(upbeat music) >> Hello and welcome to theCUBE as we present AWS Startup Showcase, The Next Big Thing in AI, Security & Life Sciences, the hottest startups. And today's session is really the next big thing in AI Security & Life Sciences. As to the AI track is really a big one most important. And we have a feature in company, fiddler.ai. I'm your host, John Furrier with theCUBE. And we're joined by the founders, Krishna Gade, founder and CEO, and Amit Paka, founder and Chief Product Officer. Great to have the founders on. Gentlemen, thank you for coming on this Cube segment for the AWS Startup Showcase. >> Thanks, John... >> Good to be here. >> So the topic of this session is staying compliant and accelerating AI adoption and model performance monitoring. Basically, bottom line is how to be innovative with AI and stay (John laughs) within the rules of the road, if you will. So, super important topic. Everyone knows the benefits of what AI can do. Everyone sees machine learning being embedded in every single application, but the business drivers of compliance and all kinds of new kinds of regulations are popping up. So we don't. The question is how do you stay compliant? Which is essentially how do you not foreclose the future opportunities? That's really the question on everyone's mind these days. So let's get into it. But before we start let's take a minute to explain what you guys do. Krishna, we'll start with you first. What does fiddler.ai do? >> Absolutely, yeah. Fiddler is a model performance management platform company. We help, you know, enterprises, mid-market companies to build responsible AI by helping them continuously monitoring their AI, analyzing it, explaining it, so that they know what's going on with their AI solutions at any given point of time. And they can be like, ensuring that, you know businesses are intact and they're compliant with all the regulations that they have in their industry. >> Everyone thinks AI is a secret sauce. It's magic beans and automatically will just change over the company. (John laughs) So it's kind of like this almost like it's a hope. But the reality is there is some value there but there's something that has to be done first. So let's get into what this model performance management is because it's a concept that needs to be understood well but also you got to implement it properly. There's some foundational things you've got to you know, walk, crawl before you walk and walk before you run kind of thing. So let's get into it. What is model performance management? >> Yeah, that's a great question. So the core software artifact most an AI system is called an AI model. So it essentially represents the patterns inside data accessing manner so that it can actually predict the future. Now, for example, let's say I'm trying to build an AI based credit underwriting system. What I would do is I would look at the historical you know, loans data. You know, good loans and bad loans. And then, I will build it a model that can capture those patterns so that when a new customer comes in I can actually predict, you know, how likely they are going to default on the loan much more activity. And this helps me as a bank or center company to produce more good loans for my company and ensure that my customer is not, you know, getting the right customer service. Now, the problem though is this AI model is a black box. Unlike regular software code you cannot really open up and read its code and read its patterns and how it is doing. And so that's where the risks around the AI models come along. And so you need a ways to innovate to actually explain it. You need to understand it and you need to monitor it. And this is where the model performance management system like Fiddler can help you look into that black box. Understand how it's doing it, monitor its predictions continuously so that you know what these models are doing at any given point of time. >> I mean, I'd love to get your thoughts on this because on the product side I could, first of all, totally awesome concept. No one debates that. But now you've got more and more companies integrating with each other more data's being shared. And so the, you know, everyone knows what an app sec review is, right? But now they're thinking about this concept of how do you do review of models, right? So understanding what's inside the black box is a huge thing. How do you do this? What does it mean? >> Yeah, so typically what you would do is it's just like software where you would validate software code going through QA and like analysis. In case of models you would try to prove the model in like different granularities to really understand how the model is behaving. This could be at a model prediction like level in case of the loans example, Krishna just gave. Why is my model saying high-risk to in particular loan? Or it might be in case of explaining groups of loans. For example, why is my model making high-risk predictions to loans made in California or loans made to all men? Was it loans made to all women? And it could also be at the global level. What are the key data factors important to my model? So the ability to prove the model deeper and really opening up the black box and then using that knowledge to explain how the model is working to non-technical folks in compliance. Or to folks who are regulators, who just want to ensure that they know how the model works to make sure that it's keeping up with kind of lending regulations to ensure that it's not biased and so on. So that's typically the way you would do it with the machine learning model. >> Krishna, talk about the potential embarrassments that could happen. You just mentioned some of the use cases you heard from a mid-saying you know, female, male. I mean, machines, aren't that smart. (John laughs) >> Yeah. >> If they don't have the data. >> Yeah. >> And data is fragmented you've got silos with all kinds of challenges just on the data problem, right? >> Yeah. >> So nevermind the machine learning problems. So, this is huge. I mean, the embarrassment opportunities. >> Yeah. >> And the risk management on whether it's a hack or something else. So you've got public embarrassment by doing something really went wrong. And then, you've got the real business impact that could be damaging. >> Absolutely. You know, AI has come forward a lot, right? I mean, you know, you have lots of data these days. You have a lot of computing power an amazing algorithms that you can actually build really sophisticated models. Some of these models were known to beat humans in image recognition and whatnot. However, the problem is there are risks in using AI, you know, without properly testing it, without properly monitoring it. For example, a couple of years ago, Apple and Goldman Sachs launched a credit card, right? And for their users where they were using algorithms presumably AI or machine learning algorithms to set credit limits. What happened was within the same household husband and wife got 10 times difference in the credit limits being set for them. And some of these people had similar FICO scores, similar salary ranges. And some of them went online and complained about it and that included the likes of Steve Wozniak as well. >> Yeah. >> So this was, these kind of stories are usually embarrassing when you could lose customer trust overnight, right? And, you know, you have to do a lot of PR damage. Eventually, there was a regulatory probate with Goldman Sachs. So there are these problems if you're not properly monitoring area systems, properly validating and testing them before you launch to the users. And that is why tools like Fiddler are coming forward so that you know, enterprises can do this. So that they can ensure responsible AI for both their organization as well as their customers. >> That's a great point, I want to get into this. What it kind of means and the kind of the industry side of it? And then, how that impacts customers? If you guys don't mind, machine learning opposite a term MLOps has been coined in the industry as you know. Basically, operations around machine learning, which kind of gets into the workflows and development life cycles. But ultimately, as you mentioned, this black box and this model being made. There's a heavy reliance on data. So Amit, what does this mean? Because now is it becomes operational with MLOps. There is now internal workflows and activities and roles and responsibilities. How is this changing organizations, you know separate the embarrassment, which is totally true. Now I've got an internal operational aspect and there's dev involved. What's the issue? >> Yeah, so typically, so if you look at the whole life cycle of machine learning ops, in some ways mirrors the traditional life cycle of kind of DevOps but in some ways it introduces new complexities. Specifically, because the models can be a black box. That's one thing to kind of watch out for. And secondly, because these models are probabilistic artifact, which means they are trained on data to grab relationships for what kind of potentially making high accuracy predictions. But the data that they see in life might actually differ and that might hurt their performance especially because machine learning is applied towards these high ROI use cases. So this process of MLOps needs to change to incorporate the fact that machine learning models can be black boxes and machine learning models can decay. And so the second part I think that's also relevant is because machine learning models can decay. You don't just create one model you create multiple versions of these models. And so you have to constantly stay on top of how your model is deviating from your reality and actual reality and kind of bring it back to that representation of reality. >> So this is interesting, I like this. So now there's a model for the model. So this is interesting. You guys have innovated on this model performance management idea. Can you explain the framework and how you guys solve that regulatory compliance piece? Because if you can be a model of the model, if you will. >> Then. >> Then you can then have some stability around maintaining the code basis or the integrity of the model. >> Okay. >> How does that? What do you guys offer? Take us through the framework and how it works and then how it ties to that regulatory piece? >> So the MPM system or the model performance management system really sits at the heart of the machine learning workflow. Keeping track of the data that is flowing through your ML life cycle, keeping track of the models that are going, you know, we're getting created and getting deployed and how they're performing. Keeping track of the whole parts of the models. So it gives you a centralized way of managing all of these information in one place, right? It gives you an oversight from a compliance standpoint from an operational standpoint of what's going on with your models in production. Imagine you're a bank you're probably creating hundreds of these models, but a variety of use cases, credit risk, fraud, anti-money laundering. How are you going to know which models are actually working very well? Which models are stale? Which models are expired? How do you know which models are underperforming? You know, are you getting alerts? So this is what this kind of governance, this performance management is what the system offers. It's a visual interface, lots of dashboards, the developers, operations folks, compliance folks can go and look into. And then they would get alerts when things go wrong with respect to their models. In terms of how it can be helpful to meet in compliance regulations. For example, let's say I'm starting to create a new credit risk model in a bank. Now I'm innovating on different AI algorithms here immediately before I even deploy that model I have to validate it. I have to explain it and create a report so that I can submit to my internal risk management team which can then review it, you know, understand all kinds of risks around it. And then potentially share it with the audit team and then keep a log of these reports so that when a regulator comes visits them, you know they can share these reports. These are the model reports. Is that how the model was created? Fiddler helps them create these reports, keep all of these reports in one place. And then once the model is deployed, you know, it basically can help them monitor these models continuously. So that they don't just have one ad hoc report when it was created upfront, they can a continuous monitoring continuous dashboard in terms of what it was doing in the last one whatever number of months it was running for. >> You know what? >> Historically, if you were to regulate it like all AI applications in the U.S. the legacy regulations are the ones that today are applied as to the equal credit opportunity or the Fed guidelines of like SR 11-7 that kind of comment that's applicable to all banks. So there is no purpose-built AI regulation but the EU released a proposed regulation just about three weeks back. That classifies risk within applications, and specifically for high-risk applications. They propose new oversight and the ads mandating explainability helping teams understand how the models are working and monitoring to ensure that when a model is trained for high accuracy, it maintains that. So now those two mandatory needs of high risk application, those are the ones that are solved by Fiddler. >> Yeah, this is, you mentioned explainable AI. Could you just quickly define that for the audience? Because this is a trend we're seeing a lot more of. Take a minute to explain what is explainable AI? >> Yeah, as I said in the beginning, you know AI model is a new software artifact that is being created. It is the core of an AI system. It's what represents all the patterns in the data and coach them and then uses that knowledge to predict the future. Now how it encodes all of these patterns is black magic, right? >> Yeah. >> You really don't know how the model is working. And so explainable AI is a set of technologies that can help you unlock that black box. You know, quote-unquote debug that model, looking to the model is introspected inspected, probate, whatever you want to call it, to understand how it works. For example, let's say I created an AI model, that again, predicts, you know, loan risk. Now let's say some person, a person comes to my bank and applies for a $10,000 loan, and the bank rejects the loan or the model rejects the loan. Now, why did it do it, right? That's a question that can explain the way I can answer. They can answer, hey, you know, the person's, you know salary range, you know, is contributing to 20% of the loan risk or this person's previous debt is contributing to 30% of the loan risk. So you can get a detailed set of dashboards in terms of attribution of taking the loan risk, the composite loan risk, and then attributing it to all the inputs that the model is observing. And so therefore, you now know how the moral is treating each of these inputs. And so now you have an idea of like where the person is getting effected by this loaner's mark. So now as a human, as an underwriter or a loan officer lending officer, I have knowledge about how the model is working. I can then have my human intuition or lap on it. I can approve the model sometimes I can disapprove the model sometimes. I can use this feedback and deliver it to the data science team, the AI team, so they can actually make the model better over time. So this unlocking black box has several benefits throughout their life cycle. >> That's awesome. Great definition. Great call. I want to grab get that on the record for the audience. Also, we'll make a clip out of that too. One of the things that I meant you brought up I love and want to get into is this MLOps impact. So as we were just talking earlier debugging module models and production, totally cool, relevant, unpacked a black box. But model decay, that's an interesting concept. Can you explain more? Because this to me, I think is potentially a big blind spot for the industry, because, you know, I talked to Swami at Amazon, who runs their AI group and, you know, they want to make AI easier and ML easier with SageMaker and other tools. But you can fall into a trap of thinking everything's done at one and done. It's iterative is you've got leverage here. You got to keep track of the performance of the models, not just debugging them. Are they actually working? Is there new data? This is a whole another practice. Could you explain this concept of model decay? >> Yeah, so let's look at the lending example Krishna was just talking about. If you expect your customers to be your citizens, right? So you will have examples in your training set which might have historical loans made to people that the needs of 40, and let's say 70. And so you will train your model and your model will be trained our highest accuracy in making loans to these type of applicants. But now let's say introduced a new loan product that you're targeting, let's say younger college going folks. So that model is not trained to work well in those kinds of scenarios. Or it could also happen that you could get a lot more older people coming in to apply for these loans. So the data that the model can see in life might not represent the data that you train the model with. And the model has recognized relationships in this data and it might not recognize relationships in this new data. So this is a constant, I would say, it's an ongoing challenge that you would face when you have a live model in ensuring that the reality meets your representation of the reality when you train the model. And so this is something that's unique to machine learning models and it has not been a problem historically in the world of DevOps. But it is a very key problem in the DevOps. >> This is really great topic. And most people who are watching might want to might know of some of these problems when they see the main mainstream press talk about fairness in black versus white skin and bias and algorithms. I mean, that's kind of like the press state that talk about those kinds of like big high level topics. But what it really means is that the data (John laughs) of practiced fairness and bias and skewing and all kinds of new things that come up that the machines just can't handle. This is a big deal. So this is happening to every part of data in an organization. So, great problem statement. I guess the next segue would be, why Fiddler, why now? What are you guys doing? How are you solving these problems? Take us through some use cases. How people engage with you guys? How you solve the problem and how you guys see this evolving? >> Great, so Fiddler is a purpose-built platform to solve for model explainability of modern monitoring and moderate bias detection. This is the only thing that we do, right? So we are super focused on building this tool to be useful across a variety of, you know, AI problems, from financial services to retail, to advertising to human resources, healthcare and so on and so forth. And so we have found a lot of commonalities around how data scientists are solving these problems across these industries. And we've created a system that can be plugged into their workflows. For example, I could be a bank, you know, creating anti-money laundering models on a modern AI platform like TensorFlow. Or I could be like a retail company that is building a recommendation models in, you know, PyTorch, like library. You can bring all of those models into one under one sort of umbrella, like using Fiddler. We can support a variety of heterogeneous types of models. And that is a very very hard technical problem to solve. To be able to ingest and digest all these different types of monotypes and then provide a single pane of glass in terms of how the model is performing. How explaining the model, tracking the model life cycle throughout its existence, right? And so that is the value prop that Fiddler offers, the MLOps team, so they can get this oversight. And so this plugs in nicely with their MLOps so they don't have to change anything and give the additional benefit... >> So, you're basically creating faster outcomes because the teams can work on real problems. >> Right. >> And not have to deal with the maintenance of model management. >> Right. >> Whether it's debugging or decay evaluations, right? >> Right, we take care of all of their model operations from a monitoring standpoint, analysis standpoint, debugability, alerting. So that they can just build the right kind of models for their customers. And we give them all the insights and intelligence to know the problems with behind those models behind their datasets. So that they can actually build more accurate models more responsible models for their customers. >> Okay, Amit, give us the secret sauce. What's going on in the product? How does it all work? What's the secret sauce? >> So there are three key kind of pillars to Fiddler product. One is of course, we leverage the latest research, and we actually productize that in like amazing ways where when you explain models you get the explanation within a second. So this activates new use cases like, let's say counterfactual analysis. You can not only get explanations for your loan, you can also see hypothetically. What if this the loan applicant was, you know, had a higher income? What would the model do? So, that's one part productizing latest research. The second part is infrastructure at scale. So we are not just building something that would work for SMBs. We are building something that works on enterprise scale. So billions and billions of predictions, right? Flowing through the system. We want to make sure that we can handle as larger scale as seamlessly as kind of possible. So we are trying to activate that and making sure we are the best enterprise grade product on the market. And thirdly, user experience. What you'll see when you use Fiddler. Finally, when we do demos to kind of customers what they really see is the product. They don't see that the scale right, right, right then and there. They don't see the deep reason. What they see, what they see are these like beautiful experiences that are very intuitive to them. Where we've merged explainability and monitoring and bias detection in like seamless way. So you get the most intuitive experiences that are not just designed for the technical user, but also for the non-technical user. Who are also stakeholders within AI. >> So the scale thing is a huge point, by the way. I think that's something that you see successful companies. That's a differentiator and frankly, it's the new sustainability. So new lock-in, if you will, not to be in a bad way but in a good way. You do a good job. You get scale, you get leverage. I want to just point out and get your guys' thoughts on your approach on the frame. Where you guys are centralized. >> Right. >> So as decentralization continues to be a wave you guys are taking much more of a centralized approach. Why is that done? Take us through the decision on that. >> Yeah. So, I mean, in terms of, you know decentralization in terms of running models on different you know, containers and, you know, scoring them on multiple number of nodes, that's absolutely makes sense, right? When from a deployment standpoint from a inference standpoint. But when it comes to actually you know, understanding how the models are working. Visualizing them, monitoring them, knowing what's going on with the models. You need a centralized dashboard that a lapsed user can actually use or a head of AI governance inside a bank and use what are all the models that my team is shipping? You know, which models carry risk, you know? How are these models performing last week? This, you need a centralized repository. Otherwise, it'll be very very hard to track these models, right? Because the models are going to grow really really fast. You know, there are so many open source libraries, open source model architecture has been produced. And so many data scientists coming out of grad schools and whatnot. And the number of models in enterprise is just going to grow many many fold in the coming years. Now, how are you going to track all of these things without having a centralized platform? And that's what we envisaged a few years ago that every team will need an oversight tool like Fiddler. Which can keep track of all of their models in one place. And that's what we are finding from our customers. >> As long as you don't get in the way of them creating value, which is the goal, right? >> Right. >> And be frictionless take away the friction. >> Yeah. >> And enable it. Love the concept. I think you guys are on something big there, great products. Great vision. The question I have for you to kind of wrap things up here. Is that this is all new, right? And new, it's all goodness, right? If you've got scale in the Cloud, all these new benefits. Again, more techies coming out of grad school and Computer Science and Engineering, and just data analysis in general is changing. And there's more people to be democratized to be contributing. >> Right. >> How do you operationalize it? How do companies get this going? Because you've got a new thing happening. It's a new wave. >> Okay. >> But it's still the same game, make business run better. >> Right. >> So you've got to deploy something new. What's the operational playbook for companies to get started? >> Absolutely. First step is to, if a company is trying to install AI, incorporate AI into their workflow. You know, most companies I would say, they're in still early stages, right? There a lot of enterprises are still, you know, developing these models. Some of them may have been in labs. ML operationalization is starting to happen and it probably started in a year or two ago, right? So now when it comes to, you know, putting AI into practice, so far, you know, you can have AI models in labs. They're not going to hurt anyone. They're not going to hurt your business. They're not going to hurt your users. But once you operationalize them then you have to do it in a proper manner, in a responsible manner, in a trustworthy manner. And so we actually have a playbook in terms of how you would have to do this, right? How are you going to test these models? How are you going to analyze and validate them before they actually are deployed? How are you going to analyze, you know, look into data bias and training set bias, or test set bias. And once they are deployed to production are you tracking, you know, model performance or time? Are you tracking drifting models? You know, the decay part that we talked about. Do you have alerts in place when model performance goes all over the place? Now, all of a sudden, suddenly you get a lot of false positives in your fraud models. Are you able to track them? We have the personnel in place. You have the data scientists, the ML engineers, the MLOps engineers, the governance teams in place if it's in a regulated industry to use these tools. And then, the tools like Fiddler, will add value, will make them, you know, do their job, institutionalize this process of responsible AI. So that they're not only reaping the benefits of this great technology. There's no doubt about the AI, right? It's actually, it's going to be game changing but then they can also do it in a responsible and trustworthy manner. >> Yeah, it's really get some wins, get some momentum, see it. This is the Cloud way. It gets them some value immediately and grow from there. I was talking to a friend the other day, Amit, about IT the lecture. I don't worry about IT and all the Cloud. I go, there's no longer IT, IT is dead. It's an AI department now. (Amit laughs) So and this is kind of what you guys are getting at. This now it's data now it's AI. It's kind of like what IT used to be enabling organizations to be successful. You guys are looking at it from the perspective of the same way it's enabled success. You put it out that you provision (John laughs) algorithms instead of servers they're algorithms now. This is the new model. >> Yeah, we believe that all companies in the future as it happened to this wave of data are going to be AI companies, right? So it's really just a matter of time. And the companies that are first movers in this are going to have a significant advantage like we're seeing that in like banking already. Where the banks that have made the leap into AI battles are reaping benefits of enabling a lot more models at the same risk profile using deep learning models. As long as you're able to like validate these to ensure that they're meeting kind of like the regulations. But it's going to give significant advantages to a lot of companies as they move faster with respect to others in the same industry. >> Yeah, quickers too, saw a friend too on the compliance side. You mentioned trust and transparency with the whole EU thing. Some are saying that, you know, to be a public company, you're going to have to have AI disclosure soon. You're going to have to have on the disclosure in your public statements around how you're explaining your AI. Again, fantasy today. But pretty plausible. >> Right, absolutely. I mean, the real reality today is, you know less than 10% of the CEOs care about ethical AI, right? And that has to change. And I think, you know, and I think that has to change for the better, because at the end of the day, if you are using AI, if you're not using in a responsible and trustworthy manner then there is like regulation. There is compliance risk, there's operational business risk. You know, customer trust. Losing customers trust can be huge. So I think, you know, we want to provide that you know, insurance, or like, you know like a preventative mechanism. So that, you know, if you have these tools in place then you're less likely to get into those situations. >> Awesome. Great, great conversation, Krishna, Amit. Thank you for sharing both the founders of Fiddler.ai. Great company. On the right side of history in my opinion, the next big thing in AI. AI departments, AI compliance, AI reporting. (John laughs) Explainable AI, ethical AI, all part of this next revolution. Gentlemen, thank you for joining us on theCUBE Amazon Startup Showcase. >> Thanks for having us, John. >> Okay, it's theCUBE coverage. Thank you for watching. (upbeat music)

>> live from San Francisco, celebrating 10 years of high tech coverage. It's the Cube covering Veum World 2019. Brought to you by VM Wear and its ecosystem partners. >> Hey, welcome back here and live here in Mosconi North. The Emerald 2019 Cube Live coverage on Shopping Day Volante Jr Jr. Who's here? EVP general manager, Telco and Edge of Cloud for Vienna. Where Thanks for coming on. Thanks for having me. I know you're super busy. We don't have a lot of time. Get right to it. Um five g a big part of the key. No discussion that's gonna enable a whole bunch of Pakal the pregame show pre gaming not even talk about that. Also. Telco on the Edge Computing Big part Michael Dell said, Edges the future Now these air to emerging areas for you guys. What's the positioning? What's the update? >> No, absolutely. I mean, if you look a tw telecom infrastructure. For the longest time, telcos have played a role just as pure basic connectivity providers. And with five g coming on board, they finally have an opportunity to break out of that and redefine the cloud off the future. So for us the big opportunity around five g is not just the better provisioning off like Higher Man With Service is to consumer for voice and data buy the whole set off new enterprise service is that can be provided on top of this five g network. And in order to be able to do that, you really need to go in with a virtualized telco Cloud architecture. Underneath that, and so we are working with carriers globally now preparing them for five G with an architecture that's going to help them deploy. New service is faster for both their consumer as well as enterprise. >> Going to be the white knight at, so to speak. For these telcos because they've been struggling for years over the top and any kind of differentiates service is even in the network layer. Exactly. I've had tons of rack and stack machine, so they're after their well, well stacked up in terms of computer storage. Also connectivity to the edge. That's the back hall. So you have back haul, which is connectivity. Companies that have massive expertise in scale but fumbling in operational cloud natives that >> by not just that, but I also think that having the idea off on application platform that allows them to go and deploy service is faster and then decide whether they're just going to play at the network connectivity level or at the application tear or a full SAS tear. These are all options that are open to them now with this notion off. Telco five G coupled with an NFI and cloud telco cloud infrastructure. Underneath that and never before have they had this option to doing that. And this is now open to them >> and the cloud native is there greenfield for AP supporter having applications on top of it. Exact icing on the cake, right? >> Exactly, Exactly. And so they're all looking at core architectures and then, potentially, their radio architectures now all being opened up toe deploying new service is that are much faster to provisions and then extending that to EJ and >> five G's deploying. So we know it's out there. So it is pre game is Pat, Guzman said. You know, not even an inning Yet in the metaphor of baseball innings, I >> gotta ask you get my phone. That's not that's fake ill. I know it >> did that with four g to >> skeptic e stands for evolution, which is coming soon. >> That's vaporware for tell Coke language. The surface area is going to radically get bigger with this capability. Yeah, security's gonna be baked in. This is the number one concern for io ti. And more importantly, industrial I ot We've been reporting on silicon angle dot com. This is a national security issue because we're under cyber attacks. Town's getting locked out with ransomware critical infrastructure exposed. We're free country, and I want to be free. We don't lock down. So you have security built into this new promiscuous landscape that is called the coyote Edge. Because you wanna have no perimeter. You want the benefits of cloud. But one whole malware is in there. One take over physical device could cost lives. >> Yeah, there's a big concern. Yeah. What's your thoughts? Yeah, No. So I think there >> are two ways of looking at it. One is the way you looked at it in terms of the security perimeter expanding and then us making sure that we have the right level off infrastructure security baked in to enable this to be an easier, manageable security architecture. This is sort of the pitch you heard from Mia Mary, even in the context of our acquisition of carbon black and how we're thinking about baking security into the infrastructure, the other way of looking at this is if you think about some of the concerns around providers off telecom infrastructure today and how there might be or might not be security back doors. This is happening in today's hardware infrastructure. Okay, so in fact, I would argue that a sick software defined architecture, er, actually ends up providing you greater levels of security. Because what you now have is the option off running all of these network functions as secured as software workloads in a policy envelope that you can introspect. And then you can decide what kind of security you want to deploy on what kind of workload. >> That's an innovative approach. But it doesn't change much, really, from an infrastructure standpoint, does it? Or does it? >> No, it does, >> because now, instead of having a hardware box where you have to worry, I mean, if it's a close, hard red box and you don't quite know what is happening there, the question is, is that more secure than a infrastructure radio running the software that you can actually introspect. I would argue that the software defined approach is more secure than having a hardware box that you don't know. >> I would buy the premise that certainly we know that supply chain concerned. You know the speculation Super Micro, which never was proved. >> It doesn't matter who the vendor is or what the country is. It really is a concern in terms of not being able to introspect what has happened Going inside >> for my tea shop. I'm running VM where operating I want developers. So now you're going to tell Coz you revitalize their business model? They had a rule out appy. Now what did you see? That connecting is gonna be connective tissue between >> I'll think about it. I didn't feel goto a telco. We look at really three stakeholders in there. One is I t the second Is there be to be or enterprise facing business and then the 3rd 1 is their core and access network or the CTO. We're now have a value proposition of having a uniform architecture across all three stakeholders with the uniform ability to create applications and drop it on top of each of these infrastructures with the ability to manage and secure these again in a uniform way, not just that, but also make this work well with other cloud infrastructures private, hyper scale, public as well as EJ. >> That's table stakes. You have to do that. These jokers have to operate whatever >> well it is, But it's not. I mean, if you think about what the infrastructure off a tailcoat today is, it's far from that, because it's it's sort of a closed environment. You can't access anything from a telco environment in order to go build an application to it, and it does not resemble anything like any club >> you could enable Telco. Just I'm just kind of thinking connecting the dots here real time in the Cube. If I'm a telco, hell, I'll take that VM wear on a deli and see model. Make me a cloud and I'll sell Cloud Service is to markets that kind of >> it is. Actually it's a very important part of our business model because most telcos would not move their own infrastructure from a network standpoint onto a public cloud. But they are eagerly awaiting the ability to operate their own network as a cloud, and if they can have somebody manage that for them, then that is very much within the >> you're enabling. An increase in the number of cloud service provides potentially the paint on the makeup of the telco tier one tier two tier three size. Pretty much >> potentially. I mean, it's taking an existing operator and having them operate in a more agile way and potentially increasing anew form off a cloud service >> provided telcos wouldn't move into the public cloud because of they want to control. And the cost is that right or it's >> mostly control. It's not about cost. It's about taking What is your sort of coordinating for, ah, packet corps or for a radio network? Yeah, and there is also an angle around competition, I think telcos our what in about the Amazons of the world and the azure eyes of the world potentially becoming a service provided >> themselves. And that's what I wanted to ask you about the business impact of all this discussion you guys were having is, you know, the cost for bits coming down. The amount of data is increasing faster. You got over the top providers just, you know, picking off the telcos. Telcos can't compete their infrastructures of so hardened. Will this all change that? >> Absolutely So. I think that it has the potential to changing all that. I don't think all the telcos will take advantage of it. Some off them might end up being more traditional and sort of sticking to where they were. But for those that are willing to make the leap, I mean, as an example, Vodafone is a customer that has actually gone in with this architecture with us. A. T and T is working with us with the Vela Cloud software from via Mary bringing a new form off branch computer branch connectivity through SD man. So these are all examples of telcos that are actually leading the >> charter. But if they don't lean in, they have this vision there either. Well, it's either because they're protected by their local government or they're going to go out of business. No, I would >> agree. I mean, it's sort of silly from our standpoint to be talking about five G and not thinking about this as the architecture for five, right? I mean, if you only focus on radio waves and your wireless network that's like a part of the problem, but you really need to have the ability to deploy these agile service's. Otherwise, you could get killed by >> the O. T. T. So how do you compete against the competition? What's the business plan that you have? C. Five G? We see that in the horizon that's evolving its evolution, so to speak. Pun intended on edge is certainly very relevant for enterprises, whether it's manufacturing or industrial or just people. Yeah, >> I'd say there are two things. One is a CZ. I'm sure you heard from folks at GM, where our vision is this notion of any any anywhere. We've talked about any cloud at any application that any device. So that becomes one of the strongest different chaining factors in terms of what V Amir can bring. Tow any of our customers compared to the competition, right? Nobody can actually make it really across these dimensions. If you then take that architecture and use that to deploy a telco cloud, we're now making investments that are telco specific that allow the tailcoat than take this and make the most out of it. As an example, we're investing in open stack we're investing in container ization. We just bought a company called Johanna and Johanna essentially allows the operator to go and provide metrics from their radio access networks. Use at that to train a learning engine and then feed that back so that the operator can tune their network to get like fewer dropped calls in the region. So if you combined technology like that with this, any cloud infrastructure that we have underneath that that's the best in class deployment methodology for any. Tell Cho to deploy >> five. Your business model metrics for you internally is get Maur deployments. What stage of development five G certainly is in a certain stage, but you know, edges there. Where is the Progress bar? If you're the kind of oh, >> it's actually mold phenomenally. I mean, every time we have conversations like this, we're moving about further in terms off. How many carriers are deploying on via mare on a telco cloud Architecture? How many subscribers are basically being serviced by an architectural like this? And then how many network functions are being deployed? Two of'em air architecture. So we are over 100 carriers now we are over. We have about 800 million subscribers, or so that about globally are being serviced by a V M Air supported network. On then, we have essentially over 120 network functions that >> are operating on top of you. Usually bring in all the same stuff that's announced that the show that stuff's gonna fold into the operating platform or Joe Chuckles have different requirements. Off course. It's >> both. We take the best of what is there from the sort of overall vehement factory and then as a team. My team then builds other widgets on top that are telco specific. >> How big is your your tam up Terry for you? >> Well, so the best way to look at it as telcos globally spend about a trillion dollars in capital investment and then probably to X that in terms of their operating expenditure over the course off all of the things that they do right? And out of that, I would say probably a tent off that. So if you take about $100 billion opportunity, opens itself up toe infrastructure investment in terms off the kinds of things that we're talking about now, they're not gonna move from like 0 200 of course. So if you take some period of time, I would say good subset off that $100 billion opportunity is gonna open itself up >> to it. This kind of business cases, eliminating that two x factor, at least reducing it. Is that exactly? That's not just that Service is that's, >> ah, cost reduction alternative. But then you have the ability to go deploy. Service is faster, so it's really a combination off both sort of carrot and the stick, right? I mean, the character here is the ability to go monetize More new service is with five G faster. The stick is that if you don't do it, Ortiz will get there faster and your costs off. Deploying your simple service is will increase his >> telcos, in your opinion, have what they have to do to get the DNA chops to actually be able to compete with the over to top OT T providers and be more agile. I mean, it's obviously sort of new skills that they have to bring in a new talent. Yeah, >> well, first and foremost, they need toe get to a point where their infrastructure is agile and they get into a business model off knowing how to monetize that agile infrastructure. So, for example, they could offer network as a service on a consume as you go basis. They could offer a platform as a service on top off that network in order for or titties to go build applications so they can do Rev shares with the forties. Or they could have offer. Full service is where they could go in and say, We are the conferencing provider for videoconferencing for enterprises. I mean, these are all models that >> the great conversation love to do. Your Palo Alto? Yes. Have you in our studio want to do more of a deep dive? We love the serious, super provocative, and it's important Final question for you. Though Pat Sr here on the Cube, lay asked him, Look back in the past 10 years. Yeah, look back in the next 10 years. What waves should everyone be riding? He said three things that working security and kubernetes humans being number one actually promoting convinced everyone for the ride, for obvious reasons, clouded. I get that, but networking Yeah, that's your world. That's changing. Which which events do you go to where you meet your audience out there in the telco because networking is a telco fundamental thing. Sure moving packets around. This is a big thing, >> eh? So far, operator networking related stuff, I would say. I mean the biggest shows that for us would be Mobile World Congress as an example, right? It's where many operators are. But I would also say that when we do our own events like this is the ember. But the movie forums in in Asia packers an example. A lot of the telco conversations I find they are best done one on one before. Yeah, the forums are our forums, but we will goto have one on one conversations or small group conversations >> with our telco customers. Locals Shakaar Thanks for spending. You get a hard stop. Very busy. >> Thank you. Thanks for having me >> here, Sugar Yaar, Who's here inside the Cube bringing down five G, which is still pregame. A few winning something first thing is gonna come up soon, but edges super hot. A lot of telco customers be back with more live coverage of the emerald after this short break

>> live from Las Vegas. It's the queue covering del Technologies. World twenty nineteen. Brought to you by Del Technologies and its ecosystem partners. >> Hello and welcome to Del >> Technologies with Cubes Coverage Our tenth year covering DMC World del World Here >> Pat Kelsey who test Not your time yet, but you're going to be coming on later. >> Great key note. Thanks for coming by. >> I appreciate it. Explored back tomorrow. You later. All right. >> Not Kelson. You're kicking off the cube coverage. Three days. The wall, the wall colors. Got two sets. Shotgun of content. We got to cube cannons blowing out the content. I'm John Force to minimum David. Want a key note? Uh, really kind of the tectonic plates in the industry. Kind of coming together you had on stage is something. The Tele CEO of Microsoft, Michael Dell, CEO of Down, founder of Del Technology and Pat Gayle Sr. Legends in the industry Captains of the industry. Really a critical juncture for Del technology worlds and a slew of other announcements. But the Del Cloud unified workspace but showing Microsoft on stage. This is a game changing move for Del technology world sure del del Technologies. But also of'Em. Where. Bm where in bed with eight of us. We know that cover that relationship now, going multi cloud all the way with Azure and seeing the CEO on stage Pretty incredible days. >> I think you nailed it. It's a V m wear story, John, and the numbers tell it. VM wears market value's eighty three billion Del owns eighty percent of it. That's sixty >> six billion. What's left. Dell's market value is forty seven billion. That says, the Del Cores worth negative nineteen billion. If it weren't for VM, where Satya Nadella wouldn't be here and you're seeing Michael Dell really drive the integration? He said that several times on stage today. How much collaboration? I love the collaboration across the divisions. You saw Jeff Clarke with Pack yell Sigur talking about new desktop management, talking about VM wear Cloud on del. It's of'Em were story You're right on >> and pack. Kelsey is to really key message up their simplicity, simplifying I t. The Common operate. I felt like we were in a Cube interview four years ago because that's was the basis of hybrid cloud now kind of coming to fruition. Clear visibility, at least on the tech stack side on the operating side, this is an operator world in a developer world, and simplicity and ease of operations is going to be the critical differentiated for the winners. >> Yeah, so So, John. First of all, I think we're getting some clarity on this multi cloud world. Look, one of the things that Veum where did so? Well, not just that wave, A virtual ization, but V Centre was the centre of I t management. And the question is, can they extend that into multi cloud world? When Veum where made the partnership with a W s. It's like, Oh my gosh, what does that mean to Del We got the answer today. What? That means Adele Veum were cloud on Del AMC hardware for me personally. That relationship between VM Rendell I think it's closer from the top executive all the way on down to the field go to market than it ever was. I was one of the first people working with VM where a DMC I watched that relationship emcee always kept them is kind of the way own you, But you're gonna be independent work across the board across the board. You hear. You know V s right. V X, Ray Allen and XX and P. K s and all these wonderful products Dell and VM work developing together, going to market together. It has ripples, but Amazon likes it. Microsoft like that big deal to see Veum wear and Microsoft partnered together. There are some challenges with some other partners Visa vi, Cisco And you know, some of some of the others, like IBM and HB that, if historically partner a lot with the anywhere but a lot of exciting news and definitely on >> and cha gi ve m were knocked down Google last month. >> So, guys, this is the theme we're seeing. We see Zoom went public. That was a videoconferencing disrupting an existing industry people thought would never be disrupted. You heard something and tell a stay on stage. Say on stage here that the new generation of new APS need new infrastructure. So a re vamp, a reset revitalisation of infrastructure to power APS via cloud. It's kind. The same game computing resource is software APS but with a whole new distributor architecture. A boom is coming. We see the stock market is up huge. You see the tech earnings last week across the board. Solid results. This is now a game change. This is not a bad business to be in. You know what was once could be. A declining business sees more remote workers, people working from multiple locations, mobile unification with cloud computing, a complete renaissance across the board game. I mean, this is a big revenue opportunity. >> Well, Mike Michael Dell's Kino wasn't just about products. It was about innovation. He talked about solving world problems, a big picture stuff on. Then he let Pat and Jeff get down a little bit more into the product. Weeds and you'LL hear more of that. But Michael is laying out a huge vision. What a juxtaposition between that's what, four, five years ago, you had sort of Joe Tucci, the chairman, up on stage. Michael was there. You had. You had John Chambers there. Now Michael owns the whole kit and caboodle. He's calling the shots, and people want to do business with them. Veum, where again, As you pointed >> out to me and Lucia question, you've been following the emcee for a long time. When we interviewed Michael Dell years ago, when he was in private that he bought AMC one of things. He said a lot. People were pooh poohing the whole deal. Why they want to buy that boat anchor. He said, scale matters. So are we seeing a new generations do elected to weigh in on this too, of competitive strategy where scale matters because you look at what Del Technologies has done and is doing there essentially rolled up the global I t business and are competing at scale with synergies not even looked at before early on when we talked about it. But we started see from fruit off that scale Amazon prove scale cloud Uh, Microsoft moves of the clouds scale up now the earnings air up Thoughts >> Well, what strikes me, John, is that, you know, they always talk about end end cos talk about synergy. Synergy is a code word for cutting what you heard today. You had be ave up there, you know, talking about a video and talking about the end end capabilities that Del technology brings Del by acquiring the emcee. And of course, VM. Where is a much way more strategic partner for corporations way more than many of these startups? Khun B. so that is their linchpin. You could maybe criticize him on innovation and, oh, maybe they don't have the hottest product, but and end throw in financial services and other services. People want to do business with this company because they trust >> to scale clouds scale, delle scale, scale. >> So we heard Tom suite this morning. Talk about that, Del. Maybe I missed a couple of turns in the marketplace and they needed to go private to kind of rearrange things When they bought emcee. We knew that there are a couple of tail winds that they could arrive hyper converge infrastructure. Absolutely one. We've been watching that trend since day one that their outpacing the industry there. The leader. If you talk from a software standpoint, VM wears their. If you talk from a hardware standpoint, Dell's there who's number two in the space nutanix, which also is a complicated relationship. But Del sells that in Vienna, where still is the primary hyper visor on that environment, so they're still beating the market growth. But they're doing that by gaining market share on DH taking it. Michael always loves to talk about when he's taking market from the business So the question is the overall macro, you know, how long can they keep that double digit growth going? And Dave, I know you're looking to begin with Tom Sweet. A >> ninety billion dollar business grew fourteen percent last year. So this company, in order to grow it has to gain share because the market is not. You're not going that fast. You can't rely on repatriation. I'm sorry that people are going to just disappear from the cloud and come back. So you've got to gain share the other thing, I think, to their favours. Let's face it, they really did have their act together in storage. They were kind of missing the boat there and took their eye off the ball. PC stayed strong. They got their act together in storage, which helped with the product. Mitch mixed higher margins. So last year was a very, very strong year. Twenty twenties going to be a tougher compare, but it seems like they still have some knobs to turn >> just about competition. But, um, Nutanix, what do they do? VM where relationship with a W s. I'm sure. Andy Jackson looking distant, healing words like chaotic, complex, the bane of our existence. Kind of talking about cloud in general and you deal with multiple clouds were packed. Nelson, you say that, um kind of public cloud losing babe flavor here means to you got the public cloud dominating. Now, all this talk about on premise and you got nutanix out there. What? What happens in Nutanix here? >> Yes. Oh, look, Nutanix astute. Doing well on Dell is a very important O am. But way just on nutanix made a big partnership with Hewlett Packard Enterprise. Which, of course, I'm sure Michael doesn't like that happening. You know, Nutanix needs to keep growing their rice software company. It's interesting to talk about the other competitors I mentioned Cisco. Cisco is transforming themselves into a software company. Del Del Technology is the core business wants to be the leading infrastructure company they have VM wear. Bumi and Pivotal are their software branch with the core. Business is really around that scale that that that whole you know, infrastructure piece and it's a different chuck it the Mark >> Chuck Robbins that Cisco CEO Cisco's not yet made a big, bold move like a red at move. Well, could nutanix be that move game? >> Well, I don't know. I don't know. I think I play is an I o T. But But But to your point about your question about the cloud Cloud is not attenuating Amazons, with thirty billion dollar company growing forty one percent a year throwing off twenty five thirty percent operating margins. I mean, that's where the innovation is. That's where the scale is. Everybody wants to do multi cloud because they don't have a cloud. It's your only path if you don't have a cloud. So So I think Cloud's got a long walk >> look and they talk to you know, I tell you, you know, my community got all excited when Michael got up on stage and said, We're all in on Corin eh? Teas and what we're doing with multi cloud you're going to hear under the covers here. Everything is going from VM wear V M as that unit down to container ization, you know, talking about at that application modernization. That's where they're going to lean on VM wear modernizing some what they're doing. And you know, of course, pivotal in Bhumi are the ones that are the tip of the spear in that area. >> I don't think David, it's a suit point there. The Amazon growth will continue because if you look at what Del Technologies has rolled out today, certainly that Microsoft thing is well shot across the bow. Multi cloud, Nice checkbox. Great to see the committee of the CEO there. But everything benefits with sass in the clouds. SAS is a cloud game And if scale on the clouds gonna be there, I only see the public cloud getting stronger because the scales they're the economics cannot be ignored. Certainly the data equation will be interesting, but anon a premise infrastructure that's set up operating like a cloud. I think we'LL ultimately benefit because Amazons weak link, if there is one, is that they really don't have a sass business, right? So they have a series of customers that deuce ***. But that's going to be an opportunity for all those workloads to run on the clouds. And the question is >> going to be >> how how >> cloud like is what we here today. And I I'm a skeptic. I want to see it first, you know, Show me. >> Yeah. No, I mean, what do we hear? What are you know Veum works, you know, services on Azure. It's the STD sea stack. So we understand what that is. It is more than just virtualization. But we used to say Private Cloud just can't be virtual ization plus plus. So Veum wears, you know, expanding and changing that model. But, you know, is it cloud enough? I mean the David, you know? Oh, you want to finance it with an effects we could totally have That affects affects the two. It's great. But, you know, >> at the end of the day, innovation and economics winds and the cloud guys have the scale. I mean, look at the amount of money we heard from Google last month. They spent what, twelve billion dollars in Cap Ex through April. It would take Oracle six years to spend that much in Cap Exit would take IBM three and a half four years to spend that much in CAF X. They're cost structure is going to be so much lower. And ultimately, I believe that's going to win. >> Talk about the winners and losers because we heard at the Bank of America you mentioned also what you just said. They're the future has redefined not how you got here, how you move forward. What's the competitive positioning posture for a winning supplier in the modern era of Iranian Cloud? >> I think it's really smart that Adele is forcing these integrations and getting out ahead of this multi cloud thing, I guess said before. If you don't have a public cloud, you've gotto get into that multi cloud management business. VM wears their their their obvious linchpin. They're early in the game. This is Guest is going to play over the next five to seven years. But VM wear has knocked down eight of us. Google, now Azure. They've got a relationship with Alibaba. It's just a matter of time before you see that one happening. So they are in the pole position. The other one is IBM Red Hat. I mean, those are the two favorites in my >> and by the way, red hats here. And if you want to run, you know the latest greatest red hat solution on the Del Ready notes. You know, of course you can do that. So you know, we'd love to talk about competition, but at the end of the day, it's what's good for customers and can they pick and choose the option of their choice. How much do I get? A full stack. That's the same. And how much is their choice? And I didn't hear the word choice. Ah, lot because, you know, they were focusing on certain announcement day. But absolutely, Adele has done a good job in the space in the cloud space of laying out the top choices that customers want. >> The choice wasn't used because the choices del they'LL ship you VX rails. I'm not sure they'll be shipping other things in there. Maybe they will, too. Thanks for the analysis. Degraded. Al says, man, It's gonna be a great show. Three days of wall to wall comes to cube sets two cannons of content coming your way here A Dell Technology world. The Cube cannons stay with us for three days. I'm jumpers Do Minimum day Volonte Lisa Martin, Rebecca Knight All here in Las Vegas for Delta No stay with us We'LL be right back

>> Announcer: It's theCUBE covering Sapphire Now 2017 brought to you by SAP cloud platform and HANA enterprise cloud. (electronic music) >> Hello everyone, I'm John Furrier with theCUBE. We are here for special Sapphire Now coverage inside theCUBE studios covering all the action in Orlando, Florida SAP Sapphire Now happening in Orlando. CUBE has been covering Sapphire, this is the eighth season covering Sapphire watching the innovations from SAP happened over the past eight years. It's been incredible. And our coverage continues here with Scott Harrison senior director of Sr Director America's ISV Platform as a Service with SAP. Scott, welcome to this CUBEConversation during our special coverage of Sapphire Now in Orlando. >> Thank you, thank you very much for having me. >> So you're role is partners in ISV and so the cloud has become a great enabler for partners. You seeing them transform their business and look at real lucrative opportunities. Both in making money but also extending their customer base. So what are customers expecting to see and what are they hearing at Sapphire this year? >> Well I think what customers are seeing at Sapphire is that there is some tremendous new innovation from SAP. We are the cloud company powered by HANA and we're delivering great solutions to help customers digitize their business. The transformational journey of the digital enterprise is real. SAP is leading the way. And in regards to partners, partners are key to helping SAP and customers be successful. We're enabling them to build solutions, to enable those solutions and deliver them to customers so that the customers can not only get the benefits of SAP but the get the benefits of some of the partner's innovation in real time. >> Talk about the growing ecosystem because SAP certainly has been changing. And in talking to Bill McDermott over the years there really hasn't been a course correction for SAP. They've been on this trajectory for awhile. Certainly maybe some some zigs and zags and some acquisitions here and there, but for the most part the journey trajectory has been the same. But the opportunities are shifting. Talk about the landscape of the ISV ecosystem that you guys have and what tweaks are you making where are you putting the pedal to the metal where are you pulling back what are you doubling down on? >> Sure, we're really doubling down on our partners and partner innovation. We have 600 partners globally that are building on SAP cloud platform. That's a fantastic number and that's just the partners building on cloud platform. We have over a thousand applications that our partners have built that have launched into the SAP app center which you're hearing great things about at Sapphire. So we're doubling down on partners helping us innovate we're doubling down on an end-to-end program to not only help partners build solutions that solve customer problems but jointly going to market with them so that they can be successful. Creating new revenue routes to market for their organizations. >> Your SAP is no newbie when it comes to partners I mean, look at the SAP. They run software. The biggest companies in the world going back to the old days. I mean, old days, showing my age here. But in the late 80's, early 90's during that boom SAP set the table, became, now running the software on some of the biggest businesses in the world. And McDermott's always got a quote "The top fortune 100 all run on SAP." Or something like that. But the landscape has changed. So I always looked at the partner ecosystem or the partner story and the partner traction as the canary in the coal mine for company's success. So here at Sapphire what Because partners are always about "what's in it for me?" They won't say the directly but it's ultimately the proof point. If it's not good for the partners it's probably not good for business. What's the impact at Sapphire this year for partners? What's the big impact, announcement, trends that are really going to get the partners super excited? When they say hey, this is going to help my business. >> Yeah, I think there's a couple things that partners are really excited about to help their business. Number one is some of the announcements coming out around cloud platform and the multi-cloud capabilities that SAP will have. Additionally it will be in terms of revenue routes and go-to-market as you know we have launched the SAP app center which is not only just an app center to discover new applications, but to actually transact and drive revenue through the SAP app center. So we have partners that are showcasing their solutions on the SAP app center. And customers have the ability to discover, try and buy those applications. That's a real impact for partners in terms of driving new revenue and routes to market and minimizing the cost of sales the best that they possibly can. >> Talk about the Go-to-Market and the subscription models because one of the things I find fascinating about the cloud is it's an evolution and a continuation of some of the things, we talked about the old days. But really the business models are changing. Talk about the specific things that you're doing with partners. Because the digital transformation is no doubt a huge opportunity but it's a business model change and technology changing in real time. What's the big go-to-market tweak that you feel the partners are excited for? >> I think what partners are really excited for is the idea of creating a subscription based revenue model for their organization. Whether they're a traditional SI or whether they're a reseller there are more pressures on the margins than ever before. And what we're providing for partners is the ability to create a new revenue model where they can offer subscription based services powered by cloud platform. So it's their innovation and IP running on cloud platform and it gives them that subscription based revenue model so that they can change the dynamics of their company. And be able to increase valuations of their company have additional revenue flowing through. >> Scott, one of the themes this year at Sapphire and certainly last year really put the stake in the ground was the Apple deal. The iOS, you're starting to see cloud native developers really extending the range, if you will of the traditional SAP reach. Which, you know, huge developer community. You know, SAP in particular. And you're seeing others, like Cisco moving outside their quote, swim lanes, around developers going after these cloud native developers. We're hearing the same thing from partners inside theCUBE and we talked to the, whether it's the large SIs, the ISVs. SIs are a little bit different because they have the big money. But a lot of the ISVs are really doubling down on their development staff. Which, those roles are changing. You don't have to be a hardcore full-staff developer >> Right. >> to be a developer any more. How are you seeing the impact of some of the things happening at Sapphire that are going to really go to the ISVs saying it's okay to staff up and be developer focused. And that's really where the action is. What's the story there? >> Yeah, it's a great story that we've done in conjunction with Apple and the iOS SDK, right? And that being announced within cloud platform. So we have great partners that have been a part of that >> John: So you have a good story for developers? For ISV? >> We have a fantastic story for ISV and developers. One of the examples, and there are many is one of Innovapptive. They are a start-up company of four years ago. They develop mobile solutions on cloud platform and they have been part of this launch to be able to use the iOS SDK to develop mobile applications within the HANA cloud platform and leveraging that SDK. >> Alright Scott, final question for you. Bottom line, the ISV partner that's out there on the show floor at Sapphire Orlando, and the folks potentially watching online here. Bottom line me, what's in it for me? I'm an ISV, I'm a partner, what is SAP doing? What's different now? Why is it good for me to continue and extend or double down my relationship with SAP? >> Yeah, we really have made it very easy to partner with SAP. You can come in and build solutions on our technologies very easily. And we can help you take it to market. You get instant access to all of the SAP customers worldwide. so whether you're a developer with an idea or you're a very large traditional SI you have the ability to build new innovation you have the ability to easily showcase that in the app center and other places within SAP and you have the ability to go-to-market jointly with us. So we want you to win. Because as a ISV developing a solution when you're successful, and only when you're successful is when SAP is successful with our partners. >> John: And what are you guys doing specifically to make that frictionless for the partner? >> We're enabling them with key technologies we're giving them the ability to build easily and then we're putting together go-to-market plans for the partners to be able to execute and sell successfully. >> Final, final question. What's the big take-away from Sapphire this year? What's the ah-ha? If you kind of look at the stage, look down on the stage and watch all the action happening >> Yeah >> in Orlando. What's the big walk-away there for you and the partners? >> I think the walk-away for the partners is that SAP is 100% behind you in terms of helping you and most importantly your customers with their digital transformation. We're making it easy for you to innovate. We're making it easy to showcase who you are. And we're putting some of our best cloud solutions into our partner ecosystem so that they can extend those and create new routes to market. >> Alright Scott Harrison here on the special SAP Sapphire Now 2017 coverage from the studios here at Palo Alto. I'm John Furrier. Thanks for watching. More continued coverage after this short break. (electronic music)

>> Host: Live from Las Vegas. It's The Cube! Covering Oracle Modern Customer Experience 2017. (electronic music) Brought to you by Oracle. >> Okay, welcome back everyone, we're here live at the Mandalay Bay for Oracle's Modern CX Show, Modern Customer Experience, this is the Cube, I'm John Furrier. My co-host, Peter Burris, two days of wall-to-wall coverage. Day two, my next guest is Katrina Gosek, Senior Director Commerce Product Strategy, (mumbles) Oracle upper world a few years ago, and Alistair Galbraith Sr, Director of CX, Customer Experience Innovation Lab with Oracle. Welcome to The Cube, great to see you. >> Thank you. >> Thanks, welcome. >> So commerce is part of the story, it's just not marketing, there's transactions involved, there's R & D, there's a lot of technology. The show here is the common theme of just modernizing the customer experience, which is good, because it's the outcomes. But commerce is one of them. Give us the update, what's hot for you guys this week? >> Yeah, I think what's different this year, from any other year in the past is the pace of innovation is changing, because I think there's so much disruption in the commerce space, and particularly in retail and also B to B commerce. There's lots of new expectations from customers. I know we've been saying that for years, right? But I think the technologies now, that can enable some new experiences, have rapidly changed. Now it's completely fathomable to leverage AI to drive more high-end personalization or to leverage internet of things, to embed commerce more into everyday experience. >> John: Where's the innovation in retail? 'Cause retail's not a stranger to data. They've had data models going back, but certainly digital changes things, they're at the edge of the networks, so it's a little bit of internet of things meets consumer data, the data's huge if you can get the identity of the person. That seems to be the key conversation: how do you guys enable that to take advantage of the sea of data that you're providing form the data cloud, third party and first party data? >> Well I think there's a lot of fun approaches. Oracle has a technology called the Oracle ID Graph, which starts to merge a lot of identities across channels, so where customers are using data cloud, that can inform those micro interactions as they move between channels, and I think one of the trends we've been seeing this year that we're talking about as My Channel, is that customers no longer really complete one interaction or one transaction in one place. They might start on mobile, move to voice, move into a physical store, and we're trying to track that customer in all of those places, so a lot of our focus, and you see data cloud moves into AI, is enabling brands to move this data around more easily without needing to know everything about the customer themselves. >> John: Well that's the key for the experience of the customer, because they don't want to have to answer the same questions again if they're on a chat bot, and they've already been at a transaction. Knowing what someone's doing at any given time is good contextual data. >> Alistair: Yep. >> Well it's funny you say that, because when we talk to customers or end consumers, they're not thinking, "I need more artificial intelligence, "I need more data around my experience, "I need internet of things", they're thinking, "I want convenience, I want this to be fast and quick, "I want you to know me as a brand, "I don't want to have to re-enter everything. "If I'm talking to a customer service agent, "versus someone in the store, versus interacting online". So data's a huge part of that, the challenge is how do you make it consistent? >> John: Katrina has a great point: it's not the technology, it's about what they're trying to do. >> Katrina: Yeah, exactly, very much. >> Well the experience comes back to, in many respects, convenience, and, "I want you to sustain "the state of where I am in my journey for me". >> Katrina: Correct, yeah. >> Or at least not blow my state up. So it's interesting, the journey used to be a role or a context thing, and now we're adding physical location to it, as well as device. So go back to this notion of new experiences. 'Cause it's got to be more than, you can look at something on your phone and then transact on your phone. What are some of the new experiences on the horizon? 'Cause that is a lot to do with where you guys think digital technology's going to go. >> I think some of those experiences are micro-interactions, so that could be people are using voice shopping, but not for the entire purchase, just a re-order this thing, what's the status of this thing? And brands are also using the data that they're gathering to tweak and adjust those interactions. So we're seeing data coming from real world devices and IOT changing the expectation of the customer, as they, maybe, we showed some stories where people are re-ordering products using voice, and then when they shift between these channels, that micro piece of data is really changing that interaction. The other challenge we're seeing is the consistency of the interaction, you said yourself, not only it's the complexity of "what did I do?", but if I do something here and I do something here, I should get the same experience both times. >> So we're talking mostly at this point about the B to C, the consumer world. In many respects, some of the most interesting experiences, we can envisage in the B to B world, where a community of sellers is selling to a community of buyers, and the state that's really important is how does that buying community interact with each other? As they discover things and share information. So how do you see this notion of new experiences starting to manifest itself in the B to B world? >> Katrina: Yeah, it's interesting you say that, because I often, we work with both B to C and B to B clients, and I actually think B to B has always been more focused on personalization, because they do have so much information about their customers, contract data, a lot of information about the buyer, the companies, they've always done kind of online custom personalized catalogs. So I think there's a lot that B to C can learn from B to B about how to leverage that data to personalize experiences. >> John: And vice-versa too, it's interesting, to that point, the B to C is a leading indicator on the experience side, but B to B's got the blocking and tackling down, if they have the data. 'Cause having the data, you get the goods. Okay, so here's the question for you: with the consumers going to digital, you're seeing massive, we were reporting yesterday, here on The Cube and also on siliconhill.com, as well as Adage, not that we didn't predict this, but ad spend now on digital has surpassed TV for the first time. Which is an indicator, but the ad tech world's changing, because how people are engaging with the customer is changing, so the question is, what technology is going to help transition those ad dollars, from banner ads to older formats to something more compelling and using data? 'Cause you can imagine retail being less about click, buy, to sharing data. So the spend's going to only grow on advertising or reaching consumers. That conversion, that experience is going to have to move from direct response clicking, to more experience, what tech is out there? >> Well, I think the biggest challenge has always been tracking and personalizing for a unique interaction. Just the sheer volume of data that's coming in, it's just too hard to consume. So I think the blend of AI and AI with the ability to tweak, adjust, look at multi-variate tests, and change the interaction as it goes, that's going to really massively affect the journeys for retailers, and I think the big benefit as brands move to the cloud, the cost of innovation, the cost of trying something and failing is so much less, and the pace of innovation is so much faster, I think we're seeing people try new things with the data they've got. Find out what works and what doesn't. >> Here's a question for you guys. We're talking to Jess Cahill, when this came up yesterday as well, Peter brought this up as part of the big data action going on with the AI and whatnot. Batch to real time is a shift, and this is clear here in the show that the batch is there, but still an older, but real time data in motion consumers in motion are out there, so the real time is now the key. Can you comment on that? >> I think it goes back to what Alistair was saying earlier about those micro-moments. I think transacting in new and unexpected places, ways, I think that's the key, and that's actually a huge challenge for our customers, because you have to be able to use that data in real time, because that customer is standing there with their phone, or in front of Alexa, or a speaker. >> John: It's an opportunity. >> It's a huge opportunity, and I think those opportunities are everywhere now. In a couple of years be the refrigerator, if you're re-ordering groceries, leveraging the screen, so I think that's going to be the challenge, but I think we've got time to help our customers figure out how to leverage that in real time. I think staying nimble and agile is going to be key and failing fast, and I guess a more positive way to say this-- >> The Agile Marketer, I think we had Roland Smart on yesterday, he literally wrote the book. But this is interesting, if you have the data, you can do these kinds of things. So the question is, certainly your point about the refrigerator and all these different things is going to create the omni-channel nightmare. It's not going to be, certainly multi-multi-omni. It's going to be too many challenges to deal with. >> Alistair: I think we prefer to see it as the omni-channel dream, than the nightmare. (group laughs) >> So many channels, there's no more channels, right? >> Well I think that's where things like Marketing Cloud, things like Integration Cloud help orchestrate that omni-channel journey, so that to your point on marketing and ad-spend, being able to analyze whether a benefit or promotion I showed during one micro-interaction affected something somewhere else, is so challenging but so important when you're moving this ad spend around. And I think where orchestrating and joining these micro-moments together, it's really where we're focusing a lot of our investment at the moment. >> One of the big things that's happening in the industry today is we're starting to develop techniques, and approaches, methods, for conceptualizing how a real thing is turned into a digital representation. IBM calls and not to mention them, or GE, perhaps more of a customer ... (group laughs) Yeah, I just did. >> That's all right. >> This notion of a digital twin. Commerce succeeds, where online electronic commerce succeeds as we are more successful at representing goods and services digitally. What's the relationship between IOT and some of these techniques for manifesting things digitally? And commerce, because commerce can expand its portfolio, things it can cover, as more of these things can be successfully digitally represented? >> I think that's key, and that's actually one of the predictions that we talked about in our keynote is how do you represent new ways of representing the physical store, the physical space with customers, so for me, I think something that probably Back to the Future or Judy Jetson, like a few years ago, augmented reality, or virtual reality, I think now we're going to see that more. We're starting to see it more with furniture sales, for example, you're on your iPad at home, and you can put the couch you've chosen in the space, right there with you, and see if it fits, but you're in your home, you don't have to go to the furniture store, and kind of guess with your tape measure whether the couch fits or not. And I think that's applicable in B to B as well, as 3D CAD drawings, you can kind of see them in VR, or AR. >> Amazon just announced Look, yesterday, which is the selfie tool that allows you to see what you're wearing. >> I think we're going to see a lot more of it in the coming years. >> Well, in many respects, it also, going back to this, we asked the question earlier about B to B, B to C, and the ability to represent that community. We're going to start seeing more of a household approach, as to just a consumer approach, and I think you just mentioned a great one. When we are successfully, or when we are willing to start capturing more data about our physical house or what's going on inside, so that we can make more informed decisions, with others, about how we want to do things, has an enormous impact on the quality of the experience, and where people are going to go to make their purchases. >> Alistair: Definitely, and I think that as we try and merge those experiences between B to B and B to C, what we know about someone as a consumer also directly affects their buying decisions, as a B to B employee buying for their brand. And that just increases the sheer volume of data that people are trying to manage and test and orchestrate. I think we're seeing a shift not only in people being prepared to surrender some degree of privacy for a increased experience, but we're also seeing people trusting in that virtual experience being a reality when they buy. So people have a much higher trust level in AR, if I visualize a couch and then buy it, I've got a degree of faith that when it turns up, it'll be like the one I looked at. And I think that increased trust is really making virtual experiences, digital commerce, so much easier. >> I think that's an interesting point, we had CMO of Time Warner on yesterday, Kristen O'Hara, and she was, we asked her, "Oh yeah, these transformations", big use case, she's on stage, but I asked her, "How was it like the old way? "What would you do before Oracle?", she goes, "Well, there was no old way", they never did. The point is, she said, the point was we became a direct to consumer company, so B to B and B to C are completely merging. So now the B to B's have to be a B to C, inherently because of the direct connect to the consumer. Not saying that their business model's changing, just that's the way the consumer is impacting. >> Peter: Or is it data connection to a consumer? >> A data connection, and where there's gesture data, or interaction data coming in, so this makes, the B to Bs now have to bolt on more stuff, like loyalty, you mentioned loyalty, things of that nature. >> Yeah, if you're a B to B company, you're selling to other businesses, but who are the people on the other business? There are people who shop every day in consumer applications, so their expectations are, "I'm going to have a great personalized experience, "I'm going to be able to leverage the same tools "that I see in my consumer shopping experiences "for my B to B experience, why would it be different?" So I think that's something that B to B is really learning from B to C as well. >> True, but although there seems to be something of a counter-veiling trend, but an increasing number of people are now working at home. So in many respects, where we're going to, is we're talking about experience, not just being online. One of my little heroes, when I was actually trying to do development, a million years ago, was Christopher Alexander. The Timeless Way of Building, which was one of the basic texts that people use for a lot of this customer experience stuff, and the observation that he made was, you talk about spaces, you talk about people moving into spaces to do things in context. And increasingly, the spaces that we have to worry about are not just what's on the screen, but the physical space that people move in, and operate in, an the idea is, I'm going somewhere to do something, and I'm bringing physical space with me. So all of these, the ability to represent space, time and interests and wants and needs, are going to have an enormous impact on experience. Wouldn't you agree? >> Massively, and I think the challenge using that same approach is that people are co-existing in multiple spaces concurrently. They no longer do one thing at the same time. >> Peter: They may be in the same physical place, but have two different contexts associated with it. Like working my home office, I'm both a father, as well as an employee. >> Alistair: Yes. >> And those two sometimes conflict. (Katrina laughs) >> Yeah, absolutely, and you're a consumer and an employee, and as a father, you're potentially affecting the decisions that the rest of your household is making, as well as the decisions that your business is making, all in slightly different ways. But those two experiences with the B to B and B to C, overlap one another. >> Peter: In fact, switching contexts from consumer to father is one of the primary reasons why I lose where I am in the journey. So these are very powerful, and the ability to have the data and then go to your customers, and say, "We will be able to provide that end to end for you, "so that you can provide a consistent "and coherent experience for your customers" is really crucial. Is that kind of where you're taking us? >> Yeah, I mean we've always commerce isn't kind of a standalone little thing, it really connects and glues together so many other types of experiences, so it connects to marketing, it connects to service, you need all of that, to be able to make the experience work. So we're really focused on making sure that it's easy to connect those applications together, that its easy to manage them behind the scenes, and that it appears seamless to the customer on the front end. >> One other thought that I have is, and in many respects, increasingly, because we're going to be able to represent more things digitally, which means we'll be able to move more stuff through commerce platforms. This is where the CX is going to meet the customer road, is in the commerce platforms. Do you guys agree with that? You're going to measure things all over the place, but I'm just curious-- >> John: It's their products, yeah. >> What do you think? Is it going to be increasingly the basis for honest CX? >> Well we're already seeing it become the basis, so I wouldn't say it's a future thing, I think it's been a reality for quite some time, where commerce is the hub that kind of connects, in retail, the store to marketing experiences. >> John: It's bonafide data is what it is too. >> Yeah. >> That's good data. >> Katrina: It holds so much product information, transaction information, customer information, and it just connects and leverages. I don't know if you would agree? >> Alistair: I would agree completely, and I think you look at the fact that most companies ultimately are selling a product, so that's commerce, and I think the transition is that rather than going into the commerce site or the commerce space, you see a lot of brands over the last 12 months have got rid of their store.brand.com thing and just merged their commerce experience into everything else, you're always selling. And we've customers deploy commerce without the cart, but as a product and communication marketing model, to get this tracking data moving around. >> We were talking about Jack earlier, yesterday, Berkowitz, who was talking data, we were talking about data, good data, dirty data, clean data, and data quality in general. >> Katrina: It's a tough problem. >> In context to value, and he said a quote, he said, "Good data makes things happen, "great data makes amazing things happen". And to your point, retail, commerce data, you can't, it's undisputed, it's a transaction. It's a capture in time, and that can be used in context to help other data sets become more robust. >> Well, in many respects it's the most important first person data that you have in your business. >> Katrina: Yeah, and I think from an Oracle perspective, what we're doing with the adaptive intelligent applications for commerce, and for the other applications as well, and particular for commerce is combing that first hand information you have about your products and your customers as an online business, but then the immense amount of data that the data cloud has behind the scenes that augments and allows you to automatically personalize, when a customer comes to your storefront, because they're coming already with all the context that they have elsewhere out in the world, and you can combine that with your own data, and I think really enhance the experience. >> John: Yeah it's funny, we were joking yesterday, Oracle went to bed a software company, woke up a data company. >> Katrina: Yeah (laughs). >> So the data cloud is pretty impressive, what's happened there and what that's doing. >> Katrina: It's amazing, it's a huge differentiator for us. >> Huge differentiator. Okay, final word, I'd like both you guys to just quickly comment to end this segment, awesome segment on commerce and data, which we love. But your reaction to the show, what's the bottom line, what's exciting you this week? Share with the folks, each of you, a quick soundbite of what's happening here and the impact people should know about. >> Sure from a commerce perspective, this is the first year where we've got a 50/50 split in our customer base, so we're seeing a lot of our un-premise customers move to cloud, which is great, and we're really growing our commerce cloud customer base. I'm very excited about that. >> And you're trying to get 100% now, it's never going to be a hundred. >> Katrina: (laughs) Yeah, we need to work with customers and what's right for them, but yeah, it's very exciting right now. >> Alistair, your take? >> I think for me, it's just the sheer pace of innovation, we're seeing brands go from un-premised stories that would take 12, 15, 18 months to add new features, make changes to small nimble brands rolling out incredible innovative features in 12, 18 week time frames, and we're seeing more people having more discussions around the art of the possible. >> John: All right, Katrina, Alistair, great comment, great insight, great conversation about data and commerce, of course cloud, it's the marketing clouds, all cloud world, it's commerce cloud, it's data cloud, it's just the cloud (laughs). I'm John Furrier, Peter Burris, move live coverage here from Las Vegas, Oracle Modern CX after this short break. (electronic music) >> Host: Robert--