(upbeat music) >> Hello, everyone, welcome to theCUBE. I'm John Furrier, the host of theCUBE in Palo Alto, California. Also it's SiliconANGLE News. Got two great guests here to talk about AI, the impact of the future of the internet, the applications, the people. Amr Awadallah, the founder and CEO, Ed Alban is the CEO of Vectara, a new startup that emerged out of the original Cloudera, I would say, 'cause Amr's known, famous for the Cloudera founding, which was really the beginning of the big data movement. And now as AI goes mainstream, there's so much to talk about, so much to go on. And plus the new company is one of the, now what I call the wave, this next big wave, I call it the fifth wave in the industry. You know, you had PCs, you had the internet, you had mobile. This generative AI thing is real. And you're starting to see startups come out in droves. Amr obviously was founder of Cloudera, Big Data, and now Vectara. And Ed Albanese, you guys have a new company. Welcome to the show. >> Thank you. It's great to be here. >> So great to see you. Now the story is theCUBE started in the Cloudera office. Thanks to you, and your friendly entrepreneurship views that you have. We got to know each other over the years. But Cloudera had Hadoop, which was the beginning of what I call the big data wave, which then became what we now call data lakes, data oceans, and data infrastructure that's developed from that. It's almost interesting to look back 12 plus years, and see that what AI is doing now, right now, is opening up the eyes to the mainstream, and the application's almost mind blowing. You know, Sati Natel called it the Mosaic Moment, didn't say Netscape, he built Netscape (laughing) but called it the Mosaic Moment. You're seeing companies in startups, kind of the alpha geeks running here, because this is the new frontier, and there's real meat on the bone, in terms of like things to do. Why? Why is this happening now? What's is the confluence of the forces happening, that are making this happen? >> Yeah, I mean if you go back to the Cloudera days, with big data, and so on, that was more about data processing. Like how can we process data, so we can extract numbers from it, and do reporting, and maybe take some actions, like this is a fraud transaction, or this is not. And in the meanwhile, many of the researchers working in the neural network, and deep neural network space, were trying to focus on data understanding, like how can I understand the data, and learn from it, so I can take actual actions, based on the data directly, just like a human does. And we were only good at doing that at the level of somebody who was five years old, or seven years old, all the way until about 2013. And starting in 2013, which is only 10 years ago, a number of key innovations started taking place, and each one added on. It was no major innovation that just took place. It was a couple of really incremental ones, but they added on top of each other, in a very exponentially additive way, that led to, by the end of 2019, we now have models, deep neural network models, that can read and understand human text just like we do. Right? And they can reason about it, and argue with you, and explain it to you. And I think that's what is unlocking this whole new wave of innovation that we're seeing right now. So data understanding would be the essence of it. >> So it's not a Big Bang kind of theory, it's been evolving over time, and I think that the tipping point has been the advancements and other things. I mean look at cloud computing, and look how fast it just crept up on AWS. I mean AWS you back three, five years ago, I was talking to Swami yesterday, and their big news about AI, expanding the Hugging Face's relationship with AWS. And just three, five years ago, there wasn't a model training models out there. But as compute comes out, and you got more horsepower,, these large language models, these foundational models, they're flexible, they're not monolithic silos, they're interacting. There's a whole new, almost fusion of data happening. Do you see that? I mean is that part of this? >> Of course, of course. I mean this wave is building on all the previous waves. We wouldn't be at this point if we did not have hardware that can scale, in a very efficient way. We wouldn't be at this point, if we don't have data that we're collecting about everything we do, that we're able to process in this way. So this, this movement, this motion, this phase we're in, absolutely builds on the shoulders of all the previous phases. For some of the observers from the outside, when they see chatGPT for the first time, for them was like, "Oh my god, this just happened overnight." Like it didn't happen overnight. (laughing) GPT itself, like GPT3, which is what chatGPT is based on, was released a year ahead of chatGPT, and many of us were seeing the power it can provide, and what it can do. I don't know if Ed agrees with that. >> Yeah, Ed? >> I do. Although I would acknowledge that the possibilities now, because of what we've hit from a maturity standpoint, have just opened up in an incredible way, that just wasn't tenable even three years ago. And that's what makes it, it's true that it developed incrementally, in the same way that, you know, the possibilities of a mobile handheld device, you know, in 2006 were there, but when the iPhone came out, the possibilities just exploded. And that's the moment we're in. >> Well, I've had many conversations over the past couple months around this area with chatGPT. John Markoff told me the other day, that he calls it, "The five dollar toy," because it's not that big of a deal, in context to what AI's doing behind the scenes, and all the work that's done on ethics, that's happened over the years, but it has woken up the mainstream, so everyone immediately jumps to ethics. "Does it work? "It's not factual," And everyone who's inside the industry is like, "This is amazing." 'Cause you have two schools of thought there. One's like, people that think this is now the beginning of next gen, this is now we're here, this ain't your grandfather's chatbot, okay?" With NLP, it's got reasoning, it's got other things. >> I'm in that camp for sure. >> Yeah. Well I mean, everyone who knows what's going on is in that camp. And as the naysayers start to get through this, and they go, "Wow, it's not just plagiarizing homework, "it's helping me be better. "Like it could rewrite my memo, "bring the lead to the top." It's so the format of the user interface is interesting, but it's still a data-driven app. >> Absolutely. >> So where does it go from here? 'Cause I'm not even calling this the first ending. This is like pregame, in my opinion. What do you guys see this going, in terms of scratching the surface to what happens next? >> I mean, I'll start with, I just don't see how an application is going to look the same in the next three years. Who's going to want to input data manually, in a form field? Who is going to want, or expect, to have to put in some text in a search box, and then read through 15 different possibilities, and try to figure out which one of them actually most closely resembles the question they asked? You know, I don't see that happening. Who's going to start with an absolute blank sheet of paper, and expect no help? That is not how an application will work in the next three years, and it's going to fundamentally change how people interact and spend time with opening any element on their mobile phone, or on their computer, to get something done. >> Yes. I agree with that. Like every single application, over the next five years, will be rewritten, to fit within this model. So imagine an HR application, I don't want to name companies, but imagine an HR application, and you go into application and you clicking on buttons, because you want to take two weeks of vacation, and menus, and clicking here and there, reasons and managers, versus just telling the system, "I'm taking two weeks of vacation, going to Las Vegas," book it, done. >> Yeah. >> And the system just does it for you. If you weren't completing in your input, in your description, for what you want, then the system asks you back, "Did you mean this? "Did you mean that? "Were you trying to also do this as well?" >> Yeah. >> "What was the reason?" And that will fit it for you, and just do it for you. So I think the user interface that we have with apps, is going to change to be very similar to the user interface that we have with each other. And that's why all these apps will need to evolve. >> I know we don't have a lot of time, 'cause you guys are very busy, but I want to definitely have multiple segments with you guys, on this topic, because there's so much to talk about. There's a lot of parallels going on here. I was talking again with Swami who runs all the AI database at AWS, and I asked him, I go, "This feels a lot like the original AWS. "You don't have to provision a data center." A lot of this heavy lifting on the back end, is these large language models, with these foundational models. So the bottleneck in the past, was the energy, and cost to actually do it. Now you're seeing it being stood up faster. So there's definitely going to be a tsunami of apps. I would see that clearly. What is it? We don't know yet. But also people who are going to leverage the fact that I can get started building value. So I see a startup boom coming, and I see an application tsunami of refactoring things. >> Yes. >> So the replatforming is already kind of happening. >> Yes, >> OpenAI, chatGPT, whatever. So that's going to be a developer environment. I mean if Amazon turns this into an API, or a Microsoft, what you guys are doing. >> We're turning it into API as well. That's part of what we're doing as well, yes. >> This is why this is exciting. Amr, you've lived the big data dream, and and we used to talk, if you didn't have a big data problem, if you weren't full of data, you weren't really getting it. Now people have all the data, and they got to stand this up. >> Yeah. >> So the analogy is again, the mobile, I like the mobile movement, and using mobile as an analogy, most companies were not building for a mobile environment, right? They were just building for the web, and legacy way of doing apps. And as soon as the user expectations shifted, that my expectation now, I need to be able to do my job on this small screen, on the mobile device with a touchscreen. Everybody had to invest in re-architecting, and re-implementing every single app, to fit within that model, and that model of interaction. And we are seeing the exact same thing happen now. And one of the core things we're focused on at Vectara, is how to simplify that for organizations, because a lot of them are overwhelmed by large language models, and ML. >> They don't have the staff. >> Yeah, yeah, yeah. They're understaffed, they don't have the skills. >> But they got developers, they've got DevOps, right? >> Yes. >> So they have the DevSecOps going on. >> Exactly, yes. >> So our goal is to simplify it enough for them that they can start leveraging this technology effectively, within their applications. >> Ed, you're the COO of the company, obviously a startup. You guys are growing. You got great backup, and good team. You've also done a lot of business development, and technical business development in this area. If you look at the landscape right now, and I agree the apps are coming, every company I talk to, that has that jet chatGPT of, you know, epiphany, "Oh my God, look how cool this is. "Like magic." Like okay, it's code, settle down. >> Mm hmm. >> But everyone I talk to is using it in a very horizontal way. I talk to a very senior person, very tech alpha geek, very senior person in the industry, technically. they're using it for log data, they're using it for configuration of routers. And in other areas, they're using it for, every vertical has a use case. So this is horizontally scalable from a use case standpoint. When you hear horizontally scalable, first thing I chose in my mind is cloud, right? >> Mm hmm. >> So cloud, and scalability that way. And the data is very specialized. So now you have this vertical specialization, horizontally scalable, everyone will be refactoring. What do you see, and what are you seeing from customers, that you talk to, and prospects? >> Yeah, I mean put yourself in the shoes of an application developer, who is actually trying to make their application a bit more like magic. And to have that soon-to-be, honestly, expected experience. They've got to think about things like performance, and how efficiently that they can actually execute a query, or a question. They've got to think about cost. Generative isn't cheap, like the inference of it. And so you've got to be thoughtful about how and when you take advantage of it, you can't use it as a, you know, everything looks like a nail, and I've got a hammer, and I'm going to hit everything with it, because that will be wasteful. Developers also need to think about how they're going to take advantage of, but not lose their own data. So there has to be some controls around what they feed into the large language model, if anything. Like, should they fine tune a large language model with their own data? Can they keep it logically separated, but still take advantage of the powers of a large language model? And they've also got to take advantage, and be aware of the fact that when data is generated, that it is a different class of data. It might not fully be their own. >> Yeah. >> And it may not even be fully verified. And so when the logical cycle starts, of someone making a request, the relationship between that request, and the output, those things have to be stored safely, logically, and identified as such. >> Yeah. >> And taken advantage of in an ongoing fashion. So these are mega problems, each one of them independently, that, you know, you can think of it as middleware companies need to take advantage of, and think about, to help the next wave of application development be logical, sensible, and effective. It's not just calling some raw API on the cloud, like openAI, and then just, you know, you get your answer and you're done, because that is a very brute force approach. >> Well also I will point, first of all, I agree with your statement about the apps experience, that's going to be expected, form filling. Great point. The interesting about chatGPT. >> Sorry, it's not just form filling, it's any action you would like to take. >> Yeah. >> Instead of clicking, and dragging, and dropping, and doing it on a menu, or on a touch screen, you just say it, and it's and it happens perfectly. >> Yeah. It's a different interface. And that's why I love that UIUX experiences, that's the people falling out of their chair moment with chatGPT, right? But a lot of the things with chatGPT, if you feed it right, it works great. If you feed it wrong and it goes off the rails, it goes off the rails big. >> Yes, yes. >> So the the Bing catastrophes. >> Yeah. >> And that's an example of garbage in, garbage out, classic old school kind of comp-side phrase that we all use. >> Yep. >> Yes. >> This is about data in injection, right? It reminds me the old SQL days, if you had to, if you can sling some SQL, you were a magician, you know, to get the right answer, it's pretty much there. So you got to feed the AI. >> You do, Some people call this, the early word to describe this as prompt engineering. You know, old school, you know, search, or, you know, engagement with data would be, I'm going to, I have a question or I have a query. New school is, I have, I have to issue it a prompt, because I'm trying to get, you know, an action or a reaction, from the system. And the active engineering, there are a lot of different ways you could do it, all the way from, you know, raw, just I'm going to send you whatever I'm thinking. >> Yeah. >> And you get the unintended outcomes, to more constrained, where I'm going to just use my own data, and I'm going to constrain the initial inputs, the data I already know that's first party, and I trust, to, you know, hyper constrain, where the application is actually, it's looking for certain elements to respond to. >> It's interesting Amr, this is why I love this, because one we are in the media, we're recording this video now, we'll stream it. But we got all your linguistics, we're talking. >> Yes. >> This is data. >> Yep. >> So the data quality becomes now the new intellectual property, because, if you have that prompt source data, it makes data or content, in our case, the original content, intellectual property. >> Absolutely. >> Because that's the value. And that's where you see chatGPT fall down, is because they're trying to scroll the web, and people think it's search. It's not necessarily search, it's giving you something that you wanted. It is a lot of that, I remember in Cloudera, you said, "Ask the right questions." Remember that phrase you guys had, that slogan? >> Mm hmm. And that's prompt engineering. So that's exactly, that's the reinvention of "Ask the right question," is prompt engineering is, if you don't give these models the question in the right way, and very few people know how to frame it in the right way with the right context, then you will get garbage out. Right? That is the garbage in, garbage out. But if you specify the question correctly, and you provide with it the metadata that constrain what that question is going to be acted upon or answered upon, then you'll get much better answers. And that's exactly what we solved Vectara. >> Okay. So before we get into the last couple minutes we have left, I want to make sure we get a plug in for the opportunity, and the profile of Vectara, your new company. Can you guys both share with me what you think the current situation is? So for the folks who are now having those moments of, "Ah, AI's bullshit," or, "It's not real, it's a lot of stuff," from, "Oh my god, this is magic," to, "Okay, this is the future." >> Yes. >> What would you say to that person, if you're at a cocktail party, or in the elevator say, "Calm down, this is the first inning." How do you explain the dynamics going on right now, to someone who's either in the industry, but not in the ropes? How would you explain like, what this wave's about? How would you describe it, and how would you prepare them for how to change their life around this? >> Yeah, so I'll go first and then I'll let Ed go. Efficiency, efficiency is the description. So we figured that a way to be a lot more efficient, a way where you can write a lot more emails, create way more content, create way more presentations. Developers can develop 10 times faster than they normally would. And that is very similar to what happened during the Industrial Revolution. I always like to look at examples from the past, to read what will happen now, and what will happen in the future. So during the Industrial Revolution, it was about efficiency with our hands, right? So I had to make a piece of cloth, like this piece of cloth for this shirt I'm wearing. Our ancestors, they had to spend month taking the cotton, making it into threads, taking the threads, making them into pieces of cloth, and then cutting it. And now a machine makes it just like that, right? And the ancestors now turned from the people that do the thing, to manage the machines that do the thing. And I think the same thing is going to happen now, is our efficiency will be multiplied extremely, as human beings, and we'll be able to do a lot more. And many of us will be able to do things they couldn't do before. So another great example I always like to use is the example of Google Maps, and GPS. Very few of us knew how to drive a car from one location to another, and read a map, and get there correctly. But once that efficiency of an AI, by the way, behind these things is very, very complex AI, that figures out how to do that for us. All of us now became amazing navigators that can go from any point to any point. So that's kind of how I look at the future. >> And that's a great real example of impact. Ed, your take on how you would talk to a friend, or colleague, or anyone who asks like, "How do I make sense of the current situation? "Is it real? "What's in it for me, and what do I do?" I mean every company's rethinking their business right now, around this. What would you say to them? >> You know, I usually like to show, rather than describe. And so, you know, the other day I just got access, I've been using an application for a long time, called Notion, and it's super popular. There's like 30 or 40 million users. And the new version of Notion came out, which has AI embedded within it. And it's AI that allows you primarily to create. So if you could break down the world of AI into find and create, for a minute, just kind of logically separate those two things, find is certainly going to be massively impacted in our experiences as consumers on, you know, Google and Bing, and I can't believe I just said the word Bing in the same sentence as Google, but that's what's happening now (all laughing), because it's a good example of change. >> Yes. >> But also inside the business. But on the crate side, you know, Notion is a wiki product, where you try to, you know, note down things that you are thinking about, or you want to share and memorialize. But sometimes you do need help to get it down fast. And just in the first day of using this new product, like my experience has really fundamentally changed. And I think that anybody who would, you know, anybody say for example, that is using an existing app, I would show them, open up the app. Now imagine the possibility of getting a starting point right off the bat, in five seconds of, instead of having to whole cloth draft this thing, imagine getting a starting point then you can modify and edit, or just dispose of and retry again. And that's the potential for me. I can't imagine a scenario where, in a few years from now, I'm going to be satisfied if I don't have a little bit of help, in the same way that I don't manually spell check every email that I send. I automatically spell check it. I love when I'm getting type ahead support inside of Google, or anything. Doesn't mean I always take it, or when texting. >> That's efficiency too. I mean the cloud was about developers getting stuff up quick. >> Exactly. >> All that heavy lifting is there for you, so you don't have to do it. >> Right? >> And you get to the value faster. >> Exactly. I mean, if history taught us one thing, it's, you have to always embrace efficiency, and if you don't fast enough, you will fall behind. Again, looking at the industrial revolution, the companies that embraced the industrial revolution, they became the leaders in the world, and the ones who did not, they all like. >> Well the AI thing that we got to watch out for, is watching how it goes off the rails. If it doesn't have the right prompt engineering, or data architecture, infrastructure. >> Yes. >> It's a big part. So this comes back down to your startup, real quick, I know we got a couple minutes left. Talk about the company, the motivation, and we'll do a deeper dive on on the company. But what's the motivation? What are you targeting for the market, business model? The tech, let's go. >> Actually, I would like Ed to go first. Go ahead. >> Sure, I mean, we're a developer-first, API-first platform. So the product is oriented around allowing developers who may not be superstars, in being able to either leverage, or choose, or select their own large language models for appropriate use cases. But they that want to be able to instantly add the power of large language models into their application set. We started with search, because we think it's going to be one of the first places that people try to take advantage of large language models, to help find information within an application context. And we've built our own large language models, focused on making it very efficient, and elegant, to find information more quickly. So what a developer can do is, within minutes, go up, register for an account, and get access to a set of APIs, that allow them to send data, to be converted into a format that's easy to understand for large language models, vectors. And then secondarily, they can issue queries, ask questions. And they can ask them very, the questions that can be asked, are very natural language questions. So we're talking about long form sentences, you know, drill down types of questions, and they can get answers that either come back in depending upon the form factor of the user interface, in list form, or summarized form, where summarized equals the opportunity to kind of see a condensed, singular answer. >> All right. I have a. >> Oh okay, go ahead, you go. >> I was just going to say, I'm going to be a customer for you, because I want, my dream was to have a hologram of theCUBE host, me and Dave, and have questions be generated in the metaverse. So you know. (all laughing) >> There'll be no longer any guests here. They'll all be talking to you guys. >> Give a couple bullets, I'll spit out 10 good questions. Publish a story. This brings the automation, I'm sorry to interrupt you. >> No, no. No, no, I was just going to follow on on the same. So another way to look at exactly what Ed described is, we want to offer you chatGPT for your own data, right? So imagine taking all of the recordings of all of the interviews you have done, and having all of the content of that being ingested by a system, where you can now have a conversation with your own data and say, "Oh, last time when I met Amr, "which video games did we talk about? "Which movie or book did we use as an analogy "for how we should be embracing data science, "and big data, which is moneyball," I know you use moneyball all the time. And you start having that conversation. So, now the data doesn't become a passive asset that you just have in your organization. No. It's an active participant that's sitting with you, on the table, helping you make decisions. >> One of my favorite things to do with customers, is to go to their site or application, and show them me using it. So for example, one of the customers I talked to was one of the biggest property management companies in the world, that lets people go and rent homes, and houses, and things like that. And you know, I went and I showed them me searching through reviews, looking for information, and trying different words, and trying to find out like, you know, is this place quiet? Is it comfortable? And then I put all the same data into our platform, and I showed them the world of difference you can have when you start asking that question wholeheartedly, and getting real information that doesn't have anything to do with the words you asked, but is really focused on the meaning. You know, when I asked like, "Is it quiet?" You know, answers would come back like, "The wind whispered through the trees peacefully," and you know, it's like nothing to do with quiet in the literal word sense, but in the meaning sense, everything to do with it. And that that was magical even for them, to see that. >> Well you guys are the front end of this big wave. Congratulations on the startup, Amr. I know you guys got great pedigree in big data, and you've got a great team, and congratulations. Vectara is the name of the company, check 'em out. Again, the startup boom is coming. This will be one of the major waves, generative AI is here. I think we'll look back, and it will be pointed out as a major inflection point in the industry. >> Absolutely. >> There's not a lot of hype behind that. People are are seeing it, experts are. So it's going to be fun, thanks for watching. >> Thanks John. (soft music)

>>live from Las Vegas. It's the Q covering AWS executive. Something brought to you by extension. >>Welcome back, everyone to the cubes. Live coverage of the ex Censure Executive Summit here at AWS. Reinvent I'm your host, Rebecca Knight. We have two guests for this segment. We have Satya Adric, Carl Adder Gala. Sorry, He is the VP single family technology at Fannie Mae. Thanks so much for coming on the show. Satya >>glad to be here. >>And we have Dave Baldwin, VP Architecture, Cloud Engineering at Fannie Mae. Thank you so much for coming on the show D thanks >>for having us. >>So we're talking today about transforming the mortgage industry through through the cloud. Fannie Mae is obviously a foundational part of the US home mortgage industry, and it's been around for a long time. But at a time right now, where there is just so much tremendous change going on in the industry, particularly with the emergence of fintech and other push button mortgage providers, talk a little bit about the last 3 to 5 years. In terms of the changes, you've seen two to the business. You want to start? >>Yeah, I will. So So when we look at the industry changes. What Fannie Mae does is mostly in the secondary market, so our core business hasn't changed from the point of taking the lone synchronizing and selling. However, in the mortgage industry, when we talk about the bar or experience and then the lenders how they have improved the experience across the board, I think is it has been a huge shift right three years ago. The discussion has bean always about Hey, can we do more reliably? Can we do more faster? Right? Those were the conversations, but now the expectations off our lenders and bottles have significantly increased. Right now, they're talking about user experience. How can we meet our bar or where they are, Right. So the lenders have got a lot of expectations on us in terms of how do you feel? Feel that that is the first biggest change in the realm off several of these, right? The 2nd 1 ese, the data has become the currency now, right? It has significantly improved our posture around finding about, um, their assets that income, their employment. Right. So you guys may have seen a lot off David surgeon. It is a product that we have launched in that well, so data revolution has been a big change. And then how we're utilizing that to serve Margaret's industry, our lenders and borrowers, thereby we also reduce the risk within the industry. Right? So those two have bean huge changes. Then there is a technology revolution in terms off AP eyes, Microsurgery says. How do I plug and play? How do we reduce my cost when I'm locking a bottle or two alone? Right. And these are the things that are lenders have bean pushing us on right? Reduced the cycle from somebody coming to the application to taking a loan, closing alone and delivering to Fannie Mae. Shrink the timeline and in doing it, reduce our costs. Right? So these are being like more and more expectations Have bean really set from the border for a few from the lender point of view on Fanny me and all our innovation. Our transformation is all about meeting them and also setting standard for them. What is great in this industry and that's that's what has been going on in the last 3 to 5 years. >>Yes, and that you just laid out a tremendous number of trends and all this disruptive change when you were trying to meet these new expectations from your lenders and your borrowers. Dave. What? What are the in making this journey to, from to to say, I'm sorry from to the Cloud, How are you thinking about these challenges ahead at a time where the user experience is so important? Data is currency and this technology revolution, >>well, it's a big change and, you know, and it's a change across people, process and technology. So if you think about it, what we've done is we've started to trade a new operating model, which really is a lot more engaging, and and it requires an uptick, a scale and really ah, a new way of working right. We've even gone as far as to introduce lean management in a tools and processes. But if you think about it, the people definitely have to change. If you think about it from a process point of view, you're you're really looking at reimagining the way some of the mortgage industry works right, because there's a lot of demand for it. At the end of the day, the customer expectations and especially If you go all the way to the borrower, the customer expectations is very different. You know, they're very they they don't understand unnecessarily why they would have to fill out all this paperwork, right? When don't you already have the information? And to sati is point about data. That's why it's so important to get that data together. Because if we can harness it right, then we can truly start to re imagine these processes and make it so much easier for a borrower nor a lender to work together and eventually work with us. So and then finally, you know, from a tech point of view with the introduction of the cloud, you know, that new foundational sort of technology that really gives you something to pivot off, you can really you can really start to take advantage of the micro service architectures and the new technical capabilities that can help make this really right. And so that's That's generally how we look at our digital transformation and and as you start to think about prioritization, how do I move those? How do I think about the applications that are going to change and how they're gonna neither either Transformer moved to the cloud. You really start to think of you know what business value and I'm trying to achieve 1st 2nd 3rd right? And then what applications won't make it, You know, they're gonna be completely redone. And what applications? Frankly, we're gonna have to move along with it to manage some of the dependencies we're going. >>So I think one more point I wanted and Rebecca is that when we look at this B to B businesses, they're very tightly integrated, right? Our companies have been integrated when we are extending out information explained, extending the responses in the past. Anybody talks about experience, right? It is about Hey, there will be there are technological glitches, but you don't want to impact big. That's used to be the norm. Not anymore. I think when we look at now one of the top customer slate, if you blink from the infrastructure layer point of view, there is business loss. People are not just looking for resiliency anymore. People are looking for fault tolerance, especially when it comes to the top to your customers. Right. So I think we can see the underpinning off cloud and also how we architect our applications to meet that kind of need. It's not just about being resilient anymore. Gotta be. You cannot lose a transaction. But I think those things have bean more and more that we're hearing from our customer base, and we feel like the cloud journey is going to be underpinning for these types of expectations from our customers. >>So how do you work with partners like Accenture in AWS? When you embark on this journey and think through the your business imperatives and think through your strategy, >>I think when when we think about our partnership's. First of all, there are a lot of partners that we have and that we've had for years, as we as we really not only do digital transformation, but you got to run the business, too, while you're doing this transformation. And so you know, when you think about it, the way the wake centers worked with us is you know they number one have helped us with a cloud strategy. So that's a very hard thing to Dio because you think about all the different personalities in your organization and all the people that you have to bring together. You know what Accenture helped us with. It is to really level, said everyone and get everybody on the same page in terms of, you know, where we want to go on how we wanna head on this journey. The second thing that they helped us with was really the program management. So that's a huge undertaking to write and given the fact that it's very different and these are new things that we're doing in our firm. It's good to have that external expertise that that sort of done it with other companies and they can bring that to bear with eight of us. You know, eight of us is is one of one of the major providers that we're using. Thio post a lot of our business applications, and if you think about that there, you know we're taking advantage of their technology. We're leveraging some of their pro serve professional service is thio, help us get it right and help us sort of not only with the implementation, but in some cases the governance and control frameworks that are highly regulated. Organization like ours needs So >>and I think if you think about this from the scale point of view, right? Everybody knows there is war for talent, right? We use our partners in terms of how can we scale these things that are new operating models? New technological? Because there is a change curl in bringing up the entire employees based without extent, These guys can be catalyst. In addition to that, they can be scaled provided us, right. I think that's how we can I use these, But it is action generator B s. >>This morning during Andy Jassy fireside chat, he talked a lot about the importance of innovation and experimentation and trying different things. How What's the experience of innovation at Fannie Mae? How do you innovate with partners or just thinking about all of the changed expectations? How do you make sure you are trying to solve the right problems? Describe your process creative process >>again, I think, um, when we I think about this innovation process and how we do water in Fannie Mae right three years ago, it is about Hey, how do we get our employee base to think about the possibilities right on Veran bunch of hackathons innovation days so that you get excitement from the teams, but in the last one and 1/2 year. It's more about innovation that can reap benefits, right? So we call it as focused innovation. We have, ah, clear cut Enterprise Innovation team. And they're on some of these innovation days and whatever have you within the within the firm so that you get the ideas and we have a process called pitch. So all these ideas feeding to lack of a better time a funnel where we have this enterprise innovation groups actually scan through the I. D. S and then can identify what things we can use and where we want to put our innovation investments. Right. So there is, ah, set off funnel requirements and gates we go through to identify Hey, this is where we want to do. And how we do is that Fanny Me is a lot more design thinking shop, right? So customer is at the center of everything. So anything we do, we will have some sort of research first, right with the customers and then how that might push the needle such that it can reach different boundaries through innovation. Right? So our processes cultivated ideas from inside. Also, look at what is happening with the trends. We have a strong strategy group. They're gonna look at this and our innovation team is always on the hunt for Hey, what is happening in industry in the cutting edge, How do you bring these three dimensions and then come up with a bunch of ideas? And then we have a funnel process where we identified what moves? What's this? What stays? Because there are other things that are at play. Is this innovation ready for the market? Now? Does it have to wait that sort of There are so many dimensions that going to that. But we have a structure process, and we have AH, dedicated team who can manage is that yet uses the creativity of the employees to be able to participate in animation. I mean, that's how we have a wall this process from. Think of the possibilities, too focused innovation. >>I think there's one extra point as well, like when it comes to technology side of that, it's it's creating a safe place for people to experiment, right, So we have a sandbox, the environment that we've created, an Amazon there in eight of us, and what we're doing is we're actually releasing some of the controls. I mean, obviously there's security and compliance, but released some of the controls and and just put a few guard rails in place so that people can experiment safely and not impact our firm, you know, in a very negative way. So >>talk about your employees and how they received this, this major transformation, and how are you receiving feedback in terms of their productivity in their engagement with the process? Dave. >>So you know, I would say this. There are lots of different types of employees, right? And like I said earlier, we also have as we're building the new, we also have to continue to support what we're running. So So what we've done is we've actually rolled out on South. We'll talk about it more detail because his team rolled it out. But, you know, but we have rolled out some training. You know, we've created a change management process, an organization right. Working with our human resource is so that we can up left, you know, sort of skills. And that's what I think. What's important is you're not going to be able to find the people out there to do everything that you need to do right. What's really important is creating those opportunities to carry the people that you have in your organization along with you for the journey as they learn you benefit right as an organization. So but salty should talk about some >>of the training. Yeah, so I take your question in two parts one. Is that how the employee base is taking the message of this district transformation or don't have right again? We have a compelling vision and mission like people that fanny man, they what? They take pride in fulfilling the mission. That's that's the 1st 1 along the way, when we crafted our message around why we're doing this. That is a lot more compelling. It is meaningful for our customers, our employees, right? So I think the messaging has been very important. Then, when you look at the things that we're trying to do, our cutting edge right from the employee point, if you it is a lot of excitement, because that keeps them at the cutting edge of what is happening in the world that makes them more marketable, right? Naturally, people are excited about it, but like any transformation, right? There will be camps off who will come across the change car up front like they're catalyst. Right? And then there are some in the middle and summer can a lagging right? But when we look at the entire gambit off the employee base, majority off them are. Hey, we are on board with this. We want to do it. We want to learn, How do we get there? And the company has done several different things to help the employees through this kind of knowledge cover I would call rather than the change career. We have a whole bunch of training plans that we have laid out. People have been wall until early taking. I mean, maybe a classroom training, maybe a self, sir. Uh, type off, download this particular module and then kind of read upon it and then also provide them to practice them with the sandbox. Right? So all these things have been done. I think one challenge we had actually facing now is that we can train them up pretty easily if we haven't put them in a place to practice it. Then it kind of fades away. So we're now kind of trying to see. Okay, let's identify groups off people. Give them a tool where they can assess for them their own self. What I wanted to learn such that I can become that and then be eligible for doing that right so that now they learn. And then they're put in a role on a project that they can actually practice on. So we are in that posture of that right now. So I think, but employee base is really excited about this, >>So I want to. I want to end where we started where Sati described the myriad changes that are taking place in your industry and getting back to your your cause, which is helping the customer buy a home, get it, get it, get it more easily, qualify for a loan. Can you think about the customer experience of the home buying process 3 to 5 10 years from now? And how it will be different as Fannie Mae embarks on this on this cloud journey. Do you want to start David? Just think. Look into your crystal ball >>and it's great. I wish I had a crystal ball. That would be great, but but you know. Look, we're making significant advancements, you know, working, working with our customers, taking that customer first mentality. And, ah, and and, you know, the mortgage industry itself is right for a change. I mean, you know, and and we're in a good position to really help and drive a lot of that. So my expectation, if I were to look out, I would expect to see a world where you know that borrower experience gets a lot better. I mean, one of the things we've learned to our research is that you know what is it? 40% of people actually cry as they're going through the mortgage experience, >>and they're not tears of joy. No, it's actually, you >>know, tougher to get into a tougher to think through the mortgage process, you know, and really take that big leap than it is to, you know, our Cielo tells us all the time than it is to actually apply for college. It z, it's often on bigger life event our goal. How do we make that simpler? How do we make people have a much more pleasant experience? Right? Waken do that with our data. We can make sure that they don't have to fill out those amazing forms. Heck, find the information. Sometimes they don't have it. You know, we're in a better position, right? You know, really? Get Teoh. You know, I can't promise a single click experience, but we're all gonna try to aspire to that, because that's what the customers out there with their cell phones and their technology or used to right. So we've got to get at least somewhere close to being there. >>So in the bottle, it expedient sight. I think we can even now see one tap market. How do we get them right? I think that's probably not too far. It's probably within two or three years. That's if I were to think about that. But if you want to think about 5 to 6 years, 10 years, if I am an individual driving by a home and then take your phone and say, Hey, can I buy this home? That should be able to tell you this is your lender and then go. That's right. And again from Fannie Mae, a point if you re help the lenders and they helped the borrowers threat. So through this transformation, what we're doing is that set up an engine that can be nimble, that can move fast. That runs with the low investment so that if we were to pivot, do things testing, learn and then change your game. We are fully in the position to be able to do that, right So and however fast, fast, you can experiment, those many different ideas will come out, and then some of them will reap fruit. And all of these for two things, like for our customers. How do we benefit our company, Fannie Mae? And how do we move the needle in industry? I think these are the three things that we want to achieve through this transformation. And we're building an engine to be able to do those types of things. I wish I could say this is one thing we would do. That's not what we're trying to do. Being a position where we can move quickly, we can lead industry. We can set the standard and then make good for the good for the American house. So that's all stories. >>Exciting times. Thank you so much. Both for coming on the Cube. Satti on Dave. Thank you. I'm Rebecca night. Stay tuned for more of the cubes. Live coverage of the Ex Censure Executive Summit coming up in just a little bit.

>> Live, from Las Vegas. It's theCUBE! Covering Dell Technologies World 2019, brought to you by Dell Technologies, and its ecosystem partners. >> Welcome to theCUBE's coverage of Dell Technologies World 2019 from Las Vegas at the Sands Expo Center. I'm Lisa Martin with John Furrier, this is day one of two sets of coverage for three days for theCUBE. There are at least 15,000 people here, we just came from a great keynote, Michael Dell, Pat Gelsinger, Jeff Clarks, Sati Netella was here. John and I are pleased to welcome back to theCUBE one of our guests, we've got Doug Schmitt, president of Dell Technologies Services. Doug, welcome back. >> Well, thank you for having me. >> And you've brought a partner in crime, we have Alex Barretto, Senior Vice President of Dell Technologies Services, Strategic Planning, and Technology. Alex, welcome to theCUBE. >> Thank you, happy to be here. >> So guys, I always love the keynotes. Michael always has- Michael and team always have great energy. Lot of cool announcements, all talking about digital transformation. But Doug, let's start with you, let's talk about the transformation of Dell Technologies Services. Give us an overview of your organization, and what you're doing for Dell Technologies Services. >> Yeah, well thank you for having us back. I know we were here last year talking a little bit about Dell Technologies, and wow, what an opening keynote this morning. And following up on that; look, service is key component, obviously. Helping our customers through their transformation. Our number one priority, it's really simple. It's literally about, for, and helping the customers. Whether it be specifically kind of, three areas: to sport, deployment, and their manning services. And helping them not only keep their data centers to the edge, running correctly. Making sure to help them through their transformations that they're going through, that we talked a lot about this morning. And then, what we do is we support our customers really with 60,000 people globally, about half of those are Dell Badge, the others, we leverage partners in various countries for. Look, it's about getting up every day and making sure everything runs correctly for them. And that's our job. >> Alex, talk about the strategy for services. Because one of the highlights in the keynote was Bank of America talking about how they got where they are today, and they go forward. It's not the same, things are changing, you guys have to change. What's changing in sevices? What's the strategy? Because it's a whole new ballgame. >> Yeah, great question. In fact, technology is- we have to ask ourselves of our own transformation. In fact, Doug and I spend quite a bit of time talking about a technology world map. Really, if you open the aperture of 'What is technology?', it's everything from data science, to our bots, to our software engineers, into the AI, engineers are developing both in-house as well as partnering with others. That is really the essence of what we're doing in services, and you see customers like Bank of America really adopting that. Because it's helpful in the value that customers get out of our technology. >> And the data was also important, they mentioned data. How are you guys using data in services? I'm sure you must be data-driven. I mean, the mandate up from high, Michael's like, "It's a data-driven world, it's clear as day." >> Absolutely, data is essential. In fact, if you look at the amount of data that's out there, and the growth of the data, it's just phenomenal. But the way I actually like to talk about data is the insights we get from data, right? Data is interesting, but the value that you get from data comes from the insights. So, we actually spent a lot of time developing models, and that's why we use a lot of data scientists, a lot of software engineers. Again, to develop models to generate value from the data. That value is what customers are looking for, and what we're focused on. >> In terms of value, one of the things that was also talked about this morning in the keynote is people and the workforce being massively distributed for any kind of business. 81% of the average worker, is outside of the traditional office, with over half of these people, I'm one of them, working in at least three different places every week. You've got customers that are highly distributed, as is your workforce. What can you talk to us, Alex, about the unified workspace announced on stage this morning? >> Fantastic new offering that we have, obviously you heard from Jeff onstage talking about that. And if you look at that, there are a couple elements that are interesting to me. First, you see all the pieces of Dell Technologies coming together to create greater value for the customer, and if you look at the value that's generated there, to your point, wherever you are as a customer, you're able to access your specific information, whatever the device. And so, if you think about your whole experience, device independent, as well as from a software standpoint, we can offer all in one. >> How, how is-- Sorry Doug, how is service integral to this, you know? >> Well that's-- yeah. What that's really about is so, you have workspace one, coming from VM, great offer and product. And then you have our services, which would be pro-deploy, are pro-support and in some cases, even the manning services, coming together with that to provide a wrapper around that. So, customers have that end-to-end experience with unified workspace, getting those four great service offerings together. Which really then brings it all together for the customer. So they have to do very little, quite frankly, to make that happen. >> One of the comments from Sati Netella was the whole new renaissance of IT needs infrastructure. You see the VX rail being bundled into data centers and service, the demo of the VM-ware cloud, where the just deploy a data center to the edge. I mean, this is just completely game-changing. How is that changing how you guys do the services? Because you guys, it was self-healing. There was a lot of stuff in the dashboard-- no one was deployed, it was all being done with software. How is this changing your mix of business, personnel, economics? >> Great question. You know, we talk about how we're helping customers transform Dell Technologies, well look, services is going through its own transformation as well. And I think that's what you're bringing up. And really, there's four pivots around that transformation we see inside of services that we have to do to stay up and make sure that we're cutting-edge for our customers. The first is around technology, Alex talked a little bit about that. But really, what that's about is the telemetry to help our customers. Data insights, it's not just the data. The second is around our systems that we're putting in place to leverage all that telemetry. You know, we're basically building a whole new CRM, bringing everything together. Our field capabilities, in terms of systems we're building out as well. So a massive transformation on the infrastructure inside just running this to support really. It's a $150 million install base. >> Can you share just stats or data on what's the most popular services you're deploying? And which ones are trending? Like, which ones are kind of, people kicking the tires on? Obviously, you've got the grooves swing on some of your key products. What's the hottest, services/products that you have? >> Well look, our Pro Support Plus is a very hot product for us, it literally provides end-to-end support for our customers, provides what we call a technical account manager, or service account manager with it. It gives you the insights then to really go help you. So it's not then about break/fix anymore. What it's about is proactive, predictive service, and then actually using that to go to the customer and say, "Hey, you know what? "Here's what we're seeing, here's how you can improve "your environment, not only prevent issues from happening, "but what are we doing to actually improve, "and carry that environment forward." And our customers love that. >> Any up and coming, trending products, services you see? Obviously, I can see yeah, there's probably going to be some new services there, but what are going to be the hot new techniques? >> I think seeing the same spot in ProManage which you'll see us carry forward here, and carrying it into the managing service is how do we continue to provide more of that end-to-end? Really, what you're seeing is a convergence of deployment, support, and managing service all really coming together. Our customers are really looking for more and more of that one-stop shop, but one offer across the board. So that's what we're seeing. >> But just to add to that, if you our ProSupport Suite, we have SupportAssist, which is our technology behind ProSupport. And the insights that we're generating; we have 55 million devices connected now. So you look at the connectivity, and the value customers are getting out of that, it's amazing. 20 Terabytes of data per day generated out of those devices. It's a lot of information coming in, customers see the value, they connect more, and again, back to your loop that you're talking about the data. >> Well, the security visibility too, just looking at the data, with all those devices now with Windows, and all the new multiple vendors. I mean, you've got all that data. >> That's right. But I think it's the insights, you know, we keep talking about that. Those insights are really helping us leverage that for the customer so they can see in front of them, and I think what we always say internally is "Look, customers aren't looking for a rear-view mirror. "They're looking through the windshield." The more we can use that insight, to help them see when and where they need to get through for their own transformation, is what it's all about. >> And talk to us about how both of you-- Doug, we'll start with you, how have customers been sort of symbiotic to the digital transformation of services in terms of knowing, "We've got to get predictive"? How are they helping you to evolve what you're delivering so that ultimately, services is part of this technology differentiation and product front that Dell Technologies has? >> Yeah, well, you know the history of Dell Technologies is really the core of our foundation. Culturally, for all 140,000 of us, is listening to the customer. And I think that culture has allowed us to adapt and stay close to not only what the customers are telling us, using the insights we're getting back, but knowing where the customers want to head. And it truly is a one-on-one listening to the customers, listening to where their issues are at, then using this technology and their solutions to solve their problems they're bringing up. But I got to tell you, there's not a big hammer that just- one answer for that. Literally, it's how are we helping consumers? How are we helping small, medium, business? Large? All of them have a variation of what's the same, and all of them have a variation of difference as well. >> Alex, how about strategy for a minute, the strategic landscape, how has Dell Technologies Services changed with the vendor landscape? Now you've got multiple vendors, it turns into multiple clouds, multiple clouds with open source software. You've got all kinds of new things emerging. How do you stay on top of it, what's the strategy, what's the long game look like for you guys? >> If I were to summarize in a nutshell, it's software. We're investing quite a bit in software, whether that is within our predictive capabilites, but as well as in deployment services, and Doug alluded to ProManage. So software is a pivotal, key component. So this is how we are approaching from a services standpoint. Whether you talk support, deploy, or manage services, the umbrella around that is really our capability to do the software component. So that's where we are placing our bets, we think that's where the future is. Whether it's SupportAssist, or our ProManager offering. It's all the backbone based on software development. >> And where is, we talked a lot about digital transformation and services, but the people, the people being essential to, we need the technology to do our jobs in any industry. What about skill, upleveling skills? It's great to have all the technology, but we need to have people to be trained, certified, professionals to be able to maximize the value of the services. Doug, go ahead and start, and then Alex, maybe from a strategic perspective, where is that people, cultural part of the services? >> Well, look it's huge. I don't think it's just for services, I hear our customers talk about it as well. And as Alex just mentioned, that software is driving more and more of it. You know, we use a lot of different acronyms and titles to kind of describe it, Digital Transformation, AI, BI. I mean there's all of this, but it is is all summarized in Digital Transformation. And the impact it has on our team members is vast. So look, open communication, yes, it is changing the way we do business, and quite frankly the world's doing business, the simple tasks are getting more and more automated through these insights, and they're going away. Making it easier for our customers means you're not getting as many break/fix calls, you're not getting these transactions. But what we're doing at the same time is we're upscaling the team, telling them where we need to be in the future, helping them with those skillsets, reset. The interesting thing is our team members are seeing the value of it, their jobs actually become more enriched because you're doing higher value things for our customers. But there is a transformation going on and-- >> And Doug, there's cultural changes as well, as we think about how we measure the business, some of the metrics that we look at, legacy metrics versus new metrics, they are different now. How we think about people development is different. So, I think it's a great question, 'cause the actual talent transformation, it's huge. There's short-term impact, and long-term impact. And if you don't plan that right, obviously you can't execute a strategy. >> How should your customers start rethinking about how they're leveraging the services? Because with unified workspace, data center as a service, and now multi-cloud, architecture is really important. Where the data sits, using real-time data you mentioned in software and data, so as they think about now, looking at not resetting, but taking services for their advantage. 'Cause they look at services, they want to be in the right position. It seems like architectures are more important now. Multi-cloud architecture. So, more technical people involved, the roles are changing. What should customers, how should they expect to be thinking about that? >> It's another great question. Well look, I'll let Alex follow up with his thoughts on this one. But I think this is really about us, the customers have to look as a true partnership. What we're really there trying to help them with every single day, is we talk about keeping the solutions in the system running to what they need, what they wanted. But we can also help by helping their staff free up time through the services we have, so they can stay focused on their transformation and provide the value that their teams and customers are looking for. That's really how we see that. So in other words, go into them and say, "Hey look, "we can take some of these tasks off, whether it be the deployment, unified workspace we talked about, you know, that was announced today. These are all about not only providing better technology for their team members and their customers, but then leveraging their time then to go spend it on their transformation. That's really it, quite frankly, simply put. >> Yeah, I would say it depends. Customers want to do a variety of things, so it depends on their business outcomes. So, at the end of the day, I would say, as you look at Dell Technologies, we have all the Lego blocks. You tell us what you're trying to achieve from a business standpoint, and we have the Lego blocks to make it happen. I think we're in a unique position to be able to deliver that valuable proposition to customers. So it's not a one size fits all. >> More data, more workloads, I've heard the term workload mentioned so many times in all my CUBE interviews, we all talk about workloads, but now with IOT and Edge, you're going to see a proliferation of more workloads, some small, some massive, and managing that workload is a huge challenge for organizations. This comes up as the number one issue. How does services play into that, how do you guys make that easier, and I love the operating model of simplicity, but when you guys take that realization into services, what do you guys bake out of that? What comes out of that? >> Yeah, I would say two things. First, the reason that workloads exists is that it's important for the business. So it's got to be up at times, it's got to be 100 percent. It's got to be up and running. We make sure that that happens. Second, if you look at the workloads, they're actually running critical pieces of the business. So we actually assure that we are providing additional value, beyond actually just running infrastructure, actually keeping value and how you should optimize that infrastructure so you can do more with less. >> Can you give, is there an example of a customer? John mentioned B of A was highlighted this morning, Draper was as well, I think some of the Trailblazer Winners were right before we started. A customer that comes to mind that really demonstrates the value that they're getting from Dell Technologies' suite of services? >> Well, look, I think there's a lot of those. But going back to maybe, we talked about the customers today in the keynote speeches that were happening. But look, there's a lot of small and medium businesses that are one, trying to stay with and ahead of technology. Lots of cases actually farther ahead in their transformation. I think I know of one that I recently had a conversation with, a doctor's office had four or five offices in a town here in the US. And they're staying ahead of that. They want us to "Look, we want to buy things that have "easy deployment, easy install/run. We also need you "to come in and help us tell us how to access "and leverage the technology we have better." Running it easier, staying ahead of that digital transformation, and providing really, their virtual CIO, with a technical account manager pulling all that together. You know, all from the storage, their server, their client products coming together; they don't view it as-- the customer's not coming to us and talking to us about individual products. It's not the discussion. What they're saying is "We need to purchase this, "we know we need this solution, we need to have you guys "come and pull it all together, we're looking "for our people to take care of the patients, "get the information that needs to the government, "and get paid, that's it. "And we need you to help us pull all that together." And we're doing that. >> Doug, my final question for you. Michael Dell always talks about this, within the hallway conversations, or on theCUBE. He says, "The best way to create valuable teams is to attract and retain the best talent." How are you guys attracting and retaining the talent, because the workforces are changing, the technology's changing. What are some of the hard problems? Because people love to solve hard problems. What's the pitch for people out there watching, that might want to work in the services group? What's the environment like? How do you attract great people? What kind of problems do they work on? Give a little taste. >> Well, first of all, you know, you have to love and want to take care of our customers, that's really exciting to me, and I know to the other 60,000 team members. That's why we get up for every day. There's an energy that comes from that. I mean, you're getting up and helping our customers whether they're hospitals, small, medium businesses, or consumers. Really being productive in their lives, whatever it may be. So there's an energy that comes from that, I think a lot of people enjoy doing that. It can't be more exciting than that, right? Second of all, career. Just so many aspects to this. You think about digital future technology, we have everything from being able to go out in the field and help our customers to remote, there's just so many different opportunities. And then we also have our employee resource group. So even participating beyond just work, we have the ability to join all of our different resources groups, whether it be Pride, or Veterans, or whatever they may be. People like and see value to just coming into work, but being able to take their passions that they have on the outside and bring it in as well. >> Real citizenship opportunities to bring and contribute back. >> Exactly right, giving back to our communities. very strong, very strong. You know I get an immense amount of pride in the things that I want to contribute to outside of work, and seeing and getting empowered by Dell to do those things. And then constant learning, constant, constant learning. >> I would also hint at a bit of competitive imagination. (Laughing) If you heard any barking during our interviews, speaking of things to do outside of work, we're next to Michael's Angel Paws, which is near and dear to Michael Dell's heart. That's the service dogs that are actually here for all of us to get our dog fixes on. So Doug, Alex, thank you so much for explaining to us the momentum, the excitement behind the digital transformation of Dell Technologies Services. >> Thank you for having us. >> Our pleasure. >> Thank you. For John Furrier, I'm Lisa Martin, you're watching theCUBE Live at Dell Technologies World 2019. This is day one of two sets of CUBE coverage. Stick around, our next guest will join us shortly.

>> Live from Las Vegas. It's the Cube covering Adobe Summit twenty nineteen brought to you by X Ensure Interactive. >> Hey, welcome back, everyone. Cubes live coverage here in Las Vegas for W twenty nineteen. I'm Jeffery Jeffery, my co host. Next guy's a demon Danza whose the global president of a censure interactive operations Welcome to the Cube. Thanks for joining us. >> Thank you. Thanks for having me. >> So learning a lot about the interactive piece I sent you. Interactive. What is the Centre Interactive operations? What does that do? What's the function? >> Extension Interactive Operations is the manage service arm of Accenture Interactive. And together we design, build and activate scale the best experiences on the planet for our clients. What we were finding is you know, a lot of clients were very happy with our design lead creation of experiences, but they really wanted more help to activate, operate and scale those experiences across the world. I think scale ability is now becoming the crux of many of our CMO conversations. And so it was very important for us to build out Accenture Interactive operations to scale those experiences for our clients, >> given example of what it entails. And I'm just trying to follow it through. So, like, operations, meaning like Okay, that interactive team sets up everything they hated off to you and you guys wired together is in the cloud. Isn't analytics think us through how the operations workflow is? >> Yeah, well, except your interactive very much design and build the solution for clients. And absolutely, we then come into play to make sure that way Developer, man and machine operating model. So basically, we spoke marketing engines for clients that a data powered and also we design hub and spoke models for clients across the world to give them their speed, scale and agility that they now need in their coms. So very much, you know, we architect the right or model that is needed. The client that's the marketing operating model as well as the content operating model, so that we can effectively taken experience and scale it across multiple touchpoints seamlessly with huge brand consistency across every single consumer touch. >> So they stand out very quickly then, so that their goal is okay. Get it into market quickly, stand it up, get it going >> absolutely. And rapid. Standard is really so important because there's a speed in in sort of compression of go to market, and now clients can't have weeks and months of lag time between a creation off a product and the deployment of the broader on DH. So that's why we critically have come to the party with a very man and machine and data driven model. Teo, Give them that speed. So it really is from idea mediation, proof of concept, out to market. We truncated that whole supply chain and marketing supply chain quite significantly >> so that you talked about scale and global reach. But at the same time, your warrants personalization, right? So the challenge of personalization at scale is very different than just scale for scale sake. So how are you helping clients address that part of the equation? >> Well, first and foremost with any approach to hyper personalization, the way that we actually consume and segment the data is critical. So at its centre, interactive operations will play a key role in dealing with first, second and third party data off a client to be able to devise the right cohort groups that they need to effectively target in a world of hyper personalization that's directly related to their growth ambitions. Then we will make sure that the data actually feed the content creation and customization, so that the right message conversation experiences going out to the right client at the right time in the right way. And I think that, you know, we've really hone that for a lot of clients. BMW, Disney, Malia Hotels, G S, k, Et cetera, et cetera. And it's proving unbelievably successful. >> You guys are a huge partner of Adobe and partner of the Year, pretty much every year. Great presence globally. You've got to be excited when you look at the charts on yesterday's Kino when they lay out the platform because they're setting up exactly the kinds of mechanisms around data pipeline ing, semantic translations and then really time personal. I mean, they're building everything into a platform to make a data driven, and that's the hard part of all this. I mean, what you just laid out is a hugely complex story, and to do that quickly is huge task. >> Oh, absolutely. You >> gotta like what adobes doing now with their Platform >> I am loving water job he's doing, and they're making it easier. They are almost accelerating. Where now referring to is the platform ization of marketing on DH. You know, marketing technology is now circle thirty percent off the marketing budget. That's a lot, that's I mean, that's obviously the highest it's ever been. And it's only going to go one way. So now, to be able to actually set up designed the right marketing technology, leverage it fully Onda. Also, once you've got foundational tech like Adobe Toe, also build additional vertical bespoke technology onto that really starts to get clients too competitive. And so >> that's some of the challenges markers have because we've seen the evolution of the Internet infrastructure since their Web one dot oto whatever version you call it now. But in my mind, I just see this montage of this Martek stack that logo slides that comes out every year and it's Oh my God, it's like, huge. So So So the question is, has Martek failed to live up to his expectations? All these point solutions? Or is it just natural evolution that these things are kind of consolidating into kind of pillars of of technologies with more business conversations over the top? Because that's the question that way. Here, a lot from practitioners. Just look, I don't need another platform. I don't need another tool. I got tons of tool, got tons of platform options. I just want this stuff to work. Absolutely. How do you see this? Key challenges from marketers >> I think I think it's incredibly challenging, just challenging into your reference to the Loom Escape. I mean, the Loomascape has over six thousand Martech and adtech companies in it, and we're going to see an acceleration of that consolidation in that landscape. You're absolutely right. The point solutions are going quickly accelerate to an end to end solution. So everyone is a bit of musical chairs going on at the moment. With regards to the M in a landscape on DH, it's getting more acute, actually buy them by the week. So market is a very, very challenged still, to be able to procure the right technology to be able to also make sure that they're getting maximum utilization from that technology. Some of that technology is very, very expensive, so they have bought the licenses. But actually they don't necessarily have the skills, the talent, the capabilities to drive the technology effectively. It's almost like having a Ferrari but not having a driving licence. So we're helping clients to be able to properly drive the technology and to be able to also ascertain if they have the right technology in the first place, because the landscape is moving so quickly >> or the more the wrong technology and repurpose it and re skill. I mean, it's a huge operational challenge. Absolutely. Your operation comes in and this is This comes up a lot in our conversations. I love the new capability. I just wish I knew howto implement it >> and >> then operationalize it and staff around it so that everything's in my marketing mix and in agility way, not a waterfall kind of >> completely. And that's what we do in terms of our human and machine model. We look at the ad tech Martek stacks that we're building for clients. Make sure that they're truly proprietary, bespoke doing the job that they're intended to do in terms of marketing for growth and then literally we help clients maximize everything that they can get out of that technology and making sure that really data and analytics is driving the content creation, driving the content customization cause you're now in a world of algorithmic optimization when it comes to atomic content, lots and lots of little pieces of content that I needed to fire at loading loads of different cohort groups. We could take that all on and actually make it pretty painless for a client to do that across multiple countries. >> Thank you. What about from the other side of the equation? The receiver of all this micro targeted atomic for major consumer? This's so much stuff. I was like It's like it's like driving through a snowstorm with your headlights at night. You know, it's just like, how do you get through the tent? How did you get people's attention? How are you helping people get attention in this increasingly cluttered, busy and just, you know, over sensitized, you know, kind of inbound world in which we live as consumers? And it's one thing for me to see. I think of the poor B to B marketers. Oh my goodness, what a crazy challenge they have now. >> Yeah, I mean, I think it's a great question, and I think that now it's it's less about attention. Necessarily. It's more about relevance because if you manage to achieve hyper relevance in your communication, you know, customer first communication, then by default, you are going to get the right attention and you're going to get the right result from that experience, conversation, communication, etcetera, etcetera. So really, I think being able to really excel at hyper personalization is really what we're focused on now. And data is the answer to that. And data hand in hand with artificial intelligence and machine learning really gives us an unbelievable combination on puts hyper personalization on steroids. >> I'm gonna ask you on that point, cause content becomes a key part of the marketing mix at all at levels er known and all well paid all that good stuff. But content has is about data to because being relevant is also contextually aligned with targeted distribution of that of that that those audiences. So the question is we're seeing with our video's content drives a lot of community engagement. How are customs? Think about the role of community because as the users become part of their brand engine, this is now part of a new closed loop that's developing. How do you guys see that connecting? Because if you get the content right and you get the targeting through your operations, you then will they be able to put certain content in certain channels with the right data. That means the programming has to be relevant, which is another task. But if they get that right, the community engagement goes off the charts. How do you see the community part of developing? What is the brand marketers do after that? >> I think the community aspect is critically important, and it's hand in hand with the importance of first party data and everything that I mean, we really are gravitating towards a world of first party marketing activation. The first party data that clients hold is unbelievably potent, and there in lies your your the secrets of success to creating a highly engaged community. And, yes, we are taking a leadership role now in producing long and short form content. When it comes to making sure that it's laser focus to that particular Koval group, it has to be hyper relevant on DH. Absolutely, to your point, some of the community members want to create that content themselves. So we also play a part in whether it's the finer points of influence of marketing, making sure that we're helping thes stakeholders create the right content and then helping them distributed effectively and efficiently >> and then scoring users and reputation Relevant Reputation >> comes yes, because they become I mean, key influences in B to C and beater B to B are so important is when it as it pertains to the viral ity of the communication. So they're almost like channels, you know, the influences are almost like channels in off themselves, and they can actually, you know, put the communication on steroids if they are effective at there >> for the news. I think I get what you're saying. That the new formula is a collection of niches is the new reach number. It's a rather nice blast to the reaches. It's a collection of niches that are programmable, inexpressible >> absolutely. It's almost like the collection of cohort groups together gives you that mass communication. >> I'm curious kind of the take on softer some of the softer types of communications that content around, you know, mission. And we heard you know, sati and the keynote earlier today. Talking about mission and a lot of people are are really not so much concerned, but they care. They care about what the mission of the company is in some of these kind of social and, you know, not necessarily direct attributes of the product or direct benefits of using the product, but more of a private company, not necessarily product that they sell. How do you see that evolving in kind of the marketers tool kit and kind of the rising importance of that type of of engagement with community? >> Yeah, when we told took Teo client CM o's and CDO. Specifically, we talk about purpose as well as the product differentiation. I think in today's world, you have to have both on by purpose. You don't necessarily have to have a lofty purpose because not everyone can look at a lot of CPG clients. They can't have a lofty purpose, but they can be purposeful. They could be hyper relevant in your life, and that's what we try and attain and achieve. So I think it's very, very important reading a lot of work at the moment, with clients almost stepping back and saying, Well, what business are you actually in? What is your raison Detrol? What is your purpose in life and how do we amplify that then through all forms of communication? Because then once you've got that sussed. You really do have the the critical ingredients off designing, creating the best experiences on the planet and activating them. >> Transparency becomes a big part of the user trust equation as well as a user experience and relevance. Because of your transparent, they want to see the day that this becomes a whole new dynamic. >> Transparency is critical because anyone can find out anything in two minutes, you know, on the interweb. So you know, you have to. Transparency is not trust. Transparency is not >> enough. All right, so I gotta ask you about the conflict between innovation and regulation and market. A name is because we've seen innovation always run hard and fast, and then regulation tries to catch up and kind of fit in first party date. It's super important as this new shift digital was happening where it's kind of moving from the old, you know, email blast to the old communications static channels to more dynamic, You starting to see the rise of distribution platforms like Facebook, LinkedIn, Twitter, among other zillion other third party AP. I driven platform. They're all having third party data. So how do you How does the customer your customer brands balance The need for first party information that they have and or are now putting their content out in these channels is a huge thing because not everyone has opened data. So how do you guys review that trend? And how early is it? What needs to be done? Is it okay? >> Yeah. I mean, first and foremost, the clients that do have very rich first party data, particularly financial clients, telco clients, etcetera. We really helped them amplify that first party data to help them activate with clients that don't necessarily have rich first parties ater like a lot of CPG clients, we help them build that first party data. And that's also sometimes where the purpose comes in on the community building comes in because when you get those two things, you know when you hone those two things, you can actually start to build a community, and then you can start to build Richard first party data so that we can help clients activate off of that third party data. We're getting a little bit more forensic with regards to whether or not that third party data is truly additive. And sometimes it's the smaller third party verticals specific to travel, etcetera, farmer, et cetera, et cetera. Where the third party data is actually most potent. So it's important. Teo. Almost look att depth more than bread when it comes to you >> and blending the data together. >> Exactly. But it has to be additive because there are some third party data sources which aren't truly additive toe activation. Therefore, we can discard them. >> Nikki. Great content. You're amazing. Insights are broad and great. Really relevant. Thank you for sharing data here on the Q. Appreciate it. >> Thanks for having me. It's been fun. >> Live coverage here, too, Joe be summat. Twenty nineteen. I'm Jeffery, Jeff Frick, Dave Tune from or day to coverage after this short break.