from the customer, what are their requirements, how are they going to take this cutting edge digital content, and then be able to make it into beautiful, engaging films that we all know and love, How To Train Your Dragon's coming out very soon and we're excited about seeing it, but those kind of partnerships really matter, and how people are leaning in to the cloud, and how they're leaning in to hypercloud, multicloud, we want to hear what our customers need and work with them to be able to really build out that technology and innovation for the future. >> Konstantin, last question for you, what are you, I know you had a session yesterday, what are you excited to hear about from you partner NetAPP at the event this week? >> I'm excited to hear about the people, it's a very put attention of the details, of what the NetAPP mean regarding the data management. And the data driven company, what is the real time feedback to the customers, and improvement of the customer experience, and one of the things that I like is the simplicity to use the NetAPP technology that give us the speed of reaction, and transform the information into knowledge, and how can I say in experience to know how to do the things >> Well Konstantin, Jean, thank you so much for stopping by and giving us a really cool, sexy example of how NetAPP is helping a company like Ducati really revolutionize the racing side and the consumer side of the businesses. And we want to encourage you to go to NetAPP.com search Ducati and you will find a very cool video, on how these two companies are working together. For Stu Miniman, I'm Lisa Martin, you're watching the Cube live, all day from NetAPP Insight 2018, Stu and I will be right back with our next guest. (techno music)

>> Announcer: Live from Miami Beach, Florida, it's theCUBE, covering UiPath Forward Americas, brought to you by UiPath. >> Welcome back to Miami, everybody. You're watching theCUBE. We're at UiPath Forward Americas. Dave Vellante with Stu Miniman. TheCUBE is the leader of, what are we the leader of? (laughs) >> Live tech coverage, Dave. >> The leader in live tech coverage. I've been blowing that line every week. Thanks for watching, everybody. We've got a great segment here. Jean Younger is here. She's the vice president, Six Sigma Leader, Security Benefit. She's to my near left, and Donna O'Donnell is here, director of key accounts at UiPath all the way from New York. Donna, thanks for coming on. >> Thank you. >> Dave: Great to see you guys. >> Thank you for having us. >> Thank you. >> All right, so we're well into day one. We're getting the Kool-Aid injection from customers and UiPath constituents, but Jean, let's start with you. Talk about your role, what's the company do, fill us in. >> Our company is an annuity company. We sell financial products for life insurance and annuities. We have about 30 billion under management, so it's a fairly large company out of Kansas. So, my role there is as a Six Sigma leader. We go in and we look at areas that need improvement or across the company, and one of the things I found, I'd been with the company almost five years now, and what I found is a lot of times, we're really good about putting manual processes in and never getting rid of 'em. We have day two issues of a tech. A tech goes live and you got a list of day two stuff that didn't get fixed, never gets fixed. It's just easier to do it, and cheaper, to leave it manual. So we have a lot of that in the company. With my job, seeing the various processes throughout the company, I was like what can we do to get rid of some of this stuff, get rid of that, get knowledge work back on the worker's plate instead of manipulating a spreadsheet or creating a report that they do every morning and it takes 'em the first 30 minutes or the first seven hours of their day is creating this one report every single day. We started looking at technology and came across UiPath. >> See, we call it GRS, getting rid of stuff. >> Jean: Yep. >> So, Donna, your job is to make these guys successful, right? >> Absolutely, so basically I just facilitate the smart people within the company. I listen to the business needs that Jean and other large clients have. We bring the resources, the products, and if we can't find it, we will absolutely find it and do everything we can to meet the needs. >> So, what's your automation story? When'd you get started? Paint a picture for us, the size, the scope. >> Okay, so last year about this time is when I started looking into it. I had just rolled out of another area that we had completely destroyed and built back up, and I was on to my next escapade in security benefit. >> Dave: Are you a silo buster, is that the new-- >> Yeah, I kind of go in and fix things. I'm kind of a fixer is basically what my job is. We'd rolled out and came back into Six Sigma to start looking and this came up. I'd seen the technology and I was like I wonder if it could work in our company. And so, we started doing kind of dog and pony show. We'd pull the different silos in, talk to 'em and say hey, here's what RPA can do for you. Is that something that you have some processes that might work? And we knew that there were processes in there, but we brainstormed with 'em for about 30 minutes. And out of that 30 minute, hour long conversation, we came out of there with about a hundred processes that people had already identified. And we kept going through there, I took that information, I built a business case, 'cause I knew to get the money, I needed to show them that there would be cost out potentially, and/or that I could take resources and move 'em into more critical areas that we didn't have the staffing. And so I had instances where, one of them that we're doing is out of our HR department. During the raise and salary time, they had two individuals that spent 60 hours a week for four months doing the same thing, same report over and over, and that's one of the processes we're actually going to implement here pretty soon. So, I came up with 'em and put the business plan together and asked for the money, and after kind of a long journey, I got the money. >> Long journey. (Jean and Donna laugh) >> It's never short enough is it? Jean, I mean, one of the things, Six Sigma is really good at measuring things. I mean, that's how you understand everything. You want to reduce variation. There was a line that really jumped out at me at the keynote is I want to go from pretty accurate to perfectly accurate, and when you were describing that there were a lot of things that were manually done. I mean, I lived in engineering for a lot of years and it was anything that somebody had to manually do, it was like oh wait, how can we change that? Because we didn't have RPA 10 years ago when I was looking at this, but how are you measuring these results? You talked about people doing repetitive tasks and the like. What other things are you finding to help get you along those reducing the variation inside the company? >> You know, it's interesting because I also teach the Six Sigma courses there, and one of my slides I've had for years teaching that class is most business processes are between 3.2 and 3.6, 3.8 sigma, which is like 95 to 98% accurate, and I said that's all the better we can usually do because of the expense that it would normally be to get us to a Six Sigma. You look at the places that have Six Sigma. It's life threatening, airplane engines. You hope they're at least Seven Sigma, those type of things, but business processes? 3.5, 3.2. But now, I get to change that because with RPA, I can make them Six Sigma very cheap, very cheaply, because I can pull 'em in, I got my bot, it comes over, pulls the information, and there's no double-keying. There's no miskeys. It's accuracy, 100% accuracy. >> So, what's the ripple effect in terms of the business impact? >> Cost savings, efficiency, customer experience. I mean, think about it. You're a customer, you get your policy, your name's wrong. How happy are you? You're not real happy. You send it back. So, no more of that. I mean, that's huge. So anything touching the customer going out of our business should be exactly how they put it on the application, especially if it was typed. Now, if it was handwritten, all hands are down on that, but if it was typed, it should be accurate. >> Donna, that's really powerful. I worked in a large corporation, we had a Six Sigma initiative and we know how much time and effort and people we were going to put in to have this little movements. >> Incremental change. >> An incremental change here to say. >> Donna: Pretty amazing. >> Blown away to tell you, Six Sigma and it's cheap. Well, what are you seeing? >> And I absolutely see. So, in addition to cost savings, it makes her more agile. But the big thing is, it makes it error free. The robots work 24 hours a day, seven days a week. Runs on itself, and Jean's going to get those efficiencies that she needed. >> How about let's talk more about the business case? I'm interested in the hard dollar piece of it. I've talked to a number of people at this show and others, and they tend not to just fire people. They got to redeploy 'em. Sometimes the CFO goes well, where's my hard dollars come from? So, where did your hard dollars come from? (laughs) >> From the CFO. (laughs) And right now, I have to prove that out yet. We're just in its infancy. We're just starting to bring up processes. In fact, yesterday and today we're dealing with several processes coming up, and so realistically, right now I've got about 300 processes. We haven't timed 'em all out yet, but I know right now that's between probably 12 and 15,000 hours of time savings that we will get on an annual basis. >> Okay, what one of the customers said today is, one example they used is they actually put it in next year's budget >> Correct. >> Which I loved. In other words, we're going to do more revenue for the same headcount, or less cost or whatever it is. That's a reasonable justification, maybe even better, right? Because it's got some forward motion to it. Is that kind of discussion and thinking come up? >> Headcount is under discussion right now. We're going through budgeting right now, and so yeah, that was part of the way that we justified the less headcount. Instead of hiring to fill another position, we would remove jobs from a certain person and be able to shift them into another role. And so that savings, non-hiring, as well as one of the processes we're doing is in our investment area. They couldn't afford to get another person. They couldn't get another headcount, so I gave them a headcount with a bot. I'm doing all their processes that they've only been able to do on a monthly basis, we're doing 'em every day. It's 52 processes they're going to do every day. It's an amazing, I gave 'em a head right there, bam. >> But we're also finding that the folks that were doing the mundane and repetitive tasks can focus on more creative work, more interesting work that they believe in and that they're motivated to do. We see that happening all the time. >> What does that mean for culture inside your company? Was there resistance at first? I have to think it's got to improve morale that it's like oh wait, I'm not getting in trouble for making mistakes now and I can go focus on things that fit better. >> You know, I think ultimately it will. Initially, there was a feeling gosh, the bots are going to take my job. But that was one thing we were pretty careful about initially going out and just saying what is it that you can't do? We all work 50, 60, some of them people are working 70 hours a week, and if I can take 10 or 20 hours away from them, they are lovin' us. There's individuals that are saying come here. I'll show you what I need. They also realize the ability of the bot to do it right all the time takes a little stress off of them, because they know they're going to get the right numbers, then, to analyze, 'cause that's a big thing. In the finance area, in the close, in the accounting area, what we're doing there is we're taking a lot of those simple process that somebody has to do and do them for them so then guess what? We can close earlier, get our books closed earlier in the month, as well as allow them longer time to analyze the results. So instead of the book's closed and then we go uh-oh, found a problem. Got to reopen the ledger and make an entry, we have less and less of that. Those are expectations that are set right now for our teams is that hey, let's get rid of the stuff that we can, and then let's see what's left. >> And Dave, I used to meet with clients and they used to say wow, this is a really interesting technology. Tell me about it. And now they're like holy crap, I'm behind the eight ball with my competition. How do we get this going quick? How do we get it going fast? In 2016, it was a $250 million industry, and by 2021, it's going to be a $3 billion industry we learned today. So it's pretty powerful. >> I think those numbers are low, by the way. >> I think they're low, too. What they said today, it's going to be a $3.4 billion industry. >> I think it's a 10x factor, probably by 2023 to 2025, I think this is going to be a $10 billion business. I've done a lot of forecasting in my life. That's just a gut feel swag, but it sort of feels like that. I think there's some pieces that are, there's some blind spots in terms of use cases and applications that we can't even see yet. Culturally, the light bulb moment, just listening to you, Jean, was the, first of all you're saying, you want your weekends back? Yeah! And then the second is it sounds like the employees are involved in sort of defining those processes, so they own it. >> And that's how we're scaling. I mean, we already realized we're a bottleneck. Our COE is a bottleneck and so we're like hey, right now, finance, it's not the end of the year. It's end of quarter, but those process are lighter than end of the year. So hey, can we get anything done? They're doing our documentation for us. They're actually taping themselves doing it, they're writing up the documentation. We come in and we look at it, and then we have a programmer doing it, but we're talking about how do we move that programming piece down to them as well, so we can get our scale up? Because I can't get through 300 processes in my small COE without a lot of help from the business. >> But Dave, most of our clients, the way that they scale very quickly is through partners. So, partners can do one of many things. They can be the developers, they can be the implementers, they could create the center of excellence, or they could pick which are the low-hanging processes. When we started off with Jean while she was going through the approval process, I brought out four partners, I gave 'em my own little mini RFP. They each had a four-hour time slot. They presented in front of Jean and we narrowed it down to two, and two of the partners are here at this event today. Most clients need to depend on partners. >> Well, that's key Donna, right? And I've said before, when you start seeing the big names that are around here, you know it's an exciting space. They don't just tiptoe and play around and games. They do some serious work for businesses. We got to turn the conversation to diversity, generally, but I also want to ask you specifically about women in tech. So, Stu and I were in a conference at Splunk earlier this week. The CEO of Carnival had a great line about diversity. He said, a big believer in diversity, of course. He's African American, and he said 40 years ago when I cracked in business, there weren't a lot of people I worked with that looked like me. I thought that was striking, Stu. I think there's always been women in tech, but not enough and a lot of stories about things that have happened to women in tech. It's changing slowly. A lot of women enter the field and then leave because they don't see a path to their future in things they like. What do you guys think about the topic, two women here on the panel today, which is our pleasure to have you. You can see, we need help. We have women working for us, (Jean and Donna laugh) but there's an imbalance there. >> You're right. >> What do you tell someone like us who's trying to find more women or more diversity and bring them into their-- >> Jean has many opinions in this space. Go ahead, Jean, I love your opinions in this space. >> I told the story at one of the UiPath events. I've been, as a lawyer, chemist, I've always been in pretty much a man's world. That's been my life in corporate America, and all along as I looked back, Donna was the first woman that sat across me to negotiate a contract. The entire time that I've been in the tech world, in the business world in corporate America, I had women working for me when I was at an insurance company negotiation very large contracts and stuff. They were on my side of the table. She was the first woman that I negotiated with on the other side of the table, and I think that's really sad, and I think we all have to look and say, how can we do better than that? How can we make us diverse? I look around here and you have all colors, all sizes, it's wonderful and it energizes you. And I am really a true believer in a really diverse workforce. I look at that and I think, 'cause they bring so many cool ideas, they think differently. Young, old, you put 'em all in a room and it's just amazing what they come up with, and I think if business leaders would hear that and think about that instead of hearing the same type of person, what's that same type of person that has your same background going to give you? He's not going to give you the transformation, or he or she. It's going to be kind of the same, what you're used to. You need that jolt, and I believe the more diverse people that we have around the table trying to solve the problem, it's amazing. I sat, last week, and I had a 22-year-old woman come into my office, Shirat, who's 30-ish and from India, and I had Amy who grew up in Topeka, hasn't left Topeka, myself. We were sitting around a table and another guy came and he probably 30. So you had a big, broad range. Somebody just out of college, me that's been out of college a long time, sitting around the table and we came up with, they thought they were dead in the water, and within 30 minutes of us just throwing different ideas out, we came up with a solution that we could continue going with. I mean, their faces were downtrodden and everything when they walked in, and when they left, we were excited, we were ready to go. Now, if we don't nurture that type of conversation, we're never going to get diversity. That's what diversity's about. If you think about it that way, wow. We went from having a problem that was a total dead stop and we weren't going to be able to proceed to 30 minutes later having a great solution and keeping running. And I truly believe it was because we had a diverse group of people around that table. >> Studies have been done of the clear value of diversity, the decisions that are made are better and drive business value. One of the challenges is finding the people, and it was pointed out to me one time, it's just because you're looking inside your own network. You got to go outside your own network, and it takes longer, it's more work. You just got to allocate the time, and it's good advice. It's hard work, but you got to do it to make change. >> And sometimes you got to take a chance. Sometimes, because it is outside of your network, you're not comfortable necessarily with the answers they give you or the way they approach a subject. I mean, you've got to feel comfortable, and CEOs and CFOs and the C-suite has to start thinking about that, because if you wanted to be transforming, that's how you transform. You don't transform thinking the same way every day. You're not going to transform. >> Let me ask you a question. You said you're a fixer, so I wrote down the adjectives that I would use to describe a fixer, and I want to know if this has been the way in which people have described you. You got to be smart, you got to be a quick study, you got to be a good listener, you got to be confident, self-assured, tough, decisive, collaborative. Are those the adjectives that have described you as a fixer over the years? >> Yes, I think those are you qualities, by the way. >> I don't doubt they're your qualities. Is that how people refer to you in business? >> Yeah, I think so. I mean, I've done the test where they say are you a collaborator or do you push? And I get the mix. I'm either a collaborator or I'm a person that's pushing her own belief, and I know exactly who said I was a person that was only pushing her own belief, and I know the ones that said I was a collaborator. But that is, you got to be collaborative. >> I believe you have those attributes, but the reason for my question is a lot of times when it's a woman fixer, those aren't the adjectives that they would use to describe you. It would be abrasive or combative. I mean, you hear adjectives like that. Same exactly attributes as a male fixer, just described differently. Has that changed in your view? >> I go about things probably a little bit differently than men do, and I've had to adapt. Like I said, I've been a chemist. What was I? 8% of the community of chemists is a woman, so I've had to adapt my style. And I do a lot of drive-bys, I do a lot of one-on-one discussions over the lunch, over hey, do you have a few minutes? I need to talk to you. So, I do a lot of that type of collaboration before I ever get into that big meeting where I'm pushing my one direction. I've got my buddies all lined up already, and so I don't think it feels like I'm abrasive or that I'm, because I've fought those battles privately already. So maybe I've adapted my style that I don't get those types of reactions, but that's what you got to do. You've got to learn how to work the system. >> At the same time, I think that, and this is a compliment, I think Jean on the outside, it's tough to earn her respect in the beginning, but if you do, there's nobody more fiercely loyal than Jean. So you got to earn your way in there, and that's got to be consistent, like a 15-step process to get there. (Jean laughs) >> Yeah. >> And you can't let go because if you let go-- >> Dave: They're hard to get, huh? >> She's going to make you think on number six day you're not good enough, and then you just got to keep on going. So I understand what you're stating, Dave. You have to keep on going, and if you get there there's nothing that Jean wouldn't do for you. As she's here, she's on the advisory board of UiPath. She is the most, once you prove yourself, that's it. It's going to be hard to change that, but it's not easy to get there. >> So this inherent bias, people are tribal in nature and they're biased. Does things like automation and RPA, AI, does it eliminate that bias or does it codify it? >> Wow, interesting question. I don't know, I don't know the answer to that. >> Dave: I don't think anybody knows. >> I don't know that either. >> I've never really thought about it. I mean, to me RPA is just another tool in my toolkit, you know? And if I can fix it with AI, great, or UiPath, if I can use that to fix it with RPA, great. If I need another toolkit, I'll go use that toolkit. But I do know that it's a way that individuals, you can get a lot of young people into your organization that have great ideas. I'm stocking up with interns and I'm using, like I said, woman we hired, she was my intern, graduated in May, and the next day she had a full-time job. And she's done a phenomenal job. And that's what RPA has done for our business, because it's an entree in that then they're in and they're doing this simpler technology, then people see how wonderful they are and they can go and move into bigger and better roles. And that's what I'm trying to encourage is get some really smart people in with this tool, and that's what UiPath has enabled, I think, people that maybe they're not the best coders, or maybe they're not the best BAs, but you put that together and they're knocking it out of the park. The young ones are knocking it out of the park on this technology. It's amazing. >> We did several blockchain and Crypto conferences this year, you want to talk about diversity, and I mean it's old money, it's new money, it's women, it's people in turbans, it's people with color. It's actually quite amazing, and one of the older investors, I asked him what's your secret? He said, "I surround myself with millennials." (laughs) >> Jean: Correct. >> That was good advice, but very diverse crowd in Crypto. You don't have to be Ivy League, Silicon Valley and white, Caucasian, to be successful, right? >> Dave, I was representing RPA at a Women in Tech conference last week in the FinTech environment, and I was talking, sitting next to Crypto and Bitcoin and at the end, the lines lined up for RPA. And I would say to the girls, why are you lined up for RPA? And they basically said you are the disruptor. RPA is the disruptor. There was a speaker here today that says RPA's the gateway drug to artificial intelligence, which is absolutely true. RPA is operational right now, it's working today, and there's elements of AI that are here today, but there's elements that are future technology. But RPA's completely ready to go, operational, mainstream in most enterprise companies. >> And I know we kind of went off topic there but it's relevant and it's important and it's a passion of ours, so really appreciate you guys coming on theCUBE. >> Thank you. >> Thank you, Dave. Thank you, Stu. >> All right, keep it right there everybody. Stu and I will be back with our next guest right after this short break. You're watching theCUBE live from UiPath Forward in Miami. Right back. (upbeat electronic music)

>> From Sunnyvale, California in the heart of Silicon Valley, it's theCUBE! Covering Accelerate Your Journey to AI. Brought to you by NetApp. >> Hi, I'm Peter Burris with Wikibon and theCUBE and we're broadcasting from theCUBE here from NetApp's data visionary center today. We've got a number of great conversations with some NetApp executives, specifically about the role that NetApp and AI are going to play together as the market evolves. And we're joined first by Jean English, who's a Senior Vice President and CMO of NetApp. Jean, welcome to theCUBE. >> Great, thanks Peter, nice to see you again. >> Lot of great stuff to talk about, Jean, so let's start with this interesting relationship, NetApp, AI, the centerpiece of it is data. >> Yes. >> What does that mean? >> Absolutely. Well I think just to start, technology is changing everyday lives. Digital transformation really tops the strategic agenda of most CEOs today. When you think about what does that mean in terms of data, data is the lifeblood of an organization. And it has to really be able to seamlessly flow through that organization to really add value. So we think of data as the heart, and when we think about data and AI, we want to accelerate the journey to AI. But to do that, you have to be able to holistically manage your data. >> So as we think about the need to manage data, that says that there's a number of challenges that customers face. You have to be able to bring great technology, but in ways that allow customers to do things specifically with it. So talk a little bit about the relationship that NetApp is developing with its customers to try to ensure that that journey to AI can be accelerated. >> Absolutely. Well the first is really around when we think about digital transformation, and especially as AI is the heart of it, how are they going to get more connected to their customers? A better customer experience. An experience that allows them to feel connected not only to the experience they have with the company, but to their peers, and to their customers, as well as suppliers. We also know that we want to be able to think about what do customers need to do to create new value? And new business opportunities, new services, new companies? Companies are also looking at how do they optimize their operations? How do they even take out the cost of back office, and take out that capital to be able to fuel innovation, especially when it comes to customer engagement. AI is becoming more and more a part of how companies are doing each of those. They're using those analytics and insight to be able to power through that digital transformation, which is now really being seen as a data-driven digital transformation. >> Well, we certainly agree at Wikibon, SiliconANGLE, and theCUBE. We believe that the relationship between business and digital business is, in fact, that digital business uses data as an asset. >> Mhmm. >> There's a special class of customer, though, as we move forward, and that is some of the hyperscalers, the big cloud suppliers, who are participating in this process of driving so much innovation in the industry. Serving them is a particular challenge. Talk to us a little bit about how that works. >> Sure. Well, we are definitely seeing that there is a certain class of customers that are starting to think about what do they do to thrive on data? And not only can they thrive, but they have to be able to put data as an asset. It has to be at the top of the strategic agenda of the company. It has to be able to seamlessly flow through that company. We're seeing that they're called data thrivers. Those thrivers are set apart. They're driving bottom line revenue, they're driving increased customer acquisition, they're seeing definitely higher profit margins. But in all those results we notice that there's a few things they're really doing right, and they're getting it right. One of those is that they're using the cloud. They're using public clouds. They're using private clouds. They're acquiring more dev-op skills. They're hiring data scientists. They're really being able to think about how do they hire digital officers, data officers, and a lot of that is around how they want to leverage AI. We know that over 50% of companies will start to adopt AI next year. We know that they're going to start to leverage AI to gain better insight. These new roles of people are definitely the ones who are being able to think about how did they manipulate that data, how did they use that data to have a competitive advantage, and how did they leverage the cloud to get more services like AI from these big cloud providers. >> Well, it's pretty clear as you try to service that broad a range of potential customers that you have to have a couple of touchstones to keep coming back to. Increasingly, design has to be one of them. Thinking in terms of design great products, but also designing engagement, designing how you work with customers, designing how you work with partners. Now, you have, along with your team, has bought some of that data first, data-driven notions into how you've designed this data visionary center. Talk to us a little bit about how you have been using design to ensure that great experience across the board from NetApp. >> Absolutely. Well first, as NetApp thinks about how to holistically manage data, that was really the inception of data fabric. And data fabric was a vision, it was a strategy years ago. And we've been really working to see how do we bring that strategy alive? And being that data visionary for our customers thinks about from the edge, to the core, to the cloud. And what do we do to help bring that data fabric across so you can seamlessly manage data, integration points across all those environments, you can migrate data to the cloud, you can make sure you're consuming data services, like analytics and AI, and you're really being able to bring that value back. AI is at the center of that. We wanted to design an experience that brought data fabric to life for our customers. One, how did they modernize their current architectures? Especially with cloud-connected flash and what we're doing with AI. We wanted to make sure that we were thinking about "How did they build these private clouds? What do they need to do to really bring out applications at speed?" Third is we wanted to inspire innovation with the cloud. And the work we're doing with the cloud providers. We've had new services like cloud volumes that have been launching with AWS, with Azure as well as Google. And with all of the biggest clouds, we've been thinking about how do we bring that customer experience to life? That design comes forward through the data visionary center, where we are today. This center is where we want to actually have customers come in and be inspired by what they can do in their own digital transformation journey. We want to build trust with those customers and partners. We want them to know that we understand their industry, we understand their needs, we understand what's happening in the market. IOT, AI, what's happening with securing data. How did they think about leveraging the cloud to really maximize business impact? We want to be able to have frank conversations. Inform each other of our strategies. How did they then able to interpret those and internalize that information? The whole data visionary center's been based on "How do we help them to be able to grow? How do they partner with us so they can leverage our services to help them to maximize the value of data?" So we provide those opportunities. Hands-on kiosks, demos, learning, even being able to do what we've done with NVIDIA with an advanced solution around even our events at solution where they can start to play with AI in real time. Then we want to be able to enjoy the conversation here at the data visionary center, and talk about next steps in the journey ahead. So we're excited about the data visionary center. We just opened it a few months ago, and we're thrilled to be able to invite customers and partners to be here. >> So let's extrapolate, extend beyond the data visionary center and make the observation that marketing broadly has become altered, changed, transformed as a consequence of using data. Marketing at NetApp in particular is interesting because you're fundamentally marketing data-driven as a concept. So how is marketing's evolved experience with data informing how NetApp broadly engages customers and builds products? >> CMOs are becoming one of the top functions to really drive digital transformations. When you think about how do you connect and engage with customers more? How do you engage with them on a personalized level? How do you ensure that you're having that constant communication, online, offline? And continuously being able to build that relationship. Marketing's at the center of that. We're excited that we're a data-driven organization, and as a data-driven organization, we're having real business impact to the business and real customer engagement. We're excited that we're at the heart of what we're doing to transform the business. Not only from our branding and how we think about reinventing NetApp, we are data-driven company. We are data-driven as we think about that aspiration for our customers. Our data visionary concept is about how do we inspire people to want to bring all that data together and really simplify and integrate, and then unleash that potential for their own companies. Marketing is at the center of how we're engaging people, especially in the cloud. And as we have a no-touch experience and customers are engaging with us to be able to download trials, being able to see demos, being able to watch other customers and where they are on their own journey. But being able to surface that, again, digitally as well as offline and personal engagement. Analytics, big part of what we're doing to understand customer needs better. Understanding those needs from the solutions they expect from us, understand their needs from what they're enduring in the market, and then being able to help the company think about that in terms of road maps, think about that in terms of key messages, think about that in terms of real solutions and real engagement. >> Jean English, Senior Vice President and CMO of NetApp, thanks again for being on theCUBE >> Thanks, Peter. >> And talking about data-driven and marketing. >> Thank you. Nice to see you. >> Good to see you again.

>> Announcer: Live from Berlin, Germany. It's theCube, covering NetApp Insight 2017. Brought to you by, NetApp. >> Welcome back to theCube's live coverage of NetApp Insight 2017, I'm your host Rebecca Knight along with my co-host Peter Burris. We are joined by Jean English. She is the Senior Vice President and Chief Marketing Officer of NetApp, thanks so much for comin' on the show. >> Thank you for having me, we're glad you're here with us to join us at Insight Berlin. >> We're always excited to do anything with NetApp. So, talk a little bit about NetApp's digital transformation. You're now at a year's long transformation from storage, your legacy, to data. Talk a little bit about your positioning in the market. >> Sure, so I think people have previously thought of NetApp as storage, and what we're so focused on now is data. And why data? Because that's what we hear from our customers, our partners, the analysts, is what is really topping their needs right now. If we think about how companies are transforming, they're having to think about digital transformation is topping the list. It's topping the most strategic agendas of most CEOs. But what happens is they have to think about the data. It has become a life blood of their business, and as it seamlessly flows through that business, and what does it mean to either optimize their operations, if they've gotta increase their customer touch points, do they have to create new product services, and even businesses. So we feel like right now that is where our focus is on data, and it's so much a part of our heritage that we look to the future as well. >> One of the things that you're working on now is helping customers use data in new, exciting, innovative, creative ways, can you talk broadly about your approach to that, and how you're drawing inspiration on customers and then empowering them? >> Absolutely, so we really try to think about, what is our purpose? And our purpose could be true to our heritage from 25 years ago, we just celebrated our 25 year anniversary this past spring, and it is to empower our customers to change the world with data. Just a few of those, we've seen now, especially in hybrid cloud environments, customers have to think about how are they gonna simplify to integrate data across on-prem, cloud environments, to accelerate digital transformation. One example of that is EidosMedia. We love their story, because their talking about how to get news stories, real time, through a cloud platform, into the hands of journalists that can publish real time live insights. Real time journalism, and so when you think about the speed that has to happen with creating stories, getting 'em published, getting 'em out to news networks, that's data. And it's a good data story. >> When you think about the data story though, a lot of people talk about how data is a fuel, or data is. And we tend to think, at least at SiliconANGLE Wikibon, that that's probably not the best analogy, because data's different from other resources. Most resources share the economics of scarcity, you can do this, or you can do that, but data's different because data could be copied, data can be shared. But data also can be appropriated inappropriately. Could you talk a little bit about the relationship or the direction that NetApp's taking to on the one hand, facilitate the sharing of data strategically while at the same time, ensuring that proper security and IP controls are placed on it. >> So I think people are looking to make sure that they can share freely data, and seamlessly integrate data across multiple sources. Right now what we find is that whether it's because you've had data that's been on-prem, and maybe that's more structured. Now we're startin' to see more unstructured data. So data's becoming a lot more diverse. People are constantly looking for the latest source of truth of data, so dynamic, and because it's so distributed across environments, people are trying to figure out, how do you integrate data, how do you share data, but it's all about simplicity, 'cause they need it to be efficient. They need to make sure that it's protected, so security is top of minds, so data protection is the upmost of importance. They're looking for ways to embrace future technologies. And whether that's thinking about different cloud environments, SAS applications, and then how do they create the most open opportunities. A lot of people aren't just putting their data in one cloud, what we're finding is, is it's a multi-cloud world, and they're looking for a holistic solution to more easily and seamlessly manage their data through those environments. >> But the infrastructure has to move from as you said, a storage orientation towards something that's going to facilitate the appropriate sharing and integration of data. Like a fabric. >> Yes. >> Can you talk a little bit about that. >> So we started the conversation around data fabric, it was one of the first people to really talk about data fabric in the market back in 2013. And this vision was about how do you seamlessly be able to share and integrate data across cloud and on-prem environments. That has become so true in how we've been building out that data fabric today. We just launched a few weeks ago that we are the first industry leading storage data service in the Microsoft Azure console, so that people can easily be able to, can do complete storage capabilities in cloud storage, in Microsoft, we've also been developing solutions to make sure that, maybe if you're not wanting to do everything in Office365 and Azure, you wanna back it up to AWS, so how do you have better backup capabilities? Sharing of data across clouds. We're also seeing that you may wanna sync data, so maybe once you put data into the cloud, and you run analytics or even machine learning, how do you then get data back? Because you wanna make sure that you're constantly being able to look holistically at your customers. This notion of one cloud, to back to on-prem, multi-cloud environments, has been critical as we think about customers and where they're going. >> One of the things we're also hearing about at this conference is, this is the day of the data visionary, and this is where people who are thinking about how to store data, use data, extract data, find value in the data. The demands on them, the pressures on them, are so intense. How is NetApp helping those people, sort of understanding where they are, not only in their businesses, but also in their trajectories of their careers, and then helping them move forward. >> We've been really thinking about who is really using data to disrupt, and are this disruptive use of data to really drive business results. It's not just about having the data, it's about how are you gonna have an impact on the business. So we start to think about this notion of who is a data thriver? Who's thriving with data versus who's just surviving and in fact, some are even resisting. So we actually partner with IDC to launch a study on data thrivers to look at who is truly looking at driving new revenue streams, attracting new customers, how are they able to use data as correlistic part of their business. Not some one off or side project to help do the digital transformation, but what was gonna drive really good business results. Data as an asset. Data across business and IT. And we see new roles are emerging from this. We're seeing that, Chief Data Officers, there's Chief Digital Officers, Chief Data Scientists, Chief Transformation Officers. All new roles that have been emerging in the last couple of years, but these data thrivers are seeing tremendous business impact. >> So, what is it that separates those people, I mean I think that, those really, those companies and those business models, and what are sort of the worst case scenarios for those companies that are just surviving and not necessarily thriving, in this new environment. >> Yeah, I think it's interesting, we're seeing that companies that actually put data at the center of what they do. So we think of it as a data-centric organization, are seeing 6x in what they're seeing in terms of being able to drive real customer acquisition. When we think about what it means to drive operational efficiency, when we think about 2x times in terms of profitability, real bottom line results, compared to people that are simply just surviving with data. What's interesting is that when we start to think about what are the attributes of these people, so business and IT working together in unison. These roles in fact that are emerging are starting to become those catalysts and change agents that are bringing IT and the business more together. We're also seeing that when you think of data as an asset, even to the bottom line, how does data become more critical in terms of what they see in terms of being a differentiated advantage for the company. Also, thinking through quality, quality, quality. You've gotta make sure that the data is of highest quality and it's constantly being cleansed. Then in terms of how do we think of it being used across the business, it's not just about holding data and locking it away behind a firewall. Data more today is so dynamic, distributed and diverse, that you have to let it be utilized and activated across the business. And then to think through, it's starts not just in terms of what customers are using and seeing from data, what they can actually see in terms of customer touch points and having a better customer experience, but then how do you make sure it even comes back to the development to create new products, create new services, maybe even eliminate waste. Stop doing product lines based on what they're seeing from actual usage. So it's a pretty fascinating space right now, but the data thriver is the new thought we're thinking in terms of getting that out in the market and really sharing more so with our clients, so that they can benchmark themselves as well. >> So, you're a CMO. >> Yes. >> You're telling a story, but you also have operational responsibilities. How would you tell your peers to use data differently? >> Well, I think there's a couple things. I mean, for me data's the life blood of how we think about how we actually create a better customer experience. We're using data constantly to better understand what are our customer's needs, and those customers are evolving. Before, in the loyalist that we love was storage architects and admins, we're starting to see that people are thinking about how to use more hybrid cloud data services with CIOs. How are they gonna look at a cloud strategy? With DevOps, how are they gonna create, deploy, and, applications at speed? How are they gonna be able to help to really think through, what are they gonna do to drive more analytics and better workload usage, and efficiencies? Our clients are evolving, and when we think about how do you reach those clients differently, we have to know who they are. We have to use data to understand them. We have to be more personalized. We just relaunched our entire digital experience, so that when we try to look at how do you bring people into something that's more customized, more personalized, what does it mean to be a cloud architect that's thinking about a data backup and protection plan. What does it mean for someone in DevOps who's thinking about how do I actually create and deploy an application at speed? How do you think about someone that's gonna look at the needs from a CIO, so much differently than before. But, using data, using customization, thinking about an engaging experience, bringing 'em through that experience so that we solve their business challenges. We use data and analytics every day. I think of us as being the new data scientists. People say, is it art or is it science and marketing? I'm like, it's a little bit of the storytelling, absolutely, we have to lead with stories, but the data and the analytics is where we really understand our customers best. So using analytic models, using predictive models, using more ways in which we can actually reach customers in new ways we never have before through social. But bring them into a new conversation. Analytics, analytics, storytelling, and understanding, getting closer to new clients like we never have before, and then thinking through how do we use that full-circle loop of learning to get better and better in how we engage our customers in ways they want to engage with us. >> I wanna switch gears just a second, and I know that you've just been nominated as an International Board Member. You were a Board Member before, of Athena of the Triangle, which is about supporting and inspiring women in the technology industry. As we know that this is the dearth of women, technologists, is a big problem in the US and globally. Can you tell us a little more about the organization and what you're doing? >> So, Athena International is really about, how do you promote women's leadership? It's across the world, in fact we just launched some very exciting initiatives in China where I lived for a year, and the President of Athena International is a friend of mine, and she was really looking at how do you foster growth, especially in emerging markets and countries where women's leadership can be so profound in terms of how do you impact the business, government, and market, and really overall global success. Athena is focused on, is technology, but it's also with women in many industries. But really, how do you gain the powerful mentorships, how do you gain powerful access to programs, to having more access to expertise that can help them to think through business models, business cases. How do they grow their business, it might be from financial to career counseling, to mentoring on marketing, but it's really thinking through women's leadership as a whole. >> And is NetApp also working on behalf of those, of that cause too? >> We're really focused on, today in fact we're gonna be hosting the, the annual Women in Technology Summit. So we're so focused on how do we think about developing women in technology, how to think about that across not only our employees, but our partners and our customers, and it's not just about women, this is men and women working together to determine how do we stop the fact that we've got to get more access to women in mentorships and sponsorships, and really really driving how we have leadership as we grow, really grow into our careers, and can drive more business impact. >> Great. Well Jean, thanks so much for coming on theCUBE, >> Thank you. >> It was really fun talking to you. >> Absolutely, thank you both. >> I'm Rebecca Knight for Peter Burris, we will have more from NetApp Insight, here in Berlin, Germany in just a little bit.

>> Announcer: Live from Berlin, Germany. It's The Cube, covering NetApp Insight 2017. Brought to you by NetApp. Welcome back to The Cube's live coverage of NetApp Insight 2017. I'm your host, Rebecca Knight, along with my cohost, Peter Burris. We are joined by Jean English. She is the senior vice president and chief marketing officer of NetApp. Thanks so much for coming on the show. >> Thank you for having me. >> We're glad you're here with us to join us at Insight Berlin. We're always excited to do anything with NetApp. So talk a little bit about NetApp's digital transformation. You're now at a years long transformation from storage, your legacy, to data. Talk a little bit about your positioning in the market. >> Sure. I think people have previously thought of NetApp as storage. And what we are so focused on now is data. And why data? Because that's what we hear from our customers, our partners' analysts, is what is really topping their needs right now. And when we think about how companies are transforming, they're having to think about digital transformation is topping the list, is topping the most strategic agendas of most CEOs. But what happens is they have to think about the data and how does it become a lifeblood of their business? How does it seamlessly flow through that business? And what does it mean to either optimize their operations, if they've got to increase their customer in touch points, if they have to create new products, services, and even businesses. So we feel like right now that is why our focus is on data. And it's so much a part of our heritage that we look to the future as well. >> So, one of the thing's that you're working on now is helping customers use data in new, exciting, innovative, creative ways. Can you talk broadly about your approach to that and how you're drawing inspiration from customers and then empowering them? >> Absolutely. We really try to think about what is our purpose. And our purpose could be true to our heritage from 25 years ago, we've just celebrated our 25 year anniversary this past spring. And it is to empower our customers to change the world with data. And just a few of those we see now, especially is hybrid cloud environments, customers have to think about how are they going to simplify and integrate data across on-prem, cloud environments, to accelerate digital transformation. One example of that is EidosMedia. We love their story, because they're talking about how to get new stories, real time, through a cloud platform into the hands of journalists that can publish real-time live insights, real-time journalism. And so, when you think about the speed that has to happen with creating stories, getting them published, getting them out to news networks... That's data, and it's a good data story. >> When you think about the data story, though, a lot of people talk about how data is a fuel or data is... And we tend to think, at least it's looking like a Wikibon, but that's probably not the best analogy. Because data's different from other resources. Most resources share the economics of scarcity. You can do this or you can do that. But data's different, because data could be copied, data could be shared, but data also could be appropriated inappropriately. Could you talk a little bit about the relationship, or the direction that NetApp's taking to, on the one hand, facilitate the sharing of data strategically while at the same time ensuring that proper security and IP controls are placed on it? >> Absolutely. I think people are looking to make sure they can share freely, data, and seamlessly integrate data across multiple sources. Right now what we find, whether it's because you've had data that's been on-prem, and maybe that's more structured. Now we're starting to see more unstructured data. So data's becoming a lot more diverse. People are constantly looking for the latest source of truth of data. It's so dynamic, and because it's so distributive across environments, people are trying to figure out how do you integrate data, how do you share data. But it's all about simplicity because they need it to be efficient. They need to make sure that it's protected. So security is top of minds, data protection is utmost of importance. They're looking different ways to embrace future technologies. And whether that's thinking about different cloud environments, Sass applications, and then how do they create the most open opportunities. A lot of people aren't just putting their data in one cloud. What we're finding is it's a multi-cloud world and they're looking for a wholistic solution to more easily and seamlessly manage their data through those environments. >> The infrastructure has to move from a storage orientation towards something that's going to facilitate the appropriate sharing and integration of data. Like a fabric. You could talk a little bit about that. >> Yes. We started the conversation around data fabric. Was one of the first people to really talk about data fabric in the market back in 2013. And this vision was about how do you seamlessly be able to share and integrate data across cloud and on-prem environments. That has become so true in how we've been building out that data fabric today. We just launched a few weeks ago that we are the first industry leading storage data service in the Microsoft Azure console. So that people can easily be able to do complete storage capabilities in cloud storage in Microsoft. We've also been developing solutions to make sure that maybe if you're not wanting to do everything in Office 365 and Azure, you want to back it up to AWS. So how do you have better backup capabilities? Sharing of data across clouds. We're also seeing that you my want to sync data. So maybe once you put data into the cloud and you run analytics or even machine learning, how do you get data back? Because you want to make sure that you're constantly being able to look wholistically at your customers. So this notion of one cloud to back to on-prem, multi-cloud environments has been critical as we've been thinking about customers and where they're going. >> One of the things we're also hearing about at this conference is that this is the day of the data visionary, and this is where people who are thinking about how to store data, use data, extract data, find value in the data... The demands on them, the pressures on them are so intense. How is NetApp helping those people? Understanding where they are, not only in their businesses, but also in their trajectories of their careers. And then helping them move forward. >> Absolutely. We've been really thinking about who is really using data to disrupt. And are this disruptive use of data to really drive business results. It's not just about having the data. It's about how are you going to have it impact on the business. So we started to think about this notion of who is a data thriver. And who's thriving with data versus who's just surviving. And in fact, some are even resisting. So we actually partner with IDC to launch a study on data thrivers. To look at who is truly looking at driving new revenue streams, attracting new customers. How are they able to use data as a corlistic part of their business? Not some one off or side project to help through the digital transformation, but what was going to drive really good business results, data as an asset, data across business and IT. And we see new roles are emerging from this. So we're seeing chief data officers, chief digital officers, chief data scientists, chief transformation officers. All new roles that have been emerging in the last couple of years. But these data thrivers are seeing tremendous business impact. >> So what is it that separates those people? I think of those companies and those business models. And what are some of the worst case scenarios for those companies that are just surviving and not necessarily thriving in this new environment? >> It's interesting. We're seeing that companies that actually put data at the center of what they do, so we think of it as a data-centered organization, are seeing 6x in what they're seeing in terms of being able to drive real customer acquisition. And we think about what it means to drive operational efficiency. When think about 2x times in terms of profitability, real bottom line results, compared to people that are simply just surviving with data. What's interesting is that when we started to think about what are the attributes of these people. So, business and IT working together in unison. These roles, in fact, that are emerging are starting to become those catalyst and change agents that are bringing IT and the business more together. We're also seeing that, when you think of data as an asset, even to the bottom line, how does data become more critical in terms of what they see, in terms of being a difference and an advantage for the company. Also, thinking through quality, quality, quality. So you've got to make sure that the data is of highest quality and it's constantly being cleansed. Then, in terms of how do we think of it being used across the business. It's not just about holding data and locking it away behind a firewall. Data, more today, is so dynamic, distributed, and diverse that you have to let it be utilized and activated across the business. And then to think through, it starts not just in terms of what customers are using and seeing from data, but they can actually see, in terms of customer touch points and having a better customer experience. But then how do you make sure it even comes back to development to create new products, great new services, maybe even eliminate waste? Stop doing product lines based on what they're seeing from actual usage. So it's a pretty fascinating space right now. But the data thriver is the new thought we're thinking in terms of getting that out in the market and really sharing that more so with our clients. So that they can benchmark themselves as well. >> Peter Burris: So, you're a CMO? Yes. You're telling a story, but you also have operational responsibilities. How would you tell your peers to use data differently? >> Well, I think there's a couple things. For me, data is the lifeblood of how we think about how we actually create a better customer experience. We're using data constantly to better understand what are our customers' needs? And those customers are evolving. Before, and the royalists that we love with storage architects and admins. We're starting to see that people are thinking about how to use more hybrid cloud data services. With CIOs, how are they going to look at a cloud strategy? With DevOps, how are they going to create deploying and applications at speed? How are they going to be able to help to really think through? What are they going to do to drive more analytics and better workload usage and efficiencies? So our clients are evolving. And when we think about how do you reach those clients differently? We have to know who they are. We have to use data to understand them. We have to be more personalized. We just relaunched our entire digital experience so that when we try to look at how do you bring people into something that's more customized, more personalized? What does it mean to be a cloud architect that's thinking about a data backup and protection plan? What does it mean to someone at DevOps that's thinking about how do I actually create and deploy an application at speed? How do you think about someone that's going to look at the needs from a CIO so much differently than before? But using data, using customization, thinking about an engaging experience, bringing them through that experience so that we solve their business challenges. We use data in analytics everyday. I think of us as being the new data scientists. People say, is it art or is it science and marketing? And I'm like, well it's a little bit of story telling. Absolutely we have to leave the stories. But the data, the analytics is where we really understand our customers best. And so using analytic models, using predictive models. Using more ways in which we can actually reach customers in new ways we never have before through social. But bring them into a new conversation. So, analytics, analytics, story telling and understanding, getting closer to new clients like we never have before, and then thinking through how do we use that full circle loop of learning to get better and better at how we engage our customers in ways they want to engage with us. >> I want to switch gears just a second. And I know that you've just been nominated as an international board member. You were a board member before of Athena of the Triangle, which is about supporting and inspiring women in the technology industry. As we know, the dearth of women technologists is a big problem in the U.S. and globally. Can you tell us a little bit more about the organization and what you're doing? >> Sure. So, Athena International is really about how do you promote women's leadership? And it's across the world. In fact, we just launched some very exciting initiatives in China, where I lived for a year. And the president of Athena International is a friend of mine and she was really looking at how do you foster growth, especially in emerging markets in countries where women's leadership can be so profound in terms of how do impact a business, government, and market and really overall global success. Athena is focused on its technology. But it's also women in many industries. But really, how do you gain the powerful mentorships? How do you gain powerful access to programs? To having more access to expertise that can help them to think through business models, business cases. How do they grow their business? It might be from financial, to career counseling, to mentoring on marketing, but it's really thinking through women's leadership as a whole. >> And is NetApp also working on behalf of that cause too? >> Today, in fact, we're going to be hosting the annual women in technology summit. And so we're so focused on how do we think about developing women in technology. How to think about that across not only our employees, but our partners and our customers. And it's not just about women. This is men and women working together to determine how do we stop the fact that we've got to get more access to women in mentorships and sponsorships. And really really driving how we have leadership as we grow into our careers and can drive more business impact. >> Great. Well Jean, thanks so much for coming on The Cube. It was really fun talking to you. Absolutely. Thank you both. I'm Rebecca Knight for Peter Burris, we will have more from NetApp Insight here in Berlin, Germany in just a little bit.

>> Announcer: Live from Las Vegas, it's The Cube, covering NetApp Insight 2017, brought to you by NetApp. >> Okay, welcome back everyone. We're here live in Las Vegas, Mandalay Bay. This is The Cube's exclusive coverage of NetApp Insight 2017. I'm John Furrier, the cohost of The Cube, co-founder of SiliconANGLE Media with my cohost, Keith Townsend with CTO Advisors. Our next guest is Jean English. She's the Chief Marketing Officer of NetApp. Great to see you, thanks for having us, and thanks for coming on The Cube. >> Oh, thank you, thank you guys for being here. >> So NetApp is no longer a storage company, we learned. But then last year, now this year, you're a data company. >> Jean: (laughs) That's right. >> The brand promise is still the same. Take us through, as the Chief Marketing Officer, you have to, it's a complex world. One of your concepts here we've been seeing is winning while in a tough environment and IT is a tough environment. I got application development going on. I got DevOps. I got data governance. I got security issues, internet of things. It's a challenging time for our customers. How is your brand promise evolving? >> So we really see that NetApp is the data authority for hybrid cloud, and the amazing thing is is that what we see is our customers aren't talking to us about storage anymore. They're talking to us about data, and what their data challenges are, and most companies are trying to think through if they're going to transform, how are they going to harness the wealth of the data. What are they going to do to maximize the value of the data? >> And the cloud too is center stage, 'cause the cloud is a forcing function that's changing the relationship of your partners, VARs who has a lot of folks on talking about the dynamics with customers around multiple clouds. We saw on stage the announcement with Microsoft. Congratulations. >> Jean: Thank you. >> So you've been in Amazon for a while. We've been covering that, but the on-premise work still is growing, where you have the data from Wikibon Research came out shows that the on-premise true private cloud, which is defined as cloud operation business model is actually growing. However, the decline in automation of non-differentiated labor is declining by 1.5 billion over the next five years, which means the SAS market is going to continue to explode and grow, so the on-premise is actually growing, as is the cloud. How does that change the narrative for you guys, or does it, or is that a tailwind for NetApp? >> We think it's a complete tailwind in for NetApp. When we think about data today, we see that it's really becoming more distributed across environments. It's definitely more dynamic, as you're looking for the latest source of truth. And the diversity of data, especially with machine learning. I mean, it is exploding. So, how do you start to be able to build that data together? We really think of it as that our customers want to maximize that value and the only way to do that is to start to think about how do they bring it together, and how do they get more insight from that data, and then how do they have more access and control of that data, and then the most questions we usually get from our customers around, how do I make sure it's secure? But the really big point is is that, as we think about what NetApp is doing, it has been about three things that we see with our customers. They have to make sure that they're modernizing what they have today, and that goes to the on-prem environment, so if it's going to be that they got to accelerate applications, they want to make sure that they have that. But this notions of building clouds, even building private clouds. And we think of that as a next-generation data center, especially with DevOp environments. Then harnessing the power of the cloud and hybrid cloud world. And if they are not able to really leverage the cloud for SAS applications, if they're leveraging the cloud for backup, or even disaster recovery, data protection, that's where we see that these three imperatives, when they come together, that they're truly, truly able to unleash the power. >> So we saw on stage, CEO George Kurian talking about his personal situations in light of what's happened in Las Vegas here. Data is changing the world, and your tagline is "Change the world with data." So I got to ask you, obviously, data, we see a lot of examples in society and also personal examples of data being harnessed for value. The cloud can be great there, it's all on-prem. How do you guys position NetApp as a company? I know there's a lot of positioning exercises in marketing you do, but positioning is really important. That's what you do. The tagline is kind of the emotional aspect of it, okay, changing the world, let's change the world with data. I believe that. But what's the positioning of NetApp? How would you say that the positioning- What's the positioning statement of NetApp? >> The positioning statement of NetApp, I think we've really seen a big break in the positioning in the last couple of years. And why is because the customers are demanding something different. They're really looking for more hybrid cloud data services. And what are those data services that accelerate and integrate data, and that notion of on-prem and in the cloud, that's where we see what's going to happen to accelerate digital transformation. And so, this notion of yes, thought about as storage before, customers are demanding more for their data and they need data services, especially in hybrid environments to really be able to drive their business. >> The old expression, "Position it, they will come." And you guys have done a good job with the data. Okay, now let's get to the customer reality. You have to go out and do the tactical marketing. They're busy, right? There's a lot of noise out there. We just came back from New York and our Big Data NYC event that we ran in conjunction with Strata, which is a separate event, and it's clear they don't want the hype. They want reality. The rubber's hitting the road because they're so busy, and with the the security and the governance challenges- GDPR, for instance, in Europe is a huge pressure point for data. A lot of challenges but they want the magic. (laughter) It should be easy, right? But it's not. How do you guys go out day to day and take that to the field message? What's your strategy? >> Well, you talked about changing the world with data. And it feels like a lofty promise, but we really believe that when we come down to the purpose of why NetApp exists, it is to empower our customers to change the world with data and that's something that NetApp has been focused on not just for today, but the 25 years of history, and then also into the future. So what makes that the reality? Well number one, they want something that's simple. And so this notion of simplicity, and no matter how they think about managing or optimizing their data, it's got to be simple and easy to manage. Optimized to protect, I think data protection is critically important. Things about safeguarding data across its life cycle. and I think that NetApp has always been focused on how to make sure data is secure and protected. And that now is what we're seeing in the cloud too. So, all the relationships and partnerships that we've been creating and solidifying, AWS has been for the last couple years, we've had some latest`announcements of what we're doing to really make sure we have stronger data protection in multi-cloud environments. Obviously, today from what we're doing with Microsoft Azure, in really providing- Not even having to know how to manage storage, you can do it easily in Azure, and- >> No, I'm sorry. I really love this, this message from NetApp. As a traditional technologist, I understand NetApp disrupting the original storage CN Market with Fowlers, you guys were one of the first in the cloud with AWS, so from a trusted partner inside of the infrastructure team, I understand the vision of NetApp. But the transformation also means that you're starting to expand that conversation beyond just that single customer of the storage admin, of the infrastructure group. How is that messaging been going towards that new group of customers within your customers who have said, "NetApp? Isn't that a storage company?" How is that transformation been going? >> (laughs) You know, when we talk about reinventing, NetApp is reinventing itself. And that's what we're going through right now. And what we see is, is that the customers that we know and love, the storage admins and the storage architects, those are definitely tried-and-true and we love our relationships with them. But we see that the demands around data are growing and those demands are starting to reach more into DevOps, application developers, definitely into cloud enterprise architects as we think about cloud environments. The CIO is now under more pressure to think through how- They have a mandate to move to the cloud. Now what? But who do they want to move with? Someone that they've trusted before, and by the way, because we've been first, and because we're so open with all our relationships with the cloud providers, why not move with us? Because we can help them think through it. >> So you're keeping the core. You're not pivoting off the core, you're building on top of the core, extending that. Is that what you're saying? >> We're building off of a really great foundation of who we've had as customers all along. We're establishing new relationships, though, as well, with cloud enterprise architects, and today, we actually just had here at Insight our first executive summit, where we brought together CIOs and CTOs and really talked about what's happening with data and organizations, what's happening with data that's being disruptive, what's happening if you want to thrive, based on data as well. >> There used to be an old expression back in the day when Polaroid was around, "What's the new Polaroid picture of something?" Now it's Instagram, so I have to ask this question. What is the new Instagram picture of NetApp with the customers that you have and for customers now in the data space, there's a lot of data conversations happening. What is that picture of NetApp? What should they know about NetApp? >> NetApp is in the cloud. >> Yeah, I love that messaging that NetApp is in the cloud. And how important is that moving forward? Especially as we look at technology such as ONTAP. They have been there from the beginning. I love the NFS on Azure story, but that's powered by ONTAP, which I kind of- It took me a few minutes to kind of get it, because I'm thinking, "ONTAP in Azure, that's bringing the old to the new." But that's not exactly what it is. What messaging do you want customers to get out of something like an NFS in Azure? >> We want them to understand that they don't have to know anything about storage to be able to protect and manage their data. No matter what environment that they're in. >> And by the way, we've been looking at and commenting critically on The Cube many events now that multi-cloud is a pipe dream. Now I say that only as folks know me. It's real. Customers want multi-cloud, but multi-cloud has been defined as, "Oh, I run 365 on Azure, and I got some analytics on Redshift on Amazon, I do some stuff on-prem. That's considered multi-cloud because there happen to be stuff on multiple clouds. You guys are doing something with cloud orchestrate that's quite interesting. It truly is multiple clouds in the sense that you can move data, if I get this right, across clouds. >> Jean: That's right. >> So it's in a complete transparent way, seamless way, so I don't have to code anything. Is that true? If that's true, then you might be one of the first multi-cloud use cases. >> We are one of the first multi-cloud use cases. We have created the data fabric, which is really looking at how do you seamlessly integrate across multiple clouds or on-prem environments? The data fabric, we've been talking about this vision for a couple of years. What we're seeing now is customers are seeing it come to reality. And now that we have more and more relationships expanding, as we mentioned we've been building SAS offerings with AWS for a couple years, we just had the big announcement today with Microsoft Azure. We're working with IBM Cloud. We're also working with Google Cloud, Alibaba, so as we think about a seamless data fabric, they want frictionless movement in and out of the cloud. >> Jean, I got to change gears for a second, because one of the things we've been observing over the past couple of months, certainly we were at the Open Source Summit, Linux Foundation. Open source is growing exponentially now. You've seen the new onboarding of developers in general and enterprise is going to take the bulk of that. Companies are supplying personnel to contribute on open source projects. That's continuing to happen. Nothing new there. But it's starting to change the game. You see Blockchain out there, getting some traction, ICOs and all that hype, but it points to one thing. Communities are really valuable. So as a marketer, I know you were at IBM, very community-oriented, very open source oriented, the role of communities is going to be super important as customers discover- So marketing is changing from batch marketing, you know, surge email marketing to real-time organic with communities. It's not just have a social handle. Really, have you guys looked at the B2B marketing transformation as customers start to make selections and take opinions in the new organic communities, because you have people in these projects, in open source, who are making decisions based on content. What's your view on communities and the importance of communities? >> Well, we believe highly in communities. Our A-Team is a community with us that is so strong, and they're our biggest advocates. They get brought in very, very early on in terms of learning about our new technologies and learning our story and understanding our strategy and where we're moving. I think you may have talked to some of our A-Team members before. >> John: Quite strong, very strong. >> But they are an amazing group of people and we believe highly that their advocacy is what is really going to help us to stay in touch and be really close to these new buyers as well. >> And you've got to really internalize that too in the company. Operationally, any best practices you can share with other CMOs? 'Cause this is a challenge for a lot of marketers is, how do you operationalize something new? >> Yes, well, we're finding that this notion of reinvention and it starts with the company itself. And it starts with their own employees. So when we talk about the shift from storage to data, we're even having our own employees talk about their own data story and how do they connect data. George talked about his data story, actually, on the main stage in our keynote the other day. But connecting to that's been really important. This notion of transforming to think about these new customers and new buyers, it starts with the customer needs, it's not about a product-out discussion. And so, a new story to a new buyer, relevancy, what's happening in their industry, and then engagement, engagement, engagement. >> I've been following NetApp since they were start-up and they went public, great story. They have a DNA of reinvention. David Hitz is going to to come out, I'm sure. We'll talk about that, because he's been an entrepreneur, but he's also had that entrepreneurial DNA. It's kind of still in the company, so my question to you is, from a personal perspective, what have you learned or observed at NetApp during this reinvention, not a pivot, it's not at all. It's more of an inflection point for NetApp and a new way, a new way to engage with customers, a new way to build products, a new way to do software development, a new way to use data. This is a theme we're seeing. What's your personal observation, learnings that you could share? >> Well, in my first month, what I really learned is just the absolute amazing culture of what NetApp has and this notion of we're always embracing what our customers want to where we move. So what our customer wants, we move with it. We embrace it holistically. Years and years ago, you know, Linux and Windows. A couple of years later, virtualization, virtualized environments. Could've killed us. Made us stronger. Now, embracing the cloud. A lot of our customers say, "I would have canceled the meeting with you, but now I understand that you're interested in the cloud and that you're in the cloud, I've totally changed my mind." And we say, "We love the cloud. We embrace the cloud holistically." >> You guys are progressive. I've noticed it's a competitive strategy kind of theory but as the old expression goes, "You got to eat your own to get to the new market. Some companies will milk the market share dry and then can't get to the new model. This is the reinvention challenge. When do you stop making profits to build for the future? It's a tough call. >> It is, but that's why we listen to what our customers say. And so, when they talked about wanting to move to the cloud a few years ago, we said, "We're going to be the first to holistically embrace the cloud." >> Okay, so you got the NetApp Insight 2017 going on in Berlin. Okay, that brings up the question, because it's in Germany, so I have to ask. GDPR has been super hot. The global landscape, how is that going on for NetApp? Obviously you have some experience in outside the US. It's not always the US, North America centric world. What's the global story for NetApp? >> It's not. I lived in China and Singapore, and I know that there are demands that are not just US-centric. When we talk about Germany, I was just there a few months ago, and this notion of how do we start to address the articles that are in GDPR that help to make sure that we have the right compliance and protection for data inside of a country and inside of Europe. We actually have expertise in that area. We've been actually consulting and talking with customers about what they want to do with data compliance and we're being asked now to say, "How does NetApp help address those articles? How do we come back with solutions to help control data and make sure we have the right access of data?" So, we're already consulting with customers. We know it's a top priority, and we have expertise to be able to help. >> We had Sheila FitzPatrick on. She's the Chief Privacy Officer. Very colorful, very dynamic, a lot of energy. >> Jean: She is. (laughs) >> She's going to slap anyone around who says you don't bolt on privacy. Good policy conversations, the policies converging in with that. It's interesting, the global landscape- The Cube will be in China next week for the Alibaba Cloud Conference, so we're going to go report, see what's going on there, so huge international challenge around regulations and policy. Does that affect the marketing at all? Because policy kind of is data privacy and security. Security super hot, obviously. Data security is number- A big thing. How does policy intersect with the technology? How as a CMO do you get that realized and put into action? >> Well, I think basing on the foundation that we're always optimized to protect. That's one of our key foundations of why people choose NetApp. We definitely know that there are other demands that are happening in local markets. I was just in Australia few weeks ago and was meeting with the New South Wales government, which they've had a mandate that all of the agencies need to use their own cloud platform. They've been working with NetApp to ensure that they can have the right data management solutions on that platform. And from a marketing perspective, we embrace that. And so we work with, whether it's Telstar, we're working with New South Wales, we're thinking about how do we ensure that that message is strong, because we know customers there have different demands than just what's in the US. >> So when you get CIOs and and senior executives together at a summit like you guys had over the past few days, ideas start to percolate, problem start to come across. What was some of the biggest policy concerns throughout those conversations? Was it GDPR? Was it something else? What's top-of-mind? >> What we're hearing top-of-mind right now is data governance. And I think that that could be towards data compliance in terms of GDPR for Europe. I think it expands beyond Europe, though. I just heard, like I said, in Australia, where they're having demands based on the government of what's needed to be really driven through a cloud platform. We're hearing through our customers in the last couple weeks about if I'm moving to the cloud, number one, I want to have seamless transition during the move in or out of the cloud, but I got to make sure I've got the right governance model in place. >> So we've heard this repeatedly. Customers moved into the cloud. How many customer are coming to you saying, "You know what, for whatever reason, whether it's cost, agility, the overall capability we thought we'd have available in the cloud, not really what we thought it would be. We need help moving it back." And what is that conversation like? >> Well, it's a conversation that we're able to help with pretty easily. Right now, we have had customers that have either had one, a cloud mandate, so they got to think about how am I going to move all my data to the cloud. Once they actually start getting into the detail, we do a design workshop where we help them think about maybe there's not all workloads going to the cloud. Maybe some workloads go in the cloud. We have had a customer who did move the majority of workloads in the cloud and then decided, actually, we think we'll get better cost performance and better efficiencies if we actually have those back on-prem. We said, "No problem. We can help you with that too." And I think that's the beauty of what we talked about with data fabric is, we're able to help them think through, no matter where they want their data, on-prem or in the cloud, we can help them. >> Jean, thanks for coming up here. I know your time is super valuable. I got to get one more point in, 'cause I want to make sure we get that out there. Public sector. NetApp's position strong, getting better? What's your thoughts? A quick update on public sector. >> We are very, very strong on public sector. We've actually had a strong presence in public sector with our customers for many years. And we're continuing to help them think about too how they start to look at cloud environments. >> All right, Jean English, CMO here on The Cube. Getting the hook here in the time. She's super busy. Thanks for coming. Congratulations- >> Jean: Thank you. >> On great positioning and looking forward to chatting further at The Cube. Live coverage here, Las Vegas at the Mandalay Bay. I'm John Furrier, Keith Townsend. We'll be right back with more live coverage after this short break. (upbeat music)

>> Announcer: Live from New York, it's theCUBE, covering the IBM machine learning launch event. Brought to you by IBM. Now, here are your hosts, Dave Vellante and Stu Miniman. >> Alright, we're back. Jean Francois Puget is here, he's the distinguished engineer for machine learning and optimization at IBM analytics, CUBE alum. Good to see you again. >> Yes. >> Thanks very much for coming on, big day for you guys. >> Jean Francois: Indeed. >> It's like giving birth every time you guys give one of these products. We saw you a little bit in the analyst meeting, pretty well attended. Give us the highlights from your standpoint. What are the key things that we should be focused on in this announcement? >> For most people, machine learning equals machine learning algorithms. Algorithms, when you look at newspapers or blogs, social media, it's all about algorithms. Our view that, sure, you need algorithms for machine learning, but you need steps before you run algorithms, and after. So before, you need to get data, to transform it, to make it usable for machine learning. And then, you run algorithms. These produce models, and then, you need to move your models into a production environment. For instance, you use an algorithm to learn from past credit card transaction fraud. You can learn models, patterns, that correspond to fraud. Then, you want to use those models, those patterns, in your payment system. And moving from where you run the algorithm to the operation system is a nightmare today, so our value is to automate what you do before you run algorithms, and then what you do after. That's our differentiator. >> I've had some folks in theCUBE in the past have said years ago, actually, said, "You know what, algorithms are plentiful." I think he made the statement, I remember my friend Avi Mehta, "Algorithms are free. "It's what you do with them that matters." >> Exactly, that's, I believe in autonomy that open source won for machine learning algorithms. Now the future is with open source, clearly. But it solves only a part of the problem you're facing if you want to action machine learning. So, exactly what you said. What do you do with the results of algorithm is key. And open source people don't care much about it, for good reasons. They are focusing on producing the best algorithm. We are focusing on creating value for our customers. It's different. >> In terms of, you mentioned open source a couple times, in terms of customer choice, what's your philosophy with regard to the various tooling and platforms for open source, how do you go about selecting which to support? >> Machine learning is fascinating. It's overhyped, maybe, but it's also moving very quickly. Every year there is a new cool stuff. Five years ago, nobody spoke about deep learning. Now it's everywhere. Who knows what will happen next year? Our take is to support open source, to support the top open source packages. We don't know which one will win in the future. We don't know even if one will be enough for all needs. We believe one size does not fit all, so our take is support a curated list of mid-show open source. We start with Spark ML for many reasons, but we won't stop at Spark ML. >> Okay, I wonder if we can talk use cases. Two of my favorite, well, let's just start with fraud. Fraud has become much, much better over the past certainly 10 years, but still not perfect. I don't know if perfection is achievable, but lot of false positives. How will machine learning affect that? Can we expect as consumers even better fraud detection in more real time? >> If we think of the full life cycle going from data to value, we will provide a better answer. We still use machine learning algorithm to create models, but a model does not tell you what to do. It will tell you, okay, for this credit card transaction coming, it has a high probability to be fraud. Or this one has a lower priority, uh, probability. But then it's up to the designer of the overall application to make decisions, so what we recommend is to use machine learning data prediction but not only, and then use, maybe, (murmuring). For instance, if your machine learning model tells you this is a fraud with a high probability, say 90%, and this is a customer you know very well, it's a 10-year customer you know very well, then you can be confident that it's a fraud. Then if next fraud tells you this is 70% probability, but it's a customer since one week. In a week, we don't know the customer, so the confidence we can get in machine learning should be low, and there you will not reject the transaction immediately. Maybe you will enter, you don't approve it automatically, maybe you will send a one-time passcode, or you enter a serve vendor system, but you don't reject it outright. Really, the idea is to use machine learning predictions as yet another input for making decisions. You're making decision informed on what you could learn from your past. But it's not replacing human decision-making. Our approach with IBM, you don't see IBM speak much about artificial intelligence in general because we don't believe we're here to replace humans. We're here to assist humans, so we say, augmented intelligence or assistance. That's the role we see for machine learning. It will give you additional data so that you make better decisions. >> It's not the concept that you object to, it's the term artificial intelligence. It's really machine intelligence, it's not fake. >> I started my career as a PhD in artificial intelligence, I won't say when, but long enough. At that time, there were already promise that we have Terminator in the next decade and this and that. And the same happened in the '60s, or it was after the '60s. And then, there is an AI winter, and we have a risk here to have an AI winter because some people are just raising red flags that are not substantiated, I believe. I don't think that technology's here that we can replace human decision-making altogether any time soon, but we can help. We can certainly make some proficient, more efficient, more productive with machine learning. >> Having said that, there are a lot of cognitive functions that are getting replaced, maybe not by so-called artificial intelligence, but certainly by machines and automation. >> Yes, so we're automating a number of things, and maybe we won't need to have people do quality check and just have an automated vision system detect defects. Sure, so we're automating more and more, but this is not new, it has been going on for centuries. >> Well, the list evolved. So, what can humans do that machines can't, and how would you expect that to change? >> We're moving away from IMB machine learning, but it is interesting. You know, each time there is a capacity that a machine that will automate, we basically redefine intelligence to exclude it, so you know. That's what I foresee. >> Yeah, well, robots a while ago, Stu, couldn't climb stairs, and now, look at that. >> Do we feel threatened because a robot can climb a stair faster than us? Not necessarily. >> No, it doesn't bother us, right. Okay, question? >> Yeah, so I guess, bringing it back down to the solution that we're talking about today, if I now am doing, I'm doing the analytics, the machine learning on the mainframe, how do we make sure that we don't overrun and blow out all our MIPS? >> We recommend, so we are not using the mainframe base compute system. We recommend using ZIPS, so additional calls to not overload, so it's a very important point. We claim, okay, if you do everything on the mainframe, you can learn from operational data. You don't want to disturb, and you don't want to disturb takes a lot of different meanings. One that you just said, you don't want to slow down your operation processings because you're going to hurt your business. But you also want to be careful. Say we have a payment system where there is a machine learning model predicting fraud probability, a part of the system. You don't want a young bright data scientist decide that he had a great idea, a great model, and he wants to push his model in production without asking anyone. So you want to control that. That's why we insist, we are providing governance that includes a lot of things like keeping track of how models were created from which data sets, so lineage. We also want to have access control and not allow anyone to just deploy a new model because we make it easy to deploy, so we want to have a role-based access and only someone someone with some executive, well, it depends on the customer, but not everybody can update the production system, and we want to support that. And that's something that differentiates us from open source. Open source developers, they don't care about governance. It's not their problem, but it is our customer problem, so this solution will come with all the governance and integrity constraints you can expect from us. >> Can you speak to, first solution's going to be on z/OS, what's the roadmap look like and what are some of those challenges of rolling this out to other private cloud solutions? >> We are going to shape this quarter IBM machine learning for Z. It starts with Spark ML as a base open source. This is not, this is interesting, but it's not all that is for machine learning. So that's how we start. We're going to add more in the future. Last week we announced we will shape Anaconda, which is a major distribution for Python ecosystem, and it includes a number of machine learning open source. We announced it for next quarter. >> I believe in the press release it said down the road things like TensorFlow are coming, H20. >> But Anaconda will announce for next quarter, so we will leverage this when it's out. Then indeed, we have a roadmap to include major open source, so major open source are the one from Anaconda (murmuring), mostly. Key deep learning, so TensorFlow and probably one or two additional, we're still discussing. One that I'm very keen on, it's called XGBoost in one word. People don't speak about it in newspapers, but this is what wins all Kaggle competitions. Kaggle is a machine learning competition site. When I say all, all that are not imagery cognition competitions. >> Dave: And that was ex-- >> XGBoost, X-G-B-O-O-S-T. >> Dave: XGBoost, okay. >> XGBoost, and it's-- >> Dave: X-ray gamma, right? >> It's really a package. When I say we don't know which package will win, XGBoost was introduced a year ago also, or maybe a bit more, but not so long ago, and now, if you have structure data, it is the best choice today. It's a really fast-moving, but so, we will support mid-show deep learning package and mid-show classical learning package like the one from Anaconda or XGBoost. The other thing we start with Z. We announced in the analyst session that we will have a power version and a private cloud, meaning XTC69X version as well. I can't tell you when because it's not firm, but it will come. >> And in public cloud as well, I guess we'll, you've got components in the public cloud today like the Watson Data Platform that you've extracted and put here. >> We have extracted part of the testing experience, so we've extracted notebooks and a graphical tool called ModelBuilder from DSX as part of IBM machine learning now, and we're going to add more of DSX as we go. But the goal is to really share code and function across private cloud and public cloud. As Rob Thomas defined it, we want with private cloud to offer all the features and functionality of public cloud, except that it would run inside a firewall. We are really developing machine learning and Watson machine learning on a command code base. It's an internal open source project. We share code, and then, we shape on different platform. >> I mean, you haven't, just now, used the word hybrid. Every now and then IBM does, but do you see that so-called hybrid use case as viable, or do you see it more, some workloads should run on prem, some should run in the cloud, and maybe they'll never come together? >> Machine learning, you basically have to face, one is training and the other is scoring. I see people moving training to cloud quite easily, unless there is some regulation about data privacy. But training is a good fit for cloud because usually you need a large computing system but only for limited time, so elasticity's great. But then deployment, if you want to score transaction in a CICS transaction, it has to run beside CICS, not cloud. If you want to score data on an IoT gateway, you want to score other gateway, not in a data center. I would say that may not be what people think first, but what will drive really the split between public cloud, private, and on prem is where you want to apply your machine learning models, where you want to score. For instance, smart watches, they are switching to gear to fit measurement system. You want to score your health data on the watch, not in the internet somewhere. >> Right, and in that CICS example that you gave, you'd essentially be bringing the model to the CICS data, is that right? >> Yes, that's what we do. That's a value of machine learning for Z is if you want to score transactions happening on Z, you need to be running on Z. So it's clear, mainframe people, they don't want to hear about public cloud, so they will be the last one moving. They have their reasons, but they like mainframe because it ties really, really secure and private. >> Dave: Public cloud's a dirty word. >> Yes, yes, for Z users. At least that's what I was told, and I could check with many people. But we know that in general the move is for public cloud, so we want to help people, depending on their journey, of the cloud. >> You've got one of those, too. Jean Francois, thanks very much for coming on theCUBE, it was really a pleasure having you back. >> Thank you. >> You're welcome. Alright, keep it right there, everybody. We'll be back with our next guest. This is theCUBE, we're live from the Waldorf Astoria. IBM's machine learning announcement, be right back. (electronic keyboard music)

>> Narrator: The Cube presents, On the Ground. (techno music) >> Hi I'm Peter Burris, welcome to, an On the Ground here at Oracle Headquarters, with Silicon Angle media The Cube. Today we're talking to JP Dijcks, who is the master product manager inside, or one of the master product managers, inside Oracle's big data product group, welcome JP. >> Thank you Peter. >> Well, we're going to talk about how developers get access to this plethora, this miasma, this unbelievable complexity of data that's being made possible by IOT, traditional applications, and other sources, how are developers going to get access to this data? >> That's a good question Peter, I still think that one of the key aspects to getting access to that data is SQL, and so that's one of the ways we are driving, try to figure out, can we get the Oracle SQL engine, and all the richness of SQL analytics enabled on all of that data, no matter the what the format is, or no matter where it lives, how can I enable those SQL analytics on that, and then obviously we've all seemed to shift in APIs, and languages, like people don't necessarily always want to speak SQL and write SQL questions, or write SQL queries. So how do we then enable things like R, how do we enable plural, how do we enable Python, all sorts of things like that, how do we do that, and so the thought we had was, can we use SQL as the common meta-data interface? And the common structure around some of this, and enable all of these languages on top of that through the database. So that's kind of the baseline of what we're thinking of, of enabling this to developers and large communities of users. So that's SQL as an access method, do you also envision that SQL will also be a data creation language? As we think about how to envision big data coming together from a modeling perspective. >> So I think from a modeling perspective the meta-data part we certainly look at as a creation or definition language is probably the better word, how do I do structured queries, 'cause that's what SQL stands for, how do I do that on Jason documents, how do I do that on IOT data as you said, how do I get that done, and so we certainly want to create the meta-data, in like a very traditional data base catalog, or if you compare to a Hive Catalog, very much like that. The execution is very different, it uses the mechanisms under the cover that no SQL data bases have, or that Hadoop HDFS offer, and we certainly have no real interest in doing insert into Hadoop, 'cause the transaction mechanisms work very very differently, so its really focused on the meta-data areas and how do I expose that, how do I classify and categorize that data in ways people know and have seen for years. >> So that data manipulation will be handled by native tools, and some of the creations, some of the generation, some of the modeling will be handled now inside SQL, and there are a lot of SQL folks out there that have pretty good afinity for how to work with data. >> That's absolutely correct. >> So that's what it is, now how does it work? Tell us a bit about how this big data SQL is going to work, in a practical world. >> Okay. So we talked about the modeling already. The first step is that we extend the Oracle database and the catalog to understand things like Hive objects or HDFS kind of, where does stuff live. So we expanded and so we found a way to classify the meta-data first and foremost. The real magic is leveraging the Hadoop stack, so you ask a BI question and you want to join data in Oracle transactions, finance information, let's say with IOT data, which you'd reach out to HDFS for, big data SQL runs on the Hadoop notes, so it's local processing of that data, and it works exactly as HDFS and Hadoop work, in other words, I'm going to do processing local, I'm going to ask the name note which blocks am I supposed to read, that'll get run, we generate that query, we put it down to the Hadoop notes. And that's when some of the magic of SQL kicks in, which is really focused on performance, its performance, performance, performance, that's always the problem with federated data, how do I get it to perform across the board. And so what we took was, >> Predictably. >> Predictably, that's an interesting one, predictable performance, 'cause sometimes it works, sometimes it doesn't. So what we did is we took the exadata that was stored on the software, with all the magic as to how do I get a performance out of a file system out of IO, and we put that on the Hadoop notes, and then we push the queries all the way down to that software, and it does filtering, it does predicate pushdown, it leverages features like Parquet and ORC on the HDFS side, and at the end of the day, it kind of takes the IO requests, which is what a SQL query gives, feeds it to the Hadoop notes, runs it locally, and then sends it back to the database. And so we filter out a lot of the gunk we don't need, 'cause you said, oh I only need yesterdays data, or whatever the predicates are, and so that's how we think we can get an architecture ready that allows the global optimization, 'cause we can see the entire ecosystem in its totality, IOT, Oracle, all of it combined, we optimized the queries, push everything down as far as we can, algorithms to data, not data to algorithms, and that's how we're going to run this performance, predictably performance, on all of these pieces of data. >> So we end up with, if I got this right, let me recap, so we've got this notion that for data creation, data modeling, we can now use SQL, understood by a lot of people, doesn't preclude us from using native tools, but at least that's one place where we can see how it all comes together, we continue to use local tools for the actual manipulation elements. >> Absolutely. >> We are now using synergy like structures so we can push algorithm down to the data, so we're moving a small amount of data to a large amount of data, 'cause its cost down and improves predictability, but at the same time we've got meta-data objects that allow us to anticipate with some degree of predictability how this whole thing will run, and how this will come together back at the keynote, got that right? >> Got that right. >> Alright, so, next question is what's the impact of doing it this way? Talk a bit about, if you can, about how its helping folks who run data, who build applications, and who actually who are trying to get business value out of this whole process. >> So if we start with the business value, I think the biggest thing we bring to the table is simplicity, and standardization. If I have to understand how is this object represented in NoSQL, how in HDFS, how did somebody put a Jason file in here, I have to now spend time on literally digging through that, and then does it conform, do I have to modify it, what do I do? So I think the business value comes out of the SQL layer on top of it. It all looks exactly the same. It's well known, it's well understood, its far quicker to get from, I've got a bunch of data, to actually building a VI report, building a dashboard, building KPIs, and integrating that data, there's nothing new to data, its a level of abstraction we put on top of this, whether you use API or in this case we use SQL, 'cause that's the most common analytics language. So that's one part of how it will impact things. The 2nd is, and I think that's where the architecture is completely unique, we keep complete control of the query execution, from the meta-data we just talked about, and that enables us to do global optimization, and we can, and if you think this through a little bit, and go, oh global optimization sounds really cool, what does that mean? I can now actually start pushing processing, I can move data, and its what we've done in the exadata platform for years, data lives on disk, oh, Peter likes to query it very frequently, let's move it up to Flash, let's move it up to in-memory, let's twist the data around. So all the sudden we got control, we understand what gets queried, we understand where data lives, and we can start to optimize, exactly for the usage pattern the customer has, and that's always the performance aspect. And that goes to the old saying of, how can I get data as quickly to a customer when he really needs it, that's what this does, right, how can I optimize this? I've got thousands of people querying certain elements, move them up in the stack and get the performance and all these queries come back in like seconds. Regulatory stuff that needs to go through like five years of data, let's put it in cheap areas, and let's optimize that, and so the impact is cheaper and faster at the end of the day, and all 'cause there's a singular entity almost that governs the data, it governs the queries, it governs the usage patterns, that's what we uniquely bring to the table with this architecture. >> So I want to build on the notion of governance, because actually one of the interesting things you said was the idea that if its all under a common sort of interfaces, then you have greater visibility, where the data is, who owns it, et cetera. If you do this right, one of the biggest challenges that business are having is the global sense of how you govern your data. If you do this right, are you that much closer to having a competent overall data governance? >> I think we were able to set up a big step forward on it, and it sounds very simple, but we now have a central catalog, that actually understands what your data is and where it lives, in kind of like a well-known way, and again it sounds very simple but if you look at silos, that's the biggest problem, you have multiple silos, multiple things are in there, nobody knows really what's in there, so here we start to publish this in like a common structural layer, we have all the technical meta-data, we track who queries what, who does all those things, so that's a tremendous help in governance. The other side of course, because we still use native tools to let's say manipulate some data, or augment or add new data, we now are going to tie in a lot of the meta-data, that comes from say the Hadoop ecosystem, again into this catalog, and while we're probably not there yet just today on the end to end governance everything's kind of out of the box, here we go. >> And probably never will be. >> And we probably never will, you're right, and I think we set a major step forward with just consolidating it, and exposing people to all the data the have, and you can run all the other tools like, crawl my data and check box anything that says SSN, or looks like a social security number, all of those tools are are still relevant. We just have a consolidated view, dramatically improved governance. >> So I'm going to throw you a curve ball. >> Sure. >> Not all data I want to use is inside my business, or is being generated by sensors that I control, how does big data SQL and related technologies play a role in the actual contracting for additional data sources, and sustaining those relationships that are very very fundamental, how data's shared across organizations. Do you see this information being brought in under this umbrella? Do you see Oracle facilitating those types of relationships, introducing standards for data sharing across partnerships becomes even easier? >> I'm not convinced that big data SQL as a technology is going to solve all the problems we see there, I'm absolutely convinced that Oracle is going to work towards that, you see it in so many acquisitions we've done, you see it in the efforts of making data as a service available to people, and to some extent big data SQL will be a foundation layer to make BI queries run smoother across more and more and more pillars of data. If we can integrate database, Hadoop, and NoSQL, there's nothing that says, oh and by the way, storage cloud. >> And we have relatively common physical governance, that I have the same physical governance, and you have the same physical governance, now its easier for us to show how we can introduce governance across our instances. >> Absolutely, and today we focus a lot on HDFS or Hadoop as the next data pillar, storage cloud, ground to cloud, all of those are on the roadmap for big data SQL to catch up with that, and so if you have data as a service, let's declare that cloud for a second, and I have data in my database in my Hadoop cluster, again, all now becomes part of the same ecosystem of data, and it all looks the same to me from a BI query perspective, from an analytics perspective. And then the, how do I get the data sharing standards set up and all that, part of that is driving a lot of it into cloud, and making it all as a service, 'cause again you put a level of abstraction on top of it, that makes it easier to consume, understand where it came from, and capture the meta-data. >> So JP one last question. >> Sure. >> Oracle opens worlds on the horizon, what are you looking for, or what will your customers be looking for as it pertains to this big data SQL and related technologies? >> I think specifically from a big data SQL perspective, is we're going to drive the possible adoption scope much much further, today we work with HDFS an we work with Oracle database, we're going to announce certain things like exadata, Hadoop will be supportive, we hold down super cluster support, we're going to dramatically expand the footprint big data SQL will run on, people who come for big data SQL or analytics sessions you'll see a lot of the roadmap looking far more forward. I already mentioned some things like ground to cloud, how can I run big data SQL when my exadata is on Premis, and then the rest of my HDFS data is in the cloud, we're going to be talking about how we're going to do that, and what do we think the evolution of big data SQL is going to be, I think that's going to be a very fun session to go to. >> JP Dijcks, a master product manager inside the Oracle big data product group, thank you very much for joining us here On the Ground, at Oracle headquarters, this is The Cube.

>> Narrator: Live from San Francisco, it's theCUBE, covering RSA Conference 2020 San Francisco. Brought to you by SiliconANGLE Media. >> Welcome back everyone. This is theCUBE's coverage from RSA Conference on Moscone South. I'm John Furrier, host of theCUBE. You know, cybersecurity is changing, and the next technology is right around the corner, and it's got to be invented somewhere, and of course Accenture Labs is part of it. Our next guest is Lisa O'Connor, Global Security R&D Lead for Accenture Labs. Lisa's working on some of those hard problems all around the world. Thank you for joining me today. Thanks for coming on. >> Thank you for having me. >> So, we always get the good scoop from Accenture, because you have a lot of smart people in that company. You know, they know their stuff. I know you got a huge analytics team. I've talked to Jean-Luc Chatelain before, and I know you got a massive amount of, deep bench of talent. But as you have to go do the applied R&D, and maybe some of the crazy ideas, you got to start thinking about where the puck is going to be. >> Absolutely. >> You got to understand that. Well, it's pretty clear to us that Cloud is certainly there. Palo Alto Networks had a disappointing earnings yesterday, because their on-premises business is shifting to the Cloud. You're seeing hybrid operating model and multicloud for the enterprise, but now you got global challenges. >> We absolutely do. >> Huge, so what are you guys working on that's coming? Tell us. >> So we're working on lots of exciting things, and Cloud is one of them. But, some of the things I'm so passionate about in labs, and I have the best job at Accenture. Don't tell anyone. (laughs) I do. So, we are working on, like Jean-Luc is working on applied intelligence, we are working on robust AI. So, when we think about AI in the future, how do we feel that, and know that it's okay? How do we put it out there and know it's safe in production, we've done the right training, we've made our model resilient to what's out there? One of the things we see happening, and I love AI, love it. It has great potential, and we get great insights out of it, but a lot of times we stop, we get the insights, and we say, "Okay, it's in the box, we got a couple hits there, "we're good, it's good." No, maybe not. And so really, it's learning and creating the actually applied attacks on AI, and then figuring out what the right defenses are. And, depending on what type of machine learning you're using, those defenses change. And so, we're having a great time in our lab in Washington D.C., working on basically defending AI and building those techniques, so that what we put out as Accenture is robust. >> You know, it's interesting, AI, you watch some of the hardcore, you know, social justice warriors out there going after Amazon, Google, you know, because they're doing some pretty progressive things. Oh, facial recognition, you got AI, you got Alexa. You know, a lot of people are like, "Oh, I'm scared." But, at the end of the day, they also have some challenges like network security, so you have all this AI up and down the stack. And, one thing I like about what's being talked about in the industry is the shared responsibility model. So, I got to ask you, as AI becomes exciting, but also, balancing, frightening to people, how do you get that shared responsibility model, so we get it right, do the experimentation, without people freaking out? (laughs) So, it's kind of like this weird mode we're in now, where I want to do more AI, because I think it benefits society, but everyone's freaking out. >> Yeah, so, in our tech vision that we just launched, The Tech Vision 2020, there's a lot of talk about value and values, which is really important when we think about AI because we can get great value out of it, but there's a values piece of it and it's how we're using it, how we're getting those insights. Because, the one thing, we have this circle, and it's between customer experience, because the companies that do customer experience well are going to excel, they're going to keep their clients, they're going to do amazing things, they're going to become sticky. But, to do that well, you have to be a good custodian of their data and their information, and curated experiences that they want, and not the creepy ones, not the ones they don't want. And so, we really look at that trust is necessary in that ecosystem, in building that, and keeping that with clients. So, that's something that came out of our technology vision. And, in fact, we're going to be talking at the Executive Women's Forum, this is tomorrow, and we're going to be having a panel on AI, and defending it, which will be very interesting. >> Make sure your people film that conference. We'd like to get a view of it on YouTube after. We love those conferences, really insightful. But, I want to get back to what you were talking about, the fun side. >> Yeah. >> You got a lot of new things on, your guys are kicking the tires on, scratching the surface on. You have two operating labs, one in Washington D.C., and one in Israel. What city in Israel? Is it in Tel Aviv or-- >> Herzliya. >> Okay, did not know. >> Yeah, the tech district, just north of Tel Aviv. It's the hotspot. >> So, Silicon Valley, D.C., and Israel, hotbeds of technology now. >> Yes. >> What's coming out of those labs, what's hot? >> Oh, there's so much exciting stuff coming out of our lab in Herzliya. One of the things that we have, and it's something that's been long and coming, it's been brewing for a while, but it's really looking at creating a model of the enterprise security posture. And, when I say a model of it, I'm talking about a cyber digital twin. Because, so much we can't do in our production networks, we don't have the capabilities. We can look around the room, but we don't have the capabilities on the SOCs team side, to ingest all this stuff. We need a playground where we can ask the what-ifs, where we can run high performance analytics, and we do that through a temporal knowledge graph. And, that's a hard thing to achieve, and it's a hard thing to do analytics at scale. So, that's one of the big projects that we're doing out of our Israel lab. >> Are you saying digital twins is a framework for that? >> Yeah. >> Does it really work well with that? >> So the knowledge graph, we can create digital twins around many things, because a digital twin is a model of processes, people, technologies, the statefulness of things, and configurations, whatever you want to pull in there. So, when we start thinking about, what would we take in to create the perfect enterprise security posture? What would give us all the insights? And, then we can ask the questions about, okay, how would an adversary do lateral movement through this? I can't fix everything that's a 10, but I could fix the right ones to reduce the risk impactfully. And, those are the kind of what-ifs that you can do. >> That's real sci-fi stuff, that's right around the corner. >> Yeah, it is. >> That simulation environment. >> It is. >> What-ifs. Oh my god, the company just got hacked, we're out of business. That's your simulation. You could get to, that's the goal, right? >> It absolutely is, to ask those good business questions about the data, and then to report on the risk of it. And, the other thing, as we move to 5G, this problem's getting bigger and bigger, and we're now bringing in very disparate kinds of compute platforms, computing-at-the-edge. And, what does that do to our nice little network model that we had, that our traditional systems are used to defending against? >> I mean, just the segmentation of the network, and the edge opens up so much more aperture-- >> Yes, it does (laughs). >> to the digital twin, or a knowledge graph. You brought up knowledge graph, I want to get your thoughts on this. I was just having dinner last night with an amazing woman out of New York. She's a Ph.D. in computer science. So, we're talking about graphs, and I love riffing on graph databases. But, the topic came up about databases in general, because with the cloud, it's horizontally scalable, you've got all kinds of simulation, a lot of elasticity going on, there's a lot of software being written on this. You got time series database, you got relational database, you got unstructured, and you got graphs. You got to make them all work together. This is kind of the unique challenge. And, with security, leveraging the right database, and the right construct is a super important thing. How do you guys look at that in the labs? Because, is it something that you guys think about, or is it going to be invisible someday? >> Oh, we think about it a lot. In fact, we've had a number of research projects over the last five years now, actually six years, where we've really pivoted hard in cyber security to graph databases. And, the reason for that is, the many-to-many relationships, and what we can do in terms of navigating, asking the questions, pulling on a thread, because in cyber hunting, that's what we're doing. In many of these use cases that we're trying to defend an enterprise, we're following the next new path based on the newest information of now what the challenge is, or what the current configuration is. So, that's really important. So, graph databases enable that so well. Now, there's still the architecture challenge of, okay, when I ask a query, what am I doing? Am I disrupting the whole apple cart? Do I have to process everything over, or is there a way to do that elegantly, where I can ask my query, and because of how I've structured it in storage, I can do it much better, and I can do it much more efficiently. And that, I think, is where the opportunities are. >> I got to tell you, I'm getting exited now on this whole database discussion, because you think about the logic around what you just said. A graph database with that kind of complexity, when you factor in contextually different things happening at any given time, the database needs to be parsed and managed differently. >> Yes. >> That's a huge challenge. >> It is a great research challenge, which is why we're doing it. >> What is that, how far along are we going to be able to have this dynamic, self-evolving, self-governing, self-healing data modeling? Is that coming soon, or... >> Yeah, I hope so. We wrote about it a couple of years ago. >> You did? >> The self-healing enterprise, aspirational. But I think, I mean, we try to get to real time, right? And, we try to get to real time, and again, refactoring. As we talk about what an adversary is going to do, or lateral movement through a business process, we're talking about a lot of computational horsepower to recalculate all that, process it again, update it, and then again present that back. So the number of things we're asking, how we're asking it becomes also very important to the structure. >> Just, it goes zooming up a little bit, high level, what we're really talking about here is value >> of the data. >> Absolutely. >> And, when you get into the valuation of the nodes, and the arcs, and all that graphs, and other databases, you got to know what to pay attention to. It's kind of like going into the hospital and hearing all these alarms going off. At some point you don't know what's, until they hear a flat line, or whatever. >> Right. That's a bad one. >> I mean, well that's obvious. But, now sometimes there's so many alerts, there's so many alarms. How do you understand at any given time what to pay attention to, because obviously when someone's having a problem you want to pay attention to it. If it's a security alert, that's prioritized. >> And the devil is in the analytics, right? What's the question we're asking, and the analytics that give us that prioritization? And that's non-trivial, because there are a lot of other folks that are doing prioritization in a different manner. To do it at scale, and to do it, not just one hop out, but I want to go all the way to the crown jewels, I want that whole path navigated, and I want to know where to cut along that path. That's a hard thing to do. And so, we've actually developed, and we've submitted patents for them, but we've developed new analytics that'll support that. >> Awesome. Well Lisa, I want to ask you kind of a, I'll give you a plug here, just going to get it out, because I think it's important. Skills gap's a big thing, so I want to give you a minute to explain, or share what you're looking for in your hiring. Who are you looking for? What kind of, the make-up of individual, obviously? Maybe, do you use straight, more academic paper kind of people, or practitioners? I mean, when you look to hire, what are some of the priorities that you look for, and who would thrive in an Accenture Lab's environment? >> Oh, my goodness. >> Take a minute to share what you're looking for. >> Yeah, so we love people that think out of the box, and those kinds of people come from very different backgrounds. And so, part of that is, some of them we look for Ph.D.'s, that have wonderful applied skills, and applied is a key word there. White papers are great, I need to be able to prove something, I need to be able to demo something that has value. So, having the applied skills to a business challenge is really important. So, that sort of ground, understanding the business, very important too. But, our talent comes from many different areas. I mean, I kind of joke, my lab looks like the UN, it's wonderful. I have people from across the globe that are in our cyber security lab. I have, in our Washington D.C. lab, we're 50% women, which is also exciting, because we want different experiences, and we shoot for cognitive diversity, right? So, we're looking for people that think differently about solving problems, and are not encumbered by what they've seen in the past, because we're trying to be tip of spear. And, I'm sure you know that from Paul Daugherty. >> Yeah. >> We are trying to be three to five years over the horizon. >> You guys got a good narrative. I always love talking to Accenture, they have a good vision. So, I got to ask you, the next logical question is, obviously, in the news, you see everyone talking about breaches, and ya know, it's not a breach if the door's open, you just walk in. They're really walking in, nothing was really breached, you're just giving it to them. >> Yeah. It's a passive invitation. >> (laughs) Hey come on in. Human error is a big part of it, but then, breach is obviously targeted, phishing, and all that good stuff. But, as those stories get told, there's a whole nother set of stories that aren't being told that are super important. So, I'd love to get your thoughts on, what are the most important stories that we should be talking about that aren't being talked about? >> Yeah, so I have two that are front-of-mind for me. One theme we come back to, and it's not sexy, it's hygiene. It is IT hygiene, and so many of the large companies, and even medium, small companies, we have legacy technology, and keeping that adds complexity, it adds to the whole breadth and depth of what we have to manage and defend. Keeping that attack surface simple and small, cloud-enabled, all those good things, is a real asset and it makes it much easier to defend. So, that's kind of the first non-sexy one, hygiene. The other one I'll say that I think is a challenge that we are not dealing with yet, quantum computing, right? And so, we're on the way to getting our post quantum cryptography in place, but there's another dimension to it, and it's our histories. So, all of the things that have passed on the wire, all the communications with the key exchanges, all that brilliant stuff, is sitting somewhere. Once we get to that point where this becomes very routine, and it's coming fast, we predicted eight years, two years ago. >> So, all that exhaust is somewhere, pent up. >> It's somewhere that, we have to think about how much data we're keeping as custodians, how we're managing it, and then we have to think about the exposure from our past, and say, "Okay, what does that mean that, that was out there?" "Is it aged enough that it doesn't have value?" And, I think there's a real triage that needs to be done, and certainly data management. >> I think, you know, the hygiene brings up a good point. It reminds me of the story Andy Jassy was telling about the mainframe customer that they couldn't find who had the password. They had to find their person, who was retired 10 years earlier to get the password. You don't forget things, but also, there's a human component in all this. Humans and machines are working together. >> Absolutely. >> And. that's a huge part of it. It's not just machines dominating it all, there's going to be a human component, there's a societal impact that we're seeing with information. And, whether that's out in the open, or behind closed doors, there's all kinds of things looming. >> There are, and I think one of the things in the companies that we're seeing who are embracing innovation well, are doing a lot of retraining. Because, the things that people are excellent at, AI is not good at, and the things that AI is good at, are not at all what people are good at. So, the good news is there is a beautiful teaming there, if we retool the skills, or if we re-envision those roles, so that people can get into those roles, and I think that's really important, because I'd rather see AI do all the heavy lifting well, and be trustworthy, and robust and all those great things, and the people be doing the much smarter things that require a human. >> Does the process serve the purpose? Does the purpose serve the process? Same kind of question, right? >> Exactly. >> AI, you can't have great AI that does nothing. >> That's right. >> (laughs) So, it has to be relevant. >> It absolutely does. >> Relevance is kind of a big thing. >> And we own that context, right? Humans own that context. >> Yeah. Yeah. Yeah. Well, thanks for coming in, and sharing the insight. Really appreciate it. Final question, it's always tough to pick your favorite child, but what is your most coolest thing you're working on right now? >> I'll tell you, the cyber digital twin stuff is so cool. >> The what? >> The cyber digital twin stuff is so cool. When you see the power of what that picture, and the analytics can do, we'll show ya. >> Do you have a demo of that now? >> We absolutely do. >> You do. Is it online, or is it more in person you got to see it? >> More in person. >> Okay. >> Folks can reach out, yeah. >> We'll have to get the exclusive on that. >> We do. >> I love those simulations. I think it's very beneficial. >> It is. >> A lot of learning. I mean, who doesn't want practice? >> Well, and a picture, you know that is worth a million dollars. It's just incredible to look at it, and it clicks. It clicks of all the potential things you could ask or do. And, that's the exciting part now, as we show this with customers' and we co-innovate with customers', they're coming up with a laundry list of questions. >> And, this is the beautiful thing about cloud, is that new capabilities are emerging every day, and you could use the good ones. Lisa O'Connor is here. Thank you very much for sharing your insights. Global Security R&D Lead for Accenture Labs. TheCUBE coverage, getting all the signal here on the show floor, extracting that from all the noise. I'm John Furrier, thanks for watching. (upbeat music)