>>from around the globe. It's the cue with digital coverage of out systems. Next Step 2020 brought to you by Out Systems. I am stupid, man. And this is the Cubes coverage of out systems. Next step 2020. And we've love when we get to be able to talk to the practitioners when we come to these events and happy to welcome to the program first time dress. Bruce Bottles. He is the digital channels director at Humana. Give a presentation this year. Also last year. The physical event. Bruce, thank you so much for joining us. Great having on the Cube >>A stew. Thanks so much for having me. It's pleasure to be here. >>All right. So Bruce Humana, a company that most people probably are familiar, you know, health care, of course, super important in general. And even more so in 2020. But if you could just set up for us a little bit, how should we think of Humana these days, your role inside the organisation on? Then we'll get into the discussion from there. >>Yeah, it's a great point, you know, because Humana is and has been going through a pretty significant transformation and one of the big reasons why I joined human about 2.5 years ago was this goal to go from Justin Insurance Company to really a full service healthcare company. So to now, now we're really bridging the gateway where we're almost half of our staff are caregivers are doctors and nurses and clinicians and the other half of us kind of run the business. Eso My role is digital channels, as you would expect, leading up efforts across humana dot com Our mobile APS go through 65 other fitness and, well, this APS as well as pharmacy business. So, uh, good question. >>Awesome. First, I tell you, one of the my favorite conversations over the last few years has been that discussion, you know, digital transformation. It was a buzzword. It gets a little bit overused. But from our standpoint, the companies that are doing it, you know, data is centrally important. We understand what we're doing. We're leveraging modern technologies and worms out there. Can you bring us back a little bit? You know, 2.5 years ago, I'm sure you're rapidly going through a whole bunch of changes, but you know what's the mandate? What are some of the key important pieces along that journey? >>Yeah, that's a great point, because I I do think digital transformation, unfortunately, is a little bit over used and, like most technology waves can be hyped. Um, you know, But the reality is for us, a Humana is that you are heart truly desires to reach our customers, and new and better ways is to meet their needs. Not only that, we know they have today, but the anticipation forecast what those needs are gonna be tomorrow and start building those solutions today for what we know they're gonna need in the near future. So what are the challenges that I saw when I came to the company a couple years ago Was just the quality in the speed and ability to react to new opportunities and unforeseen circumstances and challenges Is that ability to move fairly quickly. To me, that's one of the keys of digital transformation. Is that out? The speed and quality? >>Well, you know, Bruce absolutely. You know, in 2020 hit, the commentary we had is those those companies that have already gone down this journey, as you say, agility. Big able to react really fast, are happy that they done it in anybody that hadn't gone really started down or gone fast were like, Oh, my gosh, I need to get there fast because obviously, 2020 brought a lot of new challenges in place. I want to hold off one minute longer before talking about the specific 2020 challenges because you've got a great story there, but out system says you've been a partner with them. You spoke last year. Conference. What do you bring us back as to how they first got involved? And, you know, what was the plan? Uh, pre 2020? >>Yeah. So it's my journey has been interesting. I've been part of our systems for about six years now, actually. And ah, one of the reasons I came to Humana was the opportunity to introduce the company to a new way to this low code concept. Had used out systems to start a couple of companies prior to Humana and, ah, about 18 months ago, we actually signed the first contract at human of without systems. So you know what? We really are joined Now, is this new opportunity to move quickly to build things differently and to respond Those Like I said, those opportunities that were neighborhood didn't have before. So that's my journey without system that didn't start with Humana. But, ah, I have really enjoyed working with them over the last six years. >>Well, is, you said that ability react fast is something that's been the promise of, but forms clouds and the like wealth. 2020 20. You need to react fast. So, uh, enough set up, I guess. Why don't you tell us how cove in 19 the impact what you you and your team needed to do to kind of move fast and get toe what the internal as well as external customers we're going to need. >>Yeah, thanks for the intro up. You know it really? Let me take it back just a little bit to 2019. So in 2019 we realized that one of our top five interactions that our customers do is they come to our websites and are perhaps looking for a doctor. Uh, we're looking for a hospital or clinic or a pharmacy. And I, doctor, a dentist, etcetera. It's one of the top five interactions on our site. And what we realized is that it was a very disjointed experience. It had been grown up over years. Not uncommon to most. You have Fortune 50 companies. Ah, it was a silo. If you wanted to find a medical doctor, it was different than if you wanted to find a vision, doctor. And it was different if you wanted to find a pharmacy, etcetera s. So not only was it a different experience for customers, but there were different technical solutions. And the cost of maintaining this disparate solutions was really prohibitive to us. Innovating. So I set forth the strategy. Since I was the business owner of one of these, this capability of a dot finding a doctor. I said the roadmap and said we're going to unify them all. So that was our original challenges. To unify all of these fighters into a single provider finder. Well, that was going great. And write about the end of February. We had pharmacy Finder was the first one and then covert hit in March. And thank goodness it did, because hit then because we were ready to respond to one of the most important things our customers asked for And that is help me find a place to get a covert 19 test. We had a giant spreadsheet that the call center was trying to maintain and manage an answer those calls as they would come in and say, Hey, help me find a location to get a test. Well, if you know anything about covert testing, it changes constantly. The testing locations change constantly the type of test they have, the supplies that they have the hours of operations. So it was a daunting task, to say the least. So that's when I stood up and said, Hey, can we volunteer? Can we gather a bunch of volunteers to quickly build some solutions that will help not only the call center, but help our customers serve themselves? So that's really where this Cove in 19 test location came from. It was is out of the genesis of what we had started doing on the provider finder space. >>Yeah, I'm curious. Bruce, I know you gave a presentation here at the event, kind of walk through what you had, Bill. But if you were to look at it, how long did it take to build the covert test? finder, and you've got lots of experience without systems. If you had not already started on this back in 2019 if you had just said OK, I've got a spreadsheet I need to bring in a technology. If I started from scratch, how much longer do you think it would have taken for your team to be able to react? Oh, deploy this new solution. >>That's a great question. In one of the key victories I think we had is you, Honestly, the first challenge that he rented the spreadsheet. We solved that spreadsheet problem in a weekend. So I pulled together some volunteers. I was one of them, and we actually built the replacement for the spread she in a weekend, so that was pretty astounding. That s so the call center was grateful for that, and they quickly had a very unique solution there. But that was really just the touching point where we then took it to is building on top of this unified provider finder. We said, Well, you know, the covert night be testing locations are it s as just in assessments, just another type of provider. So with that perspective, we started building a full back office suite where we had a team of 30 to 40 analysts constant locally, looking across the United States, invalidating testing, location, information, hours of operation, calling them, making sure that they're accurate and then importing all the information into the centralized database that was out systems. Um, and then we quickly were able to build a customer experience where they could. Self search customers could go out there, do a search finding, assessing location themselves, I'd say time wide. We spent about a month building the back office and then deploying out the first version to our customers as well. Very, very rapid, very high quality. On what we've taken it further even since that first month, we're just now actually building it into and integrating it with, ah, health bought that we have developed in parallel separately. Um, but it's just illustrates the agility that we've had the flexibility to be able to take a solution that started out as hey, I want to find a doctor to quickly morphed to help me find a test location for Cove in 19. >>Yeah, it's amazing. Burst. I think back in my career, you know, very early in my career how long it would take to, you know, build the schema, build out a database and populate all the data on how many interference you need to do that to the websites to Now that that that modern app deployment 30 days, you know, that's phenomenal. From kind of full end to end. Obviously you still have some Resource is keeping things up to date. Did you have a rough swag? If you didn't hadn't already been using out systems, would this have been, you know, 23 months or is getting from from the ground up? How long does that take? >>Yeah, good question. You know, overall. Ah, eso Short answer is probably what it took us about four months using traditional methods eso instead of four months, about a month. And that's pretty consistent. What is what we have seen with all of the apse that we've built so far? Without systems, we're seeing about four times the value. I like to say four x value in that being, you know, a quarter of the cost a quarter of the time and we typically will over deliver on scope. It's not too often you can say that, you know, we made it, you know, on budget on time. But we over to alert scope. But but generally speaking, we're seeing about four x value. And I would just say coincidentally, when I was doing the startups I mentioned earlier, I would see up to 10 x value compared to traditional hand coating and large development teams in the start up environment. So smaller companies, I think, should expect to see even better than forex. >>Well, that's great. For since you have such a long history without systems, I'd love to get your take on some of the enhancements is you look at it. It's not just a platform, but they're helping give guidance to build faster. There's really, you know, ai being built in. You know, what have you seen over the years? What's exciting you these days? Anything else that you're kind of asking for, that maybe we should be looking for down on the road map. >>You know, that's one of the greatest things I really enjoy about the ancestors. Partnership is their level of investment in the platform, and they're like like I'm constantly trying to think forward in health care. What of our customers going to need tomorrow. Out Systems is doing the same saying, Hey, what is Bruce going to need to drive his digital business forward in the future? So two big things really come to mind. Number one is mobile. When Version 10 was launched, uh, I started on version nine when versus Ted would launch. It was it was lights out when it came to Mobile. It was an absolute game changer. For the first time, I didn't have to have a large IOS and Android team and a Web team and a back office team so typical I'd have four different teams when the specialties I didn't need that anymore. We could do full stack now with just about any of any developer, so that was huge. The second huge innovation is, I would say the AI you mentioned is that now that the new, um, developer productivity that you see embedded in the app suggestions the it's almost like the platform anticipates what developers need next in their daily tasks. Eso I know that's been a big help. Um, and I think the last thing that I'm looking forward to, that I know they're working on feverishly is really bringing it mawr to even a wider audience of citizen developers. So, designers, we've got a few use cases where our marketing team has worked with us in some of their marketers and designers that aren't developers at all sauce building things. And they said, Hey, you know, after the first couple of APS they designed with us, they said, I I think we can do this ourselves for some basic things. So they did. They started building some basic things. I'm really looking forward to that push out to or, you know, more business folks even further than what they had done before. >>Yeah, but persists. Such a good point. Something I've seen in the serverless community, really enabling, Aziz said. Back in the early days, it was programming you wrote lines of code coding was you pulled pieces. The discussion of low code is trying to make it even simpler and with more modern platform for more about on tools. As you said it tous ip eight things you don't need to You can even have that citizens developer, as you said, go out there. So, uh, first want to give you the final word just you know, Valuev. Seen you've been part of the out systems events in the past. What do you enjoy talking your peers about sharing your story? What? One of the things that you want to make Sure that people, if they're coming to virtual on, maybe it's their first time understand about shows like next step. >>Yeah, next step is just a fantastic event. It's like I always said it. I'm a calendar, never miss it. Disappointed, won't be ableto sit and have a meal with some of the folks in person, but we'll get through it next year. But no, I I'd say you know the sessions. Of course. You know my session. I was excited to share more detail. Ah, on how we went about creating this cove in 19 in this universal finder. So there's tons and tons and tons of sessions just like those great get great insights. Ah, and to make new contacts as well. So I would encourage folks to, you know, pick me up on Twitter, picked up on lengthen ah, and others and, you know, network, because when it comes down to it, we're all innovators, and we're all trying to solve the needs of the communities that we serve. And I believe we're better together. So thanks for having to have me >>Well, person, but we love being able to share those stories. Thank you so much for what you were able to do. Such a valuable, important thing that the community as a whole. And thank you for sharing your story on the Cube. >>Great. Thanks again for having me. Thanks to >>stay with us for watch more coverage from out systems. Next step is to Milliman, and thank you for watching the Cube.

(funky music) >> Live from Las Vegas, it's theCUBE, covering Informatica World 2019. Brought to you by Informatica. >> Hey, welcome back everyone, this is theCUBE's live coverage here in Las Vegas for Informatica World 2019. I'm John Furrier, your host, with Rebecca Knight who's on the floor getting some data, getting some reports. She's my co-host here this week. Next guest is Bruce Chizen, board member of Informatica, OG, original gangster of the tech scene. Been there, done that. Welcome back to theCUBE, great to see you. >> Yeah, great to see you, John. >> Big alumni. I love having you on because you're kind of, you're a historian through experience, still active in the industry, obviously, Informatica. Four years private. >> Historian, that's scary. >> You've been around the block. You've seen more waves than I have, and that's a lot. But, you know, you've done a lot of things and you've seen the waves. You've run companies, you've been on boards. You've been on Informatica board. Four years private, a lot of great things can go on. Michael Dell proved that. He took Dell Computer, which is now Dell Technologies, he took it private, and I asked him. He wanted to retool and didn't want to do the shot clock of being a public company. Filing, and sour beans and all those regulations, 'cause he knew what was coming, the wave was coming. Informatica did the same thing, so I'm expecting an IPO, or MNA big deal happening. But four years, with great product people, you're on the board. Data, our original conversation four years ago on theCUBE, hasn't changed. >> No. It's the same wave, and now everyone's jumping on the wave. >> The good thing for Informatica is, as a private company, we got to do things that we could not have done as a public company. The level of investment we made in R&D, the transition from perpetual, or on-premise, to subscription. The investment in the sales organization. Couldn't have done that as a public company 'cause the shareholders tend to be too short term focused. >> And also I will add, just to get your reaction to, is that, my observation, looking at these situations when you have smart people, the board, like yourself, and the product team. Which I've been complimentary of Informatica's, as you know. Some other critical analysis, but that's different. But, great product engineering people. When you don't have the pressure of time, you could watch things gestate and when you're early, you have an advantage. Talk about that, because that's a strategic thing, most people aren't talking about, but you an early lead on data. You've had product engineering leadership, and you had time. >> It's not as easy as you make it sound. Keep in mind, Informatica is owned by financial sponsors. Private equity. >> Yeah, there's some pressure. >> CPP. And it's up to people like myself on the board, the other independent board member, the management team, to continue to remind the investors that if we make early investments and they pay off the company will be worth more and they'll ultimately make more money and their partners will make more money. >> I made it sound like you're on the beach drinking wine. >> A great example is what Informatica did with the data catalog. That was an early investment. No one really knew whether it would pan out. Sounded good, but it required a significant investment, that came out of the pockets of our investors and we were able to convince them to do that. Another great example is CLAIRE. You know, AI is hot. Well had we not invested in CLAIRE, three, three and a half years ago, CLAIRE would not be in existence today. Couldn't have done that as a public company. >> And it gives you a little bit of a lead, again, there's just no shot clock on public. But yeah, the private executives, they're not going to let you sit around and hit the beach and clip coupons. You got to work hard. But I got to ask >> The other thing you've seen the company has gone from a great point product company, great products, to really developing a platform, and architecting a platform. Which requires a significant amount of engineering. >> I was going to ask you about that, I'm glad you jumped the gun on that. Platform is the key. Speaking of platforms, I was just at Adobe, a company you're very familiar with, they're rolling out a new platform. Platforms are now back in vogue but it's not the old way. The old way was build a platform, have a competitive advantage, lock in your nested solution in imitability. Now it's platform open, different twist. How is that different? 'Cause you've seen the platform where you got to own it, barest entry, proprietary technology, to platform that's open extensible. >> Yeah, customers have gotten smart. No customer wants to be held hostage to one individual platform. SAP being a great example. Microsoft Windows being another example. They want to make sure that if they choose one platform, they could easily migrate to another. It's one of the reasons why Informatica is in such a sweet spot, because we allow our customers to choose which Cloud infrastructure providers they want to put their workloads on. And they can use multiple Cloud infrastructure. >> I got to ask about the competition now. Not competition but co-opetition, just marketplace in general. Everybody's jumping on the same wave that you guys have been on. You go to YouTube.com/Siliconangle look up Informatica videos I've done here with the team and you four years ago. Look up some of the things we were talking about, not a lot of many people talk about data driven, hardcore analytics, next-gen. These are the kind of topics that in AI machine learning, now everyone's talking about them. What's different about Informatica as the noise level increases around some of these things? Certainly, it's pretty obvious AI is going to be hot. Multi-generational Cloud, multi-generational things can happen. Operations, AI automation. >> Yeah. >> But what's different about Informatica? What should people know about Informatica that might be unique that you can lend some insight into? >> So when I think about the competition, or the co-opetition, I put those competitors in two buckets. There's a whole slew of smaller players that have some really good point products. Fortunately for Informatica, they don't have the scale to compete. And when I say scale to compete, not just on the go to market side, but they can't afford to invest two hundred million dollars a year in research and development building a complete platform. So, even though they're kind of ankle biters and occasionally I feel like the company has to slap them around, and they're annoyances, I don't think they're a big threat. The Cloud infrastructure players, the platform guys, Google, AWS, Azure, will continue to provide data tools that are developed for their stack. They will do some things that will be good enough. The good news is Informatica does great as it relates to enterprise Cloud management. So, if an enterprise really cares about their data, and they really care about having choice in the future, and they don't want to be held hostage to any one platform, Informatica is the only game in town. >> You're one of the best at doing theCUBE. This is our tenth year, and I remember telling some NetApp people because they invested in Cloud early, too, they don't get the credit. This is another example of Informatica invested early on in Cloud. I talked to Emmett and Anil years ago, they were well down that Cloud path. So Johnny-come-lately's going to jump on the Cloud 'cause there's an advantage so props to Informatica. >> And plus it's not Cloud only. Most of the large enterprises are hybrid, they will be hybrid for many years to come. In fact, if you look at workloads today, they majority of the workloads are still on-premise. >> Scales come up a lot. You know my commentary and theCUBE, everyone who watches me knows I like to rap about I was the first to call Amazon the trillion dollar opportunity because of the scale. Scale is the new competitive advantage, I've said that. I've said open is the new lock in. Value is the new lock in is what I said. So now you've got scales. The question is how does a startup compete if scale is table stakes? Is it race for funding? Snowflakes got to three billion dollar evaluation. Are they worth three billion? We're going to analyze that in theCUBE later. But they raise almost a billion dollars in cash. Do you scale up with cash and grow? >> Great technology. It starts out with really great technology. An organization like Snowflake, great technology. Look at Databricks, great technology. So, I look at the great new startups, what makes them great is that they have an innovative technological solution that's hard to replicate. Then they get the funding, and they're able to scale. That's what it takes to be a startup. >> And that's almost the OG, original gangster, Vectra Capital model. >> That's correct. >> Agile, iterate your way to success. No craft, no scale. Just speed. Is the world going back to the old formula? >> It's going back to innovation. To technical innovation. Especially given that you have so many scale players. You can no longer just come in there as a startup. Money alone is not going to enable you to be successful. >> All right I want you to pay it forward for all the young people graduating. I just was at my daughter's Cal, Berkeley graduation yesterday. Although she wasn't in this class. Cal just graduated their inaugural first-generation class of data science. Databricks was involved in that, they donated a lot of software. They're very Cal oriented. People who graduate high school, elementary school, this is a new field. Not enough jobs. Berkeley, a leading institution, first class ever in data science. What skill gaps are out there that need to be filled that people could learn now to get ahead and get an advantage in the workforce? >> My view, John, it starts in middle school with math. If we could help our kids who are in middle school to get through algebra, studies have shown they will move on to undergrad and then many of them will move to graduate work. We've got to start early. Yeah, there's some simple fixes. Help people become coders, help people do other things. But the reality is >> If you can't get the algebra done you're not going to code. >> We have to solve the longer term problems. So when I think about jobs of the future, we've got to create people who are creative, but at the same time understand the basics. >> Math, stats, great stuff. Final question. Are you going to run a company again soon? >> So I get that question quite often. First of all, I love doing what I do today, which is kind of a lot of little stuff. I do miss running a company. But, as I've told a whole bunch of people, I have no desire to ever report to a board again. So unless I own 51% of that company, I will not be running a company. >> Well now you know the deal terms, anyone who's watching for an investment from Bruce partnering with them. Great stuff. What's missing? What's around the corner? What are people missing in the news these days in the trends? What's coming that's exciting that nobody's talking about? >> I think what's happening, and this happens each wave, there's been so much excitement about the movement from On-Premises to Cloud, about AI and machine learning, I don't think people really appreciate how early it is. That we're this much in to it and we've got a long ways to go. And the old workflows that are on-premise, the amount of advancement in artificial intelligence and machine learning has so far to go, that people need to be patient and continue to invest aggressively in what's going to transpire ten years from now, not six months from now. And then you add things like 5G, faster speed WiFi, that also is going to have this huge impact. >> Great insight, Bruce. Thanks for sharing that insight. Get the kids learning math in middle school, gateway to coding, gateway to graduate work. Next ten waves, lot of waves coming. Bruce, thanks for sharing the insight. Good to see you again. >> Thanks, John. It's a pleasure. >> CUBE coverage here in Informatica World 2019. I'm John Furrier with theCUBE. Thanks for watching. We'll be back with more after this short break. (funky music)

>> Live from Las Vegas, it's theCUBE covering VMworld 2018. Brought to you by VMware and its ecosystem partners. >> Welcome back, everyone. It's theCUBE live here in Las Vegas for Vmworld 2018. It's theCUBE's three days of wall-to-wall coverage. I'm John Furrier with my co-host this segment, Alan Cohen, who's an industry legend, retired now, doing a lot of boards, as our guest analyst here for this segment. Our next two guests-- >> Another word for unemployed. (all laugh) >> Bartender in Silicon Valley ??? On boards. Our next two guests, Bruce Shaw, Senior Director of Globalization Solutions, remaking what it means to partner in the cloud, and of course, Keith Norbie, theCUBE alumuni, Manager of bus dev, does the bus dev for NetApp. Guys, thanks for coming on. Thanks for spending the time. >> Oh, thanks for having us. >> The first thing I want to get to is, give us an update on the relationship with NetApp and VMware. Obviously, Pat Gelsinger, spring in his step. Go back three years ago, his job was on the line. So much has happened, the relationship with Amazon, the clarity around the cloud, cloud operations, the role of infrastructure in that, with devops driving programmable infrastructure. Kind of the world's spinning in the NetApps front door right now. >> Yeah, we feel pretty good about it. Keith, he runs that relationship, so I'll let him lead the answer. >> I thought it was best said, and we can kind of unite together, VMware and NetApp on moving from data centers to centers of data. NetApp's been on this data visionary, and sort of the data authority track for a couple years now. You guys have known that; you've been to a net admin site. The relationship, really, is complementary from that perspective, and it goes back many years, more than a decade. If you look at our common base, VMware, of course, has 500,000 users in its install base. We've got a couple 100,000, so it's a gigantic opportunity together to move people exactly in the acts that Pat talked about in the keynote, act one through act four, and getting us all to multi cloud. When you look at the relationship, and the base of the ONTAP products that we have VMware and the architecture, all the way to cloud volumes, and then the latest architecture that we've just done with VMware for NetApp HCI, there's a lot to talk about. >> I've been covering NetApp since theCUBE, nine years, This is our ninth VMWorld, but I've been following the company since the late 90s when they went public. Always a culture of learning and adaptability, but to survive in the past 10 years, specifically, it's really been about adaptation, because if you look at that model, a lot of losers are dead, bankrupt, see companies come and go, but the ones that are customer-centric seem to win. Jassy on stage, very customer-centric. VMware, listening to their customers, got a great community. You guys have a very loyal customer base, both on the customer side, going back to the original products and the partners. >> Right. >> So Bruce, as you think about partnering in the cloud era, when you're now looking at all kinds of different relationships, whether it's in the staff from a technology standpoint, or go to market, or whatever the machination of the relationship is, you got to think differently, so I got to ask you the question. How do you partner? 'Cause it's not just about the profit anymore. What is value in this era? Take a minute to explain the vision. >> Yeah, and you hit it right in the head. The value question is no longer the primary driver of what you're going after. When I say value, just pure revenue stream. You want to look at, obviously, the evolution to an ecosystem, and we spent a lot of time with that on the internal side. Not that anybody cares about what we do under the covers. We restructured our business units from one single business unit into three, so we've got a cloud-focused CDS, which is cloud focuses on the hyperscalers, and our cloud volumes business. CIBU, which is our conversion, hyperconversion infrastrcutures, and then of course, the guys that handle ONTAP, and the big stuff on the back end that provides the building blocks to all of that. >> These are dedicated teams, right? >> Dedicated teams. Dedicated business units, and that gives us the potential of three pathways, in terms of which we partner, and my goal since I came in to run the group in January has been, how do we transition from a traditional alliances organization to evolve to one where we're much more focused on production of solutions, designing with our partners solutions that meet in the market. We're a very channel-focused company. We obviously, you look at the success that NetApp's had over the 10 years with Cisco and FlexPod, that's a meet in the market model, focused on validation to provide solutions for customers, for industry problems, and trying to replicate that through key strategic partners that hit the ecosystem to do it, and that's been a very effective approach for us, and we've spent a lot of time kind of recrafting the organization to match up both with our BUs, and then our delivery through what we call pathways, and that pathway begins from everything, from the channels to the GSIs. We have a new G100 account group, and then to our own sales force, of course. >> All right, so what's in it for me as the customer? I'm like, at the end of the day, it's like, okay, you're reorganized, sounds good. Focused teams, highly cohesive, good segmentation, dedicated teams. What's the impact for the customer? >> The impact for you guys, it's easier to implement, lower cost, quicker delivery, and the assurance that you actually have a validated architecture that's using best of ??? For what you want, as opposed to, I've bought a monolithic stack of something and I'm locked in, and maybe it's the a piece of this and the b of that. You can actually choose your Lego bricks to put together, and we'll stand behind it with the validation that this works. >> Maybe to just kind of pull a layer back on that. Obviously today, we have Andy Jassy on stage with VMware a year later. People were extremely cynical a year ago when that announcement went down. Here they are, they're throwing up their hands. Actually, today-- >> Capitulation was the term. >> Yeah, right, it's capitulation now, but if you are now partnering, and you're building alliances in the cloud era. Three or four years ago, people were saying, "The cloud, they're the enemy. "We can't do business with that." That's what they said, that their customers, their partnerships. How has that changed, and how do you think about partnerships with the cloud providers today? >> Three years ago, the smart people out there said the cloud is going to kill NetApp. >> Right. >> Right? We're an on-premise, standalone storage company. The cloud is the end. Well, fast forward to now, the cloud is our best friend. It's our biggest growing area. You look at the business we do with the hyperscalers under Anthony Lye, and that's the fastest-growing piece of the business we got. We've made it very easy, through ONTAP, to work in either a cloud only relationship, or a hybrid, where you're moving things from on-prem to off-prem and vice versa, and that's becoming main focus of our business, and from an alliances standpoint, of course, once you have it in our own key ingredient, then it's what are the partners that we partner with to bring them into that, to make it a more cohesive solution. >> And then ???Senator, if I might have a second question. >> Of course. >> If I am a customer, and on one side you have your alliance with VMware, and the other side I have my growing initiatives with AWS, or Google Cloud, it doesn't matter. Where does NetApp fit between those two environments? 'Cause you have alliances with both sides. >> Yeah. >> Sure. >> What do I count on NetApp for, because I'm looking multi cloud, I'm looking at migration. How do I think about you in that-- >> To me, I think it's pretty clear. It's all of it needs data to run, just like software needs hardware to run on. Even though it's in cloud, it's rendered. It is all about the transition of being very hardware-defined to being software-defined, to being really function-defined, and once you start to modernize an architecture that way, or a general organization that's trying to deliver IT services, it's the delivery of those things the start to define where you have to take things that are both on-prem and in the cloud, so the entire thing around multi cloud sort of requires that you have strategies for things that are in current data centers that just have to become more cloud-like in their functions and their functionality. Delivering it as a service is not just the mantra, but it's the time to value, and it's the consumption style. As an example, as we're trying to do things on-prem with our NetApp HCI solution, doing embedded OEM with VMware isn't because we want to sell VMware licenses. It's because we want to make it as fast a possible, and as easy for our customer to be able to turn it on and start using it, similar to your experience buying a new iPhone. We want to have you be able to add software to it, like NSX, like vRealize, or a full VMware private cloud stack is something that will hopefully take minutes, rather than hours, weeks or months, because we want that time to value, that consumption experience to be the king, and that extends to data protection, that extends to security. We're not just a storage company. We're a data company that's really in the game for the full stack, and the advantage we have is that we're in all the hyperscalers, and I think we can help VMware there, ??? >> The piece I'd add, I think that's different than before, is most companies think about alliances is us plus them, and in the cloud environment, it's us plus plus plus plus plus to get a solution, and having a much different approach, where it's, okay, we're going to have to be multi-partnered in a cloud environment to go get this done, and that also requires a different alliance motion. >> Less tennis, more soccer. >> Yeah, exactly (John laughs). Great analogy. >> It's yours. >> Tell them the source was theCUBE. >> This show demonstrates how an ecosystem has really extracted the maximum value out of the partners, because there's a ton of this extension to the partner, the channel partner, the pathway partner, to really go and do, moreso than VMware having to do it all themselves, or NetApp having to do it all themselves. It is about that three-way partnership between the product, the solution, and the delivery partner itself, and what AWS even say to them, they said in the partner keynote yesterday that what they want out of the partners is capabilities, and isn't that awesome? We want competencies and capabilities to understand who can deliver these certain capabilities, security, networking, storage, app refactoring, you can go down the list. >> I want to ask you guys, while I've got you both here. I want to get your reaction to something Pat Gelsinger said. He said two things I want get your comments on. One was, he made a comment that said, "No one should ever have to pay for DR ever again CapEx," and two, he made a comment about how AI's 30 years old, and, "Hello, AI, good to see you. "Welcome to the introduction of AI, 30 years later." >> I think he said it's an overnight 30-year success. >> It's an overnight 30-year success, exactly. So one, never pay for DR CapEx, and then hello AI, so again, that kind of signals what's going on. You got the service model, and then you got AI. It's an enabler, and one is a changeover. Curious what are your thoughts on the reaction to those two comments. >> I think the DR statement, while bold, might not be the solution for everybody (John laughs). I think there's certain folks that would say, based on their requirements, they have to have a traditional DR regardless, whether it's compliance or whatever else, but certainly, you should look at how the cloud infrastructure is targeted. There's a lot of cost savings to be gleaned from that, and we are absolutely investing in how we take the services we offer and make them much more readily available as a consumption model, as you go, as you consume, as opposed to a traditional CapEx type purchase. >> So a little bit over the top, but kind of directionally correct, in your mind? >> Yeah absolutely. >> Never going to go away. It's kind of like storage, it never went away. >> Certainly, I think it will continue to decline and decline and decline, but also to declare it over, people still buy desktops, right? That was declared dead in '97. >> Dave and I were just talking about infrastructures were supposed to be dead 10 years ago. >> Pat's always said he's been a fan of NetApp, so I don't want to project words into his mouth, but I think he's been there for us, in a majority of the NetApp and VMware interactions at Vmworld. >> There's a picture of Pat wearing a NetApp jersey at a CUBE event. >> Yes, that was a big moment for us, obviously. >> So the AI piece too, any thoughts on that comment or the AI comment? >> I'll defer the AI to him, but I would just say that on the DR thing is that, we already have that in cloud volumes, and a lot of the data services we're doing in AWS and the public cloud, so I think we present a clear example of that. AI. >> AI, Pat's exactly right. Something that's been around forever, that's really getting a lot of air time right now, but he's precisely right. We see the growth of AI applications in usage is absolutely huge, and when you combine that with the types of instruments that are collecting data, what's wired today versus what wasn't two, three, five years ago, obviously, as a storage company, there's just an exponential amount of data growth that's being captured out there, based upon these AI type machines that are only getting faster and smarter, so for us, we're welcoming the the 30-year success. It's great that it's here to the party. As we look at that ecosystem, that's where we're heavily investing and expanding our partnerships and our routes to market, because we're all so focused on that. >> Maybe just to follow on that, so the traditional conversation people have about cloud is it's somebody else's data center. >> It's somebody else's, right. >> But now, the cloud discussion is about, we were just talking about AI, self-driving cars, edge clouds, so the nature of where all this data reside is becoming much more dynamic and much more distributed. >> That's the point, it's much more distributed. >> How does that fit in to where you guys are going? >> We think it's great. It fits perfectly with our business model of being able to move your data around in a multi cloud environment, and have it where you need it to be, whether it's on the edge, even further out, kind of the fog of the cloud, or all the way at the center where you want it to be, so we think it fits the model that we have, from data everywhere, the data fabric. That's really what we've been designing for years and pushing to. This is the realization of that strategy. In our minds, is that's what we're arriving at. >> Partner program, quick update as we wrap up. What's the update on any kind of tiering? Do you guys have a strategy? You've obviously got more partners engaged. Sounds like cloud gives more touch points. Give a quick overview of what's going on. >> Jeff McCullough's our channel chief. He has done a great job coming in, and absolutely driving that program more aggressively out in to the field in North America. We've got a bunch of stuff, but I don't want to steal his thunder coming up at Insight, >> (laughs) That's okay. >> Not sure what I can steal at the moment. We are aggressively investing in the channel program. We have been, and will continue to be a channel-driven company. Even myself as the alliances head, we look at always, and Keith mentioned it, that third piece of the three in the box is always who's the delivery partner, and how can we help them, and obviously, the underlying tenet of that always is, let's make it meaningful, and let's be honest, meaningful to a partner is, they make money, they have services that they can absolutely embrace and then deliver. >> What's next for the relationship with AWS, and what other top partners you have. You mentioned NVIDIA before we came on camera. What's next for VMware and some of your top name partners? >> We've got some big announcements coming up with VMware, if you want to tease one of them. >> The reality in the world is that, if you want to buy solutions from VMware, a VMware validated design is kind of the pathway to really getting the mark of validation, and so we're on that path as well. We're looking to get that down the road. We've got some early tracks to it. We announced the first leg of that at this show called the net verified architecture for VMware private cloud. That gives us the first proof points that we're running the entire stack on NetApp HCI. We're going to use this as a way, along with ONTAP over time to be able to have on-prem solutions, as well as cloud volumes. With futures, they showcased it yesterday, with some future previews of VMC with cloud volumes, so look for that to come in the future timeframe. >> ONTAP AI? >> ONTAP AI. >> Back to your AI question, we just announced a joint meet in the market solution with NVIDIA, a conversion architecture, where it's NetApp storage, NVIDIA's GTX CPU servers. We've got some switching in there from Cisco, and you've got a very solid conversion infrastructre that goes specifically and targets the AI market. >> And AI, they're a pretty strategic partner, you guys with NVIDIA. >> They are. >> They've been hot lately, I mean, talk about AI. >> There's a lot of guys smiling in that booth over there. (Bruce and John laugh) They look pretty happy. >> They can't make enough GPUs for all those block chain miners. >> I think the key factor for the new alliance model is that the context shifts depending upon the market you're trying to reach, so if it's the AI market, typically NVIDIA's going to lead that conversation. If you flip it to the EUC market, and you look at GPU acceleration for BDI, they're an ecosystem to VMware driving the Horizon package, so it's a very interesting context that you have to be very savvy on to understand how the technologies fit together in a way that solution partners already today are putting them together for customers, and that AWS and all the hyperscalers know natively. >> You guys get a lot of good props. Congratulations on your success. Notable hallway conversations, certainly here and out in the field, I've talked with customers. You guys are good. With the solid state drives, and the software investment you made, it's paying off, so congratulations. >> Flash has been huge for us. >> Good luck with the new reorganization. Bruce, Keith, good too see you. >> It's great to see a solid player of come through the ACI. >> We're here on theCUBE. We'll be right back. Stay with us for more live coverage after this short break. I'm John Furrier with Alan Cohen. We'll be right back; stay with us.

>> From Boston Massachusets, it's the Cube, covering LiveWorx 18, brought to you by PTC. >> Welcome back to the seaport in Boston everybody, you're watching the Cube, the leader in live tech coverage and my name is Dave Vellante. We're here, this is day one of the PTC LiveWorx show, the confluence of internet of things, Edge Computing, AI, Block chains, security, a lot of innovation going on here in this new industry that's being formed out of a lot of older and existing incumbent industries. Lieutenant Bruce Litchfield is here, he's the VP of sustainment operations at Lockheed Martin. Bruce, thanks so much for coming on the Cube, appreciate you coming on. >> Thanks David, how are you today? >> I'm doing great thanks, it's a good show here, a lot of excitement, a lot of really interesting demos, we see you lot of movement here but I wonder if can talk about your military experience and how it relates to your current role at Lockheed Martin? >> Sure, so I spent 30 plus years in the military, and I retired as a lieutenant general so. >> Well, thank you for your service really. >> You know, it's an honor to serve and time when by fast and really got to work with some great people. And when you have that in your blood, it's hard to walk away and not continue service. I got a chance to work with Lockheed Martin who delivers the products and builds the products that I grew up with in the air force. Most of my career was in the sustainment and keeping them flying kind of aspect of the air force so now I get to work on them from a corporate perspective and continued to deliver products and capabilities and upgrade them so that tomorrow can be better than today. And that folks out in the field make sure that when the systems are needed and they have to use them, they're ready, capable, and, to go to, do whatever it is. >> Okay, sustainment is in your title and that's your current role, so by sustainment you mean, it works, when you need it to work, is that, describe that a little bit? That's right so, I use the simple term, keep them flying. And when you think about that, all over the world, 365 days a year, 27-7, you never know when a mission needs to take off or a soldier, sailor, eminent marine might need a capability to save a life, change the course of a battle, or otherwise make a difference. If a Lockheed Martin system's involved, I want to make sure it's there and ready to go and they don't have to worry about whether it's going to be able to succeed in the mission. >> So what's the role of technology in keeping systems up? I know in the IT world, it used to be just get two of everything, or three of everything, or four of everything, and just make things redundant. That kind of thinking's obviously evolved but what tech is Lockheed Martin bringing to this problem? >> If you look over the systems, and I'll just take, I came from the air force, and so the air force is flying weapon systems that are 50 plus years old along with we are delivering now the F35, which is the absolute latest in technology and capability. And so when I look at the evolution of technology over the time, it really is very impressive. I really do term sustainment as a systems engineering problem, it's making sure the part is there, it's making sure the system's reliable, it's making sure the tech data, it's making sure the support equipment. Anything that the maintenance person may need to get that jet airborne. Got to make sure it's there at the right time at the right place. And so if you look at the technology of how it's evolved over the year, it's much the same as our capability to go to war is, from what I would consider the command and control of World War Two or you just launched a jet. In fact we talked about it today. For one raid in World War Two, it took almost 200 bombers to hit one target, dropping over, almost a half a million tons of munitions, to today one aircraft can hit multiple targets with precision accuracy and keeping our air men safe, so the technology's evolved, along with how we sustain aircraft, which has really evolved over that time. >> So much more software obviously involved in aircraft today, how has the industry dealt with the increase in complexity as a result of things like software and code, but at the same time, it's clearly delivering more reliable systems and more efficient systems as you described? >> That's right, so think about in this way. Underpinning an inherent capability, such as the F35, is a reliability of this system. So if just take that one weapon system. So we have, right now, delivered over 300 aircraft and they're bedded down at over 14 locations, around the world. 74% of the items in that aircraft have never failed, over the time that they been out there, including over, about a hundred thousand hours worth of flight hours. Then when you start looking at that, almost 94% of them meet or exceed their liability requirements. So now we're just down to a few parts that we've got to make sure that we improve through regular upgrades that you would do under normal conditions to make the most reliable system. Then on top of that, you put the software embedded in the aircraft, it helps the folks on the flight line know what's failed, where it's failed and then know how to troubleshoot and so you've brought technology to a point of what I would call human interaction on the flight line. >> You talk a lot about predictive maintenance and anticipating failures. Presumably that is part of this capability, is that, I mean, how real is that? Is it in action today? Is it sort of a future thing or can you talk about that? >> So, it's very much in action today and we have a predictive health and what we're really trying to drive to is a condition based maintenance airplane. In other words, if you think about going to a commercial airline, you don't want it to fly to fail, you want to make sure that when ever you show up that it's ready, you board it and you take off. Well, we're evolving the technology that involves us to go to a condition based maintenance so we can do maintenance on the off time and when the aircraft not needed or what I would call a scheduled kind of time frame and that helps ensure that we don't just, it's mission ready whenever the pilots need it or when ever the sorty requirements call for it. >> Okay, so, let's talk about some of the challenges that you guys face in terms of bringing technology and sustaining this technology into whatever generation of aircraft? I think we're in fifth generation today? First of all what's fifth generation what are some of the challenges that you face? >> So let's start with fifth gen, so from an operational perspective, when someone says fifth gen technology, it's really taken into account what I would consider low visibility or in other words, making the aircraft hard to detect. It's putting avionic sensors on there so that the pilot knows what's going on around them and is able to fuse that information, to to give them very explicit information of what's happening on the battlefield and then be able to keep those that are supporting him informed of what's happening. It's a high maneuverability of the weapon system as well as speed that it goes. So there's the technology aspects of fifth gen and then what I like to refer to is fifth gen sustainment and that's really what we're doing at Lockheed Martin. What we want to be able to do is bring fifth gen sustainment capability to the field and drive the cost down so it's at a fourth gen or below the price of what current systems are. So get new technology, modern technology, sustain it at a very high readiness rate at a cost lower than what they currently see today. So fifth for fourth is one of the mantra's that we're trying to deliver, or at least drive the cost down, as low as possible. And one of the challenges that I would say is that balance between how do you have that capability and then keep the cost down? So you have to do things differently. You have to evolve to a new way of looking, so we talked about, a condition based maintenance or evolving to it and a capability where you don't fly to fail. You do it when the system's down when you do it on a scheduled basis to do that. At the same time you have to integrate all the capabilities together for software, to bring in analytics to the capabilities that you have and prognostics kind of maintenance to the field. And so it's a systems engineering, a complex instrument system's engineering problem so really that's what makes, kind of, I would call the strength of Lockheed Martin, which prides itself on being a technology company, making tomorrow better than today. >> Yeah, and a system's thinker. >> And a system's thinker. >> When you talk about these capabilities, observability, avionics capabilities, maneuverability, increased speeds, I just, it just jumps in my head, data. Let's talk about the role of data in analytics, I mean, the data explosion here, how are you dealing with all of that data? >> So we get close to a terabyte worth of information a day, and then how you exploit that really goes across the entirety of what I would call the sustainment ecosystem. And if you look at it, sustainment probably, we can break it down into about 11 different areas, whether it's supply chain, whether it's managing the inventory that we have within supply chain, whether it's in reliability, prognostics. Whether it's in the maintenance repair and overhaul capability. So we're bringing analytics across the entire spectrum of that and what we're out doing right now, is getting best of breed capabilities so that we can piece together a holistic picture to better sustain this weapon system, so data is the key to doing that. At the end of the day it's how do you bring that data and then bring it to what I would call the analog piece or the human being at the flight line that still has to maintain the parts. But we want to make sure the right parts at the right place at the right time. >> So the human is still the last mile. That terabyte a day, is the majority of that stored, it is persisted or is there a lot of it that's kind of throw away data? Can you? >> No, I mean, the great news id we capture that data and so we have a chance to go utilize it to improve not only what tomorrow is but if I look at analytics for sustainment piece, I look at it in three pieces. One is a dashboard, alright where are you? What's the status? Okay that's good, that's your speedometer. Then it is how do you do decision aids and tools, which means how do you make better decisions to affect maybe tomorrow's operation? Then there's a third part about it which is predictive analytics, how do I make decisions today that affect me three to five years apart and that I can make a decision today and have confidence that down the road that's absolutely going to be the right decision? >> And I mean, the first two, the status and the decision aids, those are real time or near real time. >> Very much so. >> Pretty much instantaneous types of things, that's a challenge obviously to deal with that. >> It is and then we are dealing with a defense. You got to be always cognizant of security, cyber security, and making sure that what you do keeps that data safe and make sure that no one be able to tamper with it so that your making real time decisions based on the known capabilities of the data and where it comes from. >> Well Bruce thank you very much for coming on the Cube. I hope you're enjoying the LiveWorx show. It was really a pleasure having you. >> David thank you, it's a great show and it's great to be here. >> Our pleasure. >> Okay, keep it right there everybody, we'll be back with our next guest. You're watching the Cube live, from LiveWorx in Boston. We'll be right back.

>> Narrator: Live from Las Vegas, it's theCUBE covering Informatica World 2018, brought to you by Informatica. >> Welcome back, everyone, this is theCube, exclusive coverage of Informatica World 2018, live in Las Vegas at the Venetian Ball Room here. I'm John Furrier, the host of theCUBE, analyst here at theCUBE, with Peter Burris, analyst and also my co-host these past two days. Our next guest is Bruce Chizen, who is the executive chairman of Informatica, one of the leaders of the company. Great to have you back, good to see you. >> Good, great to be here, guys. >> It's like an annual pilgrimage. We get together here, and hear the perspective. Also, we had Jerry Held on yesterday, board member, very senior in the industry. You guys are legends. You've been there, done that. You've seen how many waves, how many waves have you seen? >> Yeah, I was just sharing with somebody, I was at Microsoft in 1983, so I guess I go back a little while. >> You've seen a lot of waves. Okay, so this wave is interesting, because we were talking about the keynote and talking about the timing of how data, super important, there's no debate on the role of data, but timing in the industry, you got cloud, multi-cloud, you've got things like containerization, Kubernetes, you're starting to see that microservices model appear. The role of virtualization is not as prominent as it once was, given what's happening in the stack, but certainly, data is super-strategic. GDPR, this Friday, goes into action. So, shot across the bow with GDPR, data at the center. Explain the phenomenon. >> Yeah, so, look, what's happening is, more data is being generated today than ever before. I think Anil Chakravarthy, CEO, said this morning during his keynote, it's increasing twofold every six months. It's just an amazing amount of data that's occurring, both through data warehouses, as well as realtime data through things like IoT and other streaming types of mechanisms, and at the same time, every enterprise in the world is trying to figure out how to transform this business, leveraging that data, and that data exists across so many different platforms, whether it's on-premise, whether it's the cloud, whether it's a combination of both, whether it's multiple clouds. So, trying to homogenize all this data, or to be able to capture it and get it usable in one place for analytics, for decision making, is an incredible task. Fortunately, it plays into Informatica's strength. >> I want to get your thoughts on two dimensions to that, because I agree, that's all happening, but you add the pressure to scale with the cloud, okay, that is a huge deal, okay, as well as, build then new applications faster. So, this pressure, not just to kind of get it right in the data, you got to scale with the cloud, so there's a lot of big things being built out. >> Yeah, and it's not as simple as the cloud, it's the combination of leveraging on-premise workflows with the cloud, with new applications or new workflows, and how do you make sure you have data integrity between those two environments? And I'll add another layer to it, most enterprises don't want to be held hostage to one cloud infrastructure provider, and what you are seeing is, those enterprises leveraging multiple cloud infrastructures. So, between the data that's on-premise, the data that might be residing in Azure, data that might be residing in AWS, trying to make sure that there's one view of this data, and that it's secure, it's cleansed, it's of high quality, is a greater task than ever before. >> So, Bruce, let me build on that and see if you agree with this. It sounds to what you're suggesting is that we've got all this data, it's growing very fast, but we have to be able to do two things to it. We have to be able to organize it, and we have to turn it into objects or things that have business value so that we can generate returns on it, appreciable increasing returns on it. Is that kind of the centerpiece of what we're talking about here at Informatica World? >> Absolutely, and if you look at the quick success of the enterprise data catalog that was launched last year and the number of customers that have already adopted the platform, which really is a catalog of the metadata that sits across the data across the entire enterprise. The fact that so many customers have adopted a 1.O product that quickly is validation that they want to be able to leverage and take advantage of all of this data that's sitting in thousands and thousands of different entities within their own enterprise. >> So with your experience, you think the adoption's greater than what you've seen, but put it in comparison, compare the magnitude of that adoption. >> We expected a handful of customers to adopt it in the first year, we have hundreds of customers that have adopted it in the first year. >> John: So, well over the forecast. >> Well over our forecast. >> Well, they bought it. Are they adopting and changing the practices, evolving their organizations, imagining new ways of generating work, as a consequence of being able to discover and apply data faster? >> They know they want to analyze their data. They want to use tools like Power BI, tools like Tableau. What they haven't been able to do is use those tools as effectively as they would have liked to, 'cause they didn't a mechanism to capture all that data or to view all that data across their entire enterprise. The other challenge they had was there was no data integrity that existed, because the data in one repository was different than the data in a different repository. To be able to have one view of that data means that the information that they're analyzing is accurate, which didn't exist before. >> Alright, so what's next? That's table, not table stakes, but the first low-hanging fruit. Value proposition is, okay, I get a sense of the metadata, where is everything, so that's check. >> Yeah, so, there's two things in my mind, one is making sure that we make it easy for them to use any of the cloud platforms. So today, the company announced their relationship with Microsoft, with Azure, with Informatica's IPaaS running natively on Azure, in addition to what already exists with Amazon AWS. The second thing is to continue to add AI capability to that metadata, so instead of a person having to navigate and collect all of that information, is to use intelligence to be able to make sense of-- >> John: Machines. >> Machines. >> Streaming the data in faster, handling the volume. >> And being able to throw out garbage and use only what's really-- >> That's what I want to push you on, so everybody said, oh, we're going to apply AI, but they don't say what the AI is going to do, and I think specifically, as it relates to MDM, as it relates to catalogs, replaces some of these other things, it's identifying patterns, identifying inconsistencies in data objects, it's identifying how it feeds different workflows commonly. That kind of stuff. Are there other things that we're really trying to apply this AI to to improve data quality, data consistency, data flows, usability? >> It's going to do all of that, which is what was, it required a human to do in the past. In addition, as the machine, as the AI engine or the machine learns, the ability to do this more quickly is going to become apparent. So, with this massive amount of data being exposed, the last thing you want to do is to have the decision maker being slowed down. So AI is just going to speed it up significantly. >> Bruce, talk about the state of the company. Obviously, we've had Bruce on, we tried to get a little teaser out of him on what's going on with the board level, stock option, grants, so on and so forth. I'm only kidding. Obviously a valuable company, we've been watching it and covering you guys and pointing out, actually earlier on than others, the benefits of the data. Certainly it's become a very valuable private company. Once public, now private. You were involved in that journey, outcome for an offering soon, or bankers must be licking their chops, prospects, not saying when are they going public, I don't want to ask that question, but there's obviously a trajectory. What's the company's position, vis-à-vis the financial health and growth? >> Informatica will be one of those rare instances in the world of private equity, where a sponsor has come in and decided on a growth model top line revenue versus bottom line profitability. >> You mean shedding the parts? >> Shedding the parts, really squeezing the company for maintenance revenue, for cash. What Permira and CPP, the two investors, have done has really helped the company to continue to focus on growth. So, when we look at R&D expenditures, they're close to 200 million dollars, which is well above industry average as a percentage of revenue. >> So they came in to build the company. >> Came in to build it, and more importantly, grow it. It's exceeded our expectations, haven't determined a timeline to go public, there is a possibility you could see an offering sometime in 2019. >> And we talked with also Jerry and others yesterday about this notion of timing, right? Timing's everything in life. You couldn't ask for a better time to be the Switzerland, or whatever domicile you want to call that's neutral to multiple platforms. Certainly, the data layers' a nice position, you've got companies like NetApp underneath, having a nice layer, storage, so you've got the data fabric there, you guys are playing across multiple clouds. This makes it a unique opportunity. Now, why is this time for being the Switzerland of data important, and how should customers look at this timing of the movement for Informatica vis-à-vis the industry trend? >> Yeah, enterprises want to make sure they don't get held hostage to any one vendor. That happened in the past with the likes of an SAP for ERP. They don't want to fall into that trap. They want to be able to move their workflows between Azure, between AWS, between Oracle, and continue to have legacy workflows on-premise where necessary. So, they want someone, they want a provider who's going to provide them with a solution that's not biased and is not going to show any preference towards any one provider. Many years ago, I had the privilege of being the CEO of Adobe, and if you think about it, PDF, Acrobat, was the Swiss solution, or the Switzerland of documents. And the reason why PDF became so popular and became the standard was because nobody was comfortable with .DOC being that solution. The same is true-- >> Because of the incompatibility of the operating systems? >> .DOC, two reasons, one is nobody wanted to be held hostage to Microsoft, they already felt uncomfortable with Windows and Office. >> Ended up becoming hostage to Microsoft anyway, but that's all good. >> And, at the same time, .DOC showed preference towards a Microsoft environment. >> Peter: And it was the wrong technology. >> And it didn't work across platform. >> Exactly. >> In the case of Informatica, Informatica is the only scaled provider in the data business that has a solution that works across all environments, all vendors, all providers, hybrid, on-premise, cloud, multiple infrastructure providers. >> So, my summary of what everything you said Bruce is that Informatica today is a company that's going to help you organize your data, so you can put more data to work. >> Absolutely. >> Alright, Bruce, thanks for coming on. Great to see you, always a pleasure. We've got to do it again in the studio in Palo Alto, get you in, get some information out of you on what's going on with the public offering. (Bruce laughs) Great company, congratulations, it's been a fun ride, I can't wait to hear all the war stories when it's all said and done, great job. Switzerland of data here. At Informatica World, it's theCUBE, out in the open, sharing you the data here in Las Vegas. More live coverage, stay with us, Be right back. (techno music)

>> Announcer: Live from Chicago, Illinois, it's theCUBE. Covering VeeamOn 2018 brought to you by Veeam. >> We're back at VeeamOn 2018, you're watching theCUBE, the leader in live tech coverage. I'm Dave Vellante with my cohost Stu Miniman. Stu, always great working with you. Bruce Shaw is here, he's the Senior Director of Global Alliances and Industry Solutions at NetApp. Great to see you, thanks for coming on theCUBE. >> Thanks for having me. >> So, I got to start out with NetApp, I mean, we've followed NetApp for decades, ya know, from the very beginning back when I was at IDC, Stu, you were probably still in your mother's womb. (laughing) But you guys are back in a big way, I mean, for a while there it looked vulnerable. You took advantage of the Dell EMC merger. You're gaining share again, you're growing, stock price is up, there's a spring in your step, what's going on? >> Well, a lot of things are going on. I think we've had a lot of leadership additions to the company, Henri Richard joined and took over as the CSO with the company. We've got a new CMO in Jean English. But more importantly, a lot of the areas that we were late to the market, and candidly we've admitted we were late. We didn't have a good Flash story a couple years ago. We've been very aggressive with Flash over the last 24 to 18 months. We're now the fastest growing Flash storage provider out in the market, and we think we'll exit this year as number one. In fact, we think that's the current course and trajectory. We're very happy with where that's going. The FlexPod partnership with Cisco was great this past year. We had a record year in Converged infrastructure, which was a down market, we picked up about 13 points a share according to IDC, so a lot of the cylinders are starting to fire, but the one that is probably the biggest and the most shocking for folks is three, four years ago, the belief was that cloud was going to kill on-prem storage for companies like NetApp. I think the one thing that they did right ahead of the curve was they embraced the cloud. They've got great partnerships with Google, Amazon, the hyperscalers, and cloud strategy and the business that drives the company there is the fastest part of the company, and Anthony Lye runs that team, and it's doing an amazing job. >> Explain how, and you're absolutely right, many, most, frankly myself at times, felt that way. Explain how cloud is a tailwind and not just a one-way street into the roach motel. >> Oh well, there isn't an enterprise today that isn't thinking about cloud in some way, shape, or form, right? Now, ya have prognosticators on either side saying it's all going to the cloud or something less than that, but the truth is when you look at a strategy like ONTAP and the ability to move your data, whether it's on-prem or to the cloud and manage it through our data fabric story, that's where NetApp really starts coming into their own. I think, again, that's where we've been able to take advantage, and it's not just having it one way or the other or being good just with the hyperscalers or good with the guys that want to be secure because most companies do a hybrid story, and they want to bit of both. >> Well, I think the one thing that I would observe about NetApp, having followed the company for many, many years, which I think gives you an advantage, is NetApp really has always had storage services in software that were largely decoupled from the hardware, and that allowed you to get into cloud early, don't ya think, Stu? >> Yeah, absolutely, and Bruce, we're here at VeeamOn, and their message sounds a lot like that to me, so maybe help explain, we were just talking to Veeam's CMO, when you hear some of the descriptions of storage services, software, multicloud, and everything, NetApp and Veeam sound alike. How are they complementary in, ya know, maybe where do they bump up against each other, yeah? >> Yeah, well, we both compete in the same market, which is storage, so of course, there's areas where we're going to compete with each other, but we are very complementary in terms of the story and the markets that we serve, right? NetApp is incredible strong in the enterprise. Veeam has great commercial channel presence, so from a route to market there's a lot of complementary stuff we do with each other. Price point, in terms of where we hit the market and the things that we go after, we have a lot of opportunity where there's not overlap to help each out to the point they're now, the relationship's evolved over the last four years where we're actually doing OEM of each other's products. We've got our E-Series we just announced yesterday that we're OEMing with these guys, which again is targeted at exactly those markets. The story between the two that we're both at our core not hardware companies, not storage companies, but data management companies really is where this starts to come together and play well. The fact that they're mutually supportive of each other makes for a really strong value proposition for the customer and the channel, especially the guys like the service providers or ya know, hybrid cloud providers, it's a big time story for them. >> So you're growing with, the partnership with Veeam is growing. >> Right. >> Ya got a combination of trends that become tailwinds, but then you've got execution. Can you explain what are those tailwinds, and what's the execution ethos with the partnership? >> We are a channel-only company for all intents and purposes. >> Dave: Oh yeah, I don't know what the number is now, but you've always been very, very high performing. >> Yeah, I know, so we look at businesses that we drive, and channel is at the core of what we do, so when you have a tailwind like, ya know, where we are with Flash and the growth there, the channel partners are making more money, the programs that are coming for them, we're not taking business that they're doing today and pushing it towards the cloud. Again, we're talking about the story that's transitory between the two, so for a lot of the channel providers that are out there getting in the market, that's a very powerful story for them. That it's not a competitive business, we're not going to try to create our own cloud service to take away from them. We want to help them as they migrate between the two. >> All right, Bruce, one of the other areas we're hearing a lot about at this show that I think lines up with NetApp is the analytics and AI, can you maybe talk about how that ties into the products? >> Yeah, I mean, you look at a lot of these markets like AI, like analytics in terms of what companies are doing, it sheds off a tremendous amount of data, right? And that data is at the heart of what they want to analyze and go through, and when they bring those things to market, the goal is how I quickly move it from where I'm capturing it to where I need it, and ONTAP does a really good job of doing that in terms of being able to take the data to where they need it, whether it's at the edge or whether it's back at the core of the company, so that you can actually do the real work with it and gain the insights that drive the business. >> Bruce, what's the resale agreement that you have with Veeam, can you explain that? >> We have Veeam on our price list. Our sales reps can sell Veeam, can be compensated for it, vice versa, they can absolutely hook in and drive away with NetApp, and now that we're getting products like E-Series where their product is embedded in ours, that only strengthens that kind of motion. So for a NetApp sales rep today, if they have an opportunity where Veeam is needed on it as part of the offering, it's absolutely in their wheelhouse to go sell it, and they get the sale level of love and attention from quote and comp standpoint that they would if it was NetApp only products. >> So this is kind of interesting innovation that Veeam, I think, has been out in front of, they, and I dunno how they do it, Stu, but I think Veeam understands the lifetime value of a customer and is willing to make, put sweat equity into a deal as part of a partnership to make it transparent to a partner sales force. >> Yeah absolutely. >> That's innovation in business model. >> Absolutely, we're very proud of our sales force and the work that they're able to do. We view ourselves as kind of the last big enterprise standalone storage company that's out there doing this, and I run strategic alliances, and some partners integrate really well with our sales guys. Others, it's more of a, ya know, it requires more work. To your point, Veeam has done a superb job at identifying how and where they play with our folks and getting together where we go to market together. >> It's interesting, we used to, ya know, several years ago now, ask the question can NetApp remain independent. We've seen all these independent storage companies kind of go away. Used to have this conversation with David Scott at 3PAR all the time, EMC itself wasn't able to maintain it, and then NetApp got to the point where it was almost too big for an acquisition, and although stock price was down, everybody, NetApp was the rumor of MNA more than any company I can think of in the storage business, but now you're seeing sort of antithetical to what most people expected, it's kind of like the cloud we were talking about before, storage companies emerged. Pure was the first one over a billion since NetApp. What are your thoughts, and what's that, I wonder what, you guys must talk in the hallways about that whole, the dynamics of the industry. It seems like it's still a viable business model to be best of breed. >> It's very viable, so I took over running the strategic alliances at the beginning of January, and my dance card's full. I can't believe the number of folks that are calling up wanting to partner. I think we've gotten much more mature in terms of how we view the market and our ability to get strategically with other companies to be successful, and there absolutely is always going to be a place out there for a best of breed story. Customers want the best technology that they can get to handle their business needs, and if we partner with great partners, whether it's Veeam or others to provide that for them, I think the viability of NetApp only gets stronger not weaker. >> It's interesting because now ya got NetApp, Pure, Nutanix, soon to be Veeam, as billion dollar independent pure play companies in the storage business. Isilon couldn't get there, Data Domain couldn't get there, Compellent couldn't get there, 3PAR couldn't get there, Lefthand couldn't get, EqualLogic, I can go down the list. They were never able to reach that escape velocity, and maybe it is cloud, maybe cloud is that weird tailwind for people who can figure out how to take advantage of cloud and hybrid cloud, your thoughts? >> Yeah, I think it is, number one. I think also the companies that you mentioned at various times, and I'm a hardware industry dinosaur, I've been around forever. A lot of those companies you talk about the difficult moment from them was hey, we're a storage company, now we want to add compute or now we want to go into this part of the market that put them at odds with the guys they were partnering with. George, our CEO, has been absolutely maniacal with his vision of our path forward is managing data, period. Whatever that form takes, we don't need to be a compute company, we don't need to be a networking company, we want to be a data company. I think how that then drives the decisions, whether it's partnering with cloud, whether it's going into new markets with HCI, even if it's things about transforming the legacy data center from traditional data center and how it's managed on-prem to something that's all Flash driven and much more efficient and much more programmable than it was in the past, so it's easier to administer, those are the areas that we can go innovate, and as long as we're partnering with the right partners out in the industry, that makes us a very good viable destination for the customer without worrying about well, do we have a compute node, are we in the server business now, are we suddenly in the switch business? Those are things that are not even on our radar. >> Yeah, I mean, you guys are in a unique position from that standpoint. You're very large now, you're the largest independent storage company, so everybody wants to work with you. You don't bump up into these adjacencies, and you can make bets, you can place your chips in areas whereas some of the startups, there's tons of innovation, but it's really hard to hit that escape. The amount of resources that you need, the money you need for promotion, the talent war that's going on out there, the go-to-market challenges, the partner challenges, so you guys are in a pretty good position right now. >> We really are, and I think we've actually done a lot of the restructuring internally to continue that and capitalize on it. Probably the biggest change, which outside the company, most folks wouldn't notice immediately, is that we moved at the beginning of this year to a three distinct business unit structure where we're focusing on three parts of the business to go forward. We've got our cloud business unit, which is driving into, as I said, the hyperscalers under Anthony Lye. We've got cloud data center, which is more of the new technologies like HCI and Converge and object storage technology like StorageGRID, and that's, right now that's an incredibly fast growing business for us. Then, of course, we've got our traditional storage software infrastructure business where we have products like E-Series and modernizing the data center, which is primarily driven with this transition to Flash. You've got three BUs now that are maniacally focused on the different areas of the market where we see here's an immediate opportunity in Flash. Here's a slightly longer opportunity in things like hybrid cloud and HCI and Converge infrastructure and a much longer term bet was how does the cloud really become a piece where we're managing between all of those. It lets us be a lot nimble between it. It's almost like three subbusinesses where we're going to market. >> Yeah, Dave, and actually that aligns perfectly with the research we've been doing for over five years from server stand and true private cloud, you've got the hyperscale, you've got the transformation locally in spanning those two, and then you've got that transition from the traditional. >> Oh, I think it's a sound strategy, and it'll serve us well in the years to come. >> There's obviously a lot of noise about artificial intelligence in the marketplace. You've got some companies trying to position to be the platform for machine intelligence or artificial intelligence, what's NetApp's point of view on that? >> Well certainly, we share some of that, but again, I think at the end of the day for us, it's much more important about fine, wherever I'm capturing that artificial intelligence is not likely the place where I'm going to do a lot of the analytics and work on it, so it really does come down to, ya know, am I moving it up to the cloud to do that work, where am I making my big insights, where am I mining through it, and then how am I relating that back, whether it's at the edge or whether it's at the core data center, and again, we think with ONTAP, with the partners that we're going to market with for AI, for ML, IoT, that's the difference maker for us at the end of the day. It's not that we're just another storage company storing the telemetry data off of a car for AI, we're putting it into a format and a form that's usable quickly, efficiently, real time, where Tesla can go make a decision on the car right now, not days, weeks, months from now. >> All right, Bruce, well hey, thanks for coming on theCUBE. Really appreciate your time and good luck. >> Enjoyed having me, thank you. >> All right, great. >> Good to see you guys. >> All right, keep it right there everybody. We'll be back with our next guest. You're watching VeeamOn 2018, this is theCUBE.

>> Narrator: Live, from Madrid, Spain, it's theCUBE, covering HPEE Discover Madrid 2017, brought to you by Hewlett Packard Enterprise. >> Welcome back to Madrid, everybody. This is theCUBE, the leader in live tech coverage. My name is Dave Vellante, and we're here with my co-host Peter Burris, and this is day one of HPEE Discover Madrid. Susan Blocher is here, she's the vice-president of portfolio marketing at Hewlett Packard Enterprise, and Bruce Trevarthen joins her. He's the CEO and founder, I believe, of Layer X. Welcome back, both of you, to theCUBE. >> Thank you David. >> All right so Susan, big show for you guys, and we have these six months cadence of big messages >> Susan: Yes. >> And customer shows, so what are we going to hear this afternoon at the keynotes? >> Wow. I'll tell you we've got a lot of exciting news to talk about. First of all, the way customers are consuming IT is really changing, cloud is changing the game. We got some amazing announcements to talk about around how we're going to help customers in the hybrid IT space consume IT differently. We're going to talk about how we're helping them manage across multi-cloud environments. We're going to talk about bringing artificial intelligence and machine learning to the data center which is really transformational. So, lot's of exciting news here. >> Good, okay! So we'll be covering the keynotes here just actually in about a half hour or so, we kick off. Meg, Antonio >> Yes. you've got a new leader so we're going to hear from him, we've been hearing from him for some time now. >> Very exciting. >> Looking forward to hearing from him. Okay, Bruce. It's been awhile since we talked about layerX. Tell us what's transpired in the last couple years. Set up layerX, what you guys are all about and what's new. >> Sure, so it's a cloud service provider based out of New Zealand. Multiple platforms giving us that resilience. You know, that sort of general cloud people all know what cloud is these days. But really for us the journey it just continues. We keep, from a strategy point of view we keep looking at where is cloud adoption at, where is cloud going, are these hyperscale providers going to enter every country and every market? And really, sort of, make us, sort of in country boutique operators less relevant. So you're always asking that question and then you're sort of hit with this new wave of expectations down from the clients. Hybrid IT has been the big push in the last 12 months and what's really encouraging for us when we get hit with this new sort of level of interest and a slight tangent on this manage services delivery is that HPE already thinking the same way. They've already come up with a product line that's going to plug that gap. So we work very closely with HPE with their edge line and the OEM team globally, to deliver HPE hardware on customer site or on premise. And then we put our own software on that, we link it back into the core V-grid environment, and that really, for a customer they keep those workloads on site where they need to be. And then you've got that public cloud environment for the disaster recovery and the workloads that don't need to be on site. >> So let's unpack that a little bit. Tagline, Hewlett Packard Enterprises uses make hybrid IT simple, that's the objective. >> [Susan]- That's right. >> You know, IT is complicated, hybrid IT is complicated. What's the starting point to make it simple Bruce, from your perspective? Is it to make the infrastructure as invisible as possible, is it bringing the cloud upward model? Maybe talk about those steps. >> Sure. Well, I mean, one of the first things we try to do to make it simple is we don't mention cloud. We talk ultimately about what workload is the customer consuming and where do they belong? And so, we're invariably seeing more and more workloads that really shouldn't go centralized in a data center they should be on site. So, GPU accelerated desktops for oil and gas research, or some of our clients doing 3D engineering, you know, CAD design work. You can put that in a data center, and we have, but then you're at the mercy of the fiber connections. Speed of the fiber connection, the resilience of the fiber connection, and the cost absolutely. And so keeping some of those workloads on site just makes sense. But how can you then leverage the benefit of that centralized IT in the event of a disaster if all of your workloads are actually on site? And that's where it's got to be hybrid. You can have those workloads on site but all your files and all that capability is sort of mirrored in the cloud environment. So if you have a fiber cut, then you can use a cellular network to get there. Or if you have an on site disaster, then you can spend the equivalent resources in the data center, but on demand, rather than dedicated to you. >> We like to say that customers want or the way that we summarize it at Wikibon is, customers want the cloud experience where the data demands. >> Dave: 'cause we do talk about cloud >> 'cause we do talk about cloud periodically. Well, but you have to, because at the end of the day it's driving a new way of thinking. Not just about the technology, but how you solve business problems. And it comes back to how do you think about the business problem differently. I love New Zealand, I've been there a couple times. I've worked with a lot of customers and the minute that you said New Zealand I was like, right! How do, how does the cloud experience, how are you solving problems differently than you did a few years ago because of not only the HPEE partnership, but thinking differently about these problems? >> Thinking differently is definitely something you have to do to stay relevant, right, to keep up with the market. Almost ten years ago we thought what we felt was a little differently, when we adopted the HPEE 3PAR, and that really was a technology that gave us the ability to change our mind regarding storage. Spin forward now to 2017. In April this year we put in our first HPE Synergy platform. This month we're just putting in our second HPE Synergy platform. And Synergy gives us for compute what HPE 3PAR gave us for storage. The ability to change our mind, to be programmatic or autonomous with the deployment of resources for a customer need. And so for a public cloud environment, that's basically spinning up compute nodes as required for the demand within the clusters. But it also introduces by way of the technology capability, a new channel, or a new revenue opportunity. Because now we can actually programmatically spin up compute nodes of any flavor, for a customer in a private cloud environment. So this is physical tend to the customer opposed to virtual, you know, cloud. We can do that just as easily as we can a VN because of Synergy. >> And that's really exciting. I think what Bruce is really representing here is that he can focus on business outcomes for his customers. And you, Dave, you said it makes the infrastructure transparent. Transparent but underneath that is really differentiated capability and value like the ability to spin up and spin down composable infrastructure on demand. Like the ability to bring world class security to that infrastructure. So all of those things are underpinning the services that layerX is able to deliver. >> So I would think part of making Hybrid IT simple is not just throwing a bunch of products at your customers. >> Right. >> We heard on the last financial call that HPE is changing the way... >> Exactly. >> ...it reports. It's going to report hybrid IT, which is essentially your portfolio. >> Susan: Exactly. >> So it's server, storage, networking and relevant services around that >> That' right. >> Susan: And software. >> And software that powers all that, so talk about how you're going to market and how that aligns with how you guys want to buy. >> Yeah, well think about it from, let's talk about it from the layerX perspective. When you look at Synergy, that is not a piece of hardware, that is truly software defined intelligence built into innovative hardware. Based on our Gen 10 server platform, which in and of itself is the world's most secure industry standard server platform because we have built in silicon route of trust, and things like that, so what you get is all of that put together. All of that integrated. That software defined intelligence, the technology innovation, the infrastructure innovation. And wrappered with the services that both support the layerX company and their customers. >> Maybe talk about your customers a bit more. What are they really pushing you hard to do? What are the big challenges they face, and how are you addressing those? >> One of the most common conversations with cloud is obviously cost. Everyone's trying to commoditize this resource to the Nth degree every day, but the vGrid which is the our brand for our cloud platform, The vGrid position really is around performance and reliability and we back that up through HPE hardware platforms and a software stack that enables that. But our customers are really driving us to make sure that we stay relevant. Not only with that performance and reliability but still on cost. Even though we are giving them enterprise and beyond capabilities as an SMB, cost is still a major defective for an SMB. So for us to keep our overheads low we need automation. You know we're not going to go put in, no disrespect to the product line, but we're not going to go and put in maybe an Apollo or a CloudLine solution, we're going to stick with Synergy and previously the ProLion because of the added value wrapped around that that actually gives us the peace of mind and the operational efficiency through our engineering team to get the work done far more effectively. Now with Synergy takes it up to a whole new level because this is all composable now. My CTO mentioned to me the other day they just put in a new 8450 3PAR. And he said, "All I had to do "was create the CPG's in the 3PAR and OneView did the rest." He's like I don't have to go into all these other steps that he used to have to do. So, it saves time and time is expensive. Not only from a human resource point of view, but go to market speed. >> Well, converged hardware was about having a common set of support technologies. The whole notion of hyperconverge starting to converge the actual administrative tasks. But what I remember, the last time that I was in New Zealand and talked with large users, was a real emphasis on analytics because of New Zealand being an island with great resources in some respects and less resources in others, energy, telecommunications. How is the modern economy of New Zealand with some of the constraints that it faces driving the use of digital technology to lift up industry, services, and the quality of life in New Zealand? >> We're seeing that in a very far reaching kind of industry verticals. And more so now with obviously IOT's become a pretty hot topic, but IOT backed by all the smart and on-demand composable architecture is really making a difference to primary industries, making them more productive more effective, more efficient. But really the customers in New Zealand we're a nation of early adopters. We have 96% of our companies are six or less people. So, we're dealing with SMB's that have to box above their weight. They have to adapt, they have to do more with less. You know all of this cliches that really encumber the average small company, and we have a lot of them. So the demands from an IT perspective are give me what my enterprise counterparts have but at a per user, or resource unit per month kind of model so cloud just makes so much sense for them. >> Susan, big takeaways from Madrid? What do you want the world to walk away with? >> Well I think first of all, when we say we're going to help make hybrid IT simple, what we're talking about and really exemplified with layerX is we're talking about from the edge to the core to the cloud. So, really end to end. The other really exciting thing that we're here talking about is AI, artificial intelligence. Deep learning, machine learning. And you talked about it in the context of edge computing and IOT which is obviously super hot, but we are also bringing AI to the data center. So as we look at-- >> Peter: In other words, making data center operations, IT operations, >> Making the data center autonomous, self healing, self managing. You look at the automobile industry, autonomous cars, right? Well think about how that's going to be applied to autonomous data centers. That's what we're going to be talking about. >> Shoes for the cobbler's children. >> You got it. >> Well, and think about the impact that has on the business where you're allowing people not to spend money on whatever, lung provisioning, >> Right. >> And server management, but really focusing on some other more strategic aspects of their business whether it's digital transformation, AI, other data-oriented activities. >> Exactly. >> Sometimes the data has to be here and you want to make sure that when the data's there it has the same services are available to the business, >> Susan: Yes. >> to take advantage of that asset where it is. >> Real time analytics for the data that matters to our customers at the edge and in the cloud, as well as applying that same AI to the telemetry of the data center and using that to make the data center more efficient, more effective, more autonomous and self-healing. >> Awesome. So, keynotes are coming up very shortly. We'll be running those on our twitch channel twitch.com/siliconangle. You can check those out obviously at HPE as well, HPE.com Susan and Bruce, thanks very much for coming to theCUBE, >> Thank you so much, appreciate it. >> setting up the afternoon. Really appreciate your time. >> No problem. >> Thank you. >> Alright, keep right there buddy. We'll be back after the keynotes. This is theCUBE. We're live from HPE Discover, Madrid. (electronic music)

(bright orchestral music) >> Hello everyone, and welcome to theCUBE Conversations here in Palo Alto Studios. For theCUBE, I'm John Furrier, the co-founder of SiliconANGLE Media inc. My next guest is Bruce Arthur, who's the Vice President of engineering at Banter.ai. Good friend, we've known each other for years, VP of engineering, developer, formerly at Apple. >> Yes. >> Worked on all the big products; the iPad-- had the the tin foil on your windows back in the day during Steve Jobs' awesome run there. Welcome to theCUBE. >> Thank you, it's good to be here. >> Yeah, great, you've got a ton of experience and I want to get your perspective as a developer, VP of engineering, entrepreneur, you're doing a startup around AI. Let's have a little banter. >> Sure. >> Banter.ai is a little bit a chat bot, but the rage is DevOps. Software really models change, infrastructure as code, cloud computing. Really a renaissance of software development going on right now. >> It is, it's changing a lot. >> What's your view on this? >> Well, so, years and years ago you would work really hard on your software. You would package it up in a box and you'd send it over the wall and you hope it works. And that seems very quaint now because now you write your software, you deploy it the first day, and you change it six times that day, and you're A/B-testing it, you're driving it forward, it's so much more interactive. It does require a different skillset. It also doesn't, how do I say this carefully? It used to be very easy to be craft, to have high craft and make a very polished product, but you didn't know if it was going to work. Today you know if it's going to work, but you often don't get to making sure it's high quality, high craft, high value. >> John: So, the iteration >> Exactly, the iteration runs so fast, which is highly valuable, but you sort of just a little bit of you miss the is this really something I am proud of and I can really work with it because you know, now the product definition can change so quickly, which is awesome but it is a big change. >> And that artisan crafting thing is interesting, but now some are saying that the UX side is interesting because, if you get the back end working, and you're iterating, you can still bring that artisan flavor back. We heard that cloud computing vendors like Amazon, and I was just in China for Alibaba, they're trying to bring this whole design artisan culture back. Your thoughts on the whole artisan craft in software, because now you have two stages, you have deploy, iterate, and then ultimately polish. >> Right, so, I think it's interesting, it used to be, engineering is so expensive and time-consuming. You have to design it upfront and you make one version of it and you're done. That has changed now that engineering has gotten easier. You have better tools, we have better things, you can make six versions and that used to be, so back in the day at Apple, you would make six versions, five of which Steve would hate and throw out, and eventually they would get better and better and better and then you would have something you're proud of. Now those are just exposed. Now everybody sees those, it's a very different process. So you, I think, the idea that you. Engineering used to be this scarce resource. It's becoming easier now to have many versions and have more engineers working on stuff, so now it is much more can I have three design teams, can they compete, can they make all good ideas, and then who's going to be the editor? Who evaluates them and decides I like this from this one, I like that, and now let's put this together to make the right product. >> So, at Apple, you mentioned Steve would reject, well, that's well-documented. >> Sure. >> It's publicly out there that he would like, really look at the design-side. Was it Waterfall-based, was it Agile, Scrum, did you guys, was it like, do you lay it all out in front of him and he points at it? What were some of the work flows like with Steve Jobs? >> So, when he was really excited about something he would want to meet with them every week. He'd want to see progress every week. He'd give lots of feedback every week, there'd be new ideas. It was very Steve-focused. I think the more constructive side of it was the design teams were always thinking about What can we build, how do we put it in front of him, and I remember there was a great quote from a designer that said. It's not that Steve designs great things, it's that you show him three things, and if you throw him three bad things, he'll pick the least bad. If you show him three great things, he'll pick the most great, But it's not, it was more about the, you've got to iterate in the process, you've got to try ideas, you take ideas from different people and some of them, like, they sound like a great idea. When we talk, it sounds really good. You build it, and you're like, that's just not, that's just not right. So, you want, how do I say this? You don't want to lock yourself in up front. You want to imagine them, you want to build them, you want to try 'em. >> And that's, I mean, I've gotten to know the family over the years, too, through some of the Palo Alto interactions, and that's the kind of misperception of Steve Jobs, was that he was the guy. He enabled people, he had that ethos that-- >> He was the editor, it's an old school journalism metaphor, which is, he had ideas, he wanted, but he also, he ran the team. He wanted to have people bring their ideas and come in. And then he decided, this is good, this is not. That's better, you can do better, let's try this. Or, sometimes, this whole thing stinks. It's just not going anywhere. So, like, it was much more of that. Now it's applied to software, and he was a marketing genius, about sort of knowing what people were going to go for, but there was a little bit of a myth for it, that there's one man designing everything. That is a very saleable marketing story. >> The mythical man. (laughs) >> Well, it's powerful, but no, there's a lot of people, and getting the best work of all those people. >> I mean, he's said on some of the great videos I've watched on YouTube over the years, Hire the best people, only work with the best, and they'll bring good stuff to the table. Now, I want to bring that kind of metaphor, one step further for this great learning lesson, again it's all well-documented on YouTube. Plenty of Steve videos there, but now when you go to DevOps, you mention the whole quality thing and you got to ship fast, iterate, you know there's a lot of moving fast break stuff as Zuckerberg would say, of Facebook, although he's edited his tune to say move fast and be reliable. (laughing) Welcome to the enterprise, welcome to software and operations. This is now a scale game at the enterprise side 'cause, you know, you start seeing open source software grow so much now, where a lot of the intellectual property might be only 10% of software. >> Right. >> You might be using other pieces. You're packaging it so that when you get it to the market, how do bring that culture? How do you get that innovation of, Okay, I'm iterating fast, how do I maintain the quality. What are some of your thoughts on that? Because you've got machine learning out there, you've got these cool things happening. >> Yup. So, you want, how do I say this? You just, you really need to leave time to schedule it. It needs to be in your list. There's a lot of figuring out what are we going to build and you have to try things, iterate things, see if they resonate with consumers. See if they resonate with people who want to pay. See if they resonate with investors. You have to figure than out fast, but then you have to know that, okay, this is a good prototype. Now I have to make it work better because the first version wouldn't scale well, now it has to scale, now it has to work right for people, now you have to have a review of: here's the bugs, here's the things that are not working. Why does this chatbot stop responding sometimes? What is causing that? Now, the great story is, with good DevOps, you actually have a system that's very good at finding and tracking those problems. In the old world, so the old world with the shrink-wrap software, you'd throw it over the fence. If it misbehaves, you will never know. Today you know. You've got alerts, you've got pagers going off, you've got logs, >> It's instrumented big-time. >> Yeah, exactly, you can find that stuff. So, since you can actually make, you can make very high-quality software because you have so much more data about what's going on with it, it's nice. And actually, chatbot software has this fascinating little side effect, with, because it's all chats and it's all text, there are no irreproducible bugs. You can go back and look at exactly what happened. I have a recording, I know exactly what happened, I know exactly what came in, I know what came out, and then I know that this failure happened. So, it's very reproducible, sort of, it's nice you can, it doesn't always work this way, but it's very easy to track down problems. >> It's event-based, it's really easy to manage. >> Exactly, and it's just text. You can just read it. It's not like I have to debug hacks, it's just these things were said and this thing died. >> No core dumps. (laughs) >> No, there's nothing that requires sophisticated analysis, well the code is one thing, but like, the sequence of events is very human-readable, very understandable. >> Alright, so let's talk about the younger generation. So, we've been around the block, you and I. We've talked, certainly many times around town, about the shifts, and we love these new waves. A lot of great waves coming in, we've seen many waves. What's going on, in your mind, with the younger generation? Because this is a, some exciting things happening. Decentralized internet. >> Bruce: Yup. >> There's blockchain, getting all the attention. Outside of the hype, Alpha VCs, Alpha engineers, Alpha entrepreneurs are really honing in on blockchain because they see the potential. >> Sure. >> Early people are seeing it. Then you've got cloud, obviously unlimited compute potentially, the new, you know, kind of agile market. All these young guys, they never shipped, actually never loaded Linux on a server. (laughing) So, like, what are you seeing for the younger guys? And what do you see as someone who's experienced, looking down at the next, you know, 20 year run we see. >> So, I think what I see that's most exciting is that we now have people solving very non-technical problems with technology. I think it used to be, you could build a computer, you could write code, but then, like, your space was limited to the computer in front of you. Like, I can do input and outputs. I can put things on the screen, I can make a video game, but it's in this box. Now everyone's thinking of much bigger, Solving bigger problems. >> John: Yeah, healthcare, we're seeing verticals. >> Yeah, healthcare's a massive one. You can, operation things, shipping products. I mean, who would've thought Amazon was going to be delivering things, basically. I mean, they're using technology to solve the physical delivery of objects. That is, the space of what people are tackling is massive. It' no longer just about silicon and programming, it's sort of, any problem out there, there's someone trying to apply technology, which is awesome and I think that's because these people these youngsters, they're digital natives. >> Yeah. >> They've come to expect that, of course video conferencing works, of course all these other items work. That I just need to figure out how to solve problems with them, and I'm hopeful we're going to see more human-sized problems solved. I think, you know, we have, technology has maybe exacerbated a few things and dislocated, cost a lot of people jobs. Disconnected some people from other sort of stabilizing forces, >> Fake news. (laughs) >> Fake news, you know, we need-- >> John: It's consequences, side effects. >> I hope we get people solving those problems because fake news should now be hard to solve. They'll figure it out, I think, but, like, the idea is, we need to, technology does have a bit of a responsibility to solve, fix some of the crap that it broke. Actually, there's things that need, old structures, journalism is an old profession. >> Yeah. >> And it used to actually have all these wonderful benefits, but when the classified business went down the tubes, it took all that stuff down. >> Yeah. >> And there needs to be a venue for that. There needs to be new outlets for people to sort of do research, look things up, and hold people to account. >> Yeah, and hopefully some of our tools we'll be >> I hope so. >> pulling out at Silicon Angle you'll be seeing some new stuff. Let's talk about, like just in general, some of the fashionable coolness around engineering. Machine learning, AI obviously tops the list. Something that's not as sexy, or as innovative things. >> Sure. >> Because you have machines and industrial manufacturing plant equipment to people's devices. Obviously you worked at Apple, so you understand that piece, with the watch and everything. >> Yup, >> So you've got, that's an internet, we're things, people are things too. So, machines and people are at the edge of the network. So, you've got this new kind of concept. What gets you excited? Talk about how you feel about those trends. >> So, there's a ton going on there. I think what's amazing is the idea that all these sensors and switches and all the remote pieces can start to have smarts on them. I think the downside of that is some of the early IoT stuff, you know, has a whole open SSL stack in it. And, you know, that can be out of date, and when you have security problems with that now your light switch has access to your tax returns and that's not really what you want. So, I think there's definitely, there's a world coming, I think, at a technical level, we need to make operating systems and tools and networking protocols that aren't general purpose because general purpose tools are hackable. >> John: Yeah. >> I need to have a sensor and a switch that know how to talk to each other, and that's it. They can't rewrite code, they can't rewrite their firmware, they can't, like, I want to be able to know that, you have a nice office here, if somebody came in and tried to hack your switches, would you ever know? And the answer's like, you'd have no idea, but when you have things that are on your network and that serve you, if they're a general, if they're a little general purpose computing device, they're a mess. Like, you know, a switch is simple. A microphone, a microphone is simple. There's an output from it, it needs, I think we, >> So differentiated software for device. >> Well, let's get back to old school. You studied operating systems back in the day. >> Yeah. >> A process can do whatever the hell it wants. It can read from memory, it can write to disk, it can talk to all these buses. It's a very, it can do, it's very general purpose. I don't want that in my switch. I want my switch to be sort of, much more of these old little micro-controller. >> Bounded. >> Yeah, it's in a little box. I mean, so the phone and the Mac have something called Sandbox, which sort of says, you get a smaller view of the world. You get a little piece of the disk, you can't see everything else, and those are parts of it, but I think you need even more. You need, sort of, this really, I don't want a general purpose thing, I want a very specific thing that says I'm allowed to do this and I'm allowed to talk to that server; I don't have access to the internet. I've got access to that server. >> You mentioned operating systems. I mean, obviously I grew up in the computer science genre of the '80s and you did as well. That was a revolution around Unix. >> Yes. >> And then Berkeley, BSD, and all that stuff that happened around the systems world, operating systems, was really the pioneers in computing at that time. It's interesting with cloud, it's almost a throwback now to systems thinking. >> Bruce: It's true, yeah. >> You know, people looking at, and you're discussing it. >> Bruce: Yeah, Yeah. >> It's a systems problem. >> Yeah, it is. >> It's just not in a box. >> Right, and I think we witnessed the, let's get everyone a general purpose computer and see what they can do. And that was amazing, but now you're like I don't want everything to be a general I want very specific, I want very little thing, dedicated things that do this really well. I don't want my thermostat actually tracking when I'm in the house. You know, I want it to know, eh, maybe there's someone in the house, but I don't want it to know it's me. I don't want it reporting to Google what's going on. I want it to track my temperature and manage that. >> Our Wikibon team calls the term Unigrid, I call it hypergrid because essentially it's grid computer; there's no differentiation between on-premise and cloud. >> Right. >> It's one pool of resource of compute and things processes. >> It is, although I think, and that's interesting, you want that, but again you want it, how do I say this? I get a little nervous when all of my data goes to some cloud that I can't control. Like, I would love if, I'll put it this way. If I have a camera in my house, and imagine I put security cameras up, I want that to sort of see what's going on, I don't want it to publish the video to anywhere that's out of my control. If it publishes a summary that says, oh, like, someone came to your door, I'm like, okay, that's a good, reasonable thing to know and I would want to get that. So, Palo Alto recently added, there's traffic cameras that are looking at traffic, and they record video, but everyone's very nervous about that fact. They don't want to be recorded on video. So, the camera, this is actually really good, the camera only reports number of cars, number of bikes, number of pedestrians, just raw numbers. So you're pushing the processing down to the end and you only get these very anonymous statistics out of it and that's the right model. I've got a device, it can do a lot of sophisticated processing, but it gives nice summary data that is very public, I don't think anyone's really >> There's a privacy issue there that they've factored into the design? >> Yes, exactly. It's privacy and it's also the appropriateness of the data, you don't want, yeah, people don't want a camera watching them when they go by, but they're happy and they're like, oh, yeah, that street has a big increase in traffic, And there's a lot of, there were accidents here and there's people running red lights. That's valuable knowledge, not the fact that it's you in your Tesla and you almost hit me. No. (laughs) >> Yeah, or he's speeding, slow down. >> Exactly, yeah, or actually if you recorded speeders the fact that there's a lot of speeding is very interesting. Who's doing it, okay, people get upset if that's recorded. >> Yeah, I'm glad that Palo Alto is solving their traffic problem, Palo Alto problems, as we say. In general, security's been a huge issue. We were talking before we came on, about just the security nightmare. >> Bruce: Yes. >> A lot of companies are out there scratching their heads. There's so much of digital transformation happening, that's the buzzword in the industry. What does that mean from your standpoint? Because engineers are now moving to the front lines. Developers, engineering, because now there's a visibility to not just the software, it's an end goal. They call it outcome. Do you talk to customers a lot around, through your entrepreneurial venture, around trying to back requirements into product and yet deliver value? Do you get any insight from the field of kind of problems, you know, businesses are generally tryna solve with tech? >> So, that's interesting, I think when we try to start tech companies, we usually have ideas and then we go test that premise on customers. Perhaps I'm not as adaptable as I should be. We're not actually going to customers and asking them what they want. We're asking them if this is the kind of thing that would solve their problems. And usually they're happy to talk to us. The tough one, then, is then are they going to become paying customers, there's talking and there's paying, and they're different lines. >> I mean, certainly is validation. >> Exactly, that's when you really know that they care. It is, it's a tough question. I think there's always, there's a category of entrepreneur that's always very knowledgable about a small number of customers and they solve their problems, and those people are successful and they're often, They often are more services-based, but they're solving problems because they know people. They know a lot of people, they know what their paying point are. >> Alright, so here's the real question I want to know is, have you been back to Apple in the new building? >> Have I been to, I have not been in the spaceship. (laughing) I have not been in the spaceship yet. I actually understand that in order to have the event there, they actually had to stop work on the rest of the building because the construction process makes everything so dirty; and they did not want everyone to see dirty windows, so they actually halted the construction, they scrubbed down the trees, they had the event, and now it's, but now it's back. >> Now it's back to, >> So, I'll get there at some point. >> Bruce Arthur it the Vice President of Banter.ai, entrepreneur, formerly of Apple, good friend, Final question for you, just what are you excited about these days and as you look out at the tooling and the computer science and the societal impact that is seen with cloud and all these technologies, and open source, what do you, what are you excited about? >> I'm most excited, I think we actually have now enough computing resources and enough tools at hand that we can actually go back and tackle some harder computer science problems. I think there's things that used to be so big that you're like, well, that's just not, That's too much data, we could never solve that. That's too much, that would take, you know, that would take a hundred computers a hundred years to figure out. Those are problems now that are becoming very tractable, and I think it's been the rise of, yeah, it starts with Google, but some other companies that sort of really made these very large problems are now tractable, and they're now solvable. >> And open source, your opinion on open source these days? >> Open source is great. >> Who doesn't love more code? (laughs) >> Well, I should back this up, Open source is the fastest way to share and to make progress. There are times where you need what's called proprietary, but in other words valuable, when you need valuable engineers to work on something and, you know, not knowing the providence or where something comes from is a little sticky, I think there's going to be space for both. I think open source is big, but there's going to be-- >> If you have a core competency, you really want to code it. >> Exactly, you want to write that up and you-- >> You can still participate in the communities. >> Right, and I think open source is also, it's awesome when it's following. If there's something else in front, it follows very fast, it does a very good job. It's very thorough, sometimes it doesn't know where to go and it sort of meanders, and that's when other people have advantages. >> Collective intelligence. >> Exactly. >> Bruce, thanks for coming on. I really appreciate it, good to see you. This is a Cube Conversation here in the Palo Alto studio, I'm John Furrier, thanks for watching. (light electronic music)

(techno music) >> Hello and welcome to the special Cube presentation here in the Palo Alto studios of TheCube. I'm here with the Extend SD-Wan to the Wireless LAN segment here at Riverbed. I'm John Furrier. Our next guest is Bruce Miller, Vice President of Product Marketing at Riverbed Xirrus. Welcome to the segment: Extend the SD-Wann to the Wireless Lan Wi-Fi. [Production Man] No Wi-Fi. (sharp clap) >> Production Man: (mumbles) let's try it again. Let's get that good solid intro. >> Okay, good call. (laughing) >> Production Man: Reset please. >> Been a long day. >> Production Man: Yeah, that's okay. >> That's how long? >> Production Man: Well let's see. >> It's a tongue-twister on extend the wireless LAN. (laughing) Doesn't just roll off the tongue. (laughing) I got flustered, hold on. I got to make my font bigger. >> Production Man: You only get one mulligan. >> John: I buy mulligans when I play, or use lifesavers. (techno music) >> Hello and welcome to the special Cube presentation here in the studios in Palo Alto, California. I'm John Furrier, co-host of TheCube. This special segment: Experiencing the Future of Networking With the Extend the SD-WAN to Wireless LAN segment conversation with Bruce Miller, Vice President of Product Marketing at Riverbed Xirrus. Thanks for joining me today. Thanks for coming in. >> Great. Thanks for having me. >> So we had a whole segment on experiencing the future of networking with SD-WAN in action, but this is a dedicated segment really addressing the hottest area in the planet right now, relative to networking, that's wireless. Known as wireless LAN, local area networking or Wi-Fi. It's pervasive. It's everywhere. Most everyone knows about Wi-Fi if they have a device. They've had connections at large stadiums, large events, lot of use cases for it. But there's also the use case of internet of things. So this certainly is a topic of conversation for the future -- >> Absolutely. >> John: Of networking. >> Yeah and Wi-Fi is pervasive like you said. It's the connection to the internet for most people. In fact, a lot of people equate that; Wi-Fi equals the internet for a lot of teenagers for example. And as you mentioned, the IoT and where we are moving forward, you know it's all about growth and scale. And we only had maybe one or two Wi-Fi devices five or six years ago and now we're walking around with three, sometimes four. We have college students showing up with 15 sometimes, to their dorm. So it's very pervasive and the IoT, as you mentioned, billions and billions of devices coming online. So what we've seen is very much a scale and the need to scale these Wi-Fi networks. >> Yeah and then folks watching that are in the business of IT, you know we're all consumers too. So we've all been to stadiums or places where there's plenty of Wi-Fi, but you just can't get -- >> Bruce: Right. >> The (mumbles) to load. That's a backhaul issue, or in some cases there's not enough Wi-Fi frequency around. So there's been a dense challenge, there's been scale challenges. And then on the IoT side, for large enterprises, they have requirements that have to meet the network-- >> Right. >> Configuration. So there's complexity and scale on many fronts. This is the top priority companies. >> Yeah. >> How do you see that evolving? Because Wi-Fi wasn't really kind of built for that in the old days? >> Yeah. >> How has it evolved today? >> And it is actually a topic that Xirrus kind of saw very early on. And so if you go back 10, 12 years when we first put the company together, it was foreshadowing or foreseeing that this was going to happen. There was a lot of money going into the Wi-Fi devices, if you actually think about it, the Wi-Fi devices we're carrying around, but not the infrastructure itself. So we set out to solve that problem. And really the market then eventually kind of came to us in the sense of; hey, how do I get 10,000 people online at a convention center for example, or 20,000 people, 80,000 people in a stadium. Those are the extreme examples. But in general, it's just pervasive everywhere. You know you need Wi-Fi indoors, outdoors, in the elevator shafts, in the bathrooms. I mean we're called to cover any kind of scenario from that perspective. And so Xirrus, you know that was a challenge that we took on. And today I believe we solved it very, very well, because we can scale into these scenarios. And it keeps on going up into the right. I mean there's more traffic. There's more devices on the network every single day. Millions of devices in fact are provisioned to connect to Wi-Fi every single day that are new. And that keeps on, like I said, going up, and up. >> So scale and density has been your forte at Xirrus, now part of Riverbed though the acquisition. >> Bruce: Right. >> Translate that to the end-user or customer for you, which is the person either in IT or someone in operational technologies that has to deploy network fast. >> Bruce: Right. >> And they're going to use wireless Wi-Fi for that. What's in it for them? >> Yeah, and that's a very key part of it is deploying and getting this out there very simply and at scale. And you know provisioning the Wi-Fi network, deploying something that is now basically utility. You think about it, gas, water, electric, all these things are utilities. Wi-Fi's basically the same thing. In fact, I was just visiting a higher-ed customer of ours who made that statement. If the power goes out, the students are asking for Wi-Fi. They expect it to still work, right? It's more important, in fact, almost to them if they don't have that. So -- >> God forbid they lose the internet, but they're happy to live without power. >> Yeah, yeah, or water or whatever. So we see it that way. Wi-Fi is a utility. You need to make it utility-grade. You need to make it enterprise-grade, so we can scale and support those things. So you hit on a couple of those key things. How do you do it at scale? And then how do you provision and make that very ubiquitous and be able to role that out in a broad fashion? And that's key to what we do. >> I know you got a demo, we're going to get to that shortly. So stay tuned. Stay with us for the demo. We'll walk through a use case. Let's talk about the integration with Riverbed. Why is now important? Because I think we all can imagine and see how Wi-Fi is relevant. No doubt about it. Scale is a huge thing happening as more devices come online; people and machines. But when it has to connect into the network, that's a big conversation point with IT practitioners and people in these large companies. They want more Wi-Fi. They want it secure. They want it at scale. They want it with all the policies. Where's that integration with Riverbed? Can you explain how that works? >> Right. And that's key to where the acquisition came from. So we kind of talked about scale and then complexity, and how you deploy these things. The integration with Riverbed is really focused on the second one where there's the SD-WAN story that we've been talking about and the vision for running common policies across the WAN, the LAN, the WLAN into the data center, all managed though the cloud. And Xirrus fulfills that WLAN piece of that equation where it can be deployed at the wireless edge, connecting all those devices in an enterprise, or in whatever deployment you're talking about. And now the policies that are actually deployed are common with what is being put into the SD-WAN portion of it. So in the Riverbed side of things, that's a SteelConnect solution. So we're integrating in, as part of the SteelConnect solution, to support the software to find LAN, so to speak, at the edge of the network with switches and Wi-Fi access points that will support that. And so the synergies are very much there in terms of providing that vision across the entire network. >> So full integration of the SteelConnect from a management and provisioning standpoint -- demo perspective. >> Right. Yeah, configuration and the policies. Especially the application layer policies where you can say, hey I have a new CRN application I'm rolling out, or database application. And then that policy to prioritize that and insure a good user experience could be rolled out across the entire network. >> Give some quick use cases of customer industries that you guys are successful in. >> Sure. Probably the one we're best known for is what we call large public venues or LPVs. So this could be, for example, Liverpool Football Club which is a great name for us. Microsoft is another customer. So these are places where you have literally 10,000 and 20,000 people connecting at once, or 80,000 people in the stadium for example, a portion of those are connected to Wi-Fi. That is a very, very difficult scenario to actually solve. So we did some things that are very unique in the industry to support those kind of situations. Another big one for us is education. That is actually the biggest Wi-Fi market in general if you look at how many people are buying it or what kind of organizations are buying Wi-Fi. And we have some very large customers there; Brigham Young University for example and Idaho, Columbus State University. These are scenarios where they've rolled out ubiquitous Wi-Fi across campus, you know, stadiums, basketball arenas, all the way to the dorms, to the offices, to the auditoriums, to the libraries, indoor, outdoor, I mean it's very broad-use cases. And that's what you see in higher ed. >> I mean the Wi-Fi really kind of redefines, doesn't reimagine, but it redefines what a campus is. I mean in college -- >> Bruce: Yeah. >> You know what a campus is; hospitals, large venues like public flash mob contained campus. >> Yeah. >> The problem there's different. >> Yeah. >> There's 28 people trying to get into the -- >> All at the same time. >> Spectrum. >> Yeah, we call that flash traffic when you see, like at halftime maybe of a game, or some event happens. >> John: Touchdown, and all the videos. >> Yeah and everybody wants do do it at the same time. And those are very challenging to support those kind of scenarios. And that's something that we have really defined a solution that can handle very well. >> Well congratulations. Thank you for building that, because I love to get my Wi-Fi at Stanford Stadium and all the other places that need to have that. >> Bruce: Sure. >> And when I go to Liverpool to watch a soccer game-- >> Bruce: Yeah. I'll be kind of thinking about you guys. >> Bruce: Next time you're there. >> Okay, let's get into the demo. Let's take the real life, in action of extending SD-WAN to wireless LANs with Wi-Fi. >> Right. >> Show us what you got here. >> Bruce: Sure. So the first thing I want to talk about is provisioning the network. We have solution called CommandCenter that makes that very fast and easy. And this is actually a view of a dashboard that shows multiple tenants in a cloud management system. Okay, so imagine each of these as a separate customer. Or if I'm a large organization, this could be separate sites or locations. So I'm going to just do an example here and say let's create a new customer, and say TheCube is that customer. >> John: All right, I like that. >> Bruce: I will say that we're enabling you with Wi-Fi. So I'll create TheCube. And what this is actually doing is just with literally a few mouse clicks I've actually created a new cloud instance that is TheCube. And then what I can come down here and do is edit that location. And let's just say that, well let's see here, Joe is going to be the administrator of that. So he's going to have access to manage that network. And then I have identified a couple access points here. I'm just going to drag and drop those in there. And these are now provisioned to TheCube. And then the last thing I'm going to do is, let's take a profile. So let's say, I have a configuration template, or whatever, maybe I'll just call you. You have a business profile and I'm going to deploy that to your location as well. Hit deploy. And basically, just that quickly what I've done is actually spun up a new customer. So you can imagine if you're a service provider in fact, then that means you're quicker to revenue. I'm actually able to turn on a customer and start charging him for Wi-Fi. >> John: Let's stay on this example with TheCube. Because I think this is really important to the dense qua problem. So we go to Moscone Center all the time. >> Bruce: Sure. >> And they have Wi-Fi. They have large crowds come in. And we're used to doing a live broadcast there. >> Right, sure. >> So I'd love to have my own Wi-Fi provisioned. Is that what happened there? Could they potentially say, you know, dedicate this access point or this subnet of the network to TheCube? >> They could, I mean it would be a variation on this, but absolutely. I mean one of the things that we do very well is taking a Wi-Fi device or an AP and segment it out for use cases like that. >> John: AP being access point. >> Access point, exactly. So in a convention environment like that, those are actually quite challenging 'cause you have so many people on the network. And what you need to do is carve out a resource that might be dedicated to that. So if you can't get good Wi-Fi-- >> John: Like good video, like we do video production-- >> We can do that. >> and so we want to-- >> Yeah. >> Actually prioritize the video traffic. >> Bruce: Absolutely. And we'll show that a little bit later in the demo. >> The recreational. >> Bruce: Yeah, you separate it out, right. And make sure that-- >> So continue, so that on-ramping there-- >> Bruce: Yeah, so basically this was just showing you how quickly you can create TheCube. This is the environment that I basically set up. It's got a couple APs. It's ready to go. I can now start. I can plug in those access points, and that side is up and running. So that's the provisioning aspect. The second aspect of Wi-Fi that we don't talk about is access to the network itself. This is actually a challenge with a lot of environments that's how do I get all of these people onto the network at the same time and do that very easily without IT getting a phone call saying, hey help me I dunno what the password is or -- >> John: Are we onboarding users and stuff like that? >> Bruce: Yeah, onboarding. Well we have a solution there, it's called EasyPass. And that solution allows you to create the portals that you see when you log into -- >> John: Like (mumbles) tollbooths? >> Bruce: Yeah, and it basically provides a very easy way of doing that. So let's just say this is TheCube guest, and I'll create a new portal. And this is a guest network right, so I know when I came in here today, I connected to the Wi-Fi network and I had to figure out how to do that, and what was the password. So let's just say we're creating a Wi-Fi network here. This just shows how easy and quick that interface is. I can customize the page. Let's select an image. We'll select a background image here. And then actually use Facebook and Google can be optionally used to log in. So just that quickly I've created a portal that says, this is what you're going to see when you log in. Now obviously if it's TheCube you put your own logos and data there. But the idea here is that a user can come in here and either register with his email or use Facebook or Google for example to get on the network. >> John: Is that (mumbles) thing in through the preexisting credentials? >> Bruce: This is used, in this case, yeah with Facebook you're using the credential that they have to get onto their system. And You're basically using that for Wi-Fi as well, so that the user name and password is now providing access. >> John: So it's seamless to the user what their choice is. >> Bruce: Yeah. And some people use Facebook, others will just connect with their email. >> John: Some people want to register, but most people just want to connect with either Twitter, LinkedIn, or whatever they have. >> Bruce: Yeah, yeah. And so this basically just shows how quick and easy it is to set up a guest page that gets somebody on the network. Very simple to use. And so IT administers love this because it simplifies their job significantly. The other thing I wanted to show here real quick is just the Microsoft Azure to Google integration. We actually have integration directly with these two ecosystems where if you already are in a Office 365 shop or a Google App shop as a lot of schools are, they can just use those credentials. The user logs in with their laptop, with their username, password, and it gets them access to Wi-Fi at the same time. Kill two birds with one stone. >> John: So if it's active directory, you got your Microsoft. If it's Google and what they use you can do that. >> Bruce: Right, yeah. So it's all in the cloud. So now this is again, moving everything into the cloud as opposed to using some local resource to do authentication and maintaining those resources. >> John: That seems to be the theme with Riverbed; simplify. >> Bruce: Right, absolutely. And this is the two big things here. We're scaling the Wi-Fi network to support these broad use cases. And then we're simplifying it with the tools to enable that to roll out very smoothly. >> Well all the research points to, that manual task that don't add value will be automated away. And those tasks will be shifted to more value activities. >> Right. >> Okay, so take us through monitoring. Now what happens when, you know I'm doing my Snapchats or Instagram, or my Facebook Lives, and you go, whoa, whoa, whoa. >> Bruce: Right. >> John: Or I'm interested in knowing if someone's downloading the latest movie on BitTorrent. >> Bruce: Yeah, yeah and that's very key. So if I go back to our solution here. The dashboard actually shows what's going on in the network. So this is actually a very flexible interface. You can move things around, create widgets, do different things. And in fact we have a map function where you would lay all the stuff out on a map and then I can actually show what the coverage is, for example that Wi-Fi and a floorplan. This happens to be my house. >> John: That's an RF metric? >> Bruce: That is actually RF coverage within this location of these access points. >> John: That is very cool. >> Bruce: Then I can jump in here and troubleshoot from there. But to your point in terms of what's going on -- >> John: So it shows overlaying clouds and channels and all those deep, deep configuration stuff. >> Bruce: All the information if you need to go there. >> John: And you just don't need to get involved in that. >> Bruce: Most of this stuff is automated. There's the auto button for a lot of this when you hook up the Wi-Fi the first time. You don't want to have to tweek all of those things. So we have the auto button that 90% of the users would use or more. And then if you needed to tune it we can go from there. But yeah, to your point in terms of application policies and controls. Here's an example of what we do here. For example, I can see what types of traffic is on this network here. So let's look at for example, YouTube. And we see that there's actually a couple users here that are using a lot of YouTube traffic. I can click on any of these applications and see what the amount of traffic is associated with that. But what's more interesting then is doing something about it. So what we have is a policy engine that recognizes 1,600 different applications and allows me to create policies on them. I can create rules and say, okay let's look at YouTube specifically, which is a streaming media application. And you can see we have hundreds in here, in fact 1,600 total. And I can block YouTube if I so desire from the network. Or maybe I allow it in there, but I limit that traffic per user to say 500 K or something like that so they maybe can't watch a 4 K video or something like that. So Enterprise is-- >> John: Make it crawl for them. >> Bruce: Yeah, you can do it, but you can't overload the network. So Enterprise is hospitals. You know schools love this because they can get that granular control of the network. And maybe this happens to be instead of Enterprise that's using a database, maybe they're an Oracle shop, and so they want to raise the quality of service on that and put that high priority. So you could do that just the same. >> John: And so whatever the priority is, they can get bandwidth through it. So if it's live gaming, and you want to have that game be, that's what I want. >> Bruce: Exactly. >> John: Or minimize it. >> Bruce: So this really, what this map ends up doing is mapping the wireless to the business needs of the organization that's deploying it. >> John: So the optimization of the network, you can look at much more clearly with the visualization, and make decisions. On the network map there with the RF. Is that for placement of access points? Or is that more for understanding propagation or -- >> Bruce: It's, yeah we have a separate design tool that allows you to design those heat maps. And then when you actually have a live network what you were looking at was actually the coverage estimation based on what's actually deployed. >> John: So it's kind of -- >> Bruce: So if an AP goes down, it turns red and then you'll see a hole in your coverage and you'll know that you have a problem that you have to go and solve. >> Okay, great. So it's (mumbles) gives you a hand. >> Yeah. >> Okay, analytics. What other analytics do you have in the demo that you could share? >> Bruce: Right, so analytics is an interesting one. We have a lot of data that we pull into the network from the Wi-Fi. So if you think about it, we know who is on the network. We know what they're doing. What applications they're going to. We know where they are, 'cause we actually calculate the location of those users. And that information is all pulled into this central location here. So if I pull in a couple of these analytics charts you actually see now what is going on in that location over time. So here we have users and how long they're actually in the network. >> John: Can you see the URL path they're using? >> Bruce: That's in the application portion. This is just kind of showing bulk, like how many users are showing in the network and how long are they there. And then how many are there, and how many are actually repeat or new. So a retail customer may be interested that, if it's like I'm getting 40% existing customers coming back, but maybe there's 60% on a given day. And then that can change over time depending on location. So the bottom line is Wi-Fi is turning, for us, into a big data challenge or solution to where I can take all that data on who, what, where, why that they're doing and then turn that into business intelligence that the retailer, that's a big one, can use for making more intelligent decisions about how they run their business. >> Okay, so bottom line for the folks watching, with respect to wireless; what's the future state that they need to be thinking about in terms of planning for Wi-Fi and to experience the future of networking by extending SD-WAN to the wireless LAN? >> Right, so there's a lot of things to consider when you look at Wi-Fi. What you're doing today is probably not going to be the same as what you do next year, and certainly not five years from now. So this is actually a big challenge for a lot of our customers to kind of get that future view of what's going to happen, because they're making a purchase decision today that's going to last them for awhile. So what we look at is solving the problems that those users might run into, which can be scale, you might be using and seeing double or triple the number of users in traffic in the next few years, so you have to solve that. You have to solve the security problems, which we didn't talk about too much today, but EasyPass is one of the solutions for that. I want to ensure those users can get on, but make sure that they're secure, my corporate data is going to be protected. And then finally the simplicity of doing that. So I know Wi-Fi is going to change. I know the network requirements are going to change. How can I simply go into an interface, though this cloud management solution we provide and make those changes that are needed and adapt to that dynamic that we're talking about. And then all of that then folds into the broader picture of the SD-WAN story that we talk about with Riverbed, where now I can do some of those things across the LAN and WAN holistically through a common control point. >> And the common control point is key because the users don't view things as LAN and WAN. They just want their stuff. >> Bruce: Yeah, right. >> Wherever they are. >> Yeah, they don't care. So they might be connected into the Wi-Fi, so that's pretty visible, but in the end the Wi-Fi could work fine, but if that WAN connection is down or compromised, or anywhere in between the data center, all these things have to be working. >> And the tools to make the integration easier, whether it's Microsoft 365, and Google, On-Premise or GoogleLogin or Facebook. >> Right, right, all those ecosystems. I mean this is the big part of what we're trying to do is tap into those systems that everybody is using anyway and make it all seamless. >> John: And easy. >> So everyone knows how to log into their Google or Facebook account, so now let's just make that part of the Wi-Fi experience. >> And security's all solid? >> Yeah, security is solid if you use it. And that's the big thing about Wi-Fi is there's a lot of open guest network still out there. And little by little you're seeing those become secure, but what tends to happen is that complexity and security are kind of at odds with each other. The more secure you make a network, the more complex. >> John: And here you're making it easier. >> That's why EasyPass and the name, that's what we do to make that as simple as possible because security is very important. >> Bruce Miller: Extending the SD-WAN to the Wireless LAN in our segment experiencing the future of networking. Thanks so much for sharing. I'm John Furrier. Thanks for watching. (techno music)

>> Narrator: Live, from San Francisco, it's the Cube, covering Informatica World 2017. Brought to you by Informatica. (techno music) >> Hey, welcome back, everyone. Live here in San Francisco, this is the Cube's exclusive coverage of Informatica World 2017, our third year covering Informatica, and more to come. I'm John Furrier with Silicon Angle, the Cube. My co-host, Peter Burris, Head of Research for Silicon Angle Media, as well as General Manager of Wikibon.com, check out the great research at Wikibon. Some great stuff there on IOT, cloud ping data, great stuff. Of course, go to SiliconAngle.com for all the coverage YouTube.com/SiliconAngle for all the Cube videos. Our next guest is Bruce Chizen, board member of a lot of private companies, also Special Advisor at Informatica. You're on the board of Informatica, no? >> Executive Chair. >> John: Executive Chair of Informatica. Not only as Special Advisor, Executive Chair. Welcome back, good to see you. >> Great to be here. >> You were on last year, great to have you back. What a popular video. Jerry Held was on yesterday. Let's get some Board insights, so first question, when are you going public? (laughing) >> Good one. >> John: Warmed you up, and then, no. I mean the performance is doing well. Give us a quick update. >> Company's doing well. Q4 was a good quarter, Q1 was a good quarter. I think we will be positioned to do something late 2018, early 2019. A lot depends on how the company continues to do. A lot depends on the market. The private equity investors are in no hurry. >> John: Yeah. >> But it's always nice to have that option. >> So it's one of the things we, yeah, great option. Doing well. We heard that also from some of the management. We got O'Neil coming on, we'll press him on some of the performance side, but always had good products out, we talked about it last year. But the industry's going through a massive transformation. You've seen many waves over the years. The waves are hitting. What's your perspective right now? I mean, it's a pretty big wave. You got to get the surfboard out there, there's a set coming in. What's the big wave right now? >> So, data is driving every transformation within every organization. Any company that is not using and taking advantage of data will be left behind. You look at how companies like Amazon and Google and now a lot of our customers like Schwab and Tesla and others, the way they're using data, that will allow them to continue to either be successful in the case of a Schwab, or be a disruptor, like somebody like Tesla. Fortunately for us at Informatica, we are helping to drive that digital transformation. >> One of the things that I always observe, younger than you are, I've only seen a few waves in my day, but in the waves that were the most impactful in terms of creating wealth, and opportunity, and innovation, has had a cool and relevant factor. Meaning, if you go back to the PC days, it was cool and relevant. If you go back to mini computer, cool and relevant. And it goes on and on and on. And certainly internet, cool and relevant. But now, the, you mention Tesla. I'm testing driving one on Friday. My kids are like "Don't buy the Audi, buy the Tesla." This is my kids. So it's a cooler, it's a spaceship, it's cooler than the other cars. >> Bruce: Or an iPhone on wheels. >> Peter: (laughs) Exactly. A computer on wheels. >> So cool and relevant, talk about what is the cool and relevant thing right now. You talk about user experience, that's one. Data's changing it. So how is data being the cool and relevant trend? Point to some things that... >> If you look at what's happening from the chip on up, everything, everything will be intelligent. And I hate to use the term "internet of things," but the reality is everything will have intelligence. And that intelligent information will be able to be taken advantage of because of the scale of the cloud. Which means that any company will be able to take information, data, analyze it on the cloud, and then use it to do something with. And it's happening now. Fortunately, Informatica sits right in the middle of that, because they're the ones who could rationalize that data on behalf of their customers. 'Cause there's going to be a lot of it and somebody needs to govern it, secure it, homogenize it. >> John: You consider them an enabling platform? >> Absolutely, absolutely. I was joking, we just went through a rebranding exercise. And it's kind of cute, new logo, and it's kind of bold and sleek and it shows we'll have a leader, but it's a logo. But there's really around the messaging, we are finally getting across that we are the ones unleashing the power of data. That's what Informatica does. We'd just never really told anybody about it. We're very product focused, not really helping customers understand how uniquely positioned the company was. >> And it's also, you guys have done some things. Let's just go back and look at going private. Brought a new management team, have product chops again, we've talked about that in previous years. Last year in particular. So, okay, you have the wind at your back. Now you got Sally as a CMO, now you got to start being a humble braggart about the cool stuff you're doing. So which is marketing, basically. >> That's correct. >> John: But now, it's digital. >> Yeah. >> So, what's the Board conversation like, you say "Go, go build the brand!" >> So first of all, being private is great. (laughing) Because we get to do things you couldn't do as a public company. We're, a lot of our customers what to buy the products and solutions via subscription, that has huge impact to the P&L, especially in the short term. Cash flow's fine. So the PE guys are going okay, it's great, because we'll come out of this as a better company, and our customers like it because that's the way they want to buy products. So, that helps a lot. The conversation at the Board level has been, "Wow, we're number one in every category in which "we participate in. "Everything from big data to cloud integration "to traditional on-premise, to real-time streaming, "and, and, and data security." >> You're only one of three vendors in the Google general availabilities banner which went out yesterday. We covered that on Silicon Angle. >> We're number one there, we had AWS speak at our conference, we had Azure speak at our conference. All of the cloud guys love Informatica because we are the ones who are uniquely positioned to deal with all this data on behalf of their customers. As a private company, we're able to take advantage of that, spend some extra money on marketing. You know a lot of our customers know about us, but a lot more should know about us. So, part of coming out, having a new logo, having a new digital campaign, changing the website, that costs money. But as a private company, we get to do that. Because the fruits of those efforts will end up occurring a couple of years down the road, which is fine. >> So let me see if I can weave those two thoughts together in what I thought was an interesting way. Given that increasingly a lot of data's going to be in the cloud, and that's where the longer analysis is going to be required, that means a lot of the tools are going to have to be in the cloud. Amazon Marketplace is going to be a place where a lot of tools are going to be chosen. People are going to go into the Amazon Marketplace and see a lot of different options, including some that are free. They may not work as well, but they're free. You guys, what happens with marketing, and what's happening with that kind of a trend, is you need to buy, as customers, to choose tools that are actually going to work to serve or to solve the problem, to do the work that you need them to perform. And so what Sally Jenkins, the CMO, has done, with this new branding, is introduce the process of how do you buy us more customers to choose the right tool to do the right job? Does that make sense to you? >> It makes absolute sense, free is good. But be careful what you ask for. Sometimes you get what you pay for. You're talking about enterprise data. You want it to be governed, you want it to be secure. You want it to be accurate. >> John: Now there's laws coming out where you have to do it. >> You look at GTB... >> Peter: GDBPR. >> GDBPR in Europe, the privacy issues. You look at what's happening with Facebook, or what was reported today with France and how they're not happy with Facebook's privacy behaviors. It's an issue. It's an issue for anybody who does business anywhere, especially if you're a global company and you do business in Europe. You have to worry about corporate governance. Data security, data governance, data security. That's Informatica. The other thing is, while there will be some customers who will say "I'm going to AWS," there will be more customers who will either say "I have some legacy "systems that I'm going to leave on-premise, "and new projects will be in the cloud." Or they're going to say "I'm moving everything to "the cloud, but I don't want to be held hostage "by one cloud provider." And they're going to go with Amazon and Azure and Google and maybe Oracle, and, and, and. And again, because Informatica is Swiss, we're able to provide them with a solution that allows them to accomplish their data needs. >> Well, congratulations on the performance, I want to get that out of the way. But I want to ask a specific question on the historical, holistic picture of Informatica. Going back, what were the key bets that you guys made? 'Cause you guys sit around, and you got the private equity now coming to the table, they have expectations, but at the end of the day you've got to build a business. What were the key bets that is yielding the fruit that we're seeing? >> The number one bet was that the company had great products and a great R&D organization. We believed that, and fortunately, we got it right. Because if you don't have great products and passionate R&D organizations around the world, you can't make up for that. It doesn't make a difference how much you spend on marketing. At least not in the business that we're in. So that was number one bet, and that proved to play out well. The second thing was, this was a company that had done so well for so long that they never needed to change their business processes to behave like a billion, two billion, three billion, four billion dollar company. Many of their business processes were like that of a 200 million dollar company. And that's easier to fix. So things around back end, IT, legal, finance, go-to-market, marketing, sales. >> John: Less of a risk from an investment standpoint. >> That's correct. So that's what we believed, we were right And where we've been spending most of our energy and effort is helping the company, through the new management team, improve their business processes and their go-to-market. >> So we had a critical analysis yesterday during our wrap up session, and one of the comments I made, I want to get your reaction to this, was although impressive, your number one and all these Gartner Magic Quadrant categories, but that's an old scoreboard. If we're really living in digital transformation, those shouldn't really be a tell sign for what the performance of the new KBIs or the new metrics are. And so we were pontificating and analyzing what that would be, still unknown, we're going to see it. But Peter had a good point, he said "At the end "of the day, customer wins." >> Yeah, that was my reaction. It's like at the end of the day, all that matters do the customers.... >> What's the scoreboard look for customer wins? I know you were at the executive summit they had yesterday at the Intercontinental right around the corner. I had a chance to meet some of them at that dinner, some conversation. But I want to get your perspective. What is the vibe of the customers, what are those customer wins, and how does that translate into future growth for Informatica? >> Any customer who is looking at data, data management, strategically, is going with Informatica. >> Mmm hmm. >> There are a number of competitors that we have who try to compete with Informatica at the product level, and they end up doing okay through pricing, through better sales tactics, but when we have the opportunity to speak to the Chief Data Officer, the CIO, the CEO, they go with Informatica. It's the reason why Tesla went with Informatica on their project where they're trying to tie together the auto business with the solar business. Because if they get to know both sets of customers and are able to sync that up, one plus one will be greater than two for them, and that's why they did that deal. Or it's why Amazon has chosen our MDM solution for their sales operations. So you look at leading companies who are able to look at the enterprise level, at the strategic level, they are going with Informatica. That's why we know we're winning. >> So Bruce, give us three sentences, what is strategic data management? >> Strategic data management is being able to take reams and reams of data from all different platforms, traditional legacy, big data, real-time solutions, and data from the cloud and be able to look at it intelligently. Use artificial intelligence and machine learning to be able to analyze that data in a more intelligent way, and then act on it. >> So two questions on that point, I was going to ask about the AI washing going on in the industry. Every event now is like, "Oh my god, AI, we've got AI," but that's not really AI. What is AI, we call it augmented intelligence because you're really augmenting with the data, but even Google IO's got a little neural net throwback to the 80s, but what's your thoughts on how customers should look through the lens of b.s. to say, "Wow, that's the real AI, or the real "augmented intelligence." >> Does it do anything? That's ultimately the question that a Chief Data Officer or CIO or CEO...is something changing because of the artificial intelligence being applied? In the case of Informatica, we announced an AI platform called Clair, "clairvoyant," so artificial intelligence. What is Clair? It allows you to develop solutions like our enterprise information catalog, where an organization has thousands and thousands of databases, it's able to look at the metadata within those databases and then over time keep disclosing more and more data appropriate to the information that you're looking for. So then, if I'm an analyst or a businessperson, a marketing person, a sales person, I can take action on the right set of data. That's true artificial intelligence. >> Bruce, I want to get to one final point as we are winding down here. Again, you've seen many waves. But I want to talk about the companies that are trying to get through the transition of this transformation, Informatica certainly cleared the runway, they've got some things to work on, certainly brand-building. I see that as their air cover in many rising tide will float a lot of boats in the ecosystem. But there are companies where they have been in the infrastructure business and the cloud is one big infrastructure, selling boxes and whatnot. Other companies have traditional software models, download, whatever you want to call it, on-prem licenses, not subscriptions. They're working hard. Your advice to them if you are on their Board, or as a friend, what do you say to them, what do they got to do to get through this? And how should customers look at who's winning and who's losing, in terms of progress? >> The world of enterprise computing is moving to the cloud. Legacy systems will remain for a while. They need to figure out how to take their legacy solutions and make them relevant to the world of cloud computing. And if they can't do that, they should sell their company or get out of business. (laughing) >> And certainly data is the oil, it's the gold, it's the lifeblood of an organization. >> Of any organization. Even at Informatica, internally, we're using our own intelligent data platform to do our own marketing. Sally Jenkins is working closely with our CIO Graeme Thompson on working on solutions where we could help better understand what our customers want and need, so we can provide them with the right solution, leveraging our intelligent data leg. >> Bruce, thanks for coming on the Cube. Really appreciate your insight. Again, you've seen a lot of waves, you've been in the industry a long time, you have great Board presence, as well as other companies. Thanks for sharing the insight, and the data here on the Cube. A lot of insights and analytics being extracted here and sharing it with you. Certainly we're not legacy, we don't need to sell our business, we're doing great. If you haven't, make the transition. Good advice, thanks so much. >> Bruce: Great to be here. >> Bruce Chizen inside the Cube here. I'm John Furrier with Peter Burris. Stay with us for more coverage after this short break. (techno music)

(dramatic music) >> Narrator: Live from Fisherman's Wharf in San Francisco. It's theCube. Covering IBM Chief Data Officer Strategy Summit Spring 2017. Brought to you by IBM. >> Hey, welcome back, everybody. Jeff Frank here with theCube. We are wrapping up day one at the IBM CEO Strategy Summit Spring 2017 here at the Fisherman's Wharf Hyatt. A new venue for us, never been here. It's kind of a cool venue. Joined by Peter Burris, Chief Research Officer from Wikibon, and we're excited to have practitioners. We love getting practitioners on. So we're joined by this segment by Bruce Tyler. He's a VP Data Analytics for IBM Global Business Services. Bruce, nice to see you. >> Thank you. >> And he's brought along Fawad Butt, the Chief Data Governance Officer for Kaiser Permanente. Welcome. >> Thank you, thank you. >> So Kaiser Permanente. Regulated industry, health care, a lot of complex medical issues, medical devices, electronic health records, insurance. You are in a data cornucopia, I guess. >> It's data heaven all the way. So as you mentioned, Kaiser is a vertically integrated organization, Kaiser Permanente is. And as such the opportunity for us is the fact that we have access to a tremendous amount of data. So we sell insurance, we run hospitals, medical practices, pharmacies, research labs, you name it. So it's an end to end healthcare system that generates a tremendous amount of dataset. And for us the real opportunity is to be able to figure out all the data we have and the best uses for it. >> I guess I never really thought of it from the vertical stack perspective. I used to think it was just the hospital, but the fact that you have all those layers of the cake, if you will, and can operate within them, trade data within them, and it gives you a lot of kind of classic vertical stack integration. That fits. >> Very much so. And I didn't give you the whole stack. I mean, we're actually building a medical school in Southern California. We have a residency program in addition to everything else we've talked about. But yeah, the vertical stack does provide us access to data and assets related to data that are quite unique. On the one side, it's a great opportunity. On the other side, it has to be all managed and protected and served in the best interest of our patrons and members. >> Jeff: Right, right. And just the whole electronic health records by themselves that people want access to that, they want to take them with. But then there's all kinds of scary regulations around access to that data. >> So the portability, I think what you're talking about is the medical record portability, which is becoming a really new construct in the industry because people want to be able to move from practitioner to practitioner and have that access to records. There are some regulation that provide cover at a national scale but a lot of this also is impacted by the states that you're operating in. So there's a lot of opportunities where I can tell some of the regulation in this space over time and I think that will, then we'll see a lot more adoption in terms of these portability standards which tend to be a little one off right now. >> Right, right. So I guess the obvious question is how the heck do you prioritize? (laughter) You got a lot of things going on. >> You know, I think it's really the standard blocking/tackling sort of situation, right? So one of the things that we've done is taken a look at our holistic dataset end to end and broken it down into pieces. How do you solve this big problem? You solve it by piecing it out a little bit. So what we've done is that we've put our critical dataset into a set of what we call data domains. Patient, member, providers, workers, HR, finance, you name it. And then that gives us the opportunity to not only just say how good is our data holistically but we can also go and say how good is our patient data versus member data versus provider data versus HR data. And then not only just know how good it is but it also gives us the opportunity to sort of say, "Hey, there's no conceivable way we can invest "in all 20 of these areas at any given point." So what's the priority that aligns with business objectives and goals? If you think about corporate strategy in general, it's based on customers and demand and availability and opportunities but now we're adding one more tool set and giving that to our executives. As they're making decisions on investments in longer term, and this isn't just KP, it's happening across industries, is that the data folks are bringing another lens to the table, which is to say what dataset do we want to invest in over the course of the next five years? If you had to choose between 20, what are the three that you prioritize first versus the other. So I think it's another lever, it's another mechanism to prioritize your strategy and your investments associated with that. >> But you're specifically focused on governance. >> Fawad: I am. >> In the health care industry, software for example is governed by a different set of rules as softwares in other areas. Data is governed by a different set of rules than data is governed in most other industries. >> Fawad: Correct. >> Finance has its own set of things and then some others. What does data governance mean at KP? Which is a great company by the way. A Bay Area company. >> Absolutely. >> What does it mean to KP? >> It's a great question, first of all. Every data governance program has to be independent and unique because it should be trying to solve for a set of things that are relevant in that context. For us at KP, there are a few drivers. So first is, as you mentioned, regulation. There's increased regulation. There's increased regulatory scrutiny in pressure. Some things that have happened in financial services over the last eight or ten years are starting to come and trickle in to the healthcare space. So there's that. There's also a changing environment in terms of how, at least from an insurance standpoint, how people acquire health insurance. It used to be that your employer provided a lot of that, those services and those insurances. Now you have private marketplaces where a lot of people are buying their own insurance. And you're going from a B2B construct to a B2C construct in certain ways. And these folks are walking around with their Android phones or their iPhones and they're used to accessing all sorts of information. So that's the customer experience that you to to deliver to them. So there's this digital transformation that's happening that's driving some of the need around governance. The other areas that I think are front and center for us are obviously privacy and security. So we're custodians of a lot of datasets that relate to patients' health information and their personal information. And that's a great responsibility and I think from a governance standpoint that's one of the key drivers that define our focus areas in the governance space. There are other things that are happening. There's obviously our mission within the organization which is to deliver the highest coverage and care at the lowest cost. So there's the ability for us to leverage our data and govern our data in a way which supports those two mission statements, but the bigger challenge in nuts and bolts terms for organizations like ours, which are vertically integrated, is around understanding and taking stock of the entire dataset first. Two, protecting it and making sure that all the defenses are in place. But then three, figuring out the right purposes to use this, to use the data. So data production is great but data consumption is where a lot of the value gets captured. So for us some of the things that data governance facilitates above all is what data gets shared for what purposes and how. Those are things that an organization of our size deliver a tremendous amount of value both on the offensive and the defensive side. >> So in our research we've discovered that there are a lot of big data functions or analytic functions that fail because they started with the idea of setting up the infrastructure, creating a place to put the data. Then they never actually got to the use case or when they did get to the use case they didn't know what to do next. And what a surprise. No returns, lot of costs, boom. >> Yep. >> The companies that tend to start with the use case independently individual technologies actually have a clear path and then the challenge is to accrete knowledge, >> Yes. >> accrete experience and turn it into knowledge. So from a governance standpoint, what role do you play at KP to make sure that people stay focused in use cases, that the lessons you learn about pursuing those use cases then turn to a general business capability in KP. >> I mean, again, I think you hit it right on the head. Data governance, data quality, data management, they're all great words, right? But what do they support in terms of the outcomes? So from our standpoint, we have a tremendous amount of use cases that if we weren't careful, we would sort of be scatterbrained around. You can't solve for everything all at once. So you have to find the first set of key use cases that you were trying to solve for. For us, privacy and security is a big part of that. To be able to, there's a regulatory pressure there so in some cases if you lose a patient record, it may end up costing you $250,000 for a record. So I think it's clear and critical for us to be able to continue to support that function in an outstanding way. The second thing is agility. So for us one of the things that we're trying to do with governance and data management in general, is to increase our agility. If you think about it, a lot of companies go on these transformation journeys. Whether it's transforming HR or trying to transform their finance functions or their business in general, and that requires transforming their systems. A lot of that work, people don't realize, is supported and around data. It's about integrating your old data with the new business processes that you're putting out. And if you don't have that governance or that data management function in place to be able to support that from the beginning or have some maturity in place, a lot of those activities end up costing you a lot more, taking a lot longer, having a lower success rate. So for us delivering value by creating additional agility for a set of activities that as an organization, we have committed to, is one for of core use cases. So we're doing a transformation. We're doing some transformation around HR. That's an area where we're making a lot of investments from a data governance standpoint to be able to support that as well as inpatient care and membership management. >> Great, great lessons. Really good feedback for fellow practitioners. Bruce, I want to get your perspective. You're kind of sitting on the other side of the table. As you look at the experience at Kaiser Permanente, how does this equate with what you're seeing with some of your other customers, is this leading edge or? >> Clearly on point. In fact, we were talking about this before we came up and I'm not saying that you guys led, we led the witness here but really how do you master around the foundational aspects around the data, because at the end of the day it's always about the data. But then how do you start to drive the value out of that and go down that cognitive journey that's going to either increase value onto your insights or improve your business optimization? We've done a healthy business within IBM helping customers go through those transformation processes. I would say five years ago or even three years ago we would start big. Let's solve the data aspect of it. Let's build the foundational management processes around there so that it ensures that level of integrity and trusted data source that you need across an organization like KP because they're massive because of all the different types of business entities that they have. So those transformation initiatives, they delivered but it was more from an IT perspective so the business partners that really need to adopt and are going to get the value out of that were kind of in a waiting game until that came about. So what we're seeing now is looking at things around from a use case-driven approach. Let's start small. So whether you're looking at trying to do something within your call center and looking at how to improve automation and insights in that spec, build a proof of value point around a subset of the data, prove that value, and those things can typically go from 10 to 12 weeks, and once you've demonstrated that, now how do can you scale? But you're doing it under your core foundational aspects around the architecture, how you're going to be able to sustain and maintain and govern the data that you have out there. >> It's a really important lesson all three of you have mentioned now. That old method of let's just get all the infrastructure in place is really not a path to success. You getting hung up, spend a lot of money, people get pissed off and oh by the way, today your competitors are transforming right around you while you're >> Unless they're also putting >> tying your shoes. >> infrastructure. >> Unless they're also >> That's right. (laughter) >> tying their shoes too. >> Build it and they will come sounds great, but in the data space, it's a change management function. One of my favorite lines that I use these days is data management is a team sport. So this isn't about IT, or this isn't just about business, and can you can't call business one monolith. So it's about the various stakeholders and their needs and your ability to satisfy them to the changes you're about to implement. And I think that gets lost a lot of times. It turns into a technical conversation around just capability development versus actually solving and solutioning for that business problem set that are at hand. >> Jeff: Yeah. >> Peter: But you got to do both, right? >> You have to. >> Bruce: Absolutely, yeah. >> Can I ask you, do we have time for another couple of questions? >> Absolutely. >> So really quickly, Fawad, do you have staff? >> Fawad: I do. >> Tell us about the people on your staff, where they came from, what you're looking for. >> So one of the core components of data governance program are stewards, data stewards. So to me, there are multiple dimensions to what stewards, what skills they should have. So for stewards, I'm looking for somebody that has some sort of data background. They would come from design, they would come from architecture, they would come from development. It doesn't really matter as long as they have some understanding. >> As long as you know what a data structure is and how you do data monitoring. >> Absolutely. The second aspect is that they have to have an understanding of what influence means. Be able to influence outcomes, to be able to influence conversations and discussions way above their pay grade, so to be able to punch above your weight so to speak in the influence game. And that's a science. That's a very, very definitive science. >> Yeah, we've heard many times today that politics is an absolute crucial game you have to play. >> It is part of the game and if you're not accounting for it, it's going to hit you in the face when you least expect it. >> Right. >> And the third thing is, I look for people that have some sort of an execution background. So ability to execute. It's great to be able to know data and understand data and go out and influence people and get them to agree with you, but then you have to deliver. So you have to be able to deliver against that. So those are the dimensions I look at typically when I'm looking at talent as it relates particularly to stewardship talent. In terms of where I find it, I try to find it within the organization because if I do find it within the organization, it gives me that organizational understanding and those relationship portfolios that people bring to the table which tend to be part of that influence-building process. I can teach people data, I can teach them some execution, I can't teach them how to do influence management. That just has to-- >> You can't teach them to social network. >> Fawad: (laughing) That's exactly right. >> Are they like are the frustrated individuals that have been seen the data that they're like (screams) this is-- >> They come from a lot of different backgrounds. So I have a steward that is an attorney, is a lawyer. She comes from that background. I have a steward that used to be a data modeler. I have a steward that used to run compliance function within HR. I have a steward that comes from a strong IT background. So it's not one formula. It's a combination of skills and everybody's going to have a different set of strengths and weaknesses and as long as you can balance those out. >> So people who had an operational role, but now are more in an execution setup role. >> Fawad: Yeah, very much so. >> They probably have a common theme, though, across them that they understand the data, they understand the value of it, and they're able to build consensus to make an action. >> Fawad: That's correct. >> That's great. That's perfect close. They understand it and they can influence, and they can get to action. Pretty much sums it up, I think so. All right. >> Bruce: All right thank you. >> Well, thanks a lot, Bruce and Fawad for stopping by. Great story. Love all the commercials on the Warriors, I'm a big fan and watch KNBR. (laughter) But really a cool story and thanks for sharing it and continued success. >> Thank you for the opportunity. >> Absolutely. All right, with Peter Burris, I'm Jeff Frank. You're watching theCube from the IBM Chief Data Officer Strategy Summit Spring 2017 from Fisherman's Wharf, San Francisco. We'll be right back after this short break. Thanks for watching. (electronic music)

>> We're back at the ARIA Las Vegas. We're covering CrowdStrike's Fal.Con 22. First one since 2019. Dave Vellante and Dave Nicholson on theCUBE. Adam Meyers is here, he is the Senior Vice President of Intelligence at CrowdStrike. Adam, thanks for coming to theCUBE. >> Thanks for having me. >> Interesting times, isn't it? You're very welcome. Senior Vice President of Intelligence, tell us what your role is. >> So I run all of our intelligence offerings. All of our analysts, we have a couple hundred analysts that work at CrowdStrike tracking threat actors. There's 185 threat actors that we track today. We're constantly adding more of them and it requires us to really have that visibility and understand how they operate so that we can inform our other products: our XDR, our Cloud Workload Protections and really integrate all of this around the threat actor. >> So it's that threat hunting capability that CrowdStrike has. That's what you're sort of... >> Well, so think of it this way. When we launched the company 11 years ago yesterday, what we wanted to do was to tell customers, to tell people that, well, you don't have a malware problem, you have an adversary problem. There are humans that are out there conducting these attacks, and if you know who they are what they're up to, how they operate then you're better positioned to defend against them. And so that's really at the core, what CrowdStrike started with and all of our products are powered by intelligence. All of our services are our OverWatch and our Falcon complete, all powered by intelligence because we want to know who the threat actors are and what they're doing so we can stop them. >> So for instance like you can stop known malware. A lot of companies can stop known malware, but you also can stop unknown malware. And I infer that the intelligence is part of that equation, is that right? >> Absolutely. That that's the outcome. That's the output of the intelligence but I could also tell you who these threat actors are, where they're operating out of, show you pictures of some of them, that's the threat intel. We are tracking down to the individual persona in many cases, these various threats whether they be Chinese nation state, Russian threat actors, Iran, North Korea, we track as I said, quite a few of these threats. And over time, we develop a really robust deep knowledge about who they are and how they operate. >> Okay. And we're going to get into some of that, the big four and cyber. But before we do, I want to ask you about the eCrime index stats, the ECX you guys call it a little side joke for all your nerds out there. Maybe you could explain that Adam >> Assembly humor. >> Yeah right, right. So, but, what is that index? You guys, how often do you publish it? What are you learning from that? >> Yeah, so it was modeled off of the Dow Jones industrial average. So if you look at the Dow Jones it's a composite index that was started in the late 1800s. And they took a couple of different companies that were the industrial component of the economy back then, right. Textiles and railroads and coal and steel and things like that. And they use that to approximate the overall health of the economy. So if you take these different stocks together, swizzle 'em together, and figure out some sort of number you could say, look, it's up. The economy's doing good. It's down, not doing so good. So after World War II, everybody was exuberant and positive about the end of the war. The DGI goes up, the oil crisis in the seventies goes down, COVID hits goes up, sorry, goes down. And then everybody realizes that they can use Amazon still and they can still get the things they need goes back up with the eCrime index. We took that approach to say what is the health of the underground economy? When you read about any of these ransomware attacks or data extortion attacks there are criminal groups that are working together in order to get things spammed out or to buy credentials and things like that. And so what the eCrime index does is it takes 24 different observables, right? The price of a ransom, the number of ransom attacks, the fluctuation in cryptocurrency, how much stolen material is being sold for on the underground. And we're constantly computing this number to understand is the eCrime ecosystem healthy? Is it thriving or is it under pressure? And that lets us understand what's going on in the world and kind of contextualize it. Give an example, Microsoft on patch Tuesday releases 56 vulnerabilities. 11 of them are critical. Well guess what? After hack Tuesday. So after patch Tuesday is hack Wednesday. And so all of those 11 vulnerabilities are exploitable. And now you have threat actors that have a whole new array of weapons that they can deploy and bring to bear against their victims after that patch Tuesday. So that's hack Wednesday. Conversely we'll get something like the colonial pipeline. Colonial pipeline attack May of 21, I think it was, comes out and all of the various underground forums where these ransomware operators are doing their business. They freak out because they don't want law enforcement. President Biden is talking about them and he's putting pressure on them. They don't want this ransomware component of what they're doing to bring law enforcement, bring heat on them. So they deplatform them. They kick 'em off. And when they do that, the ransomware stops being as much of a factor at that point in time. And the eCrime index goes down. So we can look at holidays, and right around Thanksgiving, which is coming up pretty soon, it's going to go up because there's so much online commerce with cyber Monday and such, right? You're going to see this increase in online activity; eCrime actors want to take advantage of that. When Christmas comes, they take vacation too; they're going to spend time with their families, so it goes back down and it stays down till around the end of the Russian Orthodox Christmas, which you can probably extrapolate why that is. And then it goes back up. So as it's fluctuating, it gives us the ability to really just start tracking what that economy looks like. >> Realtime indicator of that crypto. >> I mean, you talked about, talked about hack Wednesday, and before that you mentioned, you know, the big four, and I think you said 185 threat actors that you're tracking, is 180, is number 185 on that list? Somebody living in their basement in their mom's basement or are the resources necessary to get on that list? Such that it's like, no, no, no, no. this is very, very organized, large groups of people. Hollywood would have you believe that it's guy with a laptop, hack Wednesday, (Dave Nicholson mimics keyboard clacking noises) and everything done. >> Right. >> Are there individuals who are doing things like that or are these typically very well organized? >> That's a great question. And I think it's an important one to ask and it's both it tends to be more, the bigger groups. There are some one-off ones where it's one or two people. Sometimes they get big. Sometimes they get small. One of the big challenges. Have you heard of ransomware as a service? >> Of course. Oh my God. Any knucklehead can be a ransomwarist. >> Exactly. So we don't track those knuckleheads as much unless they get onto our radar somehow, they're conducting a lot of operations against our customers or something like that. But what we do track is that ransomware as a service platform because the affiliates, the people that are using it they come, they go and, you know, it could be they're only there for a period of time. Sometimes they move between different ransomware services, right? They'll use the one that's most useful for them that that week or that month, they're getting the best rate because it's rev sharing. They get a percentage that platform gets percentage of the ransom. So, you know, they negotiate a better deal. They might move to a different ransomware platform. So that's really hard to track. And it's also, you know, I think more important for us to understand the platform and the technology that is being used than the individual that's doing it. >> Yeah. Makes sense. Alright, let's talk about the big four. China, Iran, North Korea, and Russia. Tell us about, you know, how you monitor these folks. Are there different signatures for each? Can you actually tell, you know based on the hack who's behind it? >> So yeah, it starts off, you know motivation is a huge factor. China conducts espionage, they do it for diplomatic purposes. They do it for military and political purposes. And they do it for economic espionage. All of these things map to known policies that they put out, the Five Year Plan, the Made in China 2025, the Belt and Road Initiative, it's all part of their efforts to become a regional and ultimately a global hegemon. >> They're not stealing nickels and dimes. >> No they're stealing intellectual property. They're stealing trade secrets. They're stealing negotiation points. When there's, you know a high speed rail or something like that. And they use a set of tools and they have a set of behaviors and they have a set of infrastructure and a set of targets that as we look at all of these things together we can derive who they are by motivation and the longer we observe them, the more data we get, the more we can get that attribution. I could tell you that there's X number of Chinese threat groups that we track under Panda, right? And they're associated with the Ministry of State Security. There's a whole other set. That's too associated with the People's Liberation Army Strategic Support Force. So, I mean, these are big operations. They're intelligence agencies that are operating out of China. Iran has a different set of targets. They have a different set of motives. They go after North American and Israeli businesses right now that's kind of their main operation. And they're doing something called hack and lock and leak. With a lock and leak, what they're doing is they're deploying ransomware. They don't care about getting a ransom payment. They're just doing it to disrupt the target. And then they're leaking information that they steal during that operation that brings embarrassment. It brings compliance, regulatory, legal impact for that particular entity. So it's disruptive >> The chaos creators that's.. >> Well, you know I think they're trying to create a they're trying to really impact the legitimacy of some of these targets and the trust that their customers and their partners and people have in them. And that is psychological warfare in a certain way. And it, you know is really part of their broader initiative. Look at some of the other things that they've done they've hacked into like the missile defense system in Israel, and they've turned on the sirens, right? Those are all things that they're doing for a specific purpose, and that's not China, right? Like as you start to look at this stuff, you can start to really understand what they're up to. Russia very much been busy targeting NATO and NATO countries and Ukraine. Obviously the conflict that started in February has been a huge focus for these threat actors. And then as we look at North Korea, totally different. They're doing, there was a major crypto attack today. They're going after these crypto platforms, they're going after DeFi platforms. They're going after all of this stuff that most people don't even understand and they're stealing the crypto currency and they're using it for revenue generation. These nuclear weapons don't pay for themselves, their research and development don't pay for themselves. And so they're using that cyber operation to either steal money or steal intelligence. >> They need the cash. Yeah. >> Yeah. And they also do economic targeting because Kim Jong Un had said back in 2016 that they need to improve the lives of North Koreans. They have this national economic development strategy. And that means that they need, you know, I think only 30% of North Korea has access to reliable power. So having access to clean energy sources and renewable energy sources, that's important to keep the people happy and stop them from rising up against the regime. So that's the type of economic espionage that they're conducting. >> Well, those are the big four. If there were big five or six, I would presume US and some Western European countries would be on there. Do you track, I mean, where United States obviously has you know, people that are capable of this we're out doing our thing, and- >> So I think- >> That defense or offense, where do we sit in this matrix? >> Well, I think the big five would probably include eCrime. We also track India, Pakistan. We track actors out of Columbia, out of Turkey, out of Syria. So there's a whole, you know this problem is getting worse over time. It's proliferating. And I think COVID was also, you know a driver there because so many of these countries couldn't move human assets around because everything was getting locked down. As machine learning and artificial intelligence and all of this makes its way into the cameras at border and transfer points, it's hard to get a human asset through there. And so cyber is a very attractive, cheap and deniable form of espionage and gives them operational capabilities, not, you know and to your question about US and other kind of five I friendly type countries we have not seen them targeting our customers. So we focus on the threats that target our customers. >> Right. >> And so, you know, if we were to find them at a customer environment sure. But you know, when you look at some of the public reporting that's out there, the malware that's associated with them is focused on, you know, real bad people, and it's, it's physically like crypted to their hard drive. So unless you have sensor on, you know, an Iranian or some other laptop that might be target or something like that. >> Well, like Stuxnet did. >> Yeah. >> Right so. >> You won't see it. Right. See, so yeah. >> Well Symantec saw it but way back when right? Back in the day. >> Well, I mean, if you want to go down that route I think it actually came from a company in the region that was doing the IR and they were working with Symantec. >> Oh, okay. So, okay. So it was a local >> Yeah. I think Crisis, I think was the company that first identified it. And then they worked with Symantec. >> It Was, they found it, I guess, a logic controller. I forget what it was. >> It was a long time ago, so I might not have that completely right. >> But it was a seminal moment in the industry. >> Oh. And it was a seminal moment for Iran because you know, that I think caused them to get into cyber operations. Right. When they realized that something like that could happen that bolstered, you know there was a lot of underground hacking forums in Iran. And, you know, after Stuxnet, we started seeing that those hackers were dropping their hacker names and they were starting businesses. They were starting to try to go after government contracts. And they were starting to build training offensive programs, things like that because, you know they realized that this is an opportunity there. >> Yeah. We were talking earlier about this with Shawn and, you know, in the nuclear war, you know the Cold War days, you had the mutually assured destruction. It's not as black and white in the cyber world. Right. Cause as, as Robert Gates told me, you know a few years ago, we have a lot more to lose. So we have to be somewhat, as the United States, careful as to how much of an offensive posture we take. >> Well here's a secret. So I have a background on political science. So mutually assured destruction, I think is a deterrent strategy where you have two kind of two, two entities that like they will destroy each other if they so they're disinclined to go down that route. >> Right. >> With cyber I really don't like that mutually assured destruction >> That doesn't fit right. >> I think it's deterrents by denial. Right? So raising the cost, if they were to conduct a cyber operation, raising that cost that they don't want to do it, they don't want to incur the impact of that. Right. And think about this in terms of a lot of people are asking about would China invade Taiwan. And so as you look at the cost that that would have on the Chinese military, the POA, the POA Navy et cetera, you know, that's that deterrents by denial, trying to, trying to make the costs so high that they don't want to do it. And I think that's a better fit for cyber to try to figure out how can we raise the cost to the adversary if they operate against our customers against our enterprises and that they'll go someplace else and do something else. >> Well, that's a retaliatory strike, isn't it? I mean, is that what you're saying? >> No, definitely not. >> It's more of reducing their return on investment essentially. >> Yeah. >> And incenting them- disincening them to do X and sending them off somewhere else. >> Right. And threat actors, whether they be criminals or nation states, you know, Bruce Lee had this great quote that was "be like water", right? Like take the path of least resistance, like water will. Threat actors do that too. So, I mean, unless you're super high value target that they absolutely have to get into by any means necessary, then if you become too hard of a target, they're going to move on to somebody that's a little easier. >> Makes sense. Awesome. Really appreciate your, I could, we'd love to have you back. >> Anytime. >> Go deeper. Adam Myers. We're here at Fal.Con 22, Dave Vellante, Dave Nicholson. We'll be right back right after this short break. (bouncy music plays)

>>Okay, welcome back everyone to the Cube's live coverage here in Las Vegas for Amazon re Mars two days of coverage, we're getting down to wrapping up day one. I'm John furrier host of the cube space is a big topic here. You got machine learning, you got automation, robotics, all spells Mars. The two great guests here to really get into the whole geo scene. What's going on with the data. We've got Marcus Norren business development and geo data. Sogeti part of cap Gemini group, and Yoki well kissed portfolio lead data and AI with Sogeti part of cap, Gemini gentlemen, thanks for coming on the queue. Appreciate it. Thanks >>For having us. >>Let me so coming all the way from Sweden to check out the scene here and get into the weeds and the show. A lot of great technology being space is the top line here, but software drives it. Um, you got robotics. Lot of satellite, you got the aerospace industry colliding with hardcore industrial. I say IOT, robotics, one, whatever you want, but space kind of highlights the IOT opportunity. There is no edge in space, right? So the edge, the intelligent edge, a lot going on in space. And satellite's one of 'em you guys are in the middle of that. What are you guys working on? What's the, the focus here for cap gem and I Sogeti part of cap >>Gemini. I would say we focus a lot of creating business value, real business value for our clients, with the satellites available, actually a free available satellite images, working five years now with this, uh, solutioning and, uh, mostly invitation management and forestry. That's our main focus. >>So what's the product value you guys are offering. >>We basically, for now the, the most value we created is working with a forest client to find park Beal infests, uh, in spruce forest. It's a big problem in European union and, uh, Northern region Sweden, where we live now with the climate change, it's getting warmer, the bark beetle bases warm more times during the summer, which makes it spread exponentially. Uh, so we help with the satellite images to get with data science and AI to find these infestations in time when they are small, before it's spread. >>So satellite imagery combined with data, this is the intersection of the data piece, the geo data, right? >>Yeah. You can say that you have, uh, a lot of open satellite data, uh, and uh, you want to analyze that, that you also need to know what you're looking for and you need data to understand in our case, a certain type of damage. So we have large data sets that we have to sort of clean and train ML models from to try to run that on that open data, to detect these models. And, and when we're saying satellite data and open data, it's basically one pixel is 10 by 10 meters. So it's not that you will see the trees, but we're looking at the spectral information in the image and finding patterns. So we can actually detect attacks that are like four or five trees, big, uh, using that type. And we can do that throughout the season so we can see how you start seeing one, two attacks and it's just growing. And then you have this big area of just damage. So >>How, how long does that take? Give me some scope to scale because it sounds easy. Oh, the satellites are looking down on us. It's not, it's a lot of data there. What's the complexity. What are the challenges that you guys are overcoming scope to scale? >>It's so much complexity in this first, you have clouds, so it's, uh, open data set, you download it and you figure out here, we have a satellite scene, which is cloudy. We need to have some analytics doing that, taking that image away basically, or the section of the image with it cloudy. Then we have a cloud free image. We can't see anything because it's blurry. It's too low resolution. So we need to stack them on top of each other. And then we have the next problem to correlate them. So they are pixel perfect overlapping. Yeah. So we can compare them in time. And then they have the histogram adjustment to make them like, uh, the sensitivity is the same on all the images, because you have solar storms, you have shady clouds, which, uh, could be used still that image. So we need to compare that. Then we have the ground proof data coming from, uh, a harvester. For instance, we got 200,000 data points from the harvester real data points where they had found bark Beal trees, and they pulled them down. The GPS is drifting 50 meters. So you have an uncertainty where the actually harvest it was. And then we had the crane on 20 meters. So, you know, the GPS is on the home actually of the home actual machine and the crane were somewhere. So you don't really know you have this uncertainty, >>It's a data integration problem. Yeah. Massive, >>A lot of, of, uh, interesting, uh, things to adjust for. And then you could combine this into one deep learning model and build. >>But on top of that, I don't know if you said that, but you also get the data in the winter and you have the problem during the summer. So we actually have to move back in time to find the problem, label the data, and then we can start identifying. >>So once you get all that heavy lifting done or, or write the code, or I don't know if something's going on there, you get the layering, the pixel X see all the, how complex that is when the deep learning takes over. What happens next? Is it scale? Is it is all the heavy lifting up front? Is the work done front or yeah. Is its scale on the back end? >>So first the coding is heavy work, right? To gets hands on and try different things. Figure out in math, how to work with this uncertainty and get everything sold. Then you put it into a deep learning model to train that it actually run for 10 days before it was accurate, or first, first ation, it wasn't accurate enough. So we scrap that, did some changes. Then we run it again for 10 days. Then we have a model which we could use and interfere new images. Like every day, pretty quickly, every day it comes a new image. We run it. We have a new outcome and we could deliver that to clients. >>Yeah. I can almost imagine. I mean, the, the cloud computing comes in handy here. Oh yeah. So take me through the benefits because it sounds like the old, the old expression, the juice is not worth the squeeze here. It is. It's worth the squeeze. If you can get it right. Because the alternative is what more expensive gear, different windows, just more expensive monolithic solutions. Right? >>Think about the data here. So it's satellite scene. Every satellite scene is hundred by a hundred kilometers. That pretty much right. And then you need a lot of these satellite scene over multiple years to combine it. So if you should do this over the whole Northern Europe, over the whole globe, it's a lot of data just to store that it's a problem. You, you cannot do it on prem and then you should compute it with deep learning models. It's a hard problem >>If you don't have, so you guys got a lot going on. So, so talk about spaghetti, part of cap, Gemini, explain that relationship, cuz you're here at a show that, you know, you got, I can see the CAPI angle. This is like a little division. Is it a group? Are you guys like lone wolves? Like, what's it like, is this dedicated purpose built focus around aerospace? >>No, it's actually SOI was the, the name of the CAPI company from the beginning. And they relaunched the brand, uh, 2001, I think roughly 10, 20 years ago. So we actually celebrate some anniversary now. Uh, and it's a brand which is more local close to clients out in different cities. And we also tech companies, we are very close to the new technology, trying things out. And this is a perfect example of this. It was a crazy ID five years ago, 2017. And we started to bring in some clients explore, really? Open-minded see, can we do something on these satellite data? And then we took it step by step together of our clients. Yeah. And it's a small team where like 12 >>People. Yeah. And you guys are doing business development. So you have to go out there and identify the kinds of problems that match the scope of the scale. >>So what we're doing is we interact with our clients, do some simple workshops or something and try to identify like the really valuable problems like this Bruce Park people that that's one of those. Yep. And then we have to sort of look at, do we think we can do something? Is it realistic? And we will not be able to answer that to 100% because then there's no innovation in this at all. But we say, well, we think we can do it. This will be a hard problem, but we do think we can do it. And then we basically just go for it. And this one we did in 11 to 12 weeks, a tightly focused team, uh, and just went at it, uh, super slim process and got the job done and uh, the >>Results. Well, it's interesting. You have a lot of use cases. We gotta go down, do that face to face belly to belly, you know, body to body sales, BI dev scoping out, have workshops. Now this market here, Remar, they're all basically saying a call to arms more money's coming in. The problems are putting on the table. The workshop could be a lunch meeting, right. I mean, because Artis and there's a big set of problems to tackle. Yes. So I mean, I'm just oversimplifying, but that being said, there's a lot going on opportunity wise here. Yeah. That's not as slow maybe as the, the biz dev at, you know, coming in, this is a huge demand. It will be >>Explode. >>What's your take on the demand here, the problems that need to be solved and what you guys are gonna bring to bear for the problem. >>So now we have been focus mainly in vegetation management and forestry, but vegetation management can be applicable in utility as well. And we actually went there first had some struggle because it's quite detailed information that's needed. So we backed out a bit into vegetation in forestry again, but still it's a lot of application in, in, uh, utility and vegetation management in utility. Then we have a whole sustainability angle think about auditing of, uh, rogue harvesting or carbon offsetting in the future, even biodiversity, offsetting that could be used. >>And, and just to point out and give it a little extra context, all the keynotes, talk about space as a global climate solution, potentially the discoveries and or also the imagery they're gonna get. So you kind of got, you know, top down, bottoms up. If you wanna look at the world's bottom and space, kind of coming together, this is gonna open up new kinds of opportunities for you guys. What's the conversation like when you, when this is going on, you're like, oh yeah, let's go in. Like, what are you guys gonna do? What's the plan, uh, gonna hang around and ride that wave. >>I think it's all boils down to finding that use case that need to be sold because now we understand the satellite scene, they are there. We could, there is so many new satellites coming up already available. They can come up the cloud platform, AWS, it's great. We have all the capabilities needed. We have AI and ML models needed data science skills. Now it's finding the use cases together with clients and actually deliver on them one by >>One. It's interesting. I'd like to get your reaction to this Marcus two as well. What you guys are kind of, you have a lot bigger and, and, and bigger than some of the startups out there, but a startup world, they find their niches and they, the workflows become the intellectual property. So this, your techniques of layering almost see is an advantage out there. What's your guys view of that on intellectual property of the future, uh, open source is gonna run all the software. We know that. So software's no going open source scale and integration. And then new kinds of ways are new methods. I won't say for just patents, but like just for intellectual property, defen differentiation. How do you guys see this? As you look at this new frontier of intellectual property? >>That's, it's a difficult question. I think it's, uh, there's a lot of potential. If you look at open innovation and how you can build some IP, which you can out license, and some you utilize yourself, then you can build like a layer business model on top. So you can find different channels. Some markets we will not go for. Maybe some of our models actually could be used by others where we won't go. Uh, so we want to build some IP, but I think we also want to be able to release some of the things we do >>Open >>Works. Yeah. Because it's also builds presence. It it's >>Community. >>Yeah, exactly. Because this, this problem is really hard because it's a global thing. And, and it's imagine if, if you have a couple of million acres of forest and you just don't go out walking and trying to check what's going on because it's, you know, >>That's manuals hard. Yeah. It's impossible. >>So you need this to scale. Uh, and, and it's a hard problem. So I think you need to build a community. Yeah. Because this is, it's a living organism that we're trying to monitor. If you talk about visitation of forest, it's, it's changing throughout the year. So if you look at spring and then you look at summer and you look at winter, it's completely different. What you see. Yeah. Yeah. So >>It's, it's interesting. And so, you know, I wonder if, you know, you see some of these crowdsourcing models around participation, you know, small little help, but that doesn't solve the big puzzle. Um, but you have open source concepts. Uh, we had Anna on earlier, she's from the Amazon sustainability data project. Yeah, exactly. And then just like open up the data. So the data party for her. So in a way there's more innovation coming, potentially. If you can get that thing going, right. Get the projects going. Exactly. >>And all this, actually our work is started because of that. Yes, exactly. So European space agency, they decided to hand out this compar program and the, the Sentinel satellites central one and two, which we have been working with, they are freely available. It started back in 2016, I think. Yeah. Uh, and because of that, that's why we have this work done during several years, without that data freely available, it wouldn't have happened. Yeah. I'm, I'm >>Pretty sure. Well, what's next for you guys? Tell, tell me what's happening. Here's the update put a plug in for the, for the group. What are you working on now? What's uh, what are you guys looking to accomplish? Take a minute to put a plug in for the opportunity. >>I would say scaling this scaling, moving outside. Sweden. Of course we see our model that they work in in us. We have tried them in Canada. We see that we work, we need to scale and do field validation in different regions. And then I would say go to the sustainability area. This goes there, there is a lot of great >>Potential international too is huge. >>Yeah. One area. I think that is really interesting is the combination of understanding the, like the carbon sink and the sequestration and trying to measure that. Uh, but also on top of that, trying to classify certain Keystone species habitats to understand if they have any space to live and how can we help that to sort of grow back again, uh, understanding the history of the, sort of the force. You have some date online, but trying to map out how much of, of this has been turned into agricultural fields, for example, how much, how much of the real old forest we have left that is really biodiverse? How much is just eight years young to understand that picture? How can we sort of move back towards that blueprint? We probably need to, yeah. And how can we digitize and change forestry and the more business models around that because you, you can do it in a different way, or you can do both some harvesting, but also, yeah, not sort of ruining the >>Whole process. They can be more efficient. You make it more productive, save some capital, reinvest it in better ways >>And you have robotics and that's not maybe something that we are not so active in, but I mean, starting to look at how can autonomy help forestry, uh, inventory damages flying over using drones and satellites. Uh, you have people looking into autonomous harvesting of trees, which is kind of insane as well, because they're pretty big <laugh> but this is also happening. Yeah. So I mean, what we're seeing here is basically, >>I mean, we, I made a story multiple times called on sale drone. One of my favorite stories, the drones that are just like getting Bob around in the ocean and they're getting great telemetry data, cuz they're indestructible, you know, they can just bounce around and then they just transmit data. Exactly. You guys are creating a opportunity. Some will say problem, but by opening up data, you're actually exposing opportunities that never have been seen before because you're like, it's that scene where that movie, Jody frost, a contact where open up one little piece of information. And now you're seeing a bunch of new information. You know, you look at this large scale data, that's gonna open up new opportunities to solve problems that were never seen before. Exactly. You don't, you can't automate what you can't see. No. Right. That's the thing. So no, we >>Haven't even thought that these problems can be solved. It's basically, this is how the world works now. Because before, when you did remote sensing, you need to be out there. You need to fly with a helicopter or you put your boots on out and go out. Now you don't need that anymore. Yeah. Which opened up that you could be, >>You can move your creativity in another problem. Now you open up another problem space. So again, I like the problem solving vibe of the, it's not like, oh, catastrophic. Well, well, well the earth is on a catastrophic trajectory. It's like, oh, we'll agree to that. But it's not done deal yet. <laugh> I got plenty of time. Right. So like the let's get these problems on the table. Yeah. Yeah. And I think this is, this is the new method. Well, thanks so much for coming on the queue. Really appreciate the conversation. Thanks a lot. Love it. Opening up new world opportunities, challenges. There's always opportunities. When you have challenges, you guys are in the middle of it. Thanks for coming on. I appreciate it. Thank you. Thanks guys. Okay. Cap Gemini in the cube part of cap Gemini. Um, so Getty part of cap Gemini here in the cube. I'm John furrier, the host we're right back with more after this short break.

(upbeat music playing) >> Welcome to theCUBE's coverage of Couchbase ConnectONLINE Mary Roth, VP of Engineering Operations with Couchbase is here for Couchbase ConnectONLINE. Mary. Great to see you. Thanks for coming on remotely for this segment. >> Thank you very much. It's great to be here. >> Love the fire in the background, a little fireside chat here, kind of happening, but I want to get into it because, Engineering and Operations with the pandemic has really kind of shown that, engineers and developers have been good, working remotely for a while, but for the most part it's impacted companies in general, across the organizations. How did the Couchbase engineering team adapt to the remote work? >> Great question. And I actually think the Couchbase team responded very well to this new model of working imposed by the pandemic. And I have a unique perspective on the Couchbase journey. I joined in February, 2020 after 20 plus years at IBM, which had embraced a hybrid, in-office remote work model many years earlier. So in my IBM career, I live four minutes away from my research lab in Almaden Valley, but IBM is a global company with headquarters on the East Coast, and so throughout my career, I often found myself on phone calls with people around the globe at 5:00 AM in the morning, I quickly learned and quickly adapted to a hybrid model. I'd go into the office to collaborate and have in-person meetings when needed. But if I was on the phone at 5:00 AM in the morning, I didn't feel the need to get up at 4:30 AM to go in. I just worked from home and I discovered I could be more productive there, doing think time work, and I really only needed the in-person time for collaboration. This hybrid model allowed me to have a great career at IBM and raise my two daughters at the same time. So when I joined Couchbase, I joined a company that was all about being in-person and instead of a four minute commute, it was going to be an hour or more commute for me each way. This was going to be a really big transition for me, but I was excited enough by Couchbase and what it offered, that I decided to give it a try. Well, that was February, 2020. I showed up early in the morning on March 10th, 2020 for an early morning meeting in-person only to learn that I was one of the only few people that didn't get the memo. We were switching to a remote working model. And so over the last year, I have had the ability to watch Couchbase and other companies pivot to make this remote working model possible and not only possible, but effective. And I'm really happy to see the results. A remote work model does have its challenges, that's for sure, but it also has its benefits, better work-life balance and more time to interact with family members during the day and more quiet time just to think. We just did a retrospective on a major product release, Couchbase server 7.0, that we did over the past 18 months. And one of the major insights by the leadership team is that working from home actually made people more effective. I don't think a full remote model is the right approach going forward, but a hybrid model that IBM adopted many years ago and that I was able to participate in for most of my career, I believe is a healthier and more productive approach. >> Well, great story. I love the come back and now you take leverage of all the best practices from the IBM days, but how did they, your team and the Couchbase engineering team react? And were there any best practices or key learnings that you guys pulled out of that? >> The initial reaction was not good. I mean, as I mentioned, it was a culture based on in-person, people had to be in in-person meetings. So it took a while to get used to it, but there was a forcing function, right? We had to work remotely. That was the only option. And so people made it work. I think the advancement of virtual meeting technology really helps a lot. Over earlier days in my career where I had just bad phone connections, that was very difficult. But with the virtual meetings that you have, where you can actually see people and interact, I think is really quite helpful. And probably the key. >> What's the DNA of the company there? I mean, every company's got the DNA, Intel's Moore's Law, and what's the engineering culture at Couchbase like, if you could describe it. >> The engineering culture at Couchbase is very familiar to me. We are at our heart, a database company, and I grew up in the database world, which has a very unique culture based on two values, merit and mentorship. And we also focus on something that I like to call growing the next generation. Now database technology started in the late sixties, early seventies, with a few key players and institutions. These key players were extremely bright and they tackled and solved really hard problems with elegant solutions, long before anybody knew they were going to be necessary. Now, those original key players, people like Jim Gray, Bruce Lindsay, Don Chamberlin, Pat Selinger, David Dewitt, Michael Stonebraker. They just love solving hard problems. And they wanted to share that elegance with a new generation. And so they really focused on growing the next generation of leaders, which became the Mike Carey's and the Mohan's and the Lagerhaus's of the world. And that culture grew over multiple generations with the previous generation cultivating, challenging, and advocating for the next, I was really lucky to grow up in that culture. And I've advanced my career as a result, as being part of it. The reason I joined Couchbase is because I see that culture alive and well here. Our two fundamental values on the engineering side, are merit and mentorship. >> One of the things I want to get your thoughts on, on the database questions. I remember, back in the old glory days, you mentioned some of those luminaries, you know, there wasn't many database geeks out there, there was kind of a small community, now, as databases are everywhere. So you see, there's no one database that has rule in the world, but you starting to see a pattern of database, kinds of things are emerging, more databases than ever before, they are on the internet, they are on the cloud, there are none the edge. It's essentially, we're living in a large distributed computing environment. So now it's cool to be in databases because they're everywhere. (laughing) So, I mean, this is kind of where we are at. What's your reaction to that? >> You're absolutely right. There used to be a few small vendors and a few key technologies and it's grown over the years, but the fundamental problems are the same, data integrity, performance and scalability in the face of distributed systems. Those were all the hard problems that those key leaders solved back in the sixties and seventies. They're not new problems. They're still there. And they did a lot of the fundamental work that you can apply and reapply in different scenarios and situations. >> That's pretty exciting. I love that. I love the different architectures that are emerging and allows for more creativity for application developers. And this becomes like the key thing we're seeing right now, driving the business and a big conversation here at the, at the event is the powering of these modern applications that need low latency. There's no more, not many spinning disks anymore. It's all in RAM, all these kinds of different memory, you got centralization, you got all kinds of new constructs. How do you make sense of it all? How do you talk to customers? What's the main core thing happening right now? If you had to describe it. >> Yeah, it depends on the type of customer you're talking to. We have focused primarily on the enterprise market and in that market, there are really fundamental issues. Information for these enterprises is key. It's their core asset that they have and they understand very well that they need to protect it and make it available more quickly. I started as a DBA at Morgan Stanley, back, right out of college. And at the time I think it was, it probably still is, but at the time it was the best run IT shop that I'd ever seen in my life. The fundamental problems that we had to solve to get information from one stock exchange to another, to get it to the SEC are the same problems that we're solving today. Back then we were working on mainframes and over high-speed Datacom links. Today, it's the same kind of problem. It's just the underlying infrastructure has changed. >> Yeah, the key, there has been a big supporter of women in tech. We've done thousands of interviews and why I got you. I want to ask you if you don't mind, career advice that you give women who are starting out in the field of engineering, computer science. What do you wish you knew when you started your career? And if you could be that person now, what would you say? >> Yeah, well, a lot of things I wish I knew then that I know now, but I think there are two key aspects to a successful career in engineering. I actually got started as a math major and the reason I became a math major is a little convoluted. As a girl, I was told we were bad at math. And so for some reason I decided that I had to major in it. That's actually how I got my start, but I've had a great career. And I think there are really two key aspects. First, is that it is a discipline in which respect is gained through merit. As I had mentioned earlier, engineers are notoriously detail-oriented and most are, perfectionists. They love elegant, well thought-out solutions and give respect when they see one. So understanding this can be a very important advantage if you're always prepared and you always bring your A-game to every debate, every presentation, every conversation, you have build up respect among your team, simply through merit. While that may mean that you need to be prepared to defend every point early on, say, in your graduate career or when you're starting, over time others will learn to trust your judgment and begin to intuitively follow your lead just by reputation. The reverse is also true. If you don't bring your A-game and you don't come prepared to debate, you will quickly lose respect. And that's particularly true if you're a woman. So if you don't know your stuff, don't engage in the debate until you do. >> That's awesome advice. >> That's... >> All right, continue. >> Thank you. So my second piece of advice that I wish I could give my younger self is to understand the roles of leaders and influencers in your career and the importance of choosing and purposely working with each. I like to break it down into three types of influencers, managers, mentors, and advocates. So that first group are the people in your management chain. It's your first line manager, your director, your VP, et cetera. Their role in your career is to help you measure short-term success. And particularly with how that success aligns with their goals and the company's goals. But it's important to understand that they are not your mentors and they may not have a direct interest in your long-term career success. I like to think of them as, say, you're sixth grade math teacher. You know, you getting an A in the class and advancing to seventh grade. They own you for that. But whether you get that basketball scholarship to college or getting to Harvard or become a CEO, they have very little influence over that. So a mentor is someone who does have a shared interest in your long-term success, maybe by your relationship with him or her, or because by helping you shape your career and achieve your own success, you help advance their goals. Whether it be the company success or helping more women achieve leadership positions or getting more kids into college on a basketball scholarship, whatever it is, they have some long-term goal that aligns with helping you with your career. And they give great advice. But that mentor is not enough because they're often outside the sphere of influence in your current position. And while they can offer great advice and coaching, they may not be able to help you directly advance. That's the role of the third type of influencer. Somebody that I call an advocate. An advocate is someone that's in a position to directly influence your advancement and champion you and your capabilities to others. They are in influential positions and others place great value in their opinions. Advocates stay with you throughout your career, and they'll continue to support you and promote you wherever you are and wherever they are, whether that's the same organization or not. They're the ones who, when a leadership position opens up will say, I think Mary's the right person to take on that challenge, or we need to move in a new direction, I think Mary's the right person to lead that effort. Now advocates are the most important people to identify early on and often in your career. And they're often the most overlooked. People early on often pay too much attention and rely on their management chain for advancement. Managers change on a dime, but mentors and advocates are there for you for the long haul. And that's one of the unique things about the database culture. Those set of advocates were just there already because they had focused on building the next generation. So I consider, you know, Mike Carey as my father and Mike Stonebraker as my grandfather, and Jim Gray as my great-grandfather and they're always there to advocate for me. >> That's like a schema and a database. You got to have it all right there, kind of teed up. Beautiful. (laughing) Great advice. >> Exactly. >> Thank you for that. That was really a masterclass. And that's going to be great advice for folks, really trying to figure out how to play the cards they have and the situation, and to double down or move and find other opportunities. So great stuff there. I do have to ask you Mary, thanks for coming on the technical side and the product side. Couchbase Capella was launched in conjunction with the event. What is the bottom line for that as, as an Operations and Engineering, built the products and rolled it out. What's the main top line message for about that product? >> Yeah. Well, we're very excited about the release of Capella and what it brings to the table is that it's a fully managed and automated database cloud offering so that customers can focus on development and building and improving their applications and reducing the time to market without having to worry about the hard problems underneath, and the operational database management efforts that come with it. As I mentioned earlier, I started my career as a DBA and it was one of the most sought after and highly paid positions in IT because operating a database required so much work. So with Capella, what we're seeing is, taking that job away from me. I'm not going to be able to apply for a DBA tomorrow. >> That's great stuff. Well, great. Thanks for coming. I really appreciate it. Congratulations on the company and the public offering this past summer in July and thanks for that great commentary and insight on theCUBE here. Thank you. >> Thank you very much. >> Okay. Mary Roth, VP of Engineering Operations at Couchbase part of Couchbase ConnectONLINE. I'm John Furrier, host of theCUBE. Thanks for watching. (upbeat music playing)