(upbeat jazz music) >> From our studios, in the heart of Silicon Valley, Palo Alta, California. This is a Cube Conversation. >> Hi, welcome to the Cube Studio for another Cube Conversation where we go in-depth with thought leaders driving business outcomes with technology. I'm your host Peter Buriss. As enterprise is look to take advantage of new classes of applications like AI and others that make possible this notion of a data first or data driven enterprise in a digital business world. They absolutely have to consider what they need to do with their stored resources to modernize them to make possible new types of performance today, but also sustain and keep open options for how they use data in the future. To have that conversation we're here with David Floyer, CTO and co-founder of Wikibon. David welcome to the conversation. >> Thank you. >> So David you've been looking at this notion of modern storage architectures for 10 years now. >> Yeah. >> And you've been relatively prescient in understanding what's gonna happen. You were one of the first guys to predict well in advance of everybody else that the crossover between flash and HDD was gonna happen sooner rather than later. So I'm not going to spend a lot of time quizzing you. What do you see as a modern storage architecture? Let's, just let it rip. >> Okay well let's start with one simple observation. The days of standalone systems for data have gone we're in a software defined world and you wanna be able to run those data architectures anywhere where the data is. And that means in your data center where it was created or in the cloud or in a public cloud or at the edge. You want to be able to be flexible enough to be able to do all of the data services where the best place is and that means everything has to be software driven. >> Software defined is the first proposition of modern data storage facility? >> Absolutely. >> Second. >> So the second thing is that there are different types of technology. You have the very fastest storage which is in the in the DIRUM itself. You have NVDIMM which is the next one down from that expensive but a lot cheaper than the DIMM. And then you have different sorts of flash. You have the high performance flash and you have the 3D flash, you know as many layers as you can which is much cheaper flash and then at the bottom you have HDD and even tape as storage devices. So how. The key question is how do you manage that sort of environment. >> Where do we start because it still sounds like we still have a storage hierarchy. >> Absolutely. >> And it still sounds like that hierarchy is defined largely in terms of access speeds >> Yeap. >> And price points. >> Price points. Yes. >> Those are the two Mason and bandwidth and latency as well are within that. >> which are tied into that? >> which are tied into those. Yes. So what you, if you're gonna have this everywhere and you need services everywhere what you have to have is an architecture which takes away all of that complexity, so that you, all you see from an application point of view is data and how it gets there and how is put away and how it's stored and how it's protected that's under the covers. So the first thing is you need a virtualization of that data layer. >> The physical layer? >> The virtualization of that physical layer. >> Right right. >> Yes. And secondly you need that physical layer to extend to all the places that may be using this data. You don't wanna be constrained to this data set lives here. You want to be able to say Okay, I wanna move this piece of programming to the data as quickly as I can, that's much much faster than moving the data to the processing. So I want to be able to know where all the data is for this particular dataset or file or whatever it is, where they all are, how they connect together, what the latency is between everything. I wanna understand that architecture and I want to virtualize view of that across that whole the nodes that make up my hybrid cloud. >> So let me be clear here so, so we are going to use a software defined infrastructure >> Yeah. that allows us to place the physical devices that have the right cost performance characteristics where they need to be based on the physical realities of latency power availability, hardening, et cetera. >> And the network >> And the network. But we wanna mask that complexity from the application, application developer and application administrator. >> Yes. >> And software defined helps do that, but doesn't completely do it. >> No. Well you want services which say >> Exactly, so their services on top of all that. >> On top of all that. >> Absolutely. >> That are recognizable by the developer, by the business person, by the administrator, as they think about how they use data towards those outcomes not use storage or user device but use the data. >> Data to reach application outcomes. That's absolutely right. And that's what I call the data plane which is a series of services which enable that to happen and driven by the application requirements themselves. >> So we've looked at this and some of the services include end end compression, duplication, >> Duplication. backup restore, security, data protection. >> Protection. Yeah. So that's kind of, that's kind of the services that now the enterprise buyer needs to think about. >> Yes. >> So that those services can be applied by policy. >> Yes. >> Wherever they're required based on the utilization of the data >> Correct. >> Where the event takes place. >> And then you still have at the bottom of that you have the different types of devices. You still have you still won't >> A lot of hamsters making stuff work. >> You still want hard disk for example they're not disappearing, but if you're gonna use hard disks then you want to use it in the right way for using a hard disk. You wanna give it large box. You want to have it going sequentially in and out all the time. >> So the storage administration and the physical schema and everything else is still important in all these? >> Absolutely. But it's less important, less a centerpiece of the buying decision. >> Correct. >> Increasingly it's how well does this stuff prove support the services that the business is using to achieve your outcomes. >> And you want to use costs the lowest cost that you can and they'll be many different options open, more more options open. But the automation of that is absolutely key and that automation from a vendor point of view one of the key things they have to do is to be able to learn from the usage by their customers, across as broad a number of customers as they can. Learn what works or doesn't work, learn so that they can put automation into their own software their own software service. >> So it sounds like we talking four things. We got software defined, still have a storage hierarchy defined by cost and performance, but with mainly semiconductor stuff. We've got great data services that are relevant to the business and automation that mask the complexity from everything. >> And a lot of the artificial AI there is, automated >> Running things. Fantastic. David Floyer, talking about modern storage architectures. Once again thanks for joining us on the Cube Conversation. And I'm your host Peter Burris. See you next time. (jazz music)

(upbeat music) >> From our studios, in the heart of Silicon Valley, Palo Alto, California. This, is a CUBE conversation. >> Hi, and welcome to this special CUBE conversation. I'm Stu Miniman coming from our Boston area studio, and joining me for this special discussion of hybrid cloud monetization innovation white space, I have James Kobielus, who is our lead analyst out of the DC area. And also have David Floyer, who is the author of Wikibon's 'Hybrid Cloud Topologies' coming to us from San Francisco. Gentlemen, thank you so much for joining us. >> Happy to be here. >> You're welcome. Alright, so we've been talking about hybrid cloud quite a bit. And the reason we're doing that is if you look here in 2019, public cloud we think we understand it. It's well defined, we've talked about it, we can talk about the winners and losers, we can talk about innovation and growth. There's a lot of money there. Couple of years ago we spent a lot of time looking at private cloud. We put out research, what we call 'true private cloud', and the reason we called it that is because how do we differentiate it from virtualization? Things like the operating model, how we buy it, how we consume it, how we management. All is different than the traditional data center. When you talk about hybrid cloud, it's interesting. When you think back at the early days, it was well I take public, I take private, I put 'em together and I have hybrid cloud. But, is there much more than just selling those pieces? And earlier this year, David Floyer put out the hybrid cloud taxonomy, really put together some of the planes that we should be examining, as well as the spectrum of the offerings. Today we're going to talk about some of the opportunities to really up-level and where there's opportunities for customers to get a lot of value, and therefore the ecosystem will also be able to get some revenue and monetize that. But, David, to kick things off, if you could just give us, kind of the primary thesis of that hybrid cloud taxonomy for those that haven't seen it before. >> Okay so, we've created the taxonomy, which if you imagine it going from left to right, is multi-cloud, and then loosely coupled hybrid cloud, tightly coupled hybrid cloud, true distributed hybrid cloud, and autonomous standalone clouds. So those are the five labels that we've given to them. And, if you think about those five labels, there are four characteristics, which increase from left to right. State, for example, the autonomous standalone cloud is all about state. It's about the state of a IoT, or a moving car, or whatever it is. Integration, the level of integration, automation, and hybrid applications. So those are the four levels which change, and then covering those, we have the concept of planes. So we're looking at different types of planes, network planes, data planes, control planes, and there are other planes as well. And looking at a functionality that's in those planes, which has to increase the further to the right you go. >> Alright, thank you, David. And there's a lot nuance and complexity in a lot of areas to kind of dig in. But before we go into specifics there, can hybrid cloud be more than just a composite of the various pieces? You know, where's their innovation? Where's their white space? Where is this going to be more than just say the world of the past where we talked about multi-vendor? >> Well, I think the way to answer that is to think about what is the most important characteristic of data centers, characters to computing? And that is, what is different now is data. Data is spread everywhere. You have data at the edge. You have data in your own data centers. You have data in the clouds, you have data in SAS clouds. Data is distributed. If you wanted maximize the value of that data, then you need services, not that just pull everything up to one cloud, that's one model. But the key disadvantage of that is it takes time, takes time and a lot of money to move all of that data up. So, a better model is to move your code and services to that data. And to do that, you need a hybrid cloud mechanisms to achieve that, you've got to be able to send that information across the network in some way. And you've got to be able to coordinate where and how you send the code and the services. >> Yeah. Well, David, we've been talking for a couple of years now. Data is really at the center of all of this discussion. You talk about cloud, we've talked about big data for years. I want to pull in Jim. So, Jim, data is your world, you're talking developers, and data scientists, and of course the giant wave of AI has data at that center. So, you've been look at writing a lot about the role that data and AI play in this hybrid cloud discussion. So, up-level us a bit to some of the apps and the data, as to how this fits to this overall discussion. >> Oh, yes yes. Well, AI of course rides on data. And really AI rides on entire pipeline and workflow of data, from sources through to data lakes, where the models are built and trained, to then the serving of the built-out models into downstream applications, which also have their own local data and so forth. So, we look at hybrid clouds they, and multi-clouds, they quite often bring a lot more complexity by their very nature into the whole AI development and operations pipeline. But there are, there's value to be gained from using distributed data for all manner of AI applications. The applications become more powerful because they can leverage more data, you can build more types of models to do more kinds of inferencing and so forth. So, when you look now at the multi-cloud, we have distributed data, distributed models, distributed workloads that are doing everything from natural language processing to face recognition and beyond. That's the power of AI. Now, in hybrid cloud environment, you need, like David said, these planes to enable all degree of integration. And one of the planes, is the data plane. And the data plane, at its very heart, involves moving the data where it needs to be for training the model, for doing validation of training models to make sure they continue to be fit for purpose and so forth. And much more of the training is happening at the edges now, because that's where the actual AI is living, because that's where the data lives and dies. So what you need to make that happen, that data plane needs to be highly versatile, increasingly needs to be able to work in more of a meshed multi-cloud environment and that's sort of the bleeding edge of Istio and all those other things that we're seeing coming into the mainstream of AI and data management in the multi-cloud. >> Yeah, I'm glad you brought edge into the discussion because often it's the, battle of public versus private cloud. And that's not really the discussion, it's about my applications, it's about my data, it's where things naturally going to live. We've done lots of interviews where you talk about just, you know, the natural laws of the cloud. There is, latency and the speed of light are still very important things. You know, David actually spent many years talking with you about these pieces and, the role as to what lives in my data center, what lives in the public cloud, what ends up the edge, where code goes, where data goes is a complex thing. But, David, you know I think we're going to spend most of our time talking about this data plane, help us peel the onion a little bit on this. One of the services that should be extracted from the individual platforms that we've looked at is data protection. Is that part of the data plane? Is it the main piece of the data plane? How does that and other services fit into this discussion of hybrid cloud? >> Uh yes, data protection is obviously a key component. And, I think a good way of thinking about it is that in most cases would be multiple data planes. You will want a data plane, for example, the helps you with high-speed record moving or high-speed small pieces of data moving around, which is maybe of transient use. The type of characteristics and network to support it, the protocols and the distributed management of that is going to be very very different from, for example, data that you need to get ready for an AI. Example where you're training something. So where bandwidth is much more important. So there will be, in my opinion, multiple data planes. There's a big opportunity here for vendors because you need to be able to run your storage services across all the different hybrid versions that you have. You need to be able to run that at the edge, you need to be able to run that in your local private cloud, and you'll also need to be able to run that in whatever other clouds, public clouds as well. So, a key characteristic then is all of this is going to be code. All of this is about moving those services. And if you think about the types of services that you want in that environment. If you want to write a hybrid application where you are having data in one place and compute in one place, and data somewhere else. You need to know the latency, for example, how far away in time is that data? Should I move the data here or should I move the code to the data? You need operational systems, you need... you need orchestration that will manage that for you. So, you need different horses for different courses, we'll need different data solutions for different types of application. Different ones for AI, different ones for transactional processing. For example, complex one like maybe you have a transactional system and you want to, at the same time, to do a large amount of fraud detection. That's a different type of application and different databases associated with that. If you're at the edge you're going to be using far more time series databases, state databases... Whereas you would be using traditional SQL databases for your systems of record. Does that help in explaining? >> It does quite a bit, David, and I would say to people, please check out Wikibon.com, you can see some of David's research, it brings back to mind just the discussion we had on software defined in the infrastructure space pulling the services away from just hardware and being independent, but that is a discussion, David, you've been having for decades. And I've been reading some of your stuff from even before I joined the team. So, it's great to see kind of what's the same and what's different as we build these out. Jim, the piece I heard from David is a lot of, you know, there's the database and there's all of these services that we have. But at the core of it, when I go back to that data, one of the things we've been grappling is companies, is how can I actually monetize that data and get value out of it? >> (Laughs) >> One of the things that we talked about, you know, big data was supposed to be that bit-flip from oh my god how do I deal with all that data to oh boy I've got all this data and I can do something with it. And... it had rather mixed results. So for AI, there's lots of companies out there, that'll help unlock the value of data. It's going to be the rocket-ship to drive things forward, AI's going to drive of this, so, it's a complex environment and there's lots of things that companies would have to spend, so you know, are they going to have to spend more money? Or can they actually make money when it comes to our data? Give us a little bit of an insight as to what you're seeing there. >> Well, monetizing the data, Stu, where AI and machine learning come into the picture, is that essentially these are statistical models that are derived from the data and provide monetizable value if deployed into working applications. So that's what the whole data science pipeline is all about. It's taking the source data, looking for the predictive variables, building models to incorporate those predictive variables to do, you know, face recognition, or natural language processing, etc, into models that are trained and deployed into working applications to do to inferencing. That's all the monetization train, as it were, for AI. And so, what we're seeing, what Wikibon is seeing, is that there has been, in the last several years, a growing niche in the industry of workflow tools, DevOps tools for the data science pipeline that handle all of those processes and enable teams of data scientists, and data engineers, and subject matter experts, and so on, to work together to really industrialize the process of extracting that value, building those models from the data and deploying into all manner of applications, including deploying these models, AI, over kubernetes and within containers and in serverless environments. This is happening. I mean, we're seeing all over the world and every industry enterprises setting up very much industrialized processes for incorporating data science into the very heart of application development. >> Jim, that's awesome. So I'll go back as I've heard Peter Buriss talk about, the thing that differentiates a company before and after they've gone through that digital transformation is how they can actually leverage that data, are you a data driven company? Is that something you can take advantage of inside what you're doing? So, we've only scratched the surface. Jim and David, really appreciate you talking about that. My call to action for people out there is if you go to Wikibon.com you're going to see the regular aim of research coming up for the team on this. We actually have regular conversation with the community and welcome your input. If you go to, excuse me, Crowdchat.net/actionitem you'll find the latest and you'll see, if you look on the right side, some of the previous ones. And, of course, our team is at lots of events. All the big cloud and infrastructure and software shows. Check out thecube.net for all of those. For Jim, David, I'm Stu, thanks so much for watching. Please reach out to us with any question and as always, thank you for watching theCUBE. (Jazzy music)

(digital music) >> From Yorktown Heights, New York It's theCUBE! Covering IBM Cloud Innovation Day. Brought to you by IBM. >> Hi, it's Wikibon's Peter Burris again. We're broadcasting on The Cube from IBM Innovation Day at the Thomas J Watson Research Laboratory in Yorktown Heights, New York. Have a number of great conversations, and we got a great one right now. Rob Thomas, who's the General Manager of IBM Analytics, welcome back to theCUBE. >> Thanks Peter, great to see you. Thanks for coming out here to the woods. >> Oh, well it's not that bad. I actually live not to far from here. Interesting Rob, I was driving up the Taconic Parkway and I realized I hadn't been on it in 40 years, so. >> Is that right? (laugh) >> Very exciting. So Rob let's talk IBM analytics and some of the changes that are taking place. Specifically, how are customers thinking about achieving their AI outcomes. What's that ladder look like? >> Yeah. We call it the AI ladder. Which is basically all the steps that a client has to take to get to get to an AI future, is the best way I would describe it. From how you collect data, to how you organize your data. How you analyze your data, start to put machine learning into motion. How you infuse your data, meaning you can take any insights, infuse it into other applications. Those are the basic building blocks of this laddered AI. 81 percent of clients that start to do something with AI, they realize their first issue is a data issue. They can't find the data, they don't have the data. The AI ladder's about taking care of the data problem so you can focus on where the value is, the AI pieces. >> So, AI is a pretty broad, hairy topic today. What are customers learning about AI? What kind of experience are they gaining? How is it sharpening their thoughts and their pencils, as they think about what kind of outcomes they want to achieve? >> You know, its... For some reason, it's a bit of a mystical topic, but to me AI is actually quite simple. I'd like to say AI is not magic. Some people think it's a magical black box. You just, you know, put a few inputs in, you sit around and magic happens. It's not that, it's real work, it's real computer science. It's about how do I put, you know, how do I build models? Put models into production? Most models, when they go into production, are not that good, so how do I continually train and retrain those models? Then the AI aspect is about how do I bring human features to that? How do I integrate that with natural language, or with speech recognition, or with image recognition. So, when you get under the covers, it's actually not that mystical. It's about basic building blocks that help you start to achieve business outcomes. >> It's got to be very practical, otherwise the business has a hard time ultimately adopting it, but you mentioned a number of different... I especially like the 'add the human features' to it of the natural language. It also suggests that the skill set of AI starts to evolve as companies mature up this ladder. How is that starting to change? >> That's still one of the biggest gaps, I would say. Skill sets around the modern languages of data science that lead to AI: Python, AR, Scala, as an example of a few. That's still a bit of a gap. Our focus has been how do we make tools that anybody can use. So if you've grown up doing SPSS or SaaS, something like that, how do you adopt those skills for the open world of data science? That can make a big difference. On the human features point, we've actually built applications to try to make that piece easy. Great example is with Royal Bank of Scotland where we've created a solution called Watson Assistant which is basically how do we arm their call center representatives to be much more intelligent and engaging with clients, predicting what clients may do. Those types of applications package up the human features and the components I talked about, makes it really easy to get AI into production. >> Now many years ago, the genius Turing, noted the notion of the Turing machine where you couldn't tell the difference between the human and a machine from an engagement standpoint. We're actually starting to see that happen in some important ways. You mentioned the call center. >> Yep. >> How are technologies and agency coming together? By that I mean, the rate at which businesses are actually applying AI to act as an agent for them in front of customers? >> I think it's slow. What I encourage clients to do is, you have to do a massive number of experiments. So don't talk to me about the one or two AI projects you're doing, I'm thinking like hundreds. I was with a bank last week in Japan, and they're comment was in the last year they've done a hundred different AI projects. These are not one year long projects with hundreds of people. It's like, let's do a bunch of small experiments. You have to be comfortable that probably half of your experiments are going to fail, that's okay. The goal is how do you increase your win rate. Do you learn from the ones that work, and from the ones that don't work, so that you can apply those. This is all, to me at this stage, is about experimentation. Any enterprise right now, has to be thinking in terms of hundreds of experiments, not one, not two or 'Hey, should we do that project?' Think in terms of hundreds of experiments. You're going to learn a lot when you do that. >> But as you said earlier, AI is not magic and it's grounded in something, and it's increasingly obvious that it's grounded in analytics. So what is the relationship between AI analytics, and what types of analytics are capable of creating value independent of AI? >> So if you think about how I kind of decomposed AI, talked about human features, I talked about, it kind of starts with a model, you train the model. The model is only as good as the data that you feed it. So, that assumes that one, that your data's not locked into a bunch of different silos. It assumes that your data is actually governed. You have a data catalog or that type of capability. If you have those basics in place, once you have a single instantiation of your data, it becomes very easy to train models, and you can find that the more that you feed it, the better the model's going to get, the better your business outcomes are going to get. That's our whole strategy around IBM Cloud Private for Data. Basically, one environment, a console for all your data, build a model here, train it in all your data, no matter where it is, it's pretty powerful. >> Let me pick up on that where it is, 'cause it's becoming increasingly obvious, at least to us and our clients, that the world is not going to move all the data over to a central location. The data is going to be increasingly distributed closer to the sources, closer to where the action is. How does AI and that notion of increasing distributed data going to work together for clients. >> So we've just released what's called IBM Data Virtualization this month, and it is a leapfrog in terms of data virtualization technology. So the idea is leave your data where ever it is, it could be in a data center, it could be on a different data center, it could be on an automobile if you're an automobile manufacturer. We can federate data from anywhere, take advantage of processing power on the edge. So we're breaking down that problem. Which is, the initial analytics problem was before I do this I've got to bring all my data to one place. It's not a good use of money. It's a lot of time and it's a lot of money. So we're saying leave your data where it is, we will virtualize your data from wherever it may be. >> That's really cool. What was it called again? >> IBM Data Virtualization and it's part of IBM Cloud Private for Data. It's a feature in that. >> Excellent, so one last question Rob. February's coming up, IBM Think San Francisco thirty plus thousand people, what kind of conversations do you anticipate having with you customers, your partners, as they try to learn, experiment, take away actions that they can take to achieve their outcomes? >> I want to have this AI experimentation discussion. I will be encouraging every client, let's talk about hundreds of experiments not 5. Let's talk about what we can get started on now. Technology's incredibly cheap to get started and do something, and it's all about rate and pace, and trying a bunch of things. That's what I'm going to be encouraging. The clients that you're going to see on stage there are the ones that have adopted this mentality in the last year and they've got some great successes to show. >> Rob Thomas, general manager IBM Analytics, thanks again for being on theCUBE. >> Thanks Peter. >> Once again this is Peter Buriss of Wikibon, from IBM Innovation Day, Thomas J Watson Research Center. We'll be back in a moment. (techno beat)

>> Narrator: Live from Las Vegas, it's theCUBE, covering Informatica World 2018. Brought to you by Informatica. >> Okay, welcome back, everyone. Live here in Las Vegas at the Venetian, this is Informatica World 2018, CUBE's exclusive coverage. It's our fourth year covering Informatica World, and boy, what a transition; it's been fun to watch. I'm John Furrier, the co-host of theCUBE, with Peter Burris, Head of Research for Wikibon, SiliconANGLE, and theCUBE. Our next guest is Sally Jenkins, Executive Vice President, Chief Marketing Officer at Informatica. Welcome back, good to see you. >> Thank you, John, it's nice to see you too. >> Very comfortable here, you guys having a great event, congratulations. It's crowded, but it doesn't feel crowded. A lot of sessions are going on. What's going on with the event? Give us some stats, you've got a lot of partners here. >> Yeah, so we are very happy to be back in Las Vegas, and we are taking this up a whole notch a bit, if you can notice. We've got close to 4,000 folks who saw the Opening General Session this morning. For the first time ever, we're live streaming, and sent out a note that we were live streaming to over 250,000 customers, so I'm real happy about that. Because, as you know, with the rebrand last year, it was all about getting our message out and upleveling our message, so we're really happy that our message is getting out there, with everything that came from General Session this morning, and then, tomorrow with Closing General Session. >> Just gets bigger every year, so congratulations. >> Thank you. >> Great to see that everything comes in. Of course, the products are just right in line. The timing couldn't have been better. Multi-cloud, everything's kind of clicking. GDPR over the top, little push there for all the international customers. But the big story that we see is the journeys that are happening. You guys have been on a journey as your own company, digital disruption, digital transformation. But there's multiple journeys. Can you just take us through the vision of how you guys see the journeys, and how does Informatica fit into the customers, 'cause your customers are also changing? >> Sally: Yes, that's right. >> Do you change your business model? Anil laid it out, customers have this journey. What's the four journies? >> Yes, that's a great question, John. So we have, of course, been customer-centric ourselves. We've adapted our journeys to accommodate the journeys that we know our customers are on. And this whole conference is centered around those four journeys, so hybrid cloud, next-gen analytics, 360 engagement, and data governance and compliance. So that's what we've heard our customers deal with day in and day out, in their data-centric initiatives, and so we wanted to encapsulate that into the entire conference. So that's what it's all about, and that's an extension of our messaging that we laid out last year. So you'll see that again and again and again in a consistent fashion. >> "Disrupt Intelligently", I saw the messaging. First of all, great artwork, great branding, a lot of the images; what does that mean? 'Cause you've got all kinds of great imagery, people on the move, mobile, data's involved, obviously, the center of it. >> Well, that and data is the critical foundation for what we call "Intelligent Disruptive". So disruption with a purpose is intelligent. And we believe, with our technology, that our customers can then unleash the power of their data to create what we call their next intelligent disruption. So we were very thoughtful about the choice of words there, 'cause disruption can be considered a negative, but we see it as very much a positive, and a way for customers to leapfrog the competition, and set the tone for their markets. >> This is an interesting concept. We were talking with a lot of the customers you've had on; we've had Toyota on, and they said, quote, these testimonials just kind of pop out, "We knew we had the data; we had all these problems "we hadn't connected, but we actually had the data "when they actually connected us, and said, "we could have foreseen this." >> Sally: That's right. >> So they were disrupted in a negative way, the fact that they were trying to connect, now they're set up. And then he used an example, once they got set up, that they didn't predict that all this inbound data from the cars were coming in. So again, that's a disruption, but now they've handled it. Is that kind of where you guys were kind of connecting the dots on the intelligent piece? >> Yeah, that's right, we're helping our customers understand what to do with the data, right? So they know the data exists, but we need to help them turn it into actionable insights that leads to their next disruption, and again and again and again with their different projects. And so those are the conversations that we've been having with our customers. Just helping them, we say, unleash the power of their data. The data's there, we need to make it useful and valuable to them. >> And competitive advantage, obviously, seeing data, ease of use as a competitive strategy. Now the Microsoft announcement was interesting, because you can see that you can take an on-prem dataset, go through the Azure portal in their console, which is very cloud-native, you know, press a few buttons, connect to Informatica's intelligent cloud service, and move data. >> Sally: That's right. >> I mean, it's not like there's someone behind the curtain; it's actually a working product. >> No, it's real, it's real and it's available for preview, and if you saw the keynote this morning, you heard from Scott Guthrie. He said this whole partnership between Informatica and Microsoft, and I quote, "A match made in heaven". So there's something real there. Microsoft and their customers see the value in partnering with us, so we were really pleased to announce that today. >> I'm going to check the Internet, but I think this might be the first iPaaS integration into Azure at this level. 'Cause it's pretty deep with these guys. So that's going to certainly set up hybrid cloud instantly. >> That's right, that's right. And scale, right, we're enterprise-scale to begin with, obviously, so is Microsoft. So it's a good partnership. >> Okay, from the branding piece, I got to ask you, you guys did the rebranding, what's your one-year review, if you have to give yourself a report card, check, check, check, straight As, perfect score? If you could go back and do- >> Well, I'd like to say that we were in the honor roll. And we measure ourselves based on what our customers tell us, so we were very deliberate in choosing a few areas of which we wanted to see progress, and that is, the first one is, were people aware that we're a cloud company? And I'm delighted to say that, yes, we've absolutely moved the needle on that, so they associate Informatica with cloud, as you know, we're the number one in enterprise cloud data management. That's what we kicked off last year. And so you'll see a continued investment around the globe in the brand. We believe that good brand health is what leaders do, in terms of setting the pace for their industry. And that's exactly what we're doing. So, one year into it, we feel really good. We did what we set out, and we delivered on what we said we were going to do. And if you all remember last year's part of the rebrand, as soon as we went external, then we needed to shift our focus back internally, and think about what does this mean to our employees, and how do we leverage the culture that we already had inside Informatica and build upon that? And that's exactly what we've been working on. So we rolled out a new set of values in January. To no surprise, they're called We-DATA. And DATA stands for Do Good, Act as One Team, Think Customer First, and Aspire for the Future. And so that's what we're doing right now, is rolling that out around the world to our employees. And that was based on employee feedback, as well. >> That's bottoms up, that's good organic listening. I got to talk about branding, 'cause this is something that we're seeing a lot of. We're seeing a lot of shifts going on. When you have these shifts you mentioned earlier, about getting a competitive advantage, a leg up on the competition, you guys had that same opportunity. Because the brand, pecking order of companies is going to change with these new waves coming. With data, certainly, so it's a huge opportunity. Do you guys talk about that when you're in the brand meetings, and you're talking about with the execs, the power of the brand, and building the brand? >> Sally: Absolutely. >> And what are some of the things you're focused on to help continue to build that brand? >> Well, I think where you're going with this is what's the financial impact or value that the brand has? And everybody, from our industry analysts, to the financial analysts, to our customers, partners, they put a value on the brand. So if you don't define who you are in the market, then you let everybody else define you, and then there's no value in that. So that's really what we set out to do last year, is we wanted to define who we were, and be proud of it, and take ownership of it. >> Put a stake in the ground. >> Yeah, and then continue to invest in that. So when I say we'll continue to invest in the brand, that is about our messaging, and making sure that we are very clear as to who we are, as I said, 'cause we're setting the pace for this industry. >> And the brand promise real quick, just to summarize, if you had to kind of sum up the bumper sticker for Informatica, Disrupt Intelligently, kind of add to that, what would be the brand promise to your customers? >> Yeah, so it's the Disruptive Power of Data. And then what falls out of that is Unleashing the Power of Data, right? So that's our brand promise to our customers, is that's what we were talking about earlier, that's exactly what we do for them with our technology, and how can we help them stay ahead of their competition? >> That's great, look at the trends too. Look at what GDPR's doing, and some of the block chain stuff that's kind of emerging, it's power to the people. People want to have control of the data. >> Sally: That's right, putting the control back in their hands. >> Great stuff, so thanks for coming on theCUBE. Appreciate it, great to see you, congratulations. >> Thanks, John. >> And great to have our fourth year, our fifth year with Anil, we saw him at Amazon re:Invent in 2014, so great to continue to watch you guys grow. It's been fun to watch. >> Great, good, well stay tuned, there's more to come for sure. >> Right, can't wait to hear. It's theCUBE live here at Informatica World, two days of coverage here. We're getting down to the second day. We've got more action coming; stay here with us. I'm John Furrier, Peter Buriss, we'll be back after this short break.

>> Announcer: Live from Madrid, Spain, it's The Cube covering HPE Discover Madrid 2017. Brought to you by: Hewlett Packard Enterprise. >> Welcome back to HPE Discover, 2017 in Madrid. This is The Cube, the leader in live tech coverage, my name is Dave Vellante, I'm here to rap with my co-host, Peter Burris. >> Hey, Dave. >> Dave: Good couple a days. >> Oh, you know what I just discovered. I discovered The Cube is the antidote to jet lag. (laughs) >> That's right, when you get interesting people on. >> Oh, man. >> It pumps you up. >> Totally. Just unbelievable, exciting and it's all framed by... Well let's start where we talked about yesterday, we proposed that increasing what we're seeing in the industry is the new model of computing being established by Amazon and then the other poll, where it was known, we know that it's not all gonna be one cloud, it's not all gonna be a central cloud model, or essentialize cloud model. There's gonna be other places where data's gonna need to be processed. >> Dave: Well, that's what we believe. >> That's what we believe, and... There's physics behind that statement. There's legal regulations about data residency, behind that statement. But, we didn't know who was gonna step up and lead that other side and it's nice to see this conference indicate that HPE is in a position to help demonstrate, or help show the industry how cloud truly can go from centralized down to the edge. >> Yeah, and I think as I said a number of times, the strategy's coming into focus, you could debate it. You could say, "well, splitting it up was the wrong thing to do. "They lost their supply chain." But, Meg's argument, and then Antonio's argument always was, "look, we're gonna be more focused, "it's gonna allow us to do "a better job for our customers. "Yes, we're gonna be service's lead." They didn't say this. "Our margines are gonna be lower, "you don't have software anymore, "but that's okay, we can learn how to make money at that." And you know, the old HPE went through a similar transition. Kinda, got out of the HPEX business and got out of building it's own OS, and relying more on Microsoft and Intel and it made a lot of money. In those days. >> Peter: It did well. >> Did very well. It didn't invest under the herd regime the way it could have or should have and that hurt and then it spun out and made a lot of missteps but... Meg, to her credit, didn't make a lot of missteps. There was the initial entrance into the public cloud, they pulled back fast, they failed fast on that, good. Yeah, maybe there was some organizational issues early on but in general, the acquisitions have been solid, the strategy... >> And well integrated. >> And well integrated, absolutely. >> Peter: They've gotten value out of 'em. >> The strategies has been... I think clear internally, it wasn't always clear externally but they stayed calm about that, they didn't freak out about that. Helped that the stock price was going up a little bit, 'cause it was pretty depressed for a while. >> And shareholders weren't incontestable like they were for many years. >> That's right, and so, that gave them a little bit of time to bring it all together... It's finally here and I think Meg is stepping down at absolutely the right time. >> Or at a... She's stepping down at a good time, she's leaving a company that is much stronger than it was when she took it over. >> And that's what you want, one of the things I'm personally proud of when I left IDC it was in really good shape when I left, it wasn't a mess that I handed to somebody else. Had a lot of messes and IDC that I turned around as you well know. So, I think, I feel as though the company's in good shape and good hands. And, again, I think the... I don't know if you're a stock analyst or if you're pounding the table saying "buy this stock." 'Cause it is a relatively low margin business and there's a lot of competition, there's knife fights out there, it's not a high growth business, but on the flip side, it's clean, it throws off a lot of cash, they got a decent balance sheet and the customers love 'em. >> And that's the most important thing, it's the customers. Look, I... Disclosure, I actually did a significant consulting stint, here at HPE, right around the time of the compact acquisition and I saw what happened and for many years, the senior manager and team of HPE behaved as though they presumed that scale was it's own reward. If we get bigger, we'll find efficiencies, we'll find opportunities. Just being big, is the objective and I think that they have wandered in the desert trying to find those opportunities, that were the consequence of just being big and they never materialized. >> They weren't there. >> They never... It was like mirages on the horizon, they never materialized and I think if there's anything to your point that Meg has successfully done, is she's gotten the company to say, "don't chase the mirages, chase the customer. "Let's come back to what made HPE great for so long." And the idea that, if we stay focused on the customer and focus on technology, we can put them together in unique and interesting ways that will bind us to what customers are doing. And if you take a look at this event and the new messaging, and the things that they're focusing on it feels like, to me, that HPE is no longer wandering in the desert. You and I are smart guys, we are... Typically we can look at a company and we can see whether or not they know what they're doing and when you said, "well, you know what. "Maybe they had it all figured out inside, "and the rest of us couldn't see it." No, that's not the case. It was not figured out inside and that's what we saw but under Meg, it has become increasingly more figured out and the consequence of that... And it's been very, very plan full. She first was figured out and then she told Wall Street and Wall Street was happy with the numbers, and then she figured out and she started talking to customers when customers were there and now she's figuring it out, she's telling a broader market place. >> Well, and when she stopped by- >> And Antonio's got a great big story to tell. >> And both of those guys stopped by to see us. Meg spent 10 minutes with us, we were chatting here on the open mics and she was very good. Meg, one on one situation, in a small crowd is phenomenal. I've always said that about Meg. Not the greatest presence on stage, not a super dynamic speaker, she's not a Steve Jobs, obviously nobody is, but... But, man, is she credible in a one on one situation. One of the things she said to us was, "Y'know, we kinda got lucky..." My words, "with Aruba, we bought him "because we thought we could compete with "Cisco better, we bought him obviously "because it was a great business, a growth business," and boom all of a sudden, this intelligent edge thing hit. You sprinkle in a little Dr. Tom Bradicich and boom, off you go and you've got not only a great business, you got something that is becoming increasingly strategic for organizations. Great example, I mean the nimble acquisition. We heard, yesterday, Bill Philbin talking about, "well, when we got nimble-" was it Bill Philbin, no it was somebody else today it was... Alain Andreoli. He said, "we picked up nimble 'cause it was a great "flash company, but then we saw this inside thing, "we said, wow, we can spread this thing "across our entire portfolio." That's where- >> And the example he gave was: in six months, it's not running on... >> On three par and then it's gonna run... His goal, he says, "I'm not committing to this, "but my goal is by the end of the next year "it's gonna be running across the entire "server and storage and networking line." That would be a major accomplishment. If in fact, we'll see how much of this stuff is actually impactful to the business, how much it can actually save money you know, anticipate failures, I don't know. We'll see, it's AI, it's a perfect application. You guys have written a lot on the Wikibon team about AI for ITOM. >> Oh yeah, look... >> Dave: And this is a good example. >> I'm not the kinda guy, as you know, that gets all excited about technology for technology's sake. I like thinking about technology and how it's gonna be applied, more problems are gonna be solved and so as we, in Wikibon, started running around and getting all excited about AI, my challenge to the guys was: Well, show me the two concrete cases, where it's gonna have a material business impact and one of the most important cases is, it's got a material business impact and how IT runs itself because you cannot... IT cannot reduce the number of people it's got and take on these increasingly complex application, problems, and portfolios unless they get a lot of help and the best, most likely source of that help is by bringing a lot of these new AI technologies that are capable of taking concrete, real time action in response to what's happening within the infrastructure and the applications at any given time. >> Yeah, now... Couple other things, just observations. Ana Pinczuk came on, great leader, woman in tech, big proponent of advancing women's causes, especially in tech. She had mixed feelings about Meg stepping down, obviously you have a woman leader, I thought her comments there were... Were quite interesting, but she said, "But I am up for the challenge "to continue the mission." Which leads me to Antonio. Antonio is outwardly a humble guy, he may have a big ego I don't know, he's been on The Cube a number of times, but he certainly doesn't come across as a guy who's looking to get credit. He's a quiet but very competent leader, he knows the business very well. Really interesting to see what his relationship- >> Peter: Homegrown. >> Homegrown, which is 22 years at HPE, technology background, not a U.S... Born individual, now living in the U.S. obviously. But, somebody with international experience which is always been an attribute that's valued at HPE. Gonna be interesting to see what his relationship is with Wall Street. Will he be sort of a quiet leader that lets the CFO take front and center, which would be fine. Or will he slowly sort of advance, he's not been sitting on the earnings calls. I'm interested to see how he handles it, or he may just say, "you know what, "I'm gonna go execute in the business "and let the results speak for themselves." So, I'm kind of curious as to how that all... All plays out. It's a big job, it's a big role as you pointed out with me the other day. Big role for him, big job for him. Serious opportunities to make a mark in the industry. >> Again, and you raise a really great point. Meg had a very good reputation on Wall Street, the knock on her when she came on, was she didn't know customers. Antonio's got a great reputation with customers, you're asking the question: is he gonna get to know Wall Street? A great CEO has to be able to take care of customers and owners He seems very... Look, this is a, this whole simplification of how they're gonna bring cloud technologies to where their data's gonna require is apparently, based on what we heard, in large part Antonio's brain child. He conceived it, he invested in it, he nurtured it, he took risks for it, he put some skin in the game and now it's coming to fruition, that's great, and he's got customers lining up behind it. We'll see, this is another place where we'll see, but I don't think that there's... There's no reason to suspect, just looking at Antonio's track record, why Wall Street would abandon him. On the contrary, there's reasons to suspect that he will also be able to develop that set of skills that Wall Street needs to do their job. But, clearly this is a guy that's gonna turn on a lot of customers. >> Yeah, and as I say, it's gonna be interesting to see what his relationship, like look at a guy like Frank Slootman, who had a great relationship with Wall Street, everybody loved him 'cause he just performed but he's a hard-driving, in your face kinda guy, who developed close relationships with the street. It's gonna be, as they say, I gotta watch that, to see how Antonio interacts with them. I think it's important to have a relationship with... >> Peter: With your ownership, yeah it usually is. >> And I think that's the one big question mark here is, where has his presence been there but so we'll watch and I'm confident he'll step up to that. Okay. Let's see, The Cube... Next week? Cube-con? >> Peter: Yeah. >> Next week in Austin. Right, so development. You'll see The Cube expanding way beyond it's original infrastructure route, so obviously HPE Discover, big infrastructure show. But we're at Amazon Reinvent this week, it's our big cloud show. We obviously... All the IBM shows are being consolidated into one show called Think. This year The Cube will be there. But CES is gonna be January, we were there last year, likely be there again. Cisco live is on the radar, we're gonna be at Cisco live I think both in Barcelona and most likely in the states this year, so that's another big thing. A lot of developer shows, Docckercon, Kubecon, working with the Linux Foundation, developers are really the lynch pin, developers in cloud. Really big areas of growth. IOT, some IOT conferences that we're gonna be doin' this year. Obviously, our big data heritage we still do a lot of work there, so. It's been an unbelievable year, I think a 125 shows for The Cube. TheCube.net, new website, our new clipper tool, you see the clips that come out, so. A lot of innovation comin' out of Siliconangle Media, check out Siliconangle.com. Peter, the work that your team is doing on the Wikibon side, Wikibon.com. Unbelievable amounts of research that you guys are crackin' out. Digital business, AI, AI for ITOM stuff that we talked about, we still do some stuff in infrastructure, true private cloud. >> New computing architectures, memory based computer architectures. >> So, fantastic work there and... Yeah, so we're looking forward to another great year. Thanks everybody for these last two days, thanks to the crew, great job. Everybody at home. We're out. Dave Vellante for Peter Buriss from Madrid. Thanks for watching. (upbeat music)

>> Narrator: Live from Silicon Valley, it's theCUBE, covering Google Cloud, Next 17. >> Hey, welcome back everyone. We're here live in the Palo Alto Studios, SiliconANGLE Media, is theCUBE's new 4400 square foot studio, here in our studio, this is our sports center. I'm here with Stu Miniman, analyst at Wikibon on the team. I was at the event all day today, drove down to Palo Alto to give us the latest in-person updates, as well as, for the past two days, Stu has been at the Analyst Summit, which is Google's first analyst summit, Google Cloud. And Stu, we're going to break down day one in the books. Certainly, people starting to get onto there. After-meetups, parties, dinners, and festivities. 10,000 people came to the Google Annual Cloud Next Conference. A lot of customer conversations, not a lot of technology announcements, Stu. But we got another day tomorrow. >> John, first of all, congrats on the studio here. I mean, it's really exciting. I remember the first time I met you in Palo Alto, there was the corner in ColoSpace-- >> Cloud Air. >> A couple towards down for fries, at the (mumbles) And look at this space. Gorgeous studio. Excited to be here. Happy to do a couple videos. And I'll be in here all day tomorrow, helping to break down. >> Well, Stu, first allows us to, one, do a lot more coverage. Obviously, Google Next, you saw, was literally a blockbuster, as Diane Greene said. People were around the block, lines to get in, mass hysteria, chaos. They really couldn't scale the event, which is Google's scale, they nailed the scale software, but scaling event, no room for theCUBE. But we're pumping out videos. We did, what? 13 today. We'll do a lot more tomorrow, and get more now. So you're going to be coming in as well. But also, we had on-the-ground, cause we had phone call-ins from Akash Agarwal from SAP. We had an exclusive video with Sam Yen, who was breaking down the SAP strategic announcement with Google Cloud. And of course, we have a post going on siliconangle.com. A lot of videos up on youtube.com/siliconangle. Great commentary. And really the goal was to continue our coverage, at SiliconANGLE, theCUBE, Wikibon, in the Cloud. Obviously, we've been covering the Cloud since it's really been around. I've been covering Google since it was founded. So we have a lot history, a lot of inside baseball, certainly here in Palo Alto, where Larry Page lives in the neighborhood, friends at Google Earth. So the utmost respect for Google. But really, I mean, come on. The story, you can't put lipstick on a pig. Amazon is crushing them. And there's just no debate about that. And people trying to put that out there, wrote a post this morning, to actually try to illustrate that point. You really can't compare Google Cloud to AWS, because it's just two different animals, Stu. And my point was, "Okay, you want to compare them? "Let's compare them." And we're well briefed on the Cloud players, and you guys have the studies coming out of Wikibon. So there it is. And my post pretty much sums up the truth, which is, Google's really serious about the enterprise. Their making steps, there's some holes, there's some potential fatal flaws in how they allow customers to park their data. They have some architectural differences. But Stu, it's really a different animal. I mean, it's apples and oranges in the Cloud. I don't think it's worthy complaining, because certainly Amazon has the lead. But you have Microsoft, you have Google, you have Oracle, IBM, SAP, they're all kind of in the cluster of this, I call "NASCAR Formation", where they're all kind of jocking around, some go ahead. And it really is a race to get the table stake features done. And really, truly be serious contender for the enterprise. So you can be serious about the enterprise, and say, "Hey, I'm serious about the enterprise." But to be serious winner and leader, are two different ball games. >> And a lot to kind of break down here, John. Because first of all, some of the (mumbles) challenges, absolutely, they scaled that event really big. And kudos to them, 10,000 people, a lot of these things came together last minute. They treated the press and analysts really well. We got to sit up front. They had some good sessions. You just tweeted out, Diane Greene, in the analyst session, and in the Q&A after, absolutely nailed it. I mean, she is an icon in the industry. She's brilliant, really impressive. And she's been pulling together a great team of people that understand the enterprise. But who is Google going after, and how do they compete against so of the other guys, is really interesting to parse. Because some people were saying in the keynote, "We heard more about G Suite "than we heard about some of the Cloud features." Some of that is because they're going to do the announcements tomorrow. And you keep hearing all this G Suite stuff, and it makes me think of Microsoft, not Amazon. It makes me think of Office 365. And we've been hearing out of Amazon recently, they're trying to go after some of those business productivity applications. They're trying to go there where Microsoft is embedded. We know everybody wants to go after companies like IBM and Oracle, and their applications. Because Google has some applications, but really, their strength is been on the data. The machine the AI stuff was really interesting. Dr. Fei-Fei Li from Stanford, really good piece in the keynote there, when they hired her not that long ago. The community really perked up, and is really interesting. And everybody seems to think that this could be the secret weapon for Google. I actually asked them like, in some of the one-on-ones, "Is this the entry point? "Are most people coming for this piece, "when it's around these data challenges in the analytics, "and coming to Google." And they're like, "Well, it's part of it. "But no, we have broad play." Everything from devices through G Suite. And last year, when they did the show, it was all the Cloud. And this year, it's kind of the full enterprise suite, that they're pulling in. So there's some of that sorting out the messaging, and how do you pull all of these pieces together? As you know, when you've got a portfolio, it's like, "Oh well, I got to have a customer for G Suite." And then when the customer's up there talking about G Suite for a while, it's like, "Wait, it's--" >> Wait a minute. Is this a software? >> "What's going on?" >> Is this a sash show? Is this a workplace productivity show? Or is this a Cloud show? Again, this is what my issue is. First of all, the insight is very clear. When you start seeing G Suite, that means that they've got something else that they are either hiding or waiting to announce. But the key though, that is the head customers. That was one important thing. I pointed out in my blog post. To me, when I'm looking for it's competitive wins, and I want to parse out the G Suite, because it's easy just to lay that on, Microsoft does it with 365 of Office, Oracle does it with their stuff. And it does kind of make the numbers fuzzy a little bit. But ultimately, where's the beef on infrastructure as a service, and platform as a service? >> And John, good customers out there, Disney, Colgate, SAP as a partner, HSBC, eBay, Home Depot, which was a big announcement with Pivotal, last year, and Verizon were there. So these are companies, we all know them. Dan Greene was joking, "Disney is going to bring their magic onto our magic. "And make that work." So real enterprise use cases. They seem to have some good push-around developers. They just acquired Kaggle, which is working in some of that space. >> Apogee. >> Yeah, Apogee-- >> I think Apogee's an API company, come on. What does that relate to? It has nothing to do with the enterprise. It's an API management solution. Okay, yes. I guess it fits the stack for Cloud-Native, and for developers. I get that. But this show has to nail the enterprise, Stu. >> And John, you remember back four years ago, when we went to the re:Invent show for the first time, and it was like, they're talking to all the developers, and they haven't gotten to the enterprise. And then they over-pivoted to enterprise. And I listen to the customers that were talking and keynote today, and I said, "You know, they're talking digital transformation, "but it's not like GE and Nike getting up on stage, "being like, "'We're going to be a software company, "'and we're hiring lots--'" >> John: Moving our data center over. >> They were pulling all of over stuff, and it's like, "Oh yeah, Google's a good partner. "And we're using them--" >> But to be fair, Stu. Let's be fair, for a second. First of all, let's break down the keynotes. And then we'll get to some of the things about being fair. And I think, one, people should be fair to Diane Greene, because I think that the press and the coverage of it, looking at the media coverage, is weak. And I'll tell you why it's weak. Cause everyone has the same story as, "Oh, Google's finally serious about Cloud. "That's old news. "Diane Greene from day one says "we're serious with the Cloud." That's not the story. The story is, can they be a serious contender? That's number one. On the keynote, one, customer traction, I saw that, the slide up there. Yeah, the G Suite in there, but at least they're talking customers. Number two, the SAP news was strategic for Google. SAP now has Google Cloud platform, I mean, Google Cloud support for HANA, and also the SAP Cloud platform. And three, the Chief Data Science from AIG pointed. To me, those were the three highlights of the keynote. Each one, thematically, represents at least a positive direction for Google, big time, which is, one, customer adoption, the customer focus. Two, partnerships with SAP, and they had Disney up there. And then three, the real game changer, which is, can they change the AI machine learning, TensorFlow has a ton of traction. Intel Xeon chips now are optimized with TensorFlow. This is Google. >> TensorFlow, Kubernetes, it's really interesting. And it's interesting, John, I think if the media listened to Eric Schmidt at the end, he was talking straight to them. He's like, "Look, bullet one. "17 years ago, I told Google that "this is where we need to go. "Bullet two, 30 billion dollars "I'm investing in infrastructure. "And yes, it's real, "cause I had to sign off on all of this money. And we've been all saying for a while, "Is this another beta from Google. "Is it serious? "There's no ad revenue, what is this?" And Diane Greene, in the Q&A afterwards, somebody talked about, "Perpetual beta seems to be Google." And she's like, "Look, I want to differentiate. "We are not the consumer business. "The consumer business might kill something. "They might change something. "We're positioning, "this a Cloud that the enterprise can build on. "We will not deprecate something. "We'll support today. "We'll support the old version. "We will support you going forward." Big push for channel, go-to-market service and support, because they understand that that-- >> Yeah, but that's weak. >> For those of us that used Google for years, understand that-- >> There's no support. >> "Where do I call for Google?" Come on, no. >> Yeah, but they're very weak on that. And we broke that down with Tom Kemp earlier, from Centrify, where Google's play is very weak on the sales and marketing side. Yeah, I get the service piece. But go to Diane Greene for a second, she is an incredible, savvy enterprise executive. She knows Cloud. She moved from server to virtualization. And now she can move virtualization to Cloud. That is her playbook. And I think she's well suited to do that. And I think anyone who rushes to judgment on her keynote, given the fail of the teleprompter, I think is a little bit overstepping their bounds on that. I think it's fair to say that, she knows what she's doing. But she can only go as fast as they can go. And that is, you can't like hope that you're further along. The reality is, it takes time. Security and data are the key points. On your point you just mentioned, that's interesting. Because now the war goes on. Okay, Kubernetes, the microservices, some of the things going on in the applications side, as trends like Serverless come on, Stu, where you're looking at the containerization trend that's now gone to Kubernetes. This is the battleground. This is the ground that we've been at Dockercon, we've been at Linux, CNCF has got huge traction, the Cloud Native Compute Foundation. This is key. Now, that being said. The marketplace never panned out, Stu. And I wanted to get your analysis on this, cause you cover this. Few years ago, the world was like, "Oh, I want to be like Facebook." We've heard, "the Uber of this, and the Airbnb of that." Here's the thing. Name one company that is the Facebook of their company. It's not happening. There is no other Facebook, and there is no other Google. So run like Google, is just a good idea in principle, horizontally scalable, having all the software. But no one is like Google. No one is like Facebook, in the enterprise. So I think that Google's got to downclock their messaging. I won't say dumb down, maybe I'll just say, slow it down a little bit for the enterprise, because they care about different things. They care more about SLA than pricing. They care more about data sovereignty than the most epic architecture for data. What's your analysis? >> John, some really good points there. So there's a lot of technology, where like, "This is really cool." And Google is the biggest of it. Remember that software-defined networking we spent years talking about? Well, the first big company we heard about was Google, and they got up of stage, "We're the largest SDN deployer in the world on that." And it's like, "Great. "So if you're the enterprise, "don't deploy SDN, go to somebody else "that can deliver it for you. "If that's Google, that's great." Dockercon, the first year they had, 2014, Google got up there, talked about how they were using containers, and containers, and they spin up and spin down. Two billion containers in a week. Now, nobody else needs to spin up two billion containers a week, and do that down. But they learned from that. They build Kubernetes-- >> Well, I think that's a good leadership position. But it's leadership position to show that you got the mojo, which again, this is again, what I like about Google's strategy is, they're going to play the technology card. I think that's a good card to play. But there are some just table stakes they got to nail. One is the certifications, the security, the data. But also, the sales motions. Going into the enterprise takes time. And our advice to Diane Greene was, "Don't screw the gold Google culture. "Keep that technology leadership. "And buy somebody, "buy a company that's got a full blown sales force." >> But John, one of the critiques of Google has always been, everything they create, they create like for Google, and it's too Googley. I talked to a couple of friends, that know about AWS for a while, and when they're trying to do Google, they're like, "Boy, this is a lot tougher. "It's not as easy as what we're doing." Google says that they want to do a lot of simplicity. You touched on pricing, it's like, "Oh, we're going to make pricing "so much easier than what Amazon's doing." Amazon Reserved Instances is something that I hear a lot of negative feedback in the community on, and Google's like, "It's much simpler." But when I've talked to some people that have been using it, it's like, "Well, generally it should be cheaper, "and it should be easier. "But it's not as predictable. "And therefore, it's not speaking to what "the CFO needs to have. "I can't be getting a rebate sometime down the road. "Based on some advanced math, "I need to know what I'm going to be getting, "and how I'm going to be using it." >> And that's a good point, Stu. And this comes down to the consumability of the Cloud. I think what Amazon has done well, and this came out of many interviews today, but it was highlighted by Val Bercovici, who pointed out that, Amazon has made their service consumable by the enterprise. I think that's important. Google needs to start thinking about how enterprises want to consume Cloud, and hit those points. The other thing that Val and I teased at, was kind of some new ground, and he coined the term, or used the term, maybe he coined it, I'm not sure, empathy. Enterprise empathy. Google has developer empathy, they understand the developer community. They're rock solid on open source. Obviously, their mojo's phenomenal on technology, AI, et cetera, TensorFlow, all that stuff's great. Empathy for the enterprise, not there. And I think that's something that they're going to have to work on. And again, that's just evolution. You mentioned Amazon, our first event, developer, developer, developer. Me and Pat Gelsinger once called it the developer Cloud. Now they're truly the enterprise Cloud. It took three years for Amazon to do that. So you just can't jump to a trajectory. There's a huge amount of diseconomies of scale, Stu, to try and just be an enterprise player overnight, because, "We're Google." That's just not going to fly. And whether it's sales motions, pricing and support, security, this is hard. >> And sorting out that go-to-market, is going to take years. You see a lot of the big SIs are there. PwC, everywhere at the show. Accenture, big push at the show. We saw that a year or two ago, at the Amazon show. I talked to some friends in the channel, and they're like, "Yeah, Google's still got work to do. "They're not there." Look, Amazon has work to do on the go-to-market, and Google is still a couple-- >> I mean, Amazon's not spring chicken here. They're quietly, slowly, ramming up. But they're not in a good position with their sales force, needs to be where they want to be. Let's talk about technology now. So tomorrow we're expecting to see a bunch of stuff. And one area that I'm super excited about with Google, is if they can have their identity identified, and solidified with the mind of the enterprise, make their product consumable, change or adjust or buy a sales force, that could go out and actually sell to the enterprise, that's going to be key. But you're going to hear some cool trends that I like. And if you look at the TensorFlow, and the relationship, Intel, we're going to see Intel on stage tomorrow, coming out during one of the keynotes. And you're going to start to see the Xeon chip come out. And now you're starting to see now, the silicon piece. And this has been a data center nuisance, Stu. As we talked about with James Hamilton at Amazon, which having a hardware being optimized for software, really is the key. And what Intel's doing with Xeon, and we talked to some other people today about it, is that the Cloud is like an operating system, it's a global computer, if you want look at that. It's a mainframe, the software mainframe, as it's been called. You want a diversity of chipsets, from two cores Atom to 72 cores Xeon. And have them being used in certain cases, whether it's programmable silicon, or whether it's GPUs, having these things in use case scenarios, where the chips can accelerate the software evolution, to me is going to be the key, state of the art innovation. I think if Intel continues to get that right, companies like Google are going to crush it. Now, Amazon, they do their own. So this is going to another interesting dynamic. >> Yeah, it was actually one of the differentiating points Google's saying, is like, "Hey, you can get the Intel Skylake chip, "on Google Cloud, "probably six months before you're going to be able to "just call up your favorite OEM of choice, "and get that in there." And it's an interesting move. Because we've been covering for years, John, Google does a ton of servers. And they don't just do Intel, they've been heavily involved in the openPOWER movement, they're looking at alternatives, they're looking at low power, they're looking at from their device standpoint. They understand how to develop to all these pieces. They actually gave to the influencers, the press, the analysts, just like at Amazon, we all walked home with Echo Dot, everybody's walking home with the Google Homes. >> John: Did you get one? >> I did get one, disclaimer. Yeah, I got one. I'll be playing with it home. I figured I could have Alexa and Google talking to each other. >> Is it an evaluation unit? You have to give it back, or do you get to keep? >> No, I'm pretty sure they just let us keep that. >> John: Tainted. >> But what I'm interested to see, John, is we talk like Serverless, so I saw a ton of companies that were playing with Alexa at re:Invent, and they've been creating tons of skills. Lambda currently has the leadership out there. Google leverages Serverless in a lot of their architecture, it's what drives a lot of their analytics on the inside. Coming into the show, Google Cloud Functions is alpha. So we expect them to move that forward, but we will see with the announcements come tomorrow. But you would think if they're, try to stay that leadership though there, I actually got a statement from one of the guys that work on the Serverless, and Google believes that for functions, that whole Serverless, to really go where it needs to be, it needs to be open. Google isn't open sourcing anything this week, as far as I know. But they want to be able to move forward-- >> And they're doing great at open source. And I think one of the things, that not to rush to judgment on Google, and no one should, by the way. I mean, certainly, we put out our analysis, and we stick by that, because we know the enterprise pretty well, very well actually. So the thing that I like is that there are new use cases coming out. And we had someone who came on theCUBE here, Tarun Thakur, who's with Datos, datos.io. They're reimagining data backup and recovery in the Cloud. And when you factor in IoT, this is a paradigm shift. So I think we're going to see use cases, and this is a Google opportunity, where they can actually move the goal post a bit on the market, by enabling these no-use cases, whether it's something as, what might seem pedestrian, like backup and recovery, reimagining that is huge. That's going to take impact as the data domains of the world, and what not, that (mumbles). These new uses cases are going to evolve. And so I'm excited by that. But the key thing that came out of this, Stu, and this is where I want to get your reaction on is, Multicloud. Clearly the messaging in the industry, over the course of events that we've been covering, and highlighted today on Google Next is, Multicloud is the world we are living in. Now, you can argue that we're all in Amazon's world, but as we start developing, you're starting to see the emergence of Cloud services providers. Cloud services providers are going to have some tiering, certainly the big ones, and then you're going to have secondary partner like service providers. And Google putting G Suite in the mix, and Office 365 from Microsoft, and Oracle put in their apps in their Clouds stuff, highlights that the SaaS market is going to be very relevant. If that's the case, then why aren't we putting Salesforce in there, Adobe? They all got Clouds too. So if you believe that there's going to be specialism around Clouds, that opens up the notion that there'll be a series of Multicloud architectures. So, Stu-- >> Stu: Yeah so, I mean, John, first of all-- >> BS? Real? I mean what's going on? >> Cloud is this big broad term. From Wikibon's research standpoint, SaaS, today, is two-thirds of the public Cloud market. We spend a lot of time talking-- >> In revenue? >> In revenue. Revenue standpoint. So, absolutely, Salesforce, Oracle, Infor, Microsoft, all up there, big dollars. If we look at the much smaller part of the world, that infrastructures a service, that's where we're spending a lot of time-- >> And platforms a service, which Gartner kind of bundles in, that's how Gartner looks at it. >> It's interesting. This year, we're saying PaaS as a category goes away. It's either SaaS plus, I'm sorry, it's SaaS minus, or infrastructure plus. So look at what Salesforce did with Heroku. Look at what company service now are doing. Yes, there are solutions-- >> Why is PaaS going away? What's the thesis? What's the premise of that for Wikibon research? >> If we look at what PaaS, the idea was it tied to languages, things like portability. There are other tools and solutions that are going to be able to help there. Look at, Docker came out of a PaaS company, DockCloud. There's a really good article from one of the Docker guys talking about the history of this, and you and I are going to be at Dockercon. John, from what I hear, we're going to spending a lot of time talking about Kubernetes, at Dockercon. OpenStack Summit is going to be talking a lot about-- >> By the way, Kubernetes originated at Google. Another cool thing from Google. >> All right, so the PaaS as a market, even if you talk to the Cloud Foundry people, the OpenShift people. The term we got, had a year ago was PaaS is Passe, the nice piffy line. So it really feeds into, because, just some of these categorizations are what we, as industry watchers have a put in there, when you talk to Google, it's like, "Well, why are they talking about G Suite, "and Google Cloud, and even some of their pieces?" They're like, "Well, this is our bundle "that we put together." When you talk to Microsoft, and talk about Cloud, it's like, "Oh, well." They're including Skype in that. They're including Office 365. I'm like, "Well, that's our productivity. "That's a part of our overall solutions." Amazon, even when you talk to Amazon, it's not like that there are two separate companies. There's not AWS and Amazon, it's one company-- >> Are we living in a world of alternative facts, Stu? I mean, Larry Ellison coined the term "Fake Cloud", talking about Salesforce. I'm not going to say Google's a fake Cloud, cause certainly it's not. But when you start blending in these numbers, it's kind of shifting the narrative to having alternative facts, certainly skewing the revenue numbers. To your point, if PaaS goes away because the SaaS minuses that lower down the stack. Cause if you have microservices and orchestration, it kind of thins that out. So one, is that the case? And then I saw your tweet with Sam Ramji, he formally ran Cloud Foundry, he's now at Google, knows his stuff, ex-Microsoft guy, very strong dude. What's he take? What's his take on this? Did you get a chance to chat with Sam at all? >> Yeah, I mean, it was interesting, because Sam, right, coming from Cloud Foundry said, what Cloud Foundry was one of the things they were trying to do, was to really standardize across the clouds. And of course, little bias that he works at Google now. But he's like, "We couldn't do that with Google, "cause Google had really cool features. And of course, when you put an abstraction layer on, can I actually do all the stuff? And he's like, "We couldn't do that." Sure, if you talked to Amazon, they'll be like, "Come on. "Thousand features we announced last year, "look at all the things we have. "It's not like you can just take all of our pieces, "and use it there." Yes, at the VM, or container, or application microservices layer, we can sit on a lot of different Clouds, public or private. But as we said today, the Cloud is not a utility. John, you've been in this discussion for years. So we've talked about, "Oh, I'm just going "to have a Cloud broker, "and go out in a service." It's like, this is not, I'm not buying from Domino's and Pizza Hut, and it's pepperoni pizza's a pepperoni pizza. >> Well, Multicloud, and moving workloads across Clouds, is a different challenge. Certainly, I might have to some stuff here, maybe put some data and edge my bets on leveraging other services. But this brings up the total cost of ownership problem. If you look at the trajectory, say OpenStack, just as a random example. OpenStack, at one point, had a great promise. Now it's kind of niched down into infrastructural service. I know you're going to be covering that summit in Boston. And it's going to be interesting to see how that is. But the word in the community is, that OpenStack is struggling because of the employment challenges involved with it. So to me, Google has an opportunity to avoid that OpenStack kind of concept. Because, talking about Sam Ramji, open source is the wildcard in all of this. So if you look at a open source, and you believe that that PaaS layer's thinning down, to infrastructure and SaaS, then you got to look at the open source community, and that's going to be a key area, that we're certainly watching, and we've identified, and we've mentioned it before. But here's my point. If you look at the total cost of ownership. If I'm a customer, Stu, I'm like, "Okay, if I'm just going to move to the Cloud, "I need to rely and lean on my partner, "my vendor, my supplier, "Amazon, or Google, or Microsoft, whoever, "to provide really excellent manageability. "Really excellent security. "Because if I don't, I have to build it myself." So it's becoming the shark fin, the tip of the iceberg, that you don't see the hidden cost, because I would much rather have more confidence in manageability that I can control. But I don't want to have to spend resources building manageability software, if the stuff doesn't work. So there's the issue about Multicloud that I'm watching. Your thoughts? Or is that too nuance? >> No, no. First of all, one of the things is that if I look at what I was doing on premises, before versus public Cloud, yes, there are some hidden costs, but in general I think we understand them a little bit better in public Cloud. And public Cloud gives us a chance to do a do-over for this like security, which most of us understand that security is good in public Cloud. Now, security overall, lots of work to do, challenges, not security isn't the same across all of them. We've talked to plenty of companies that are helping to give security across Clouds. But this Multicloud discussion is still something that is sorting out. Portability is not simple, but it's where we're going. Today, most companies, if I'm not really small, have some on-prem pieces. And they're leveraging at least one Cloud. They're usually using many SaaS providers. And there's this whole giant ecosystem, John, around the Cloud management platforms. Because managing across lots of environment, is definitely a challenge. There's so many companies that are trying to solve them. And there's just dozens and dozens of these companies, attacking everything from licensing, to the data management, to everything else. So there's a lot of challenges there, especially the larger you get as a company, the more things you need to worry about. >> So Stu, just to wrap up our segment. Great day. Wanted to just get some color on the day. And highlighting some parody from the web is always great. Just got a tweet from fake Andy Jassy, which we know really isn't Andy Jassy. But Cloud Opinion was very active to the hashtag, that Twitter handle Cloud Opinion. But he had a medium post, and he said, "Eric Schmidt was boring. "Diane Greene was horrible. "Unfortunately, day one keynote were missed opportunity, "that left several gaps, "failed to portray Google's vision for Google Cloud. "They could've done the following, A, "explain the vision for the Cloud, "where do they see Google Cloud going. "Identify customer use cases that show samples "and customer adoption." They kind of did that. So discount that. My favorite line is this one, "Differentiate from other Cloud providers. "'We're Google damn it,' isn't working so well. "Neither is indirect shots as S3 downtime, "didn't work either as well as either. "Where is the customer's journey going? "And what's the most compelling thing for customers?" This phrase, "We're Google damn it," has kind of speaks to the arrogance of Google. And we've seen this before, and always say, Google doesn't have a bad arrogance. I like the Google mojo. I think the technology, they run hard. But they can sometimes, like, "Customer support, self-service." You can't really get someone on the phone. It's hard to replies from Google. >> "Check out YouTube video. "We own that too, don't you know that?" >> So this is a perception of Google. This could fly in the face, and that arrogance might blow up in the enterprise, cause the enterprises aren't that sophisticated to kind of recognize the mojo from Google. And they, "Hey, I want support. "I want SLAs. "I want security. "I want data flexibility." What's your thoughts? >> So Cloud Opinion wrote, I thought a really thoughtful piece leading up to it, that I didn't think was satire. Some of what he's putting in there, is definitely satire-- >> John: Some of it's kind of true though. >> From the keynote. So I did not get a sense in the meetings I've been in, or watching the keynote, that they were arrogant. They're growing. They're learning. They're working with the community. They're reaching out. They're doing all the things we think they need to do. They're listening really well. So, yes, I think the keynote was a missed opportunity overall. >> John: But we've got to give, point out that was a teleprompter fail. >> That was a piece of it. But even, we felt with a little bit of polish, some of the interactions would've been a little bit smoother. I thought Eric Schmidt's piece was really good at end. As I said before, the AI discussion was enlightening, and really solid. So I don't give it a glowing rating, but I'm not ready to trash it. And tomorrow is when they're going to have the announcements. And overall, there's good buzz going at the show. There's lots going on. >> Give 'em a letter. Letter grade. >> For the keynote? Or the show in general? >> So far, your experience as an analyst, cause you had the, again, to give them credit, I agree with you. First analyst conference. They are listening. And the slideshow, you see what they're doing. They're being humble. They didn't take any real direct shots at its competitors. They were really humble. >> And that is something that I think they could've helped to focus one something that differentiated a little bit. Something we had to pry out of them in some of the one-on-ones, is like, "Come on, what are you doing?" And they're like, "We're winning 50, 60% of our competitive deals." And I'm like, "Explain to us why. "Because we're not hearing it. "You're not articulating it as well." It's not like we expect them, it's like, "Oh wait, they told us we're arrogant. "Maybe we should be super humble now." It's kind of-- >> I don't think they're thinking that way. I think my impression of Google, knowing the companies history, and the people involved there, and Diane Greene in particular, as you know from the Vmware days. She's kind of humble, but she's not. She's tough. And she's good. And she's smart. >> And she's bringing in really good people. And by the way, John, I want to give them kudos, really supported International Women's Day, I love the, Fei-Fei got up, and she talked about her, one of her compatriots, another badass woman up there, that got like one of the big moments of the keynote there. >> John: Did they have a woman in tech panel? >> Not at this event. Because Diane was there, Fei-Fei was there. They had some women just participating in it. I know they had some other events going on throughout the show. >> I agree, and I think it's awesome. I think one of the things that I like about Google, and again, I'll reiterate, is that apples and oranges relative to the other Cloud guys. But remember, just because Amazon's lead is so far ahead, that you still have this jocking of position between the other players. And they're all taking the same pattern. Again, this is the same thing we talked about at our other analysis, is that, certainly at re:Invent, we talked about the same thing. Microsoft, Oracle, IBM, and now Google, are differentiating with their apps. And I think that's smart. I don't think that's a bad move at all. It does telegraph a little bit, that maybe they got, they could add more to show, we'll see tomorrow. But I don't think that's a bad thing. Again, it does make the numbers a little messy, in terms of what's what. But I think it's totally cool for a company to differentiate on their offering. >> Yeah, definitely. And John, as you said, Google is playing their game. They're not trying to play Amazon's game. They're not, Oracle's thing was what? You kind of get a little bit of the lead, and kind of just make sure how you attack and stay ahead of what they're doing, going to the boating analogy there. But Google knows where they're going, moving themselves forward. That they've made some really good progress. The amount of people, the amount of news they have. Are they moving fast enough to really try to close a little bit on the Amazon's world, is something I want to come out of the show with. Where are customers going? >> And it's a turbulent time too. As Peter Burris, our own Peter Buriss at Wikibon, would say, is a turbulent time. And it's going to really put everyone on notice. There's a lot to cover, if you're an analyst. I mean, you have compute, network storage, services. I mean, there's a slew of stuff that's being rolled out, either in table stakes for existing enterprises, plus new stuff. I mean, I didn't hear a lot of IoT today. Did you hear much IoT? Is there IoT coming to you at the briefing? >> Come on. I'm sure there's some service coming out from Google, that'll help us be able to process all this stuff much faster. They'll just replace this with-- >> So you're in the analyst meeting. I know you're under NDA, but is there IoT coming tomorrow? >> IoT was a term that I heard this week, yes. >> So all right, that's a good confirmation. Stu cannot confirm or deny that IoT will be there tomorrow. Okay, well, that's going to end day one of coverage, here in our studio. As you know, we got a new studio. We have folks on the ground. You're going to start to see a new CUBE formula, where we have in-studio coverage, and out in the field, like our normal CUBE, our "game day", as we say. Getting all the signal, extracting it from that noise out there, for you. Again, in-studio allows us to get more content. We bring our friends in. We want to get the content. We're going to get the summaries, and share that with you. I'm John Furrier, Stu Miniman, day one coverage. We'll see you tomorrow for another full day of special coverage, sponsored by Intel, two days of coverage. I want to thank Intel for supporting our editorial mission. We love the enterprise, we love Cloud, we love big data, love Smart Cities, autonomous vehicles, and the changing landscape in tech. We'll be back tomorrow, thanks for watching.

>> Announcer: Live from Las Vegas, Nevada; it's the theCUBE covering Accelerate 2017. Brought to you by Fortinet. Now, here are your hosts Lisa Martin and Peter Buriss. >> Hey, welcome back to theCUBE. We are live in Las Vegas at Fortinet 2017. Fortinet Accelerate 2017 I should say. I'm your host Lisa Martin. Joined by my co-host Peter Buriss. We're really excited to be here today. First time for theCUBE and we are next joined by, Drew Del Motto, who is the CFO of Fortinet. Drew, welcome to theCUBE. >> Thank you, Lisa. >> Great to have you. I really enjoyed your keynote this morning. If you weren't able to see it, very passionate, very intellectual keynote. Some of the nuggets here that I wanted to talk to you about first just to kick things off; is just sharing with us, you have over 20 years of financial management experience in network security. You said, you started as a CPA. As we look at the generation of the business economy the digital economy and also now we're at this dawn of data. Love to get your perspective on defining that to our viewers. You mentioned that data is worthless is we can't trust it. And really that it's key to business value. Can you expound upon that? How critical is data trust for an organization to achieve? >> I think it's just core to value creation because it's as simple as if you're putting information out there and you think somebody's going to get to it, then you may not put the information out there. I think I've shared a statistic where a consulting group said that there was 5X the value for data that you trust. You created more data if you trusted it and they got about 5X the data. The monetizable data, which ultimately is what drives value in the new economy. So if you look at the most valuable companies in the world, I think I mentioned Amazon, Alphabet, Google, Facebook and Microsoft. All of them cloud, mobility, analytics. They're using data in their business models to drive it, right? But you trust them, right? And that's the key point. And they feverishly, energetically protect that data. And that's why you trust your data to put it there. >> But it's not just trust the data, because one of the interesting things about data is because it can be copied, be shared, it's trust in future uses of that data. that's one of the big challenges. Not only do we have to be able to demonstrate that we have an infrastructure or a fabric of capabilities that allow us to trust data now, but also that it will allow us to change how we use the data, introduce new ways of using the data, and very quickly validate and verify that we can trust that use too. Is that true? >> Absolutely, Peter, I think that's right. And I think most companies participating in a meaningful way to the new economy, very thoughtful about what data they're looking for and how they're going to monetize that data. I think of the business models of, clearly advertising and anything that's related to advertising. Very clear to see that they need data to grow their business right. And the core is the trust of that, and they continue to do that. But then you look at the other data that's around, many people aggregate data that they use and sell back to you in some way, for location based services or personalized services. Especially in healthcare, where you see that and that's a very valuable story. And if you don't trust your healthcare data, you're probably not going to trust whatever they're trying to sell you, right? But there's a lot about of value for you personally, simply because you can improve your health. Maybe you live longer, maybe you avoid some illness that could be pretty painful. But you have to ultimately trust that, that's being used in a useful way for you and is protected, so it doesn't get in the wrong hands. >> So we think about digital business as, boils down to very simply, a digital business uses data to differentially created sustained customers. >> Drew: Fair enough. >> So, the idea then, is that I now have to start looking at my data as an asset, that can generate a return for shareholders. Generate return for customers, generate return for the stakeholders. We don't typically think of data as an asset though. As you and your peers start thinking about how to start evaluating data, or thinking about data as an asset, where are we on that journey of getting to a point where we actually look at data as something that is a source of value in and of itself and creates value in new ways? >> Peter I think it might be helpful to actually even share some numbers. 'Cause what comes to mind for me was the McKinsey study that said there was about $7.8 trillion alone generated in 2015 that's monetizing data, right? So if that data weren't there, Then, that value wouldn't be there. And that's about 10% of the global economy. That's amazing. Just think about that and you think about the companies that I mentioned earlier, the value there are about two trillion dollars of market cap right there. Clearly, the lynchpin to that is digital trust, their use of data, until you can grow it all the time. I think of it as an asset. I think that I want to have it. I want to know how to protect it. I want an architecture that's proactive. That is driven by the business, right? But complimented by a secure infrastructure, So that I know, people know, that I have digital trust. I can trust the data, right? I have to print data as a CFO, right? If my investors don't trust it, guess what? I have a problem, right? So I think it's the same way around in anything you do business wise and just think as data being the fuel of the next generation economy. Look, data's also power, not to get into politics, but think of the power of the data that the Trump campaign had in the upper Mid-West. They had some data that obviously, the other side didn't have and it was very useful for them crafting their message and getting elected. >> I think we can definitely agree, no matter what side of the fence you're on, that there was influence there from an election perspective. One of the things that I'm interested in getting your perspective on is you were talking about, in your keynote this morning, the role of the C-Suite, how it's changing. You said, "It's kind of cliche," but in the last five to seven years we've seen this either emergence of the CSO or maybe an evolution from the CSO to the CSO. And there was a panel this morning of three CSO's from AT&T, Lazard and Levi's. My ear went up wondering if I was going to hear cyber security differences based on the industry. And it really seemed, and what we've heard from some of your peers and technology partners on the show today is, it's quiet agnostic. But I'd love to get your take on, you were talking about how you view, as a CFO, data as an asset. In the role of the CSO, is this guy or gal, when it comes to cyber security, are they now on the front lines as the leader of a cooperation's digital army? Or is that digital army now maybe a little bit more broad across that C-Suite in a company that needs to trust data in order to have value? >> Great question, Lisa and it was a great panel. What I took away from it was that the CSO is very much the quarter back, right? So I think everybody plays a role, it's a team. And when they break huddle, everybody has an assignment. They look at the play they're going to call and they run it and the CSO is really taking information from everybody and rolling it together in a way to underlie the trust, making sure that they're driving towards digital trust ultimately. That's the role and they have to take input from the CEO on the business propositions, the vision. The CFO on risks and the investment profile. The CIO on how they're going to drive the business with IT, and then their role is ultimately to advise and help drive the business going forward. And make sure they're compliant. When you talk about verticals, I think it's generally agnostic. I think there are some areas where there's obviously some compliance with credit cards and financial institutions and healthcare clearly, given the information there. But generally speaking, I think it's the same all around. If they're successful, the key is to not be right themselves, but to get it right with that team. >> I love the analogy of the quarter back actually. We were talking, actually before we started this segment that there's estimates that a CSO is inheriting more than 25 different security technologies to defend and protect and remediate and we've been talking as well with some other guests, today on this show that a lot of companies now have this sort of assumed breach mentality. Can you expand a little bit more on that CSO as the quarter back. What they're inheriting and how they need to navigate through that environment in order to extract value from that data? >> Well, it's the vectors that we all hear everyday right? It's IOT, you here more mobility, more cloud and more data. And even some of the things out there just generate data, right? I think it's just an aggregation of an architecture that reflects that. There's a lot of silent business units ruling their own technology, right? And there's a lack of talent. I think that came up a lot this morning was just a complete lack of talent. There's a lot of people in college, but they don't have a lot of experience yet. So, I still think we have a dearth of talent. There's some compliance and then ultimately, you're trying to get the best architecture for the company. So, I think that's the quarterback. Really trying to bring all those conversations to the table. Help the company draft a vision that's business forward that reflects digital trust ultimately, and reflects something that's affordable and manageable. And I think you do that with an architecture, a lot of listening, I think they key is listening. Again, what I said earlier, it's not about any one person being right, it's about getting it right for the company and their customers, so they trust the data. >> That's a great message, fantastic. >> As you think about the evolution of the relationship between the CFO, who has a responsibility for risk and generating return on assets and the CSO, who is part of this new team that's going to increasingly have to think in terms of creating digital asset value. How is that relationship going to change over the next few years? >> Well, I think the new awakening, the message is that there's an opportunity for value creation. One of the things I said this morning, as a CFO, I love it when somebody brings me and investment an alternative. If they just bring me a cost, (laughing) >> That's cost and you say no. >> I take a deep breathe (chuckles) and I try not to say no, sometimes you can't control it, but really you always want to think about the business first. That's the job, right? CFO certainly. You think about your shareholders. Your trying to find them an appropriate return, the best possible return on the investment. So, it's always investment forward. Think about the investment. Does it provide the right type of return? And I don't see how anybody can argue that in this dawn of data, if you will, all the analytical opportunities out there, and the ability to drive a business with that data, and the value it creates. That trust isn't at the core and investing in that trust is a great idea. >> Also, it means, I would think, that there's going to be some experience curves associated with this process. And your ability to off the experience curves in your business is highly dependent upon how successful you are at choosing partners and laying trust in those partners so that they can do a great job of what they're doing as well. How does Fortinet tell its story to its customers, that working with us you will have a trusted partner, but also we will be providing the platform that will facilitate you being a more trusted partner? >> Well Peter, from my perspective that's an easy question. It's Fortinet's security fabric and everybody's talking about platform, but platform is like a ship with containers on it, right? You may bolt them down, but if the ship tilts they fall off. A fabric is knitted together, right? It's not a patchwork. It's not thread. it's a coat, right? It's something that you bought to protect you. And Fortinet's that security fabric reflects the breadth of product portfolio we have. It goes through the cloud, into IOT, provides the performance necessary to run the business. It doesn't create friction. It's broad, it's powerful and it's secure. And you get that transparency across the business. It updates itself automatically. It's fully integrated and it works for today and tomorrow. >> So one last question here. >> Sure. >> Drew, giving you the last word. One of the things that I also found very intriguing this morning was that you were talking about the difference between selling fear versus selling value. As we look at where Fortinet is today, and also Ken Xie the CEO did mention this morning that you got this goal as a company to become number one by 2020, which is just a few years away. What excites you about the announcements today as well as the vision of Fortinet going forward to really enable your customers and your partners to deliver the trust those customers need? >> Yeah, I think we're helping them be business forward. I think we're helping them be business first. When I look out there and I see everybody saying, "Oh the attack surface is increasing, "cyber crime, cyber criminals, somebody hacking away "in a garage in some country far away, "and they can easily do this." Those things are generally true, but what I really want to do is build an infrastructure that drives my business, so that I could participate in a big way where the economy is going and that's about data and analytics. It's like I said, it's the dawn of data. And I think we can do that in a very differentiated way and very value oriented way for our customers that no one else can do and that's Fortinet's security fabric. >> Well, what a fantastic way to end the conversation there. I love that you said how important the role of listening is. I think that's quiet an agnostic importance there. Drew Del Matto CFO of Fortinet. Thanks so much for joining us on theCUBE. >> Thank you Lisa, Thank you Peter. >> Peter: Thank you, Drew. >> And on behalf of Peter Buriss, I am Lisa Martin. You've been watching the theCUBE, stay tuned. We'll be right back. (upbeat music)

>> Announcer: Live from San Francisco, it's The Cube. Covering Oracle OpenWorld 2016. Brought to you by Oracle. Now here's your host, John Furrier and Peter Burris. >> Hey, welcome back everyone, day two of wall-to-wall coverage live broadcast on the internet, this is SiliconANGLE Media's The Cube. It's our flagship program, we go out to the events and extract the signal from the noise, I'm John Furrier co-CEO of SiliconANGLE Media, joined with Peter Burris head of research of SiliconANGLE Media, as well as the general manager of WikiBon research. Peter, we did twelve interviews yesterday, we got a line up today. And we've got a great range of content, great editorial commentary, great guests from Oracle Exec. We asked them the tough questions, we also have some great sponsored spots for our supporters. But really, it's about putting out that content I think. Yesterday, we're starting to see, and we're going to some guests today around philanthropy. Oracle is doing a lot of work in philanthropy and we're going to get some great women in tech content, something that Oracle has a great presence in. But, the big story, Day 2, is Thomas Kurian was on stage. He was not on stage for Sunday night's Larry Ellison keynote with, sorry, with Intel and so he had a personal issue and had to mail in the video. There was speculation on whether he would be here, but Kurian is the guy, he's the product guy he's running the engineering, running the product development. So we expected to hear huge announcements today. Kind of not much, I mean, as expected, infrastructure's a service, we heard about containus which was pre-announced by Larry, basically announces everything. But, not a lot of big game changing news, but a lot of the blocking and tackling a lot of the ground game for Oracle's march to the cloud. Really emphasizing on the speed of standing up a data center with the browser and API's, anyone can stand up to. All the capabilities of Oracle with standing up a virtual data center with all the isolation at the network level, giving that customer choice but bridge to the future. Again, this was expected. But this is a key part of Oracle's strategy. They need to lock down the infrastructure. To make PaaS work well and SaaS, they got to make it work well. So, not a lot of surprises, as expected, infrastructures of service. >> Well let's be honest about what Oracle's biggest threat is, what the biggest threat to Oracle. They've got this enormous presence in the applications business, we talked about yesterday, the apps business is sticky. When companies embed their applications, or embed an application into their business, they reconfigure the entire organization around it. It's hard to rip that out. They are clearly number one, and have been for a long time, in the database marketplace, and it's not hard to pop a database out. It is hard to pop a database out >> John: It's very sticky >> It's very very sticky, so hardware? It's getting a little bit easier, but the possibility that the infrastructure starts to become more public in nature, starts to move up into the database space and Oracle clearly wants to ensure that it doesn't encounter longer term problems with the bottom eroding. So it needs to sustain that presence and infrastructure and continue to give people an option, should they want to tie infrastructure directly, or continue to tie infrastructure directly to the database in the application. >> And we pressed Juan Loaiza yesterday, senior vice president on the development side, lead database guru, laid out his vision of how he sees the key elements of data center and he said it simply. Our number one priority at Oracle is to move workloads from on-prem to the cloud seamlessly back and forth... >> Peter: To our cloud. (laughing) >> So we'll say cloud for now but that's ultimately what the customers want. They want to be able to move to the cloud, ultimately have all that benefits of the operating model and the agility but moving it back and forth, again, to Oracle, it's the Oracle Cloud. So on Oracle and Oracle, job one is to make it really frickin' awesome. Fast, low-cost, and the infrastructure aside, put pressure on the Amazon choice but yet keep that there. So that's clear. But I want to ask you... >> Well let me pick up on that, maybe this is what you're going to ask me. Many years ago, I had a lot of experiences working with CIO's over the years. Many years ago I was in a staff meeting of a CIO, she was looking out across her team, and she had a way of starting the conversation with every single one of her direct reports. Head of development, head of security, head of infrastructure, and she routinely would start the question just to reinforce what she wanted folks to focus on. And every staff meeting she had, she started the conversation with the head of infrastructure with, so infrastructure's doing no harm this week. And in many respects, that's becoming the message of Oracle. Infrastructure's going to do no harm, we're going to make sure that on premise, you're covered. Cloud, you're covered. Hybrid, you're covered. We want to make sure that infrastructure's not a huge part of the conversation so you can stay focused on the upper levels. >> Yeah, that's a great point. Some people call it hardening the infrastructure, Paul Maritz in 2010 at VMWorld, talked about this hardened top and he talked about Intel processors, and saying hey, you know, Intel has a hard top and no one looks under the chip, it's totally hardened, it's proprietary code that makes stuff go fast. So I think Oracle has that same kind of mojo going on with the engineered systems and you're seeing that stuff kind of trying to harden the top so that the infrastructure doesn't do any damage. And that brings up the point though about what I'm seeing. And Oracle, I would love to get your comments here, and your take, I mean, look at the industry over the years, the competitive strategy is protect and fortify your core crown jewel. It's been the database. The database powers the application so the application certainly, a lot of revenue, but the database has been this sacred cow for Oracle. And you've been seeing it, and although they haven't been overt about it, protecting the database, keeping it in the swim lane, keeping it here, letting things develop on the side, and ultimately it was all about the database. This show, it's interesting, you're starting to see that swim lane expand. You're starting to see Oracle recognize the fact that hey it's okay to be the system of record, and it's actually quite sticky to be the systems of record in a high performance database environment, but yet yielding territory, or turf, to other databases. That's interesting because that takes the monolithic siloed mentality off the table. Question is, do you see it that way? And if so, does Oracle have to adjust its competitive strategy? >> John, I think, first off, most importantly you're absolutely right Oracle, the product that is named Oracle, is the Oracle RDBMS. When people twenty years ago talked about Oracle, that's what they were talking about. Oracle has been a database company, it's its roots. It's some of the great conversation we had yesterday were with the database people. I don't think that's going to change. I think that they're trying to extend it out and one of the ways they're looking at doing that is they're recognizing that as we look forward the next couple of years, this increasingly, it's going to be, and we talked about this a lot yesterday, how does, not only the data in the Oracle database manager become increasingly relevant to other applications and other use cases in the business. But also, how do the skills associated with that database manager become more relevant and more useful to the business, as new types of data, new types of applications, and new types of business models start to become even more relevant to the industry. So I think what Oracle... >> Like data value? >> Like data value, the value of data, how development, we talked yesterday about, maybe it was after one of the conversations, about we're now entering into this world of big data and we still don't know what I call, the body plans for business models are. We're in this notion where we don't know if it's going to look like a fish, or it's going to look like a mollusk, or it's going to look like something else. We know that it's not going to look like what the RDBMS world looks like. >> It's kind of like, what's your spirit animal in cloud. We don't know yet. >> We don't know yet, so Oracle has to be flexible as their customers have to be flexible, and not presume that it's going to look exactly like it did ten years ago. >> This game is not even started. >> There you go, and I think that's the key thing, John. I think that they're finally acknowledging that the new world is not going to look exactly like the old world. They have to be flexible, they have to facilitate their customers to be flexible so that they can rearrange things in response to new develops and innovation in the industry. >> You know I was talking to some of the people at Oracle yesterday, after the Century event folks, and what's coming down to is the industry is kind of spinning towards, we call the tech athlete, the smart people. So what's interesting is Oracle has always kind of kept their smartest brains behind the firewall. It's always been kind of competitive advantage to always serve customers on all that lock-in and competitive advantage drive revenue, they're highly profitable but now you're starting to see the battle between like Amazon web services and Oracle. Couple observations from my standpoint. One, they're putting their best technical people out front. Okay, clearly talent matters, organic growth matters, certainly the MNA thing is always going on. Amazon always puts their technical people out. So, observation, companies are putting their best technical people out there on the front lines. We're going to compete on our people. Two, the announcement volume, velocity, here at OpenWorld, probably is the most I've seen of all Oracle OpenWorld in seven years. Very similar to AWS re:Invent. There are so many announcements that are coming out of re:Invent this year, I think it's going to be more than last year, but even last year, it was raining, it was a tornado of announcements. It's hard to cover. In the tech press, talking to some of the folks yesterday, Wall Street Journal, New York Times, CNBC guys, it's like their heads are exploding. Because this is so much to cover. All the stuff's coming at the customer. And to me, that's an observation that you say, okay, what does it mean? >> Well, so let's talk about two great points tossed. Let's talk about the first one, or one of, on the Tube yesterday we talked, somebody said, you know, you mentioned who is someone at Oracle saying who is the industry's best CEO? Larry Ellison, okay, Larry Ellison's 70 years old. Larry Ellison is not going to be the CTO of Oracle forever. So number one, we're starting to see some of that talent start to emerge and start to become more out front because it has to. Number two, very importantly, John, talent creates and attracts talent. And I think the more that Oracle puts its talent out front in this period of significant disruption, that they are going to be more likely to attract other talent to Oracle. >> And that's what impacts the MNA game, too. >> You betcha. >> How to integrate in. >> We talked about what's happening amongst VCs in the Valley yesterday. And who are going to be the entrepreneurs? We're going to hear about Oracle. Is Oracle going to be more aggressive at developing some of those newly inventors and maybe not having them institutionally be part of Oracle? >> Reggie Bradford yesterday talked specifically about that MNA. Again, talent brings talent organically and inorganically. >> So putting those guys out in front is going to make Oracle a more attractive place as we go through this disruptive process. But I think the other thing that you mentioned is a really crucial point. At the end of the day, Oracle is introducing a lot of stuff, and as much as I've also ever seen. But it's coherent. One of the things that's really interesting about this conference or these sets of announcements is that they're covering everything, but it's one of the most coherent sets of announcements I've ever seen from Oracle. It's not a whole bunch of product piece parts. >> John: It's not fluffy. >> It's not fluffy and it's not piece parts. It's cloud. We are bringing all this stuff, and we're driving it into the cloud. 2017's going to be a huge year, because Oracle's, as you said yesterday, is putting everybody on alert. We're going to get really serious about this. >> And we have Oracle's keynote with Larry Ellison, you're going to watch it at three or one o'clock. And then we come back on the Cube for our analysis at 3:30. >> Peter: Pacific. >> Pacific time, we're going to go into great detail on the keynote, but one point we can't cover on here on the interest, we've got to go to our next segment is, and this is where you can expand on this, you mentioned business models. The developer is critical in the business model and the data. Data and developer, those two things we will really, really unpack at 3:30. Of course we'll analyze the heck out of Larry Ellison's keynote, because again, everyone's up front. Call to arms, this is not a false alarm for Oracle. It is battle stations. And we are going to see which company's got the best technical people out front. Where's the meat on the bone for the products? Of course, we've got it on the Cube. >> 2017 is going to be a year where leadership matters in the tech industry. >> Peter Buriss laying it down, I'm John Furrier. The Cube, all-day coverage, day two of three days. 12 videos yesterday, live broadcast again today. We'll keep pumping it out there, that's what we do. This is the Cube, we'll be right back, day two, Oracle OpenWorld live in San Francisco. We'll be right back. (upbeat instrumental music)