>> Announcer: Live from Las Vegas, it's The Cube, covering Oracle Modern Customer Experience 2017, brought to you by Oracle. (dynamic music) >> John: Hey, welcome back everyone, we're here live. Day two coverage of Oracle's Modern CX Modern Customer Experience #ModernCX. Also check out all the great coverage here on The Cube, but also on the web, a lot of great stories and one of the people behind all that is Des Cahill, who's joining Peter Burris and myself. Kicking off day two, Des, great to see you, Head of Customer Experience Evangelist, involved in a lot of the formation and really the simplification of the messaging across Cloud, so it's really one story. >> Yeah, absolutely, so John, Peter, great to be here. You know, I think the real story is about our customers and businesses that are going through transformation. So everything that we're doing at Oracle, in our CX organizations, helping these organizations make their digital business transformation and the reason they're going through this transformative process is to meet the demands of their customers. I'd say it's the era of the empowered customer. They're empowered by social, mobile, Cloud technologies and all of us in our daily lives can relate to the fact that over the last five, 10 years, the way that we buy, our journey as we buy products, as we do research, is completely different, than it used to be, right. >> Talk about the evolution, talk about the evolution of what's happening this week, because I think this is kind of a mark in time, at least from our observation, covering Oracle, this is our eighth year and certainly second year with the modern marketing experience now, >> Des: Yeah. >> the modern customer experience, where the feedback in the floor, and this is noteworthy, is that the quality is great, people at the booth are highly qualified, but it's simple. It's one fabric of messaging, one fabric of product. It feels like a platform, >> Yeah. >> and is that by design (laughs) or is that kind of the next step in the evolution of, >> Des: Yeah, John. >> Marketing Cloud meets Real Cloud and? >> Yeah, yeah, so absolutely John. I mean that, that is by design and again, to support our customers and their needs on this digital business transformation journey, it starts obviously with fantastic marketing, we've just got fantastic capabilities within our Marketing Cloud, but then that extends to Sales Cloud. If you generate leads in marketing and you're not handing them over to sales effectively or of a good sales automation engine and that goes on to commerce, CPQ, social, and service. And all of this, if we bring this back down to again, this notion of the empowered customer, if you're not providing those customers with connected experiences across marketing, sales, service, commerce, you're not... you're going to, you might lose those customers. I mean, we expect connected experiences across our whole journey. If I'm calling my cell phone provider, 'cause I got a problem, I don't, and I don't want to call one person, get transferred to another person and then go to the website to chat with someone, have a disconnected experience. I want them to, when I call, I want them to understand my history, my status as a customer, I'm spending 500 dollars a month on them, the problems I've had before. I want them to have context and to know me in that moment and as Mark Hertz says, it's like a moment of truth with my cell phone provider. Are they going to delight me and turn me into a customer advocate, or am I going to leave and go to another cell phone provider? >> Well let's talk just for a second, and I want to get your comments on this and how it relates specifically to what we're saying here. Digital has two enormous impacts. One, as you said, that a customer can take their research activities with them, on their cell phone. >> Yeah. They have learned, because of commerce and electronic commerce, they've learn to expect and demand a certain style of engagement >> Des: Right. >> and that's not going to change, so if you are not doing those things-- >> We like to say Amazon is the new benchmark, either B to C or B to B, it doesn't matter, right. >> It is a benchmark, at least on the commerce side, so it's, so that's one change, is that customers are empowered. The second big change though, is that increasingly, digital allows people to render products more as services and that's in many respects, what the Cloud's all about. >> Des: Right. >> How do you take an asset, that is a machine and render it as a service to someone? Well now we can actually use digital technologies to render things more as services. The combination of those two things are incredibly powerful, because customers, who now have the power to evaluate and change decisions all the time are now constantly making decisions, because it's a pay-as-you-go service world now. >> Des: Right. >> So how do those two things come together and inform the role, that marketing is going to play inside a business, 'cause increasingly, it seems to us that marketing is going to have to own that continuous, ongoing engagement and deliver that consistent value, so a customer does not leave, 'cause you have more opportunities to leave now. >> Well, I, so I think that's a good observation, Peter. I do think that marketers can play, and do play, a leading role in being the advocate for the customer within the brand, within the company and as a marketer myself, I think about not just the marketing function, but I think about, well, what is the experience, that that lead or that prospect going to have when I hand over to sales? And what is the experience that they are going to have, when I hand them over to service? And in my past roles as a CMO, the challenge I always faced was that I couldn't get information out of the sales automation system or out of the service automation system, so as a marketer, I couldn't optimize my marketing mix and I didn't have visibility on which opportunities I passed, which leads I passed over turned into the best opportunities, turned into the best deals, turned into the customers, that were most loyal, that got cross-sold and up-sold and were the happiest. So I think, going back to Oracle's strategy in all of this, it's about having a connected, end-to-end suite of Cloud applications, so that there's a consistent set of data, that is enabling these consistent, personalized, and immediate experiences. >> I think that's interesting and I want to just validate that, because I think, that is to me, the big sign that I think you guys are on the right track and executing and by the way, some of the things you're talking about used to be the holy grail, they're actually real now. >> Des: Right. >> The dynamic is the silos are a symptom of a digital-analog relationship. >> Des: Right. >> So when you have all digital, the moment of truth starts here, it's all digital. So in that paradigm, end-to-end wins. And at Mobile World Congress this year, one of the main themes when they talk about 5G, and all these things, that were going on, was you know, autonomous vehicles, (laughs) media entertainment, smart cities, a smart home, you know, talk to things. To your point, that's an end-to-end, so the entire world wants-- >> Des: Throw IoT in there. >> Throw IoT, >> Right. >> So again, these digital connections are all connected, so therefore, it is essentially an end-to-end opportunity. So whoever can optimize that end-to-end, while being open, while having access to the data, >> Des: Right. >> will be the winning formula. >> Des: Right. >> And that is something that we see and you obviously have that. >> And then the other piece is how do you actualize that data? Right, and I know you spoke with Jack Berkowitz about adaptive intelligent apps, it's, we're taking approach to artificial intelligence of saying, how can we bring to bear the power of machine learning, dynamic decision science, so that all this data, that's being collected and enabled by all these digital touch points, these digital signals, how do you take that data and how do you actualize that, 'cause the reality is, 80% of data that's collected today is dark, it's untouched, it's just collected, right. >> Well, here is the hard question for you, you know I am going to ask this, so I am going to ask it, here's the hard question. >> Des: Yeah. >> It really comes down to the data, and if you don't, you, connected networks and all that good stuff is great fabric, end-to-end. >> Des: Absolutely, yeah. >> This is certainly the future, it's the new normal, it's coming fast. >> Right. >> But at the end of the day, the conversation we've been having here is about the data. >> Des: Yes. >> What is your position with Oracle on connecting that data, 'cause that ultimately is what needs to flow. >> Des: Right. >> How does that work? Can you just take a minute to >> Sure, sure. >> to address that, how the data flows? >> Yeah, I think it starts with our end-to-end connected applications, that are able, that are connected with each other natively and are sharing that same data set. We obviously recognize that customers have mixed environments, so in those cases, we can certainly use our technologies to connect to their existing data stores, to synchronize with their existing systems, so it all starts with the cleanliness and quality of that baseline customer data. The second piece I'd say, is that we've made a lot of investments over the last five years in Oracle Data Cloud and Oracle Data Cloud is a set of anonymized, third party data. We've got 5 billion consumer IDs, we've got a billion business IDs. We've got a tremendous amount of data sources. We just announced a recent acquisition of a company called Moat, last week at our Oracle Data Cloud Summit in New York City. So we've made a tremendous investment in third party data, that can augment anonymized third party data, that can augment first party data, to allow people to have not just a connected view of the customer, but more of a comprehensive view and understanding of their customers, so that they can better talk to them and get them better experiences. >> That's the key there, that we're hearing with this intelligent, adaptive intelligent app kind of environment, >> Yeah, yeah. >> where machine learning. The third party data integrating within the first party data, that seems to be the key. Is that right, >> Absolutely. >> did I get that right? >> Yeah, well I would say there's a number of points, so I would say that, that, you know, you can think of the Oracle Data Cloud combining with the BlueKai DMP and being a great ad-tech business for us and a great solution for digital marketers in and of itself. What we've done with adaptive intelligent apps is that we've combined that third party data with decision science machine learning AI and we've coupled that with the Oracle Cloud infrastructure and the scale and power of that. So we're able to deliver real-time, adaptive learning and dynamic offers and content at 130 millisecond clips. So this is real-time interaction, so we are getting signals every time someone clicks, it's not a batch mode, one-off kind of thing. The third piece is that we have designed these, designed these apps to just embed natively, to plug into our existing CX applications. So if you're a marketer, you're a service professional, you're a sales professional, you can get value out of this day one. You've got a tremendous data set. You've got real-time, adaptive artificial intelligence and it plugs right into your existing apps. It's a win-win. Take your first party data, take your third party data, combine it together, put some decision science on there, some high bandwidth, incredible scale infrastructure and you're getting, you're starting to get to one-to-one marketing. You're freeing your marketing teams from being data analysts and segmenting and trying to get insight and you're letting the machine do that work and you're freeing up, you're freeing up your human capital to be thinking about higher-level tasks, about offers and merchandising and creative and campaigns and channels. >> Well, the way we think about it, Des, and I'll test you on this, is we think ultimately the machines are going to offer options. So they're going to do triage on a lot of this data >> Des: Right, right. >> and offer options to human decision-makers. Some of the discretions, we see three levels of interaction, >> Des: Yeah. >> Automated interaction, which, quite frankly, we're doing a lot of that today in finance systems. >> Des: Yes. >> But then we get to autonomous vehicles, highly deterministic networks, highly deterministic behaviors, >> Des: Right. >> that's what's going to be required in autonomy. No uncertainty. Where we have environmental uncertainty, i.e. that temperature's going to change or I, some IoT things are going to change, that's where we see the idea of turning the data and actuating it in the context of that environmental uncertainty. >> Des: Right. >> We think that this is all going to have an impact on the human side, what we call systems of augmentation, >> Des: Right. >> where the system's going to provide options to a human decision-maker, the discretion stays with the human decision-maker, culpability stays with the human decision-maker, >> Des: Right. >> but the quality of the options determine the value of the systems. >> So the augmentation is-- >> The augmentation's great. >> So let me give you a great example of that with AIA. So, take for example, you're a pro photographer and you got a big shoot the next day and your camera, your main camera you bought three months ago, it breaks. And you buy all your stuff at photog.com and you call 'em up and what could happen today? "Hi, what's your account number? "Who are you? "Wait, let me look you up, OK. "I'm sorry, I'm not authorized to get you a return." You know, boom, and the person's like, "I'm never going to buy from them again." Right, it's that moment of truth. Contrast that with a, 'cause the person making that decision, if it was the CEO getting that call, the CEO would be like, "We're going to get you a camera immediately." But that person that they're talking to is five levels down in a call center, Bismarck, North Dakota. If that person had AI, adaptive intelligent apps helping them out, then the AI would do the work in the background of analyzing the customer's lifetime value, their social reach, so their indirect lifetime value. It would look at their customer health, how many other services issues, that they have. It would look at, are there any warranty issues or known service failure issues on that camera and then it would look at a list of stores, that were within a five mile radius of that customer, that had those cameras in stock. And it would authorize an immediate pickup and you're on your way. It would just inform that person and enable them to make that decision. >> Even more than that, and this is a crucially important point, that we think people don't get when they talk about a lot of this stuff. These systems have to deliver not only data, but also authority. >> Exactly. The authority has to flow with the data. >> Des: Right. >> That's one of the advantages-- >> On both sides, by the way, on the identity and-- >> On both sides. >> And I think that employee wants that empowerment. >> Absolutely. >> No one wants to take a call and not make the customer happy, right. >> Peter: Absolutely, >> Yeah. >> because that's a challenge with some of the bolt-on approaches to some of these big applications, is that, yeah, >> Exactly. >> you can deliver a result, but then how is the result >> How is it manifested? >> integrated into the process >> Right. >> that defines and affords authority to actually make the decision? >> OK, so let's see, where are we on the progress bar then. because we had a great interview yesterday with the CMO from Time Warner. >> Yeah. >> OK, Kristen O'Hara, she was amazing. But basically, there was no old way of doing data, they were Time Warner, (laughs) they're old school media and they set up a project, you guys came in, Oracle came in, and essentially got them up and running, and it's changed their business practice overnight. >> Des: Right, right. >> So, and the other thing we heard yesterday was a lot of the stuff that was holy grail-like capabilities is actually being delivered. So give us a slice-and-dice what's shipping today, that's, that's hot and where's the work area that's road-mapped for Oracle? >> Sure, well-- >> And were you guys helping customers? >> Sure, I'll talk about a couple of examples, where we're helping customers. So, Denon and Marantz, high end audio company, brand's been around 100 years. The way music is delivered, is consumed, has changed radically in the last 20 years, changed radically in the last 10 years, changed even more radically in the last five years, so they've had to change their business model to keep up with that. They are embedding Oracle IoT Cloud into every product they sell, except their headphones, so all their speakers, all their AV receivers and they are using IoT data and Oracle Service Cloud to inform, not only service issues, like for example, they are, they're detecting failures pro-actively and they're shipping out new speakers, before they fail or they're pushing firmware to fix the problem, before it happens. They're not only using it to inform their service, they're using it to inform their R&D and their sales and marketing. Great example, they ship wireless speakers, HEOS wireless speakers, highly recommend 'em, I bought 'em for my kids for Christmas, they're the bomb. But customers were starting to... They were getting a lot of failures in these wireless speakers. They looked up the customer data, then they looked up the IoT data. They found that 80% of the speaker failures, the products were labeled Bathroom as location in the configuration of their home network setup and what they realized was that customers were listening to music in the bathroom, which is a use case they never thought of and the speakers weren't made to be water or humidity-proof, so they went to the R&D department, 14 months later, they ship a line of waterproof HEOS speakers. The second thing is they found people, who were labeling their speakers, Patio, they were using it on the patio, they didn't even have a rechargeable battery on it, so they came out with a line with a rechargeable battery on it. So they're not only using IoT data, for a machine maintenance function, >> John: 'cause they were behaving-- >> they're using IoT data to inform, inform R&D and they're also doing incredible marketing and sales activities. We had Don Freeman, the CMO of Denon on the main stage yesterday, talking about this great, great stuff they're doing. >> And what's the coolest thing this week, that you're looking at, you're proud of or excited about? >> I'm excited about a lot of stuff, John. This week is realized, you alluded to this week has been really, really fun, really great, a lot of buzz, obviously a lot of buzz around adaptive, intelligent apps and we've talked about that. But I would say also beyond a doubt, that intelligent apps for CX, we've introduced some great things in our Service Cloud, the capability to have a video chat, so Pella Windows was also on one of our panels today and they were talking about the ability for, to solve a service issue, the ability to show a video of what's going on, just increases the speed with which something can be diagnosed so much faster. We're integrating on the Service Cloud, we're integrating with WeChat and we're integrating with Facebook Messenger. Now, why would you do that? Well again, it comes back to this era of the empowered consumer. It's not enough that a company just has a website or an 0800 number that you can go to for support. Consumers are spending more time in social messaging apps, than they are on social messaging sites, so if the consumer wants to be served on Facebook Messenger, 'cause they spend their time on it, the brand has to meet them there. >> John: Yeah. >> The third thing would be the ability for the Marketing Cloud and Service and Sales Cloud, we've got chat bots, voice-driven, text-driven, AI-driven, so mobile assistant for the sales professionals, so you can input data on the road, "Hey, open an account, here's the data "for the transaction here what's going on." >> John: Yeah. >> Incredible, incredible stuff going on all over the stack. >> I think the thing, that excites me, is I look at the videos from last year and the theme was, "Man, you guys have "all these awesome acquisitions," >> Des: Right. >> "But you have this opportunity with the data," and you guys knew that and you guys tightened that together and doubled down on the data >> Des: Yeah, with banking, yeah-- >> and so I thought that was a great job and I like the messenging's clean, I think but more importantly is that in any sea change, you know, we joke about this, as we're kind of like historians and we've seen a lot of waves, >> Des: Right, for sure. >> and all these major waves, when the user's expectations shift, that's the opportunity. I think what you guys nailed here is that, and Peter alluded to it as well, is that the users are expecting things differently, completely differently. >> Let me share a stat with you. 50% of the companies that were in the Fortune 500 in the year 2000, are either out of business, acquired, gone, 50% and those companies, >> Dab or die. >> Blockbuster, Borders, did they stay relevant? >> John: Yeah. I think changing business practice based on data is what's happening, it's awesome. Des Cahill, here on The Cube. More live coverage, day two of Modern CX, Modern Customer Experience, #ModernCX. This is The Cube, I'm John Furrier with Peter Burris, we'll be right back. (dynamic music)

>> Announcer: From Sand Hill Road in the heart of Silicon Valley, it's theCUBE, presenting the People First Network, insights from entrepreneurs and tech leaders. (bright electronic music) >> Everyone, welcome to this special CUBE conversation. We're here at Sand Hill Road at Mayfield Fund. This is theCUBE, co-creation of the People First Network content series. I'm John Furrier, host of theCUBE. Our next guest, Yuvi Kochar, who's the Data-centric Digital Transformation Strategist at GameStop. Variety of stints in the industry, going in cutting-edge problems around data, Washington Post, comScore, among others. You've got your own practice. From Washington, DC, thanks for joining us. >> Thank you, thanks for hosting me. >> This is a awesome conversation. We were just talking before we came on camera about data and the roles you've had over your career have been very interesting, and this seems to be the theme for some of the innovators that I've been interviewing and were on the People First is they see an advantage with technology, and they help companies, they grow companies, and they assist. You did a lot of different things, most notably that I recognized was the Washington Post, which is on the mainstream conversations now as a rebooted media company with a storied, historic experience from the Graham family. Jeff Bezos purchased them for a song, with my opinion, and now growing still, with the monetization, with subscriber base growing. I think they're number one in subscribers, I don't believe, I believe so. Interesting time for media and data. You've been there for what, how many years were you at the Washington Post? >> I spent about 13 years in the corporate office. So the Washington Post company was a conglomerate. They'd owned a lot of businesses. Not very well known to have owned Kaplan, education company. We owned Slate, we owned Newsweek, we owned TV stations and now they're into buying all kinds of stuff. So I was involved with a lot of varied businesses, but obviously, we were in the same building with the Washington Post, and I had front row seat to see the digital transformation of the media industry. >> John: Yeah, we-- >> And how we responded. >> Yeah, I want to dig into that because I think that illustrates kind of a lot what's happening now, we're seeing with cloud computing. Obviously, Cloud 1.0 and the rise of Amazon public cloud. Clearly, check, done that, a lot of companies, startups go there. Why would you provision a data center? You're a startup, you're crazy, but at some point, you can have a data center. Now, hybrid cloud's important. Devops, the application development market, building your own stack, is shifting now. It seems like the old days, but upside down. It's flipped around, where applications are in charge, data's critical for the application, infrastructure's now elastic. Unlike the old days of here's your infrastructure. You're limited to what you can run on it based on the infrastructure. >> Right. >> What's your thoughts on that? >> My thoughts are that, I'm a very, as my title suggests, data-centric person. So I think about everything data first. We were in a time when cloud-first is becoming old, and we are now moving into data-first because what's happening in the marketplace is the ability, the capability, of data analytics has reached a point where prediction, in any aspect of a business, has become really inexpensive. So empowering employees with prediction machines, whether you call them bots, or you call them analytics, or you call them machine learning, or AI, has become really inexpensive, and so I'm thinking more of applications, which are built data-out instead of data-in, which is you build process and you capture data, and then you decide, oh, maybe I should build some reporting. That's what we used to do. Now, you need to start with what's the data I have got? What's the data I need? What's the data I can get? We were just talking about, everybody needs a data monetization strategy. People don't realize how much asset is sitting in their data and where to monetize it and how to use it. >> It's interesting. I mean, I got my computer science degree in the 80s and one of the tracks I got a degree in was database, and let's just say that my main one was operating system. Database was kind of the throwaway at that time. It wasn't considered a big field. Database wasn't sexy at all. It was like, database, like. Now, if you're a database, you're a data guru, you're a rock star. The world has changed, but also databases are changing. It used to be one centralized database rules the world. Oracle made a lot of money with that, bought all their competitors. Now you have open source came into the realm, so the world of data is also limited by where the data's stored, how the data is retrieved, how the data moves around the network. This is a new dynamic. How do you look at that because, again, lagging in business has a lot to do with the data, whether it's in an application, that's one thing, but also having data available, not necessarily in real time, but if I'm going to work on something, I want the data set handy, which means I can download it or maybe get real-time. What's your thoughts on data as an element in all that moving around? >> So I think what you're talking about is still data analytics. How do I get insights about my business? How do I make decisions using data in a better way? What flexibility do I need? So you talk about open source, you think about MongoDB and those kind of databases. They give you a lot of flexibility. You can develop interesting insights very quickly, but I think that is still very much thinking about data in an old-school kind of way. I think what's happening now is we're teaching algorithms with data. So data is actually the software, right? So you get an open source algorithm. I mean Google and everybody else is happy to open source their algorithms. They're all available for free. But what, the asset is now the data, which means how you train your algorithm with your data, and then now, moving towards deploying it on the edge, which is you take an algorithm, you train it, then you deploy it on the edge in an IoT kind of environment, and now you're doing decision-making, whether it's self-driving cars, I mean those are great examples, but I think it's going down into very interesting spaces in enterprise, which is, so we have to all think about software differently because, actually, data is a software. >> That's an interesting take on it, and I love that. I mean I wrote a blog post in 2007 when we first started playing with the, in looking at the network effects on social media and those platforms was, I wrote a post, it was called Data is the New Development Kit. Development kit was what people did back then. They had a development kit and they would download stuff and then code, but the idea was is that data has to be part of the runtime and the compilation of, as software acts, data needs to be resident, not just here's a database, access it, pull it out, use it, present it, where data is much more of a key ingredient into the development. Is that kind of what you're getting at? >> Yes. >> Notion of-- >> And I think we're moving from the age of arithmetic-based machines, which is we put arithmetic onto chips, and we then made general-purpose chips, which were used to solve a huge amount of problems in the world. We're talking about, now, prediction machines on a chip, so you think about algorithms that are trained using data, which are going to be available on chips. And now you can do very interesting algorithmic work right on the edge devices, and so I think a lot of businesses, and I've seen that recently at GameStop, I think business leaders have a hard time understanding the change because we have moved from process-centric, process automation, how can I do it better? How can I be more productive? How can I make better decisions? We have trained our business partners on that kind of thinking, and now we are starting to say, no, no, no, we've got something that's going to help you make those decisions. >> It's interesting, you mentioned GameStop. Obviously, well-known, my sons are all gamers. I used to be a gamer back before I had kids, but then, can't keep up anymore. Got to be on that for so long, but GameStop was a retail giant in gaming. Okay, when they had physical displays, but now, with online, they're under pressure, and I had interviewed, again, at an Amazon event, this Best Buy CIO, and he says, "We don't compete with price anymore. "If they want to buy from Amazon, no problem, "but our store traffic is off the charts. "We personalize 50,000 emails a day." So personalization became their strategy, it was a data strategy. This is a user experience, not a purchase decision. Is this how you guys are thinking about it at GameStop? >> I think retail, if you look at the segment per se, personalization, Amazon obviously led the way, but it's obvious that personalization is key to attract the customer. If I don't know what games you play, or if I don't know what video you watched a little while ago, about which game, then I'm not offering you the product that you are most prone or are looking for or what you want to buy, and I think that's why personalization is key. I think that's-- >> John: And data drives that, and data drives that. >> Data drives that, and for personalization, if you look at retail, there's customer information. You need to know the customer. You need to know, understand the customer preferences, but then there's the product, and you need to marry the two. And that's where personalization comes into play. >> So I'll get your thoughts. You have, obviously, a great perspective on how tech has been built and now working on some real cutting-edge, clear view on what the future looks like. Totally agree with you, by the way, on the data. There's kind of an old guard/new guard, kind of two sides of the street, the winners and the losers, but hey, look, I think the old guard, if they don't innovate and become fresh and new and adopt the modern things that need to attract the new expectations and new experiences from their customers, are going to die. That being said, what is the success formula, because some people might say, hey, I'm data-driven. I'm doing it, look at me, I'm data. Well, not really. Well, how do you tell if someone's really data-driven or data-centric? What's the difference? Is there a tell sign? >> I think when you say the old guard, you're talking about companies that have large assets, that have been very successful in a business model that maybe they even innovated, like GameStop came up with pre-owned games, and for the longest of times, we've made huge amount of revenue and profit from that segment of our business. So yes, that's becoming old now, but I think the most important thing for large enterprises at least, to battle the incumbent, the new upstarts, is to develop strategies which are leveraging the new technologies, but are building on their existing capability, and that's what I drive at GameStop. >> And also the startups too, that they were here in a venture capital firm, we're at Mayfield Fund, doing this program, startups want to come and take a big market down, or come in on a narrow entry and get a position and then eat away at an incumbent. They could do it fast if they're data-centric. >> And I think it's speed is what you're talking about. I think the biggest challenge large companies have is an ability to to play the field at the speed of the new upstarts and the firms that Mayfield and others are investing in. That's the big challenge because you see this, you see an opportunity, but you're, and I saw that at the Washington Post. Everybody went to meetings and said, yes, we need to be digital, but they went-- >> They were talking. >> They went back to their desk and they had to print a paper, and so yes, so we'll be digital tomorrow, and that's very hard because, finally, the paper had to come out. >> Let's take us through the journey. You were the CTO, VP of Technology, Graham Holdings, Washington Post, they sold it to Jeff Bezos, well-documented, historic moment, but what a storied company, Washington Post, local paper, was the movie about it, all the historic things they've done from a reporting and journalism standpoint. We admire that. Then they hit, the media business starts changing, gets bloated, not making any money, online classifieds are dying, search engine marketing is growing, they have to adjust. You were there. What was the big, take us through that journey. >> I think the transformation was occurring really fast. The new opportunities were coming up fast. We were one of the first companies to set up a website, but we were not allowed to use the brand on the website because there was a lot of concern in the newsroom that we are going to use or put the brand on this misunderstood, nearly misunderstood opportunity. So I think it started there, and then-- >> John: This is classic old guard mentality. >> Yes, and it continued down because people had seen downturns. It's not like media companies hadn't been through downturns. They had, because the market crashes and we have a recession and there's a downturn, but it always came back because-- >> But this was a wave. I mean the thing is, downturns are economic and there's business that happens there, advertisers, consumption changes. This was a shift in their user base based upon a technology wave, and they didn't see it coming. >> And they hadn't ever experienced it. So they were experiencing it as it was happening, and I think it's very hard to respond to a transformation of that kind in a very old-- >> As a leader, how did you handle that? Give us an example of what you did, how you make your mark, how do you get them to move? What were some of the things that were notable moments? >> I think the main thing that happened there was that we spun out washingtonpost.com. So it became an independent business. It was actually running across the river. It moved out of the corporate offices. It went to a separate place. >> The renegades. >> And they were given-- >> John: Like Steve Jobs and the Macintosh team, they go into separate building. >> And we were given, I was the CTO of the dotcom for some time while we were turning over our CTO there, and we were given a lot of flexibility. We were not held accountable to the same level. We used the, obviously, we used-- >> John: You were running fast and loose. >> And we were, yes, we had a lot of flexibility and we were doing things differently. We were giving away the content in some way. On the online side, there was no pay wall. We started with a pay wall, but advertising kind of was so much more lucrative in the beginning, that the pay wall was shut down, and so I think we experimented a lot, and I think where we missed, and a lot of large companies miss, is that you need to leave your existing business behind and scale your new business, and I think that's very hard to do, which is, okay, we're going to, it's happening at GameStop. We're no longer completely have a control of the market where we are the primary source of where, you talk about your kids, where they go to get their games. They can get the games online and I think-- >> It's interesting, people are afraid to let go because they're so used to operating their business, and now it has to pivot to a new operating model and grow. Two different dynamics, growth, operation, operating and growing. Not all managers have that growth mindset. >> And I think there's also an experience thing. So most people who are in these businesses, who've been running these businesses very successfully, have not been watching what's happening in technology. And so the technology team comes out and says, look, let me show you what we can do. I think there has to be this open and very, very candid discussion around how we are going to transform-- >> How would you talk about your peer, developed peers out there, your peers and other CIOs, and even CISOs on the security side, have been dealing with the same suppliers over, and in fact, on the security side, the supplier base is getting larger. There's more tools coming out. I mean who wants another tool? So platform, tool, these are big decisions being made around companies, that if you want to be data-centric, you want to be a data-centric model, you got to understand platforms, not just buying tools. If you buy a hammer, they will look like a nail, and you have so many hammers, what version, so platform discussions come in. What's your thoughts on this? Because this is a cutting-edge topic we've been talking about with a lot of senior engineering leaders around Platform 2.0 coming, not like a classic platform to... >> Right, I think that each organization has to leverage or build their, our stack on top of commodity platforms. You talked about AWS or Azure or whatever cloud you use, and you take all their platform capability and services that they offer, but then on top of that, you structure your own platform with your vertical capabilities, which become your differentiators, which is what you take to market. You enable those for all your product lines, so that now you are building capability, which is a layer on top of, and the commodity platforms will continue to bite into your platform because they will start offering capabilities that earlier, I remember, I started at this company called BrassRing, recruitment automation. One of the first software-as-a-service companies, and I, we bought a little company, and the CTO there had built a web server. It was called, it was his name, it was called Barrett's Engine. (chuckles) And so-- >> Probably Apache with something built around it. >> So, in those days, we used to build our own web servers. But now today, you can't even find an engineer who will build a web server. >> I mean the web stack and these notions of just simple Web 1.0 building blocks of change. We've been calling it Cloud 2.0, and I want to get your thoughts on this because one of the things I've been riffing on lately is this, I remember Marc Andreessen wrote the famous article in Wall Street Journal, Software is Eating the World, which I agree with in general, no debate there, but also the 10x Engineer, you go into any forum online, talking about 10x Engineers, you get five different opinions, meaning, a 10x Engineer's an engineer who can do 10 times more work than an old school, old classical engineer. I bring this up because the notion of full stack developer used to be a real premium, but what you're talking about here with cloud is a horizontally scalable commodity layer with differentiation at the application level. That's not full stack, that's half stack. So you think the world's kind of changing. If you're going to be data-centric, the control plane is data. The software that's domain-specific is on top. That's what you're essentially letting out. >> That's what I'm talking about, but I think that also, what I'm beginning to find, and we've been working on a couple of projects, is you put the data scientists in the same room with engineers who write code, write software, and it's fascinating to see them communicate and collaborate. They do not talk the same language at all. >> John: What's it like? Give us a mental picture. >> So a data scientist-- >> Are they throwing rocks at each other? >> Well, nearly, because the data scientists come from the math side of the house. They're very math-oriented, they're very algorithm-oriented. Mathematical algorithms, whereas software engineers are much more logic-oriented, and they're thinking about scalability and a whole lot of other things, and if you think about, a data scientist develops an algorithm, it rarely scales. You have to actually then hand it to an engineer to rewrite it in a scalable form. >> I want to ask you a question on that. This is why I got you and you're an awesome guest. Thanks for your insights here, and we'll take a detour into machine learning. Machine learning really is what AI is about. AI is really nothing more than just, I love AI, it gets people excited about computer science, which is great. I mean my kids talk about AI, they don't talk about IoT, which is good that AI does that, but it's really machine learning. So there's two schools of thought on machine. I call it the Berkeley school on one end, not Berkeley per se but Berkeley talks about math, machine learning, math, math, math, and then you have other schools of thought that are on cognition, that machine learning should be more cognitive, less math-driven, spectrum of full math, full cognition, and everything in between. What's your thoughts on the relationship between math and cognition? >> Yeah, so it's interesting. You get gray hair and you kind of move up the stack, and I'm much more business-focused. These are tools. You can get passionate about either school of thought, but I think that what that does is you lose sight of what the business needs, and I think it's most important to start with what are we here trying to do, and what is the best tool? What is the approach that we should utilize to meet that need? Like the other day, we were looking at product data from GameStop, and we know that the quality of data should be better, but we found a simple algorithm that we could utilize to create product affinity. Now whether it's cognition or math, it doesn't matter. >> John: The outcome's the outcome. >> The outcome is the outcome, and so-- >> They're not mutually exclusive, and that's a good conversation debate but it really gets to your point of does it really matter as long as it's accurate and the data drives that, and this is where I think data is interesting. If you look at folks who are thinking about data, back to the cloud as an example, it's only good as what you can get access to, and cybersecurity, the transparency issue around sharing data becomes a big thing. Having access to the data's super important. How do you view that for, as CIOs, and start to think about they're re-architecting their organizations for these digital transformations. Is there a school of thought there? >> Yes, so I think data is now getting consolidated. For the longest time, we were building data warehouses, departmental data warehouses. You can go do your own analytics and just take your data and add whatever else you want to do, and so the part of data that's interesting to you becomes much more clean, much more reliable, but the rest, you don't care much about. I think given the new technologies that are available and the opportunity of the data, data is coming back together, and it's being put into a single place. >> (mumbles) Well, that's certainly a honeypot for a hacker, but we'll get that in a second. If you and I were doing a startup, we say, hey, let's, we've got a great idea, we're going to build something. How would we want to think about the data in terms of having data be a competitive advantage, being native into the architecture of the system. I'll say we use cloud unless we need some scale on premise for privacy reasons or whatever, but we would, how would we go to market, and we have an app, as apps defined, great use case, but I want to have extensibility around the data, I don't want to foreclose any future options, How should I think about my, how should we think about our data strategy? >> Yes, so there was a very interesting conversation I had just a month ago with a friend of mine who's working at a startup in New York, and they're going to build a solution, take it to market, and he said, "I want to try it only in a small market "and learn from it," and he's going very old school, focus groups, analytics, analysis, and I sat down, we sat at Grand Central Station, and we talked about how, today, he should be thinking about capturing the data and letting the data tell him what's working and what's not working, instead of trying to find focus groups and find very small data points to make big decisions. He should actually utilize the target, the POC market, to capture data and get ready for scale because if you want to go national after having run a test in... >> Des Moines, Iowa. >> Part of New York or wherever, then you need to already have built the data capability to scale that business in today's-- >> John: Is it a SaaS business? >> No, it's a service and-- >> So he can instrument it, just watch the data. >> And yes, but he's not thinking like that because most business people are still thinking the old way, and if you look at Uber and others, they have gone global at such a rapid pace because they're very data-centric, and they scale with data, and they don't scale with just let's go to that market and then let's try-- >> Yeah, ship often, get the data, then think of it as part of the life cycle of development. Don't think it as the old school, craft, launch it, and then see how it goes and watch it fail or succeed, and know six months later what happened, know immediately. >> And if you go data-centric, then you can turn the R&D crank really fast. Learn, test and learn, test and learn, test and learn at a very rapid pace. That changes the game, and I think people are beginning to realize that data needs to be thought about as the application and the service is being developed, because the data will help scale the service really fast. >> Data comes into applications. I love your line of data is the new software. That's better than the new oil, which has been said before, but data comes into the app. You also mentioned that app throws off data. >> Yuvi: Yes. >> We know that humans have personal, data exhaust all the time. Facebook made billions of dollars on our exhaust and our data. The role of data in and out of the application, the I/O of the application, is a new concept, you brought that up. I like that and I see that happening. How should we capture that data? This used to be log files. Now you got observability, all kinds of new words kind of coming into this cloud equation. How should people think about this? >> I think that has to be part of the design of your applications, because data is application, and you need to design the application with data in mind, and that needs to be thought of upfront, and not later. >> Yuvi, what's next for you? We're here in Sand Hill Road, VC firm, they're doing a lot of investments, you've got a great project with GameStop, you're advising startups, what's going on in your world? >> Yes, so I'm totally focused, as you probably are beginning to sense, on the opportunity that data is enabling, especially in the enterprise. I'm very interested in helping business understand how to leverage data, because this is another major shift that's occurring in the marketplace. Opportunities have opened up, prediction is becoming cheap and at scale, and I think any business runs on their capability to predict, what is the shirt I should buy? How many I should buy? What color should I buy? I think data is going to drive that prediction at scale. >> This is a legit way that everyone should pay attention to. All businesses, not just one-- >> All businesses, everything, because prediction is becoming cheap and automated and granular. That means you need to be able to not just, you need to empower your people with low-level prediction that comes out of the machines. >> Data is the new software. Yuvi, thanks so much for great insight. This is theCUBE conversation. I'm John Furrier here at Sand Hill Road at the Mayfield Fund, for the People First Network series. Thanks for watching. >> Yuvi: Thank you. 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>> live from San Francisco, celebrating 10 years of high tech coverage. It's the Cube covering Veum World 2019 brought to you by the M wear and its ecosystem partners. >> Welcome back. I'm Stew Minuteman here with John Troyer. We're have three days, Walter Wall coverage here at VM World 2019 with lobbying Mosconi North and happy to welcome to the program. To my right is Tom Burns, who is the senior vice president general manager of networking and Solutions at Delhi Emcee and sitting to his right. Another Tom. We have Tom Gillis, who's the S V p and general manager of networking of Security inside VM wear. So I'm super excited. Go back to my roots of networking. Tom and Tom thanks so much for joining us. >> Thanks for having us. Thanks for All >> right. So, you know, Tom, you and I have talked for years now about you know, it was not just s t n, but you know, the changes in the environment. Of course, you know, networking and compute, you know, smashing together and where the role of software in this whole environment has changed. So, you know, let's start, you know, there's some news. Let's get that cover the hard news first. VM Where has the networking pieces? Dell has some software networking pieces also, and there's some more co mingling of those. So maybe walk us through that. >> Absolutely. I think the story this week is about the collaboration that's happening between Tom's team and my team in kind of innovating and disrupting in the traditional networking world. You know, Tom Sad NSX around micro segmentation network virtualization lot going on with analytics and capability to really see what's going on. The network from Cord Out EJ to cloud the acquisition of RV, which is outstanding. Other things that are going on in Vienna, where deli emcee disrupting around the segregation of hardware and software, giving customers that capability to run the nasty need for the connective ity they need, depending upon where the network is sitting. So this week we got two announcements. One is we've got worldwide shipment of the Delhi M CST Land solutions powered by being more great, you know better than none. Software combined with better than none. Hardware coming from del you see, on a global basis worldwide, you know, secure supply chain plus professional service worldwide is a parameter there, right? >> And Tom, maybe bring us in. You know, we'd watch Fellow Cloud before the acquisition esti weigh on. You know, there's a lot of solutions that fit in a couple of different markets. It's not a homogeneous market there. Maybe give us just kind of the camp point from Avella Clubs. Esty Esty. >> Wind is a white Hart market on because it has the classic combination a better, faster, cheaper. It delivers a better end user experience. It is so easy to deploy this and it saves money, NPLs, circuits and back hauling traffic those that was, ah, 19 nineties idea. It was a good idea back then, but it's time for a different approach. >> And just when I've talked to some customers and talk to them about their multi cloud environment, SD Wind, one of those enabling technologies that you know they will bring up to a mad allowed them to actually do that. >> It was it was the movement really >> office 3 65 and sass applications that drove the best human revolution and that back hauling all this traffic to headquarters and then going out to office for 65 when a user might be in, You know, Des Moines, that doesn't make any sense. And so so with us, the win we intelligently route the traffic where it needs to go delivers a better end user experience, and it saves a bunch of money. It's not hard to imagine that cheap broadband links are on order of magnitude lower than these dedicated mpls circuits. And the interesting math is that you could take two or three low cost links and deliver a better experience than with a single dedicated circuit. >> I'm kind of interested in the balance between hardware and software, right? The family trees of networking and compute kind of were different because if they had specialized needs in silicon, so where are we now? It's 2019. Where are we now? With with line speeds and X 86 then the hardware story. >> I think it'll let Tom join the discussion around speeds and feeds is not dead, but it should be dying to get a quick right. You know, it's around virtual network functions and everything really moving to the software layer. Sitting on top of commoditized X 86 based you know, hardware and the combination of these two factors help our customers a lot more with flexibility, agility, time to deploy, return on investment, all these types of things. But I mean, that's my view is a recurring theme you're gonna hear. Is that in networking? And think you're alluding to this You needed these dedicated kind of magical black boxes that had custom hardware in order to do some pretty basic processing. Whether it be switching, routing, advanced security, you had to run things like, you know, hardware. Regular expression, matching et cetera was about three years ago that Intel introduced a technology called D P D. K, which is an acceleration that allowed VM wear to deliver in software on a single CPU. You know, we could push traffic at line rates, and so so or, you know, faster than one rates. And so that was sort of like there wasn't the champagne didn't go off in the, you know, the bald in drop in Times Square. But it's a really important milestone because all of a sudden it doesn't make any sense to build these dedicated black boxes with custom hardware. Now, general purpose hardware, when you have a global supply chain and logistics partner like Dell, coupled with distributed software, can not only replace these network functions, but we can do things completely differently. And that's really you know, we're just beginning this journey because it's only recently that we've been able to do that. But I think you're gonna see a lot more that in the future. >> So we talked about SD win. Uh, there was a second announcement >> that goes back into the court. You know, the creation of a fabric inside of the data center is still a bit difficult. I mean, I've heard quotes saying It's something like 120 lines of cli, you know, per switch. So let's say 4 to 6 Leafs pitches, switches and two spine switches could take days to set up a fabric. What we've announced is the smart Fabric Director, which is a joint collaboration and development between Veum Wear and Delhi emcee that creates this capability to tightly integrate NSX envy Center into the deli emcee power switch, family of data center switches, really eliminating several cases and in fact, setting up that same fabric in less than two minutes. And we're really happy about not just the initial release. But Tom and I have a lot of plans for this particular product and in the road map for, you know, quarters and years to come about really simplifying again, the network automating it. And then, really, our version of intent based networking is the networking operating the way you configured it, you know, when you set it up and I think not just not just on day one, but two, you know and a N and you know you hit the nail on the head. Networking has changed, is no longer about speeds and feeds. It's about availability and simplicity. And so, you know, Del and GM, where I think are uniquely positions to deliver a level of automation where this stuff just works, right? I don't need to go and configure these magic boxes individually. I want to just right, you know, a line of code where my infrastructure is built into the C I. C. D pipeline. And then when I deploy workload, it just works. I don't need an army of people to go figure that out right, and and I think that's the power of what we're working together to unleash. >> So when something technology comes up like like SD win. Sometimes there's a lot of confusion in the marketplace. Vendors going out one size fits all. This will do everything Course. Where are we in the development of SD win and what is the solution? Who should be looking at taking a look at the solution now? >> SD win market, as I said, is growing depend on whose estimate you look at between 50 and 100% a year. And the reason is better, faster, cheaper. Right? So everyone has figured out, you know, like maybe it's timeto think differently about about architecture and save some money. Eso we just announced it on the PM or side, an important milestone. We have more than 13,000 network virtualization customers that includes our data center as well as yesterday, and we don't report them separately. But 13,000 is, you know, that's almost double where it was a year ago. So significant customer growth we also announced were deployed together with our partner from Del 130,000 branches around the world. So by many metrics, I think of'em, where is the number one vendor in this space to your point it is a crowded, noisy space. Everybody's throwing their hat in the Rangel. >> We do it too. >> But I think the thing that is driving the adoption and the sales of our product is that when you put this thing in, it fundamentally changes the experience for the end user. There's not a lot of networking products that do that. Like I meet customers like this thing is magic. You plug it in and all this and streaming just works, you know, like Google hangouts or Web X is like they just work and they worked seamlessly all the time that there's something there that I think it's still unique to the PM or product, and I think it's gonna continue to drive sales in the future. So I think the other strong differentiation when it comes to Del Technologies bm where in Delhi emcee combined is we have this vision around the cloud. You know, EJ core cloud and you know this hybrid multi cloud approach. And obviously SD Ram plays a critical part as one of the stepping stones as relates toe, you know, creating the environment for this multi cloud environment. So, you know, fantastic market opportunity huge growth. As Tom said, markets probably doubling in size each year. I don't know what the damn numbers are. I hate to quote, but you know, we really feel is, though now having this product in this capability inside a deli emcee, again combining our two assets, it could be the next VX rail. We're really good way. Believe the esteem and it's gonna be a gigantic market. And I think that what's interesting about our partnership is that we can reach different segments of the market in a V M, where we tend to focus on the very high end, large enterprise customers. Technically very sophisticated, delicate, rich customers we don't even know we don't even talk to, And a product is simple enough that it works in all segments. We win the very, very biggest, and we win these. You know, smaller accounts where the simplicity of a one quick deployment really really matters. >> Tom. One of the things that excited me a year ago at this show was the networking vision for a multi cloud world reminded to be of nice syrup. React. You know, when we look at networking today, most remote network admin a lot of the network they need to manage. They don't touch the gear. They don't know where it lives, but they're still responsible. Keep it up and running. And if something goes wrong, it's there. It is the update as to where we stand with that where your >> customers are asking the question, right? So our mantra is infrastructure is code, and so no one should ever have to log in with switch. No one should have to look into a Q. And you know, we should have to be like trying to move packets from here. They're just It's very, very difficult. I'm not really feasible. And so So as networking becomes software and those general purpose processors I talk about are giving us the ability to to think about not just a configuration of the network but the operation of the network in ways that were never before possible. So, for example, we announce that the show today with our monitoring product ve realise network in sight. We call it Bernie, not always such clever with the names that were really good at writing code, Vernon gives us the ability to measure application response time from the data center all the way out to the edge. So a single pane of glass we can show you. Oh, here's where it's broken whether it's in the network, whether it's in the server, whether it's the database, that's that's not responding. And we do this all without agents, right? So it's like when the infrastructure gets smart enough to be able to provide that inside, it changes the way the customer operates on. That translates into real savings and real adoption. And that's what's driving all of this momentum, right? That 7 500 to more than 13,000 customers, something has to be behind that. I think it's It's the simplicity of automation. >> CLI has come up a couple times here, and so that's kind of a dirty word. Maybe even these days, it kind of depends on who you're talking with, I think Veum Way. Rendell both spent a lot of time and effort educating the networking engineering market and also educating the kind of data center you know, the rest of the data center crew about, you know, about each other's worlds. Where again, where are we at now? It sounds like with director on with the innocent. The NSX whole stack? Yes. Uh, the role is changing of a network engineer. But again, where are we in that? In that evolution? >> I think you know, we're early on, but it's moving quite rapidly. I think the traditional network in engineer and networking admin is gonna need to evolve. You know more to this, Dev Ops. How do I bring applications? How do I manage the infrastructure? More like a platform. I mean, Tom and I truly believe that the difference between cute and network infrastructure is really going to start to dissolve over time. And why shouldn't it? I mean, based upon what's happening with the commoditization and speeds of the CPU versus the MP use coming from Mersin silicon, it's really beginning to blur. So I think, you >> know, we're in the early >> stages. I mean, certainly from a deli, see perspective. We still, at times, you know, have those discussions and challenges with traditional networking people. But let's face it, they have a tough job. When something's not working, the network administrator usually gets blamed, And so I think it's a journey, uh, and things such as the del Technology Cloud Open networking, NSX, and now SD when it will continue to drive that. And I think we're going to see a rapid change in networking over the next 12 18 to 24 months. I talked to a number of customers that has said, You know, this journey that Tom was talking about is this is a challenge because the skill set is different. My developers need to learn software, and so what? We're working with the M where is trying t o make that software easier and easier to use it actually approach like English language. So latest versions of NSX have these very simple, declarative AP eyes that you can say, Oh, server A talk to server be but not server see, Click Don Deploy. And now, in our partnership with L, we can take that Paulson push it right down into the metal, right down into the silicon. And so so. Simplification and automation are the name of the game, but it is definitely a fundamental change in the skill set necessary to do Networking. Networking is becoming more like software as opposed to, you know, speeds and feeds and packet sniffers and more the old traditional approaches. >> Tom, I don't want to give you the final word as to Ah, you know what people should be taken away from Dell in and Veum wear in the networking space. Well, >> I think across deli emcee and in being work, there's a great amount of collaboration, whether it's the Del Technology Cloud with of'em were really taking the leadership from from that perspective with this multi hybrid cloud. But in the area of networking, you know, Trudeau. Five years ago, when we announced the desegregation of hardware and software, I am in this to disrupt a networking business and to make networking very different tomorrow and in the future than it has been in the past for our customers around. He's deployment, automation and management, and I think that's a shared vision with Tom and his team and the rest of BM, where >> Tom Gillis, Tom Burns, thank you so much faster. Having eight, we'll be back with more coverage here from VM 2019 for John Troyer on stew. Minutemen as always. Thanks for watching the Cube

live from Las Vegas it's the cube covering AWS reinvent 2018 brought to you by Amazon Web Services Intel and their ecosystem partners welcome back everyone to the cubes live coverage of AWS reinvent here at the Venetian in Las Vegas I'm your host Rebecca night along with my co-host Dave Volante Rebecca we work together this week and I'm excited for our next guest he is an esteemed cube alum Harish Venkat vice president global sales enablement and marketing at Veritas technologies welcome back to the Q thank you very much thank you see you Gary good to see you David so you've been to this is not your first rodeo you know many AWS reinvents what are you hearing what what are you hearing on the ground from your customers what trends are you seeing what most excites you yeah first of all that's great to be part of reinvent you know love the buzz here it's very electrifying and we're very happy about our partnership with AWS and we're very happy about the sponsorship for reinvent as well if there are any skeptics out there who's still thinking cloud is still a fashion statement they really need to reassess their statement because proud is in full effect for both computer and storage the other trend that I'm seeing is globalization is in full effect ideas are flowing swiftly and freely through the borders and then when you think about technology technology is very exciting the global GDP is what about 79 trillion IT spend about four trillion but it's interesting to see the four trillion sort of fueling the growth for the 79 trillion I also think AI machine learning deep learning all of this is going to reshape not only the software industry but I think it's going to reshape the way we live our lives and the last thing I'll say is data hands down as the new currency for enterprise right exactly we keep hearing this data is the new oil data is the it is the currency it's even more valuable I got our take on this okay so I can take a quarter oil and/or a gallon oil I can put it in my house or I can put it in my car I can't do both with that same resource data it doesn't follow the laws of scarcity I can use that same data from multiple use cases so by premises it's more valuable than oil what do you think I think the versatility of data is not the same as oil oil has very limited purpose and I think it's important and we are all dependent on it but data is so meaningful the amount of insights you can get it provides you a competitive edge in the industry it is unbeatable so yeah oil not say mono reefs I've had the pleasure of doing a couple of Veritas solution days yes I did Veritas vision last year you guys have broken that up into multiple cities this year I did New York and Chicago just at ease with the last 30 to 45 days yeah had some great conversations with customers some Veritas execs the conversation was obviously heavy kool-aid injection of Veritas technology your roadmap your vision really really detailed stuff obviously a cloud was a piece of that the conversations here I'm sure a much more cloud oriented now can you talk about the discussions that you're having the focus that you have on cloud generally in AWS specifically yeah sure look I mean data is growing year over year and and customers are still trying to figure out how to manage the data how am I going to work out the economics of this by leveraging cloud and this is not an easy equation to solve by no means and this is where Veritas and cloud service providers like AWS are really taking the market leadership role and then figuring out how do we leverage the entire data landscape if you will so before you even think of cloud the first thing you want to know is where does my data reside and what type of data do I have so Veritas is able to provide that visibility of data classification of data we provide immense amount of deduplication ratio which helps with the economics of this ratio this equation so I think we provide an end to solution from visibility classification deduplication even helping new application and data to the cloud and the partnership with AWS is really enabling customers to solve that conundrum that you're talking so I want to double click on this you know so as a as a as a person who understands backup and recovery deeply as a working for a company that's that's their business and of course you're extending beyond backup and I understand that but you know snapshots replication that's not backup in recovery so when I see something like outpost outpost is this on Prem infrastructure appliance that AWS is bringing as part of its hybrid strategy I want to know how is that gonna be protected now of course they'll talk about the way in which they protect it but a company like yours has a different philosophy your recovery is everything the whole data management approach how do you guys think about data management and data protection you know beyond snapshots or beyond just replication can you explain that yeah so I think the best way to explain that would be to talk about a customer use case great and while several customers come to mind I want to talk about see IMC I think it's a perfect embodiment of all the business use cases that we've been discussing so far ok see IMC is China International Marine container and they've been in business since 1980 you know employ about 51,000 based out of Shenzhen in in in China and they started their digital transformation in 2017 and what they're trying to do is really achieve three things one move all of their business application to the cloud starting with their strategic ERP in this case it was s AP and s AP Hana and the other thing is because they've been around since 1980s a lot of their processes are outdated it's very manual and they had a lot of dependency on tape as part of their backup and recovery so they want to modernize but they want to modernize that piece of it and then the last thing is they wanted a state-of-the-art disaster recovery which is also required by the local compliance laws in China where it doesn't matter where your business application is running they needed a copy of data on Prem so they evaluated all the different vendors market and clearly they chose Veritas as well as AWS to solve that business problem why why did they choose you guys yeah so you know obviously Veritas is number one in data protection 15 years in a row we got more than 50 thousand customers 96 percent of Fortune 100 trust their data with us but more importantly I think it's the partnership with AWS that really helped solve this problem and let me tell you how they did it I think that's important so the first thing they did is they launched an instance of net backup in AWS you know gone are the days where you're completely dependent on purpose-built appliance people are switching over to virtual appliance and they were able to do that by the partnership with Veritas and AWS so an instance in AWS leveraging s3 for the immediate server two days after the data they moved on s3 data over to s3 ia and eventually to glacier you know obviously Andy Jessee has been talking quite a bit in terms of increased throughput from s3 to glacier which is going to help this cause and then when you when you think about how customers are dealing with the transition to the cloud not everyone's ever going to move there all of their application to the cloud it's going to be a journey with time but what that creates in a customer environment is you got critical data in the cloud critical data on prem and they're looking at one data protection solution for both on prem and cloud and this is where Veritas net back really comes and that backup really comes in well I want to ask a little bit about that journey because as you said they don't have everything in the cloud so how has Veritas and any available AWS this sort of three-way partnership how are you how does that work I mean our user hand-holding them are you is it a co-creative process can you can you riff on that a little bit yeah sure so you know just like any of their lines we start off with the technical alliance we want to make sure that whatever use case that we're going to the market and all of those use cases are really coming from customers we understand customer challenges we work with different companies and cloud service providers in this case AWS to make sure that the solution that we take to the market is complete there's absolutely no hiccups we got professional services to help them to mitigate the risk factors and to considerations that most customers are thinking about one is costs another one is performance and thanks to net backup a IR or auto image replicator you know we are able to take a 2/3 of the network bandwidth out so you can achieve all of that performance with one third the network we got incredible deduplication ratio the storage cost as a result as 50 times less than what you would get and so back to the to consideration factor performance and cost we're able to do that in collaboration with AWS so I wonder we could talk about multi cloud or poly cloud as we sometimes call it so you can infer from listening to AWS that it really is better off having a one cloud strategy but as we know oh you say you talk to customers there's no one customer cloud strategy the customers are made up of there's like the government there's multiple constituencies in the company and shadow IT and so there's multi clouds you don't care whether it's one cloud a moment about you're there to protect it but I'm interested in what years you're seeing so what are you seeing and how are you because we we know it's not more than it's more than just one it's not just on Prem in one cloud how are you approaching that problem talk about customers and what their kind of roadmap looks like in their strategic plans and where you fit yeah so back to your point I don't think we'll ever see just one cloud the dependency on just one cloud is not happening we're seeing multiple clouds we're seeing hybrid clouds obviously you know Azure stack is coming up with their own version and so is AWS and in a customer's environment you are seeing that now there's also talks about are we going to see cloud to cloud movement cloud to cloud disaster recovery I am not seeing that at all I think the economics of cloud to cloud move over our failover is just too expensive so I think we're still seeing physical to cloud cloud back to physical and then one physical to another cloud I don't see a whole lot of cloud movement so where Veritas really comes in as our ability to provide that disaster recovery both from physical to physical protect your data in the same assured way on Prem as well as the cloud allowing you to leverage the cloud as a disaster recovery mechanism in fact I was having breakfast with Bell media this morning and they have two sides in Canada that they're using disaster recovery and they're wanting to leverage cloud and he's super excited about net backup eight one two cloud catalyst you know ability to leverage cloud as the disaster recovery and with our VRP was just Veritas resiliency platform to achieve that so a culmination of all of that hopefully answers their question absolutely and I think that's right on you had referenced earlier in your commentary Harish that you see some major changes coming for the software industry and we were we were talking to Jerry Chen the other day from Greylock in a really sharp former VMware now he's you know VC so he sees a lot of stuff and he put forth the premise that everything's changing in software development as a software company I wonder if you could you could comment that Amazon is essentially giving all these this tooling to create new software apps but as a software player how do you guys look at that how are you modernizing you know your platform and what do you see is the outcome yeah so you know it's interesting you talked about VSD in New York obviously and I spoke about it and when I talked about two things over there which was really ease of use and simplicity and and that's really where the customers are gravitating we have to make sure that any platform in the software industry has the 3.click to value mantra built in you can't be having the green screens anymore so Veritas has taken the same approach we're really looking at ease of use and simplicity and three clicks to value so that's a big trend you know I talked about AI and machine learning and deep learning you know gone are the days where everyone is reacting to something now it's all predictive analytics how do I garner more information so we're building AI and machine learning into our platform where if there's an outage we're going to tell you beforehand some of the reasons before or beforehand into some of the reasons behind it and that way you can address it and not be a subject to a reactive catastrophe so I think those are two big things that I'm seeing in the software-defined storage and the second thing is just an overall ecosystem right so it's not just about standalone value but how do you collaborate with the rest of the software providers to build a bigger and better solutions as an example our relationship with AWS is speaking very highly of that we're solving bigger and better problems as a result of this we just announced our alliance with pure storage with their data hub architecture we're able to do you know data protection with IOT s which is again another trend in the marketplace where we can share protect and collaborate with pure data as well well let's talk with the edge in terms of data protection for the edge how'd how does the edge IOT how does that affect customers data protection strategies and what's Veritas is angle there yeah so you know I mentioned this in in Microsoft ignite because Satya had mentioned this in his keynote saying that the edge computing there's a lot of proliferation around that and it's not just a compute fact because a lot of data has been generated in that too so how do you make sense of all of that data how do you which ones do you protect which ones do discard so Veritas has that solution which allows you to sift through all of that data figure out which one's important classify that and then help you provide data protection for the edge computing I'm thinking about yesterday's keynote with Andy Jesse a dizzying number of announcements of new products and services new innovations and it's and this is really de rigueur at an AWS reinvent is this is this pace sustainable I mean this this constant innovation I mean is that sustainable what are you you know it's interesting you asked me that question because it's the same concept of is Moore's lot going to be sustainable right so far we're seeing that it is and as a result you're seeing all these madness around innovation you know driverless cars and you know journey to the another planet in a I and and ml and full effect and all of this is going to reshape our future so far I'm not seeing any signs of slowing down as long as Moore's law is going to keep up with its multiplier effect I think we'll see better better lifestyle and more and more innovation just the amount of patents that we're seeing with new startups it's just off the charts so I'm a big proponent of innovation and I think this will this will continue going on well I think if I could comment I think Moore's Law in many ways was was one-dimensional I mean you had the doubling of you know performance every 18 months whatever it is now you have this multi-dimensional innovation combination Moore's Law fine but you've got data you've got machine intelligence applied to that data and you've got the cloud at scale so this you have this combinatorial effect that has multiplicative effects on innovation so that our argument is the curve is actually bending you know into a nonlinear and it's mind-boggling there's big pace of innovation you certainly see that here from from Amazon it seems to be accelerating and it's it's underscored by the number of announcements that this company is making others trying to keep pace them forcing their customers to keep pace it's him it actually feels like it's it's speeding up not decelerating without a doubt and I think it depends on the type of company you're talking about if you're a startup company you know and have any of the legacy things that you're talking about you're spending all of your IT spent on innovation you look at a classy IT spend equation 85% of it just to keep the lights on and less than 10% on innovation I think that is mind-boggling to me and that's why some of these new startups are constantly challenging you know fortune 500 companies whose lifespan used to be 65 years but now at 16 years and it's constantly getting down because of this effect as well and I think that's a great point if if you're stuck in that 85% technical debt world and you don't allocate enough for innovation yeah it's it's going to be problematic and so what we see is customers looking at it as a portfolio we got run the business we have grow the business we have transformed the business we're going to deliberately allocate cash to each of those and hopefully bet on the right things yeah not a doubt I mean look at the at the end of it as a result of all these different phenomenons that we're talking about it is good for consumers because they're looking at more and more options better technology and those sort of fierce competition is always good for everyone as consumers as well as enterprise great well Harish thank you so much for coming on the cables my pleasure I'm Rebekah night for DES Volante we will have more of the cubes the live coverage of AWS re-invent coming up in just a little bit [Music]