(upbeat music) >> Hello everyone, welcome to this special Cube conversation here in Palo Alto, California. I'm John Furrier, host of theCUBE in theCUBE Studios. We've got a special video here. We love when we have startups that are launching. It's an exclusive video of a hot startup that's launching. Got great reviews so far. You know, word on the street is, they got something different and unique. We're going to' dig into it. Amit Govrin who's the CEO and co-founder of Kubiya, which stands for Cube in Hebrew, and they're headquartered in Bay Area and in Tel Aviv. Amit, congratulations on the startup launch and thanks for coming in and talk to us in theCUBE >> Thank you, John, very nice to be here. >> So, first of all, a little, 'cause we love the Cube, 'cause theCUBE's kind of an open brand. We've never seen the Cube in Hebrew, so is that true? Kubiya is? >> Kubiya literally means cube. You know, clearly there's some additional meanings that we can discuss. Obviously we're also launching a KubCon, so there's a dual meaning to this event. >> KubCon, not to be confused with CubeCon. Which is an event we might have someday and compete. No, I'm only kidding, good stuff. I want to get into the startup because I'm intrigued by your story. One, you know, conversational AI's been around, been a category. We've seen chat bots be all the rage and you know, I kind of don't mind chat bots on some sites. I can interact with some, you know, form based knowledge graph, whatever, knowledge database and get basic stuff self served. So I can see that, but it never really scaled or took off. And now with Cloud Native kind of going to the next level, we're starting to see a lot more open source and a lot more automation, in what I call AI as code or you know, AI as a service, machine learning, developer focused action. I think you guys might have an answer there. So if you don't mind, could you take a minute to explain what you guys are doing, what's different about Kubiya, what's happening? >> Certainly. So thank you for that. Kubiya is what we would consider the first, or one of the first, advanced virtual assitants with a domain specific expertise in DevOps. So, we respect all of the DevOps concepts, GitOps, workflow automation, of those categories you've mentioned, but also the added value of the conversational AI. That's really one of the few elements that we can really bring to the table to extract what we call intent based operations. And we can get into what that means in a little bit. I'll save that maybe for the next question. >> So the market you're going after is kind of, it's, I love to hear starters when they, they don't have a Gartner Magic quadrant, they can fit nicely, it means they're onto something. What is the market you're going after? Because you're seeing a lot of developers driving a lot of the key successes in DevOps. DevOps has evolved to the point where, and DevSecOps, where developers are driving the change. And so having something that's developer focused is key. Are you guys targeting the developers, IT buyers, cloud architects? Who are you looking to serve with this new opportunity? >> So essentially self-service in the world of DevOps, the end user typically would be a developer, but not only, and obviously the operators, those are the folks that we're actually looking to help augment a lot of their efforts, a lot of the toil that they're experiencing in a day to day. So there's subcategories within that. We can talk about the different internal developer tools, or platforms, shared services platforms, service catalogs are tangential categories that this kind of comes on. But on top of that, we're adding the element of conversational AI. Which, as I mentioned, that's really the "got you". >> I think you're starting to see a lot of autonomous stuff going on, autonomous pen testing. There's a company out there doing I've seen autonomous AI. Automation is a big theme of it. And I got to ask, are you guys on the business side purely in the cloud? Are you born in the cloud, is it a cloud service? What's the product choice there? It's a service, right? >> Software is a service. We have the classic, Multi-Tenancy SAAS, but we also have a hybrid SAAS solution, which allows our customers to run workflows using remote runners, essentially hosted at their own location. >> So primary cloud, but you're agnostic on where they could consume, how they want to' consume the product. >> Technology agnostic. >> Okay, so that's cool. So let's get into the problem you're solving. So take me through, this will drive a lot of value here, when you guys did the company, what problems did you hone in on and what are you guys seeing as the core problem that you solve? >> So we, this is a unique, I don't know how unique, but this is a interesting proposition because I come from the business side, so call it the top down. I've been in enterprise sales, I've been in a CRO, VP sales hat. My co-founder comes from the bottom up, right? He ran DevOps teams and SRE teams in his previous company. That's actually what he did. So, we met each other halfway, essentially with me seeing a lot of these problems of self-service not being so self-service after all, platforms hitting walls with adoption. And he actually created his own self-service platform, within his last company, to address his own personal pains. So we essentially kind of met with both perspectives. >> So you're absolutely hardcore on self-service. >> We're enabling self-service. >> And that basically is what everybody wants. I mean, the developers want self-service. I mean, that's kind of like, you know, that's the nirvana. So take us through what you guys are offering, give us an example of use cases and who's buying your product, why, and take us through that whole piece. >> Do you mind if I take a step back and say why we believe self-service has somewhat failed or not gotten off. >> Yeah, absolutely. >> So look, this is essentially how we're looking at it. All the analysts and the industry insiders are talking about self-service platforms as being what's going to' remove the dependency of the operator in the loop the entire time, right? Because the operator, that scarce resource, it's hard to hire, hard to train, hard to retain those folks, Developers are obviously dependent on them for productivity. So the operators in this case could be a DevOps, could be a SecOps, it could be a platform engineer. It comes in different flavors. But the common denominator, somebody needs an access request, provisioning a new environment, you name it, right? They go to somebody, that person is operator. The operator typically has a few things on their plate. It's not just attending and babysitting platforms, but it's also innovating, spinning up, and scaling services. So they see this typically as kind of, we don't really want to be here, we're going to' go and do this because we're on call. We have to take it on a chin, if you may, for this. >> It's their child, they got to' do it. >> Right, but it's KTLOs, right, keep the lights on, this is maintenance of a platform. It's not what they're born and bred to do, which is innovate. That's essentially what we're seeing, we're seeing that a lot of these platforms, once they finally hit the point of maturity, they're rolled out to the team. People come to serve themselves in platform, and low and behold, it's not as self-service as it may seem. >> We've seen that certainly with Kubernetes adoption being, I won't say slow, it's been fast, but it's been good. But I think this is kind of the promise of what SRE was supposed to be. You know, do it once and then babysit in the sense of it's working and automated. Nothing's broken yet. Don't call me unless you need something, I see that. So the question, you're trying to make it easier then, you're trying to free up the talent. >> Talent to operate and have essentially a human, like in the loop, essentially augment that person and give the end users all of the answers they require, as if they're talking to a person. >> I mean it's basically, you're taking the virtual assistant concept, or chat bot, to a level of expertise where there's intelligence, jargon, experience into the workflows that's known. Not just talking to chat bot, get a support number to rebook a hotel room. >> We're converting operational workflows into conversations. >> Give me an example, take me through an example. >> Sure, let's take a simple example. I mean, not everyone provisions EC2's with two days (indistinct). But let's say you want to go and provision new EC2 instances, okay? If you wanted to do it, you could go and talk to the assistant and say, "I want to spin up a new server". If it was a human in the loop, they would ask you the following questions: what type of environment? what are we attributing this to? what type of instance? security groups, machine images, you name it. So, these are the questions that typically somebody needs to be armed with before they can go and provision themselves, serve themselves. Now the problem is users don't always have these questions. So imagine the following scenario. Somebody comes in, they're in Jira ticket queue, they finally, their turn is up and the next question they don't have the answer to. So now they have to go and tap on a friend, or they have to go essentially and get that answer. By the time they get back, they lost their turn in queue. And then that happens again. So, they lose a context, they lose essentially the momentum. And a simple access request, or a simple provision request, can easily become a couple days of ping pong back and forth. This won't happen with the virtual assistant. >> You know, I think, you know, and you mentioned chat bots, but also RPA is out there, you've seen a lot of that growth. One of the hard things, and you brought this up, I want to get your reaction to, is contextualizing the workflow. It might not be apparent, but the answer might be there, it disrupts the entire experience at that point. RPA and chat bots don't have that contextualization. Is that what you guys do differently? Is that the unique flavor here? Is that difference between current chat bots and RPA? >> The way we see it, I alluded to the intent based operations. Let me give a tangible experience. Even not from our own world, this will be easy. It's a bidirectional feedback loop 'cause that's actually what feeds the context and the intent. We all know Waze, right, in the world of navigation. They didn't bring navigation systems to the world. What they did is they took the concept of navigation systems that are typically satellite guided and said it's not just enough to drive down the 280, which typically have no traffic, right, and to come across traffic and say, oh, why didn't my satellite pick that up? So they said, have the end users, the end nodes, feed that direction back, that feedback, right. There has to be a bidirectional feedback loop that the end nodes help educate the system, make the system be better, more customized. And that's essentially what we're allowing the end users. So the maintenance of the system isn't entirely in the hands of the operators, right? 'Cause that's the part that they dread. And the maintenance of the system is democratized across all the users that they can teach the system, give input to the system, hone in the system in order to make it more of the DNA of the organization. >> You and I were talking before you came on this camera interview, you said playfully that the Siri for DevOps, which kind of implies, hey infrastructure, do something for me. You know, we all know Siri, so we get that. So that kind of illustrates kind of where the direction is. Explain why you say that, what does that mean? Is that like a NorthStar vision that you guys are approaching? You want to' have a state where everything's automated in it's conversational deployments, that kind of thing. And take us through why that Siri for DevOps is. >> I think it helps anchor people to what a virtual assistant is. Because when you hear virtual assistant, that can mean any one of various connotations. So the Siri is actually a conversational assistant, but it's not necessarily a virtual assistant. So what we're saying is we're anchoring people to that thought and saying, we're actually allowing it to be operational, turning complex operations into simple conversations. >> I mean basically they take the automate with voice Google search or a query, what's the score of the game? And, it also, and talking to the guy who invented Siri, I actually interviewed on theCUBE, it's a learning system. It actually learns as it gets more usage, it learns. How do you guys see that evolving in DevOps? There's a lot of jargon in DevOps, a lot of configurations, a lot of different use cases, a lot of new technologies. What's the secret sauce behind what you guys do? Is it the conversational AI, is it the machine learning, is it the data, is it the model? Take us through the secret sauce. >> In fact, it's all the above. And I don't think we're bringing any one element to the table that hasn't been explored before, hasn't been done. It's a recipe, right? You give two people the same ingredients, they can have complete different results in terms of what they come out with. We, because of our domain expertise in DevOps, because of our familiarity with developer workflows with operators, we know how to give a very well suited recipe. Five course meal, hopefully with Michelin stars as part of that. So a few things, maybe a few of the secret sauce element, conversational AI, the ability to essentially go and extract the intent of the user, so that if we're missing context, the system is smart enough to go and to get that feedback and to essentially feed itself into that model. >> Someone might say, hey, you know, conversational AI, that was yesterday's trend, it never happened. It was kind of weak, chat bots were lame. What's different now and with you guys, and the market, that makes a redo or a second shot at this, a second bite at the apple, as they say. What do you guys see? 'Cause you know, I would argue that it's, you know, it's still early, real early. >> Certainly. >> How do you guys view that? How would you handle that objection? >> It's a fair question. I wasn't around the first time around to tell you what didn't work. I'm not afraid to share that the feedback that we're getting is phenomenal. People understand that we're actually customizing the workflows, the intent based operations to really help hone in on the dark spots. We call it last mile, you know, bottlenecks. And that's really where we're helping. We're helping in a way tribalize internal knowledge that typically hasn't been documented because it's painful enough to where people care about it but not painful enough to where you're going to' go and sit down an entire day and document it. And that's essentially what the virtual assistant can do. It can go and get into those crevices and help document, and operationalize all of those toils. And into workflows. >> Yeah, I mean some will call it grunt work, or low level work. And I think the automation is interesting. I think we're seeing this in a lot of these high scale situations where the talented hard to hire person is hired to do, say, things that were hard to do, but now harder things are coming around the corner. So, you know, serverless is great and all this is good, but it doesn't make the complexity go away. As these inflection points continue to drive more scale, the complexity kind of grows, but at the same time so is the ability to abstract away the complexity. So you're starting to see the smart, hired guns move to higher, bigger problems. And the automation seems to take the low level kind of like capabilities or the toil, or the grunt work, or the low level tasks that, you know, you don't want a high salaried person doing. Or I mean it's not so much that they don't want to' do it, they'll take one for the team, as you said, or take it on the chin, but there's other things to work on. >> I want to add one more thing, 'cause this goes into essentially what you just said. Think about it's not the virtual system, what it gives you is not just the intent and that's one element of it, is the ability to carry your operations with you to the place where you're not breaking your workflows, you're actually comfortable operating. So the virtual assistant lives inside of a command line interface, it lives inside of chat like Slack, and Teams, and Mattermost, and so forth. It also lives within a low-code editor. So we're not forcing anyone to use uncomfortable language or operations if they're not comfortable with. It's almost like Siri, it travels in your mobile phone, it's on your laptop, it's with you everywhere. >> It makes total sense. And the reason why I like this, and I want to' get your reaction on this because we've done a lot of interviews with DevOps, we've met at every CubeCon since it started, and Kubernetes kind of highlights the value of the containers at the orchestration level. But what's really going on is the DevOps developers, and the CICD pipeline, with infrastructure's code, they're basically have a infrastructure configuration at their disposal all the time. And all the ops challenges have been around that, the repetitive mundane tasks that most people do. There's like six or seven main use cases in DevOps. So the guardrails just need to be set. So it sounds like you guys are going down the road of saying, hey here's the use cases you can bounce around these use cases all day long. And just keep doing your jobs cause they're bolting on infrastructure to every application. >> There's one more element to this that we haven't really touched on. It's not just workflows and use cases, but it's also knowledge, right? Tribal knowledge, like you asked me for an example. You can type or talk to the assistant and ask, "How much am I spending on AWS, on US East 1, on so and so customer environment last week?", and it will know how to give you that information. >> Can I ask, should I buy a reserve instances or not? Can I ask that question? 'Cause there's always good trade offs between buying the reserve instances. I mean that's kind of the thing that. >> This is where our ecosystem actually comes in handy because we're not necessarily going to' go down every single domain and try to be the experts in here. We can tap into the partnerships, API, we have full extensibility in API and the software development kit that goes into. >> It's interesting, opinionated and declarative are buzzwords in developer language. So you started to get into this editorial thing. So I can bring up an example. Hey cube, implement the best service mesh. What answer does it give you? 'Cause there's different choices. >> Well this is actually where the operator, there's clearly guard rails. Like you can go and say, I want to' spin up a machine, and it will give you all of the machines on AWS. Doesn't mean you have to get the X one, that's good for a SAP environment. You could go and have guardrails in place where only the ones that are relevant to your team, ones that have resources and budgetary, you know, guidelines can be. So, the operator still has all the control. >> It was kind of tongue in cheek around the editorialized, but actually the answer seems to be as you're saying, whatever the customer decided their service mesh is. So I think this is where it gets into as an assistant to architecting and operating, that seems to be the real value. >> Now code snippets is a different story because that goes on to the web, that goes onto stock overflow, and that's actually one of the things. So inside the CLI, you could actually go and ask for code snippets and we could actually go and populate that, it's a smart CLI. So that's actually one of the things that are an added value of that. >> I was saying to a friend and we were talking about open source and how when I grew up, there was no open source. If you're a developer now, I mean there's so much code, it's not so much coding anymore as it is connecting and integrating. >> Certainly. >> And writing glue layers, if you will. I mean there's still code, but it's not, you don't have to build it from scratch. There's so much code out there. This low-code notion of a smart system is interesting 'cause it's very matrix like. It can build its own code. >> Yes, but I'm also a little wary with low-code and no code. I think part of the problem is we're so constantly focused on categories and categorizing ourselves, and different categories take on a life of their own. So low-code no code is not necessarily, even though we have the low-code editor, we're not necessarily considering ourselves low-code. >> Serverless, no code, low-code. I was so thrown on a term the other day, architecture-less. As a joke, no we don't need architecture. >> There's a use case around that by the way, yeah, we do. Show me my AWS architecture and it will build the architect diagram for you. >> Again, serverless architect, this is all part of infrastructure's code. At the end of the day, the developer has infrastructure with code. Again, how they deploy it is the neuron. That's what we've been striving for. >> But infrastructure is code. You can destroy, you know, terraform, you can go and create one. It's not necessarily going to' operate it for you. That's kind of where this comes in on top of that. So it's really complimentary to infrastructure. >> So final question, before we get into the origination story, data and security are two hot areas we're seeing fill the IT gap, that has moved into the developer role. IT is essentially provisioned by developers now, but the OP side shifted to large scale SRE like environments, security and data are critical. What's your opinion on those two things? >> I agree. Do you want me to give you the normal data as gravity? >> So you agree that IT is now, is kind of moved into the developer realm, but the new IT is data ops and security ops basically. >> A hundred percent, and the lines are so blurred. Like who's what in today's world. I mean, I can tell you, I have customers who call themselves five different roles in the same day. So it's, you know, at the end of the day I call 'em operators 'cause I don't want to offend anybody because that's just the way it is. >> Architectural-less, we're going to' come back to that. Well, I know we're going to' see you at CubeCon. >> Yes. >> We should catch up there and talk more. I'm looking forward to seeing how you guys get the feedback from the marketplace. It should be interesting to hear, the curious question I have for you is, what was the origination story? Why did you guys come together, was it a shared problem? Was it a big market opportunity? Was it an itch you guys were scratching? Did you feel like you needed to come together and start this company? What was the real vision behind the origination? Take a take a minute to explain the story. >> No, absolutely. So I've been living in Palo Alto for the last couple years. Previous, also a founder. So, you know, from my perspective, I always saw myself getting back in the game. Spent a few years in AWS essentially managing partnerships for tier one DevOps partners, you know, all of the known players. Some in public, some of them not. And really the itch was there, right. I saw what everyone's doing. I started seeing consistency in the pains that I was hearing back, in terms of what hasn't been solved. So I already had an opinion where I wanted to go. And when I was visiting actually Israel with the family, I was introduced by a mutual friend to Shaked, Shaked Askayo, my co-founder and CTO. Amazing guy, unbelievable technologists, probably one the most, you know, impressive folks I've had a chance to work with. And he actually solved a very similar problem, you know, in his own way in a previous company, BlueVine, a FinTech company where he was head of SRE, having to, essentially, oversee 200 developers in a very small team. The ratio was incongruent to what the SRE guideline would tell. >> That's more than 10 x rate developer. >> Oh, absolutely. Sure enough. And just imagine it's four different time zones. He finishes day shift and you already had the US team coming, asking for a question. He said, this is kind of a, >> Got to' clone himself, basically. >> Well, yes. He essentially said to me, I had no day, I had no life, but I had Corona, I had COVID, which meant I could work from home. And I essentially programed myself in the form of a bot. Essentially, when people came to him, he said, "Don't talk to me, talk to the bot". Now that was a different generation. >> Just a trivial example, but the idea was to automate the same queries all the time. There's an answer for that, go here. And that's the benefit of it. >> Yes, so he was able to see how easy it was to solve, I mean, how effective it was solving 70% of the toil in his organization. Scaling his team, froze the headcount and the developer team kept on going. So that meant that he was doing some right. >> When you have a problem, and you need to solve it, the creativity comes out of the woodwork, you know, invention is the mother of necessity. So final question for you, what's next? Got the launch, what are you guys hope to do over the next six months to a year, hiring? Put a plug in for the company. What are you guys looking to do? Take a minute to share the future vision and get a plug in. >> A hundred percent. So, Kubiya, as you can imagine, announcing ourselves at CubeCon, so in a couple weeks. Opening the gates towards the public beta and NGA in the next couple months. Essentially working with dozens of customers, Aston Martin, and business earn in. We have quite a few, our website's full of quotes. You can go ahead. But effectively we're looking to go and to bring the next operator, generation of operators, who value their time, who value the, essentially, the value of tribal knowledge that travels between organizations that could be essentially shared. >> How many customers do you guys have in your pre-launch? >> It's above a dozen. Without saying, because we're actually looking to onboard 10 more next week. So that's just an understatement. It changes from day to day. >> What's the number one thing people are saying about you? >> You got that right. I know it's, I'm trying to be a little bit more, you know. >> It's okay, you can be cocky, startups are good. But I mean they're obviously, they're using the product and you're getting good feedback. Saving time, are they saying this is a dream product? Got it right, what are some of the things? >> I think anybody who doesn't feel the pain won't know, but the folks who are in the trenches, or feeling the pain, or experiencing this toil, who know what this means, they said, "You're doing this different, you're doing this right. You architected it right. You know exactly what the developer workflows," you know, where all the areas, you know, where all the skeletons are hidden within that. And you're attending to that. So we're happy about that. >> Everybody wants to clone themselves, again, the tribal knowledge. I think this is a great example of where we see the world going. Make things autonomous, operationally automated for the use cases you know are lock solid. Why wouldn't you just deploy? >> Exactly, and we have a very generous free tier. People can, you know, there's a plugin, you can sign up for free until the end of the year. We have a generous free tier. Yeah, free forever tier, as well. So we're looking for people to try us out and to give us feedback. >> I think the self-service, I think the point is, we've talked about it on the Cube at our events, everyone says the same thing. Every developer wants self-service, period. Full stop, done. >> What they don't say is they need somebody to help them babysit to make sure they're doing it right. >> The old dashboard, green, yellow, red. >> I know it's an analogy that's not related, but have you been to Whole Foods? Have you gone through their self-service line? That's the beauty of it, right? Having someone in a loop helping you out throughout the time. You don't get confused, if something's not working, someone's helping you out, that's what people want. They want a human in the loop, or a human like in the loop. We're giving that next best thing. >> It's really the ratio, it's scale. It's a scaling. It's force multiplier, for sure. Amit, thanks for coming on, congratulations. >> Thank you so much. >> See you at KubeCon. Thanks for coming in, sharing the story. >> KubiyaCon. >> CubeCon. Cube in Hebrew, Kubiya. Founder, co-founder and CEO here, sharing the story in the launch. Conversational AI for DevOps, the theory of DevOps, really kind of changing the game, bringing efficiency, solving a lot of the pain points of large scale infrastructure. This is theCUBE, CUBE conversation, I'm John Furrier, thanks for watching. (upbeat electronic music)

>> Announcer: From Chicago, it's theCUBE, covering Oracle Transformation Day 2020. Brought to you by Oracle Consulting. >> Welcome back, everybody, to this special digital event coverage that theCUBE is looking into the rebirth of Oracle Consulting. Janet George is here, she's a group VP, autonomous for advanced analytics with machine learning and artificial intelligence at Oracle, and she's joined by Grant Gibson, who's a group VP of growth and strategy at Oracle. Folks, welcome to theCUBE, thanks so much for coming on. >> Thank you. >> Thank you. >> Grant, I want to start with you because you've got strategy in your title. I'd like to start big-picture. What is the strategy with Oracle, specifically as it relates to autonomous, and also consulting? >> Sure, so, I think Oracle has a deep legacy of strength in data, and over the company's successful history, it's evolved what that is from steps along the way. And if you look at the modern enterprise, an Oracle client, I think there's no denying that we've entered the age of AI, that everyone knows that artificial intelligence and machine learning are a key to their success in the business marketplace going forward. And while generally it's acknowledged that it's a transformative technology, and people know that they need to take advantage of it, it's the how that's really tricky, and that most enterprises, in order to really get an enterprise-level ROI on an AI investment, need to engage in projects of significant scope. And going from realizing there's an opportunity or realizing there's a threat to mobilizing yourself to capitalize on it is a daunting task for enterprise. Certainly one that's, anybody that's got any sort of legacy of success has built-in processes, has built-in systems, has built-in skill sets, and making that leap to be an autonomous enterprise is challenging for companies to wrap their heads around. So as part of the rebirth of Oracle Consulting, we've developed a practice around how to both manage the technology needs for that transformation as well as the human needs, as well as the data science needs to it. So there's-- >> So, wow, there's about five or six things that I want to (Grant chuckles) follow up with you there, so this is a good conversation. Janet, ever since I've been in the industry, when you're talking about AI, it's sort of start-stop, start-stop. We had the AI winter, and now it seems to be here. It almost feels like the technology never lived up to its promise, 'cause we didn't have the horsepower, the compute power, it didn't have enough data, maybe. So we're here today, it feels like we are entering a new era. Why is that, and how will the technology perform this time? >> So for AI to perform, it's very reliant on the data. We entered the age of AI without having the right data for AI. So you can imagine that we just launched into AI without our data being ready to be training sets for AI. So we started with BI data, or we started with data that was already historically transformed, formatted, had logical structures, physical structures. This data was sort of trapped in many different tools, and then, suddenly, AI comes along, and we say, take this data, our historical data, we haven't tested it to see if this has labels in it, this has learning capability in it. We just thrust the data to AI. And that's why we saw the initial wave of AI sort of failing, because it was not ready for AI, ready for the generation of AI, if you will. >> So, to me, this is, I always say this was the contribution that Hadoop left us, right? I mean, Hadoop, everybody was crazy, it turned into big data. Oracle was never that nuts about it, they just kind of watched, sat back and watched, obviously participated. But it gathered all this data, it created cheap data lakes, (laughs) which people always joke, turns into data swamps. But the data is oftentimes now within organizations, at least present, right. >> Yes, yes, yes. >> Like now, it's a matter of what? What's the next step for really good value? >> Well, basically, what Hadoop did to the world of data was Hadoop freed data from being stuck in tools. It basically brought forth this concept of platform. And platform is very essential, because as we enter the age of AI and we enter the petabyte range of data, we can't have tools handling all of this data. The data needs to scale. The data needs to move. The data needs to grow. And so, we need the concept of platform so we can be elastic for the growth of the data. It can be distributed. It can grow based on the growth of the data. And it can learn from that data. So that's the reason why Hadoop sort of brought us into the platform world. And-- >> Right, and a lot of that data ended up in the cloud. I always say for years, we marched to the cadence of Moore's law. That was the innovation engine in this industry. As fast as you could get a chip in, you'd get a little advantage, and then somebody would leapfrog. Today, it's, you've got all this data, you apply machine intelligence, and cloud gives you scale, it gives you agility. Your customers, are they taking advantage of that new innovation cocktail? First of all, do you buy that, and how do you see them taking advantage of this? >> Yeah, I think part of what Janet mentioned makes a lot of sense, is that at the beginning, when you're taking the existing data in an enterprise and trying to do AI to it, you often get things that look a lot like what you already knew, because you're dealing with your existing data set and your existing expertise. And part of, I think, the leap that clients are finding success with now is getting novel data types. You're moving from the zeroes and ones of structured data to image, language, written language, spoken language. You're capturing different data sets in ways that prior tools never could, and so, the classifications that come out of it, the insights that come out of it, the business process transformation that comes out of it is different than what we would have understood under the structured data format. So I think it's that combination of really being able to push massive amounts of data through a cloud product to be able to process it at scale. That is what I think is the combination that takes it to the next plateau for sure. >> So you talked about sort of we're entering the new era, age of AI. A lot of people kind of focus on the cloud as sort of the current era, but it really does feel like we're moving beyond that. The language that we use today, I feel like, is going to change, and you just started to touch on some of it, sensing, our senses, and the visualization, and the auditory, so it's sort of this new experience that customers are seeing, and a lot of this machine intelligence behind that. >> I call it the autonomous enterprise, right? >> Okay. >> The journey to be the autonomous enterprise. And when you're on this journey to be the autonomous enterprise, you need, really, the platform that can help you be. Cloud is that platform which can help you get to the autonomous journey. But the autonomous journey does not end with the cloud, or doesn't end with the data lake. These are just infrastructures that are basic, necessary, necessities for being on that autonomous journey. But at the end, it's about, how do you train and scale very large-scale training that needs to happen on this platform for AI to be successful? And if you are an autonomous enterprise, then you have really figured out how to tap into AI and machine learning in a way that nobody else has to derive business value, if you will. So you've got the platform, you've got the data, and now you're actually tapping into the autonomous components, AI and machine learning, to derive business intelligence and business value. >> So I want to get into a little bit of Oracle's role, but to do that, I want to talk a little bit more about the industry. So if you think about the way the industry seems to be restructuring around data, historically, industries had their own stack or value chain, and if you were in the finance industry, you were there for life, you know? >> Yes. >> You had your own sales channel, distribution, et cetera. But today, you see companies traversing industries, which has never happened before. You see Apple getting into content, and music, and there's so many examples, Amazon buying Whole Foods. Data is sort of the enabler there. You have a lot of organizations, your customers, that are incumbents, that they don't want to get disrupted. A big part of your role is to help them become that autonomous enterprise so they don't get disrupted. I wonder if you could maybe comment on how you're doing. >> Yeah, I'll comment, and then, Grant, you can chime in. >> Great. >> So when you think about banking, for example, highly regulated industry, think about agriculture, these are highly regulated industries. It is very difficult to disrupt these industries. But now you're looking at Amazon, and what does an Amazon or any other tech giant like Apple have? They have incredible amounts of data. They understand how people use, or how they want to do, banking. And so, they've come up with Apple Cash, or Amazon Pay, and these things are starting to eat into the market. So you would have never thought an Amazon could be a competition to a banking industry, just because of regulations, but they are not hindered by the regulations because they're starting at a different level, and so, they become an instant threat and an instant disruptor to these highly regulated industries. That's what data does. When you use data as your DNA for your business, and you are sort of born in data, or you've figured out how to be autonomous, if you will, capture value from that data in a very significant manner, then you can get into industries that are not traditionally your own industry. It can be the food industry, it can be the cloud industry, the book industry, you know, different industries. So that's what I see happening with the tech giants. >> So, Grant, this is a really interesting point that Janet is making, that, you mentioned you started off with a couple of industries that are highly regulated and harder to disrupt. You know, music got disrupted, publishing got disrupted, but you've got these regulated businesses, defense. Automotive hasn't been truly disrupted yet, so Tesla maybe is a harbinger. And so, you've got this spectrum of disruption. But is anybody safe from disruption? >> (laughs) I don't think anyone's ever safe from it. It's change and evolution, right? Whether it's swapping horseshoes for cars, or TV for movies, or Netflix, or any sort of evolution of a business, I wouldn't coast on any of it. And I think, to your earlier question around the value that we can help bring to Oracle customers is that we have a rich stack of applications, and I find that the space between the applications, the data that spans more than one of them, is a ripe playground for innovations where the data already exists inside a company but it's trapped from both a technology and a business perspective, and that's where, I think, really, any company can take advantage of knowing its data better and changing itself to take advantage of what's already there. >> The powerful people always throw the bromide out that data is the new oil, and we've said, no, data's far more valuable, 'cause you can use it in a lot of different places. Oil, you can use once and it's all you can do. >> Yeah. >> It has to follow the laws of scarcity. Data, if you can unlock it, and so, a lot of the incumbents, they have built a business around whatever, a factory or process and people. A lot of the trillion-dollar startups, that become trillionaires, you know who I'm talking about, data's at the core, they're data companies. So it seems like a big challenge for your incumbent customers, clients, is to put data at the core, be able to break down those silos. How do they do that? >> Mm, grating down silos is really super critical for any business. If it's okay to operate in a silo, for example, you would think that, "Oh, I could just be payroll and expense reports, "and it wouldn't matter if I get into vendor "performance management or purchasing. "That can operate as a silo." But anymore, we are finding that there are tremendous insights between vendor performance management and expense reports, these things are all connected. So you can't afford to have your data sit in silos. So grating down that silo actually gives the business very good performance, insights that they didn't have before. So that's one way to go. But another phenomena happens. When you start to grate down the silos, you start to recognize what data you don't have to take your business to the next level. That awareness will not happen when you're working with existing data. So that awareness comes into form when you grate the silos and you start to figure out you need to go after a different set of data to get you to new product creation, what would that look like, new test insights, or new capex avoidance, that data is just, you have to go through the iteration to be able to figure that out. >> And then it becomes a business problem, right? If you've got a process now where you can identify 75% of the failures, and you know the value of the other 25% of the failures, it becomes a simple investment. "How much money am I willing to invest "to knock down some portion of that 25%?" And it changes it from simply an IT problem or an expense management problem to the universal cash problem. >> To a business problem. >> But you still need a platform that has APIs, that allows you to bring in-- >> Yes, yes. >> Those data sets that you don't have access to, so it's an enabler. It's not the answer, it's not the outcome, in and of itself, but it enables the outcome. >> Yeah, and-- >> I always say you can't have the best toilet if your plumbing doesn't work, you know what I mean? So you have to have your plumbing. Your plumbing has to be more modern. So you have to bring in modern infrastructure, distributed computing, that, there's no compromise there. You have to have the right ecosystem for you to be able to be technologically advanced and a leader in that space. >> But that's kind of table stakes, is what you're saying. >> Stakes. >> So this notion of the autonomous enterprise, help me here. 'Cause I get kind of autonomous and automation coming into IT, IT ops. I'm interested in how you see customers taking that beyond the technology organization into the enterprise. >> Yeah, this is such a great question. This is what I've been talking about all morning. I think when AI is a technology problem, the company is at a loss. AI has to be a business problem. AI has to inform the business strategy. When companies, the successful companies that have done, so, 90% of our investments are going towards data, we know that, and most of it going towards AI. There's data out there about this. And so, we look at, what are these 90% of the companies' investments, where are these going, and who is doing this right, and who is not doing this right? One of the things we are seeing as results is that the companies that are doing it right have brought data into their business strategy. They've changed their business model. So it's not making a better taxi, but coming up with Uber. So it's not like saying, "Okay, I'm going to be "the drug manufacturing company, "I'm going to put drugs out there in the market," versus, "I'm going to do connected health." And so, how does data serve the business model of being connected health, rather than being a drug company selling drugs to my customers? It's a completely different way of looking at it. And so now, AI's informing drug discovery. AI is not helping you just put more drugs to the market. Rather, it's helping you come up with new drugs that will help the process of connected care. >> There's a lot of discussion in the press about the ethics of AI, and how far should we take AI, and how far can we take it from a technology standpoint, (laughs) long road map, there. But how far should we take it? Do you feel as though public policy will take care of that, a lot of that narrative is just kind of journalists looking for the negative story? Will that sort itself out? How much time do you spend with your customers talking about that, and what's Oracle's role there? Facebook says, "Hey, the government should figure this out." What's your sort of point of view on that? >> I think everybody has a role, it's a joint role, and none of us can give up our responsibilities. As data scientists, we have heavy responsibility in this area, and we have heavy responsibility to advise the clients on this area also. The data we come from, the past, has to change. That is inherently biased. And we tend to put data science on biased data with a one-dimensional view of the data. So we have to start looking at multiple dimensions of the data. We've got to start examining, I call it irresponsible AI, when you just simply take one variable, we'll start to do machine learning with that, 'cause that's not right. You have to examine the data. You've got to understand how much bias is in the data. Are you training a machine learning model with the bias? Is there diversity in the models? Is there diversity in the data? These are conversations we need to have. And we absolutely need policy around this, because unless our lawmakers start to understand that we need the source of the data to change, and if we look at the source of the data, and the source of the data is inherently biased or the source of the data has only a single representation, we're never going to change that downstream. AI's not going to help us there. So that has to change upstream. That's where the policy makers come into play, the lawmakers come into play. But at the same time, as we're building models, I think we have a responsibility to say, "Can we triangulate? "Can we build with multiple models? "Can we look at the results of these models? "How are these features ranked? "Are they ranked based on biases, sex, age, PII information? "Are we taking the PII information out? "Are we really looking at one variable?" Somebody failed to pay their bill, but they just failed to pay their bill because they were late, versus that they don't have a bank account and we classify them as poor on having no bank account, you know what I mean? So all this becomes part of responsible AI. >> But humans are inherently biased, and so, if humans are building algorithms-- >> That's right, that's right. >> There is the bias. >> So you're saying that through iteration, we can stamp out the bias? Is that realistic? >> We can stamp out the bias, or we can confirm the bias. >> Or at least make it transparent. >> Make it transparent. So I think that even if we can have the trust to be able to have the discussion on, "Is this data "the right data that we are doing the analysis on?" and start the conversation there, we start to see the change. >> Well, wait, so we could make it transparent, then I'm thinking, a lot of AI is black box. Is that a problem? Is the black box syndrome an issue, or are we, how would we deal with it? >> Actually, AI is not a black box. We, in Oracle, we are building our data science platform with an explicit feature called explainability of the model, on how the model came up with the features, what features it picked. We can rearrange the features that the model picked. So I think explainability is very important for ordinary people to trust AI. Because we can't trust AI. Even data scientists can't trust AI, to a large extent. So for us to get to that level where we can really trust what AI's picking, in terms of a model, we need to have explainability. And I think a lot of the companies right now are starting to make that as part of their platform. >> So that's your promise to clients, is that your AI will not be a black box. >> Absolutely, absolutely. >> 'Cause that's not everybody's promise. >> Yes. >> I mean, there's a lot of black box in AI, as you well know. >> Yes, yes, there is. If you go to open source and you start downloading, you'll get a lot of black box. The other advantage to open source is sometimes you can just modify the black box. They can give you access and you can modify the black box. But if you get companies that have released to open source, it's somewhat of a black box, so you have to figure out the balance between. You don't really have to worry too much about the black box if you can see that the model has done a pretty good job as compared to other models. If I triangulate the results of the algorithm, and the triangulation turns out to be reasonable, the accuracy and the r values and the matrixes show reasonable results, then I don't really have to worry if one model is too biased compared to another model. But I worry if there's only one dimension to it. >> Mm-hm, well, ultimately, to much of the data scientists' dismay, somebody on the business side is going to ask about causality. >> That's right. >> "Well, this is what "the model says, why is it saying that?" >> Yeah, right. >> Yeah. >> And, ethical reasons aside, you're going to want to understand why the predictions are what they are, and certainly, as you go in to examine those things, as you look at the factors that are causing the predictions and the outcomes, I think any sort of business should be asking those responsibility questions of everything they do, AI included, for sure. >> So, we're entering a new era, we kind of all agree on that. So I just want to throw a few questions out and have a little fun here, so feel free to answer in any order. So when do you think machines will be able to make better diagnoses than doctors? >> I think they already are making better diagnoses. I mean, there's so much, like, I found out recently that most of the very complicated cancer surgeries are done by machines, doctors just standing by and making sure that the machines are doing it well. And so, I think the machines are taking over in some aspects, I wouldn't say all aspects. And then there's the bedside manners, where you (laughs) really need the human doctor, and you need the comfort of talking to the doctor. >> Smiley face, please! (Janet laughs) >> That's advanced AI, to give it a better bedside manner. >> Okay, when do you think that driving and owning your own vehicle is going to be the exception rather than the rule? >> That, I think, is so far ahead, it's going to be very, very near future, because if you've ever driven in an autonomous car, you'll find that after your initial reservations, you're going to feel a lot more safer in an autonomous car. Because it's got a vision that humans don't. It's got a communication mechanism that humans don't. It's talking to all the fleets of cars. >> It's got a richer sense of data. >> It's got a richer sense of data, it's got a richer sense of vision, it's got a richer sense of ability to (snaps) react when a kid jumps in front of the car. Where a human will be terrified and not able to make quick decisions, the car can. But at the same time, we're going to have some startup problems. We're going to see AI misfire in certain areas, and insurance companies are gearing themselves up for that, 'cause that's just, but the data's showing us that we will have tremendously decreased death rates. That's a pretty good start to have AI driving our cars. >> You're a believer, well, and you're right, there's going to be some startup issues, because this car, the vehicle has to decide, "Do I kill that person who jumped in front of me, "or do I kill the driver?" Not kill, I mean, that's overstating-- >> Yeah. >> But those are some of the startup things, and there will be others. >> And humans, you don't question the judgment system for that. >> Yes. >> There's no-- >> Dave: Right, they're yelling at humans. >> Person that developed, right. It's treated as a one-off. But I think if you look back five years, where were we? You figure, the pace of innovation and the speed and the gaps that we're closing now, where are we going to be in five years? >> Yeah. >> You have to figure it's, I have an eight-year-old son, and I question if he's ever going to drive a car. >> Yeah. >> Yeah. >> How about retail? Do you think retail stores largely will disappear? >> Oh, I think retail, there will be a customer service element to retail, but it will evolve from where it's at in a very, very high-stakes rate, because now, with RFID, you know who's, we used to be invisible as we walked, we still are invisible as you walk into a retail store, even if you spend a lot of money in retail. And now, with buying patterns and knowing who the customer is, and your profile is out there on the Web, just getting a sense of who this person is, what their intent is walking into the store, and doing responsible AI, bringing value to that intent, not irresponsibly, that will gain the trust, and as people gain the trust. And then RFIDs, you're in the location, you're nearby, you'd normally buy the suit, the suit's on sale, bring it all together. So I think there's a lot of connective tissue work that needs to happen, but that's all coming together. >> Yeah, it's about the value-add and what the proposition to the customer is. If it's simply there as a place where you go and pick out something you already know what you're going to get, that store doesn't add value, but if there's something in the human expertise, or in the shared, felt sudden experience of being in the store, that's where you'll see retailers differentiate themselves. >> I like to shop still. (laughs) >> Yeah, yeah. >> You mentioned Apple Pay before. Well, you think traditional banks will lose control of the payment systems? >> They're already losing control of payment systems. If you look at, there was no reason for the banks to create Siri-like assistants. They're all over right now. And we started with Alexa first. So you can see the banks are trying to be a lot more customized, customer service, trying to be personalized, trying to really make you connect to them in a way that you have not connected to the bank before. The way that you connected to the bank is you knew the person at the bank for 20 years, or since when you had your first bank account. That's how you connected with the banks. And then you go to a different branch, and then, all of a sudden, you're invisible. Nobody knows you, nobody knows that you were 20 years with the bank. That's changing. They're keeping track of which location you're going to, and trying to be a more personalized. So I think AI is a forcing function, in some ways, to provide more value, if anything. >> Well, we're definitely entering a new era, the age of AI, the autonomous enterprise. Folks, thanks very much for a great segment, really appreciate it. >> Yeah, our pleasure, thank you for having us. >> Thank you for having us. >> You're welcome, all right, and thank you. And keep it right there, we'll be right back with our next guest right after this short break. You're watching theCUBE's coverage of the rebirth of Oracle Consulting. We'll be right back. (upbeat electronic music)

>> Live from Las Vegas, it's The Cube, covering Magento Imagine 2019. Brought to you by Adobe. >> Welcome to The Cube. Lisa Martin with Jeff Frick, live at The Wynn Las Vegas, for Magento Imagine 2019. This is a really buzzy event. All e-commerce innovation, tech talks, with about 3,500 folks, and we're excited to welcome to The Cube Tina Mulqueen, CEO of Kindred PR Marketing Agency as well as contribute with Forbes, Digital Trends, expert on e-commerce, I would say. Welcome to The Cube. >> Thank you so much for having me. I'm happy to be here. >> So we were talking about influencer marketing before we went live. And you have been doing, been working in that kind of before it was even a concept. We were just saying how much marketing has changed in the last few years alone, and how brands have had to to survive and be profitable, evolve with that. Give us a bit of a perspective, first on kind of Kindred PR, what you're doing, how you got involved in influencer marketing. >> Sure, so I was really fortunate to have some great mentors early in my marketing career that kind of ushered me along in the right direction and said hey, I think we should really pay attention to this whole Twitter thing and what's happening with these real, everyday people that are amassing a following on Twitter, and that's really where it started was on that platform. So I ended up on a team for CBS that did some of the influencer marketing for Vanity Fair and for their coverage of The Insider and Entertainment Tonight, and we would work with them to get event coverage to trend online. And as you mentioned, that was before, really, we knew what influencer marketing was. It wasn't really, it didn't have to a name, so to speak, at that time. And so I learned a lot from then, and we have kind of come full circle with influencer marketing, where it, I was at first working with these sort of micro influencers, as we would call them now. And then it was a lot of brands working with more of the celebrity influencers, like the Kim Kardashians of the world, and now it's gone back to brands are really interested in these micro influencers again because of the concept of authenticity, which is a big one right now, that marketers are paying attention to. >> Exactly what I was going to say. >> So how do they dance around the authenticity? It's such an interesting and knife edge, right? Because you want people to promote your products because they like them, and that's the original celebrity endorsement back in the early days, right? People actually did use the product that they endorsed. But now you get paid endorsements, and people can see through that. At the same time, it obviously has some results, or people would not continue to invest, and now it's come full circle, whereas you said because of the internet, I with some particular interest can reach a huge number of people around a really small interest set, because of the distribution of the internet. >> Right. So what's interesting is, influencer marketing, when we first really started talking about influencer marketing, we treated it as word-of-mouth marketing. And it had some incredible benefits over some more traditional kinds of marketing because it was word of mouth. And then because influencer marketing had a lot of investments, brands were investing heavily in influencer marketing, and we were dealing more with celebrity influencers, consumers became smarter as well during this time. And then they started looking at these celebrity endorsements and realizing that these are not real endorsements. And so I think that's where we're seeing this shift back to micro influencers, and people that are really using the products that these brands are touting. >> But how does a brand, how do they engage with the micro influencer? >> Actually, there's a really great case study that I always use as an example of this, and it's actually BECCA Cosmetics, which, BECCA's one of the, I think the number one, sales cosmetic line in Sephora. And they reached out, I think it was about a year ago, maybe a couple of years ago now. They reached out to an influencer because they realized that their website traffic was going up every time a certain influencer would go live on YouTube and was using their products. So BECCA reached out to this influencer that was organically using the products, and collaborated with the influencer to create a line of products of her own. And that really, I think they sold out within the first hour when they actually went live with the product line. So that's a great example of how to engage with an influencer that is organically using your brand, and making sure that you're also including their audience, in, like, the iteration of the product, because then the audience of the influencer is also invested. >> And what defines influencer versus a micro influencer? I imagine the sheer volume of followers, but there's got to be more to it than that, because there's this really cool example that you gave, what BECCA Cosmetics found was much more probably authenticity. So talk to us about not just the number drivers there, but some of the other, I mean, it's one thing to be able to blast something to 100,000 people. It's a whole other thing to actually be able to engage their followers and convert it to a transaction. >> Right. So I think that often when we hear brands talking about micro or macro influencers, they really are talking about the number of followers, but I think you bring up a really great point with respect to that level of engagement of that following and how to really tap into somebody that is engaging their following. So I think brands are going toward actual experts in their field, or actual experts in the product line in a bigger capacity now because they know that what they say is going to be more meaningful to their audience and more engaging to their audience, rather than based on number of followers alone. So there's a lot of different things that are going into play to create a better context for marketing. >> I'm curious how other metrics have evolved beyond just the transaction. So there's the followers, and then, you know, there's obviously transactions, as you said, there's website traffic. But as people, as brands are starting to realize that engagement, ongoing engagement, interaction with content is part of the relationship, separate from and a value to the actual transaction. How have their metrics changed? How are they reviewing these programs? I'm sure a lot of it at first was, "Well, we hope it works, we think it's working." But how has that matured over time? >> It definitely has matured, and there are some platforms out there that will try to quantify influencer marketing in different ways than we've seen in the past. It's gotten a lot more sophisticated. That said, marketers still have a real challenge ahead of them in terms of quantifying their efforts in a meaningful way, because it's still hard to put a number to brand sentiment. And that's a lot of what influencer marketing is. >> Right. And is it, from an investment point of view, I always think of people with a large bucket of money, right, they put a very small piece in their venture fund, which has a real low probability of a hit, but if it hits, it hits big. And when they're budgeting for the influencer program, is it kind of like that? You know, we've got this carve-out that we are not quite sure what the ROI is. We think it's important. We don't want to miss out. Versus, you know, what I'm spending on print or what I'm spending on TV, or what I'm spending on kind of traditional campaigns. How are marketers looking at that within their portfolio? >> It is a great questions, and I think that marketers know that they need to invest in influencer marketing, so we're seeing an influx of investment coming in through influencer marketing. That said, I've been in a lot of conversations with brands that are talking about, do we go the macro influencer route or do we go with the micro influencer route? And right now I think that brands are starting to realize that if you get a lot of voices or a number of voices that are sharing the same sentiment and that are able to feed off of each other with respect to the conversation and amplify each other because even if you have micro influencers with smaller following count, they're going to amplify each other's content, and that ends up in the long run, as we talked about, being more authentic. So that's where a lot of the conversations are going right now in terms of how to spend that influencer marketing budget and weighing the pros and cons of those different options. >> Well, marketing is and should be a science these days. There is so much data about all of us from everything we do every day that brands need to be able to evaluate that, leveraging platforms from Adobe Magento for example, going back to the BECCA Cosmetics and thinking well, if they evaluate these micro influencers and the lift and the traffic that they get, if they're actually using that data appropriately then that should be able to inform how they're actually carving up their investment dollars into which influencers, macro or micro, they know that is going to make the biggest impact on revenue. So it behooves marketing organizations to become scientific and actually use all this consumer data that we are all putting out through our phones, on social devices, constantly. >> Absolutely. I think it's a great point. And I hear often from clients too that they have, they've invested in these platforms that will sort of try to analyze the data, but they're not doing anything with that data. So a lot of e-commerce merchants and retailers, if you don't have a strategy on how you're going to implement that what you're learning from your consumers, then it ends up falling flat. >> What's the biggest surprise you hear from marketers today in terms of this influencer marketing? Are they confused, they're getting it, are there any, I mean you had one really good success story, are there any other, you know, kind of success stories you can share that this is a very different way to get your message into the marketplace? >> You know, one thing that I think people should do more of, that it kind of surprises me that we aren't seeing more of is using media as a channel for e-commerce merchants to have an affiliate strategy. So basically utilizing influencers in collaboration with a media channel to be able to have a new revenue stream. I think that that's something that we haven't seen very often. It's something that when I was working as the CMO for a public trading company called Grey Cloak Technologies, we worked with Sherell's, which is a company that we were acquiring at the time to consult with Marie Claire on how to incorporate influencers into their e-commerce strategy as a publisher. And that's something that I think that people could take more advantage of. >> Even just with affiliate codes or coupon codes and those types of things? They're just not really executing on it that well. >> Right, right. And I think that part of it is a technological component, like the technology isn't quite there to be able to implement, well, to be able to implement that on a wide scale. Like Marie Claire, Sherell's ended up creating the technology for them to be able to incorporate influencers into their e-commerce strategy. But I think that we're going to see more of that. >> Right, because for the influencer, that's one of many sources of revenue that they need to execute on if they're actually going to build, you know, a lifestyle business around being, you know, quote-unquote influencer. They need that affiliate revenue on top of their advertising revenue and all these other little pieces, selling t-shirts, etc. >> Right, right. And we're seeing some companies that are coming to the table to try to provide solutions. One company that I've been watching for a while is called COSIGN, and their platform basically allows influencers to integrate on the platform and link things through social media so that people can buy through a picture, on Facebook for example. So I think we're going to see more of those types of technologies as well. >> Let's talk kind of on the spirit of trends and some of the things that you are seeing. There was this big trend in the last few years of everybody wanting to be able to, we can get anything through Amazon, right? And we can get in a matter of hours. But looking at, and seeing some big box stores that did not do a good job of being able to blend physical, digital, virtual, all these storefronts. What though are you seeing in terms of companies, maybe enterprises, needing to sort of still have or offer a brick and mortar experience? Like we were talking to HP Inc. this morning, he was on stage, and this click and collect program that they launched in APEC where depending on their region, people need to be able to start and actually transact online, but actually fulfill in store. In terms of like, maybe, either reverse engineering online to brick and mortar or hybridizing the two, what are some of the trends that you're seeing that businesses really need to start paying attention to? >> Sure, so I think that omnichannel has been a buzzword for some time, and the way that marketers are looking at omnichannel now, or the way that retailers are looking at omnichannel now is a little bit different. At first, when we started talking about the concept of create this sort of seamless interplay between brick and mortar and online storefronts, it was about taking the brick and mortar experience and putting it online. And now I think marketers are getting better at realizing that those are two completely different channels, and your customer's in a different place in both of those channels. So you need to give them an experience that is relevant for the channel, and it can be totally different than what we're used to in traditional retail stores. But brick and mortar obviously does have a place. We're seeing Amazon come out with their own brick and mortar locations, and we're seeing different e-commerce startups have brick and mortar locations and be very successful with them too as an e-commerce first storefront. So there's definitely a place for brick and mortar. I think people will always have to shop in brick and mortar storefronts, although we obviously are going to get more sophisticated delivery options, and that's coming as well. But I think that it's really an interplay and it's understanding what the channels are and where your consumers are at in that space. >> And then the whole next generation of that, which we're hearing about here, like shopping inside of Instagram. So now as opposed to a destination or I'm going to some place to buy something, whether it's online or a store, now it's actually just part of experiencing the media, as you said, and oh by the way, while I'm here, that looks interesting, I'll take one of those as well. Whole different level of experience that the retailers now have to support. >> Right, absolutely. There are other technology platforms too that, like one of them is basically producing video content that you can scroll over, or let's say you were just watching a commercial on your television, or maybe it's not even a commercial. Maybe it's like real long form content, and if you scroll over a product in the image, you can purchase it out of that video. And so these things are coming as well. It's really an exciting time. But it's an exciting time to be creative as well, because you have to have some creativity behind these strategies in order to make an impression on the consumer. >> It's exciting and creepy at the same time. (Jeff laughing) I don't know if my wallet can handle that. But we'll see. But one of the things I was wondering, when you were talking about, for example, Amazon going, starting as this online mega store and now having brick and mortar stores, the acquisition of Whole Foods. I can't go in there and shop without being asked if I'm a Prime member. But what are some of the sort of foundational customer experience expectations that, because I would think personalization would be kind of a common foundation that whether I'm shopping online with whatever, I want whoever I'm buying from, especially if I have a history, I want them to know what I've bought before, maybe my average order value, to be able to kind of incentivize loyalty. But I probably want the same thing if I'm in a brick and mortar. Are you seeing some sort of key foundations that businesses, whether they do one, the other, or both, need to put in place that can span both? >> Absolutely. So I think it's a great point. I think personalization and the experience. Obviously we're hearing so much about experience in terms of e-commerce, but in brick and mortar stores in particular. But I think that the personalization piece is such an important one. But I also think that it's now getting to where we need to personalize more on the marketing for no matter what channel it is. So you need to bring that physical experience with the customer to your e-commerce efforts as well so that you can, for example, if you're going to email market to me, I want it to be relevant. I want to know that you have been paying attention to my shopping habits, and it's kind of a fine line with respect to data, but if you're going to be using my data, I want to make sure that it's useful to me and it saves me time. >> And it kind of goes back to a point Jeff and I have heard a number of times today, and that's validating me as a consumer that you understand that what I'm interested in that you have to offer, you understand it, it's important to both of us. Well Tina, I wish we had more time to keep talking with you, but we thank you so much for joining us on The Cube this afternoon and talking with us about some of the things that you're seeing, your experiences. And now I know the difference between an influencer, macro and micro, and why they can be so important to brands of any size. So thank you for your time. >> Thank you so much for having me. >> Our pleasure >> Thank you. >> For Jeff Frick, I'm Lisa Martin, you're watching us on The Cube live from Las Vegas at Magento Imagine 2019. Thanks for watching. (upbeat digital music)

>> Narrator: Live from Las Vegas, it's theCUBE, covering Magento Imagine 2019. (fizzing) (upbeat music) Brought to you by Adobe. >> Hi, welcome back to theCUBE. Lisa Martin with Jeff Frick at Imagine 2019, the Wynn, Las Vegas, with about 3500 customers, lots of partners, lots of developers, a lot of energy here. And speaking of energy, we have Jason Woosley, VP of commerce at Adobe. Jason, you came onto the stage this morning from the clouds suspended. Talk about energy. >> It was a lot of energy, and there was a message behind it, right? (clears throat) I mean we really are talking about our Cloud penetration and how that is the future. So, you know, I got to do something really cool and check something off the bucket list where I actually did descend from the sky onto the stage. It was the best Imagine entrance I've ever done (Lisa laughing) and really does talk about, you know, how important our Cloud Strategy is. Thanks for having me on, by the way. >> Absolutely. >> Our pleasure. >> So, a lot of energy here, again, community, community, community. We go to so many shows, so many people are desperate to engage developers. And you guys have that in your core. It's been there from day one. Continues to be such an important part of who you are as well as the road forward. >> It's the reason for why we are where we are today. I mean bar none, right? Our community, this eco system. And it's not something you can buy. It's not something you can even intentionally build. You have to nurture, you have to create a platform that speaks to a large audience, and then you've just got to make sure that you're treating those developers and your partners really, really well, empowering them to really differentiate that experience at the last mile. And, you know, it's a flywheel effect. You end up with this incredible community that's anxious to contribute back into our code base and they have made, what you see at this conference is a result of that community. It's not anything that Magento could do. It's not anything that Adobe could do. It is just something that has to organically happen, and then you have to nurture the heck out of it. And that, that's really what we've done. >> And this is a community that you say has grown organically to several hundred thousand people who I feel like to say that they're influential to Magento, the technologies is actually an understatement with how much, how, again, I think influential's the wrong word. They're stronger than that. >> They're absolutely core to it, right? I mean they're an extension of our development methodology. You know, I like to think about, you know, I run engineering as part of my organization, and everybody in my group is customer-facing. Just like everybody in out community is customer-facing. And so we've tried to tear down the walls that separate our community members from our internal core engineers, because it creates this incredible diversity of perspective that you can't find anywhere else. I mean, no matter how much I invest in broadly diverse engineering teams across the globe, 300,000 engineers, they call themselves Magento developers, don't take a paycheck from Adobe but contribute back to our code base, influence our road map and really show us the way. It's an incredible phenomenon. >> In the last year since the announcement of the Adobe acquisition and the actual completion of that six, seven months ago, how has that community reacted, strengthened? What have been some of your surprising observations about the community's strength? >> It is surprising, and I'll tell you why. I think we came into the acquisition with a lot of apprehension, right. There was a concern that, you know, Adobe's too big. They're too corporate. They don't really love Open Source. All untrue, right? Adobe has incredible Open Source initiatives already inside, but you don't here a lot about it. And so, our community, I think, is it's a little bit concerned about, you know, does the level of investment go down? Does all of our ability to promote that product, does that, do we start to back off of that? And of course, we have not done that at all, and in fact, what we've seen is that our community loves the Adobe acquisition. They see opportunity just as clearly as we do. We have more than triple-digit growth in the number of community contributions coming in to us since the acquisition last year. It is a clear sign that the ecosystem is fully on board with where we're going. >> Right. Well clearly the Adobe Suite provides so much gunpowder to power the commerce that's been at the core of Magento from the beginning. I mean it almost begs the question, why didn't this happen a long, long time ago? >> I think there's something to be said about that, and, but you know what, it took Adobe a while. They picked the right platform. We're very confident of that, and, you know, their investment in community is actually paying off on the Adobe side, right. When you think about digital experience products, they (Adobe) are now more active than ever in open source projects. We've got, you know, folks from Adobe Experience Manager that are writing code and contributing to Magento, which is, it's absolutely terrific. And they're now talking about how do we get the ability to kind of create that contribution mechanism and at least create a platform concept where, you know, everybody plays. It's an equal playing field. You can serve us small, you can serve us large. And it just brings everybody together to solve these common, complex problems that are joint merchant's face. >> I don't know how many times you've been on stage in the last few days but, a couple. But one of the things you really, you know, (pounding) you didn't pound on the table but you basically pounded on the table, is that we are still, totally, 100% behind SMB. >> Jason: Absolutely. >> It's our core. We're not giving that up. >> We built this market together, right. This was what made Magento what it is. It's where we play the best. We know it better than anybody else in the industry, and we're not retreating. We're doubling down. We've got ground to take in the mid-market, and I can't wait to do it. >> Right, but what's wild is you're enabling the mid-market, to compete with the tools of the big guys. So, announcements are on the integration with Amazon, announcements are on integration with Google. So it's kind of an interesting place for small retailers, small merchants. They've got to compete in this world, so you're really giving 'em an aid, an opportunity to both play in what might be a big competitor as well as leverage that ecosystem and assets as well as doing it within their own brick and mortar or their own site . >> And that's a terrific point. I think one of the reasons we do that is we've seen consumer expectations rising through the roof, right. I mean, everything from, you know, fast shipping is now one-day. And it wasn't very long ago that fast shipping, if you could get it within a week, that was pretty darn quick. >> Jeff: Right. >> But now fast shipping is one day, and that's across the board. Consumers are expecting frictionless payment. They're expecting, you know, buy online, pick up in-store, omni-channel capabilities. Really all of these capabilities. And a consumer, a shopper, really doesn't care whether you're big or small. What they care about is the experience that the consume when they interact with your brand. And so, bringing the tools of the enterprise to the mid-market allows them to compete on a more level playing field, and that's really where you generate all those great innovation. And that's where you see, you know, these smaller merchants that are really able to, you know, drive into something that, you know, may not have been a core target for some of the larger enterprises, but they find an niche and are able to deliver, but they have the same personalization needs. They have the same logistics needs. All of that has not changed just because they're a smaller organization. And so it's really on us to be able to provide them the tooling and the access to the capabilities that let them compete with the larger merchants. >> No, 'cause you're right. As consumers, which we are every day, we don't care if they're a big or small company, or what technologies that, well, no we do care, to a degree, that we can start something from a mobile phone, have a great seamless experience >> Jason: Yep. >> that's not gonna cause me to churn, because I'm not going to be able to find what I want. I want it to be personalized. I want them to know enough about me in a non-creepy way, as you say. >> That's right. If it's good, it's magic. (Lisa laughing) If it's bad, it's creepy! >> Right, regardless of-- >> That's fair. >> That's for recommendation engines. >> Yeah, no, that's fair. >> And expect that they have what I want. But also what you're doing now is giving these SMBs, these smaller organizations, the ability to harness this sort of symbiotic data power between Adobe and Magento for advertising, analytics, marketing, commerce, to be able to have that wealth of knowledge to make that experience exactly what that consumer expects. >> Exactly right. I mean it's about bringing behavioral data and the transactional data together to really get a 360 degree view of individual customers. And guess what? There's too much raw data there for Excel to ever be able to tell you anything. You've got to rely on things like artificial intelligence and machine learning so that things like Adobe Sensei to really derive insight out of that mass set of data. But that's the way you create those personalized experiences. You have to employ those techniques to get there. >> Right, I just wanted to unpack the Sensei down-spin a little bit, 'cause I think that's really interesting. You know, AI's been a great buzzword. We see it in a lot of places. You know, our Google email now automatically figures out what we want to reply to our email. But it's the integration of AI in applications is where we're really starting to see it come to market early, and this is a great example of, you know, using the Adobe AI inside of Sensei, on specific parts of the application to deliver a better application, a better consumer experience. >> And we've got a great roadmap for rolling out Artificial Intelligence capabilities to Magento commerce. It's one of the largest value adds that we'll do over the next 12 months, is really bringing those capabilities around recommendations, around experience personalization and experience targeting. Around A/B testing. And then you think a little bit into the future, and suddenly you're looking at an AI that can give you pricing recommendations and campaign recommendations, and, you know, that is a, that's a world we cannot wait to really explore fully in the commerce world, because I think that those are the tools, you know Amazon applies a lot of dynamic pricing techniques right now. It's a really expensive process. I don't know a lot of small merchants that have access to the tools to do that. We're bringing those tools to small merchants, and that's gonna change the game fundamentally, I believe. >> And a way that they can do it, almost themselves, rather than having to have a team of resources, which a small business doesn't have. >> And that is the name of the game for small business. You can't require them to have a data science team. You can't require them to have an IT staff or a Web development team. You gotta give them everything they need so that they can focus on retail, what they know best, merchandising to their customers and, you know, managing their inventory, driving up the correct margins and then making sure that they're able to grow the lifetime value of their customers, right? That's the Holy Grail for retail is when you can actually optimize against lifetime value. Because it's the number one thing that all merchants are chasing. >> Yeah, 'cause you had the guy on the keynote yesterday. I'm not in the demographic. I'm trying to remember the name of the-- >> Oh, Troy, Troy Brown from Zumiez! >> From Zumiez, yeah. >> Yeah. >> I thought it was just really interesting, you know, kind of re-thinking retail, right? Retail is not dead, but it's different, and you have to be different. And really to see how they have kind of taken their concept I thought it was pretty interesting, especially around the fact that he has no more fulfillment centers, he said. But basically, they're fulfilling from the store. They want to engage you in the store. It's a convenient thing. Especially now we see Amazon packages are all gettin' stolen off of doorsteps. But, you know, enabling them to be creative around their customer engagement, not necessarily worry about how to run a bunch of A/B tests. They let you do that complicated stuff. >> Let us take on all of the complexity, and then they can actually benefit from the insights derived from that. And what Zumiez have done, it's a phenomenal story, right. I mean, you're going away from this centralized warehouse concept, to really turning all of their stores into distribution centers, right? 704 or so, brick and mortar-strong where, you know, they now have merchandise close to their consumers. They have, you know, the ability to do showcasing, buy online, pick-up in store, all of the omni-channel techniques that are grabbing so much traction right now. And Zumiez has really capitalized. >> Jeff: Right. >> They've done a terrific job, and it's great seeing it come from these really innovative retailers, right? I mean, that show last night with Zumiez was absolutely, you know, fantastic. Their culture is super unique, highly energetic, but they're driving technology forward in a way that you might not expect from a skateboard apparel shop. >> Right, well, they're making Champion cool again. It came out of the Champion, and it was in the demo. I'm like, I didn't know Champion was a cool brand. >> Apparently, it is cool now. >> Jeff: It's cool now. >> You and I are both out of that demographic, (Jeff laughing) but it is a very good story. >> One of the things that we're hearing and seeing is that we talked about personalization and that this expectation, that as consumers, we bring to everything we buy, whatever it happens to be, but also, this sort of, looking at Amazon as an example, of going to brick and mortar from purely online, the acquisition of Whole Foods, people still wanting to have that human interaction. We talk about it all the time when we talk about AI, is that pretty much the common thread is yes, AI, and maybe yes, online to a degree, and then there's still that need and that demand for that personal face-to-face or maybe voice-to-voice interaction. >> Yeah, well, you know, its really for me, it's about taking that brand, you know, experience and making sure that it's resonating across all of your digital properties as well as all of the physical properties, right. It is about really leveraging. My brand experience is consistent across every place that I come encounter my customers, and I'm ready to transact anytime my customers are ready to transact. And when, you know, talking about Amazon. we've announced some really cool stuff this Ad Imagine on Amazon, a partnership. where Amazon sellers can now have a branded storefront on Magento. This is allowing folks that have done a terrific job selling in the market place, where you don't have a lot of opportunity for experience differentiation on the amazon.com site. >> Lisa: Right. >> And it's a terrific marketplace. More than 50% of product searches are starting on Amazon now. So it's a reality that retailers need to find a way to come to grips with. >> Jeff: Right. >> And what I'm really excited about is that those merchants that are doing really well on Amazon now have a new channel where they can create these branded experiences and really start differentiating themselves from their competitors. It's going to be a terrific story. It's Branded Storefronts for Amazon Sellers is the name of the offering. And its going to change the game for folks that have been exclusively Amazon, maybe thinking its too hard to go get an online presence that actually represents my brand. Now its a piece of cake. They've got a clean path to get there, and the capabilities go both ways, right? We also announced Amazon sales channel for Magento commerce that allows you as a branded merchant, to go and participate on the Amazon Marketplace and have full control over your inventory, your orders and all of your catalog. >> It's so funny, you know, we talk about experience but so much of retail execution is actually inventory execution, right? >> [Jason} That's Right. >> It's inventory management. That's where all your money sits. You can get it real upside down really quickly if you're not managing your inventory. And if you don't have the right amount of inventory, especially as you say with same-day delivery now being an expected behavior. And so to add the sophisticated tools on the back and to manage that inventory across that broad, kind of distribution plane, if you will, with all these different points of engagement is so critical to these guys to have any type of chance of success. >> Yeah, it is. It's absolutely critical, and we've also got a Magento order management product that specializes in sort of global inventory control. We've made terrific investments there to bring new capabilities to make sure that those omni-channel aspirations are not something that a merchant has to go invest a whole lot of money and change in their systems. I think it is interesting to think about when you talk about how B2C is really bleeding into B2B, right. As supply chain management, you know, 70% of our B2C merchants, self-described, actually engaged in B2B workflows, and almost all of our B2B-only merchants are really looking at how do I go B2B to C? >> Jess: Right. >> So there's this really great platform play happening, and the fact that Magento commerce and Adobe commerce Cloud can serve us B2B and B2C and all the hybrids in-between really puts us in a differentiated position and helps merchants not have to go invest in multiple platform, multiple maintainability and then find some way to reconcile the inventory between the two. >> Right, and we had a quote earlier today. I can't remember who said it, but I thought it was great where, you know, no longer is the actual transaction the destination. Right, but now you're bringing the transaction to, you know, kind of the journey. It's a very different way to think about a traditional funnel. It isn't the traditional funnel that you work your way down to the end. Now you're inserting commerce opportunities, >> Jason: Yep. >> engagement opportunities all along kind of this content flow. >> We kind of teased ourselves, right, We kinda lied to ourselves and said that, you know, this is a linear journey. And we've all bought into it, right. You know all the steps, right. It's a discovery, awareness, I mean all the way to post-purchase. Its not linear. People move in and out of each of those sections, and so being able to transact where the customer is ready to transact is critically important >> Jeff: Right. >> and then understanding that the post-sale service is the key to lifetime value. That's the other major learning that we're trying to take away from this. And it's why it's important to be at every point your customer is. >> Yeah, it's interesting, 'cause especially with these things, because you don't sit down to work on your phone like we sat down to work at these things. >> Jason: That's right. >> And so your attention, >> Jason: works coming to you. >> it's coming to you, and its coming in little bits. Oh, and by the way, there's a whole bunch of notifications coming on that can pull you away. >> Jason: Yeah. >> So they're very different challenges in terms of actual engagement when this is the primary vehicle. >> And increasingly, it is the primary vehicle, right? >> Jess: Absolutely. >> More than 50% of traffic to retail, e-commerce site is generated from a mobile phone, and there are emerging markets where that is the only internet-connected device, and so it's the standard. You absolutely have to take mobile very seriously. There's a great set of technologies coming online to help us get there. It's called Progressive Web Application. It's going to change the game on how mobile is treated as a device, and in fact, it gets rid of the need for discrete native applications. So instead of having an IOS app, an Android app, a desktop storefront, a mobile storefront and maybe a tablet storefront, plus your online brick and mortar, now you can actually say, my digital properties are serviced by one set of technology. And that way, when I make a change to one, it shows up in everything. I don't have all these difference code bases to maintain. It's a total cost of ownership, and really, a time-to-market play >> Lisa: I was gonna say, >> across the board. >> faster time-to market for sure. >> Absolutely. Yeah. >> With far less resources. >> Well, and bringing it so that you really have to invest in allowing your merchandisers to merchandise on your digital properties, right? If there is an engineer sitting between your merchandiser and the customer, that time lag and even just trying to get it done, there's so much frustration there. So creating these self-service tools that really allow non-technical merchandisers to go in, make adjustments to how they're selling products across all those channels very, very easily and in one place, that's gonna return a ton of value to our merchants. So its another thing that we're super excited about. >> No, you deliver that consistent experience that the consumer is expecting, and then, we were talking to PayPal earlier, start to help companies close that revenue gap of getting them from mobile to, you know, wanting to transact and making that whole process seamless. >> There's a nine billion dollar opportunity in closing the mobile gap. When you think about abandoned cards and folks that begin the checkout process for whatever reason, likely they get frustrated and don't want to type in their credit card number or don't want to type in their address, and then they move to another device or another store that's doing checkout in a more frictionless way, the nine billion dollar opportunity if you close that. >> Wow, that's huge! >> So its incredibly important. >> It is incredibly important. Well Jason, we wish we had more time, but we thank you so much for stopping by theCUBE and talking with Jeff and Me. Such an exciting time. Sounds like developers are feeling embraced. The community is happy. Customers are reacting well. So we can't wait to hear whats next, next year. >> This is the best place to be in the world in commerce. Thank you guys so much for having me on. It's always a pleasure, and I've enjoyed it a lot. >> Oh, our pleasure as well, Jason. >> Alright, thank you, guys. Thanks, Jason. >> For Jeff Frick, I'm Lisa Martin at Imagine 2019 at the Wynn, Las Vegas. Thanks for watching. (upbeat techno music)

>> From Boston, Massachusets it's theCube. Covering LiveWorx 18. Brought to you by PTC. >> Welcome back to bean town, everybody. This is theCube, the leader in live tech coverage, and we're covering LiveWorx, the three day conference hosted by PTC. We're at the BCEC, which is kind of the Starship Enterprise. I'm Dave Vellante, with my co-host Stu Miniman. As I say, Cube one day coverage of this three day conference. Maciek Kranz is here. He's the Vice President of Strategic Innovations at Cisco. Maciek, thanks for coming on theCube. >> Thank you so much for having me. It really looks like a cube. >> Usually we're out in the open, but they've put us here in a cube, which is great. Of course we were at Cisco Live last week. You were there, it was an awesome show. 27, 28 thousand people. A lot of the innovations that we're talking about here, you guys, you know, at Cisco, are obviously touching upon. Whether it was blockchain or the edge. May I ask you, innovation's in your title. What are you doing here at this conference? >> Basically we're on the mission to make sure that every company, large and small, whatever the industry you're in, gets started on the IOT journey. All of us here, we were talking about it last week at Cisco Live, we are sort of on the mission to make sure that everybody knows how to do it, how to get started, how to go through the journey. So I'm here to promote the cause. >> You had posted a blog a little bit ago on LinkedIn. Check it out, if you go to Maciek's LinkedIn profile you'll see it. Five myths around IOT, and I thought it was quite instructive. I'm going to start with the middle of it, which is IOT is this one big market, and we've been talking about how it's a trillion dollar market. It's almost impossible to size. It's so fragmented, and bringing together the operations technology and information technology world, and there's the edge, there's the core, there's hardware, there's software, there's services. How should we think about the IOT, obviously not as one big market as you pointed out in your blog. >> Right, and you actually nailed it. When you think about sort of a traditional way that technology companies think about the market, it was sort of model of just get a billion people to get on your platform and the good things will happen. Well in the IOT space, as you pointed out, it's a very fragmented market. So you basically need to have two strategies. You either become a horizontal specialist and then you integrate with a vertical specialist to develop a joint solution, or you focus on use case and you focus on one market, and you go deep and focus with customers. So from that perspective the approach is different, but in a nutshell to be successful in this space, it's not only about technology, it's about ecosystem. It's about building the coaliltion of the willing, because at the end of the day, the customers want solutions to their problems. And they don't want to just buy your technology, they want to work with you on developing solutions that drive business outcomes. >> Maciek, one of the things that's been interesting to watch is that people want to try, and they want to try faster. One of the big benefits of public cloud was that I have this sandbox that I could throw some people at, have a little bit of money, and try things and fail and try again. One of the concerns I have when I hear things like PTC and Microsoft get up on stage and say, "It's going to take 20 to 25 partners to put this together." When I hear that it's fragmented, it's going to take time, it's going to take money, help us. Are there are ways I can start playing with things to understand what will and what won't work for my environment, or is this something that I have to throw a million dollars and group of people for a year and a half on? >> It's actually a great point, and it's another, I would say, misconception, which is I need to go deep, have a sort of a big strategy. One of the things that I talk about with the customers is, yes, dream big but start small. So yes, have a sort of a big vision, big architecture, but then focus on a first project, because it's a multi-year, multi-phased journey. So from that perspective, you know, at Cisco we have roughly 14,000 customers that already got started on this IOT journey, and the use cases that we've seen sort of are in four different categories. First one is connect things, so connecting your operations, the second one is remote operations, the third one is predictive analytics, the fourth one is preventive maintenance. So don't be a hero, pick one of these four use cases, try it out, then do a ROI on this, and if your ROI is positive then do a next, maybe more sophisticated, more adventurous kind of a project down the road. So pace yourself. >> This is our 9th year doing theCube, and the one thing we've learned about information technology, operations technology, is it all comes back to data. And you pointed out again, you pointed it out in your piece, it's not just about connecting, it's about the data. So let's talk about the data, the data model. You've got edge, you've got core. You've got this really increasingly complex and elongating data pipeline. You've got physics, you've got latency. So what's your perspective on the data, how that's evolving, and how organizations need to take advantage of the data? >> Dave, I think you nailed it. It may come across funny because I work for Cisco and we connect things, but if you think about the first wave of internet, the main purpose of the devices and the way we were connecting them, was basically for you and I to get access to each other, to get access to the online data, to the online processes. The main purpose we connecting IOT devices, so that they can generate the data, and then we can analyze that data, turn these systems into solutions to drive business outcomes. So from that perspective we're actually seeing a big shift in the sort of data model, and it requires flexibility. Traditionally, we talked about cloud, right? In a cloud we usually see the use cases that require a processing of a lot of data, sort of in the batch possessing mode, or for example if you want to connect a bunch of vending machines, you can connect them directly to the cloud, because these machines actually send only very few packets and they send them very infrequently. Basically saying, "Hey, come on over "and replenish a bunch of supplies." But if you look at connected vehicle, if you look at an oil rig, in the case of oil rig, there's let's say a large one that has 100,000 sensors. These sensors generate a couple terabytes of data per day. You can't just send this data directly to the cloud through the satellite connection, right? You have to process the data on the oil rig based on the policy coming from the cloud. So from that perspective we've seen that there's a need for a more flexible architecture. We call it Fog Computing, which basically allows you to have flexibility of extending the cloud to the edge so you can process the data at the edge. You can execute on the AI functions at the edge as well. So that's one of the big architectural shifts that we've seen with IOT as well. >> Maciek, one of the opportunities of new architectures has been to do a redo for security. When it comes to IOT, though, there's a lot of concern around that, because just the surface area that we're going to have, the devices. Talk to us about how security fits into IOT. >> Yeah, it's hard to talk about IOT without mentioning security, right? And we obviously seen over the last two years a lot of press around IOT denial of service attacks and so forth, and for me I think the silver lining out of all of this news is that, first of all, that we have seen the vendor community finally taking IOT security seriously. So all the security vendors are actually investing in IOT security now appropriately. We now working together as an industry on standards, on interoperability, on sort of come on architectures, even with the device vendors who traditionally didn't pay much attention to security as well. Sort of like what we did with wifi, you remember, about 15 years ago but at a much greater scale. So the vendor community's focusing on it, but more importantly also the businesses are moving from what I would consider sort of a... I would say that kind of a denial. Hoping that their plant is not connected to the outside world and that it's secure. Moving down now to the much more modern model, which is basically a comprehensive architecture working with are-see-sos, across the enterprise, focusing on before, during, and after. So IOT now is being integrated into a broader security architecture, and IT and OT are working together. So yes, there is a concern, yes. There are a lot of events hitting the news, but I also think as an industry we're making progress. >> Just to follow up on that, Cisco obviously has an advantage in security, because you go end-to-end, you guys make everything, and you can do deep-packet inspection, and that seems to be a real advantage here. But then there's this thing called blockchain, and everybody talks about how blockchain can be applied. Where do you see blockchain fitting into the security equation? >> Yeah, I think that's a good question. Maybe a bit more broader story, I actually believe there's four legs to this digital transformations tool. There's IOT generating the data and acting on the decisions, there's AI, there is the fog computing we talked about, and the fourth tool is blockchain, which basically allows us to make sure that the data we're using we can actually trust. At the high level blockchain, people often confuse blockchain and Bitcoin and cryptocurrencies, but blockchain is an underlying technology behind sort of the crypto, that allows basically multiple parties to write their transactions in a fast and permanent way. But in the enterprise context, in IOT context, blockchain allows us to actually come up with very new use cases by looking at the provenance, and looking at the data across multiple parties. The data we can trust. For example, the use cases such as counterfeiting, there are use cases like food safety. Like patient records. Like provenance of materials. So now we can enable these use cases, because we have a single source of truth. >> I want to ask you about disruption. I like the mental model and picture that you created before of a horizontal technologies, and you kind of get vertical industries, and it seems like, again I'm bringing it back to data. We heard Super Mario at the host of the conference say this was the largest digital transformation conference. Which we laughed, like every conference is a digital transformation conference. But to us, digital transformation, digital means data. And that picture you drew of horizontal technology and vertical industries, it's all data, and data enables disruption. It used to be a vertical stack of talent and manufacturing and supply chain within an industry, and now data seems to be blowing that to pieces in digital. You see Amazon getting into, you know, buying Whole Foods in grocery. You see Apple in financial services. Others, Silicon Valley type companies, disrupting healthcare, which we all know needs disruption. What do you make of disruption? It seems like no industry is safe. It seems like Silicon Valley has this dual disruption agenda. Horizontal technology and then partnering within industries, and everything is getting turned up on its side. What do you make of it all? >> Dave, I think you nailed it. It is about and verus or, right? When you think about companies, you mentioned Microsoft, Cisco, Amazon, verus PTC or Rockwell, or Emerson and others. 10 years ago we sort of lived on a different planet, right, and rarely these companies even talked to each other. And now, even at this show, these companies are actually showing joint solutions. So that's precisely, I think, what we've seen, which is technology competence coming from the Valley and from traditional technology industry, and then the vertical and market expertise coming from these more traditional vendors. At the end of the day, it is about technology, but it is also about talent. It is about skillsets. It's about all of us pulling our resources together to develop solutions to drive business outcomes. So cloud, obviously, was a very disruptive force in our industry. But when you think about IOT, just based on what you just said, it seems to me given the assets, the resources, the people, the plants, the equipment, it seems like IOT is maybe somewhat evolutionary. Not a completely... It's a disruptive force in that's new and that it's different, but it seems like the incumbents, I mean look at PTC, their resurgence. It seems like the incumbents have an advantage here. What are your thoughts? >> I think that if they play it right they absolutely do. But it requires also a shift in mindset, and I think we seeing it already, which is moving from a vertical, one company does it all kind of mentality, into the lets build an ecosystem based on open systems, open standards, interoperability. And that's sort of a shift I think we are seeing. So for me, I think that the incumbents, if they embrace this kind of a model, they absolutely have a critical role to play. On the flip side, the technology companies realizing that they need to, it's not only about technology, but it's also about partnering. It's about integrating within legacy ecosystems and the legacy infrastructure. So each of the sides of the coin need to learn new tricks. >> Okay, last question, is your initial thoughts, anyway, on this event, some initial take aways. I know it's early, day one, but you've been here. You've heard the keynotes. Final thoughts? >> I think so far it's actually a great start to the event. I have to say, what we've talked about already, my biggest take away is to see, and actually joy, is to see companies from different walks of life working together. You have robotics companies, you have AI companies, you have industrial companies. All of them are coming up with solutions together, and that's basically what we want to see. Is breaking the barriers and multiple companies working together to move the industry forward. >> And you're also seeing the big SIs are here. I can see Accenture, I can see Deloid. I know InfoSys is here, et cetera, et cetera. So if they're here, you know there's a lot of money to be made. So Maciek, thanks very much. It's really a pleasure having you. Alright, keep it right there, everybody. This is theCube, from LiveWorx in Boston. We'll be right back after this short break.

>> Narrator: Live, from San Jose, it's theCUBE. Presenting Big Data Silicon Valley. Brought to you by SiliconANGLE Media and its ecosystem partners (mellow electronic music) >> Welcome back to theCUBE, on day two of our coverage of our event, Big Data SV. I'm Lisa Martin, my co-host is Peter Burris. We are the down the street from the Strata Data Conference, we've had a great day yesterday, and great morning already, really learning and peeling back the layers of big data, challenges, opportunities, next generation, we're welcoming back to theCUBE an alumni, the CMO of Kinetica, Dan Raskin. Hey Dan, welcome back to theCUBE. >> Thank you, thank you for having me. >> So, I'm a messaging girl, look at your website, the insight engine for the extreme data economy. Tell us about the extreme data economy, and what is that, what does it mean for your customers? >> Yeah, so it's a great question, and, from our perspective, we sit, we're here at Strata, and you see all the different vendors kind of talking about what's going on, and there's a little bit of word spaghetti out there that makes it really hard for customers to think about how big data is affecting them today, right? And so, what we're actually looking at is the idea of, the world's changed. That, big data from five years ago, doesn't necessarily address all the use cases today. If you think about what customers are going through, you have more users, devices, and things coming on, there's more data coming back than ever before, and it's not just about creating the data driven business, and building these massive data lakes that turn into data swamps, it's really about how do you create the data-powered business. So when we're using that term, we're really trying to call out that the world's changed, that, in order for businesses to compete in this new world, they have to think about to take data and create CoreIP that differentiates, how do I use it to affect the omnichannel, how do I use it to deal with new things in the realm of banking and Fintech, how do I use it to protect myself against disruption in telco, and so, the extreme data economy is really this idea that you have business in motion, more things coming online ever before, how do I create a data strategy, where data is infused in my business, and creates CoreIP that helps me maintain category leadership or grow. >> So as you think about that challenge, there's a number of technologies that come into play. Not least of which is the industry, while it's always to a degree been driven by what hardware can do, that's moderated a bit over time, but today, in many respects, a lot of what is possible is made possible, by what hardware can do, and what hardware's going to be able to do. We've been using similar AI algorithms for a long time. But we didn't have the power to use them! We had access to data, but we didn't have the power to acquire and bring it in. So how is the relationship between your software, and your platform, and some of the new hardware that's becoming available, starting to play out in a way of creating value for customers? >> Right, so, if you think about this in terms of this extreme data concept, and you think about it in terms of a couple of things, one, streaming data, just massive amounts of streaming data coming in. Billions of rows that people want to take and translate into value. >> And that data coming from-- >> It's coming from users, devices, things, interacting with all the different assets, more edge devices that are coming online, and the Wild West essentially. You look at the world of IoT and it's absolutely insane, with the number of protocols, and device data that's coming back to a company, and then you think about how do you actually translate this into real-time insight. Not near real-time, where it's taking seconds, but true millisecond response times where you can infuse this into your business, and one of our whole premises about Kinetica is the idea of this massive parallel compute. So the idea of not using CPUs anymore, to actually drive the powering behind your intelligence, but leveraging GPUs, and if you think about this, a CPU has 64 cores, 64 parallel things that you can do at a time, a GPU can have up to 6,000 cores, 6,000 parallel things, so it's kind of like lizard brain verse modern brain. How do you actually create this next generation brain that has all these neural networks, for processing the data, in a way that you couldn't. And then on top of that, you're using not just the technology of GPUs, you're trying to operationalize it. So how do you actually bring the data scientist, the BI folks, the business folks all together to actually create a unified operational process, and the underlying piece is the Kinetica engine and the GPU used to do this, but the power is really in the use cases of what you can do with it, and how you actually affect different industries. >> So can you elaborate a little bit more on the use cases, in this kind of game changing environment? >> Yeah, so there's a couple of common use cases that we're seeing, one that affects every enterprise is the idea of breaking down silos of business units, and creating the customer 360 view. How do I actually take all these disparate data feeds, bring them into an engine where I can visualize concepts about my customer and the environment that they're living in, and provide more insight? So if you think about things like Whole Foods and Amazon merging together, you now have this power of, how do I actually bridge the digital and physical world to create a better omnichannel experience for the user, how do I think about things in terms of what preferences they have, personalization, how to actually pair that with sensor data to affect how they actually navigate in a Whole Foods store more efficiently, and that's affecting every industry, you could take that to banking as well and think about the banking omminchannel, and ATMs, and the digital bank, and all these Fintech upstarts that are working to disrupt them. A great example for us is the United States Postal Service, where we're actually looking at all the data, the environmental data, around the US Postal Service, we're able to visualize it in real-time, we're able to affect the logistics of how they actually navigate through their routes, we're able to look things like postal workers separating out of their zones, and potentially kicking off alerts around that, so effectively making the business more efficient. But, we've moved into this world where we always used to talk about brick and mortar going to cloud, we're now in this world where the true value is how you bridge the digital and physical world, and create more transformative experiences, and that's what we want to do with data. So it could be logistics, it could be omnichannel, it could be security, you name it. It affects every single industry that we're talking about. >> So I got two questions, what is Kinetica's contribution to that, and then, very importantly, as a CMO, how are you thinking about making sure that the value that people are creating, or can create with Kinetica, gets more broadly diffused into an ecosystem. >> Yeah, so the power that we're bringing is the idea of how to operationalize this in a way where again, you're using your data to create value, so, having a single engine where you're collecting all of this data, massive volumes of data, terabytes upon terabytes of data, enabling it where you can query the data, with millisecond response times, and visualize it, with millisecond response times, run machine learning algorithms against it to augment it, you still have that human ability to look at massive sets of data, and do ad hoc discovery, but can run machining learning algorithms against that and complement it with machine learning. And then the operational piece of bringing the data scientists into the same platform that the business is using, so you don't have data recency issues, is a really powerful mix. The other piece I would just add is the whole piece around data discovery, you can't really call it big data if, in order to analyze the data, you have to downsize and downsample to look at a subset of data. It's all about looking at the entire set. So that's where we really bring value. >> So, to summarize very quickly, you are providing a platform that can run very, very fast, in a parallel system, and memories in these parallel systems, so that large amounts of data can be acted upon. >> That's right. >> Now, so, the next question is, there's not going to be a billion people that are going to use your tool to do things, how are you going to work with an ecosystem and partners to get the value that you're able to create with this data, out into the engine enterprise. >> It's a great question, and probably the biggest challenge that I have, which is, how do you get above the word spaghetti, and just get into education around this. And so I think the key is getting into examples, of how it's affecting the industry. So don't talk about the technology, and streaming from Kafka into a GPU-powered engine, talk about the impact to the business in terms of what it brings in terms of the omnichannel. You look at something like Japan in the 2020 Olympics, and you think about that in terms of telco, and how are the mobile providers going to be able to take all the data of what people are doing, and to related that to ad-tech, to relate that to customer insight, to relate that to new business models of how they could sell the data, that's the world of education we have to focus on, is talk about the transformative value it brings from the customer perspective, the outside-in as opposed to the inside-out. >> On that educational perspective, as a CMO, I'm sure you meet with a lot of customers, do you find that you might be in this role of trying to help bridge the gaps between different roles in an organization, where there's data silos, and there's probably still some territorial culture going on? What are you finding in terms of Kinetica's ability to really help educate and maybe bring more stakeholders, not just to the table, but kind of build a foundation of collaboration? >> Yeah, it's a really interesting question because I think it means, not just for Kinetica, but all vendors in the space, have to get out of their comfort zone, and just stop talking speeds and feeds and scale, and in fact, when we were looking at how to tell our story, we did an analysis of where most companies were talking, and they were focusing a lot more on the technical aspirations that developers sell, which is important, you still need to court the developer, you have community products that they can download, and kick the tires with, but we need to extend our dialogue, get out of our customer comfort zone, and start talking more to CIOs, CTOs, CDOs, and that's just reaching out to different avenues of communication, different ways of engaging. And so, I think that's kind of a core piece that I'm taking away from Strata, is we do a wonderful job of speaking to developers, we all need to get out of our comfort zone and talk to a broader set of folks, so business folks. >> Right, 'cause that opens up so many new potential products, new revenue streams, on the marketing side being able to really target your customer base audience, with relevant, timely offers, to be able to be more connected. >> Yeah, the worst scenario is talking to an enterprise around the wonders of a technology that they're super excited about, but they don't know the use case that they're trying to solve, start with the use case they're trying to solve, start with thinking about how this could affect their position in the market, and work on that, in partnership. We have to do that in collaboration with the customers. We can't just do that alone, it's about building a partnership and learning together around how you use data in a different way. >> So as you imagine, the investments that Kinetica is going to make over the next few years, with partners, with customers, what do you hope Kinetica will be in 2020? >> So, we want it to be that transformative engine for enterprises, we think we are delivering something that's quite unique in the world, and, you want to see this on a global basis, affecting our customer's value. I almost want to take us out of the story, and if I'm successful, you're going to hear wonderful enterprise companies across telco, banking, and other areas just telling their story, and we happen to be the engine behind it. >> So you're an ingredient in their success. >> Yes, a core ingredient in their success. >> So if we think about over the course of the next technology, set of technology waves, are they any particular applications that you think you're going to be stronger in? So I'll give you an example, do you envision that Kinetica can have a major play in how automation happens inside infrastructure, or how developers start seeing patterns in data, imagine how those assets get created. Where are some of the kind of practical, but not really, or rarely talked about applications that you might find yourselves becoming more of an ingredient because they themselves become ingredients to some of these other big use cases? >> There are a lot of commonalities that we're starting to see, and the interesting piece is the architecture that you implement tends to be the same, but the context of how you talk about it, and the impact it has tends to be different, so, I already mentioned the customer 360 view? First and foremost, break down silos across your organization, figure out how do you get your data into one place where you can run queries against it, you can visualize it, you can do machine learning analysis, that's a foundational element, and, I have a company in Asia called Lippo that is doing that in their space, where all of the sudden they're starting to glean things they didn't know about their customer before to create, doing that ad hoc discovery, so that's one area. The other piece is this use case of how do you actually operationalize data scientists, and machine learning, into your core business? So, that's another area that we focus on. There are simple entry points, things like Tableau Acceleration, where you put us underneath the existing BI infrastructure, and all of the sudden, you're a hundred times faster, and now your business folks can sit at the table, and make real-time business decisions, where in the past, if they clicked on certain things, they'd have to wait to get those results. Geospatial visualization's a no-brainer, the idea of taking environmental data, pairing it with your customer data, for example, and now learning about interactions. And I'd say the other piece is more innovation driven, where we would love sit down with different innovation groups in different verticals and talk with them about, how are you looking to monetize your data in the future, what are the new business models, how does things like voice interaction affect your data strategy, what are the different ways you want to engage with your data, so there's a lot of different realms we can go to. >> One of the things you said as we wrap up here, that I couldn't agree with more, is, the best value articulation I think a brand can have, period, is through the voice of their customer. And being able to be, and I think that's one of the things that Paul said yesterday is, defining Kinetica's success based on the success of your customers across industry, and I think really doesn't get more objective than a customer who has, not just from a developer perspective, maybe improved productivity, or workforce productivity, but actually moved the business forward, to a point where you're maybe bridging the gaps between the digital and physical, and actually enabling that business to be more profitable, open up new revenue streams because this foundation of collaboration has been established. >> I think that's a great way to think about it-- >> Which is good, 'cause he's your CEO. >> (laughs) Yes, that sustains my job. But the other piece is, I almost get embarrassed talking about Kinetica, I don't want to be the car salesman, or the vacuum salesman, that sprinkles dirt on the floor and then vacuums it up, I'd rather us kind of fade to the behind the scenes power where our customers are out there telling wonderful stories that have an impact on how people live in this world. To me, that's the best marketing you can do, is real stories, real value. >> Couldn't agree more. Well Dan, thanks so much for stopping by, sharing what things that Kinetica is doing, some of the things you're hearing, and how you're working to really build this foundation of collaboration and enablement within your customers across industries. We look forward to hearing the kind of cool stuff that happens with Kinetica, throughout the rest of the year, and again, thanks for stopping by and sharing your insights. >> Thank you for having me. >> I want to thank you for watching theCUBE, I'm Lisa Martin with my co-host Peter Burris, we are at Big Data SV, our second day of coverage, at a cool place called the Forager Tasting Room, in downtown San Jose, stop by, check us out, and have a chance to talk with some of our amazing analysts on all things big data. Stick around though, we'll be right back with our next guest after a short break. (mellow electronic music)

>> Announcer: Live from New York, it's theCUBE! Covering Machine Learning Everywhere: Build Your Ladder To AI. Brought to you by IBM. >> Well, good morning! Welcome here on theCUBE. Along with Dave Vellante, I'm John Walls. We're in Midtown New York for IBM's Machine Learning Everywhere: Build Your Ladder To AI. Great lineup of guests we have for you today, looking forward to bringing them to you, including world champion chess master Garry Kasparov a little bit later on. It's going to be fascinating. Dave, glad you're here. Dave, good to see you, sir. >> John, always a pleasure. >> How you been? >> Up from DC, you know, I was in your area last week doing some stuff with John Furrier, but I've been great. >> Stopped by the White House, drop in? >> You know, I didn't this time. No? >> No. >> Dave: My son, as you know, goes to school down there, so when I go by my hotel, I always walk by the White House, I wave. >> Just in case, right? >> No reciprocity. >> Same deal, we're in the same boat. Let's talk about what we have coming up here today. We're talking about this digital transformation that's going on within multiple industries. But you have an interesting take on it that it's a different wave, and it's a bigger wave, and it's an exciting wave right now, that digital is creating. >> Look at me, I've been around for a long time. I think we're entering a new era. You know, the great thing about theCUBE is you go to all these events, you hear the innovations, and we started theCUBE in 2010. The Big Data theme was just coming in, and it appeared, everybody was very excited. Still excited, obviously, about the data-driven concept. But we're now entering a new era. It's like every 10 years, the parlance in our industry changes. It was cloud, Big Data, SaaS, mobile, social. It just feels like, okay, we're here. We're doing that now. That's sort of a daily ritual. We used to talk about how it's early innings. It's not anymore. It's the late innings for those. I think the industry is changing. The describers of what we're entering are autonomous, pervasive, self-healing, intelligent. When you infuse artificial intelligence, I'm not crazy about that name, but when you infuse that throughout the landscape, things start to change. Data is at the center of it, but I think, John, we're going to see the parlance change. IBM, for example, uses cognitive. People use artificial intelligence. I like machine intelligence. We're trying to still figure out the names. To me, it's an indicator that things are changing. It's early innings now. What we're seeing is a whole new set of opportunities emerging, and if you think about it, it's based on this notion of digital services, where data is at the center. That's something that I want to poke at with the folks at IBM and our guests today. How are people going to build new companies? You're certainly seeing it with the likes of Uber, Airbnb, Waze. It's built on these existing cloud and security, off-the-shelf, if you will, horizontal technologies. How are new companies going to be built, what industries are going to be disruptive? Hint, every industry. But really, the key is, how will existing companies keep pace? That's what I really want to understand. >> You said, every industry's going to be disrupted, which is certainly, I think, an exciting prospect in some respects, but a little scary to some, too, right? Because they think, "No, we're fat and happy "and things are going well right now in our space, "and we know our space better than anybody." Some of those leaders might be thinking that. But as you point out, digital technology has transformed to the extent now that there's nobody safe, because you just slap this application in, you put this technology in, and I'm going to change your business overnight. >> That's right. Digital means data, data is at the center of this transformation. A colleague of mine, David Moschella, has come up with this concept of the matrix, and what the matrix is is a set of horizontal technology services. Think about cloud, or SaaS, or security, or mobile, social, all the way up the stack through data services. But when you look at the companies like Airbnb and Uber and, certainly, what Google is doing, and Facebook, and others, they're building services on top of this matrix. The matrix is comprised of vertical slices by industry and horizontal slices of technology. Disruptors are cobbling together through software and data new sets of services that are disrupting industries. The key to this, John, in my view, anyway, is that, historically, within healthcare or financial services, or insurance, or manufacturing, or education, those were very siloed. But digital and data allows companies and disruptors to traverse silos like never before. Think about it. Amazon buying Whole Foods. Apple getting into healthcare and financial services. You're seeing these big giants disrupt all of these different industries, and even smaller guys, there's certainly room for startups. But it's all around the data and the digital transformation. >> You spoke about traditional companies needing to convert, right? Needing to get caught up, perhaps, or to catch up with what's going on in that space. What do you do with your workforce in that case? You've got a bunch of great, hardworking people, embedded legacy. You feel good about where you are. And now you're coming to that workforce and saying, "Here's a new hat." >> I think that's a great question. I think the concern that one would have for traditional companies is, data is not foundational for most companies. It's not at their core. The vast majority of companies, the core are the people. You hear it all the time. "The people are our greatest asset." That, I hate to say it, but it's somewhat changing. If you look at the top five companies by market cap, their greatest asset is their data, and the people are surrounding that data. They're very, very important because they know how to leverage that data. But if you look at most traditional companies, people are at their core. Data is kind of, "Oh, we got this bolt-on," or it's in a bunch of different silos. The big question is, how do they close that gap? You're absolutely right. The key is skillsets, and the skills have to be, you know, we talk about five-tool baseball players. You're a baseball fan, as am I. Well, you need multi-tool players, those that understand not only the domain of whether it's marketing or sales or operational expertise or finance, but they also require digital expertise. They know, for example, if you're a marketing professional, they know how to do hypertargeting. They know how to leverage social. They know how to do SEO, all these digital skills, and they know how to get information that's relevant and messaging out into the marketplace and permeate that. And so, we're entering, again, this whole new world that's highly scalable, highly intelligent, pervasive, autonomous. We're going to talk about that today with a lot of their guests, with a lot of our guests, that really are kind of futurists and have thought through, I think, the changes that are coming. >> You can't have a DH anymore, right, that's what you're saying? You need a guy that can play the field. >> Not only play the field, not only a utility player, but somebody who's a utility player, but great. Best of breed at all these different skillsets. >> Machine learning, we haven't talked much about that, and another term, right, that certainly has different definitions, but certainly real specific applications to what's going on today. We'll talk a lot about ML today. Your thoughts about that, and how that squares into the artificial intelligence picture, and what we're doing with all those machines out there that are churning 24/7. >> Yeah, so, real quick, I know we're tight on time here. Artificial intelligence to me is the umbrella. Machine learning is the application of math and algorithms to solve a particular problem or answer a particular question. And then there's deep learning, which is highly focused neural networks that go deeper and deeper and deeper, and become auto-didactic, self-learning, in a manner. Those are just the very quick and rudimentary description. Machine learning to me is the starting point, and that's really where organizations really want to start to learn and begin to close the gap. >> A lot of ground to cover, and we're going to do that for you right here on theCUBE as we continue our coverage of Machine Learning Everywhere: Your Ladder To AI, coming up here, IBM hosting us in Midtown, New York. Back with more here on theCUBE in just a bit. (fast electronic music)

>> Hi, I'm Peter Burris, and welcome once again to Action Item. (funky electronic music) Every week, Wikibon gathers together the research team to discuss seminal issues that are facing the IT industry. And this week is no different. In the next couple of weeks, somewhere near 100,000 people are gonna be heading to Las Vegas for the Amazon, or AWS re:Invent show from all over the world. And this week, what we wanna do is we wanna provide a preview of what we think folks are gonna be talking about. And I'm joined here in our lovely Palo Alto studio, theCUBE studio, by Rob Hof, who is the editor-in-chief of SiliconANGLE. David Floyer, who's in analyst at Wikibon. George Gilbert, who's an analyst Wikibon. And John Furrier, who's a CUBE host and co-CEO. On the phone we have Neil Raden, an analyst at Wikibon, and also Dave Vellante, who's co-CEO with John Furrier, an analyst at Wikibon as well. So guys, let's jump right into it. David Floyer, I wanna hit you first. AWS has done a masterful job of making the whole concept of infrastructure as a service real. Nobody should downplay how hard that was and how amazing their success has been. But they're moving beyond infrastructure as a service. What do we expect for how far up Amazon is likely to go up the stack this year at re:Invent? >> Well, I can say what I'm hoping for. I agree with your premise that they have to go beyond IAS. The overall market for cloud is much bigger than just IAS, with SaaS and other clouds as well, both on-premise and off-premise. So I would start with what enterprise CIOs are wanting, and they are wanting to see a multi-cloud strategy, both on-premise and multiple clouds. SaaS clouds, other clouds. So I'm looking for AWS to provide additional services to make that easier. in particular, services, I thought of private clouds for enterprises. I'm looking for distributed capabilities, particularly in the storage area so they can link different clouds together. I want to see edge data management capabilities. I'd love to see that because the edge itself, especially the low-latency stuff, the real-time stuff, that needs specialist services, and I'd like to see them integrate that much better than just Snowball. I want to see more details about AI I'd love to see what they're doing in that. There's tremendous potential for AI in operational and to improve security, to improve availability, recovery. That is an area where I think they could be a leader of the IT industry. >> So let me stop you there, and George I wanna turn to you. So AWS in AI how do we anticipate that's gonna play out at re:Invent this year? >> I can see three things in decreasing order of likelihood. The first one is, they have to do a better job of tooling, both for, sort of, developers who want to dabble in, well get their arms around AI, but who aren't real data scientists. And then also hardcore tools for data scientists that have been well served by, recently, Microsoft and IBM, among others. So this is this Iron Man Initiative that we've heard about. For the hardcore tools, something from Domino Data Labs that looks like they're gonna partner with them. It's like a data-science workbench, so for the collaborative data preparation, modeling, deployment. That whole life cycle. And then for the developer-ready tooling, I expect to see they'll be working with a company called DataRobot, which has a really nifty tool where you put in a whole bunch of training data, and it trains, could be a couple dozen models that it thinks that might fit, and it'll show you the best fits. It'll show you the features in the models that are most impactful. In other words, it provides a lot of transparency. >> So it's kind of like models for models. >> Yes, and it provides transparency. Now that's the highest likelihood. And we have names on who we think the likely suspects are. The next step down, I would put applying machine learning to application performance management and IT operations. >> So that's the whole AI for ITOM that David Floyer just mentioned. >> Yeah. >> Now, presumably, this is gonna have to extend beyond just AI for Amazon or AWS-related ITOM. Our expectation's that we're gonna see a greater distribution of, or Amazon take more of a leadership in establishing a framework that cuts across multi-cloud. Have I got that right, David Floyer? >> Absolutely. A massive opportunity for them to provide the basics on their own platform. That's obviously the starting point. They'll have the best instrumentation for all of the components they have there. But they will need to integrate that in with their own databases, with other people's databases. The more that they can link all the units together and get real instrumentation from an application point of view of the whole of the infrastructure, the more value AI can contribute. >> John Foyer, the whole concept of the last few years of AWS is that all roads eventually end up at AWS. However, there's been a real challenge associated with getting this migration momentum to really start to mature. Now we saw some interesting moves that they made with VMware over the last couple of years, and it's been quite successful. And some would argue it might even have given another round of life to VMware. Are there some things we expect to see AWS do this time that are gonna reenergize the ecosystem to start bringing more customers higher up the stack to AWS? >> Yeah, but I think I look at it, quickly, as VMware was a groundbreaking even for both companies, VMware and AWS. We talked about that at that research event we had with them. The issue that is happening is that AWS has had a run in the marketplace. They've been the leader in cloud. Every year, it's been a slew of announcements. This year's no different. They're gonna have more and more announcements. In fact, they had to release some announcements early, before the show, because they have, again, more and more announcements. So they have the under-the-hood stuff going on that David Floyer and George were pointing out. So the classic build strategy is to continue to be competitive by having more services layered on top of each other, upgrading those services. That's a competitive strategy frame that's under the hood. On the business side, you're seeing more competition this year than ever before. Amazon now is highly contested, certainly in the marketplace with competitors. Okay, you're seeing FUD, the uncertainty and doubt from other people, how they're bundling. But it's clear. The cloud visibility is clear to customers. The numbers are coming in, multiple years of financial performance. But now the ecosystem plays, really, the interesting one. I think the VMware move is gonna be a tell sign for other companies that haven't won that top-three position. >> Example? >> I will say SAP. >> Oh really? You think SAP is gonna have a major play this year where we might see some more stuff about AWS and SAP? >> I'm hearing rumblings that SAP is gonna be expanding their relationship. I don't have the facts yet on the ground, but from what I'm sensing, this is consistent with what they've been doing. We've seen them at Google cloud platform. We talked to them specifically about how they're dealing with cloud. And their strategy is clear. They wanna be on Azure, Google, and Amazon. They wanna provide that database functionality and their client base in from HANA, and roll that in. So it's clear that SAP wants to be multi-cloud. >> Well we've seen Oracle over the past couple of years, or our research has suggested, I would say, that there's been kind of two broad strategies. The application-oriented strategy that goes down to IAAS aggressively. That'd be Oracle and Microsoft. And then the IAAS strategy that's trying to move up through an ecosystem play, which is more AWS. David Floyer and I have been writing a lot of that research. So it sounds like AWS is really gonna start doubling down in an ecosystem and making strategic bets on software providers who can bring those large enterprise install bases with them. >> Yeah, and the thing that you pointed out is migration. That's a huge issue. Now you can get technical, and say, what does that mean? But Andy Jassy has been clear, and the whole Amazon Web Services Team has been clear from day one. They're customer centric. They listen to the customers. So if they're doing more migration this year, and we'll see, I think they will be, I think that's a good tell sign and good prediction. That means the customers want to use Amazon more. And VMware was the same way. Their customers were saying, hey, we're ops guys, we want to have a cloud strategy. And it was such a great move for VMware. I think that's gonna lift the fog, if you will, pun intended, between what cloud computing is and other alternatives. And I think companies are gonna be clear that I can party with Amazon Web Services and still run my business in a way that's gonna help customers. I think that's the number one thing that I'm looking for is, what is the customers looking for in multi-cloud? Or if it's server-less or other things. >> Well, or yeah I agree. Lemme run this by you guys. It sounds as though multi-cloud increasingly is going to be associated with an application set. So, for example, it's very difficult to migrate a database manager from one place to another, as a snowflake. The cost to the customer is extremely high. The cost to the migration team is extremely high, lotta risk. But if you can get an application provider to step up and start migrating elements of the database interface, then you dramatically reduce the overall cost of what that migration might look like. Have I got that right, David Floyer? >> Yeah, absolutely. And I think that's what AWS, what I'm expecting them to focus on is more integration with more SaaS vendors, making it a better place-- >> Paul: Or just software vendors. >> Or software vendors. Well, SaaS vendors in particular, but software vendors in particular-- >> Well SAP's not a SaaS player, right? Well, they are a little bit, but most of their installations are still SAP on Oracle and moving them over, then my ass is gonna require a significant amount of SAP help. >> And one of the things I would love to see them have is a proper tier-one database as a service. That's something that's hugely missing at the moment, and using HANA, for example, on SAP, it's a tier-one database in a particular area, but that would be a good move and help a lot of enterprises to move stuff into AWS. >> Is that gonna be sufficient, though, given how dominant Oracle is in that-- >> No, they need something general purpose which can compete with Oracle or come to some agreement with Oracle. Who knows what's gonna happen in the future? >> Yeah, I don't know. >> Yeah we're all kinda ignoring here. It will be interesting to see. But at the end of the day, look, Oracle has an incentive also to render more of what it has, as a service at some level. And it's gonna be very difficult to say, we're gonna render this as a service to a customer, but Amazon can't play. Or AWS can't play. That's gonna be a real challenge for them. >> The Oracle thing is interesting and I bring this up because Oracle has been struggling as a company with cloud native messaging. In other words, they're putting out, they have a lot of open source, we know what they have for tooling. But they own IT. I mean if you dug up Oracle, they got the database as David pointed out, tier one. But they know the IT guys, they've been doing business in IT for years as a legacy vendor. Now they're transforming, and they are trying hard to be the cloud native path, and they're not making it. They're not getting the credit, and I don't know if that's a cultural issue with Oracle. But Amazon has that positioning from a developer cloud DNA. Now winning real enterprise deals. So the question that I'm looking for is, can Amazon continue to knock down these enterprise deals in lieu of these incumbent or legacy players in IT. So if IT continues to transform more towards cloud native, docker containers, or containers in Kubernetes, these kinds of micro services, I would give the advantage to Amazon over Oracle even though that Oracle has the database because ultimately the developers are driving the behavior. >> Oh again I don't think any of us would disagree with that. >> Yeah so the trouble though is the cost of migrating the applications and the data. That is huge. The systems of record are there for a reason. So there are two fundamental strategies for Oracle. If they can get their developers to add the AI, add the systems of intelligence. Make them systems of intelligence, then they can win in that strategy. Or the alternative is that they move it to AWS and do that movement in AWS. That's a much more risky strategy. >> Right but I think our kind of concluding point here is that ultimately if AWS can get big application players to participate and assist and invest in and move customers along with some of these big application migrations, it's good for AWS. And to your point John, it's probably good for the customers too. >> Absolutely. >> Yeah I don't think it's mutually exclusive as David makes a point about migrating for Oracle. I don't see a lot of migration coming off of Oracle. I look at overall database growth is the issue. Right so Oracle will have that position, but it's kind of like when we argued about the internet growth back in 1997. Just internet users growing was so great that rising tide flows. So I believe that the database growth is going to happen so fast that Amazon is not necessarily targeting Oracle's market share, they're going after the overall database market, which might be a smaller tier two kind of configuration or new architectures that are developing. So I think it's interesting dynamic and Oracle certainly could play there and lock in the database, but-- >> Here's what I would say, I would say that they're going after the new workload world, and a lot of that new workload is gonna involve database as it always has. Not like there's anything that the notion that we have solved or that database is 90% penetrated for the applications that are gonna be dominant matter in 2025 is ridiculous. There's a lot of new database that's gonna be sold. I think you're absolutely right. Rob Hof what's the general scuttlebutt that you're hearing. You know you as editor of SiliconANGLE, editor-in-chief of SiliconANGLE. What is the journalist world buzzing about for re:Invent this year? >> Well I guess you know my questions is because of the challenges that we're facing like we just talked about with migrating, the difficulty in migrating some of these applications. We also see very fast growing rivals like Google. Still small, but growing fast. And then there's China. That's a big one where is there a natural limit there that they're gonna have? So you put these things together, and I guess we see Amazon Web Services still growing at 42% a year or whatever it's great. But is it gonna start to go down because of all these challenges? >> 'Cause some of the constraints may start to assert themselves. >> Rob: Exactly, exactly. >> So-- >> Rob: That's what I'm looking at. >> Kind of the journalism world is kinda saying, are there some speed bumps up ahead for AWS? >> Exactly, and we saw one just a couple, well just this week with China for example. They sold off $300 million worth of data centers, equipment and such to their partner in China Beijing Sinnet. And they say this is a way to comply with Chinese law. Now we're going to start expanding, but expanding while you're selling off $300 million worth of equipment, you know, it begs a question. So I'm curious how they're going to get past that. >> That does raise an interesting question, and I think I might go back to some of the AI on ITOM, AI on IT operations management. Is that do you need control of the physical assets in China to nonetheless sell great service. >> Rob: And that's a big question. >> For accessing assets in China. >> Rob: Right. >> And my guess is that if they're successful with AI for ITOM and some of these other initiatives we're talking about. It in fact may be very possible for them to offer a great service in China, but not actually own the physical assets. And that's, it's an interesting question for some of the Chinese law issues. Dave Vellante, anything you want to jump in on, and add to the conversation? For example, if we look at some of the ecosystem and some of the new technologies, and some of the new investments being made around new technologies. What are some of your thoughts about some of the new stuff that we might hear about at AWS this year? >> Dave: Well so, a couple things. Just a comment on some of the things you guys were saying about Oracle and migration. To me it comes down to three things, growth, which is clearly there, you've talked about 40% plus growth. Momentum, you know the flywheel effect that Amazon has been talking about for years. And something that really hasn't been discussed as much which is economics, and this is something that we've talked about a lot and Amazon is bringing a software like marginal economics model to infrastructure services. And as it potentially slows down its growth, it needs to find new areas, and it will expand its tan by gobbling up parts of the ecosystem. So, you know there's so much white space, but partners got to be careful about where they're adding value because ultimately Amazon is gonna target those much in the same way, in my view anyway that Microsoft and Intel have in the past. And so I think you've got to tread very carefully there, and watch where Amazon is going. And they're going into the big areas of AI, trying to do more stuff with the Edge. And anywhere there's automation they are going to grab that piece of value in the value chain. >> So one of the things that we've been, we've talked about two main things. We've talked about a lot of investments, lot of expectations about AI and how AI is gonna show up in a variety of different ways at re:Invent. And we've talked about how they're likely to make some of these migration initiatives even that much more tangible than they have been. So by putting some real operational clarity as to how they intend to bring enterprises into AWS. We haven't talked about IoT. Dave just mentioned it. What's happening with the Edge, how is the Edge going to work? Now historically what we've seen is we've seen a lot of promises that the Edge was all going to end up in the cloud from a data standpoint, and that's where everything was gonna be processed. We started seeing the first indications that that's not necessarily how AWS is gonna move last year with Snowball and server-less computing, and some of those initiatives. We have anticipated a real honest to goodness true private cloud, AWS stack with a partnership. Hasn't happened yet. David Floyer what are we looking for this year? Are we gonna see that this year or are we gonna see more kind of circumnavigating the issue and doing the best that they can? >> Yeah, well my prediction last year was that they would come out with some sort of data service that you could install on your on-premise machine as a starting point for this communication across a multi cloud environment. I'm still expecting that, whether it happens this year or early next year. I think they have to. The pressure from enterprises, and they are a customer driven organization. The pressure from enterprises is going to mandate that they have some sort of solution on-premise. It's a requirement in many countries, especially in Europe. They're gonna have to do that I think without doubt. So they can do it in multiple ways, they can do it as they've done with the US government by putting in particular data centers, whole data centers within the US government. Or they can do it with small services, or they can have a, take the Microsoft approach of having an AWS service on site as well. I think with pressure from Microsoft, the pressure from Europe in particular is going to make this an essential requirement of their whole strategy. >> I remember a number of years going back a couple decades when Dell made big moves because to win the business of a very large manufacturer that had 50,000 work stations. Mainly engineers were turning over every year. To get that business Dell literally put a distribution point right next to that manufacturer. And we expect to see something similar here I would presume when we start talking about this. >> Yeah I mean I would make a comment on the IoT. First of all I agree with what David said, and I like his prediction, but I'm kind of taking a contrarian view on this, and I'm watching a few things at Amazon. Amazon always takes an approach of getting into new markets either with a big idea, and small teams to figure it out or building blocks, and they listen to the customer. So IoT is interesting because IoT's hard, it's important, it's really a fundamental important infrastructure, architecture that's not going away. I mean it has to be nailed down, it's obvious. Just like blockchain kinda is obvious when you talk about decentralization. So it'll be interesting to see what Amazon does on those two fronts. But what's interesting to note is Amazon always becomes their first customer. In their retail business, AWS was powering retail. With Whole Foods, and the stuff they're doing on the physical side, it'll be very interesting to see what their IoT strategy is from a technology standpoint with what they're doing internally. We get food delivered to our house from Amazon Fresh, and they got Whole Foods and all the retail. So it'll be interesting to see that. >> They're buying a lot of real estate. And I thought about this as well John. They're buying a lot of real estate, and how much processing can they put in there. And the only limit is that I don't think Whole Foods would qualify as particularly secure locations (laughing) when we start talking about this. But I think you're absolutely right. >> That only brings the question, how will they roll out IoT. Because he's like okay roll out an appliance that's more of an infrastructure thing. Is that their first move. So the question that I'm looking for is just kind of read the tea leaves and saying, what is really their doing. So they have the tech, and it's gonna be interesting to see, I mean it's more of a high level kind of business conversation, but IoT is a really big challenging area. I mean we're hearing that all over the place from CIOs like what's the architecture, what's the playbook? And it's different per company. So it's challenging. >> Although one of the reasons why it looks different per company is because it is so uncertain as to how it's gonna play out. There's not a lot of knowledge to fuse. My guess is that in 10 years we're gonna look back and see that there was a lot more commonality and patterns of work that were in IoT that many people expected. So I'll tell you one of the things that I saw last year that particularly impressed me at AWS re:Invent. Was the scale at which the network was being built out. And it raised for me an interesting question. If in fact one of the chief challenges of IoT. There are multiple challenges that every company faces with IoT. One is latency, one is intellectual property control, one is legal ramification like GDPR. Which is one of the reasons why the whole Europe play is gonna be so interesting 'cause GDPR is gonna have a major impact on a global basis, it's not just Europe. Bandwidth however is an area that is not necessarily given, it's partly a function of cost. So what happens if AWS blankets the world with network, and customers to get access to at least some degree of Edge no longer have to worry about a telco. What happens to the telco business at least from a data communication standpoint? Anybody wanna jump in on that one? >> Well yeah I mean I've actually talked to a couple folks like Ericson, and I think AT&T. And they're actually talking about taking their central offices and even the base stations, and sort of outfitting them as mini data centers. >> As pops. >> Yeah. But I think we've been hearing now for about 12 months that, oh maybe Edge is going to take over before we actually even finish getting to the cloud. And I think that's about as sort of ill-considered as the notion that PCs were gonna put mainframes out of business. And the reason I use that as an analogy, at one point IBM was going to put all their mainframe based databases and communication protocol on the PC. That was called OS2 extended edition. And it failed spectacularly because-- >> Peter: For a lot of reasons. >> But the idea is you have a separation of concerns. Presentation on one side in that case, and data management communications on the other. Here in this, in what we're doing here, we're definitely gonna have the low latency inferencing on the Edge and then the question is what data goes back up into the cloud for training and retraining and even simulation. And we've already got, having talked to Microsoft's Azure CTO this week, you know they see it the same way. They see the compute intensive modeling work, and even simulation work done in the cloud, and the sort of automated decisioning on the Edge. >> Alright so I'm gonna make one point and then I want to hit the Action Item around here. The one point I wanna make is I have a feeling that over, and I don't know if it's gonna happen at re:Invent this year but I have a feeling that over the course of the next six to nine months, there's going to be a major initiative on the part of Amazon to start bringing down the cost of data communications, and use their power to start hitting the telcos on a global basis. And what's going to be very very interesting is whether Amazon starts selling services to its network independent of its other cloud services. Because that could have global implications for who wins and who loses. >> Well that's a good point, I just wanna add color on that. Just anecdotally from my perspective you asked a question and I went, haven't talked to anyone. But knowing the telco business, I think they're gonna have that VMware moment. Because they've been struggling with over the top for so long. The rapid pace of innovation going on, that I don't think Amazon is gonna go after the telcos, I think it's just an evolutionary steamroller effect. >> It's an inevitability. >> It's an inevitability that the steamroller's coming. >> So users, don't sign longterm data communications deals right now. >> Why wouldn't you do a deal with Amazon if you're a telco, you get relevance, you have stability, lock in your cash flows, cut your deal, and stay alive. >> You know it's an interesting thought. Alright so let's hit the Action Item around here. So really quickly, as a preface for this, the way we wanna do this is guys, is that John Furrier is gonna have a couple hour one on one with Andy Jassy sometime in the next few days. And so if you were to, well tell us a little about that first John. >> Well every re:Invent we've been doing re:Invent for multiple years, I think it's our sixth year, we do all the events, and we cover it as the media partner as you know. And I'm gonna have a one on one sit down every year prior to re:Invent to get his view, exclusive interview, for two hours. Talk about the future. We broke the first Amazon story years ago on the building blocks, and how they overcame, and now they're winning. So it's a time for me to sit down and get his insight and continue to tell the story, and document the growth of this amazing success story. And so I'm gonna ask him specific questions and I wanted, love to know what he's thinking. >> Alright guys so I want each of you to pretend that you are, so representing your community, what would your community, what's the one question your community would like answered by Andy Jassy. George let's start with you. >> So my question would be, are you gonna take IT operations management, machine learn enable it, and then as part of offering a hybrid cloud solution, do you extend that capability on-prem, and maybe to even other vendor clouds. >> Peter: That's a good one, David Floyer. >> I've got two if I may. >> The more the merrier. >> I'll say them very quickly. The first one, John, is you've, the you being AWS, developed a great international network, with fantastic performance. How is AWS going to avoid conflicts with the EU, China, Japan, and particularly about their resistance about using any US based nodes. And from in-country telecommunication vendors. So that's my first, and the second is, again on AI, what's going to be the focus of AWS in applying the value of AI. Where are you gonna focus first and to give value to your customers? >> Rob Hof do you wanna ask a question? >> Yeah I'd like to, one thing I didn't raise in terms of the challenges is, Amazon overall is expanding so fast into all kinds of areas. Whole Foods we saw this. I'd ask Jassy, how do you contend with reality that a lot of these companies that you're now bumping up against as an overall company. Now don't necessarily want to depend on AWS for their critical infrastructure because they're competitors. How do you deal with that? >> Great question, David Vellante. >> David: Yeah my question is would be, as an ecosystem partner, what advice would you give? 'Cause I'm really nervous that as you grow and you use the mantra of, well we do what customers want, that you are gonna eat into my innovation. So what advice would you give to your ecosystem partners about places that they can play, and a framework that they should think about where they should invest and add value without the fear of you consuming their value proposition. >> So it's kind of the ecosystem analog to the customer question that Rob asked. So the one that I would have for you John is, the promise is all about scale, and they've talked a lot about how software at scale has to turn into hardware. What will Amazon be in five years? Are they gonna be a hardware player on a global basis? Following his China question, are they gonna be a software management player on a global basis and are not gonna worry as much about who owns the underlying hardware? Because that opens up a lot of questions about maybe there is going to be a true private cloud option an AWS will just try to run on everything, and really be the multi cloud administrator across the board. The Cisco as opposed to the IBM in the internet transformation. Alright so let me summarize very quickly. Thank you very much all of you guys once again for joining us in our Action Item. So this week we talked about AWS re:Invent. We've done this for a couple of years now. theCUBE has gone up and done 30, 35, 40 interviews. We're really expanding our presence at AWS re:Invent this year. So our expectation is that Amazon has been a major player in the industry for quite some time. They have spearheaded the whole concept of infrastructure as a service in a way that, in many respects nobody ever expected. And they've done it so well and so successfully that they are having an enormous impact way beyond just infrastructure in the market place today. Our expectation is that this year at AWS re:Invent, we're gonna hear a lot about three things. Here's what we're looking for. First, is AWS as a provider of advanced artificial intelligence technologies that then get rendered in services for application developers, but also for infrastructure managers. AI for ITOM being for example a very practical way of envisioning how AI gets instantiated within the enterprise. The second one is AWS has had a significant migration as a service initiative underway for quite some time. But as we've argued in Wikibon research, that's very nice, but the reality is nobody wants to bond the database manager. They don't want to promise that the database manager's gonna come over. It's interesting to conceive of AWS starting to work with application players as a way of facilitating the process of bringing database interfaces over to AWS more successfully as an onboarding roadmap for enterprises that want to move some of their enterprise applications into the AWS domain. And we mentioned one in particular, SAP, that has an interesting potential here. The final one is we don't expect to see the kind of comprehensive Edge answers at this year's re:Invent. Instead our expectation is that we're gonna continue to see AWS provide services and capabilities through server-less, through other partnerships that allow AWS to be, or the cloud to be able to extend out to the Edge without necessarily putting out that comprehensive software stack as an appliance being moved through some technology suppliers. But certainly green grass, certainly server-less, lambda, and other technologies are gonna continue to be important. If we finalize overall what we think, one of the biggest plays is, we are especially intrigued by Amazon's continuing build out of what appears to be one of the world's fastest, most comprehensive networks, and their commitment to continue to do that. We think this is gonna have implications far beyond just how AWS addresses the Edge to overall how the industry ends up getting organized. So with that, once again thank you very much for enjoying Action Item, and participating, and we'll talk next week as we review some of the things that we heard at AWS. And we look forward to those further conversations with you. So from Peter Burris, the Wikibon team, SiliconANGLE, thank you very much and this has been Action Item. (funky electronic music)

>> Announcer: Live from Las Vegas. It's theCUBE covering VMworld 2017, brought to you by VMware and its ecosystem partners. >> Okay, welcome back, everyone. Live here at VMworld 2017 day three wrap-up. We're going to wrap up the whole show. I'm John Furrier with Dave Vellante, Stu Miniman, Keith Townsend. Cube, set, two sets of coverage. Guys, great job, we have Justin Warren as well, John Troyer, Lisa Martin. Great team, guys, amazing. Three days, a lot of content, wall-to-wall coverage. Double barrel shotgun of Cube content. Amazing. What's left in the tank? Let's get this done. Dave, your thoughts as VMworld comes down to a close. >> Well, so I missed VMworld last year as you know, 'cause I was doing another show. Pat was giving me a lot of grief for that. But if I go back two years ago, two years ago VMware was shrinking. Its license revenue was in decline. Its cloud strategy was in continued disarray. Customers were kind of, you know, losing a lot of faith. >> John: Ecosystem was in turmoil. >> And the world thought that Amazon was going to completely destroy this company. Fast forward two years later, license growth, you know, 12-13%, the company's growing. It's nearly eight billion dollars, three billion dollars of operating cash, big stock buybacks, clarity on the cloud and, I think, and I'd love for Keith's opinion on this, a recognition of the customers that "I can't just throw everything in the cloud." Okay, that's one thing, but what I can do is try to bring the cloud model to my data, and AW, I mean Amazon, sorry, VMware is going to be a partner in doing that. And I think those have all been tailwinds along with some product cycles and some >> John: And Dell Technologies buying out from the federation which was taking on water. Let's not forget. Let's not forget about the federation EMC owned VMware and that was bought by Dell. >> People talk about the Dell discount. I'm not seeing the Dell discount right now. >> What is a Dell discount? What does that mean? >> The Dell discount is because Dell owns VMware, just like when EMC owned VMware, it somehow shackles them and depresses the value. Michael obviously doesn't agree. >> So product focus as well has been not diminished at all. The products are front and center. They still got the sessions. Guys, on the product side, what's your view? >> Strong product offering. I really love the message they want. A lot of the response from the community was like, "Pat is feeling energized." He has this shadow of what is going to happen post-acquisition. Is there going to be a Dell discount? You know what? VMware, you know, famously, five years ago, Pat was onstage. He said he's going to double down on virtualization. He jettisoned Pivotal, and we were all wondering, "What is he doing?" Proved over the long run he was right. Last year, this year, he's doubled down, not on just virtualization, but on this concept of SDDC. And it's finally starting to pay off. We're seeing consistently this concept of VCF. VMware cloud foundation on premises, off prem, and even in AWS, ironically. You know, three or four years ago, we were like, well, is OpenStack going to eat VMware's lunch? VMware has turned the tables and become that OpenStack layer, that consistent cloud layer, at least for that legacy type of way to do IT. Taking your internal data center processes and moving them to the cloud consistently across their vCAN network in the AWS. >> So if I get this right, you're basically saying that VMware essentially went from a position where they're twisting in the wind at all levels, turmoil in every department, every, house is on fire, to pulling one major bold bet, grab it out of the hat, kicking ass, taking names, Pat Gelsinger and team made good calls. >> You know what, I'm not a fan of calling what VMware's SDDC thing a private cloud. I don't think it's true private cloud. It is valuable to the infrastructure, but it's not private cloud, but customers love the message. Take what I'm doing now, check an easy box, move it into AWS or vCAN and it's resonating. >> Well certainly, Stu just gave you the eye dagger, 'cause Stu, the true private cloud report from Wikibon, which has been going viral at the show, been the talk of the show, everyone has been talking about it, Wikibon's true private cloud report. People love that, too, because the message is simple, take care of business at home, called the on prem. Yeah, change the operating model, that's going to take some time. >> So, my thought on this is, for years, we were talking about the stack wars. Lately, we've been talking about the cloud wars, and for the last few years, when I talked to the partner ecosystem, they were shrinking their booths. They were looking for alternatives. Remember Cisco? Aw geez, flaying anything but VMware. Let's see if we can do this. You know, IBM who was a big VMware partner. Well, they got rid of X86. Where are they going to part with VMware? On and on, HPE going closer with Microsoft. Even Dell, pre-acquisition, how much deeper they going to go with Microsoft? Now, you know, John, we've been talking on theCUBE for a while. You know, there's Microsoft. Their stack, their partnerships, their application, where they're putting it. Amazon, huge elephant in the room, when they made the deal it was like, oh well, you know, Pat's on his way out the door, and he's kind of, you know, pulling one over on Dell before he leaves. Now, I think we understand a little bit better where this fits in that portfolio of the Dell family. Open source, still something we beat on Pat and EMC before that. They're not really open source. They've got a proprietary software alternative that their partners seem excited about. They've really fumbled around with their cloud strategy for a year. They've got one that seems to be going well. We'll see, 4,500 service provider partners, the Amazon thing. We will still see where revenue comes. >> Stu, that's a good point. Pat Gelsinger was kicking ass as a CEO now, but his channels on his job many times, so props to Pat. He made some good calls, stayed on course, held the line on the direction, did not cave at all, him and his team, they did it. There's been some turnover as we know in VMware. I'll see the results. I'll clear the scoreboard. They're winning. Question I'll put to you guys right now. Impact of Andy Jassy from AWS here on day one. How much of an impact was that? He made some statements. And the question I want to ask you, in addition to the impact, is he said, "This is not an optical deal." Most companies make optical illusional deals, make it look like they're all in, and they don't really deliver. So one, impact of Jassy being here and two, who was he talking about? >> Dave: Well >> Where's the Barney deal? >> Well, so okay, first thing is I saw, I've always seen that AWS deal from Andy Jassy's perspective as TAM expansion. Big part of a CEO's job is, I've got to expand my TAM, especially when you see the growth of AWS, and it's slowing down a little bit, even though it's still impressive. He's got to expand his TAM. Well, how does AWS do that? Look to 500,000 VMware customers. So that's number one. Barney deal? There are a lot of Barney deals out there. I mean, most... >> What are you referring to, 'cause Google came on the stage the next day. I was getting tweets saying "Azure?" Stu, guys, who's the deal? Who was Andy Jassy talking about when he was looking at the VMware customers saying, essentially, this is not, implying others are? >> I'm not sure that he was necessarily throwing shade at anyone specifically. What there was is there was 18 months from when this deal went through, a lot of work. This was a lot of engineering work. Talk to the cloud foundation team, talk to the VSAN team. The amount of work to actually integrate, because we know Amazon actually has an extensive engineering team. They hyper-optimize what they're doing, so this is not some white box that I just slapped VMware on and said the BIOS, you know, it works and everything where I still am a little concerned if I'm, you know, a VMware employee as customers, I talked to some customers that really excited about this, the Lighthouse customers. They say it's going to get my team that loves their vCenter. They love everything, it's going to help them move faster. Then, you're talking to, "Oh there's these services they're going to be able to use." I'm like well, how much are they going to realize oh hey, this is great, and the VMware sales reps are just going to get eaten by the lion while the customer goes off. >> And so the impact's big then, you're saying, but you won't answer the question of who he's referring to. You don't think he's referring to anyone. Keith, what do you think? >> Let's look at, I like the comment about how difficult the integration was. Last year when I read, it said something like, wait, hold on what, the AWS, who is notorious about controlling their message, what I thought was funny is that Andy didn't use the term private cloud, he didn't use the term VMware cloud, he, VMware infrastructure and AWS, which is a massive engineering effort. So from that, I question whether or not they could execute upon that, but Andy Jassy being onstage on Monday showed the commitment that we're going to make these other services work, the total addressable market of 500,000 additional customers. You don't do this for bare metal servers. >> John: VMware has 500,000 customers? >> Yeah. That's the total addressable market, but that's not where AWS is going to grow by halting physical servers, by selling more Lambda, selling more CDN, selling more PAS, is the key, and where VMware and AWS relationship his weak is in that true integration between the two hybrid IT environments. So when you say, "Where's the barney deals?" the barney deals are, I think it's across the industry. Unless you're getting fully in bed and committed to make that level of investment >> No but engineering resources, this comes back down to what, the new kind of engagement between biz dev deals look like. You need to have that kind of level. >> I have no problem pointing to the Nutanix Google deal, anything that people are doing with Azure, no one's partnered at this level. >> Okay, Azure is a good one too, because I've heard from startups that have been enticed by the dollars, 'cause Microsoft's been sprinkling some cash on, who have left to go back to AWS, because of technical reasons, reverse proxies, basically software clued just to basically make stuff work. >> Well, so, where do we, how much do we know about the IBM VMware relationship? Because I mean IBM's >> Pat brought it up today. >> Soft layer hosting, right? They've got a lot more experience with VMware, IBM has said, I think they're shipping, they've been shipping for quite some time. So there's an example of engineering that had already largely been done, that's actually delivering value for customers. Pat probably brought it up because it's a great distribution channel for him. And I think Keith's right on. AWS doesn't speak in terms of VMs. They talk in terms of cloud services, like Lambda, database services, middleware, PAS layers, that's really where they're going to hook people in this community into their platform. >> Okay, so here's a question to end the segment as we wrap up the show, because this is kind of where it's all going. To me, my big epiphany was the following. Andy Jassy, statesman, Harvard MBA, now CEO of AWS, ticking names, ticking this, huge accomplishments, he's done great in his career, he's only getting better. And then Sam Ramji, great developer chops, knows software ecosystems, not Andy Jassy in terms of the title, but in terms of status, still a solid guy. Two contrasting positions, running the biggest cloud today, to Google brainpower, okay? So you're looking at that and you're saying, "Hmm, where is this going to go?" So the question on the table is, what does it take for someone to be successful in today's IT environment? Does IT need to be smarter in business or does need to be more smarter in IT, or both, and does Google have enough IQ in IT to actually make the products fast enough or are they at risk? >> Well I'll take the customer point of view, and you know, we always talk about people, process, technology. The technology is maturing, and it's maturing pretty quickly, but maybe still not quite to the point where the true private cloud vision is where we need it to be, but what's going to slow that down is the people and process side is going to take a lot longer. Stu, you made a comment yesterday, VMware's moving at the pace of the CIO. >> It's Keith's line, he's been using all week. >> Okay, great line and Robin Matlock heard that today, course marketing CMO said, "And the CIO needs to move faster." (men laugh) Well guess what? They can't. I thought that was just a perfect testament >> But that is exactly the dilemma isn't it? >> It really is, and this stuff is hard. And cloud doesn't necessarily make it any easier, (laughs) if anything, it makes it more complex, 'cause it's a completely new business model. >> But remember the old term, forklift upgrade? Okay, you don't have forklift upgrades anymore, you have rip and replace, whatever word you want to use. >> Stu: Now we have lift and shift. >> Lift and shift, rip and replace, lift and shift. Is Google, and this is my challenge to Sam, I didn't have time to ask him this question, I'll certainly do one on one next time I see him. Is Google smart enough with IQ in IT, certainly we know they're smart enough, but do they have enough IQ in IT to really make the transformation, or are they betting on a rip and replace version of a cloud? >> So John, no doubt Google's smart, and they built amazing things that, the ripple that Google has through the industry is phenomenal. They spin off whole industries based on what they're doing. Google played a very different game than Amazon is, you know, when you talk to customers and how they're first getting onto Google, you know, data's really important, analytics of course. Couple of years ago Google was saying, "Oh, we're just going to be that data analytics cloud," now of course they're trying to be a big player. Amazon, the company, remember, Amazon isn't just AWS. Andy Jassy fits into Jeff Bazer's great plans. You know, I'd love to hear, when we go to reinvent, what's happening in Whole Foods that's impacted by AWS. They are everywhere, they are, you know, Walmart did. >> How about TAM expansion, my wife's checking Amazon even more. >> But this is really interesting right, because Walmart's now using its muscle to say, "Hey, you going to do business "with AWS" >> Absolutely >> "And Whole Foods? "You're not doing business with us." So the point being that digital business is allowing companies to traverse industries and now you're seeing it in really interesting competitive lashbacks. >> So Capital One was onstage, I say something that over the past couple of years been controversial, no one believes me, but I believe this is what needs to happen. Capital One claimed that it's a technology company, they're not a bank. Well I want to bank with a bank, that' a whole 'nother conversation. But technology is just a tool to get your job done, and just like we had bookkeepers that knew Excel and then eventually Excel just became a part of your toolkit. AI, I talked to Chuck Hollis of Oracle about this on the podcast the other day. AI is just going to be a business toolkit that a business user uses. To the question, business users will become smarter at using technology. The cloud providers that enables the business user to have the least amount of friction to use that technology, to solve business challenges will win. The question is, is that Google or Andy Jassy, who has done it with Amazon, or some other cloud provider that's eating their own dog food. >> Okay guys, let's wrap this up. Let's go around the table, one word, two words, how do you wrap up VMware's position vis a vis as they go forward? >> VMware's on fire, I think the data center's on fire, the ecosystem is reforming around the cloud. And there's a lot of momentum right now, I mean I'm wondering, okay, what's going to happen to derail this, but right now the fundamentals look very good. >> Relevant, John. >> Yeah. >> Cool and relevant again. It's right, you know, cool, we can all argue, you know, look, I like what I heard with Amazon, it was better than I was expecting coming in. You know, getting in there, they talked about serverless, they talked about edge computing, something I actually had a couple really good conversations ticking to, partners doing IoT, and customers looking at that. If they can be relevant, not just in the data center, but in the cloud, and even at the edge, VMware's going to have a good life going forward. >> Yeah, and I'll wrap it up, you stole my word relevant, so I'll say, I'll a little bit further than relevant, VMware is still the leader in enterprise infrastructure software. They're not letting that lead go. >> But just on that, the last thing, they're an infrastructure software company. I think they showed how they can be more than that in the future. >> And my take is, smart strategy playing out, now people are starting to realize the long game that Pat's been playing. It's showing up in the financial results, and there's clarity, and you can see the game playing out, you're starting to see there where they're going to position, so good job, guys, that's a wrap. Want to thank our sponsors. Without sponsors theCUBE would not be able to come for the three days of wall-to-wall coverage provided to the community. We get great support from the folks on Twitter, we get support from the folks who watch the videos, want to thank you for watching, and also the sponsors, VMware, Hewlett Packard Enterprises, Dell EMC, IBM, OVH, CenturyLink, Datrium, Densify, Druva, Hitachi, INFINIDAT, Kamarino, NetApp, Nutanix, Red Hat, Rackspace, Rubrik, Skytap, Veeam and Zadara Storage. Thanks to all the 20 sponsors that we can go out and bring our best stuff here. Really appreciate your support. Thanks for watching theCUBE. This is a wrap from VMworld, thanks guys, thanks everybody here, and that's a wrap for VMworld 2017, thanks for watching.

>> Announcer: Live from Manhattan, it's theCube, covering AWS Summit, New York City, 2017. Brought to you by Amazon Web Services. >> Welcome back to the Big Apple as we continue our coverage here on theCube of AWS Summit 2017. We're at the Javits Center. We're in midtown. A lot of hustle and bustle outsie and inside there, good buzz on the show floor with about 5,000 strong attending and some 20,000 registrants also for today's show. Along with Stu Miniman, I'm John Walls, and glad to have you here on theCube. And Dustin Kirkland now joins us. He's at Ubuntu, the product and strategy side of things at Canonical, and Dustin, good to see you back on theCube. >> Thank you very much. >> You just threw a big number out at us when we were talking off camera. I'll let you take it from there, but it shows you about the presence, you might say, of Ubuntu and AWS, what that nexus is right now. >> Ubuntu easily leads as the operating system in Amazon. About 70%, seven zero, 70% of all instances running in Amazon right now are running Ubuntu. And that's actually, despite the fact that Amazon have their own Amazon Linux and there are other, Windows, Rails, SUSE, Debian, Fedora, other alternatives. Ubuntu still represents seven out of 10 workloads in Amazon running right now. >> John: Huge number. >> So, Dustin, maybe give us a little insight as to what kind of workloads you're seeing. How much of this was people that, Ubuntu has a great footprint everywhere and therefore it kind of moved there. And how much of it is new and interesting things, IOT and machine learning and everything like that, where you also have support. >> When you're talking about that many instances, that's quite a bit of boat, right? So if you look at just EC2 and the two types of workloads, there are the long-running workloads. The workloads that are up for many months, years in some cases. I met a number of customers here this week that are running older versions of Ubuntu like 12.04 which are actually end of life, but as a customer of Canonical we continue providing security updates. So we have a product called Extended Security Maintenance. There's over a million instances of Ubuntu 12.04 which are already end of life but Canonical can continue providing security updates, critical security updates. That's great for the long-running workloads. The other thing that we do for long-running workloads are kernel live patches. So we're able to actually fix vulnerabilities in the Linux kernel without rebooting, using entirely upstream and open source technology to do that. So for those workloads that stay up for months or years, the combination of Extended Security Maintenance, covering it for a very long time, and the kernel live patch, ensuring that you're able to patch those vulnerabilities without rebooting those systems, it's great for hosting providers and some enterprise workloads. Now on the flip side, you also see a lot of workloads that are spikey, right. Workloads that come and go in bursts. Maybe they run at night or in the morning or just whenever an event happens. We see a lot of Ubuntu running there. It's really, a lot of that is focused on data and machine learning, artificial intelligence workloads, that run in that sort of bursty manner. >> Okay, so it was interesting, when I hear you talk about some things that have been running for a bunch of years, and on the other side of the spectrum is serverless and the new machine learning stuff where it tends to be there, what's Canonical doing there? What kind of exciting, any of the news, Macey, Glue, some of these other ones that came out, how much do those fit into the conversations you're having? >> Sure, they all really fit. When we talk about what we're doing to tune Ubuntu for those machine learning workloads, it really starts with the kernel. So we actually have an AWS-optimized Linux kernel. So we've taken the Ubuntu Linux kernel and we've tuned it, working with the Amazon kernel engineers, to ensure that we've carved out everything in that kernel that's not relevant inside of an Amazon data center and taken it out. And in doing so, we've actually made the kernel 15% smaller, which actually reduces the security footprint and the storage footprint of that kernel. And that means smaller downloads, smaller updates, and we've made it boot 30% faster. We've done that by adding support, turning on, configuring on some parameters that enable virtualization or divert IO drivers or specifically the Amazon drivers to work really well. We've also removed things like floppy disk drives and Bluetooth drivers, which you'll never find in a virtual machine in Amazon. And when you take all of those things in aggregate and you remove them from the kernel, you end up with a much smaller, better, more efficient package. So that's a great starting point. The other piece is we've ensured that the latest and greatest graphics adapters, the GPUs, GPGPUs from Invidia, that the experienced on Ubuntu out of the box just works. It works really well, and well at scale. You'll find almost all machine learning workloads are drastically improved inside of GPGPU instances. And for the dollar, you're able to compute sometimes hundreds or thousands of times more efficiently than a fewer CPU type workload. >> You're talking about machine learning, but on the artificial intelligence side of life, a lot of conversation about that at the keynotes this morning. A lot of good services, whatever, again, your activity in that and where that's going, do you think, over the next 12, 16 months? >> Yes, so artificial intelligence is a really nice place where we see a lot of Ubuntu, mainly because the nature of how AI is infiltrating our lives. It has these two sides. One side is at the edge, and those are really fundamentally connected devices. And for every one of those billions of devices out there, there are necessarily connections to an instance in the cloud somewhere. So if we take just one example, right, an autonomous vehicle. That vehicle is connected to the internet. Sometimes well, when you're at home, parked in the garage or parked at Whole Foods, right? But sometimes it's not. You're in the middle of the desert out in West Texas. That autonomous vehicle needs to have a lot of intelligence local to that vehicle. It gets downloaded opportunistically. And what gets downloaded are the results of that machine learning, the results of that artificial intelligence process. So we heard in the keynotes quite a bit about data modeling, right? Data modeling means putting a whole bunch of data into Amazon, which Amazon has made it really easy to do with things like Snowball and so forth. Once the data is there, then the big GPGPU instances crunch that data and the result is actually a very tight, tightly compressed bit of insight that then gets fed to devices. So an autonomous vehicle that every single night gets a little bit better by tweaking its algorithms, when to brake, when to change lanes, when to make a left turn safely or a right turn safely, those are constantly being updated by all the data that we're feeding that. Now why I said that's important from an Ubuntu perspective is that we find Ubuntu in both of those locations. So we open this by saying that Ubuntu is the leading operating system inside of Amazon, representing 70% of those instances. Ubuntu is, across the board, right now in 100% of the autonomous vehicles that are running today. So Uber's autonomous vehicle, the Tesla vehicles, the Google vehicles, a number of others from other manufacturers are all running Ubuntu on the CPU. There's usually three CPUs in a smart car. The CPU that's running the autonomous driving engine is, across the board, running Ubuntu today. The fact that it's the same OS makes it, makes life quite nice for the developers. The developers who are writing that software that's crunching the numbers in the cloud and making the critical real-time decisions in the vehicle. >> You talk about autonomous vehicles, I mean, it's about a car in general, thousands of data points coming in, in continual real time. >> Dustin: Right. >> So it's just not autonomous -- >> Dustin: Right. >> operations, right? So are you working in that way, diagnostics, navigation, all those areas? >> Yes, so we catch as headlines are a lot of the hobbyist projects, the fun stuff coming out of universities or startup space. Drones and robots and vacuum cleaners, right? And there's a lot of Ubuntu running there, anything from Raspberry Pis to smart appliances at home. But it's actually, I think, really where those artificially intelligent systems are going to change our lives, is in the industrial space. It's not the drone that some kids are flying around in the park, it's the drone that's surveying crops, that's coming to understand what areas of a field need more fertilizer or less water, right. And that's happening in an artificially intelligent way as smarter and smarter algorithms make its way onto those drones. It's less about the running Pandora and Spotify having to choose the right music for you when you're sitting in your car, and a lot more about every taxicab in the city taking data and analytics and understanding what's going on around them. It's a great way to detect traffic patterns, potentially threats of danger or something like that. That's far more industrial and less intresting than the fun stuff, you know, the fireworks that are shot off by a drone. >> Not nearly as sexy, right? It's not as much fun. >> But that's where the business is, you know. >> That's right. >> One of the things people have been looking at is how Amazon's really maturing their discussion of hyrid cloud. Now, you said that data centers, public cloud, edge devices, lots of mobile, we talked about IOT and everything, what do you see from customers, what do you think we're going to see from Amazon going forward to build these hybrid architectures and how does that fit in to autonomous vehicles and the like? >> So in the keynote we saw a couple of organizations who were spotlighted as all-in on Amazon, and that's great. And actually almost all of those logos that are all-in on Amazon are all-in on Amazon on Ubuntu and that's great. That's a very small number of logos compared to the number of organizations out there that are actually hybrid. Hybrid is certainly a ramp to being all-in but for quite a bit of the industry, that's the journey and the destination, too, in fact. That there's always going to be some amount compute that happens local and some amount of compute that happens in the cloud. Ubuntu helps provide an important portability layer. Knowing something runs well on Ubuntu locally, it's going to run well on Ubuntu in Amazon, or vise versa. The fact that it runs well in Amazon, it will also run well on Ubuntu locally. Now we have a support -- >> Yeah, I was just curious, you talked about some of the optimization you made for AWS. >> Dustin: Right. >> Is that now finding its way into other environments or do we have a little bit of a fork? >> We do, it does find it's way back into other environments so, you know, the Amazon hypervisors are usually Xen-based, although there are some interesting other things coming from Amazon there. Typically what we find on-prem is usually more KVM or Vmware based. Now, most of what goes into that virtual kernel that we build for Amazon actually applies to the virtual kernel that we built for Ubuntu that runs in Xen and Vmware and KVM. There's some subtle differences. Some, a few things that we've done very specifically for Amazon, but for the most part it's perfectly compatible all the way back to the virtual machines that you would run on-prem. >> Well, Dustin, always a pleasure, >> Yeah. >> to have you hear on theCube. >> Thanks, John. >> You're welcome back any time. >> All right. >> We appreciate the time and wish you the best of luck here the rest of the day, too. >> Great. >> Good deal. >> Thank you. >> Glad to be with us. Dustin Kirkland from Canonical joining us here on theCube. Back with more from AWS Summit 2017 here in New York City right after this.

>> Narrator: From the Silicon Angle Media Office in Boston, Massachusetts, it's theCUBE. Now, here's your host, Stu Miniman. >> Hi, I'm Stu Miniman and we're here at the east coast studio for Silicon Angle Media. Happy to welcome back to the program, a many time guest, Chris Selland, who is now the Vice President of strategic growth with Unifi Software. Great to see you Chris. >> Thanks so much Stu, great to see you too. >> Alright, so Chris, we'd had you in your previous role many times. >> Chris: Yes >> I think not only is the first time we've had you on since you made the switch, but also first time we've had somebody from Unifi Software on. So, why don't you give us a little bit of background of Unifi and what brought you to this opportunity. >> Sure, absolutely happy to sort of open up the relationship with Unifi Software. I'm sure it's going to be a long and good one. But I joined the company about six months ago at this point. So I joined earlier this year. I actually had worked with Unifi for a bit as partners. Where when I was previously at the Vertica business inside of HP/HP, as you know for a number of years prior to that, where we did all the work together. I also knew the founders of Unifi, who were actually at Greenplum, which was a direct Vertica competitor. Greenplum is acquired by EMC. Vertica was acquired by HP. We were sort of friendly respected competitors. And so I have known the founders for a long time. But it was partly the people, but it was really the sort of the idea, the product. I was actually reading the report that Peter Burris or the piece that Peter Burris just did on I guess wikibon.com about distributed data. And it played so into our value proposition. We just see it's where things are going. I think it's where things are going right now. And I think the market's bearing that out. >> The piece you reference, it was actually, it's a Wikibon research meeting, we run those weekly. Internally, we're actually going to be doing them soon we will be broadcasting video. Cause, of course, we do a lot of video. But we pull the whole team together, and it was one, George Gilbert actually led this for us, talking about what architectures do I need to build, when I start doing distributed data. With my background really more in kind of the cloud and infrastructure world. We see it's a hybrid, and many times a multi-cloud world. And, therefore, one of the things we look at that's critical is wait, if I've got things in multiple places. I've got my SAS over here, I've got multiple public clouds I'm using, and I've got my data center. How do I get my arms around all the pieces? And of course data is critical to that. >> Right, exactly, and the fact that more and more people need data to do their jobs these days. Working with data is no longer just the area where data scientists, I mean organizations are certainly investing in data scientists, but there's a shortage, but at the same time, marketing people, finance people, operations people, supply chain folks. They need data to do their jobs. And as you said where it is, it's distributed, it's in legacy systems, it's in the data center, it's in warehouses, it's in SAS applications, it's in the cloud, it's on premise, It's all over the place, so, yep. >> Chris, I've talked to so many companies that are, everybody seems to be nibbling at a piece of this. We go to the Amazon show and there's this just ginormous ecosystem that everybody's picking at. Can you drill in a little bit for what problems do you solve there. I have talked to people. Everything from just trying to get the licensing in place, trying to empower the business unit to do things, trying to do government compliance of course. So where's Unifi's point in this. >> Well, having come out of essentially the data warehousing market. And now of course this has been going on, of course with all the investments in HDFS, Hadoop infrastructure, and open source infrastructure. There's been this fundamental thinking that, well the answer's if I get all of the data in one place then I can analyze it. Well that just doesn't work. >> Right. >> Because it's just not feasible. So I think really and its really when you step back it's one of these like ah-ha that makes total sense, right. What we do is we basically catalog the data in place. So you can use your legacy data that's on the main frame. Let's say I'm a marketing person. I'm trying to do an analysis of selling trends, marketing trends, marketing effectiveness. And I want to use some order data that's on the main frame, I want some click stream data that's sitting in HDFS, I want some customer data in the CRM system, or maybe it's in Sales Force, or Mercado. I need some data out of Workday. I want to use some external data. I want to use, say, weather data to look at seasonal analysis. I want to do neighborhooding. So, how do I do that? You know I may be sitting there with Qlik or Tableau or Looker or one of these modern B.I. products or visualization products, but at the same time where's the data. So our value proposition it starts with we catalog the data and we show where the data is. Okay, you've got these data sources, this is what they are, we describe them. And then there's a whole collaboration element to the platform that lets people as they're using the data say, well yes that's order data, but that's old data. So it's good if you use it up to 2007, but the more current data's over here. Do things like that. And then we also then help the person use it. And again I almost said IT, but it's not real data scientists, it's not just them. It's really about democratizing the use. Because business people don't know how to do inner and outer joins and things like that or what a schema is. They just know, I'm trying do a better job of analyzing sales trends. I got all these different data sources, but then once I found them, once I've decided what I want to use, how do I use them? So we answer that question too. >> Yea, Chris reminds me a lot of some the early value propositions we heard when kind of Hadoop and the whole big data wave came. It was how do I get as a smaller company, or even if I'm a bigger company, do it faster, do it for less money than the things it use to be. Okay, its going to be millions of dollars and it's going to take me 18 months to roll out. Is it right to say this is kind of an extension of that big data wave or what's different and what's the same? >> Absolutely, we use a lot of that stuff. I mean we basically use, and we've got flexibility in what we can use, but for most of our customers we use HDFS to store the data. We use Hive as the most typical data form, you have flexibility around there. We use MapReduce, or Spark to do transformation of the data. So we use all of those open source components, and as the product is being used, as the platform is being used and as multiple users, cause it's designed to be an enterprise platform, are using it, the data does eventually migrate into the data lake, but we don't require you to sort of get it there as a prerequisite. As I said, this is one of the things that we really talk about a lot. We catalog the data where it is, in place, so you don't have to move it to use it, you don't have to move it to see it. But at the same time if you want to move it you can. The fundamental idea I got to move it all first, I got to put it all in one place first, it never works. We've come into so many projects where organizations have tried to do that and they just can't, it's too complex these days. >> Alright, Chris, what are some of the organizational dynamics you're seeing from your customers. You mention data scientist, the business users. Who is identifying, whose driving this issues, whose got the budget to try to fix some of these challenges. >> Well, it tends to be our best implementations are driven really, almost all of them these days, are driven by used cases. So they're driven by business needs. Some of the big ones. I've sort of talked about customers already, but like customer 360 views. For instance, there's a very large credit union client of ours, that they have all of their data, that is organized by accounts, but they can't really look at Stu Miniman as my customer. How do I look at Stu's value to us as a customer? I can look at his mortgage account, I can look at his savings account, I can look at his checking account, I can look at his debit card, but I can't just see Stu. I want to like organize my data, that way. That type of customer 360 or marketing analysis I talked about is a great use case. Another one that we've been seeing a lot of is compliance. Where just having a better handle on what data is where it is. This is where some of the governance aspects of what we do also comes into play. Even though we're very much about solving business problems. There's a very strong data governance. Because when you are doing things like data compliance. We're working, for instance, with MoneyGram, is a customer of ours. Who this day and age in particular, when there's money flows across the borders, there's often times regulators want to know, wait that money that went from here to there, tell me where it came from, tell me where it went, tell me the lineage. And they need to be able to respond to those inquiries very very quickly. Now the reality is that data sits in all sorts of different places, both inside and outside of the organization. Being able to organize that and give the ability to respond more quickly and effectively is a big competitive advantage. Both helps with avoiding regulatory fines, but also helps with customers responsiveness. And then you've got things GDPR, the General Data Protection Regulation, I believe it is, which is being driven by the EU. Where its sort of like the next Y2K. Anybody in data, if they are not paying attention to it, they need to be pretty quick. At least if they're a big enough company they're doing business in Europe. Because if you are doing business with European companies or European customers, this is going to be a requirement as of May next year. There's a whole 'nother set of how data's kept, how data's stored, what customers can control over data. Things like 'Right to Be Forgotten'. This need to comply with regulatory... As data's gotten more important, as you might imagine, the regulators have gotten more interested in what organizations are doing with data. Having a framework with that, organizes and helps you be more compliant with those regulations is absolutely critical. >> Yeah, my understanding of GDPR, if you don't comply, there's hefty fines. >> Chris: Major Fines. >> Major Fines. That are going to hit you. Does Unifi solve that? Is there other re-architecture, redesign that customers need to do to be able to be compliant? [speaking at The same Time] >> No, no that's the whole idea again where being able to leave the data where it is, but know what it is and know where it is and if and when I need to use it and where it came from and where it's going and where it went. All of those things, so we provide the platform that enables the customers to use it or the partners to build the solutions for their customers. >> Curious, customers, their adoption of public cloud, how does that play into what you are doing? They deploy more SAS environments. We were having a conversation off camera today talking about the consolidation that's happening in the software world. What does those dynamics mean for your customers? >> Well public cloud is obviously booming and growing and any organization has some public cloud infrastructure at this point, just about any organization. There's some very heavily regulated areas. Actually health care's probably a good example. Where there's very little public cloud. But even there we're working with... we're part of the Microsoft Accelerator Program. Work very closely with the Azure team, for instance. And they're working in some health care environments, where you have to be things like HIPAA compliant, so there is a lot of caution around that. But none the less, the move to public cloud is certainly happening. I think I was just reading some stats the other day. I can't remember if they're Wikibon or other stats. It's still only about 5% of IT spending. And the reality is organizations of any size have plenty of on-prem data. And of course with all the use of SAS solutions, with Salesforce, Workday, Mercado, all of these different SAS applications, it's also in somebody else's data center, much of our data as well. So it's absolutely a hybrid environment. That's why the report that you guys put out on distributed data, really it spoke so much to what out value proposition is. And that's why you know I'm really glad to be here to talk to you about it. >> Great, Chris tell us a little bit, the company itself, how many employees you have, what metrics can you share about the number of customers, revenue, things like that. >> Sure, no, we've got about, I believe about 65 people at the company right now. I joined like I said earlier this year, late February, early March. At that point we we were like 40 people, so we've been growing very quickly. I can't get in too specifically to like our revenue, but basically we're well in the triple digit growth phase. We're still a small company, but we're growing quickly. Our number of customers it's up in the triple digits as well. So expanding very rapidly. And again we're a platform company, so we serve a variety of industries. Some of the big ones are health care, financial services. But even more in the industries it tends to be driven by these used cases I talked about as well. And we're building out our partnerships also, so that's a big part of what I do also. >> Can you share anything about funding where you are? >> Oh yeah, funding, you asked about that, sorry. Yes, we raised our B round of funding, which closed in March of this year. So we [mumbles], a company called Pelion Venture Partners, who you may know, Canaan Partners, and then most recently Scale Venture Partners are investors. So the companies raised a little over $32 million dollars so far. >> Partnerships, you mentioned Microsoft already. Any other key partnerships you want to call out? >> We're doing a lot of work. We have a very broad partner network, which we're building up, but some of the ones that we are sort of leaning in the most with, Microsoft is certainly one. We're doing a lot of work guys at Cloudera as well. We also work with Hortonworks, we also work with MapR. We're really working almost across the board in the BI space. We have spent a lot of time with the folks at Looker. Who was also a partner I was working with very closely during my Vertica days. We're working with Qlik, we're working with Tableau. We're really working with actually just about everybody in sort of BI and visualization. I don't think people like the term BI anymore. The desktop visualization space. And then on public cloud, also Google, Amazon, so really all the kind of major players. I would say that they're the ones that we worked with the most closely to date. As I mentioned earlier we're part of the Microsoft Accelerator Program, so we're certainly very involved in the Microsoft ecosystem. I actually just wrote a blog post, which I don't believe has been published yet, about some of the, what we call the full stack solutions we have been rolling out with Microsoft for a few customers. Where we're sitting on Azure, we're using HDInsight, which is essentially Microsoft's Hadoop cloud Hadoop distribution, visualized empower BI. So we've really got to lot of deep integration with Microsoft, but we've got a broad network as well. And then I should also mention service providers. We're building out our service provider partnerships also. >> Yeah, Chris I'm surprised we haven't talked about kind of AI yet at all, machine learning. It feels like everybody that was doing big data, now has kind pivoted in maybe a little bit early in the buzz word phase. What's your take on that? You've been apart of this for a while. Is big data just old now and we have a new thing, or how do you put those together? >> Well I think what we do maps very well until, at least my personal view of what's going on with AI/ML, is that it's really part of the fabric of what our product does. I talked before about once you sort of found the data you want to use, how do I use it? Well there's a lot of ML built into that. Where essentially, I see these different datasets, I want to use them... We do what's called one click functions. Which basically... What happens is these one click functions get smarter as more and more people use the product and use the data. So that if I've got some table over here and then I've got some SAS data source over there and one user of the product... or we might see field names that we, we grab the metadata, even though we don't require moving the data, we grab the metadata, we look at the metadata and then we'll sort of tell the user, we suggest that you join this data source with that data source and see what it looks like. And if they say: ah that worked, then we say oh okay that's part of sort of the whole ML infrastructure. Then we are more likely to advise the next few folks with the one click function that, hey if you trying to do a analysis of sales trends, well you might want to use this source and that source and you might want to join them together this way. So it's a combination of sort of AI and ML built into the fabric of what we do, and then also the community aspect of more and more people using it. But that's, going back to your original question, That's what I think that... There was quote, I'll misquote it, so I'm not going to directly say it, but it was just.. I think it might have John Ferrier, who was recently was talking about ML and just sort of saying you know eventually we're not going to talk about ML anymore than we talk about phone business or something. It's just going to become sort of integrated into the fabric of how organizations do business and how organizations do things. So we very much got it built in. You could certainly call us an AI/ML company if you want, its actually definitely part of our slide deck. But at the same time its something that will just sort of become a part of doing business over time. But it really, it depends on large data sets. As we all know, this is why it's so cheap to get Amazon Echoes and such these days. Because it's really beneficial, because the more data... There's value in that data, there was just another piece, I actually shared it on Linkedin today as a matter of fact, about, talking about Amazon and Whole Foods and saying: why are they getting such a valuation premium? They're getting such a valuation premium, because they're smart about using data, but one of the reasons they're smart about using the data is cause they have the data. So the more data you collect, the more data you use, the smarter the systems get, the more useful the solutions become. >> Absolutely, last year when Amazon reinvented, John Ferrier interviewed Andy Jassy and I had posited that the customer flywheel, is going to be replaced by that data flywheel. And enhanced to make things spin even further. >> That's exactly right and once you get that flywheel going it becomes a bigger and bigger competitive advantage, by the way that's also why the regulators are getting interested these days too, right? There's sort of, that flywheel going back the other way, but from our perspective... I mean first of all it just makes economic sense, right? These things could conceivably get out of control, that's at least what the regulators think, if you're not careful at least there's some oversight and I would say that, yes probably some oversight is a good idea, so you've got kind of flywheels pushing in both directions. But one way or another organizations need to get much smarter and much more precise and prescriptive about how they use data. And that's really what we're trying to help with. >> Okay, Chris want to give you the final word, Unify Software, you're working on kind of the strategic road pieces. What should we look for from you in your segment through the rest of 2017? >> Well, I think, I've always been a big believer, I've probably cited 'Crossing the Chasm' like so many times on theCUBE, during my prior HP 10 year and such but you know, I'm a big believer and we should be talking about customers, we should be talking about used cases. It's not about alphabet soup technology or data lakes, it's about the solutions and it's about how organizations are moving themselves forward with data. Going back to that Amazon example, so I think from us, yes we just released 2.O, we've got a very active blog, come by unifisoftware.com, visit it. But it's also going to be around what our customers are doing and that's really what we're going to try to promote. I mean if you remember this was also something, that for all the years I've worked with you guys I've been very much... You always have to make sure that the customer has agreed to be cited, it's nice when you can name them and reference them and we're working on our customer references, because that's what I think is the most powerful in this day and age, because again, going back to my, what I said before about, this is going throughout organizations now. People don't necessarily care about the technology infrastructure, but they care about what's being done with it. And so, being able to tell those customer stories, I think that's what you're going to probably see and hear the most from us. But we'll talk about our product as much as you let us as well. >> Great thing, it reminds me of when Wikibon was founded it was really about IT practice, users being able to share with their peers. Now when the software economy today, when they're doing things in software often that can be leveraged by their peers and that flywheel that they're doing, just like when Salesforce first rolled out, they make one change and then everybody else has that option. We're starting to see that more and more as we deploy as SAS and as cloud, it's not the shrink wrap software anymore. >> I think to that point, you know, I was at a conference earlier this year and it was an IT conference, but I was really sort of floored, because when you ask what we're talking about, what the enlightened IT folks and there is more and more enlightened IT folks we're talking about these days, it's the same thing. Right, it's how our business is succeeding, by being better at leveraging data. And I think the opportunities for people in IT... But they really have to think outside of the box, it's not about Hadoop and Sqoop and Sequel and Java anymore it's really about business solutions, but if you can start to think that way, I think there's tremendous opportunities and we're just scratching the surface. >> Absolutely, we found that really some of the proof points of what digital transformation really is for the companies. Alright Chris Selland, always a pleasure to catch up with you. Thanks so much for joining us and thank you for watching theCUBE. >> Chris: Thanks too. (techno music)

>> Narrator: Live from the Javits Center in New York City. It's the Cube, covering the Inforum 2017. Brought to you by Infor. >> We are wrapping up the Cube's day two coverage of conference here in New York City at Inforum. My name is Rebecca Knight, along with my cohost Dave Vellante. We're joined by Dan Barnhardt. He is the Infor Vice President of Communications. Thanks so much for joining us. >> Yes, thank you for having me. Thank you for being here two days in a row. >> It's been a lot of fun. We've had a great time. So yeah, congratulations, it's been a hugely successful conference, a lot of buzz. Recap it for us, what's been most exciting for you? >> Sure, this was our second year having a forum in New York, which is our home town. I think it was a more exciting conference than last year. We unveiled some incredible development updates, led by Coleman, our AI offering, which is an incredible announcement for us, as well as Networked CloudSuites, which takes the functionality from our GT Nexus commerce network, and bakes it into our CloudSuites, the mission critical industry CloudSuites, that we offer on the Amazon Web Services cloud. Those were really exciting developments, as well as some other announcements we made with regard to product. And then, in addition to product, we had a lot of customer momentum that we shared. Last year, we had customers like Whole Foods and Travis Perkins up here. We continued the momentum with big enterprise customers making big bets on Infor, led by Koch Industries who invested more than two billion dollars this year at Infor, and are now modernizing their human resources and their financial operations with Infor CloudSuites. Moving to the cloud HR for 130,000 employees at Koch Industries which is an incredible achievement for the product, and for cloud HR. And, that's very exciting, as well as other companies like FootLocker, which were recognized with the Innovation Award for our Progress Makers Award. They're using talent science, data science to power their employees, not to power their employees, but to drive their employees towards greater productivity and greater happiness, because they've got the right people in the right fit for FootLocker, that's very exciting. And, of course, Bank of America, our Customer of the Year, which uses our HR solutions for their workforce, which obviously is exceptionally large. >> Yes, there was a great ceremony this morning, with a lot of recognition. So, let's talk a little bit more about Coleman, this was the big product announcement, really the first product in AI for Infor. Tell us a little bit about the building blocks. >> For certain. We have a couple of AI offerings now, like predictive hotel pricing, predictive demand and assortment planning in retail, but we have been building towards Coleman and what we consider the age of networked intelligence for multiple years. Since we architected Infor CloudSuite to run mission critical ERP in the cloud, we developed the capability of having data, mission critical data that really runs a business, your manufacturing, finance, distribution core functions, in the cloud on AWS, which gives us hyper-scale compute power to crunch incredible data. So, that really became possible once we moved CloudSuite in 2014. And then in 2015, we acquired GT Nexus, which is a commerce network that unites, that brings in the 80 percent of enterprise data that lies outside the four walls, among suppliers, and logistics providers, and banks. That unified that into the CloudSuite and brought that data in, and we're able to crunch that using the compute power of AWS. And then last year at Inforum, we announced the acquisition of Predictix, which is a predictive solutions for retail. And when building those, Predictix was making such groundbreaking development in the area of machine learning that they spun off a separate group called Logicblox, just to focus on machine learning. And Inforum vested heavily, we didn't talk a lot about Logicblox, but that was going to deliver a lot of the capabilities along with Amazon's developments with Lex and Alexa to enable Coleman to come to reality. So we were able then to acquire Birst. Birst is a BI program that takes, and harmonizes, the data that comes across CloudSuite and GT Nexus in a digestible form that with the machine learning power from Logicblox can power Coleman. So now we have AI that's pervasive underneath the application, making decisions, recommending advice so that people can maximize their potential at work, not have to do more menial tasks like search and gather, which McKenzie has shown can take 20 percent of your work week just looking for the information and gathering the information to make decisions. Now, you can say Coleman get me this information, and Coleman is able to return that information to you instantly, and let you make decisions, which is very, very exciting breakthrough. >> So there's a lot there. When you and I talked prior to the show, I was kind of looking for okay, what's going to be new and different, and one of the things you said was we're really going to have a focus on innovation. So, in previous Inforums it's really been about, to me anyway, we do a lot of really hard work. We're hearing a lot about acquisitions, certainly AI and Coleman, how those acquisitions come together with your, you know, what Duncan Angove calls the layer cake, you know the wedding cake stack, the strategy stack, I call it. So do you feel like you've achieved those objectives of messaging that innovation, and what's the reaction then from the customer base? >> Without a doubt. I wouldn't characterize anything that we said last year as not innovative, we announced H&L Digital, our digital transformation arm which is doing some incredible custom projects, like for the Brooklyn Nets, essentially money balling the NBA. Look forward to seeing that in next season a little bit, and then more in the season to come. Some big projects with Travis Perkins and with some other customers, care dot com, that were mentioned. But this year we're unveiling Coleman, which takes a lot of pieces, as Duncan said sort of the wedding cake, and puts them together. This has been a development for years. And now we're able to unveil it, and we've chosen to name it Coleman in honor of Katherine Coleman Johnson, one of the ladies whose life was told in the movie Hidden Figures, and she was a pioneer African-American woman in Stem, which is an important cause for us. You know, Infor years ago when we were in New Orleans unveiled the Infor Education Alliance program so that we can invest in increasing Stem education among young people, all young people with a particular focus on minorities and women to increase the ranks of underrepresented communities in the technology industry. So this, Coleman, not only pays honor to Katherine Johnson the person, but also to her mission to increase the number of people that are choosing careers in Stem, which as we have shown is the future of work for human beings. >> So talk a little bit more about Infor's commitment to increasing number to increasing, not only Stem education, but as you said increasing the number of women and minorities who go into Stem careers. >> Certainly. We, you know Pam Murphy who is our chief operating officer, this has been an incredibly important cause to her as well as Charles Phillips our CEO. We launched the Women's Infor Network, WIN, several years ago and that's had some incredible results in helping to increase the number of women at Infor. Many years ago, I think it was Google that first released their diversity report, and it drew a lot of attention to how many women and how many minorities are in technology. And they got a lot of heat, because it was about 30, 35 percent of their workforce was female, and then as other companies started rolling out their diversity report, it was a consistent number between 30 to 35 percent, and what we identified from that was not that women are not getting the jobs, it's that there aren't as many women pursuing careers in this type of field. >> Rebecca: Pipeline. >> Yes. So in order to do that, we need to provide an environment that nurtures some of the specific needs that women have, and that we're promoting education. So we formed the WIN program to do that first task, and this year on International Women's Day in early March, we were able to show some of the results that came from that, particularly in senior positions, SVP, VP, and director level positions at Infor. Some have risen 60 percent the number of women in those roles since we launched the Women's Infor Network just a couple of years ago. And then we launched the Education Alliance Program. We partnered with institutions, like CUNY the City University of New York, the New York Urban League, and universities now across the globe, we've got them in India, in Thailand and China, in South Korea to help increase the number of people who are pursuing careers in Stem. We've also sponsored PBS series and Girls Who Code, we have a hack-athon going on here at Inforum with a bunch of young people who are building, sort of, add-on apps and widgets that go to company Infor. We're investing a lot in the growth of Stem education, and the next generation. >> And by the way, those numbers that you mentioned for Google and others at around 30, 34 percent, that's much better than the industry average. They're doing quote, unquote well and still far below the 50 percent which is what you would think, you know, based on population it would be. So mainly the average is around, or the actual number's around 17 percent in the technology business, and then the other thing I would add is Amazon, I believe, was pretty forthcoming about its compensation, you know. >> Salesforce really started it, Marc Benioff. >> And they got a lot of heat for it, but it's transparency is really the starting point, right? >> It was clear really early for companies like Salesforce, and Amazon, and Google, and Infor that this was not something that we needed to create talking points about, we were going to need to effect real change. And that was going to take investment and time, and thankfully with leadership like Charles Phillips, our CEO, and Marc Benioff were making investments to help make sure that the next generation of every human, but particularly women and minorities that are underrepresented right now in technology, have those skills that will be needed in the years to come. >> Right, you have to start with a benchmark and then know where you're moving from. >> Absolutely, just like if you're starting a project to transform your business, where do you want to go and what are the steps that are going to help you get there? >> Speaking of transforming your business, this is another big trend, is digital transformation. So now that we are at nearing the end of day two of this conference, what are you hearing from customers about this jaunting, sometimes painful process that they must endure, but really they must endure it in order to stay alive and to thrive? >> Without a doubt. A disruption is happening in every industry that we're seeing, and customers across all of the industries that Infor serves, like manufacturing, healthcare, retail, distribution, they are thinking about how do we survive in the new economy, when everything is digital, when every company needs to be a technology company. And we are working with our customers to help first modernize their systems. You can't be held back by old technology, you need to move to the cloud to get the flexibility and the agility that can adapt to changing business conditions and disruptions. No longer do you have years to adapt to things, they're happening overnight, you must have flexible solutions to do that. So, we have a lot of customers. We just had a panel with Travis Perkins, and with Pilot Flying J, who was on the Cube earlier, talking about how their, and Cook Industries our primary investor now, talking about how they're re-architecting their IT infrastructure to give them that agility so they can start thinking about what sort of projects could open up new streams of revenue. How could we, you know, do something else that we never thought of, but now we have the capability to do digitally that could be the future of our business? And it's really exciting to have all the CIOs, and SVPs of technology, VPs of technology, that are here at Inforum talking about what they're doing, and how they're imagining their business. It's really incredible to get a peek at what they're doing. >> You know, we were talking to Debbie earlier. One of the interesting things that I, my takeaway is on the digital transformation, is you know, we always say digital is data and then what we talked about was the ability to traverse industry value change, not just vertically but horizontally. Amazon buying Whole Foods is a perfect example, Amazon's a content company, Apple's getting into financial services. I wonder if you could comment on your thoughts on because you're so deep into micro-verticals, and what Debbie said was well I gave a consumer package good example to a process manufacturing company. And they were like what are you talking about, and she said look, let me connect the dots and the light bulbs went off. And they said wow, we could take that CPG example and apply it, so I wonder when we talk about digital transformation, if you see or can foresee your advantage in micro-verticals as translating across those verticals. >> Without a doubt. We talk about it as adjacent innovation. And Charles points back to an example, way back from the creation of the niche in glass, and how that led to additional businesses and industries like eyeglasses and fire preparedness, and we look at it that way for certain. We dive very deep into key industries, but when we look at them holistically across and we say oh, this is happening within the retail industry, we can identify key functionality that might change the industry of disruption, not disruption, distribution. Might disrupt the distribution industry, and we can apply the lessons learned by having that industry specialization into other industries and help them realize a potential that they weren't aware of before, because we uncovered it in one place. That's happening an awful lot with what we do with retail and assortment planning and healthcare. We run 70 percent of the large hospitals in the US, and we're learning a lot from retail and how we might help hospitals move more quickly. When you are managing life and death situations, if you are planning assortment or inventory for those key supplies within a hospital, and you can make even small adjustments that can have huge impact on patient care, so that's one of the benefits of our industry-first strategy, and the adjacent innovation that we cultivate there. >> I know we're not even finished with Inforum 2017, but we must look ahead to 2018. Talk a little bit about what your goals for next year's conference are. >> For sure. You're correct, we're not finished yet with Inforum. I know everyone here is really excited about Bruno Mars who's entertaining tonight, but we are looking forward to next year's conference as well, we're already talking about some of the innovative things that we'll announce, and the customer journeys that are beginning now, which we'd like to unveil there. We are going to be moving the conference from New York, we're going to move to Washington DC in late-September, September 24th to 27th in Washington DC, which we're very excited about to let our customers, they come back every year to learn more. We had seven thousand people attending this year, we want to give them a little bit of a variety, while still making sure that they can reach, you know, with one stop from Europe and from Asia, cause customers are traveling from all over the world, but we're very excited to see the growth that would be shared. This year, for instance, if you look at the sponsors, we had our primary SI partner Avaap was platinum partner last year. In addition to Avaap this year, we were joined by Accenture, and Deloitte, Capgemini, Grant Thorton, all of whom have built Infor practices over the last 12 months because there's so much momentum over our solutions that that is a revenue opportunity for them that they want to take advantage of. >> And the momentum is just going to keep on going next year in September. So I'll see you in September. >> Yeah, thank you very much. I appreciate you guys being here with us for the third year, second year in a row in New York. >> Indeed, thank you. I'm Rebecca Knight for Dave Vellante, we will have more from Inforum 2017 in a bit.

(soothing music) >> Announcer: Live from the Javits Center in New York City, it's theCUBE. Covering Inforum 2017. Brought to you by Infor. (energetic music) >> Welcome back to theCUBE's coverage of Inforum 2017. I'm your host, Rebecca Knight, along with my cohost, Dave Vellante. We're joined by Debbie Krupitzer, she is the vice president at Capgemini based in San Francisco. Thanks so much for joining us. >> Thank you for having me. >> It's your first time on theCUBE, so we're going to-- >> It is, I'm excited! >> It's going to be great. >> Great. >> It's going to be great. So, Capgemini has had a longstanding relationship with Infor but this year, things got a little more serious. So-- >> Debbie: It did! >> So tell us, give us a status update. >> I think we both saw the writing on the wall, which is around, my space is digital manufacturing, that's where I play, and they see it to. Right, so we see such a great opportunity around connected factory and enterprise asset management, and all these really good things that are happening in the space, and so it sort of naturally came together. So we've always worked with them, but we really saw an opportunity for this year to say, hey, this is an investment piece, we both have a lot of energy, a lot of passion around it, let's go make this happen. And so it's been super fun, lots of fun this week. >> AI has been a really big theme at this conference with the introduction of Coleman. Can you tell us a little bit about where Capgemini is putting its resources when it comes to artificial intelligence? >> Absolutely, I mean, we know it's the future. We know it's where it's at. And you know, I had a quote from Elon Musk, which was saying AI, they're taking over the world, robots are going to take over the world in less than about 45 years. I don't know if that's so much true, but what we are really focused on is the business value of AI, not in the sort of trend, or what's the hype of AI. Where can you practically use it? So for us, artificial intelligence could be consumer feedback, or it could be around machines, it could be where are we getting machines to talk to us, to tell us what's wrong? We see a ton of opportunity around this, and it's really exciting for us, but always with a pragmatic what's going to make us money, what's going to save us money, and our customers, that's what we're always focused on. >> So it's the business value. >> Always the business value. The technology hype is just the technology hype, and I think that's what we really love about this conference is that there's a practicality about it. So there's not this sort of, hey it's trendy, it's cool, let's just go do it. There's a lot of thought behind it, there's a lot of thought behind what we want to do, what we want to achieve, and what we want to invest in. And we see this as a big investment. >> So let's talk about people, process, and technology. On theCUBE, everybody always says technology's the easy part, and I think it's generally true. I think technology's generally well understood, there's a lot of open source stuff, pretty much everybody has access to generally the same technology, it's how they apply it, the processes they put behind it, and the people that really make the difference. Okay, so when you think about digital manufacturing, help us understand it, it's surely not my wheelhouse. You bring in the IT and the whole OT thing, you're bringing the IT and the operations technology worlds together, and those are worlds that have never really collided, so wonder if you could talk about that a little bit-- >> Debbie: I would love to. >> Some of the challenges that brings? >> Oh, and there's a lot! Right, so we call it the IT OT Convergence. So there's actually a name for it. So that's Operational Technology and Informational Technology, and you're right, the plant has always been its own kingdom. So whenever you think of manufacturing, these plants are like we are the kings, we do it the way we want, and they never really wanted IT involvement. But what we're finding is that the CFOs, the people who are spending the money, have already seen the value of IT in terms of Cloud, cost savings, enterprise, infrastructure. How do you apply those to the plant to get the savings, and how do you replicate it? So what we're finding is that there's always again, there's a cost factor, right? So they're going is there a way for us to leverage technologies across multiple plants where we can get those savings, versus plants just going and buying whatever they want. And that' what we're seeing as the big change. Now, you're always going to get a shift, 'cause our plant guys and girls, they're used to doing it the way they want. But the thing that we see is that we're not coming in and totally putting robots to replace these jobs. What we're coming in is making their jobs easier. We're making it more efficient. We're seeing ways to save them money. And so the plants get incented when they have outcomes where they save money, so they're really pretty interested in doing this too. >> So give us some examples of a robot working along side of someone on a factory floor. >> So, you know it's funny, but I'd say 80% of the companies we work with don't have robots. Robots are sort of a sexy cool thing that everybody thinks is out there, and they are out there and they're really cool, but normally with the robots its already highly processed, it's a highly structured environment, usually around high tech or the car companies. I'll tell you what's more fun for me, when they don't have anything, where it's still paper-based. That's more fun, because what you're doing is you're going in and showing them how you can add a sensor to a machine to give you information you've never had before. How can this tell us how to do something differently? Is there a process issue? And when you talked about technology always being the easy part, it really is. When we go into a factory, it's normally a people challenge, that's operator, whether the operator's not doing something correctly, or in the right sequence. It's process, is there a process challenge? The technology is normally the easy part. So for me, I'm that person who likes the really immature factory, 'cause that to me is where you make the most change. Somebody's already got robots, you're already doing cool stuff. I'm probably not going to show you too much. It's the ones where they have that ah-ha moment, where they go wow. >> And we've been hearing this, that a lot of this stuff is change management. So how, from Capgemini perspective, how do you approach these challenges? >> You want to get always executive buy-in, right? So it's when it's coming from the top, I think that always is really valuable. But for us, we're plant floor people. I mean, I say you got to go talk to these folks and make them understand why you're doing it and what you're doing. Because there's always fear, right? Fear of anything, fear it's going to take your job, or fear you're not going to have a job, and what we're saying is it's a reallocation. The fact is this, in our space we've got an aging workforce. And aging workforce's going away. And the Millennials don't want to work a factory floor. And the reason they don't want to work a factory floor, it's dirty or they don't think it's the kind of work they want to do. We're trying to modernize that. Use an iPad, get IoT, get technology. You're not working the plant floor, you're working a dashboard. You're looking at data, you're driving data decisions, and so we call it From Shop Floor to Top Floor. How can we drive that so our Millennials, the ones who really do want to be the guys to take, and girls, to be taking these jobs, how can we make it more exciting for them, and we think there's good opportunity for that. >> So it really is all about the data, and when you think about the factory floor, a lot of analog data. And when you talk about process, a lot of process that's changing as a result of that analog to digital. So could you talk about the data, the data architecture that you're seeing and what the discussion is around data, data value, and how to get the value, how to monetize data, not necessarily by selling data directly but how it contributes to revenue generation or cost cutting? >> Well, we say data is the new oil, but I always tell my clients it's new oil, but it's not refined oil, and you've got to refine it. And refining the oil or refining the data is finding the business value out of that data. And you're right, there's a lot of data out there. The questions we get from the manufacturers are, what data is valuable, what is not valuable, what do I need, what do I not need, what can I aggregate up? I think the most interesting thing, and I love stories, is that when you look at a line, you've got machine number one to machine number 10. And before they would never know that something that was happening on machine number one, even a small configuration or change in a widget was actually impacting machine number 10. They never had that before. Now with that data, we're taking the data off of those singular machines, we're putting it up into the Cloud, we're aggregating it, we're able to see these anomalies and go, wow, that's the reason why. We never had that before. So you'd have engineers that would go, it must be machine number 10 or it must be machine number nine, or we don't really know what's going on. Now we're able to trace that; that's great. >> So I wonder if you could share with us any insights you have around discussions going on around IP, and data ownership? Because imagine, hypothetically for example, you've got some kind of programmable logic controller, and the PLC manufacturer is collecting data because they're trying to predict the maintenance, or whatever it is, and then of course the factory is the whole system and they're collecting data. So who owns that data-- >> Debbie: Oh that's a good question. >> And what's that conversation? >> Well, I'm no lawyer and so I'm not going to get into it. So I think what you'd find is that it depends. And that's a consultant answer, but I'm going to say it depends. If you're talking about the machine data, you have bought machines that are from a manufacturer. The manufacturers would love to have that machine data, 'cause they want to know what's going on with their machines. You want to know what's going on with the machine on the floor, very specific use case, which is what's happening in my space. The manufacturers want to know what's going on in a general way, how do we make our product better, how our are customers using it? In my mind, a plant shouldn't mind about that. A manufacturer wants to get that data to make better product, faster to market, make it cheaper, easier to buy, great, take it. I think where you get challenges is when there's outcomes that are coming out of data that people are leveraging to resell as business models. I think that's where people go, but that's our proprietary customer information about how we do a specific process, or how we do something. I think that's where people get a little iffy. And I don't really see that happening so much. So much, right, and I get everybody is really scared about the Cloud. I think the interesting thing is they'll say, well we don't want all of our data, our proprietary data in the Cloud 'cause it's not secure, and what I want to tell 'em, it's more secure in the Cloud than it is at your plant. >> So that's, I'm less concerned about the security of the Cloud, maybe it's different and you got to do some extra work to figure it out. I'm more concerned with our clients around the other thing you were talking about. I'll ask you specifically. If I'm using some kind of AI and I'm developing a model using machine learning and I'm training that model, maybe it's my data, but the model, my data's informing that model. How do I know that that model is not, somehow that IP of mine is not going to end up at my competitors, and is that going into discussions and contracts and agreements? >> Absolutely it is, and I think what you'll find is a lot of vendors that are out there that are dealing with AI and data are having to set clauses up that say you will not use this data to feed into any of your algorithms, into your IP. Like do not take my data. 'Cause everyone thinks, what we do is special, and some of it may be, do not take that and learn from us. That's very specific in clauses and contracts that we're seeing. >> Is it kind of like the honor system, or is there, is there a digital way to track that? >> Yeah, I think what's getting interesting is we get the data, like the companies aren't dumb. They're hiring their own data scientists, they're not letting us go to external parties. They're saying we're going to hire our own data scientists, and we'll start segmenting the data for you. They're very clever, you know, business people are in business because they know how to make money. They're not dumb. So what they're doing is getting a whole new set of roles. They're hiring data scientists. They're hiring data architects. They're hiring people in that understand the data structures so that they can keep track of what's valuable and what's not, don't worry about it. So, I think that's a smart thing to do. Because it used to be pretty rogue. I mean, five years ago, people would be like, well I don't care if you take the data off my machine. I think people have gotten a lot more clever, and also seeing that some of the vendors are repurposing some of this data for their own profit. Nobody wants that, don't take my stuff and use it to profit yourself. >> And you were talking about earlier, just the idea of what's valuable data and what'd not valuable data, and we find we are in this deluge of data. And we don't even really know, you can't say for certain, that data is not valuable, so don't worry about it. >> Exactly, and I think that's the challenge we get is that everybody thinks it's like a pile of money. Like, that's money, don't get rid of that money. >> Rebecca: It's oil! >> Oil, don't get rid of that, right? But what we find is you're getting so much data, some of the data is really not as valuable. And I'll give an example. An on-off switch telling me the motor is running on a machine is not valuable, it doesn't matter. It matters to that company because they need to know that the machine is working, so what we want to do is segment data, and we want to be able to give the business value, or have a hypothesis around what that data is bringing us. And sometimes, I'll tell you, a lot of times a hypothesis from my business users is wrong. So they'll say, what we think of A and B is super valuable, and then we'll go in and like, actually it's not A and B. It's E, E is actually the data stream that actually has the most value for you, and this is why. And so that to me is a really fun part, 'cause they have to have that moment where they go, oh, well we were wrong about that. It wasn't, I say, you're not wrong, it's just different. So I think having that data and then understanding what you're holding on the edge, what you're putting on Cloud, what you're putting on print, what you're able to share just makes people smarter about what they've got. >> So the accounting industry doesn't have standards as to how to value data on a balance sheet. We know that. But are there off-balance sheet discussions going on that you're having with your clients in terms of helping them understand the value of their data, quantifying that value? Everybody talks about the data is the new oil, you got to be a data-driven company and all this commentary, but how do you turn that into actionable, tangible results? >> That's the hard part, right? So that's the meat of the problem. And I think what we do is we really have to deep dive with our clients to understand what's the business model, or what do they think is going on? Because we've had lots of byproduct data that's come off of certain things that they had, and we were like, this is actually a more interesting tangent here, which is a byproduct of that data that you've got. Have you guys thought about selling that? So we'll come in and come up with business models, and so Capgemini has got, we've got Cap Consulting, we have these great acquisitions that we've just made where they'll come in and we've got people who do that. Who say, this is a new business model, have you thought of a resale, or this is something that's very valuable. And we'll go in and deep dive, a lot of times it's just discovery. We don't know either. So we'll go in and say, okay, this looks interesting, have you thought about this, and just new ways, it's just new business models. >> Do you see organizations and are you helping organizations actually apply maybe conventional financial measures, whether it's NPV or enterprise value, and are they beginning to track that, and what can you share with us? >> It's so funny you said that 'cause I just, when I just was coming here and I had a lead, I had a hot lead but I had to leave and come and do this interview, and he was asking me, and I said, the one thing we do is value map your processes and your data. And it was a thing that intrigued him. He was like, how do you do that? How are you doing that? I'm like, well, what we're doing is actually, we take all of your data from a historical standpoint, and we can see what's going on historically. Now the interesting part is how do you go forward with that? And so what we're finding is that you look at this data and you say what's the value mapping in terms of where you make money? And that's different for every company, and so we work with our customers. And so literally what I do is plot here's this process, there might be 15 processes that are going on. Here's the data outcome of that process. Now you talk to me about the value in terms of where you guys make the most money. >> You know, that's interesting, because data has unique value for different processes, obviously, so you have to understand it's not fungible like a dollar bill. And so that's what you can do is share this video with your hot prospect. (laughter) >> Debbie: Exactly! >> Maybe start a deeper conversation. >> I did, I told him, I have to go but I'll be back, so hopefully he's still warm over there. But I think people don't realize that the value mapping that you do is really a standard value, like you staid, standard financial models, the net present value, all those things, ROI, all those things we've always traditionally done on every project we do the same exact thing with this. For around digital manufacturing, because what we want to do is optimize. We want to optimize on what's going to save you the most money or make you the most money. And it's really that simple. Does it save you money, does it make you money. >> So you're applying sort of conventional measures to data, mapping that to processes, and then driving business outcomes, and then quantifying that over a lifecycle. >> You got it, that's exactly it. So you gave away my secret, so now you're going to start a technology firm. >> So that's high level, sounds good, but it's not trivial to do that, you need expertise, you need the main expertise. >> You do, and every manufacturer is different, right? So I work in discrete and process manufacturing, very different, very different processes, very different ways. Process manufacturing has a little bit more complexity, not that discrete doesn't, but it's interesting because what we do is find different things for different industries too, right? Now, there's some comparables, like food and pharma. Food processing, pharma is very similar, and people don't realize that, but it's very similar. And so we're always making comparisons. Pharma's a little bit more regulated, I think that might scare people, right, 'cause they want their food to be really, it is regulated, but maybe not as regulated as your drugs. And so what we find is the hypothesis or use cases that we can leverage and repurpose across industries. And I can't tell you how many times I've been in an industry and I just had one, and it was automotive, and I gave them a consumer packaging use case where they looked at me like I was crazy. And they said, I don't get it. And I connected the dots for 'em. And I said, do you see where if you've got this in consumer packaging, what they're looking at the quality of the packaging from start to finish, and I gave them the, you know, I won't go into the details. But they had this, they just went, oh yeah. And so I think what we're finding is industries that used to be like, if you don't know automotive, if you don't know mining, you don't know consumer packaging-- >> Dave: So true. >> You don't know us, you don't know us. >> And that's changed. >> And that's changed. So what they're seeing is they're going, you know what, 'cause they're seeing like the Amazons, they're seeing these companies, you know Amazon just bought Whole Foods. What? And they didn't buy Whole Foods for the grocery, they bought them for the data. And so I say like, guys, think of this in a different way. You've got to look at other industries, and so we're getting that more and more. We'll bring them out to have discussions about innovation or what's new, cool technology, and I bring it from every sector. Now, most of the time they'll go, show me how that's applicable? And I'll show 'em, and they go, wow. We get it. >> That's a great observation. Because digital means data, and data means you can traverse industries in new ways, so I love that CPG example. You would think, what? But you're getting people to rethink. >> You really are, and they're seeing, they're like, you know, they've got to reinvent themselves. Companies are having to reinvent themselves to this digital age, and they're scared. And they're saying, we sell a commodity, what can we do differently? How are we going to survive? I don't want to be the Kodak, I don't want to be the Blockbuster, I don't want to be that company. And so we're constantly pushing our product, companies that go what are you doing different, how are you going to the next level, is it data, is it services? >> Dave: What business are you in? (laughter) Right, I mean. >> Exactly. >> Well everyone's a software company. >> It's causing people to rethink that, I mean it sort of, we're back to the what business are you really in question. Like we were twenty years ago. >> It really is, it just cycles, right? And I say everything cycles around, we're doing the same thing, we're just repackaging, call it something else. So we all do the same thing over and over. >> Well, but there are some differences. >> There are, of course, more technology, better technology, cheaper technology. I think is what I'm finding is that the price of sensors and the price of technology is going down, that it's becoming more affordable. So, what I used to hear from the manufacturers is like, well I can't afford that, we can't do that. 'Cause there're very lean margins in manufacturing, I mean there's a lot going on. And we're being able to show them, hey, it's not a ton of investment, this isn't like a 20 million dollar ERP. Small increments of money that show you how to get the save. >> Well, 20 years ago, you were purpose-building specific technology stacks for your customers, and today you're leveraging. Whether it's Cloud, a security layer, a data layer, you pick it and you're building on top of this digital matrix. And really focused on the business models, more so than the technology. >> It is, and that's what we're seeing. And I say that's why, to get back to the first question about OT IT Convergence, that's what my CFOs see. They go, we get it. We get it, now let's apply it to the plant, so let's go see how we can scale this. 'Cause you're talking anywhere from companies having 20 plants to 200 plants, that's a lot. And they want to see how they can repeat in scale, and so that's what we love about it. It's turning into a business conversation. It's not a technology conversation, which I love. >> Debbie, thank you so much for joining us. >> Thank you! >> You made it! >> I did it, yay! I got it, thank you so much. >> I'm Rebecca Knight for Dave Vellante, we will have more Inforum just after this. (rippling music) (rippling music)

>> Voiceover: Live from the Javits Center in New York City, it's The Cube, covering Inforum 2017. Brought to you by Infor. >> Welcome back to The Cube's coverage of Inforum. I am your host, Rebecca Knight, along with my co-host, Dave Vellante. We're joined by Terry Wise. He is the Vice President of Alliances for AWS. Thanks so much for coming on the program again. >> It's great to be here, yeah, thanks. >> So we are now a few years into this relationship with Infor. Where are we? Put things in perspective for us. >> Oh it's a great question. I think in some respects, this is arguably the most mature and strategic relationship we have. We've been working with Infor for, I've been at Amazon now nine years, and a better part of my nine years, we've been working with Infor, you know. In the early days it was awesome, before Infor bought the company. And, they've always done a great job of pushing us to be more enterprise-centric, more innovative in our platform and services. So it's very mature from that perspective. But I'd say, also at the same time, we're just entering a whole new days. We'd like to call it Day One at Amazon. If you look at some of the things that Charles and the team announced today with Coleman, and some of the new functionality and the growth of the cloud, I mean, we really are still at the early stages of this relationship, which is exciting. >> You know what's interesting to me Terry is, you know, Andy always talks about the fly wheel. He was, sort of, the first to use that terminology. And I was sitting in the endless meeting yesterday, and Infor was going through its architecture. And I just saw a lot of fly wheel in there. I mean, there is DynamoDB in there. I certainly saw S3. I think there was Kinesis, in terms of time series stuff. I think I saw Redshift in there. And so I wonder if you could talk about how this company, specifically, but generally, how people are leveraging net fly wheel of innovation to drive value for their customers. >> Yeah. And again, I think this goes back to the relationship we've had with Infor for so many years. Cloud is not just about cheap computing storage. It's really about platform and innovation that comes from that platform. And, you know, and partners and customers, like Infor, that have been with us a while, and they've got the skillsets internally, they've got great vision for how they want to take their customers with application functionality. They're really ripe to be able to take advantage of all the innovative platform services we build. Kinesis, Lambda for serverless computing. We're talking about some neat things around Edge. You heard Charles and Duncan today talk about Lex and some of the AI capabilities we have that are underpinning Coleman and some other new offerings. So they really are, kind of, the poster child for adopting our new services and driving innovation on top of our platform for their customer base. >> So where, if you can, look into your crystal ball a little bit. Where will we be a year from now, three years from now, with these technologies? >> So if I look out a year, I think, you know, rapid global expansion. You know, we're long past in many respects, sort of the, the early questions around cloud. Is it secure? Is it cost-effective? Is it robust and reliable? We're really past that if I look out across the globe. And now it's a question of how can we help enterprises adapt faster. And that's really, probably, the single biggest question I get from enterprise customers is, "This is great. Help me move quickly." And I think one of the neat things about the Infor relationship is, because they've packaged all of this innovation, into a set of business applications, they're actually helping customers move to the cloud quite a bit faster, and get that great value prop of cost efficiency, security, innovation, et cetera. Looking out three years, I think Duncan and the team did a very nice job today talking about the interaction ad user experience of how you're going to engage with business software moving forward. It's going to be very voice-driven. It's going to be predictive in nature so it's actually going to tell you what you need to think about versus going to a terminal or even a mobile device. So much left to do in that space. But I really do think, you know, three years from now, machine-learning won't be a buzz word, nor will artificial intelligence. It'll just be a bigger part of our daily lives. >> We were talking to Chip Coyle a little bit about trying to debunk some of the myths in cloud, specifically Amazon cloud. And I mentioned Oracle, saying that core enterprise apps really aren't going to the cloud, that's why you need Oracle. And they've got a strategy to do that, you've seen it. But then you going to see Infor, 55% of their business is in your cloud. They look like core enterprise apps. So is it, my question is, help us debunk that myth. But is it narrowly confined to companies like Infor, or are there examples of others? I mean, certainly there are companies, you guys have unbelievable logo chart. But when you peel back the onion, many of those apps are cloud-native or emerging apps. Those core of enterprise apps, we're seeing it from Infor. I wonder if you can add some color to that and are there other examples? >> Absolutely, I mean, I think there's others in the market that may be uncomfortable with the change that's happening with cloud, and therefore might be incented to try to slow that down. But I will say, the vast majority of all software companies we're engaging with are moving mission-critical enterprise apps to AWS. Some built natively in SaaS, like Infor is done. Others that are enabling, certifying their applications, SAP is another good example. You can kind of go across the stack, Adobe, AutoDesk, Siemens PLM, for product lifecycle management. And if you think about, you know, that's putting companies' core IP, the product development into the cloud to take advantage of all this agility, scale, cost-savings, et cetera. So it's been happening for a long time. Di-so is another great one, very innovative but somewhat conservative french company. They were very early on in the journey with us. And again, that's, you know, IP used to design airplanes, the things we fly around it. So it's been happening for a long time. It's accelerating. And I would say the other trend we're seeing is the companies out there that are resisting, we're hearing more and more from customers that, "Hey, that company is not helping move me to the future. Can you help me find an alternative?" So there's this big movement for enterprises to actually migrate out of legacy platforms, whether that's hardware or software, and move in to the cloud-native platforms, which are the future. >> So we see, we've been talking on The Cube for years about this whole digital transformation and how it's going to allow companies to play in different industries. Amazon, obviously. Retailer just purchased Whole Foods, getting into grocery. It's a content company. So Walmart said, "Alright, we're not going to put our stuff "in the Amazon cloud." Netflix obviously does. How do you deal with that? The obvious competitive fears of some of the customers that you have for AWS? How do you message that? And what do you tell the world? >> Sure, the first thing is, I mean, AWS, while it is part of Amazon.com, we are a separate operating group. And we've been that way since the beginning. So yeah, Amazon is a customer, just like Netflix or Nordstrom, or any of the other, you know, millions that we serve. Now a very hard customer and a very good customer. And they help drive our innovation road map. But we don't treat them any differently than we do, Netflix or the others. And part of that has to do with how we protect and secure the information that those companies put on AWS. So there's some companies out there, the one you just mentioned, that's still may be a bit uncomfortable, for whatever reasons, competitive reasons, putting information or having third parties put information related to their business on AWS. Yeah, I think that's unfortunate, I think. And it also talks about two different philosophies. We take very much a customer-centric view of the business. What's best for the customer. And if one of our partners has a better capability, we've got plenty of partners that have similar products to what we offer, but if it's the better product for the customer, we're more than happy to support that. Whereas others out there take a very competitive focus to the market. Where it's, they're watching what their competitors are doing. They're trying to head them off at the pass, or copy what their competitors are doing. In the long term, I don't think that's a fantastic strategy 'coz you're never really innovating on behalf of the customer. You're never giving them the best solution. You're actually preventing them from getting something that could be beneficial to that customer. And we just don't believe that's a long-term great business strategy for our customers and for ourselves. >> We recently saw the announcement of Amazon purchasing Whole Foods. Can you talk a little bit about this for our viewers. And talk about where, how you see the future of grocery and retail, where it's going. >> Sure, so we've announced our intention to purchase Whole Foods. It has not happenned. There's still some work to do there. But I think, you know, anytime we look at, you know, how we're going to expand, either organically or through acquisition, it's about, what are the synergies between our existing business, what the customers are looking for, and how can we create a better experience for that customer. How can we do it at scale? How can we innovate around that model? And then, you know, how can we make that a great long-term experience for the customer that ultimately drives the success and growth of our business, but also the partners that we bring in, whether again through acquisition or through third party partnership. This is kind of a, you look at this as a natural move as we look at what our customers are telling us, "Hey make it easier for us to purchase groceries and "household items." You know, and do it in a hybrid way, both, you know, combination of online and more from the physical presence. >> Terry I wonder if you could talk about, we mentioned the Edge before. And as you build out your partner strategy and the partner ecosystem. Talk more about the Edge, where it fits. Analytics at the Edge, and Amazon being the cloud, so what's your point of view on what happens at the Edge, what moves back to the cloud, the expense of moving things back to the cloud. What's your thought on that whole thing? >> Well, there's so many use cases for Edge computing. I mean, take the mining industry. You're putting huge trucks in the middle of nowhere that may have limited or very expensive connectivity. And they're capturing all kinds of, you know, information, during the natural operation of that machine. And it just makes sense that you want some level of data processing, storage, and analytics to happen on that machine. It could be a cruise ship, it could be a naval vessel, it could be an airplane. There's, you know, lots and lots of different applications there. But by doing some of that processing at the Edge, you're actually limiting the amount of data you have to send back to the central cloud. But of course, if you want to take full advantage of the analytics, you actually have to match that data with all the historical data and other real-time data that's resided in the cloud to get the result you're looking for. So it really becomes, you know, kind of this hybrid computing model. So some of it is efficiency around how much data you're sending back and forth. Some of it is just efficiency around processing, the point of data capture. Some due to connectivity reasons. Some due to other. It really is kind of this interesting new extension of hybrid cloud, if you will. We're very excited about it. >> You've made some moves in that area. I mean, Snowball was, I think, you know, one of the first. And there are other sort of Edge, what I would consider Edge-like devices or solutions. How dogmatic are you about everything living in the cloud? I mean, those are steps. Should we expect, you know, increasingly extending the reach of the cloud or is it just really going to all, your world come back to the AWS clouds? >> Yeah, yeah. It'll certainly be an extension of the cloud. That's already been happening. I mean, if you look at hybrid cloud. I think we've always been a supporter of hybrid cloud if you look at our roadmap going back many, many years with virtual private cloud, with Direct Connect, with some of the newer capabilities like Snowball, and, of course, Greengrass, our Edge capabilities. We're really extending the reach out to be much more of a hybrid store. 'Coz we recognize that not all the data today exist in the cloud or AWS in the future, you know. We think most applications will run in the cloud because the value proposition is so strong across so many different dimensions. But today, there's plenty of other places we have to connect to, again to capture the data. Now, I do think the vast majority of the data that we're capturing will be either pre-processed or sent natively into AWS to create a massive data leg so that you can start to drive these innovative machine-learning and artificial intelligence applications. The predictive analytics, the algorithms. They just don't work if you don't, they don't work effectively if you don't have massive amounts of data and you continuously refresh that data so that the algorithms can continue to learn. >> I want to double click on something you said about the value. To capture most of the value, your belief is that it's going to be in the cloud, one cloud. And others obviously have different view for a variety of different reasons. I buy the cost argument. You didn't make that argument, I'm making it. The marginal cost of having a single cloud. You know, standard, how much an A it is, superior. I'll grant that. What else is there though? Is it speed? Is it innovation? Is it standardization across the base? >> The single biggest value that I hear from customers today, but they love it, they love the cheap hosting fees, the efficiency part of it, but it really is the speed and agility. It's certainly the security model as well. I would say that most, almost every organization now that we talk to, once we've had the chance to educate them, if they haven't already done so themselves, has determined that the cloud-computing security model is much more effective than they could deliver on their own. We can just invest more. We can experiment more. We can have have multiple certifications across different industries, which every customer gets to take advantage of. But I would just come back, it's the ability to move quickly whether it's moving into new market. I was just in Europe, we were talking about it. It's so volatile there right now on so many dimensions with Brexit and some of the nationalistic politics things that are happening. Potentially the opening up more of the Middle East with the sovereign wealth funds comin' into play. There's just so much opportunity that enterprises need to be able to move quickly. And if they have to go stand up a data center somewhere else, or they can't deploy the software quickly, they're at a competitive disadvantage. So the single biggest driver from what I hear from customers and what I'm seeing is agility. >> Yeah, okay, so just to clarify, I said, cost not price. But we can debate that some other time. (Terry laughs) You just came back from Europe. You mentioned Brexit. What about things like GDPR which has taken effect but the penalties go in effect May of 18. Obviously that puts a lot of pressure on the cloud provider, as well as your customers. What are you hearing in Europe? And generally and specifically GDPR. >> Yeah, I mean, I would say the regulatory environment everywhere, but specifically in Europe, continues to evolve and it's fairly fluid. We've spent many years working with the various different regulatory bodies. The Article 29 Working Party. That's actually been crafting a lot of this legislation. So we're heavily influencing, because, if you step back, people said you couldn't do cloud, but they didn't explicitly say you could. (Rebecca and Dave laugh) So, customers are meant to, "How do I interpret this?" And some, you know, like, if I look at Nel, and I look at Societe Generale, and I look at BMW, and some of, you know, our forward-leaning European customers, Siemens is another great one, who was one of the original companies to put PII in the cloud. Here's a big German company putting PII in AWS a number of years ago. So we figured out how to get, not get around, but interpret the regulations, and then also ensure that we've got the features and capabilities to make sure that they comply with those regulations. So the full audit trail, the ability to encrypt data, the ability to make sure that data storage and localization is complying with, whether it's a country-level regulation or an industry-level regulation. So we continue to spend a lot of time and effort, monitoring and influencing that. And then building the services to make sure our customers fully comply. >> Well, you've always done well with permutations and complexity and automating that, so it's going to be fun to watch. >> Rebecca: It will indeed. >> Great. >> Terry thanks so much for joining us. We really appreciate it. It's been a lot of fun talking to you. >> Yeah, great, thanks, appreciate it. >> I'm Rebecca Knight for Dave Vellante. We will have more from Inforum just after this. (upbeat music)

>> Narrator: Live from the Javits Center in New York City, it's The Cube, covering Inforum 2017, brought to you by Infor. >> Welcome back to The Cube's live coverage of Inforum 2017. I'm your host, Rebecca Knight, along with my cohost, Dave Vellante. We are joined by Corey Tollefson. He is the senior vice president and general manager for retail here at Infor. Thanks so much for returning to The Cube. >> Happy to be here. >> Good to see you again. >> Looking forward to this, again. >> So you were, this was launched about 18 months ago, so give our viewers a status update, where are we? >> Well, it's been an amazing ride, so just 12 months ago, I think we talked about the initial prognosis of the business unit. Yeah, we just ended our fiscal year, we did about 77% year over year growth, we expanded into new markets like New Zealand and in Europe, we just opened up a brand new office in London, and we're thrilled with the market reception of our solutions. >> So talk a little bit about the solutions that you're coming up with, I mean, retail, or actually, let's back up. Let's talk a little bit about the state of retail right now and what the retailers themselves are feeling, and also, the customer experience. >> Yeah, I mean, anybody that shops understands that retail is in a complete disorder. I'd say chaos and disorder right now. >> Let's do some shopping! >> (laughs) >> Yeah, exactly, well, that's a great point. So when you think of retail, think of post World War II, where basically, the premise for retailing was an anchored mall with knowledgeable shoppers, or knowledgeable workers, associates that knew about their product, they were very product-centric. It was all about taking the car and the family and going to a destination and making it about your day. The reality is, the e-commerce world has changed the business model so much that retail is centered around these iPhones, and the smartphone, that it's 24 hours a day, 365 days a year, and that the power of the information has now shifted from the store associates, to the actual consumer, so consumers and customers can walk into a retailer and have more knowledge, not only about the products that you're selling, but even your inventory levels, you know. Looking online, being able to buy on, search online and come into the store and purchase something, so. >> Yeah, so, I mean, there was always an asymmetry, pre-Internet, the brands had all the power, they had all the information, and then it's, as you say, it's totally flipped. In many ways, digital transformation is about trying to create that balance of power again, back in the hands of the brand, right? >> Yeah, I mean, it's funny how, if you look at it over the last 20 years, at first it was the brand and the manufacturers had all of the influence, and then, the whole concept of category management and allowances and things like that in the '90s, the retailers started to have the influence. Now the reality is, it's not even the retailers or the brands anymore, it's the customer. The customer and the consumer have all the influence in the world, which is making so much chaos and disorder around what's retail and the lines have blurred between what's a brand manufacturer and what's a retailer. >> So everyone's got their sort of, I've got to compete with Amazon strategy. What are you seeing that's, that's actually working? >> Well, what's happening in the industry, you know, you may have heard that Amazon put an offer in on Whole foods and ... >> I have heard that, yeah. >> You may have heard about that, so, what it does is it's basically validating our strategy two and a half years ago, when we had the idea of putting together this retail team and what we've done since then, around, you know, modern, beautiful applications that are fueled by science and analytics, that have a beautiful user experience, all those types of technologies are codified over the last two years, and best practices that we've created by using our relationships with Crate & Barrel and Whole Foods and DSW and Nordstrom, as opposed to stuff where that was written in the 1990s. So that's what we believe has been helping our, our progress so far. >> So you've worked with Macy's and Nordstrom and Williams-Sonoma, DSW. What do you think customers want? I mean, you're talking about beautiful applications, a user experience that is satisfying and easy. >> Well, it's funny that when we talk about things like this, I mean, I just mentioned beautiful user experience because customers want to enjoy the shopping experience. You know, Duncan mentioned it earlier on the main stage around next-generation applications are almost headless. You know, the next UI is AI. >> (laughs) >> Right, it's the, it's the UI that doesn't exist, and that's where our applications are going as well. Now it's about holding onto that data, that analytics, that science, and presenting that in a format that's an offer to our customer's customer. >> Speaking of AI, you're really the first cloud suite that is going to be able to take full advantage of Coleman, the new product to launch today. Tell our viewers a little bit more about how you anticipate using Coleman. >> Well, I could get into the whole, "Coleman, tell us to look up a promo, "Coleman, tell us about this price change," there's all those different types of technologies. We're exposing all the data, so anything can be accessible by Coleman around our analytics platform. And one thing that does differentiate us is, we don't view our systems as silos, so, our execution engine for core item merchandising and our omni-channel merchandising system, and our advance analytics and forecasting and planning and replenishment system, are built on one common stack, so that it's common whether it's analytics or execution, they're converged together, so it allows us to be able to take advantage of technologies like Coleman. >> So there was an article in the journal the other day talking about how Apple was actually behind in ... You'd use the example of Siri, anybody who's used Siri knows that it, maybe not quite as where we'd like it to be, and Google and Amazon have the data, and maybe that helps them sort of lead. What is your corpus of data, obviously GT Nexus is part of that, what, but you've got to have the data source, it's all about the data, what's your data corpus? >> I'll give you a real world use case, so two years ago, when we announced the Whole Foods project, one of the design principles that we definitely went forward with, was the whole concept of no, no hierarchies, unlimited attributing, unlimited information around item, because we want to take all that information and all that attributes associated with the item, and we want to load it up into our machine learning solution. >> So, very flat. >> Very flat. We want to load that up into our advanced machine learning in our data platform in the cloud, and we can make as many science recommendations against all that information that's aggregated. So, ah. That's one of our ways in which we differentiate as well. >> Okay, and then, the other thing is, when I look at your, and we saw Soma was presenting to the analysts yesterday and putting up some architecture slides and, there was a lot of AWS in there. It appears that you're heavily leveraging that Amazon, sort of innovation flywheel. How does that affect your business? >> Well, it's a sticky wicket, right? I mean, what we've learned from working with Amazon as well as AWS is they're distinct organizations and we spent a lot of time with AWS because they spend so much money, it's been a nuclear arms race over the last decade to see who could spend the most money to build the best infrastructure and plumbing, and there is a wall that segments the two from each other, but that doesn't preclude us from working with other clouds. There's other clouds that we can use from our customer. I mean, some of our customers have requirements around leveraging Microsoft or Google, and we're happy to work with those clouds, too. >> I want to talk a little bit about international expansion. You mentioned a new office in London and also a new one in New Zealand. London seems like an obvious destination, New Zealand, not as much. Can you just explain to our viewers a little bit about why those two places? >> Well, I think the first part of that is, it's English-speaking. >> Okay, fair enough, yes. >> It's a little bit easier with less translation requirements related to those markets, but what we really like about London, is it feels like they're catching our momentum that we had two years ago in North America, and the reception we've had in London has been insane. And I wish I could be in a position to announce all the recent wins that we've had in Europe, but there's going to be more to come as well, in announcements. >> Okay, so, what are you hearing here? A little over a year in, what are the customers here telling you? What they like, what they don't like, what they want. >> Well, I think what a lot of customers are asking for is, they want to see acceleration a road map. They believe in concepts like Coleman that we had mentioned this morning, they want to take advantage of that as quickly as possible. And for us, we can provide a prescriptive journey, and it doesn't need to be a big bang where you have to deploy this huge, monolithic system. I would love nothing more than to have all of your system, all of our customers and prospects take advantage of all of our systems, but the reality is, there's some legacy systems they don't want to touch, that's okay, that's fine, we can make SAP smarter by having the best analytics platform in the retail on the planet, we believe, you know. We can take advantage of that horizontal ERP that you're running by taking advantage of some of the burst functionality, where we can come in and start taking information out of different, disparate silos. So there's not just one way of digesting an experience with Infor. >> So a lot of the ways in which companies are competing with Amazon is obviously with data, utilizing data in new ways, personalizing the experience as you mentioned, Europe, Europe, you know, last year dropped a bomb called GDPR, and the whole privacy piece and it goes and, the penalties go into effect May of '18. How are you rethinking, privacy and data protection, in this new era? >> You know, the irony on this question is, two years ago, if you would have asked the same question, the onus would be on us to provide accessibility and provide proof that it's better to go with a cloud provider? The dialog has shifted to the point where, you know, we talked about it earlier today, we've got hundreds of people that are working in cloud ops, as opposed to our retailers that might have a handful that use it, so it's almost like the onus and the risk is on our retailers of not trusting a cloud provider, for that service. >> It's true, I mean, Amazon absorbs a lot of that risk for GDPR. So, then, how do the retailers think about data protection? I mean, they don't just wash their hands and say, "Okay, Amazon will take care of it." Are the discuss, are they more sort of, data protection brokers or strategists or? >> Well, I think it comes back to, there was some interesting behavior back in the mid-90s between a couple retailers and Amazon and, that's where a lot of the trepidation came from, of working with them, I keep harping back to, there is a pretty distinct line between AWS and Amazon, and what we find is, they don't even talk to each other. So if they're listening right now, they, that's probably, that's not a knock on them, that's actually congratulations that they are completely separate units, that we don't feel like there's any issues related to privacy or, the biggest concern isn't privacy, it's around having access to information around that SKU and that item and that price point. They don't want Amazon to be able to see that price point and suddenly offer up a promo based upon inside information. >> Okay, you know, sure, I buy that. I, you know, I think Amazon is pretty reputable in terms of that, that brick wall between the two companies, but specifically, I'm talking about personal information, and how that's protected, or just generally, security, well, I guess security again, the onus is on the cloud provider, but, are you, is that a board level discussion? Is that more of a wonk level discussion in IT or just? >> Over the last two years it's evolved to the point where it's not even a discussion point anymore. >> Because of the cloud. >> Because of the cloud, the cloud adoption as well as the standards that AWS has put in place, it's almost like they've created the industry standard for, to which others now compete with. >> Great. >> So. >> When you're thinking about the future of retail, is there a piece of advice that you could give to retailers? They're listening now, they're watching The Cube. Retailers who are fearful of a digital transformation, resistant to one, or know that they have to transform in this way but just can't quite seem to get over the hump. >> Well, every day I meet with a retailer, and it's the same sentiment. They understand and appreciate that if they don't adopt, they're dead. And it's really, it's really a grave situation, and the reality is, I think we're going to usher in a golden age of retailing, because, what's left behind is the old adage of, let's just expand and create more store space and more shelf space, and we'll just see our margins go higher and our revenues go higher. Those days are done, so they need to make the most they can out of the space that they have, and the reality is, any single store, it's almost like a node on the network, and I wanted to tell this story. So last night, I was boarding a plane and I realized my shoes were not packed. It's because I didn't have them, I left them in London last week, and the reality is, I'm not the best shopper when it comes to making these decisions. So I called my personal shopper at Nordstrom. She had all the information on me. She played it against her BI report on, these are the types of trends, style, color, class, and she came back and said, "Corey, "I'm going to purchase these for you." And I said, "Great, I'll pick them up "at your Nordstrom location in Manhattan." And she said, "Oops, it doesn't open until the spring." And I thought I was completely out of luck, and the reality is, she said "don't worry about it, "there's a distribution center not that far behind, "we'll ship it directly to your hotel." And guess what, lo and behold, this morning, my shoes were there. That's the type of modern retailing that all the non-Amazon, non-Walmart.com retailers can do to be successful. >> But it's not headless. I mean, there was a human being involved, yeah. >> There was a human being there, but we're working on next generation apps, specifically with Nordstrom too, to help them create that experience so we can eliminate the heroics and make that embedded into a new modern platform. >> I love it, I love it, I'm excited. >> Okay, but wait, wait, wait. Why couldn't Amazon replicate that with its AI and, you know, geniuses and alpha geeks? >> It's the human interaction. I don't want to just necessarily interact with a bot, on Amazon.com. I called my personal shopper live, and said, "This is what the situation is, can you solve it for me?" So then she took that back, she ran it through the calculations and came back and said, "Here's what you need and I'll ship it to you." >> Well, the other thing that I think about is the physical store. Some, like every time I buy sneakers on Amazon, they never fit, so, okay, so I want to go into DSW. I love DSW. >> (laughs) >> We do, too. >> It's, like, my favorite shoe store in the world, and of course my girls love it too, so. But so, there are many situations where you really actually want that physical, look and feel and touch. >> And think about what you just said, so with DSW, most of their customers are avid shoe shoppers and they love shoes. The differentiation between DSW and Amazon is that, I believe the numbers are pretty much 70% of North America's population is within 5 to 10 miles of a DSW. Think of that as competitive advantage, being able to buy online, pick it up in the store after work, there's no delay in shipping, that's really why Amazon's trying to get into the retail space with-- >> And by the same, unless Whole Foods starts-- >> There could be a drone! >> selling shoes ... (laughs) >> Or there could be a drone, that would deliver it to me in a couple hours. Anyway, but this is next year's Inforum. This is, these are all the themes. >> That's going to be amazing, to sit down with you and talk about this year after year. >> I know, we, at the golden age, it's soon to be upon us. Corey Tollefson, always a pleasure to sit down with you. Thanks so much for joining us. >> Thank you so much, appreciate it. >> Thanks for coming on. >> I'm Rebecca Knight for Dave Vellante, we will have our wrap just after this. (peppy techno music)

>> Narrator: Live from the Javits Center in New York City, it's The Cube. Covering Inforum 2017. Brought to you by Infor. >> Welcome back to The Cube's coverage of Inforum 2017. I'm your host, Rebecca Knight, along with my cohost, Dave Vellante. We're joined by Dhiraj Shah. He is the C.E.O of Avaap. Thanks so much for joining us. You're a Cube veteran. >> My pleasure. >> So welcome back >> Yeah. >> I should say. >> Absolutely. >> Not a rookie anymore. >> Right, right, right. So Avaap is a major strategic partner with Infor. So just walk us, Tell our viewers a little bit more about the relationship and where we are. >> Absolutely. Avaap's been a partner with Infor now for the last six years and prior to that, with Lawson. We've certainly come a long way. We started it 11 years ago as a single individual. Last year when we were here, we were here as a platinum sponsor and the big announcement this year is we're a diamond sponsor. So it doesn't get larger and add great stage presence and one of the big announcements we had this year, was Go Live with Infor's new CloudSuite Financial. The first customer to go live on that Palos Help, was actually an Avaap customer, that we brought live in nine months. >> And they were mentioned in the keynotes. >> Yes, Roger was on main stage. Gave a great presentation and what we centered our belief in, is you have the enterprise software provider, which is Infor, in this case, you have the system integrator, which is Avaap and then you have the customer. For any successful outcome, you need all three of these to really partner and do well. And that's what was exhibited with Palos. >> I'm always interested in companies that place bets on an ecosystem and the leader of that ecosystem is somewhat obscure. Certainly was six years ago. I mean, I saw this in the service now community. You're a hot company. You're growing like crazy and I saw early on, companies like yours in their community say we're going to make a bet and they've done very well. They've succeeded wildly, then get acquired by Accenture and CSC, so maybe great things ahead in your future. But take us back to the decision to bet on Infor. What led to that decision. >> Absolutely, looking back is always great right? Then you know the bets have paid off. But when you make 'em, it's not the same. Our business was, prior to 2012 when we made this decision, was centered around Lawson. We had some staff augmentation business and we had micro strategy BI business. And in 2011, Infor acquired Lawson. And when Infor acquired Lawson, there was a huge amount of apprehension in the customer base. Cause everybody was thinking here comes the external team that's going to come and annihilate the customer base. >> Dave: Yeah in the private equity cash suckout. >> Yeah, so that's what they're going to do. I had the opportunity to listen to Charles and his executive team, in one of their first meetings. And Charles was very clear in his vision. He said two things I want to focus on. One, build software that's easier to use, that's beautiful and that's not upgraded every year. And the second thing was, industry focus. Now six years go, you look at the enterprise software platforms, SAP, Oracle, nobody had industry focus. It was the same piece of software, one size fits all. And Charles came in and said, industry specific software. So we bought into that vision and we said this is going to be a huge opportunity in the ecosystem and fast forward six years. We were about 20 people at that time as a entire company. We have 25 people here at Inforum. more people just attending and 450 consultants globally now. >> You know Charles Phillips is a real, is a true software visionary because if you go back a decade plus a go. If you were an industry specialist, you were a VAR. Yes, Yes >> and you weren't going to to have a multi-billion dollar valuation. That was not a way to make the big dollars, right and so it is still, was, sort of a somewhat risky bet. >> It definitely was. Cause it seems we were much smaller back then but still to shut down those businesses over night and I still have the letter that we wrote to our customers and our employees and said we believe in this and that belief has really catapulted both our organizations It's really helped Infor and it's helped Avaap to kind of, and that's one of the lessons I learned as an entrepreneur. That wonderful things happen when you focus and build really strong partnerships. >> So that letter will some day be in a museum, I'm sure but. >> Dhiraj: I think we, from your mouth to God's ears. >> But let's talk about that. That easy to use, beautiful software that is transforming specific industries. >> Dhiraj: Yeah. >> Let's talk about retail. >> Yes. Absolutely. So retail was a huge announcement last year, when they announced they're going to go after Infor as a company and build a new wordicle. We invested alongside them as their single largest partner to go and give support. What they were doing around Retail is multiple things. Because prior to this, what Infor had was a ERP platform. Financials, human capital management. What they wanted to invest is we write the merchandising system, which is at the heart of a retailer. Not been done for the last 20 years. And they're rewriting and made an announcement with the best retailer, Whole Foods and that project kind of kicked off. The second piece they did was they filled in a gap with merchandise financial planning, assortment planning by buying a company called Predictings. So Avaap, kind of went ahead of it and we started a project alongside them over the past year and now we're independently going to markets. So Payless, we just signed a contract to implement merchandise financial planning for them. And then the final leg to this will be the point of sales, which would be StarMount, which is another system that they acquired and now the whole story around retail is coming in. Cause as we hear, retail's really getting hurt. And there's a huge technology change happening in the market place. >> Now, does GT Nexus fit into that as well, in terms of compressing the, you know if you build to order, kind of. Somebody's was giving an example of a couch today. You order a couch from some retail store and it takes 12 weeks to deliver. We've all sort of been there. Does it fit into that equation? >> You know it does. Because there's a whole shipping, receiving and the point of contacts through that guy that comes into the play there and GT Nexus, as you saw on the stage today, the amount of traffic that's being used through GT Nexus, it's going to help a lot of the retailers from all they're receiving and mobile supply chain functionality. >> Let me say real consumer frustration. You order something and you wait and you wait and you wait and you're excited and all of a sudden, weeks later you get the notification, sorry. >> Rebecca: Yeah. >> It's going to either be delayed or sorry we can't deliver that. So that's lost revenue. I mean, how many times does that happen? >> Yes and when you go to website, it's a different order. When you go to a mobile page, it's a different order. >> Dave: Oh yeah. >> When yo go into the store, it's a different order. So bringing all of that together for the single back office user experience is really what is going to transform the user experience to your point. >> So, speaking at another industry or user experience and this is, more important than buying a couch, let's say your health. Then this is another way in which Infor and Avaap are really transforming of the way we shop for medical care. So give us an example of what you're doing. >> Absolutely. We're very passionate about health care. So health care is our largest wordicle by size. So about 75 percent of our business is in health care and Infor has a large presence, Two thirds of the hospitals in the nation use Infor for their ERP software. Give a simple example, we were talking retail earlier. When you go into a retail store and you want to buy a piece of clothing, you know what it's going to cost you to purchase that and the store knows what their cost is for that, cause everything's coming from a single system. In hospital's case, there are two key systems. We have EHR, which the electronic medical system and you have your ERP, which is your back office system. Your revenue, comes from your EHR system, which is typically an Epic or Asserner. And your cost information comes from your lossing system, which is 75 percent of the time, Infor. They don't talk to each other. Now the acquisition of Burst gives a tremendous opportunity for us to connect the two systems together, bring that data forward, so the hospital operators know, at the time of admission and check out, what was the revenue and what was the cost, so they can do margin analysis. >> So you can see how that benefits the hospital but it also benefits the customer. >> In the end of the day, >> The patient. >> Absolutely. Because patient outcome is what's at the heart of all the changes that we're driving toward and when there's a lot, We're talking hundreds of millions of dollars that hospitals are burning in inefficient systems right now. And if that's saved, where's that going to go? Towards better care. And that's where dollars need to be focused. Not in holes that need to be plugged in technology. >> So Dhiraj, explain where Avaap specifically adds value. Where do you pick up from the technology that Infor provides? >> Absolutely. So prior to a year ago, our focus was just on the Infor side of the platform with ERP and a year ago, we acquired a company called Falcon Consulting. Best in class, top category leader for revenue cycle, to bring an Epic expertise. So now, we have both the EHR expertise and the ERP expertise. And in fact, this was our first foray outside of Infor and we got permissions form the Infor executive team, cause this we saw as a strategic way to service the entire health care ecosystem. And that's really helped us get knowledge from both sides to now build the integration platform to service. >> And so is it the full life cycle of plan, design, implement and manage? I mean, you start with strategy and? >> Yeah, so we're starting with the office of the CIO and CFO and organizational readiness and talking about strategy consulting. Vendor selection, ERP and after, once we get into the actual implementation cycle, that's where we do the implementation of the ERP or the EHR. Once implementation is done, the third piece of it will be optimization cause most systems that implement are not optimized. You know, they're on the same archaic system that were implemented many, many years ago. And then the final piece to that is continued support. As technology is evolving so fast. You heard Charles speak about so many new technology. It's hard for customers to keep up, so we do outsource application manage service to help support their. >> So talk just a little bit more about the whole microvertical strategy. We're interested in . I mean obviously, it's real. >> Dhiraj: Absolutely. >> But what is the impact to you as a partner and your customers. >> That was a new concept for us. Cause we saw it, okay Wordicle, great and then Charles came and said, 'No No Wordicle is not enough, it's microwordicle.' So one of our businesses is manufacturing. So you take the business of process manufacturing, the process manufacturing for your brewer versus your baker versus your food distributor, very different. So we then started taking Infor's product and started building applications in the presentation layer that are adapted for those industries. So CloudSuite Food and Beverage has a variation. So Old Neighborhood Foods is one of our top customers and they're one of the largest suppliers of all porks in the northeast. So how do everything that goes behind the making of the sausage and all the recipes, all of that is very different in a business, than Albert, say if Albert's since then got a bakery that we're implementing the same product. >> Dave: And you add that value? >> Yes. >> That's a custom code that you write or? >> No, these are using Infor's tools because Infor has presentation layer tools that we use to build microwordicle specification. Reporting analytics, all of those are driven for those industries. >> So you're composing the tooling. >> Dhiraj: Correct. Correct. >> Essentially is what you're doing. So is there any application development? Any low code or is it all no code? >> Zero code on the application side. Cause that's what, being in a cloud, that's one of the controls that come in. So the systems of the 70's were all customized in the application layer and then every time there was an upgrade, you would have to go through a huge exercise to retro fit them. All of that goes away. Beause with the cloud, you don't have control of the application wear. So all these tools that I'm talking about reside in the presentation layer. >> Okay, do you run into situations though, where you say, it would be nice if I had this custom modification and what happens in that situation. You go back to Infor and ask them for it or do you say to those guys, Hey can you extend your platform to give me a low code development capability or some kind of pass layer that. >> That's a very good question and that's a real world problem that our delivery team faces and we had to mature ourselves to. I would say a majority of the case. 80 to 90 percent of the case, we go back to the customer, to have a conversation with them to adjust their process. Most, eight out of ten times, it's the customer that doesn't want to change the process. >> Dave: Yes of course. >> And that's why they want the software to fit that. We've learned through the chain management mechanisms to have educated conversations with the customers cause it's a lot more painful to change the software than to do that. In the two out of ten cases, there are exceptions of building plug-ins or going to Infor. So one of the things with our partnership with Infor, we actually give, have a direct line with their product development team and if there's a change that customers are requesting that others would benefit from, it quickly gets into their queue and then it's part of the product set. >> Well that's interesting. That's a whole nother line of questioning now because you think about the old days of technology. Technology was so mysterious. But the process you knew, right? >> Yes. >> And today, it's changing. Technology is pretty much demystified. Everybody has AI, right. But it's the process that becomes somewhat unknown. Think about IOT and the Edge and these are all, these are sort of wild west processes. >> Most often overlooked cause for project failure is chain management and organizational readiness. And that's the part we lead in with to ensure organizations understand the investment they make in ERP is not just getting a vendor to come in and do this plug and play but to have their organization adapt to what the technology really is best suited for. >> That's great. Well Dhiraj, thank you so much for joining us on The Cube. >> Well thank you. >> It's been a fun >> it was real pleasure. >> a fun conversation. >> Yeah. >> Enlightening. >> Look forward to it. >> Enlightening even to Dave. >> Absolutely, I always learn. >> Yeah. Alright, thank you. >> Thank you for joining us. We'll have more from The Cube at Inforum 2017 in a bit. >> Dhiraj: Thank you. Alright.