>> Narrator: From theCUBE studios in Palo Alto in Boston, it's theCUBE, covering IBM Think. Brought to you by IBM. >> Hi everybody, welcome back. This is Dave Vellante, and you're watching theCUBE's coverage of IBM Think 2020, the digital version of IBM Think and theCUBE is pleased to be providing the wall-to-wall coverage as we have physically for so many years at big IBM events. Jesus Mantas is here, he's the managing partner for Global Strategy for IBM and the Global Business Services. Jesus, great to see you, thanks for coming on. >> Great to be here, Dave. >> So, every guest that we've talked to this week, really, we've talked about COVID but just briefly. Here, we're going to do a bigger drill down and really try to get, Jesus your perspectives as an IBM's point of view on what's going on here. So let me start with, we've never seen anything like this before, obviously. I mean, there are some examples you got to go back to 1918, try to get some similarities, but 1918 is a long long time ago, so, what's different about this? What are the similarities? >> Yeah, it's, you know what Mark Twain used to say that history doesn't repeat, but it often rhymes. I think there are similarities of what we are experiencing right now in this pandemic with other pandemics like Spanish flu. I think the situation is unique in terms of the impact, and the synchronicity of that impact, right? So we can go back, whether if you want, economic crisis, or our society crisis, where you have either one country or one aspect being disrupted. But this is really society being interrupted, on a global scale. So its impact is unprecedented in that perspective in modern time, and I think all of us are adjusting to it. >> I want to ask you about digital transformation, because I've made the point that, while a lot of people talk digital transformation, there's been a lot of complacency, people say, not my lifetime, we're a bank, we're making a lot of money, we're doing okay. How do you think COVID-19 will sort of change that complacency and really accelerate digital transformation as a mindset and actually turn it into action? >> Yeah, I think the best way to put it is digital transformation five months ago was about obtaining competitive advantage and digital transformation today in many industries is about survival. That is how big of a change it is. The need for efficiency and cost savings, the need for resiliency that we have talked about, the need to be able to drive agility, to be able to switch and adapt, the need to make hyper local decisions, right, to use data, none of that can be done unless you have fully digitized processes, you are consuming local data and you have trained the people to really operate in those new, more intelligent processes. So, it has gone from optionality is okay, you can do okay but if you digitize you're going to do better to unless you digitize your business may not exist next year. I think that's the change, the change is, I think now is widely understood that the majority of our digitization processes have to be accelerated, and I would say there is a great statistic that when we go back in history, and there has been many, as I mentioned, of this crisis. You can look back at the two behaviors that businesses have, one is, to play defense and then what happens two years later, and the other one is, okay, you defense but you immediately switch to offense and then what happens two year later. Those companies that use this time to just defend and hunker down, history said in a couple of years later, 21% of them outperform. But those businesses that they shift from defense to offense and actually accelerate in these cases, programs like digitalization, 37% outperform. So, there is a premium for businesses that right now actually immediately switch to offense, focus on this set of digitalization and empowering cloud, managing data, ensuring the skills of the people, they're more likely not only to survive, but thrive in the next few years than those that just use this time to defend. >> To your point, it's about survival, it's not about, not getting disrupted, 'cause you're going to get disrupted, it's almost a certainty, and so in order to survive, you've got to digitally transform. Your final thoughts on digital transformation, then I want to ask you if there's a silver lining in all this. >> I think, what we do, we can't change the context. But we cannot let the context define who we are either as individuals or as company. What we can do, is to choose how do we act on that context. I would say, those organizations and those individuals that take advantage of the situation to understand that some of these behaviors are going to change, understand that the more that we shift technology to the cloud, the more that we shift work close to the cloud, the more that we use technologies like artificial intelligence and drive nonlinear decisions that massively optimize everything we do from the way that we deliver health care, to the way that we manage supply chains, to the way that we secure food, frankly, to the way that we protect the environment, there is a silver lining that technology it is one of those solutions that can help in all of these areas, and the silver lining of this is, hopefully, let's use this time to get better prepared for the next pandemia, to get better prepared for the next crisis, to implement technologies that drive efficiency faster, that create new jobs, that protect the environment, and while we cannot change the fact that we have COVID-19, we can change what happens after COVID-19, so what we return to is something better that what we enter before COVID-19. >> Very thoughtful commentary, Jesus. Thank you so much for coming on theCUBE, blessings to your family and yourself. >> Appreciated Dave, thank you, and thank you for everything you do to keep everybody informed. >> Really a pleasure. And thank you for watching everybody. This is Dave Vellante. You're watching theCUBE's coverage of IBM Think 2020 the digital event, to be right back right after the short break. (upbeat music)

>>Yeah, >>from The Cube Studios in Palo Alto and Boston. It's the Cube covering IBM. Think brought to you by IBM. >>Everybody welcome back. This is Dave Vellante, and you're watching the Cube's coverage of IBM. Think 2020 the digital version of IBM, thinking the Cube is pleased to be providing the wall to wall coverage, as we have physically. You know, so many years at big IBM events Spaces. Man test is here. He's the managing partner for global strategy for IBM and the Global Business Services. Jesus, great to see you. Thanks for coming on. >>Great to be here, Dave. >>So every guest that we've talked to this week really? We've talked about Cove it, but just briefly Ah, here. We're going to do a big drill down and really try to get Jesus, your perspectives and IBMs Point of view on what's going on here. So let me start with We've never seen anything like this before, Obviously. I mean, there are some examples going back to 1918. Try to get some similarities. But in 1918 was a long, long time ago. So So what's different about this? What are the similarities? >>Yeah, it's Ah, >>you know what Mark Point used to say? That history doesn't repeat, but it often rights, I think that are similar interests off what we're experiencing right now in this pandemic with Father from that makes like Spanish blue. I think the situation is unique in terms off the I'm the synchronicity of that impact. Right? So we can go back while they're everyone economic crisis or our society crisis where you have either one country of one aspect being disrupted. But this is really a society being disrupted, you know, on a global scale. So it impact is unprecedented in that in that perspective, in more than time. And I think all of us are adjusting to it. We upgrade 170 countries, so we've been able to see if you want every element of the curve off this convenient right? So from from getting back to a new normal, that is happening already in China and some of the countries in Asia Pacific to being just kind of like coming over the peat in Europe, North America, to some of the emerging countries where they're coming up. So so it gives the thing, gives us up what business continuity means and the importance of being prepared for this. I think it gives us a perspective on the health aspect of it as well as the economic impact. And most importantly, we've been very focused on aside the end. I don't have a lot of clients is figuring out what are they going to return back to when we say we want to return to work? I think is, what are we returning to? What are going to be the permanent changes? Where's the adaptation that is gonna be systemic and permanent? >>I want to ask you about digital transformation because I've made the point that, you know, while a lot of people talk digital transformation, there's been a lot of complacency. >>Digital transformation five months ago was about obtaining our competitive advantage on digital transformation. Today, in many industries, it's about survival, That is, that is how big of a change it is, the the need for efficiency and cost savings. We need local resiliency that we have talked about. They need to be able to drive agility, to be able to switch and about. They need to make hyper local decisions right to use data none of that can be done unless you have fully digitize processes. You are consuming local data and you have to train the people to really, um, operate in those new, more intelligent processes. So it has gone from Optionality is okay. You can do okay, But if you digitize your going to do better to, unless you digitize >>your business may not access next year. >>I've been just change the changes. I think now is widely understood that the majority of our digital digitization processes have to be accelerated. And I would say that is ah, great statistic that when we go back in history, Andi has been many. As I mentioned off this crisis, you can look back. The two >>behaviors that businesses have one is to play defense funding. What happens two years later on the other one is okay, you defense. But you immediately switched to offense and then what happens? Uh, two years later, those companies that use this time to just defend and hunker down history said in a couple of years later, 21% of them out there, But those businesses that they shift from defense to offense and actually accelerate in this case is, um, uh, programs like digitalization. 37% outperform. So very sad screaming for businesses that right now actually immediately switched to offense. Focus on this set of digitalization and empowering cloud managing data, ensuring the skills of the people. They're more likely not only to survive but thrive in the next three years. That don't just use this time >>to your point. It's about survival. It's not about, you know, not getting disrupted because you're going to get disrupted. It's almost a certainty. And so, in order to survive, you've got to digitally transform your final thoughts on digital transformation that I want to ask you. If there's a silver lining and all this, >>I think what we do, we can't change the conference. Um, but we cannot let the conflicts define who we are. Either It's individuals for this company. Well, we can do is to choose How do we act on that? I would say, um, those organizations and those individuals that take advantage of inspiration to understand that some of these behaviors are going to change, understand that the more that we should technology to the cloud, the more that we should workloads to the cloud, the more that we use technologies like artificial intelligence on Dr Nonlinear decisions that massively optimize everything we do from the way that we deliver healthcare to the way that we have managed supply change to the way that we secure food, frankly, to the way that we protect the environment that is a silver lining, that technology. It is one of those solutions that help in all of these areas, and the silver lining of this is is hopefully, let's use this time to get better, prepare for the next academia to get better, prepare for the next crisis. To implement technologies that drive efficiency faster. They create new jobs, they protect the environment. And what we cannot change The fact that we have 19 we can change. What happens after the 19. So we return to is something better than what we enter before. >>Very thoughtful commentary. Jesus, Thank you so much for coming on the cube. A blessing steer to your family and yourself. >>Appreciate it, Dave. Thank you. And thank you for everything You do too Well. Kept everybody informed. >>Really? Our pleasure. And thank you for watching everybody. This is Dave Vellante. you're watching the Cube's coverage of IBM. Think 2020. The digital event Right back. Right after this. Short break. >>Yeah, yeah, yeah, yeah.

[Music] from the cube studios in Palo Alto in Boston it's the cube covering the IBM thing brought to you by IBM everybody welcome back this is Dave Volante and you're watching the cubes coverage of IBM think 2020 the digital version of IBM thinking the cube is pleased to be providing the wall-to-wall coverage as we have physically for you know so many years at big IBM events hey Zeus man Tess is here he's the managing partner and for global strategy for IBM and the global business services hey Zeus great to see you thanks for coming on great to be here Dave so every guest that we've talked to this week really we've talked about Co vid but just briefly here we're gonna do a bigger drill down and really try to get hay-zu's your perspectives and IBM's point of view on what's going on here so let me start with we've never seen anything like this before obviously I mean there are some examples you gotta go back to 1918 to try to get some similarities but the 1918 is a long long time ago so so what's different about this what are the similarities yeah it's you know what Mark point is to say that history doesn't repeat but it often rhymes I think there are similarities of what we are experiencing right now in this pandemic with other than that makes like Spanish blue I think the situation is unique in terms of the image and the synchronicity of that impact right so we can go back whether you want economic crisis or our society crisis where you have either one country or one aspect being disruptive but this is really a society being disrupted you know at a global scale so its impact is unprecedented in that in that perspective in in more than time and I think all of us are adjusting to it we operate the hundred seventy countries so we've been able to see if you want every element of the curve of this convenient right so from from getting back to a new normal that is happening already in China and some of the countries in Asia Pacific to being just kind of like coming over the peak in Europe North America to some of the emerging countries where there coming up so to give back but I think gives us a good business continuity means and the importance of being prepared for this I think it gives us a perspective on the the health aspect of it as well as the economic impact and most importantly what we've been very focused as as IBM and on behalf of our clients is figuring out what are they going to return back to when we say we want to return to work I think there's what are we returning to what are gonna be the permanent changes where is the adaptation that is gonna be systemic and permanent I want to ask you about digital transformation because I've made the point that you know while a lot of people talk digital transformation there's been a lot of complacency digital transformation five months ago was about obtaining a competitive advantage and digital transformation today in many industries it's about survival that is that is how big of a change it is the the need for efficiency and cost savings they need for resiliency that we have talked about they need to be able to to drive agility to be able to switch Anna back they need to make hyperlocal decisions right to use data none of that can be done unless you have fully digitized processes you are consuming local data and you have trained the people to really operate in those new more intelligent processes so it has gone from optionality is ok you can do ok but if you digitize you're gonna do better too unless you digitize your business may not exist next year I think that's the change the changes I think now is widely understood that the majority of our digitized digitization processes have to be accelerated and I would say there is a great statistic that when we go back in history and there has been many as I mentioned of these crisis you can look back at the two behaviors that businesses have one is to play defense and then what happens two years later and the other one is okay you defense but you immediately switch to office and then what happens two year later those companies that use this time to just defend and hunker down history said in a couple of years later 21% of them out there but those businesses that they shift from defense to offense and actually accelerate in these cases are programs like digitalization 37% outperform so very supreme IAM for businesses that right now actually immediately switch to offense focus on this set of digitalization and empowering cloud managing data ensuring the skills of the people they're more likely not only to survive but thrive in the next few years that those that just used this tactic to your point it's about survival it's not about you know not getting disrupted because you're going to get disrupted it's almost a certainty and so in order to survive you've got a digitally transform your your final thoughts on digital transformation then I want to ask if there's a silver lining in all this I think what we do we can't change the context um but we cannot let the context define who we are either as individuals or as company what we can do is to choose how do we act on that content I would say those organizations and those individuals that take advantage of the situation to understand that some of these behaviors are going to check on this form that the more that we should technology to the cloud the more that we should work close to the cloud the more that we use technologies like artificial intelligence and drive nonlinear decisions that massively optimize everything we do from the way that we deliver health care to the way that we manage supply chains to the way that we secure food frankly to the way that we protect the environment there is a silver lining that technology it is one of those solutions that can't help in all of these areas and the silver lining of this is is hopefully let's use this time to get better prepare for the next bulimia to get better prepare for the next crisis to implement technologies the drive efficiency faster they create new jobs they protect the environment and while we cannot change the fact that we have only 19 we can change what happens after our puppy 19 so what we return to is something better that what we enter the very thoughtful commentary hey Zeus thank you so much for for coming on the cube a blessing steer to your family and yourself I appreciate it babe thank you and thank you for everything you do to keep everybody informed really our pleasure and thank you for watching everybody this is Dave a lotta you're watching the cubes coverage of IBM sync 20/20 the digital event we'll be right back right after short break [Music] you

>>Yeah, >>from The Cube Studios in Palo Alto and Boston. It's the Cube covering IBM. Think brought to you by IBM. >>Everybody welcome back. This is Dave Vellante, and you're watching the Cube's coverage of IBM. Think 2020 the digital version of IBM, thinking the Cube is pleased to be providing the wall to wall coverage, as we have physically. You know, so many years at big IBM events Spaces. Man test is here. He's the managing partner for global strategy for IBM and the Global Business Services. Jesus, great to see you. Thanks for coming on. >>Great to be here, Dave. >>So every guest that we've talked to this week really? We've talked about Cove it, but just briefly Ah, here. We're going to do a big drill down and really try to get Jesus, your perspectives and IBMs Point of view on what's going on here. So let me start with We've never seen anything like this before, Obviously. I mean, there are some examples going back to 1918. Try to get some similarities. But in 1918 was a long, long time ago. So So what's different about this? What are the similarities? >>Yeah, it's Ah, >>you know what Mark Point used to say? That history doesn't repeat, but it often rights, I think that are similar interests off what we're experiencing right now >>in this pandemic with father from that makes like Spanish blue. I think the situation is unique in terms off the I'm the synchronicity of that impact. Right? So we can go back while they're everyone economic crisis or our society crisis >>where you have either one country of one aspect being disrupted. But this is really a society being disrupted, you know, on a global scale. So it impact is unprecedented in that in that perspective, in more than time. And I think all of us are adjusting to it. Um, one of the points of view. Um, we've been able to if you want curate this. IBM is we upgrade 170 countries, so we've been able to see if you want every element of the curve off these convenient, right? So from from getting back to a new normal, that is happening already in China and some of the countries in Asia Pacific to being just kind of like coming over the peat in Europe, North America to some of the emerging countries where they're coming up. So so it gives thing gives us up what business continuity means and the importance of being prepared for this. I think it gives us a perspective on the health aspect of it as well as the economic impact. And most importantly, we've been very focused. Nous ous IBM. I don't have a lot of clients is figuring out What are they going to return back to when we say we want to return to work? I think is, what are we returning to? What are going to be the permanent changes? Where's the adaptation that is gonna be systemic and permanent? I'm not going to be just like, you know, we're going to get through this way. >>Whenever we had a CIO tell us that they weren't ready from a business resiliency business continuity standpoint, they said, we're we were all d are focused, very narrow. Uh, and wow, we really need to rethink that kind of another myth. Your thoughts on that? >>Correct. I think you go back the last three years. Business continuity in most of the decisions that binds would do, I would say I check on the box, right? So he was assumed that you needed to have a business. Continuity was heavily focused on disaster recovery that it was. He must evaluate it under the expectation that it decides there really happens that has now changed permanently, or at least for the foreseeable future, where business continuity is not a check on the box is actually a differentiating feature. And the differentiating feature comes from the fund that on now every one of our fines were prepared. Now every one of our competitors was prepared to the changes, the agility, the efficiency on if you want. The cloud ification of your business is the ability to provide the services in the face of a crisis that forces people to be socially distant, forces people to have to deliver from home. So that has actually become a much >>more important criterion buying decision. So So we, uh, fortunately, we have support very well in that we have 95% of IBM employees. I work from home in 99% of our global delivery centres on network is work from home. And we made that shit even before some of the country's declare that it was a stay at home or so. So that has Bean a feature that now our clients are appreciated. We've been able to to deliver those services so our clients could continue to deliver their services and going forward. I think that's gonna be a much more important if you want. A feature is how cloud ified is your delivery. How prepare are you? Not for just one crisis, but to make, probably subsequent crisis something normal, that one disrupt your operation? You just adapt. >>It's interesting. I had a conversation earlier with Ed Walsh, was one of your GM, said one of your hardware divisions. And and And he was explaining to me that, you know, across your 170 plus countries, you know, it was really the local supply chain. And he actually made the point detection really good quarter in Italy, which surprised me and he said, but they were sort of micro managing at the local level to your to your point. I want I want to ask you about digital transformation because I've made the point that, you know, while a lot of people talk digital transformation, there's been a lot of complacency because they're not in my lifetime where we're a bank. We're making a lot of money. We're doing okay. How do you think over 19 will sort of change that complacency and really accelerate digital transformation is a mindset and actually turn it into action? >>Yeah, I think the best way to put it is, um, digital transformation. Five months ago, it was about obtaining a competitive advantage on digital transformation. Today, in many industries, it's about survival. That is, that is how big of a change car it is. The the need for efficiency and cost savings, the need for resiliency that we have talked about. They need to be able to, um, to drive agility, to be able to switch and about. They need to make hyper local decisions right to use data that none of that can be done unless you have fully digitize processes. You are consuming local data and you have to train the people to really, um, operate in those new, more intelligent processes. So it has gone from Optionality is okay. You can do okay, but if you digitize, you're gonna do better to. Unless you digitize your business may not access next year. I think just change the changes. I think now is widely understood that the majority of our digital digitization processes have to be accelerated. And I would say that is, ah, great statistic that when we go back in history, Andi has been many. As I mentioned off this crisis, you can look back. The two behaviors >>that businesses have one is to play defense funding. What happens two years later on the other one is you defense. But you immediately switched to offense. And then what happens two years later? Those companies that use this time to just defend and hunker down history said in a couple of years later, 21% of them out there for But those businesses that they shift from defense to offense and actually accelerate in this case is, um uh, programs like digitalization. 37% of perform so very sad premium for businesses that right now actually immediately switched to offense. Focus on this set of digitalization and empowering cloud managing data, ensuring the skills of the people. They're more likely not only to survive but thrive in the next three years that don't just use this thanks >>to your point. It's about survival. It's not about, you know, not getting disrupted because you're going to get disrupted. It's almost a certainty. And so, in order to survive, you've got to digitally transform your final thoughts on digital transformation that I want to ask you if there's a silver lining and all this. >>No, I think I mean, um, I'd say the final thoughts is this a sigh said is, I don't think anybody anybody would say that government in and the Christ World crisis that that comes, is is anything that anybody would wish for or would help for. But we can change. I mean, that is the reality it is here. It's impact. It's devastation. Um, I think the human toll that comes from that many families that are being impacted for that, um, you know, I think my my my heart goes to roll those families, my own family. It's in the Spain, one of the worst countries in the world that is being impacted for this. Um so it's ah, it's clearly a tragedy. I think what we do we can't change the company. Um, but we cannot let the conflicts define who we are. Either it's individuals for this company. Well, we can do is to choose How do we act on that pump it? I would say, um, those organizations and those individuals that take advantage of inspiration to understand that some of these behaviors are going to change on this time, that the more that we should technology to the cloud, the more that we should Workloads to the cloud the more that we use technologies like artificial intelligence on Dr Nonlinear decisions that massively optimize everything we do from the way that we deliver healthcare. So the way that we manage supply change to the way that we secure food, frankly, to the way that we protect the environment that is a silver lining, that technology. It is one of those solutions that help in all of these areas, and the silver lining of this is is hopefully, let's use this time to get better, prepare for the next academia to get better, prepare for the next crisis, to implement technologies that drive efficiency faster, they create new jobs, they protect the environment and what we cannot change the fund that we have 19. We can change what happens after the 19 So we return to there's something better than what we enter before. >>Very thoughtful commentary. Jesus. Thank you so much for coming on the cube. A blessing Steer to your family and yourself. >>Appreciate it, Dave. Thank you. And thank you for everything. You do too well, Keep everybody informed. >>Really? Our pleasure. And thank you for watching everybody. This is Dave Volante. You're watching the Cube's coverage of IBM. Think 2020. The digital event. Right back. Right after this. Short break. >>Yeah, yeah, yeah.

>> Live from San Francisco, it's theCUBE. Covering IBM Think 2019. Brought to you by IBM. >> Welcome back to Moscone North, this is IBM Think 2019. You're watching theCUBE, I'm Stu Miniman, and we're going to dig into a segment talking about the cognitive enterprise. And helping me through that, I have one returning guest and one new guest to theCUBE, so furthest away from me, the returning guest is Jesus Mantas, who is the managing partner strategy for the digital platforms and innovation in the IBM Global business services. Jesus, welcome back. >> Thank you >> A little bit of a mouthful on the title. And Mani Dasgupta, CMO of the same group, the IBM Global business services. Thanks so much both for joining us. Alright, so cognitive enterprise. We're going to play a little game here first. Buzzword Bingo here, you know, can we talk about, what cognitive is, where you can't say AI, ML, platform, or enterprise in there. So do we start with the CMO first? >> Sure, I can go. Cognitive enterprise, those are two bing bing right there. What's your core competitive advantage, is what I would say. As a company, do you know why you exist? And once you get to that, how do you then take it to your clients, in a way that would help you grow, and sustain growth in the future. That truly is the future of a smart business, what we call the cognitive enterprise. >> So, Jesus, data is something we talk about a lot, at all the shows, we hear all the tropes about it's the new oil, the rocket fuel that are going to drive companies. You've got strategy and innovation in your title, I'd love you to build off as to where this cognitive enterprise fits in to those big trends of AI that we were talking about. Jinny was just on the keynote stage, talking about Watson, talking about all those pieces, so where does that fit with some of these megawaves that we're talking about. >> I think it's the way that we define this new, smarter organizations that use data to the fullest extent. And I think the way that we define it is, one is this reuse of data, your own data, the external data, and the way you aggregate it, the way that you apply AI or other things to use that. But the technology itself is a means to an end, it's not the end, so these organizations change the way the work flows, and they also train people to make sure that they understand how to operate in a world where they have more information and they can make better decisions with that data that they could before. All of that is what we are labeling. It's more than digital, it's more than AI. It is this concept of a cognitive enterprise. It's a smarter way to do what a company does. >> Okay, I'd love if you could give us a little bit of a compare, contrast. You know, the wave of big data was, there's massive amounts of data, we're going to allow the business practitioner, to be able to leverage that data. Was a great goal, unfortunately when we did research, at least half the time it wasn't really panning out there. Doesn't mean we didn't learn good things, and there weren't lots of great tools and business value generated out there. So, give us, you know, what's the same and what's different, as to this new wave. >> This is how do you make that data work for you, really. It is about, when you talk of data, you think of data that's out there, but 80% of the data today, is owned by you. And by you, I mean a business, right, you own your customers' data, you know your customer better than anybody else. So what do you really do with it? And we are at an inflection point right now, where these technologies that you just talked about, be it blockchain, be it internet of things, be it AI. You can truly bring the power of these technologies, to start making sense of that data that you own, and use it to create, what we call, your competitive advantage, your business platform. So, think about it, I can break it down. Would you just be a retailer of clothes? Or, would you be a fashion expert? And which one would have long-term success for you? Or if you think of a completely different industry, would you be an insurance provider, you sell insurance products, or would you be a risk management expert? That decision to be who you want to be, is really at the heart of the cognitive enterprise, and what we are proposing to the clients here. >> Alright, help frame for us your group, where that fits in. IBM sells hardware, software, has a huge services organization. What are the deliverables and the services and products involved in your group? >> Sure, we are the services organization of IBM, and one of the core reasons why we exist is to help our clients solve their toughest business problems. And so, if you think about it, you think about it as different puzzle pieces, but they don't quite always fit together. We exist to sharpen the edges, to sometimes round the edges, make it customized, make it right for you, so that at the end of the day, you're able to deliver results for your customers and be closer to them than ever before. >> The balance we look at in this multi-cloud world, it'd be nice if you have a little bit more standardization, but of course we know when we talk with businesses, every company is different and is challenging. So, where are the architectural engagements? What are the design criteria? Where is some of the hard work your group gets involved in? >> Yeah, I think we've been spending a lot of work and a lot of time on understanding how to get clients, most clients have done a lot of experimentation. But they rarely figured out how to get that experimentation into real production, at scale, with impact. So that's where we've spent a lot of the time. Fundamentally it has to do with, not only understanding Agile as a method, but being able to combine that with taking that journey all the way through to production, actually integrating with compliance requirements that, if you're in a regulated industry, you have to do, and do that in a way that doesn't become a digital island. I think what we have learned is, when companies see this big divide between, that's the legacy world and that's the new world you can never put those two together. So we came up with this concept of IBM Garage, which is the way in which our team, the services side, can actually bring it all together, and it gets massively enhanced and improved, with technology like containers, like Kubernetes, because now you can actually open up architectures, without reinventing them, and connect them with new technology, and do that synchronously. So you can basically be modernizing your legacy, you can be creating new innovation, in the form of new platforms, but you can do it at the same time, and as you do that through cycles, you also change the skillsets that you have in your company, because if you don't change that skillset, you're always going to have a problem scaling. That's what we do, that's what we help the clients do. >> Yeah, skillsets are so critical. Something we've been hearing over and over is, that whole digital transformation, this isn't some 18 to 24 month going to deploy some software, bring in a lot of consultants, they go and do it, hopefully it works and then they walk away. We're talking about much faster time frames, usually agile methodology, talk about skillset-changing. How do we help customers move fast and accelerate, because that's really the faster, faster, faster, it's just one of those driving things we hear. >> I was talking to one of the clients this morning, and what she said is, it's so helpful to have a framework, just to know where to start, and also to know, sometimes it's there in their mind, but they want to see it in front of them, how to break a problem down into smaller components, so that you can get to value faster, so we have actually a seven-step process, of the cognitive enterprise. So we start with, what is your core platform? In fact, Jesus coined this term, he calls it the digital Darwinism. Do you want to talk about the digital Darwinism, Jesus? >> Yeah, I think it reflects very well this urgency. In the analog world when most businesses are based on how clients choose you based on proximity, based on convenience, based on brand, based on trust, based on price. Even if you're not great at it, you have enough friction in an analog world, that the clients will keep coming. All of us and more of our things that we do every day, are in our phone, and they are digitally accessible, all of that friction disappears, and what happens then is, the people that are very good at something becomes, everybody goes to them, and the people that are not the best. I call it, they either thrive or they die very quickly. So in the digital world, being really good at something is a lot more important than in the analog world. You can survive being average in the analog world. Once you get to the digital world, it's transparent. Everyone will know, you're the best, you're not the best, and nobody would pick you if you're not the best, so it's really important to reconfigure yourself, and understand the trust and your brand, understand how digitally you translate what you are, and then make sure that your clients will keep choosing you in a digital world as much as they were choosing you in an analog world. >> I tell you, that resonates really well with me. The old line you used to hear is, if you want to get something done, give it to someone who's really busy, because they will usually figure out a way to do it. I spent a handful of years in my career doing operations, and what I did when I was in operations, when I talked to people in IT, is tell me next quarter and next year, do you think you're going to have more or less work more data to deal with, more thing thing, and of course the answer is, we all know that pace of change is the only thing that's constant in this industry. So, if I don't figure out how I automate, change, or get rid of the stuff that I'm not good at, we're just going to continue to be buried. Are there commonalities that you see, as success factors or how do you help measure, what are some key KPIs that customers walk out of, when they go through an engagement like this? >> Yeah, just carrying on from where Jesus left off, the second step is very close to what you were just saying. It's about the data and how you're using that data. So some of the key success factors would be, what is the output of it, and it's not in the proof of concept phase anymore. It is real-time, it is big, people are doing it at a grand scale. I think, Jesus, maybe we take it through the seven steps, and then the key success criteria comes right at you, right after that. So after you do the workflow, after you do the data for internal competitive advantage, we go to the next step, which is all about workflows. You want to talk a bit about that? >> Yeah, I think one of the advantages that artificial intelligence brings to companies is, the fact that you can now, I mean as a human, there is only so much data that you can ingest. There is a limit, and most businesses try to optimize what that is and how you make decisions. But, artificial intelligence becomes this aid that will read and summarize things for you. So now you can take into account, into workflows, massive amounts of information, to optimize, or even not having to do things you had to do before, at a scale that, as a human you cannot do. This idea of inserting AI into workflows is the real idea. I think we talk a lot about AI as a technology, but that's just a means to an end. The end is a workflow that is embedded with blockchain, with AI, with IOT, and then people that are trained to engage with those workflows, so you actually change the output. And I think that's the big idea, that step of, it is workflow that is embedded with AI, it's not just about the technology, it's the combination of the main industry, and the technology that actually creates that >> And where does it sit, right? Where does it sit? Your tech choices, the architecture choices are also important. And we joked about this, like if you really like Netflix, and you're watching something and something is coming up after three seconds, how does it know what you really like? But it does, but think about this. This wouldn't be possible on a 1950s television set. So you've got to think about what's your tech platform of choice, how do you upgrade that, and what's the architecture look like? >> I want to give you both the final word. Lots of users here at the show. What are you most excited about? Give us an insight on some of the conversations you've been having already. >> Amazing conversations so far. The really aha-moment was, people really like to share within their peer set, so this morning I was at the business exchange, and people were having conversations, but just to bounce it off someone, who is facing the same issues that you do, across different industries, was a really aha-moment, and we have the IBM Garage actually right behind us on the other side of Moscone. We set it up so that clients can come in, and unpack their problems, and we helped them think it through, used design thinking, help them think it through. We are hoping in the next couple of days, we get lots of brilliant ideas, come from the sessions like that, and really putting the customer at the core of what you want to do. >> It's a recurring theme of all the client conversations, this idea of, they all want the speed and agility of a startup at the strength and scale of an enterprise. That's what they're asking us, as the services organization of IBM, to do is, help us not just experiment, that was good before, not good enough now. Help us do that with agility, with new technologies, but we want it to mean something at scale, globally implement it, create an impact. And I think again, the way in which hybrid multi-cloud can play into that, the way in which IBM Garage can combine the legacy world with the new world and moving people into new platforms is a really exciting method and approach that is resonating a lot with clients. >> Really appreciate you both sharing updates and absolutely as you painted a picture, just as in 1950 we didn't have the tools to run Netflix, now in 2019, we have the tools for customers to be able to help build the cognitive enterprise and not only test but get into real-world deployment at a speed that was really unheralded before today. Thanks so much for joining. We'll be back with more coverage here from IBM Think 2019. I'm Stu Miniman, and thanks for watching theCUBE. (upbeat techno music)

(inspiring piano and string music) >> Announcer: Live from Fisherman's Wharf in San Francisco, it's theCUBE, covering IBM Chief Data Officer Strategy Summit Spring 2017. Brought to you by IBM. >> Hey, welcome back, everybody. Jeff Frick here with theCUBE. We're in downtown San Francisco at the IBM Chief Data Officer Strategy Summit Spring 2017. That's a mouthful, but it's important because there's a series of these strategy summits that are happening not only in the United States, but they're expanding it all over the world, and it's really a chance for practitioners to come together, the chief data officers, to share best practices, really learn from the best, and as we love to do on theCUBE, we get the smartest people we can find, and we have them here. So first off, let me introduce Peter Burris, Chief Research Officer from Wikibon, but from IBM coming right off the keynote-- >> The smart people. >> The smart people, Inderpal Bhandari, he is the IBM Global Chief Data Officer, which is a short title and a big job, and Jesus Mantas, he's the General Manager, Cognitive Transformation, IBM Global Business Services. First off, gentlemen, welcome. >> Thank you. >> Thank you. >> It's really interesting how this chief data officer space has evolved. We've been watching it for years, back to some of the MIT CDOIQ, I think like three or four years ago nobody knew who they were, who were they going to report to, what are they going to do, what's the scope of the job. That's changed dramatically, and it really says something to IBM's credit that they just went out and got one to help really to refine and define for your customers where this is going. So first off, welcome, and let's get into it. How is the role starting to solidify as to what do chief data officers do? >> So, I'll take that. In terms of chief data officers, if you think in terms of the advent of the position, when it started out, I was one of the earliest in 2006, and I've done the job four times, and it has been continuously evolving ever since. When the job was first, in my very first job, I actually had to create the job because there was a company very interested in recruiting me, and they said they sensed that data was critical. It was a company in pharmaceutical insurance, so really very data based, right, everything is driven through data. And so, they had a sense that data was going to be extremely important, extremely relevant, but they didn't really have the position, or they didn't coin the phrase. And I suggested that there were three other chief data officers at that time in the U.S., and so, I became the fourth. At that time, it had to do with, essentially aligning data with strategy, with the strategy of the company, which means how is the company actually planning to monetize itself? Not its data, but itself. And then, essentially make sure that the data is now fit for purpose, to help them with that monetization. And so, that's all about aligning with the corporate strategy, and you have to have an officer who's capable of doing that and has that focus and is able to push that because then, once you start with that strategy, and then, there are plenty of different branches that shoot off, like governance, centralization of data, analytics, data science, and so on and so forth, and then, you have to manage that process. >> And data used to be kind of a liability, hard to think today looking back, 'cause you had to buy servers and storage, and it was expensive, and what do you do with it all? You can't analyze it. Boy, how the world has flipped. Now, data is probably one of your most important assets, but then, the big question, right, what do you do with it to really make it an asset? >> It is, it is, and it's actually fascinating to see here in the summit how even the role that was created in a few years, chief data officer, is coupled with this change in the nature of the value of that role has changed. To your point, I remember meeting some CIO friends 10 years ago that they were telling me how they were deleting data because it was too costly to have it. Now, those same CIOs would give whatever they could have to get that data back and have that history and be able to monetize the data. Because of the evolution of computing, and because now, not only the portion of the physical world that we've been able to represent with data for the last 50 years with information technology, but we're adding to that space all of this 80% of the data that even if digitized we were unable to use in processes, in decision making, in manufacturing. Now we have cognitive technology that can actually use that data, the role of the chief data officer is actually expanding significantly from what used to be the element of data science, of data governance, of data sovereignty, of data security, to now this idea of value creation with basically five times more categories of data, and it actually is a dialogue that we're having here at the summit that is the fascinating from the people who are doing this job every day. >> If you think about the challenges associated with the chief data officer, it's a job that's evolving, but partly one of the reasons why the chief data officer job is evolving is the very concept of the role that data plays in business is evolving, and that's forcing every job in business to evolve. So, the CMO's job's evolving, the CEO's job's evolving, and the CIO's job is evolving. How are you navigating this interesting combination of forces on the role of the CDO as you stake out, this is the value I'm going to bring to the business, even as other jobs start to themselves change and respond to this concept of the value of data? >> People ask me to describe my job, and there are just two words that I use to describe it. It's change agent, and that's exactly how a CDO needs to be, needs to look at their job, and also, actually act on that. Because to your point, it's not just the CDO job is evolving, it's all these other jobs are all evolving simultaneously, and there are times when I'm sitting at the table, it appears that, well, you don't really own anything because everybody else owns all the processes in the business. On the other hand, sometimes you're sitting there, and you're thinking, no, you actually own everything because the data that feeds those processes or comes out of those process is not coming back to you. I think the best way to think about the CDO job is that of a change agent. You are essentially entrusted with creating value from the data, as Jesus said, and then, enabling all the other jobs to change, to take advantage of this. >> 'Cause it's the enablement that that's where you bring the multiplier effect, it's the democratization of the data across the organization, across business roles, across departments is where you're going to get this huge multiplier. >> Yeah, and I think the role of one of the things that we're seeing and the partnership that Inderpal and I have in the way that we do this within IBM, but also, we do it for the rest of our clients is that change agency element of it is the constant infusion of design. Chief data officers were very well-known for the data science elements of it, but part of the constraint is actually no longer the computing capability or the algorithms themselves or the access to the data, which solved those constraints, is now actually preparing the business leaders to consume that and to actually create value, which changes the nature of their job as well, and that's the resistance point where embedding these technologies in the workflows, in a way that they create value in the natural flow of what these jobs actually do is extremely important. Otherwise, I mean, we were having a fascinating discussion before this, even if the data is correct, many business leaders will say, "Well, I don't believe it." And then, if you don't adopt it, you don't get the value. >> You guys are putting together this wonderful community of CDOs, chief data officers, trying to diffuse what the job is, how you go about doing the job. If you're giving advice and counsel to a CEO or board of directors who are interested in trying to apply this role in their business, what should they be looking for? What type of person, what type of background, what type of skills? >> I'll take it, and then, you can. I think it's almost what I would call a new Da Vinci. >> Peter: A new Da Vinci? >> A new Da Vinci is the Renaissance of someone that is, he's got a technology background, because you need to actually understand the mathematical and the data and the technology co-engineering aspect. >> So, if not an IT background, at least a STEM background. >> Exactly, it's a STEM background, but combined with enough knowledge of business architecture. So I call it Da Vinci because if you see the most remarkable paintings and products of Da Vinci was the fusion of mathematics and arts in a way that hadn't been done before. I think the new role of a data science is someone that can be in the boardroom elegantly describing a very sophisticated problem in a very easy to understand manner, but still having the depth of really understanding what's behind it and drawing the line versus what's possible and what's likely to happen. >> I think that's right on. I think the biggest hurdle for a chief data officer is the culture change, and to do that, you actually have to be a Da Vinci, otherwise, you really can't pull that off. >> Peter: You have to be a Da Vinci? >> You have to be a Da Vinci to pull that off. It's not just, you have to appreciate not just the technology, but also the business architecture as well as the fact that people are used to working in certain ways which are now changing on them, and then, there is an aspect of anxiety that goes with it, so you have to be able to understand that, and actually, perhaps even harness that to your advantage as you move forward as opposed to letting that become some kind of a threat or counterproductive mechanism as you move forward. >> I've done a fair amount of research over the years on the relationship between business model, business model design profitability, and this is, there's a lot of different ways of attacking this problem, I'm not going to tell you I have the right answer yet, but one of the things that I discovered when talking to businesses about this is that often it fails when the business fails to, I'm going to use the word secure, but it may not be the right word, secure the ongoing rents or value streams from the intellectual property that they create as part of the strategy. Companies with great business model design also find ways to appropriate that value from what they're doing over an extended period of time, and in digital business, increasingly that's data. That raises this interesting question, what is the relationship between data, value streams over time, ownership, intellectual property? Do you have any insight into that? It's a big question. >> Yeah, no no, I mean, I think we touched on it also in the discussion, both Jesus and I touched on that. We've staked out a very clear ground on that, and when I say we, I mean IBM, the way we are defining that is we are pretty clear that for all the reasons you just outlined, the client's data has to be their data. >> Peter: Has to be? >> Has to be their data. It has to be their insight because otherwise, you run into this notion of, well, whose intellectual property is it, whose expertise is it? Because these systems learn as they go. And so, we're architecting towards offerings that are very clear on that, that we're going to make it possible for a client that, for instance, just wants to keep their data and derive whatever insight they can from that data and not let anybody else derive that insight, and it'll be possible for them to do that. As well as clients where they're actually comfortable setting up a community, and perhaps within an industry-specific setup, they will allow insights that are then shared across that. We think that's extremely important to be really clear about that up front and to be able to architect to support that, in a way that that is going to be welcomed by the business. >> Is that part of the CDO's remit within business to work with legal and work with others to ensure that the rules and mechanisms to sustain management of intellectual property and retain rents out of intellectual property, some call it the monetization process, are in place, are enforced, are sustained? >> That's always been part of the CDO remit, right. I mean, in the sense that even before cognition that was always part of it, that if we were bringing in data or if data was leaving the company that we wanted to make sure that it was being done in the right way. And so, that partnership not just with legal but also with IT, also with the business areas, that we had to put in place, and that's the essence of governance. In the broadest sense, you could think of governance as doing that, as protecting the data asset that the company has. >> They have the derivatives now, though. You're getting stacked derivatives. >> Inderpal: It's much more complicated. >> Of data, and then insight combined, so it's not just that core baseline data anymore. >> And I like to make it an element. You've heard us say for the last five years we believe that data has become the new natural resource for the business. And when you go back to other natural resources, and you see what happened with people that were in charge of them, you can kind of predict a little bit that evolution on the chief data officer role. If you were a landowner in Texas when there was no ability to basically either extract or decline petroleum, you were not preoccupied with how would you protect land rights under the line that you can see. So, as a landowner you have a job, but you were basically focused on what's over the surface. Once actually was known that below the surface there was massive amount of value that could be obtained, suddenly that land ownership expanded in responsibility. You then have to be preoccupied, "Okay, wait a minute, who owns those land rights "to actually get that oil, and who's going to do that?" I think you can project that to the role of the chief data officer. If you don't have a business model that monetizes data, you are not preoccupied to actually figure out how to govern it or how to monetize it or how to put royalties on it, you are just preoccupied with just making sure that the data you have, it was well-maintained and it could be usable. The role's massively expanding to this whole below the line where not only the data is being used for internal purposes, but it's becoming a potential element of a strategy that is new. >> The value proposition, simply stated. >> Jesus: Value proposition, exactly. >> But you're right, so I agree with that, but data as an asset has different characteristics than oil as an asset, or people as an asset. People can effectively be applied to one thing at a time. I mean, we can multitask, but right now, you're having a conversation with us, and so, IBM is not seeing you talk to customers here at the show, for example. Data does not follow the economics of scarcity. >> Jesus: Right. >> It follows a new economics, it's easy to copy, it's easy to share. If it's done right, it's easy to integrate. You can do an enormous number of things with data that you've never been able to do with any other asset ever, and that's one of the reasons why this digital transformation is so interesting and challenging, and fraught with risk, but also potentially rewarding. So, as you think about the CDO role and being the executive in the business that is looking at taking care of an asset, but a special type of asset, how that does change the idea of taking care of the energy or the oil to now doing it a little bit differently because it can be shared, because it can be combined. >> I mean, I think in the way as technology has moved from being a mechanism to provide efficiency to the business to actually being core to defining what the business is, I think every role related to technology is following that theme, so I would say, for example, Inderpal and I, when we're working with clients or on our models, he's not just focused on the data, he's actually forming what is possible for the business to do. What should be the components of the new business architecture? It's this homogenized role, and that's why I kept saying it's like, you could have been one of those Da Vincis. I mean, you get to do it every day, but I don't know if you want to comment on that. >> I think that's exactly right. You are right in the sense that it is a different kind of asset, it has certain characteristics which are different from what you'd find in, say, land or oil or something like a natural resource, but in terms of, and you can create a lot of value at times by holding onto it, or you could create a lot of value by sharing it, and we've seen examples of both metaphors. I think as part of being the CDO, it's being cognizant that there is going to be a lot of change in this role as data is changing, not just in its nature in the sense that now you have a lot more unstructured data, many different forms of data, but also in terms of that's application within the business, and this expansion to changing processes and transforming processes, which was never the case when I first did the job in 2006. It was not about process transformation. It was about a much more classic view of an asset where it's, we create this data warehouse, that becomes the corporate asset, and now, you generate some insights from it, disseminate the insights. Now it's all about actually transforming the business by changing the processes, reimagining what they could be, because the nature of data has changed. >> I have one quick question. >> Last one. >> Very quickly, well, maybe it's not a quick question, so if you could just give me a quick answer. A couple times you both have mentioned the relationship between the CDO and business architecture. Currently, there's a relationship between the CIO and IT architecture, even the CIO and data architecture at a technical level. At IBM, do you actually have staff that does business architecture work? Is there someone, is that a formal, defined set of resources that you have, or should CDOs have access to a group of people who do business architecture? What do you think? >> We've traditionally had business architects at IBM, I think for a long time, that predates me. But again, as Jesus said, their role is also evolving. As it becomes much more about process transformation, it's different than it was before. I mean, this is much more now about a collaborative effort where you essentially sit down in a squad in an agile setting, and you're working together to redesign and reinvent the process that's there. And then, there's business value. It's less about creating large monolithic architectures that span an entire enterprise. It's all about being agile, data-driven, and reacting to the changes that are happening. >> So, turning strategy into action. >> Yes. >> And I think, again, in IBM, one of the things that we have done, our CIO, that is the organization that actually is the custodian of this cognitive enterprise architecture of which Inderpal actually is part of. So, we are actually putting it all together. It used to be an organization. Most COOs have evolved from running operations to defining shared services to now have to figure out what is the digital services version of the enterprise they need to implement, and they can't do that without a CDO in place, they just can't. >> Alright, gentlemen. Unfortunately, we'll have to leave it there. For viewers at home, tune into season two with Inderpal and Jesus. Really a great topic. Congratulations on the event, and we look to forward to the next time. >> Thank you. >> Thank you very much. >> Absolutely. With Peter Burris, I'm Jeff Frick. You're watching theCUBE from the IBM Chief Data Officer Strategy Summit Spring 2017. Be right back with more after this short break. Thanks for watching. (electronic keyboard music)

>>Prior to the pandemic, organizations were largely optimized for efficiency as the best path to bottom line profits. Many CIOs tell the cube privately that they were caught off guard by the degree to which their businesses required greater resiliency beyond their somewhat cumbersome disaster recovery processes. And the lack of that business resilience has actually cost firms because they were unable to respond to changing market forces. And certainly we've seen this dynamic with supply chain challenges and there's a little doubt. We're also seeing it in the area of cybersecurity generally, and data recovery. Specifically. Over the past 30 plus months, the rapid adoption of cloud to support remote workers and build in business resilience had the unintended consequences of expanding attack vectors, which brought an escalation of risk from cybercrime. Well, security in the public clouds is certainly world class. The result of multi-cloud has brought with it multiple shared responsibility models, multiple ways of implementing security policies across clouds and on-prem. >>And at the end of the day, more, not less complexity, but there's a positive side to this story. The good news is that public policy industry collaboration and technology innovation is moving fast to accelerate data protection and cybersecurity strategies with a focus on modernizing infrastructure, securing the digital supply chain, and very importantly, simplifying the integration of data protection and cybersecurity. Today there's heightened awareness that the world of data protection is not only an adjacency to, but it's becoming a fundamental component of cybersecurity strategies. In particular, in order to build more resilience into a business, data protection, people, technologies, and processes must be more tightly coordinated with security operations. Hello and welcome to the future of Multi-Cloud Data Protection Made Possible by Dell in collaboration with the Cube. My name is Dave Ante and I'll be your host today. In this segment, we welcome into the cube, two senior executives from Dell who will share details on new technology announcements that directly address these challenges. >>Jeff Boudreau is the president and general manager of Dell's Infrastructure Solutions Group, isg, and he's gonna share his perspectives on the market and the challenges he's hearing from customers. And we're gonna ask Jeff to double click on the messages that Dell is putting into the marketplace and give us his detailed point of view on what it means for customers. Now, Jeff is gonna be joined by Travis Vhi. Travis is the senior Vice President of product management for ISG at Dell Technologies, and he's gonna give us details on the products that are being announced today and go into the hard news. Now, we're also gonna challenge our guests to explain why Dell's approach is unique and different in the marketplace. Thanks for being with us. Let's get right into it. We're here with Jeff Padre and Travis Behill. We're gonna dig into the details about Dell's big data protection announcement. Guys, good to see you. Thanks >>For coming in. Good to see you. Thank you for having us. >>You're very welcome. Right. Let's start off, Jeff, with the high level, you know, I'd like to talk about the customer, what challenges they're facing. You're talking to customers all the time, What are they telling you? >>Sure. As you know, we do, we spend a lot of time with our customers, specifically listening, learning, understanding their use cases, their pain points within their specific environments. They tell us a lot. Notice no surprise to any of us, that data is a key theme that they talk about. It's one of their most important, important assets. They need to extract more value from that data to fuel their business models, their innovation engines, their competitive edge. So they need to make sure that that data is accessible, it's secure in its recoverable, especially in today's world with the increased cyber attacks. >>Okay. So maybe we could get into some of those, those challenges. I mean, when, when you talk about things like data sprawl, what do you mean by that? What should people know? Sure. >>So for those big three themes, I'd say, you know, you have data sprawl, which is the big one, which is all about the massive amounts of data. It's the growth of that data, which is growing at an unprecedented rates. It's the gravity of that data and the reality of the multi-cloud sprawl. So stuff is just everywhere, right? Which increases that service a tax base for cyber criminals. >>And by gravity you mean the data's there and people don't wanna move it. >>It's everywhere, right? And so when it lands someplace, I think edge, core or cloud, it's there and that's, it's something we have to help our customers with. >>Okay, so just it's nuanced cuz complexity has other layers. What are those >>Layers? Sure. When we talk to our customers, they tell us complexity is one of their big themes. And specifically it's around data complexity. We talked about that growth and gravity of the data. We talk about multi-cloud complexity and we talk about multi-cloud sprawl. So multiple vendors, multiple contracts, multiple tool chains, and none of those work together in this, you know, multi-cloud world. Then that drives their security complexity. So we talk about that increased attack surface, but this really drives a lot of operational complexity for their teams. Think about we're lack consistency through everything. So people, process, tools, all that stuff, which is really wasting time and money for our customers. >>So how does that affect the cyber strategies and the, I mean, I've often said the ciso now they have this shared responsibility model, they have to do that across multiple clouds. Every cloud has its own security policies and, and frameworks and syntax. So maybe you could double click on your perspective on that. >>Sure. I'd say the big, you know, the big challenge customers have seen, it's really inadequate cyber resiliency. And specifically they're feeling, feeling very exposed. And today as the world with cyber tax being more and more sophisticated, if something goes wrong, it is a real challenge for them to get back up and running quickly. And that's why this is such a, a big topic for CEOs and businesses around the world. >>You know, it's funny, I said this in my open, I, I think that prior to the pandemic businesses were optimized for efficiency and now they're like, wow, we have to actually put some headroom into the system to be more resilient. You know, I you hearing >>That? Yeah, we absolutely are. I mean, the customers really, they're asking us for help, right? It's one of the big things we're learning and hearing from them. And it's really about three things, one's about simplifying it, two, it is really helping them to extract more value from their data. And then the third big, big piece is ensuring their data is protected and recoverable regardless of where it is going back to that data gravity and that very, you know, the multi-cloud world just recently, I don't know if you've seen it, but the global data protected, excuse me, the global data protection index gdp. >>I, Yes. Jesus. Not to be confused with gdpr, >>Actually that was released today and confirms everything we just talked about around customer challenges, but also it highlights an importance of having a very cyber, a robust cyber resilient data protection strategy. >>Yeah, I haven't seen the latest, but I, I want to dig into it. I think this, you've done this many, many years in a row. I like to look at the, the, the time series and see how things have changed. All right. At, at a high level, Jeff, can you kind of address why Dell and from your point of view is best suited? >>Sure. So we believe there's a better way or a better approach on how to handle this. We think Dell is uniquely positioned to help our customers as a one stop shop, if you will, for that cyber resilient multi-cloud data protection solution and needs. We take a modern, a simple and resilient approach. >>What does that mean? What, what do you mean by modern? >>Sure. So modern, we talk about our software defined architecture, right? It's really designed to meet the needs not only of today, but really into the future. And we protect data across any cloud and any workload. So we have a proven track record doing this today. We have more than 1700 customers that trust us to protect them more than 14 exabytes of their data in the cloud today. >>Okay, so you said modern, simple and resilient. What, what do you mean by simple? Sure. >>We wanna provide simplicity everywhere, going back to helping with the complexity challenge, and that's from deployment to consumption to management and support. So our offers will deploy in minutes. They are easy to operate and use, and we support flexible consumption models for whatever customer may desire. So traditional subscription or as a service. >>And when you, when you talk about resilient, I mean, I, I put forth that premise, but it's hard because people say, Well, that's gonna gonna cost us more. Well, it may, but you're gonna also reduce your, your risk. So what's your point of view on resilience? >>Yeah, I think it's, it's something all customers need. So we're gonna be providing a comprehensive and resilient portfolio of cyber solutions that are secured by design. We have some ver some unique capabilities and a combination of things like built in amenability, physical and logical isolation. We have intelligence built in with AI par recovery. And just one, I guess fun fact for everybody is we have our cyber vault is the only solution in the industry that is endorsed by Sheltered Harbor that meets all the needs of the financial sector. >>So it's interesting when you think about the, the NIST framework for cybersecurity, it's all about about layers. You're sort of bringing that now to, to data protection, correct? Yeah. All right. In a minute we're gonna come back with Travis and dig into the news. We're gonna take a short break. Keep it right there. Okay. We're back with Jeff and Travis Vhi to dig deeper into the news. Guys, again, good to see you. Travis, if you could, maybe you, before we get into the news, can you set the business context for us? What's going on out there? >>Yeah, thanks for that question, Dave. To set a little bit of the context, when you look at the data protection market, Dell has been a leader in providing solutions to customers for going on nearly two decades now. We have tens of thousands of people using our appliances. We have multiple thousands of people using our latest modern simple power protect data managers software. And as Jeff mentioned, we have, you know, 1700 customers protecting 14 exabytes of data in the public clouds today. And that foundation gives us a unique vantage point. We talked to a lot of customers and they're really telling us three things. They want simple solutions, they want us to help them modernize and they want us to add as the highest priority, maintain that high degree of resiliency that they expect from our data protection solutions. So tho that's the backdrop to the news today. And, and as we go through the news, I think you'll, you'll agree that each of these announcements deliver on those pillars. And in particular today we're announcing the Power Protect data manager appliance. We are announcing power protect cyber recovery enhancements, and we are announcing enhancements to our Apex data storage >>Services. Okay, so three pieces. Let's, let's dig to that. It's interesting appliance, everybody wants software, but then you talk to customers and they're like, Well, we actually want appliances because we just wanna put it in and it works, right? It performs great. So, so what do we need to know about the appliance? What's the news there? Well, >>You know, part of the reason I gave you some of those stats to begin with is that we have this strong foundation of, of experience, but also intellectual property components that we've taken that have been battle tested in the market. And we've put them together in a new simple integrated appliance that really combines the best of the target appliance capabilities we have with that modern simple software. And we've integrated it from the, you know, sort of taking all of those pieces, putting them together in a simple, easy to use and easy to scale interface for customers. >>So the premise that I've been putting forth for, you know, months now, probably well, well over a year, is that, that that data protection is becoming an extension of your, your cybersecurity strategies. So I'm interested in your perspective on cyber recovery, you specific news that you have there. >>Yeah, you know, we, we are, in addition to simplifying things via the, the appliance, we are providing solutions for customers no matter where they're deploying. And cyber recovery, especially when it comes to cloud deployments, is an increasing area of interest and deployment that we see with our customers. So what we're announcing today is that we're expanding our cyber recovery services to be available in Google Cloud with this announcement. It means we're available in all three of the major clouds and it really provides customers the flexibility to secure their data no matter if they're running, you know, on premises in a colo at the edge in the public cloud. And the other nice thing about this, this announcement is that you have the ability to use Google Cloud as a cyber recovery vault that really allows customers to isolate critical data and they can recover that critical data from the vault back to on premises or from that vault back to running their cyber cyber protection or their data protection solutions in the public cloud. >>I always invoke my, my favorite Matt Baker here. It's not a zero sum game, but this is a perfect example where there's opportunities for a company like Dell to partner with the public cloud provider. You've got capabilities that don't exist there. You've got the on-prem capabilities. We can talk about edge all day, but that's a different topic. Okay, so my, my other question Travis, is how does this all fit into Apex? We hear a lot about Apex as a service, it's sort of the new hot thing. What's happening there? What's the news around Apex? >>Yeah, we, we've seen incredible momentum with our Apex solutions since we introduced data protection options into them earlier this year. And we're really building on that momentum with this announcement being, you know, providing solutions that allow customers to consume flexibly. And so what we're announcing specifically is that we're expanding Apex data storage services to include a data protection option. And it's like with all Apex offers, it's a pay as you go solution really streamlines the process of customers purchasing, deploying, maintaining and managing their backup software. All a customer really needs to do is, you know, specify their base capacity, they specify their performance tier, they tell us do they want a a one year term or a three year term and we take it from there. We, we get them up and running so they can start deploying and consuming flexibly. And it's, as with many of our Apex solutions, it's a simple user experience all exposed through a unified Apex console. >>Okay. So it's you keeping it simple, like I think large, medium, small, you know, we hear a lot about t-shirt sizes. I I'm a big fan of that cuz you guys should be smart enough to figure out, you know, based on my workload, what I, what I need, how different is this? I wonder if you guys could, could, could address this. Jeff, maybe you can, >>You can start. Sure. I'll start and then pitch me, you know, Travis, you you jump in when I screw up here. So, awesome. So first I'd say we offer innovative multi-cloud data protection solutions. We provide that deliver performance, efficiency and scale that our customers demand and require. We support as Travis and all the major public clouds. We have a broad ecosystem of workload support and I guess the, the great news is we're up to 80% more cost effective than any of the competition. >>80%. 80%, That's a big number, right? Travis, what's your point of view on this? Yeah, >>I, I think number one, end to end data protection. We, we are that one stop shop that I talked about. Whether it's a simplified appliance, whether it's deployed in the cloud, whether it's at the edge, whether it's integrated appliances, target appliances, software, we have solutions that span the gamut as a service. I mentioned the Apex solution as well. So really we can, we can provide solutions that help support customers and protect them, any workload, any cloud, anywhere that data lives edge core to cloud. The other thing that we hear as a, as a, a big differentiator for Dell and, and Jeff touched on on this a little bit earlier, is our intelligent cyber resiliency. We have a unique combination in, in the market where we can offer immutability or protection against deletion as, as sort of that first line of defense. But we can also offer a second level of defense, which is isolation, talking, talking about data vaults or cyber vaults and cyber recovery. And the, at more importantly, the intelligence that goes around that vault. It can look at detecting cyber attacks, it can help customers speed time to recovery and really provides AI and ML to help early diagnosis of a cyber attack and fast recovery should a cyber attack occur. And, and you know, if you look at customer adoption of that solution specifically in the clouds, we have over 1300 customers utilizing power protect cyber recovery. >>So I think it's fair to say that your, I mean your portfolio has obvious been a big differentiator whenever I talk to, you know, your finance team, Michael Dell, et cetera, that end to end capability that that, that your ability to manage throughout the supply chain. We actually just did a a, an event recently with you guys where you went into what you're doing to make infrastructure trusted. And so my take on that is you, in a lot of respects, you're shifting, you know, the client's burden to your r and d now they have a lot of work to do, so it's, it's not like they can go home and just relax, but, but that's a key part of the partnership that I see. Jeff, I wonder if you could give us the, the, the final thoughts. >>Sure. Dell has a long history of being a trusted partner with it, right? So we have unmatched capabilities. Going back to your point, we have the broadest portfolio, we have, you know, we're a leader in every category that we participate in. We have a broad deep breadth of portfolio. We have scale, we have innovation that is just unmatched within data protection itself. We have the trusted market leader, no, if and or buts, we're number one for both data protection software in appliances per idc and we would just name for the 17th consecutive time the leader in the, the Gartner Magic Quadrant. So bottom line is customers can count on Dell. >>Yeah, and I think again, we're seeing the evolution of, of data protection. It's not like the last 10 years, it's really becoming an adjacency and really a key component of your cyber strategy. I think those two parts of the organization are coming together. So guys, really appreciate your time. Thanks for Thank you sir. Thanks Travis. Good to see you. All right, in a moment I'm gonna come right back and summarize what we learned today, what actions you can take for your business. You're watching the future of multi-cloud data protection made possible by Dell and collaboration with the cube, your leader in enterprise and emerging tech coverage right back >>In our data driven world. Protecting data has never been more critical to guard against everything from cyber incidents to unplanned outages. You need a cyber resilient, multi-cloud data protection strategy. >>It's not a matter of if you're gonna get hacked, it's a matter of when. And I wanna know that I can recover and continue to recover each day. >>It is important to have a cyber security and a cyber resiliency plan in place because the threat of cyber attack are imminent. >>Power protects. Data manager from Dell Technologies helps deliver the data protection and security confidence you would expect from a trusted partner and market leader. >>We chose Power Protect Data Manager because we've been a strategic partner with Dell Technologies for roughly 20 years now. Our partnership with Dell Technologies has provided us with the ability to scale and grow as we've transitioned from 10 billion in assets to 20 billion. >>With Power Protect Data Manager, you can enjoy exceptional ease of use to increase your efficiency and reduce costs. >>Got installed it by myself, learned it by myself with very intuitive >>While restoring a machine with Power Protect Data Manager is fast. We can fully manage Power Protect through the center. We can recover a whole machine in seconds. >>Data Manager offers innovation such as Transparent snapshots to simplify virtual machine backups and it goes beyond backup and restore to provide valuable insights and to protected data workloads and VMs. >>In our previous environment, it would take anywhere from three to six hours at night to do a single backup of each vm. Now we're backing up hourly and it takes two to three seconds with the transparent snapshots. >>With Power Protects Data Manager, you get the peace of mind knowing that your data is safe and available whenever you need it. >>Data is extremely important. We can't afford to lose any data. We need things just to work. >>Start your journey to modern data protection with Dell Power Protect Data manager. Visit dell.com/power Protect Data Manager. >>We put forth the premise in our introduction that the worlds of data protection in cybersecurity must be more integrated. We said that data recovery strategies have to be built into security practices and procedures and by default this should include modern hardware and software. Now in addition to reviewing some of the challenges that customers face, which have been pretty well documented, we heard about new products that Dell Technologies is bringing to the marketplace that specifically address these customer concerns. There were three that we talked about today. First, the Power Protect Data Manager Appliance, which is an integrated system taking advantage of Dell's history in data protection, but adding new capabilities. And I want to come back to that in the moment. Second is Dell's Power Protect cyber recovery for Google Cloud platform. This rounds out the big three public cloud providers for Dell, which joins AWS and and Azure support. >>Now finally, Dell has made its target backup appliances available in Apex. You might recall earlier this year we saw the introduction from Dell of Apex backup services and then in May at Dell Technologies world, we heard about the introduction of Apex Cyber Recovery Services. And today Dell is making its most popular backup appliances available and Apex. Now I wanna come back to the Power Protect data manager appliance because it's a new integrated appliance. And I asked Dell off camera really what is so special about these new systems and what's really different from the competition because look, everyone offers some kind of integrated appliance. So I heard a number of items, Dell talked about simplicity and efficiency and containers and Kubernetes. So I kind of kept pushing and got to what I think is the heart of the matter in two really important areas. One is simplicity. >>Dell claims that customers can deploy the system in half the time relative to the competition. So we're talking minutes to deploy and of course that's gonna lead to much simpler management. And the second real difference I heard was backup and restore performance for VMware workloads. In particular, Dell has developed transparent snapshot capabilities to fundamentally change the way VMs are protected, which leads to faster backup and restores with less impact on virtual infrastructure. Dell believes this new development is unique in the market and claims that in its benchmarks the new appliance was able to back up 500 virtual machines in 47% less time compared to a leading competitor. Now this is based on Dell benchmarks, so hopefully these are things that you can explore in more detail with Dell to see if and how they apply to your business. So if you want more information, go to the data protectionPage@dell.com. You can find that at dell.com/data protection. And all the content here and other videos are available on demand@thecube.net. Check out our series on the blueprint for trusted infrastructure, it's related and has some additional information. And go to silicon angle.com for all the news and analysis related to these and other announcements. This is Dave Valante. Thanks for watching the future of multi-cloud protection made possible by Dell in collaboration with the Cube, your leader in enterprise and emerging tech coverage.

>> We're here with Jeff Boudreau and Travis Vigil, and we're going to dig into the details about Dell's big data protection announcement. Guys, good to see you. Thanks for coming in. >> Good to see you. Thank you for having us. >> You're very welcome. Let's start off, Jeff, with a high level, you know I'd like to talk about the customer, what challenges they're facing. You're talking to customers all the time, what are they telling you? >> Sure. As you know, we spend a lot of time with our customers, specifically listening, learning understanding their use cases their pain points within their specific environments. They tell us a lot, to no surprise to any of us that data is a key theme that they talk about. It's one of their most important assets. They need to extract more value from that data to fuel their business models their innovation engines, their competitive edge. So they need to make sure that that data is accessible it's secure, and it's recoverable, especially in today's world with the increased cyber attacks. >> Okay. So maybe we could get into some of those challenges. I mean, when you talk about things like data sprawl what do you mean by that? What should people know? >> Sure, so for those big three themes, I'd say, you know you have data sprawl, which is the big one which is all about the massive amounts of data. It's the growth of that data which is growing at an unprecedented rates. It's the gravity of that data and the reality of the multi-cloud sprawl. So stuff is just everywhere, right? Which increases that service, attack space for cyber criminals. >> And by gravity you mean the data's there and people don't want to move it. >> It's everywhere, right? And so when it lands someplace, think Edge, Core or Cloud, it's there. And it's something we have to help our customers with. >> Okay. So it's nuanced cause complexity has other layers. What are those layers? >> Sure. When we talk to our customers they tell us complexity is one of their big themes. And specifically it's around data complexity. We talked about that growth and gravity of the data. We talk about multi-cloud complexity and we talk about multi-cloud sprawl. So multiple vendors, multiple contracts multiple tool chains, and none of those work together in this, you know, multi-cloud world. Then that drives their security complexity. So we talk about that increased attack surface. But this really drives a lot of operational complexity for their teams. Think about, we're lack consistency through everything. So people, process, tools, all that stuff which is really wasting time and money for our customers. >> So how does that affect the cyber strategies and the, I've often said the CISO, now they have this shared responsibility model they have to do that across multiple clouds. Every cloud has its own security policies and frameworks and syntax. So maybe you could double click on your perspective on that. >> Sure. I'd say the big challenge customers have seen, it's really inadequate cyber resiliency. And specifically they're feeling very exposed. And today as the world with cyber attacks being more and more sophisticated, if something goes wrong it is a real challenge for them to get back up and running quickly. And that's why this is such a big topic for CEOs and businesses around the world. >> You know, it's funny, I said this in my open, I think that prior to the pandemic businesses were optimized for efficiency and now they're like, wow, we have to actually put some headroom into the system to be more resilient, you know? Are you hearing that? >> Yeah, we absolutely are. I mean, the customers really they're asking us for help, right? It's one of the big things we're learning and hearing from them. And it's really about three things one's about simplifying IT. Two, it's really helping them to extract more value from their data. And then the third big piece is ensuring their data is protected and recoverable regardless of where it is going back to that data gravity and that very, you know the multi-cloud world. Just recently, I don't know if you've seen it, but the global data protected, excuse me the global data protection index. >> GDPI. >> Yes. Jesus! >> Not to be confused with GDPR. >> Actually that was released today and confirms everything we just talked about around customer challenges but also it highlights an importance of having a very cyber, a robust cyber resilient data protection strategy. >> Yeah, I haven't seen the latest, but I want to dig into it. I think this, you've done this many, many years in a row. I like to look at the time series and see how things have changed. All right. At a high level, Jeff, can you kind of address why Dell and from your point of view is best suited? >> Sure. So we believe there's a better way or a better approach on how to handle this. We think Dell is uniquely positioned to help our customers as a one stop shop, if you will, for that cyber resilient multi-cloud data protection solution and needs. We take a modern, a simple and resilient approach. >> Well what does that mean? What do you mean by modern? >> Sure. So modern, we talk about our software defined architecture, right? It's really designed to meet the needs not only of today but really into the future. And we protect data across any cloud and any workload. So we have a proven track record doing this today. We have more than 1700 customers that trust us to protect more than 14 exabytes of their data in the cloud today. >> Okay. So you said modern, simple and resilient. What, what do you mean by simple? >> Sure. We want to provide simplicity everywhere, going back to helping with the complexity challenge, and that's from deployment to consumption to management and support. So our offers will deploy in minutes. They are easy to operate and use and we support flexible consumption models for whatever customer may desire. So traditional, subscription, or as a service. >> And when you talk about resilient, I mean I put forth that premise, but it's hard because people say, well, that's going to going to cost us more. Well, it may, but you're going to also reduce your risk. So what's your point of view on resilience? >> Yeah, I think it's something all customers need. So we're going to be providing a comprehensive and resilient portfolio of cyber solutions that are secured by design. We have some some unique capabilities in a combination of things like built in immuneability, physical and logical isolation. We have intelligence built in with AI parred recovery and just one, I guess fun fact for everybody is we have our cyber vault is the only solution in the industry that is endorsed by Sheltered Harbor that meets all the needs of the financial sector. >> So it's interesting when you think about the NIST framework for cybersecurity, it's all about layers. You're sort of bringing that now to data protection. >> Correct. >> Yeah. All right. In a minute we're going to come back with Travis and dig into the news. We're going to take a short break, keep it right there. (calming piano music)

>>Prior to the pandemic, organizations were largely optimized for efficiency as the best path to bottom line profits. Many CIOs tell the cube privately that they were caught off guard by the degree to which their businesses required greater resiliency beyond their somewhat cumbersome disaster recovery processes. And the lack of that business resilience has actually cost firms because they were unable to respond to changing market forces. And certainly we've seen this dynamic with supply chain challenges and there's a little doubt. We're also seeing it in the area of cybersecurity generally, and data recovery. Specifically. Over the past 30 plus months, the rapid adoption of cloud to support remote workers and build in business resilience had the unintended consequences of expanding attack vectors, which brought an escalation of risk from cyber crime. Well, security in the public clouds is certainly world class. The result of multi-cloud has brought with it multiple shared responsibility models, multiple ways of implementing security policies across clouds and on-prem. >>And at the end of the day, more, not less complexity, but there's a positive side to this story. The good news is that public policy industry collaboration and technology innovation is moving fast to accelerate data protection and cybersecurity strategies with a focus on modernizing infrastructure, securing the digital supply chain, and very importantly, simplifying the integration of data protection and cybersecurity. Today there's heightened awareness that the world of data protection is not only an adjacency to, but it's becoming a fundamental component of cybersecurity strategies. In particular, in order to build more resilience into a business, data protection, people, technologies, and processes must be more tightly coordinated with security operations. Hello and welcome to the future of Multi-Cloud Data Protection Made Possible by Dell in collaboration with the Cube. My name is Dave Valante and I'll be your host today. In this segment, we welcome into the Cube, two senior executives from Dell who will share details on new technology announcements that directly address these challenges. >>Jeff Boudreaux is the president and general manager of Dell's Infrastructure Solutions Group, isg, and he's gonna share his perspectives on the market and the challenges he's hearing from customers. And we're gonna ask Jeff to double click on the messages that Dell is putting into the marketplace and give us his detailed point of view on what it means for customers. Now Jeff is gonna be joined by Travis Vhi. Travis is the senior Vice President of product management for ISG at Dell Technologies, and he's gonna give us details on the products that are being announced today and go into the hard news. Now, we're also gonna challenge our guests to explain why Dell's approach is unique and different in the marketplace. Thanks for being with us. Let's get right into it. We're here with Jeff Padro and Travis Behill. We're gonna dig into the details about Dell's big data protection announcement. Guys, good to see you. Thanks >>For coming in. Good to see you. Thank you for having us. >>You're very welcome. Right. Let's start off, Jeff, with a high level, you know, I'd like to talk about the customer, what challenges they're facing. You're talking to customers all the time, What are they telling you? >>Sure. As you know, we do, we spend a lot of time with our customers, specifically listening, learning, understanding their use cases, their pain points within their specific environments. They tell us a lot. Notice no surprise to any of us, that data is a key theme that they talk about. It's one of their most important, important assets. They need to extract more value from that data to fuel their business models, their innovation engines, their competitive edge. So they need to make sure that that data is accessible, it's secure in its recoverable, especially in today's world with the increased cyber attacks. >>Okay. So maybe we could get into some of those, those challenges. I mean, when, when you talk about things like data sprawl, what do you mean by that? What should people know? Sure. >>So for those big three themes, I'd say, you know, you have data sprawl, which is the big one, which is all about the massive amounts of data. It's the growth of that data, which is growing at an unprecedented rates. It's the gravity of that data and the reality of the multi-cloud sprawl. So stuff is just everywhere, right? Which increases that service a tax base for cyber criminals. >>And and by gravity you mean the data's there and people don't wanna move it. >>It's everywhere, right? And so when it lands someplace, I think edge, core or cloud, it's there and that's, it's something we have to help our customers with. >>Okay, so just it's nuanced cuz complexity has other layers. What, what are those >>Layers? Sure. When we talk to our customers, they tell us complexity is one of their big themes. And specifically it's around data complexity. We talked about that growth and gravity of the data. We talk about multi-cloud complexity and we talk about multi-cloud sprawl. So multiple vendors, multiple contracts, multiple tool chains, and none of those work together in this, you know, multi-cloud world. Then that drives their security complexity. So we talk about that increased attack surface, but this really drives a lot of operational complexity for their teams. Think about we're a lack consistency through everything. So people, process, tools, all that stuff, which is really wasting time and money for our customers. >>So how does that affect the cyber strategies and the, I mean, I've often said the ciso now they have this shared responsibility model, they have to do that across multiple clouds. Every cloud has its own security policies and, and frameworks and syntax. So maybe you could double click on your perspective on that. >>Sure. I'd say the big, you know, the big challenge customers have seen, it's really inadequate cyber resiliency. And specifically they're feeling, feeling very exposed. And today as the world with cyber tax being more and more sophisticated, if something goes wrong, it is a real challenge for them to get back up and running quickly. And that's why this is such a, a big topic for CEOs and businesses around the world. >>You know, it's funny, I said this in my open, I, I think that prior to the pandemic businesses were optimized for efficiency and now they're like, Wow, we have to actually put some headroom into the system to be more resilient. You know, I you hearing >>That? Yeah, we absolutely are. I mean, the customers really, they're asking us for help, right? It's one of the big things we're learning and hearing from them. And it's really about three things, one's about simplifying it, two, it's really helping them to extract more value from their data. And then the third big, big piece is ensuring their data is protected and recoverable regardless of where it is going back to that data gravity and that very, you know, the multicloud world just recently, I don't know if you've seen it, but the global data protected, excuse me, the global data protection index gdp. >>I, Yes. Jesus. Not to be confused with gdpr, >>Actually that was released today and confirms everything we just talked about around customer challenges, but also it highlights an importance of having a very cyber, a robust cyber resilient data protection strategy. >>Yeah, I haven't seen the latest, but I, I want to dig into it. I think this is, you've done this many, many years in a row. I like to look at the, the, the time series and see how things have changed. All right. At, at a high level, Jeff, can you kind of address why Dell and from your point of view is best suited? >>Sure. So we believe there's a better way or a better approach on how to handle this. We think Dell is uniquely positioned to help our customers as a one stop shop, if you will, for that cyber resilient multi-cloud data protection solution in needs. We take a modern, a simple and resilient approach, >>But what does that mean? What, what do you mean by modern? >>Sure. So modern, we talk about our software defined architecture, right? It's really designed to meet the needs not only of today, but really into the future. And we protect data across any cloud in any workload. So we have a proven track record doing this today. We have more than 1700 customers that trust us to protect them more than 14 exabytes of their data in the cloud today. >>Okay, so you said modern, simple and resilient. What, what do you mean by simple? Sure. >>We wanna provide simplicity everywhere, going back to helping with the complexity challenge, and that's from deployment to consumption to management and support. So our offers will deploy in minutes. They are easy to operate and use, and we support flexible consumption models for whatever the customer may desire. So traditional subscription or as a service. >>And when you, when you talk about resilient, I mean, I, I put forth that premise, but it's hard because people say, Well, that's gonna gonna cost us more. Well, it may, but you're gonna also reduce your, your risk. So how, what's your point of view on resilience? >>Yeah, I think it's, it's something all customers need. So we're gonna be providing a comprehensive and resilient portfolio of cyber solutions that are secured by design. We have some ver some unique capabilities in a combination of things like built in amenability, physical and logical isolation. We have intelligence built in with AI par recovery and just one, I guess fun fact for everybody is we have our cyber vault is the only solution in the industry that is endorsed by Sheltered Harbor that meets all the needs of the financial sector. >>So it's interesting when you think about the, the NIST framework for cyber security, it's all about about layers. You're sort of bringing that now to, to data protection, correct? Yeah. All right. In a minute we're gonna come back with Travis and dig into the news. We're gonna take a short break. Keep it right there. Okay. We're back with Jeff and Travis Vehill to dig deeper into the news. Guys, again, good to see you. Travis, if you could, maybe you, before we get into the news, can you set the business context for us? What's going on out there? >>Yeah, thanks for that question, Dave. To set a little bit of the context, when you look at the data protection market, Dell has been a leader in providing solutions to customers for going on nearly two decades now. We have tens of thousands of people using our appliances. We have multiple thousands of people using our latest modern simple power protect data managers software. And as Jeff mentioned, we have, you know, 1700 customers protecting 14 exabytes of data in the public clouds today. And that foundation gives us a unique vantage point. We talked to a lot of customers and they're really telling us three things. They want simple solutions, they want us to help them modernize and they want us to add as the highest priority, maintain that high degree of resiliency that they expect from our data protection solutions. So tho that's the backdrop to the news today. And, and as we go through the news, I think you'll, you'll agree that each of these announcements deliver on those pillars. And in particular today we're announcing the Power Protect data manager appliance. We are announcing power protect cyber recovery enhancements, and we are announcing enhancements to our Apex data storage >>Services. Okay, so three pieces. Let's, let's dig to that. It's interesting appliance, everybody wants software, but then you talk to customers and they're like, Well, we actually want appliances because we just wanna put it in and it works, right? Performs great. So, so what do we need to know about the appliance? What's the news there? Well, >>You know, part of the reason I gave you some of those stats to begin with is that we have at this strong foundation of, of experience, but also intellectual property components that we've taken that have been battle tested in the market. And we've put them together in a new simple integrated appliance that really combines the best of the target appliance capabilities we have with that modern simple software. And we've integrated it from the, you know, sort of taking all of those pieces, putting them together in a simple, easy to use and easy to scale interface for customers. >>So the premise that I've been putting forth for, you know, months now, probably well, well over a year, is that, that that data protection is becoming an extension of your, your cybersecurity strategies. So I'm interested in your perspective on cyber recovery. You, you have specific news that you have there? >>Yeah, you know, we, we are, in addition to simplifying things via the, the appliance, we are providing solutions for customers no matter where they're deploying. And cyber recovery, especially when it comes to cloud deployments, is an increasing area of interest and deployment that we see with our customers. So what we're announcing today is that we're expanding our cyber recovery services to be available in Google Cloud with this announcement. It means we're available in all three of the major clouds and it really provides customers the flexibility to secure their data no matter if they're running, you know, on premises in a colo at the edge in the public cloud. And the other nice thing about this, this announcement is that you have the ability to use Google Cloud as a cyber recovery vault that really allows customers to isolate critical data and they can recover that critical data from the vault back to on-premises or from that vault back to running their cyber cyber protection or their data protection solutions in the public cloud. >>I always invoke my, my favorite Matt Baker here. It's not a zero sum game, but this is a perfect example where there's opportunities for a company like Dell to partner with the public cloud provider. You've got capabilities that don't exist there. You've got the on-prem capabilities. We could talk about edge all day, but that's a different topic. Okay, so Mike, my other question Travis, is how does this all fit into Apex? We hear a lot about Apex as a service, it's sort of the new hot thing. What's happening there? What's the news around Apex? >>Yeah, we, we've seen incredible momentum with our Apex solutions since we introduced data protection options into them earlier this year. And we're really building on that momentum with this announcement being, you know, providing solutions that allow customers to consume flexibly. And so what we're announcing specifically is that we're expanding Apex data storage services to include a data protection option. And it's like with all Apex offers, it's a pay as you go solution really streamlines the process of customers purchasing, deploying, maintaining and managing their backup software. All a customer really needs to do is, you know, specify their base capacity, they specify their performance tier, they tell us do they want a a one year term or a three year term and we take it from there. We, we get them up and running so they can start deploying and consuming flexibly. And it's, as with many of our Apex solutions, it's a simple user experience all exposed through a unified Apex console. >>Okay. So it's you keeping it simple, like I think large, medium, small, you know, we hear a lot about t-shirt sizes. I I'm a big fan of that cuz you guys should be smart enough to figure out, you know, based on my workload, what I, what I need, how different is this? I wonder if you guys could, could, could address this. Jeff, maybe you can, >>You can start. Sure. I'll start and then pitch me, you know, Travis, you you jump in when I screw up here. So, awesome. So first I'd say we offer innovative multi-cloud data protection solutions. We provide that deliver performance, efficiency and scale that our customers demand and require. We support as Travis at all the major public clouds. We have a broad ecosystem of workload support and I guess the, the great news is we're up to 80% more cost effective than any of the competition. >>80%. 80%, That's a big number, right. Travis, what's your point of view on this? Yeah, >>I, I think number one, end to end data protection. We, we are that one stop shop that I talked about. Whether it's a simplified appliance, whether it's deployed in the cloud, whether it's at the edge, whether it's integrated appliances, target appliances, software, we have solutions that span the gamut as a service. I mentioned the Apex solution as well. So really we can, we can provide solutions that help support customers and protect them, any workload, any cloud, anywhere that data lives edge core to cloud. The other thing that we hear as a, as a, a big differentiator for Dell and, and Jeff touched on on this a little bit earlier, is our intelligent cyber resiliency. We have a unique combination in, in the market where we can offer immutability or protection against deletion as, as sort of that first line of defense. But we can also offer a second level of defense, which is isolation, talking, talking about data vaults or cyber vaults and cyber recovery. And the, at more importantly, the intelligence that goes around that vault. It can look at detecting cyber attacks, it can help customers speed time to recovery and really provides AI and ML to help early diagnosis of a cyber re attack and fast recovery should a cyber attack occur. And, and you know, if you look at customer adoption of that solution specifically in the clouds, we have over 1300 customers utilizing power protect cyber recovery. >>So I think it's fair to say that your, I mean your portfolio has obvious been a big differentiator whenever I talk to, you know, your finance team, Michael Dell, et cetera, that end to end capability that that, that your ability to manage throughout the supply chain. We actually just did a a, an event recently with you guys where you went into what you're doing to make infrastructure trusted. And so my take on that is you, in a lot of respects, you're shifting, you know, the client's burden to your r and d now they have a lot of work to do, so it's, it's not like they can go home and just relax, but, but that's a key part of the partnership that I see. Jeff, I wonder if you could give us the, the, the final thoughts. >>Sure. Dell has a long history of being a trusted partner with it, right? So we have unmatched capabilities. Going back to your point, we have the broadest portfolio, we have, you know, we're a leader in every category that we participate in. We have a broad deep breadth of portfolio. We have scale, we have innovation that is just unmatched within data protection itself. We are the trusted market leader, no if and or bots, we're number one for both data protection software in appliances per idc. And we would just name for the 17th consecutive time the leader in the, the Gartner Magic Quadrant. So bottom line is customers can count on Dell. >>Yeah, and I think again, we're seeing the evolution of, of data protection. It's not like the last 10 years, it's really becoming an adjacency and really a key component of your cyber strategy. I think those two parts of the organization are coming together. So guys, really appreciate your time. Thanks for Thank you sir. Thanks Dave. Travis, good to see you. All right, in a moment I'm gonna come right back and summarize what we learned today, what actions you can take for your business. You're watching the future of multi-cloud data protection made possible by Dell and collaboration with the cube, your leader in enterprise and emerging tech coverage right back >>In our data driven world. Protecting data has never been more critical to guard against everything from cyber incidents to unplanned outages. You need a cyber resilient, multi-cloud data protection strategy. >>It's not a matter of if you're gonna get hacked, it's a matter of when. And I wanna know that I can recover and continue to recover each day. >>It is important to have a cyber security and a cyber resiliency plan in place because the threat of cyber attack are imminent. >>Power protects. Data manager from Dell Technologies helps deliver the data protection and security confidence you would expect from a trusted partner and market leader. >>We chose Power Protect Data Manager because we've been a strategic partner with Dell Technologies for roughly 20 years now. Our partnership with Dell Technologists has provided us with the ability to scale and grow as we've transitioned from 10 billion in assets to 20 billion. >>With Power Protect Data Manager, you can enjoy exceptional ease of use to increase your efficiency and reduce costs. >>Got installed it by myself, learned it by myself with very intuitive >>While restoring a machine with Power Protect Data Manager is fast. We can fully manage Power Protect through the center. We can recover a whole machine in seconds. >>Data Manager offers innovation such as Transparent snapshots to simplify virtual machine backups and it goes beyond backup and restore to provide valuable insights and to protected data workloads and VMs. >>In our previous environment, it would take anywhere from three to six hours at night to do a single backup of each vm. Now we're backing up hourly and it takes two to three seconds with the transparent snapshots. >>With Power Protects Data Manager, you get the peace of mind knowing that your data is safe and available whenever you need it. >>Data is extremely important. We can't afford to lose any data. We need things just to work. >>Start your journey to modern data protection with Dell Power Protect Data manager. Visit dell.com/power Protect Data Manager. >>We put forth the premise in our introduction that the world's of data protection in cybersecurity must be more integrated. We said that data recovery strategies have to be built into security practices and procedures and by default this should include modern hardware and software. Now in addition to reviewing some of the challenges that customers face, which have been pretty well documented, we heard about new products that Dell Technologies is bringing to the marketplace that specifically address these customer concerns. There were three that we talked about today. First, the Power Protect Data Manager Appliance, which is an integrated system taking advantage of Dell's history in data protection, but adding new capabilities. And I want to come back to that in the moment. Second is Dell's Power Protect cyber recovery for Google Cloud platform. This rounds out the big three public cloud providers for Dell, which joins AWS and and Azure support. >>Now finally, Dell has made its target backup appliances available in Apex. You might recall earlier this year we saw the introduction from Dell of Apex backup services and then in May at Dell Technologies world, we heard about the introduction of Apex Cyber Recovery Services. And today Dell is making its most popular backup appliances available and Apex. Now I wanna come back to the Power Protect data manager appliance because it's a new integrated appliance. And I asked Dell off camera really what is so special about these new systems and what's really different from the competition because look, everyone offers some kind of integrated appliance. So I heard a number of items, Dell talked about simplicity and efficiency and containers and Kubernetes. So I kind of kept pushing and got to what I think is the heart of the matter in two really important areas. One is simplicity. >>Dell claims that customers can deploy the system in half the time relative to the competition. So we're talking minutes to deploy and of course that's gonna lead to much simpler management. And the second real difference I heard was backup and restore performance for VMware workloads. In particular, Dell has developed transparent snapshot capabilities to fundamentally change the way VMs are protected, which leads to faster backup and restores with less impact on virtual infrastructure. Dell believes this new development is unique in the market and claims that in its benchmarks the new appliance was able to back up 500 virtual machines in 47% less time compared to a leading competitor. Now this is based on Dell benchmarks, so hopefully these are things that you can explore in more detail with Dell to see if and how they apply to your business. So if you want more information, go to the data protectionPage@dell.com. You can find that at dell.com/data protection. And all the content here and other videos are available on demand@thecube.net. Check out our series on the blueprint for trusted infrastructure, it's related and has some additional information. And go to silicon angle.com for all the news and analysis related to these and other announcements. This is Dave Valante. Thanks for watching the future of multi-cloud protection made possible by Dell in collaboration with the Cube, your leader in enterprise and emerging tech coverage.

>> Prior to the pandemic, organizations were largely optimized for efficiency as the best path to bottom line profits. Many CIOs tell theCUBE privately that they were caught off guard by the degree to which their businesses required greater resiliency beyond their somewhat cumbersome disaster recovery processes. And the lack of that business resilience has actually cost firms because they were unable to respond to changing market forces. And certainly, we've seen this dynamic with supply chain challenges. And there's a little doubt we're also seeing it in the area of cybersecurity generally, and data recovery specifically. Over the past 30 plus months, the rapid adoption of cloud to support remote workers and build in business resilience had the unintended consequences of expanding attack vectors, which brought an escalation of risk from cybercrime. While security in the public cloud is certainly world class, the result of multicloud has brought with it multiple shared responsibility models, multiple ways of implementing security policies across clouds and on-prem. And at the end of the day, more, not less, . But there's a positive side to this story. The good news is that public policy, industry collaboration and technology innovation is moving fast to accelerate data protection and cybersecurity strategies with a focus on modernizing infrastructure, securing the digital supply chain, and very importantly, simplifying the integration of data protection and cybersecurity. Today, there's heightened awareness that the world of data protection is not only an adjacency to, but is becoming a fundamental component of cybersecurity strategies. In particular, in order to build more resilience into a business, data protection people, technologies and processes must be more tightly coordinated with security operations. Hello, and welcome to "The Future of Multicloud Data Protection" made possible by Dell in collaboration with theCUBE. My name is Dave Vellante and I'll be your host today. In this segment, we welcome into theCUBE two senior executives from Dell who will share details on new technology announcements that directly address these challenges. Jeff Boudreau is the President and General Manager of Dell's Infrastructure Solutions Group, ISG, and he's going to share his perspectives on the market and the challenges he's hearing from customers. And we're going to ask Jeff to double click on the messages that Dell is putting into the marketplace and give us his detailed point of view on what it means for customers. Now, Jeff is going to be joined by Travis Vigil. Travis is the Senior Vice-President of Product Management for ISG at Dell Technologies, and he's going to give us details on the products that are being announced today and go into the hard news. Now, we're also going to challenge our guests to explain why Dell's approach is unique and different in the marketplace. Thanks for being with us. Let's get right into it. (upbeat music) We're here with Jeff Boudreau and Travis Vigil, and we're going to dig into the details about Dell's big data protection announcement. Guys, good to see you. Thanks for coming in. >> Good to see you. Thank you for having us. >> You're very welcome. Alright, let's start off Jeff, with the high level. You know, I'd like to talk about the customer, what challenges they're facing? You're talking to customers all the time. What are they telling you? >> Sure, as you know, we spend a lot of time with our customers, specifically listening, learning, understanding their use cases, their pain points within their specific environments. They tell us a lot. No surprise to any of us that data is a key theme that they talk about. It's one of their most important assets. They need to extract more value from that data to fuel their business models, their innovation engines, their competitive edge. So, they need to make sure that that data is accessible, it's secure and its recoverable, especially in today's world with the increased cyber attacks. >> Okay, so maybe we could get into some of those challenges. I mean, when you talk about things like data sprawl, what do you mean by that? What should people know? >> Sure, so for those big three themes, I'd say, you have data sprawl, which is the big one, which is all about the massive amounts of data. It's the growth of that data, which is growing at unprecedented rates. It's the gravity of that data and the reality of the multicloud sprawl. So stuff is just everywhere, right? Which increases that surface as attack space for cyber criminals. >> And by gravity, you mean the data's there and people don't want to move it. >> It's everywhere, right? And so when it lands someplace, think Edge, Core or Cloud, it's there. And it's something we have to help our customers with. >> Okay, so it's nuanced 'cause complexity has other layers. What are those layers? >> Sure. When we talk to our customers, they tell us complexity is one of their big themes. And specifically it's around data complexity. We talked about that growth and gravity of the data. We talk about multicloud complexity and we talk about multicloud sprawl. So multiple vendors, multiple contracts, multiple tool chains, and none of those work together in this multicloud world. Then that drives their security complexity. So, we talk about that increased attack surface. But this really drives a lot of operational complexity for their teams. Think about we're lacking consistency through everything. So people, process, tools, all that stuff, which is really wasting time and money for our customers. >> So, how does that affect the cyber strategies and the, I mean, I've often said the Cisco, now they have this shared responsibility model. They have to do that across multiple clouds. Every cloud has its own security policies and frameworks and syntax. So, maybe you could double click on your perspective on that. >> Sure. I'd say the big challenge customers have seen, it's really inadequate cyber resiliency and specifically, they're feeling very exposed. And today as the world with cyber attacks being more and more sophisticated, if something goes wrong, it is a real challenge for them to get back up and running quickly. And that's why this is such a big topic for CEOs and businesses around the world. You know, it's funny. I said this in my open. I think that prior to the pandemic businesses were optimized for efficiency, and now they're like, "Wow, we have to actually put some headroom into the system to be more resilient." You know, are you hearing that? >> Yeah, we absolutely are. I mean, the customers really, they're asking us for help, right? It's one of the big things we're learning and hearing from them. And it's really about three things. One's about simplifying IT. Two, it's really helping them to extract more value from their data. And then the third big piece is ensuring their data is protected and recoverable regardless of where it is going back to that data gravity and that very, you know, the multicloud world. Just recently, I don't know if you've seen it, but the Global Data Protected, excuse me, the Global Data Protection Index. >> GDPI. >> Yes. Jesus. >> Not to be confused with GDPR. >> Actually, that was released today and confirms everything we just talked about around customer challenges. But also it highlights at an importance of having a very cyber, a robust cyber resilient data protection strategy. >> Yeah, I haven't seen the latest, but I want to dig into it. I think this, I've done this many, many years in a row. I'd like to look at the time series and see how things have changed. All right. At a high level, Jeff, can you kind of address why Dell, from your point of view is best suited? >> Sure. So, we believe there's a better way or a better approach on how to handle this. We think Dell is uniquely positioned to help our customers as a one stop shop, if you will, for that cyber resilient multicloud data protection solution and needs. We take a modern, a simple and resilient approach. >> What does that mean? What do you mean by modern? >> Sure. So modern, we talk about our software defined architecture. Right? It's really designed to meet the needs not only of today, but really into the future. And we protect data across any cloud and any workload. So, we have a proven track record doing this today. We have more than 1,700 customers that trust us to protect more than 14 exabytes of their data in the cloud today. >> Okay, so you said modern, simple and resilient. What do you mean by simple? >> Sure. We want to provide simplicity everywhere, going back to helping with the complexity challenge. And that's from deployment to consumption, to management and support. So, our offers will deploy in minutes. They are easy to operate and use, and we support flexible consumption models for whatever the customer may desire. So, traditional subscription or as a service. >> And when you talk about resilient, I mean, I put forth that premise, but it's hard because people say, "Well, that's going to cost us more. Well, it may, but you're going to also reduce your risk." So, what's your point of view on resilience? >> Yeah, I think it's something all customers need. So, we're going to be providing a comprehensive and resilient portfolio of cyber solutions that are secure by design. And we have some unique capabilities and a combination of things like built in immutability, physical and logical isolation. We have intelligence built in with AI part recovery. And just one, I guess fun fact for everybody is we have, our cyber vault is the only solution in the industry that is endorsed by Sheltered Harbor that meets all the needs of the financial sector. >> So it's interesting when you think about the NIST framework for cybersecurity. It's all about about layers. You're sort of bringing that now to data protection. >> Jeff: Correct. Yeah. >> All right. In a minute, we're going to come back with Travis and dig into the news. We're going to take a short break. Keep it right there. (upbeat music) (upbeat adventurous music) Okay, we're back with Jeff and Travis Vigil to dig deeper into the news. Guys, again, good to see you. Travis, if you could, maybe you, before we get into the news, can you set the business context for us? What's going on out there? >> Yeah. Thanks for that question, Dave. To set a little bit of the context, when you look at the data protection market, Dell has been a leader in providing solutions to customers for going on nearly two decades now. We have tens of thousands of people using our appliances. We have multiple thousands of people using our latest modern, simple PowerProtect Data Manager Software. And as Jeff mentioned, we have, 1,700 customers protecting 14 exabytes of data in the public clouds today. And that foundation gives us a unique vantage point. We talked to a lot of customers and they're really telling us three things. They want simple solutions. They want us to help them modernize. And they want us to add as the highest priority, maintain that high degree of resiliency that they expect from our data protection solutions. So, that's the backdrop to the news today. And as we go through the news, I think you'll agree that each of these announcements deliver on those pillars. And in particular, today we're announcing the PowerProtect Data Manager Appliance. We are announcing PowerProtect Cyber Recovery Enhancements, and we are announcing enhancements to our APEX Data Storage Services. >> Okay, so three pieces. Let's dig to that. It's interesting, appliance, everybody wants software, but then you talk to customers and they're like, "Well, we actually want appliances because we just want to put it in and it works." >> Travis: (laughs) Right. >> It performs great. So, what do we need to know about the appliance? What's the news there? >> Well, you know, part of the reason I gave you some of those stats to begin with is that we have this strong foundation of experience, but also intellectual property components that we've taken that have been battle tested in the market. And we've put them together in a new simple, integrated appliance that really combines the best of the target appliance capabilities we have with that modern, simple software. And we've integrated it from the, you know, sort of taking all of those pieces, putting them together in a simple, easy to use and easy to scale interface for customers. >> So, the premise that I've been putting forth for months now, probably well over a year, is that data protection is becoming an extension of your cybersecurity strategies. So, I'm interested in your perspective on cyber recovery. Your specific news that you have there. >> Yeah, you know, we are in addition to simplifying things via the appliance, we are providing solutions for customers no matter where they're deploying. And cyber recovery, especially when it comes to cloud deployments, is an increasing area of interest and deployment that we see with our customers. So, what we're announcing today is that we're expanding our cyber recovery services to be available in Google Cloud. With this announcement, it means we're available in all three of the major clouds and it really provides customers the flexibility to secure their data no matter if they're running on-premises, in Acolo, at the Edge, in the public cloud. And the other nice thing about this announcement is that you have the ability to use Google Cloud as a cyber recovery vault that really allows customers to isolate critical data and they can recover that critical data from the vault back to on-premises or from that vault back to running their cyber protection or their data protection solutions in the public cloud. >> I always invoke my favorite Matt Baker here. "It's not a zero sum game", but this is a perfect example where there's opportunities for a company like Dell to partner with the public cloud provider. You've got capabilities that don't exist there. You've got the on-prem capabilities. We could talk about Edge all day, but that's a different topic. Okay, so my other question Travis, is how does this all fit into APEX? We hear a lot about APEX as a service. It's sort of the new hot thing. What's happening there? What's the news around APEX? >> Yeah, we've seen incredible momentum with our APEX solutions since we introduced data protection options into them earlier this year. And we're really building on that momentum with this announcement being providing solutions that allow customers to consume flexibly. And so, what we're announcing specifically is that we're expanding APEX Data Storage Services to include a data protection option. And it's like with all APEX offers, it's a pay-as-you-go solution. Really streamlines the process of customers purchasing, deploying, maintaining and managing their backup software. All a customer really needs to do is specify their base capacity. They specify their performance tier. They tell us do they want a one year term or a three year term and we take it from there. We get them up and running so they can start deploying and consuming flexibly. And as with many of our APEX solutions, it's a simple user experience all exposed through a unified APEX Console. >> Okay, so it's, you're keeping it simple, like I think large, medium, small. You know, we hear a lot about T-shirt sizes. I'm a big fan of that 'cause you guys should be smart enough to figure out, you know, based on my workload, what I need. How different is this? I wonder if you guys could address this. Jeff, maybe you can start. >> Sure, I'll start and then- >> Pitch me. >> You know, Travis, you jump in when I screw up here. >> Awesome. >> So, first I'd say we offer innovative multicloud data protection solutions. We provide that deliver performance, efficiency and scale that our customers demand and require. We support as Travis said, all the major public clouds. We have a broad ecosystem of workload support and I guess the great news is we're up to 80% more cost effective than any of the competition. >> Dave: 80%? >> 80% >> Hey, that's a big number. All right, Travis, what's your point of view on this? >> Yeah, I think number one, end-to-end data protection. We are that one stop shop that I talked about, whether it's a simplified appliance, whether it's deployed in the cloud, whether it's at the Edge, whether it's integrated appliances, target appliances, software. We have solutions that span the gamut as a service. I mentioned the APEX Solution as well. So really, we can provide solutions that help support customers and protect them, any workload, any cloud, anywhere that data lives. Edge, Core to Cloud. The other thing that we hear as a big differentiator for Dell, and Jeff touched on on this a little bit earlier, is our Intelligent Cyber Resiliency. We have a unique combination in the market where we can offer immutability or protection against deletion as sort of that first line of defense. But we can also offer a second level of defense, which is isolation, talking about data vaults or cyber vaults and cyber recovery. And more importantly, the intelligence that goes around that vault. It can look at detecting cyber attacks. It can help customers speed time to recovery. And really provides AI and ML to help early diagnosis of a cyber attack and fast recovery should a cyber attack occur. And if you look at customer adoption of that solution, specifically in the cloud, we have over 1300 customers utilizing PowerProtect Cyber Recovery. >> So, I think it's fair to say that your portfolio has obviously been a big differentiator. Whenever I talk to your finance team, Michael Dell, et cetera, that end-to-end capability, that your ability to manage throughout the supply chain. We actually just did an event recently with you guys where you went into what you're doing to make infrastructure trusted. And so my take on that is you, in a lot of respects, you're shifting the client's burden to your R&D. now they have a lot of work to do, so it's not like they can go home and just relax. But that's a key part of the partnership that I see. Jeff, I wonder if you could give us the final thoughts. >> Sure. Dell has a long history of being a trusted partner within IT, right? So, we have unmatched capabilities. Going back to your point, we have the broadest portfolio. We're a leader in every category that we participate in. We have a broad deep breadth of portfolio. We have scale. We have innovation that is just unmatched. Within data protection itself, we are the trusted market leader. No if, ands or buts. We're number one for both data protection software in appliances per IDC and we were just named for the 17th consecutive time the leader in the Gartner Magic Quadrant. So, bottom line is customers can count on Dell. >> Yeah, and I think again, we're seeing the evolution of data protection. It's not like the last 10 years. It's really becoming an adjacency and really, a key component of your cyber strategy. I think those two parts of the organization are coming together. So guys, really appreciate your time. Thanks for coming. >> Thank you, sir. >> Dave. >> Travis, good to see you. All right, in a moment I'm going to come right back and summarize what we learned today, what actions you can take for your business. You're watching "The Future of Multicloud Data Protection" made possible by Dell in collaboration with theCUBE, your leader in enterprise and emerging tech coverage. Right back. >> Advertiser: In our data-driven world, protecting data has never been more critical. To guard against everything from cyber incidents to unplanned outages, you need a cyber resilient multicloud data protection strategy. >> It's not a matter of if you're going to get hacked, it's a matter of when. And I want to know that I can recover and continue to recover each day. >> It is important to have a cyber security and a cyber resiliency plan in place because the threat of cyber attack are imminent. >> Advertiser: PowerProtect Data Manager from Dell Technologies helps deliver the data protection and security confidence you would expect from a trusted partner and market leader. >> We chose PowerProtect Data Manager because we've been a strategic partner with Dell Technologies for roughly 20 years now. Our partnership with Dell Technologies has provided us with the ability to scale and grow as we've transitioned from 10 billion in assets to 20 billion. >> Advertiser: With PowerProtect Data Manager, you can enjoy exceptional ease of use to increase your efficiency and reduce costs. >> I'd installed it by myself, learn it by myself. It was very intuitive. >> While restoring your machine with PowerProtect Data Manager is fast, we can fully manage PowerProtect through the center. We can recover a whole machine in seconds. >> Instructor: Data Manager offers innovation such as transparent snapshots to simplify virtual machine backups, and it goes beyond backup and restore to provide valuable insights into protected data, workloads and VMs. >> In our previous environment, it would take anywhere from three to six hours a night to do a single backup of each VM. Now, we're backing up hourly and it takes two to three seconds with the transparent snapshots. >> Advertiser: With PowerProtect's Data Manager, you get the peace of mind knowing that your data is safe and available whenever you need it. >> Data is extremely important. We can't afford to lose any data. We need things just to work. >> Advertiser: Start your journey to modern data protection with Dell PowerProtect's Data Manager. Visit dell.com/powerprotectdatamanager >> We put forth the premise in our introduction that the worlds of data protection in cybersecurity must be more integrated. We said that data recovery strategies have to be built into security practices and procedures and by default, this should include modern hardware and software. Now, in addition to reviewing some of the challenges that customers face, which have been pretty well documented, we heard about new products that Dell Technologies is bringing to the marketplace that specifically address these customer concerns. And there were three that we talked about today. First, the PowerProtect Data Manager Appliance, which is an integrated system taking advantage of Dell's history in data protection, but adding new capabilities. And I want to come back to that in a moment. Second is Dell's PowerProtect Cyber Recovery for Google Cloud platform. This rounds out the big three public cloud providers for Dell, which joins AWS and Azure support. Now finally, Dell has made its target backup appliances available in APEX. You might recall, earlier this year we saw the introduction from Dell of APEX Backup Services and then in May at Dell Technologies World, we heard about the introduction of APEX Cyber Recovery Services. And today, Dell is making its most popular backup appliances available in APEX. Now, I want to come back to the PowerProtect Data Manager Appliance because it's a new integrated appliance and I asked Dell off camera, "Really what is so special about these new systems and what's really different from the competition?" Because look, everyone offers some kind of integrated appliance. So, I heard a number of items. Dell talked about simplicity and efficiency and containers and Kubernetes. So, I kind of kept pushing and got to what I think is the heart of the matter in two really important areas. One is simplicity. Dell claims that customers can deploy the system in half the time relative to the competition. So, we're talking minutes to deploy, and of course that's going to lead to much simpler management. And the second real difference I heard was backup and restore performance for VMware workloads. In particular, Dell has developed transparent snapshot capabilities to fundamentally change the way VMs are protected, which leads to faster backup and restores with less impact on virtual infrastructure. Dell believes this new development is unique in the market and claims that in its benchmarks, the new appliance was able to back up 500 virtual machines in 47% less time compared to a leading competitor. Now, this is based on Dell benchmarks, so hopefully these are things that you can explore in more detail with Dell to see if and how they apply to your business. So if you want more information, go to the Data Protection Page at dell.com. You can find that at dell.com/dataprotection. And all the content here and other videos are available on demand at theCUBE.net. Check out our series on the blueprint for trusted infrastructure, it's related and has some additional information. And go to siliconangle.com for all the news and analysis related to these and other announcements. This is Dave Vellante. Thanks for watching "The Future of Multicloud Protection" made possible by Dell, in collaboration with theCUBE, your leader in enterprise and emerging tech coverage. (upbeat music)

>>the >>globe. It's the Cube with digital coverage of AWS >>reinvent 2020 >>sponsored by Intel, AWS and our community partners. Everyone welcome back to the cubes. Virtual coverage of AWS reinvent 2020 Virtual I'm John for your host. Got a great segment here with two analyst day Volonte and Zia's Carvell who's head principles of zk research dot com. Guys. Great to see you A W s Kino. Thanks for >>coming on. Let's be back in the cube. >>Welcome back. Great to see you guys. Wanna get your thoughts? Um, it's mainly you because we talked with the enterprise a lot. You are leading analyst. You cover a broad range from networking all the way up to the C suite for enterprise buyers and and technology trends. Um, Andy Jassy laid down, in my opinion, what was directionally his next 20 mile stare. The next conquest for Amazon. And that is global. I t spend they locked in the infrastructures of service pass kicking ass. There. Check check. Hello, Enterprise. Different ballgame. What's your thoughts? >>Yeah, they have so much in different areas, obviously. You know, they have dominated cloud instances right there. Mawr compute storage memory. You know insists that anybody but you can see him, um, spreading their wings now, right? I think one of the more interesting announcements was actually what they're doing with Amazon connect. That's their contact center platform. And this is something that I think, Even last year, a lot of people weren't really even sure if they'd be in a long primary in the pocket. People about this market, they were asking, If you really think Amazon's in this, there's something they're experimenting. But we're here to stay. And I think one of the interesting things that they bring to market is, you know, almost unprecedented scale with their cloud platform as well as all the machine learning algorithms. And I think if if you believe that machine learning artificial intelligence is changing, I t. Forever and that's everything from the infrastructure to the network through the applications, then they have an inherent advantage because they have all those machine learning albums built into this stuff that they dio and so they can constantly look at these different markets and disruptive, disruptive, disrupt and take more and more sharing that and that's what they've done. E think that's you know, the context and announcements were great example that they're not doing the telephony things, and, you know, they're kind of bare table stakes. They do that pretty well, but they've just unloaded a whole bunch of ai based features that >>Dave, what's your take on this context center? Because it's not just call centers. I mean, there was a whole industry around call center, unified communications. That whole world. This is about the contact. It's about the person. This is not just a nuanced thing like telephony or, you know, PBX is in the old days. Remember those days? Things is not about the call. It's about the contact. This is what Jazzy saying. >>I think that way had Diana or on early. And I said, I like the fact that their AWS specifically is going after these solutions because several years ago it was just sort of. Here's a bunch of tools. Go figure it out. I think the contact center is I mean, everybody can relate Thio the pains of going through getting rerouted, having to restate all your credentials, not knowing who you are. And so between machine learning, Alexa, Natural language processing, better work flows. I mean there's this huge opportunity toe reinvent the whole call center contact center. So, uh, yeah, I think you called it John. It's a no brainer for a W s toe Really disrupt that >>business. Well, it also puts him in a position. You know, news is breaking on the day of and yet his keynote here at reinvent that, uh, you got Salesforce spying slack for 27 close toe, $28 billion. That's a 55% premium over when they announced it. And that's like a 30 x or 50 x on on revenue. Massive number to confess the message board software. I mean, so So. So. If Amazon can come in and get the context center model, which is not just voice, it's chat, it's machine learning. It's bots. And the innovation to create a step function kind of brings it back into the that integration of user network compute. You know, I just think that it feels very edgy in the sense of edge computing, because if I'm a person, I'm mobile. If I'm a person at work or at home, so there's a whole redefinition Zs, what's your take on this edge? Play from Amazon in context toe the enterprise software landscape. That seems to be, you know, focus on buying companies like Salesforce. >>Well, I think edges really the next big foray for computing. If one of the things and you ask we talked about this, you know, was that the compute, the unit of Compute, has gotten smaller and smaller, Right? We went from data centers to servers to virtual machines, the virtual machines and clouds. Now we're talking about containers and containers on edges, and this requires, um if you if you believe in the world of distributed computing where we're gonna have mawr containers running in MAWR, places on MAWR edges, right. The value proposition where companies is now they can move their data closer to the customer. They could move data closer to the user. And so, if I'm a retailer and I'm trying to understand what a customer is doing, I could do that in store. If I'm Tesla and I'm trying to understand what the drivers doing, I could do that in car, right? If I'm a cellular provider, I could do it by cellular edge. So the edge, I think, is where a lot of the innovation is going to be at Amazon has the luxury of this massive global network. You know, they just announced the number another a number of other local nodes, including Boston and a few other places. So they've got the footprint in place. And this this is what makes Amazon's are difficult to compete with, right? They built this massive network and this all these, no doubt for their e commerce business. And now they're leveraging that deliver I t services. You can't just go build this from the ground up the variety, right? You have to be able to monetize it another way. And they've been doing that with the commerce for a long time. And so it makes them. It makes it very, very difficult for them to capture Google could with Daniel forget about the item. Oh, yeah, so good. Microsoft. Possibly. But they I think that the more distributed compute becomes the more favors Amazon, >>I would add to that if I could, John, I mean, look good. Look at the prevailing way in which many of the infrastructure the old guard is Andy. Jesse calls them. Companies have pursued the edge they've essentially taking, taking x 86 boxes and, you know, maybe made him rugged and throwing them over the fence to the edge. And that really is not gonna play the edges. Now there's not one edge. I mean, there's a very highly specific use cases and factories and windmills. And maybe maybe it's small retail organizations, and whatever it is that those are gonna be really unique situations. And I think the idea of putting a programmable infrastructure at the edge is gonna win. I also think that the edge architecture is gonna be different. It's going to require much more efficient processing to do a I Influencing a lot of the data is gonna be, uh, stay at the edge. A lot of it's not gonna be persisted. Some of it's gonna come back to the cloud. But I think most of it is actually gonna gonna either not be persisted or stay at the edge and be affected in real time. When you think of autonomous vehicles so totally different programming model, >>well, I think that's the point of what I was saying earlier Zeus was talking about Is that it's It's the edges is just different. I mean, you got purpose built stuff. I mean, they were talking by the way they have snowball. So they have, ah, hard edge device. And they got out outpost now in multiple flavors and sizes. But they also were talking about computer vision and machine learning. We're going together for that. The panoramic appliance. I think it was where there's all these different cases to your point, Dave, where it's just different. At the edge, you have the zones for five G. I mean, if you go to a five g tower, that's essentially an edge. Just there's equipment up to this. Radios is transceivers and other back haul equipment. So when you look at the totality of what it is, the diversity, I think that's why this whole idea of Lambda and Containers is interesting. Toe Zia's. When you were saying about the compute sizes being small, because if you could put compute at the edge on small pieces to match the form factor that becomes interesting. I think that's what this Lambda container announcement I found interesting because I see that playing directly into that your reaction to >>that. It actually, um, makes it. If not done correctly, it could make I t much more complex because, um, containers air interesting because they're not like virtual machines. First live in perpetuity. Containers you They're very ephemeral, right? You spin them up to 30 seconds, you spin them up for a couple of minutes that you deprecate them. So at any given point in time, you could have thousands of containers, a handful of containers, millions of containers, Right? But it necessitates a common management. Uh huh. Underlay that could be used to visualize where these containers are, what's running on them. And that's what AWS provides. You know, all the stuff they're doing Lambda and Eks and things like that that lends itself to that. So a customer can then go and almost create a container architecture that spans all their cloud's edges, even on Prem. Now, uh, when Amazon has but still be able to manage it and simplify it, I think somebody's trying to do it themselves. They're gonna find that the complexity almost becomes untenable. Unless you have a Nike organization the size of Amazon companies don't. So we're >>gonna here, we're gonna hear from Deepak singing in a few sessions. He did the eks anywhere. That's essentially kubernetes service on the data center. But look at what they did with eks anywhere and then CCS, which has a common control plane to your point, that's compelling. And so, you know, if you're a developer or you're an enterprise, you might not have If you want to go with this. I t world. We talked about earlier zeros before you came on on our last segment. Most I t is not that built out in terms of capabilities. So learning new stuff is hard, so operating Amazon might be foreign to most I t shops. This is a challenge. Did you agree with that? Or or how do you see that? >>Um, well, a lot of Amazon used, obviously just the interviews and numbers of fucked that right. Um, but I think the concept of in a world where you have that common operating layer that spans it's no longer geographically limited to a data center or to a server. You know, it's it's now distributed across your entire multi cloud or distributed cloud environment. And so one of the important things right people remember is the world is becoming more dynamic and or distributed, and your I t strategy has to follow that. If you're doing things that are counted that you're not only standing still, you're actually going backwards. And so what Amazon is doing is they're allowing companies to be is dynamic distributors. They need to be to be able to maintain that that common operating layer that actually makes it management, because without it, you just you wind up in a situation. Like I said, that's incredible. A lot of people facing that today. And that's why that's why there's this big divergence, right? This five native cos they're going fast and legacy companies that can. >>Guys, I want to spend the next 10 minutes we have getting into more of the business side from this keynote because because I know your research on digital transmission first. I know you know the networking side up and down the stack and all that good stuff, but you've been doing a lot of research around the digital transformation with the cloud. Dave, you just put out a great great breaking and else think your 55th, um, episode on digital transformation with the cloud. It's very clear that Jackie is basically preaching, saying, Hey, Clay Christensen is former professor who passed away. He brought up this whole innovator's dilemma kind of theme and saying, Hey, if you don't get the reality that you're in, you better wake up and smell the coffee. It's a wake up call. That's what he's basically saying That's my take away. This is really this business management lesson. Leadership thinking is super important, and I know we've We've talked about people process, technology. Uh, let's Covad eyes this real quick. Bottom line. What is the playbook? Do you agree with jazz? His point of view here? Um, he's pretty being hardcore. He's like, literally saying adapter die in his own way. What, you guys thoughts on this? This is a true forcing function. This cove, In reality, >>I mean I mean, if you talk about the business transformation, digital transformation, business transformation, you know, what does that mean? I, like, said earlier that the last 10 years about I t transformation, I think the next 10 is gonna be about business transformation, organizational industry transformation, and I think what that means is the entire operational stack is gonna get digitized. So your sales you're marketing your your customer support your logistics. You know you're gonna have one interface to the customer as opposed toe, you know, fragmented stovepipe siloed. You know, data sets all over the place, and that is a major change. And I think that's ultimately what a W. S is trying to affect with its model and has obviously big challenges in doing so. But But that, to me, is what digital transformation is ultimately all about. And I think you're going to see it unfold very rapidly over the next several >>years. What's your reaction? What's your view on on the on Jackie? >>And he talked about his eight steps toe reinvention. Um and e think what digital transformation to me is the willingness to re invent disruptive own business even in the face that it might look horrible for your business, right? But understanding he is there something that I think is true. And a lot of, um, business leaders don't fully by this that if something is good for your customer, they're going to do it, and you can either make it happen, or you gonna watch it happen and then have the market taken away from me because there's a lot of cases you look at how slow you know, A lot of the banks, you know, operated until you know, the a lot of these, uh, cloud native, uh, money exchange systems came around the cape. Alan Ben more and things like that, right? Even retailers Amazon completely disrupted that model. You could say that Amazon killed, you know, Toys R us, but 20 rescue Toys R Us E. And I think there's got to be this hard willingness to look at your business model and be willing to disrupt yourself. And what Kobe did, John, I think, is a taught us a lesson that you have to be prepared for anything because nobody saw this coming. And sure you can. And a lot of companies thrived out of this, and a lot of one's gone away, but that the ability to be agile has never been more important. But you're only is Angela's. Ike lets you be, and that's what that's what. The W. Is going to sell us the ability to do anything you want with your business. But the staff, you have to have the business because they're willing to do that. >>You know, that's a great point. That's so smart. It's crime that's worth calling out. And we were talking before we came on live about our business with the Cube. There's no virtual, there's no floor anymore. So we had to go virtual if we weren't in the cloud. If we weren't doing R and D and tinkering with some software and having our studio, we'd be out of business. Dave. Everyone knows it. Now Get the Cube virtual. We have some software were position, and this kind of speaks directly to what Andy Jassy said. He said. Quote. If you're not in the process of figuring out as a company, how you're going to reinvent your customer experience in your product and reinvent who you are, you are starting to unwind. You may not realize it, but you are. What he's saying is you better wake up and smell the coffee and I want to get your guys reacted. You, particularly you around your experience and research. I've noticed that some customers that had cloud going on did well with co vid and said ones that didn't are still struggling not to catch up. So you're kind of intense. You got some companies that were that were on the wave, Maybe kind of figuring it out, that we're in good position and some that were flat footed and are desperate. Um, seems to be a trend. Do you agree with that? And what's your view on this idea of being ready? What does that even mean to be? Have readiness or >>take, you don't get the data points that Andy threw up there, right? That 50% of the companies that were the global fortune $500.2000 or are no longer here, Right? That Zatz Pretty shocking statistic. And that does come, uh, you know, from the willingness to disrupt your business. And if you got you're right. The companies that had a good, solid class raging in place, we're able to adapt their business very quickly. You could you look at retailers. Some had a very strong online presence. They had online customer service set up those companies didn't find other ones, were really forced to try and figure out how to let people in the store had a mimic. You know, the in store experience, you know, through from, uh, you know, support interface or whatever. Those are the ones that really struggling. So you're right. I think companies that were on the offensive plug to Dover companies that were fully in the cloud really accelerated their business and ones that didn't buy into it. I think they're struggling to survive in a lot of They're gone. >>Yeah, and all that. John, When Jesus was talking about his view of digital transformation, I was just writing down some of the examples to your point. The folks that were sort of had were cloud ready, covert ready, if you will. And those that weren't But think about think about automobiles. You know, there's testily even a manufacturer of automobiles or they software company. Personal health has completely changed over the last nine months with remote. You know, uh, telehealth automated manufacturing. You think about digital cash, e commerce and retail is completely, you know, accelerated. Obviously toe online. Think about kids in college and kids in high school and remote learning farming. You know, we've done a great job in terms of mono crops and actually creating a lot of food. But now I think the next 10 years is gonna be how do we get more nutritious food to people and so virtually every industry is ripe for disruption, and the cloud is the underpinning of that disruption. >>Alright, guys, got a few more minutes left. I want to get your thoughts quickly on the keynote. What it means for the customers that we're watching again. This is not a sales and marketing conference as they talk about. But if you're sitting in the audience, you guys, we're watching and we're virtual um Did it hit home with you? If you're a customer, what did he what? Give us Give the grades. Where do you Where do you hit a home run? Where he missed. Did he leave anything out? What's your take Zia's? We'll start with you. >>Um, I thought it was actually really good Keynote. I thought you did a good job of making the case for AWS. They talked about the open. They have more instances than anybody. So you could do almost any kind of compute in their cloud. I think one of the important lessons variety to is the importance. You can't just do everything. The software right? Hardware Still important silicon still important that, and to meet the needs of very special he needs from things like machine learning and AI. Amazon's actually spending their own silicon very much like Athens doing with their computers. And so if you are going to be a customer service focused company, you need to think of the I T. Stack and everything from the silicon, the hardware through the software, and build that integrated experience to Amazon's giving a tools to do that Now E. Do I would like to see Amazon be a little more, um, a supposed the cloud competitive friendly. The one thing I hear from customers all the time is they love the Amazon tools. They love the optimization capabilities, but you know, if they are adopting some kind of multi cloud strategy, the Amazon tools don't work in Azure and the capital don't work in Amazon. The same with Google, and it would be well within the best interests of those three companies. They find a way to get together and allow their common framework to work across clouds. Amazon's already got a lead that they could do that, and I don't think it's gonna be, but that that is something I think that's still missing from this world is they make it very difficult for customers to move the multi cloud. >>Well, some would say some people are saying, saying that the number one in the cloud I mean, got cloud wars Bob Evans over there saying Microsoft is dominating number one position over everybody else, multiple quarters in a row Now he's looking at revenue and granted. You got a lot of propping up there you got. You know, Windows server and sequel. You got a bunch of professional services, But clearly the I as in past side of the market, Microsoft is, like, way behind um So, yeah, they've got the numbers little legacy in their Microsoft should, and they got a little base. If I'm Amazon, I'm not. I'm worried about Microsoft more than anybody. I think you know, I looking at the Civil War between the Seattle forces. I mean, this is really Microsoft's gotta greatest all base, and they could flip that license deals and >>the cloud is good enough. I mean, it's myself doing very, very well with its classic Microsoft. You know >>they your point. Microsoft is the king of good enough, right? They put out features. They market heavily to the I t pro on. They put out licensing packages, so you're almost foolish to not at least fry their products. And then they do roll it out. So it's good enough and then you live with it for a while. But ultimately, whenever people use Microsoft, they do have an alternative under in there for a very special case. But e don't wanna >>the king of good enough. That's a great line. I love that. I'm gonna use that. But this Babel fish thing for Aurora that is a huge dagger. Potentially, it's an escape valve for customers. They wanna leave Microsoft. But clearly, if Microsoft you're gonna get penalized by running your license on Amazon. >>If our CEO our i t c t, I'd say, Okay, I definitely want to do business with with Amazon. That's what I heard today from Jassy, and I would want to hedge my bets either with Microsoft, especially if I'm a Microsoft shop or with Google's from analytics heavy unquestionably. I'd want to hedge my bets and have some kind of 70 30 80 20 mix. >>Look, if you're Andy Jassy and he's told me my interview, do it directly. I asked this question. He was very forthright. He doesn't hide from the fact that, uh, customers have multiple clouds, but they have a primary and secondary, but they're not gonna have, like, five or six major clouds. Yeah, it's hard to get these teams trained at to begin with. So there's a hedge. There's a supplier leverage. I get that. He's totally gets that. But if you're Amazon, you're gonna have your annual conference. You really don't wanna be in the business of talking about the other guys cloud, you say hybrid, right? It's on my show. You know, like you're competing. This is there's definitely competition between Microsoft and A W s. So you gotta respect that. But yeah, of course. There's multiple clouds called hybrid eks everywhere. Uh, container service. I mean, >>especially global, right? Different cloud providers of different strengths in different regions. You know, Microsoft, very strong in the Gulf. AWS isn't you know. So if you're a global company, um, you know, then you almost by default, have to go multi cloud multiple cloud vendors because of geographic differences. Obviously, China, with its own set of cloud providers. So, you know, smaller midsize businesses could get away with one, but As soon as you become global, you have to use more. >>Well, I'm a big fan of distributed computing. I loved the large scale concept of distribute computing. You got regions. Now you've got local zones. You got I O t edge. You got cloud going on Prem Edge. It's really an edge game at this point. Greater now distributed hyper Put hyper next to anything hyper cloud on your sounds better Piper >>Cube. And the opportunities the cloud providers and Amazon, you know, certainly is leading. This is the ability to take this complex, hyper distributed world and use their management tools toe create a normalized operating simplify What would be an overly complex world about it? >>Okay, we got a break. Just quick plug. There's a big salesforce event coming up on December 10th. Check it out on the Amazon site that that plug in you watching the cube stay tuned for more coverage after this break

>>from around the globe. It's the Cube with digital coverage of Dell Technologies. World Digital Experience Brought to you by Dell Technologies. Hey, welcome back. You're ready. Jeffrey here with the Cube. Welcome back to our ongoing coverage of Dell Technology World 2020. The Digital Experience. I'm coming to you from Palo Alto. It's a digital event, just like everything else in 2020. But we're excited to have our next guest. I think he's coming in all the way from Atlanta, Georgia. He's Jim Shook, the director of cyber security and compliance practice at Del Technology. Jim, Great to see you. >>Thanks, Jeff. It's quite the title there. Thanks for getting all that out. >>I have a big posted notes so that, uh, that's very helpful. But, you know, it's it's actually kind of an interesting thing because you have compliance and cybersecurity and your title, and it's it's It's interesting relationship between compliance as a motivator of behavior versus you know, you need to go a lot further than just what the compliance says. So I'm curious if you can talk about that relationship between yeah, we need to be compliant, and we need to follow the rules. But you need to think a lot bigger than that. >>Yeah, definitely. I mean, there's so many different standards out there and requirements. So typically, what we'll see on the regulatory side is very much a minimum baseline, and leading the way, as usual in the cybersecurity space, will be financial and health care organizations. That's particularly true in the US, but pretty much globally, at least on the financial side. So they'll set some baselines. A lot of industries don't really have many. And so what we look at many times is just general risk to the business. And, of course, if you're a publicly traded company, that might trigger some SEC requirements or other things like that. But again, we really look at those requirements as minimum baselines, and you have to work up from there based on the organization's risk profile. >>Yeah, yeah, and we see that we see that, too, with privacy and a whole a whole bunch of stuff where traditionally the regs and the compliance kind of lag, you know where the technologies and where the markets moving. So let's before we get too deep into it. Let's let's talk about the cove it impact because obviously a huge thing. Insecurity, Uh, you know, a light switch moment in mid March when everybody had to work from home. So suddenly your tax surfaces increase exponentially. People are working out of home environments that you don't necessarily know what's going on there. Who's going on there, The shared networks with the spouse and the kids and and everybody else. And but now we're, you know, 678 months into this. This is something that's going to be going on for a while, and even the new normal will have some type of a hybrid relationship with with, you know, an increased level of remote remote work once they work from home. But it's really work from anywhere. So I wonder if you could share your thoughts about how things have transitioned from you know, what happened in mid March, taking care of your own business and your own people to, you know, then taking care of your customers and the emergencies that they had. But now really thinking in terms of more of kind of a long term, fundamental shift in the security profile that people have with all their data and information >>Yeah. Gosh, it's been really interesting. I think organizations have done an amazing job when you think about the things that they've had to get done just really overnight. So a lot has been written about the pandemic, and you mentioned Jeff to really that expanded threats surface. All of a sudden, you've got people working from home. There wasn't enough VPN capacity. A lot of places. I talked to some organizations. Employees just took their desktop off of their desk and brought it home so it wasn't really ready toe work at a remote location. But organizations really adapted well to it. Meanwhile, that was opportunity for the criminals, and they've taken it. But Jeff, one of the things that I think about two is to an extent, this is the new normal, not necessarily the work from home, but the shift that's going to consistently happen in cybersecurity. Things change. The criminals air really smart, they adapt. So that was work from home. What's the next thing going to be? There's I O T. There's remote devices. There will be some vulnerabilities. We just have to get used to this pace and continue it. Unfortunately, >>right, right, right Yeah, it's always it's always a little bit of, Ah, a cat and mouse game, Right? But what? And then one of the other trends that we're seeing, I don't know, maybe more visibility or maybe higher profile is is the ransomware attacks, right? So we've seen, you know, kind of this thing really interesting continuation of different types of security threats between just the the local kid who's just trying to do it because it's fun versus, you know, competitive stuff where people are trying to take out their competitors versus nation states and nation states being, um, you know, kind of driving these attacks. But the ransom, the ransom where we've seen before, but it seems to be increasing in frequency. Maybe we're just hearing about it. What's special about ransom, where as a specific type of security threat. >>So I started this practice about five years ago, and at that point, ransom or was just barely a blip, it was really about destruction and the way that we talk about it in the cybersecurity spaces. There's this triad, these three components of our data that we're trying to protect. So one of those is confidentiality, and that traces back to the attacks you're talking about. That's when somebody steals your data. You don't want them to do that. That breaks the confidentiality of the data. And that's really where the cybersecurity controls kind of grew up around, that you didn't want credit cards, intellectual property, healthcare information. And that's still a problem with ransom, where they're affecting the availability of the data or the integrity of the data. And those were the other two prongs that go with confidentiality. And so these attacks. That's why they feel different. Their impact in your ability to access the data, which in many cases can shut a business down. There have been headlines over the last couple of months. Some businesses that really were closed off for components of their business that were shut down, and it's because they didn't have their data or their systems, and then eventually they either found a way to recover them. Or perhaps in many cases, the speculation is they paid the ransom to get the data back, >>right. And of course, the problem with ever paying a ransom, um, is that you don't necessarily know you're going to get the data back. That you may just be encouraging them to hit you again. Eso paying the ransom is is not necessarily the best solution. And then then, in talking about this thing, turns out that in fact, not only may it not be the right solution, you may be breaking the law. This is a pretty interesting thing. I had no idea that there's really laws dictating, you know, I guess responding to a criminal threat. What? Where does that go? What's that from? >>Yeah, that's we've talked about this for a while. But it wasn't until about two weeks ago that some information was released from the Department of Treasury. So the idea here is that every not every country, many countries, the US among them have lists of countries and organizations that you can't do business with. So essentially a prohibited or sanctions list. And, as it turns out, many of the ransomware bad actors and Jeff is actually real name of one of them evil court. It sounds like a movie or a book, but that's one of the ransomware bad actors there on those lists. So if you get attacked by an organization that's on the list and you pay them. You have now completed a transaction with a prohibited entity and you're subject to potential sanctions. There was a lot written about this being a new law, or the US came up with this law, and that's not the case. The laws have been on the books for a while. It was the Department of Treasury, kind of issuing some guidance, just nudging people. Hey, by the way, you shouldn't be doing this and some of the research I've done a lot of countries have these laws. So while it's just the US that came out with this advisory, which was very public and certainly a big wake up call, these laws exist in a lot of other countries. So organizations really need to be prepared for what they're going to do if they get hit with the Ransomware attack. Not really counting on paying the ransom for the reasons that you said, Plus, it may be against the law. >>And just to make sure I understand you, it's against the law because you're effectively doing business by having a financial transaction with one of these, prohibited either organizations or they're in a prohibited country complete. >>That's correct Yeah, mostly about the organization, um, and then an interesting component of this and we won't get into too much of the weeds on the legal side. But the law is actually a strict liability. So that means it doesn't matter whether you knew or should have known that the entity was on a prohibited list. The mere fact of having that transaction makes you liable. And then the way that the the regulations are written, you can't get someone else to do your dirty work for you. So if you are facilitating that transaction anyway, you may be running afoul of those laws. >>Jesus. One more thing to worry about where you're trying to get business. You're trying to get your business back up and running, but specifically with with with ransomware and why it's different. I mean, there's been business continuity, planning forever. You know, you guys have backup and recovery solutions. Uh, you know, there's so much effort around that What's different here? Is it just because of the time in which you have to respond the availability of those backups toe to come back and get in production? What makes Ransomware so special from a business continuity perspective besides the fact that you're not allowed to pay him because it might be breaking the law. >>Ah, lot, You hit on a couple things there. So we've known forever that with D R. Disaster recovery One of the major things you're doing there is your replicating data quickly so that if you lose sight A you can pop up its site B With ransomware, you're replicating the corrupted data, so you lose that with backups. The bad guys know, just like you mentioned that if you have a backup, you could use that to recover. So they are more frequently now gathering their credentials and attacking the backup. So many cases we see the backups being deleted or otherwise destroyed. And that's really where we have focused with our power. Protect cyber recovery solution is creating a new, extra offline air gapped copy of the most critical applications. That's not going to be susceptible to the attack or the follow up attack that deletes the data. >>So let's jump into that a little bit, um, in a little bit more detailed. So this is a special solution, really targeted, um, as a defense against Ransomware because of the special attributes that ransom where, uh, e guess threatens threatens or the fact that they they also go after your backup in recovery at the same time, knowing you're gonna use that to basically lower the value of their ransom attack. That's crazy. >>Yeah, they're smart. You know, these these Attackers air smart. There's billions of dollars at stake. E think organizations like Evil Corp estimates are they could be making hundreds of millions of dollars. So they're they're not even small businesses. They're almost industries unto themselves. They have advanced tactics, They're leveraging capabilities, and they have. They have products, essentially. So when you think about your production data, your backups, your disaster recovery, those air, all in environments, that they're not accessible on the Internet. But that's where you're doing business. So there is access there. There's employees that have access, and the bad guys find ways to get in through spear phishing attacks, where they're sending emails that look like they're from somebody else and they get a foothold. Once they have that foothold, they can leverage that access to get throughout that production environment. They have access to that data, and they deleted with cyber recovery. What we're doing is we're creating a vaulted environment that's offline. They can't get there from from where they are, so they can't get access to that data. We lock it down, we analyze it, we make sure that it's good and then this happens automatically and day over day. So you've always got that copy of data. If your worst case scenario develops and you lose your production environment, that happens. You've got this copy of data for your most critical applications. You don't want to copy everything in there, but you can use to actually recover and that recover capability. Jeff is one of the pillars of a cyber security structure, so we focus a lot, kind of like you said before. What's different about these attacks? We focus a lot on protecting data and detecting bad guys. This is the recover capability that is part of all these frameworks, >>right? So there's a lot to unpack there before we get into the recovery. And kinda actually, why don't we just start there and then I want to get into the air gap because that's a great That's a great thing to dig in on the recovery what's kind of your targeted s l A Is it based on the size of the application? Um, is it based on on, you know, a different level of service. I mean, what is what is the hope? If I buy into this this solution that I can get my recovery and get back into business if I choose, not toe to pay these guys? What? What does it? What does that kind of look like? >>Most of the time, we're providing a product that our customers are deploying, and then we have some partners that will deployed as a service to, so the SLS may vary, but what we're targeting is a very secure environment, and you can look at how it's architected and think about the technologies. If it's properly operated, you can't get there. You can't get to the data. So the points that we're really looking at is how frequently do we want to update that data? So in other words, how much data can you afford to lose? And then how long will it take you to recover? And both of those? You can leverage the technologies to shorten those up to kind of your requirements. So loosely speaking, the in the shorter you make the time may cost you a little bit more money, a little bit more effort. But you can tighten those up pretty much what your requirements are going to be, >>right? Right? And then let's talk about air gaps because air gaps. That means something very, very specific. It literally means classically right, an air gap. There is a space in between these systems until electrons learn how to jump. Um, they're they're they're physically separated. Um, but that's harder and harder to do, right, because everything is now a P I based, and everything is an app that's based on a bunch of other APS, and there's calls and there's, you know, everything is so interconnected now. But you talked about something specifically said, an automated air gap. And you also said that you know, we're putting this data where it is not connected for some period of time. So I wonder if you could explain a little bit more detail how that works, how it's usually configured, um t to reintroduce an air gap into this crazy connected world. >>Yeah, it's kind of going backward to go forward in a lot of ways. When we're careful about the term, we'll use the term logical air gap because you're right, Jeff on Air Gap is there's a gap, and what we're doing is we're manipulating that air gap in a way that most of the time that data are are safe. Data are vaulted, data is on the other side of the air gap, so you can't get there. But we'll bring it up in air. Gap will logically enable that air gap so that there is a connection which enables us to update the data that's in the vault, and then we'll bring that connection back down. And the way that we've architected the solution is that even when it's enabled like that, we've minimized the capability to get into the vault. So, really, if you're a bad actor, if you know everything that's going on, you might be able to prevent the update. But you can't get into the vault unless you're physically there. And, of course, we put some controls on that so that even insiders are very limited what they can do if they get inside the vault and the A. P. T s, the advanced persistent threats. People who are coming from other countries. Since they're not physically there, they can't access that data. >>That's good. So it's on its off, but it's usually off most of the time, so the bad guys can't get across there. >>Yeah, and again it's It's important that even when it's on it za minimal exposure there. So you think about our triad, the confidentiality, integrity, availability. You know, we're blocking them from getting in so they can maybe do a denial of service type of attack. But that's it. They can't get into break into the vault and break things and destroy the data like they would in production. >>I want to shift gears a little bit gym, and I've I've gone to our essay, I think, for the last three or four years of fact, I think it was the last big live event we did in 2020 before everything came to a screeching halt. And, you know, one of the things I find interesting about the security industry is this one of these opportunities for cooperative Shin um within the security industry that even though you might work for a company that competes with another company. You know there's opportunities to work with your peers at other companies. So you have more of a unified front against the bad guys as well as learn from what's going on. Uh, with some of the other you know, people. So you can learn from the from the attacks that they're surfacing. There's interesting, uh, organization called Sheltered Harbor that it came across and doing research for this. You guys have joined it. It was basically it looks like it was built around 100 30. This this article is from earlier in the years. Probably groaning is from February 130 participating financial institutions, which collectively hold 72% of all deposit accounts and 71% of all U. S retail brokerage assets. It's a big organization focused on security, Del joined not as a financial institution but as a vendor. I wonder if you can share what this organizations all about. Why did you guys join and what? Where you see some of the benefits both for you as well as your customers? >>Yeah, there's a lot there, Jeff. I've been part of that process for a little bit over two years and kicked it off after we identified. Sheltered Harbor is an organization that we wanted to work with. So, as you said, founded by some of the banks and credit unions and other financial institutions in the US, and what's unique about it is it's designed to protect the U. S. Financial system and consumer confidence. It's not actually designed to protect the bank. So of course, that's an outcome there if you're protecting consumer confidence than it's better for the banks. But that's really the goal. And so it's a standards based organization that looked at the problem of what happens if a bank it's attacked, what happens to the customers. So they actually came up with the specifications, which follows so closely to what we do with cyber recovery. They identified important data. They built requirements, not technologies, but capabilities that a vault would need to have to protect that data. And then the process is to recover that data if an event occurred. So we talked to the team for a while. We're very proud of what we've been able to accomplish with them is the only solution provider in their advisory program, and the work that we've done with the power protect cyber recovery solution. We have some more news coming out. I'm not permitted toe announce it yet. It's pretty soon, so stay tuned, and it's just been a really great initiative for us to work with, and the team over there is fantastic. >>So I just one or two. If you can share your thoughts as as the role of security has changed over the last several years from, you know, kind of a perimeter based point of view and you know, protection and walls and, uh, firewalls and and and all these things which is completely broken down now to more of a integrated security approach and baking security into your data to your encryption to your applications, your access devices, etcetera and really integrating security more into the broader flow of product development and and delivery and and how that's impacted the security of the of the customers and impacted professionals like you that are trying to look down the road and get ahead of the next. You know, kind of two or three bad things that are coming. How is that security posture really benefited everybody out there? >>It gets a really difficult problem that we just keep working at it again. We don't have a goal, because if we're targeting here, the threat actors is a bad actors. They're gonna be here. I was reading an article today about how they're already the bad actors already employing machine learning to improve what they're doing and how they target their phishing attacks and things like that. So thinking about things like security by design is great. We have millions billions of devices, and if we start from the ground up that those devices have security built in, it makes the rest of the job a lot easier. But that whole integration process is really important to I mentioned before the recovery capability and protect and detect Well, if you look at the nice cybersecurity framework has five pillars that have capabilities within each one, and we need to keep focusing on our capabilities in those space, we can't do one and not the other. So we do multi factor authentication. But we need to look at encryption for our devices. We need to build from the ground up. We need to have those recover capabilities. It's just kind of a never ending process. But I feel like one of the most important things that we've done over the last year, partly driven by the changes that we've had, is that we're finally recognizing that cyber security is a business issue. It's not a nightie issue. So if your digital and your assets are digital, how can you confine this to a nightie group? It's It's the business. It's risk. Let's understand what risk is acceptable cover the risk that isn't and treated like a business process that it ISS. >>That's great, because because I always often wonder, you know, if you think of it as an insurance problem, you know, then you're gonna be in trouble because you can't You can't just lock everything down, right? You gotta you gotta do business. And you always think of the, you know, ships or safest, uh, at harbor. But that's not what ships are built for, right? You can't just lock everything down, but if you take it more of a business approach, so you're you're measuring investments and risk and putting dollar amounts on it. Then you can start to figure out how much should I invest in security because you can't spend ah, 100% of your revenue on security. What is the happy medium? How do you decide and how do you apply that investment where, you know, it's kind of a portfolio strategy problem >>it is. And and that's one of the areas that again my five years in the building, the practice we've seen organizations start to move to. So you want to protect your most important assets the best. And then there are things that you still want to protect, but you can't afford the time, the budget, the operational expense of protecting everything. So let's understand what really drives this business if I'm a law firm might be my billion and document management systems and health care. It's a electronic medical record and manufacturing the manufacturing systems. So let's protect the most important things the best and then kind of moved down from there. We have to understand what those systems are before we can actually protect them. And that's where the business really needs to work more closely. And they are with the I T teams with cyber security teams, >>right, and like, I like a lot of big problems, right? You gotta break it down. You gotta You gotta prioritize. You gotta, you know, start just knocking off what's important and not so overwhelmed by, you know, trying to protect everything to the same degree. This is not practical, and it's not not a good investment. >>That's exactly the case. And there's the ongoing discussions about shortage of people in the cybersecurity space, which there are. But there are things that we can do that to really maximize what those people do, get them to focus on the higher level capabilities and let the tools do some of the things that the tools air good at. >>Right. So, you know, you triggered one last point and we'll wrap on this, but I'll give you the last word. Aziz, you look forward. Two things like automation and two things like artificial intelligence and machine learning that you can apply to make those professionals more effective on automate some stuff. Um, how do you see that evolving? And does that give you big smiles or frowns as you think about your use of AI in a nml versus the bad guys, they have some of the same tools as well. >>They dio and look, we have to use those to keep up. I'll give you example with with power, protect cyber recovery. We already use AI and ML to analyze the data that's in our vault. So how do you know that the data is good? We're not gonna have somebody in the vault looking through the files by leveraging those capabilities. We could give a verdict on that data. And so you know that it's good. I think we we have to continue to be careful that we understand what the tools are. We deploy them in the right way. You can't deploy tool just to deploy honor because it's hot or because it's interesting that goes back to understanding the systems that we need to protect the risks that we can accept or perhaps cover with insurance and the risks that gosh, we really can't accept. We need to make sure that the business continues to operate here, so I think it's great. Um, the communities have really come together. There's more information sharing than ever has gone on. And that's really one of our big weapons against the bad actors. >>All right, Well, Jim, thank you so much for sharing your insight. I think your job security is locked in for the foreseeable future. We didn't even get into five G and I o t and ever increasing attack, surface and sophistication of the bad guys. So thank you for doing what you do and helping keep us safe. Keep your data safe and keeping our companies running. >>Thank you for the opportunity. >>Alright, He's Jim. Mom. Jeff. Thanks for watching the cubes. Continuous coverage of Dell Technology World 2020. The Digital Experience. Thanks for watching. We'll see you next time.

>>Hey, everyone, Thanks for taking them to join the story. Hope you and your loved ones are safe during these tough times. Let me start by introducing myself. My name is Michelle. When I walk for GlaxoSmithKline, GSK as an engineering manager in my current role, A little protocol platform A P s, which is part of the already data platform here in G S, K R and D Tech. I live in Dallas, Texas. I have a Masters degree in computer science on a bachelor's in electronics and communication engineering. I started my career as a software developer on over these years again a lot of experience in leading and building, not scale and predicts products and solutions. I also have a complete accountability for container platforms here at GSK or any tick. I've been working very closely with Dr Enterprise, which is no Miranda's for more than three years to enable container platforms that yes, came on mainly in our own Itek. So that's me. Let >>me give you a quick overview on agenda for today's talk. I'll start with what we do here at GSK on what is RND data platform. Then I'll give you an overview on What are the business drivers that >>motivated US toe? Take this container Germany on some insight into learnings on accomplishments over these years. Working with Dr Enterprise on the container platforms Lately, you must have seen a lot of articles off there which talk about how ts case liberating technologies like artificial intelligence, mission learning, UN data and analytics for the Douglas Corey process. I'm very excited to see the progress we have made in technology, but what makes us truly unique is our commitment to the patient. >>We're G escape, help millions of people, do more, feel better and live longer. Wear a global company that is focused on three were tickles pharmaceuticals vaccines on consumer healthcare. Our main intent is to lower the >>burden on the impact of diseases on the patients. Here at GSK, we allow science to drive the technology. This helps us toe build innovative products. That's helps our scientists to make better and faster additions throughout the drug discovery by plane. >>With that, let me give you some >>context on what currently data platform is how it is enabled. A T escape started in mid 2016. What used to be called us are any information platform whose main focus was to centralize curate on rationalized all the data produced within the others are in the business systems in orderto drive, a strategic business value, standardization of clinical trials, Genome Wide Association Study Analysis, also known as Jesus Storage and Crossing Off Rheal. World Evidence data some of the examples off how the only platform was used to deliver the business value four years later. No, a new set off business rivals of changing our landscape. The irony Information Platform is evolving to be a hybrid, multi cloud solution and is known as already did a platform refering to 20 >>19 GSK's annual report. These are the four teams that there are any platform will be mainly focused on. We're expanding our data capabilities to support the use. Escape by a former company on evolving into a hybrid medical platform is one of the many steps that we're taking to be future ready. Our key focus will still be making >>greater recommendations better and faster by using that wants us. We're making the areas like artificial intelligence and machine learning. No doc brings us toe. What is Germany is important. Why are we taking this German with that? Let me take you to the next topic off. Like the process of discovery, Francisco is not an easy process. Talking about the recent events occurred over the last few months on the way. How all our lives are impacted. It is a lot of talk on information going about. Why did drug discovery process is so tough working for a global health care company? I get asked this question very frequently. From many people I interact with. Question is like, Why is that? This car is so tough on why it takes so much time. Drug discovery is a complex process that involves multiple different stages on at each and every stage. There is huge amounts of data that the scientists have took process to make some decisions. Studies have shown that only 3% off small molecules entering the human studies actually become medicines. If you're new to drug discovery, you may ask, like what is the targets? Targets so low? We humans are very complex species, >>not going into the details of the process. We're G escape >>have made a lot of investments into technology that enabled us to make data river conditions. Throw the drug Discovery pipeline >>as we implement. As we started implementing these tools and technologies to enable already did a platform, we started to get a better appreciation off how these tools in track on integrate >>with each other. Our goal wants to make this platform a jail, the platform that can work at scale so that we can provide a great user experience and contribute back to the bread discovery pipeline so that the scientists can make faster editions. We want our ardently users to consume the data, and the service is available on the platform seamlessly in a self service fashion. And we also have to accomplish this by establishing trust. And then we have to end also enable the academic partnerships, acquisitions, collaborations that DSK has, which actually brings a lot of data on value to our scientists. So when we talk about so many collaborations and a lot of these systems, what this brings in is wide range off systems and platforms that are fundamentally built on different infrastructure. This is where Doctor comes into fiction on our containers significance. >>We have realized the power of containers on how we can simplify this complex ecosystem by using containers and provide a faster access off data to war scientists who didn't go >>back and contribute back to the drug discovery by play. >>With that, let me take talk to you about >>the containers journey and she escaped. So we started our container journey in late 2017. We started working with Dr Enterprise to enable the container platform. This is on our on prem infrastructure Back then, or first year or so we walked through multiple Pelosis did a lot of testing to make sure our platform is stable before we onboard either the data or the user applications. I was part of this complete journey on Dr Stream has worked with us very closely towards you. The first milestone off establishing a stable container platform. A tsk. Now, getting into 2019 we started deploying our applications in production environment. I cannot go into the details of what this Absar, but they do include both data pipelines as well as Web services. You know, initial days we have worked a lot on swamp, but in 2019 is when we started looking into communities in the same year, we enable kubernetes orchestration on the doctor and replace platform here at GSK and also made it as a de facto orchestra coming into 2020. All our micro service applications are undead. A pipelines are migrated to the container platforms on all of these are orchestrated by Cuban additional on these air applications that are running in production. As of today, we have made the container forced approach as an architectural standard across already taking GSK. We also started deploying our AML training models onto containers on All this work is happening on our Doctor Enterprise platform. Also as part off are currently platforms hybrid multicolored journey. We started enabling container and kubernetes based platforms on public clubs. Now going into 2021 on future. Enabling our RND users to easily access data and applications in a platform agnostic way is very crucial for our success because previously we had only onto him. Now we have public clothes that are getting involved on One of >>the many steps we're taking through this journey is to >>watch allies the data on ship data and containers or kubernetes volumes on demand to our our end users of scientists. And this allows us to deliver data to our scientists wherever they want in a very security on. We're leveraging doctor to do it. So that's >>our future. Learning on with that, let's take a deep dive into fuel for >>our accomplishments over these years. I want to start with a general demand and innovative one very interesting use case that we developed on Dr. This is a rapid prototyping capability that enabled our scientists seamlessly to Monday cluster communication. This was one off the biggest challenges which way his face for a long time and with the help of containers, were able to solve this on provide this as a capability to our scientists. We actually have shockers this capability in one of the doctor conferences before next. As I've said before, by migrating all over web services into containers, we not only achieved horizontal scalability for those specific services, but also saved more than 50% in support costs for the applications which we have migrated by making Docker image as an immutable artifact In our bill process, we are now able to deploy our APS or models in any container or Cuban, its base platform, either in on Prem or in a public club. We also made significant improvements towards the process. A not a mission By leveraging docker containers, containers have played a significant role in keeping US platform agnostic and thus enabling our hybrid multi cloud Germany valuable for out already did scientists. As I mentioned before, data virtualization is another viewpoint we have in terms off our next steps off where we want to take kubernetes on where we wanna leverage open it. Us. What you see here are just a few off many accomplishments which we have our, um, achieved by using containers for the past three years or so. So with that before I close all the time and acknowledge all our internal partners who has contributed a lot to this journey mainly are in the business are on the deck on the broader take. Organizations that escape also want to time document present Miranda's for being such a great partner throughout this journey and also giving us an opportunity to share this success story today. Lastly, thanks for everyone to listening to the stop and please feel free to reach out. If you have any questions or suggestions, let's be fit safe. Thank you

hello everybody and thank you for joining us today for the virtual verdict of BBC 2020 today's breakout session is entitled the shortest path to Vertica best practices for data warehouse migration ETL I'm Jeff Healey I'll leave verdict and marketing I'll be your host for this breakout session joining me today are Marco guesser and Mauricio lychee vertical product engineer is joining us from yume region but before we begin I encourage you to submit questions or comments or in the virtual session don't have to wait just type question in a comment in the question box below the slides that click Submit as always there will be a Q&A session the end of the presentation will answer as many questions were able to during that time any questions we don't address we'll do our best to answer them offline alternatively visit Vertica forums that formed at vertical comm to post your questions there after the session our engineering team is planning to join the forums to keep the conversation going also reminder that you can maximize your screen by clicking the double arrow button and lower right corner of the sides and yes this virtual session is being recorded be available to view on demand this week send you a notification as soon as it's ready now let's get started over to you mark marco andretti oh hello everybody this is Marco speaking a sales engineer from Amir said I'll just get going ah this is the agenda part one will be done by me part two will be done by Mauricio the agenda is as you can see big bang or piece by piece and the migration of the DTL migration of the physical data model migration of et I saw VTL + bi functionality what to do with store procedures what to do with any possible existing user defined functions and migration of the data doctor will be by Maurice it you want to talk about emeritus Rider yeah hello everybody my name is Mauricio Felicia and I'm a birth record pre-sales like Marco I'm going to talk about how to optimize that were always using some specific vertical techniques like table flattening live aggregated projections so let me start with be a quick overview of the data browser migration process we are going to talk about today and normally we often suggest to start migrating the current that allows the older disease with limited or minimal changes in the overall architecture and yeah clearly we will have to port the DDL or to redirect the data access tool and we will platform but we should minimizing the initial phase the amount of changes in order to go go live as soon as possible this is something that we also suggest in the second phase we can start optimizing Bill arouse and which again with no or minimal changes in the architecture as such and during this optimization phase we can create for example dog projections or for some specific query or optimize encoding or change some of the visual spools this is something that we normally do if and when needed and finally and again if and when needed we go through the architectural design for these operations using full vertical techniques in order to take advantage of all the features we have in vertical and this is normally an iterative approach so we go back to name some of the specific feature before moving back to the architecture and science we are going through this process in the next few slides ok instead in order to encourage everyone to keep using their common sense when migrating to a new database management system people are you often afraid of it it's just often useful to use the analogy of how smooth in your old home you might have developed solutions for your everyday life that make perfect sense there for example if your old cent burner dog can't walk anymore you might be using a fork lifter to heap in through your window in the old home well in the new home consider the elevator and don't complain that the window is too small to fit the dog through this is very much in the same way as Narita but starting to make the transition gentle again I love to remain in my analogy with the house move picture your new house as your new holiday home begin to install everything you miss and everything you like from your old home once you have everything you need in your new house you can shut down themselves the old one so move each by feet and go for quick wins to make your audience happy you do bigbang only if they are going to retire the platform you are sitting on where you're really on a sinking ship otherwise again identify quick wings implement published and quickly in Vertica reap the benefits enjoy the applause use the gained reputation for further funding and if you find that nobody's using the old platform anymore you can shut it down if you really have to migrate you can still go to really go to big battle in one go only if you absolutely have to otherwise migrate by subject area use the group all similar clear divisions right having said that ah you start off by migrating objects objects in the database that's one of the very first steps it consists of migrating verbs the places where you can put the other objects into that is owners locations which is usually schemers then what do you have that you extract tables news then you convert the object definition deploy them to Vertica and think that you shouldn't do it manually never type what you can generate ultimate whatever you can use it enrolls usually there is a system tables in the old database that contains all the roads you can export those to a file reformat them and then you have a create role and create user scripts that you can apply to Vertica if LDAP Active Directory was used for the authentication the old database vertical supports anything within the l dubs standard catalogued schemas should be relatively straightforward with maybe sometimes the difference Vertica does not restrict you by defining a schema as a collection of all objects owned by a user but it supports it emulates it for old times sake Vertica does not need the catalog or if you absolutely need the catalog from the old tools that you use it it usually said it is always set to the name of the database in case of vertical having had now the schemas the catalogs the users and roles in place move the take the definition language of Jesus thought if you are allowed to it's best to use a tool that translates to date types in the PTL generated you might see as a mention of old idea to listen by memory to by the way several times in this presentation we are very happy to have it it actually can export the old database table definition because they got it works with the odbc it gets what the old database ODBC driver translates to ODBC and then it has internal translation tables to several target schema to several target DBMS flavors the most important which is obviously vertical if they force you to use something else there are always tubes like sequel plots in Oracle the show table command in Tara data etc H each DBMS should have a set of tools to extract the object definitions to be deployed in the other instance of the same DBMS ah if I talk about youth views usually a very new definition also in the old database catalog one thing that you might you you use special a bit of special care synonyms is something that were to get emulated different ways depending on the specific needs I said I stop you on the view or table to be referred to or something that is really neat but other databases don't have the search path in particular that works that works very much like the path environment variable in Windows or Linux where you specify in a table an object name without the schema name and then it searched it first in the first entry of the search path then in a second then in third which makes synonym hugely completely unneeded when you generate uvl we remained in the analogy of moving house dust and clean your stuff before placing it in the new house if you see a table like the one here at the bottom this is usually corpse of a bad migration in the past already an ID is usually an integer and not an almost floating-point data type a first name hardly ever has 256 characters and that if it's called higher DT it's not necessarily needed to store the second when somebody was hired so take good care in using while you are moving dust off your stuff and use better data types the same applies especially could string how many bytes does a string container contains for eurozone's it's not for it's actually 12 euros in utf-8 in the way that Vertica encodes strings and ASCII characters one died but the Euro sign thinks three that means that you have to very often you have when you have a single byte character set up a source you have to pay attention oversize it first because otherwise it gets rejected or truncated and then you you will have to very carefully check what their best science is the best promising is the most promising approach is to initially dimension strings in multiples of very initial length and again ODP with the command you see there would be - I you 2 comma 4 will double the lengths of what otherwise will single byte character and multiply that for the length of characters that are wide characters in traditional databases and then load the representative sample of your cells data and profile using the tools that we personally use to find the actually longest datatype and then make them shorter notice you might be talking about the issues of having too long and too big data types on projection design are we live and die with our projects you might know remember the rules on how default projects has come to exist the way that we do initially would be just like for the profiling load a representative sample of the data collector representative set of already known queries from the Vertica database designer and you don't have to decide immediately you can always amend things and otherwise follow the laws of physics avoid moving data back and forth across nodes avoid heavy iOS if you can design your your projections initially by hand encoding matters you know that the database designer is a very tight fisted thing it would optimize to use as little space as possible you will have to think of the fact that if you compress very well you might end up using more time in reading it this is the testimony to run once using several encoding types and you see that they are l e is the wrong length encoded if sorted is not even visible while the others are considerably slower you can get those nights and look it in look at them in detail I will go in detail you now hear about it VI migrations move usually you can expect 80% of everything to work to be able to live to be lifted and shifted you don't need most of the pre aggregated tables because we have live like regain projections many BI tools have specialized query objects for the dimensions and the facts and we have the possibility to use flatten tables that are going to be talked about later you might have to ride those by hand you will be able to switch off casting because vertical speeds of everything with laps Lyle aggregate projections and you have worked with molap cubes before you very probably won't meet them at all ETL tools what you will have to do is if you do it row by row in the old database consider changing everything to very big transactions and if you use in search statements with parameter markers consider writing to make pipes and using verticals copy command mouse inserts yeah copy c'mon that's what I have here ask you custom functionality you can see on this slide the verticals the biggest number of functions in the database we compare them regularly by far compared to any other database you might find that many of them that you have written won't be needed on the new database so look at the vertical catalog instead of trying to look to migrate a function that you don't need stored procedures are very often used in the old database to overcome their shortcomings that Vertica doesn't have very rarely you will have to actually write a procedure that involves a loop but it's really in our experience very very rarely usually you can just switch to standard scripting and this is basically repeating what Mauricio said in the interest of time I will skip this look at this one here the most of the database data warehouse migration talks should be automatic you can use you can automate GDL migration using ODB which is crucial data profiling it's not crucial but game-changing the encoding is the same thing you can automate at you using our database designer the physical data model optimization in general is game-changing you have the database designer use the provisioning use the old platforms tools to generate the SQL you have no objects without their onus is crucial and asking functions and procedures they are only crucial if they depict the company's intellectual property otherwise you can almost always replace them with something else that's it from me for now Thank You Marco Thank You Marco so we will now point our presentation talking about some of the Vertica that overall the presentation techniques that we can implement in order to improve the general efficiency of the dot arouse and let me start with a few simple messages well the first one is that you are supposed to optimize only if and when this is needed in most of the cases just a little shift from the old that allows to birth will provide you exhaust the person as if you were looking for or even better so in this case probably is not really needed to to optimize anything in case you want optimize or you need to optimize then keep in mind some of the vertical peculiarities for example implement delete and updates in the vertical way use live aggregate projections in order to avoid or better in order to limit the goodbye executions at one time used for flattening in order to avoid or limit joint and and then you can also implement invert have some specific birth extensions life for example time series analysis or machine learning on top of your data we will now start by reviewing the first of these ballots optimize if and when needed well if this is okay I mean if you get when you migrate from the old data where else to birth without any optimization if the first four month level is okay then probably you only took my jacketing but this is not the case one very easier to dispute in session technique that you can ask is to ask basket cells to optimize the physical data model using the birth ticket of a designer how well DB deal which is the vertical database designer has several interfaces here I'm going to use what we call the DB DB programmatic API so basically sequel functions and using other databases you might need to hire experts looking at your data your data browser your table definition creating indexes or whatever in vertical all you need is to run something like these are simple as six single sequel statement to get a very well optimized physical base model you see that we start creating a new design then we had to be redesigned tables and queries the queries that we want to optimize we set our target in this case we are tuning the physical data model in order to maximize query performances this is why we are using my design query and in our statement another possible journal tip would be to tune in order to reduce storage or a mix between during storage and cheering queries and finally we asked Vertica to produce and deploy these optimized design in a matter of literally it's a matter of minutes and in a few minutes what you can get is a fully optimized fiscal data model okay this is something very very easy to implement keep in mind some of the vertical peculiarities Vaska is very well tuned for load and query operations aunt Berta bright rose container to biscuits hi the Pharos container is a group of files we will never ever change the content of this file the fact that the Rose containers files are never modified is one of the political peculiarities and these approach led us to use minimal locks we can add multiple load operations in parallel against the very same table assuming we don't have a primary or unique constraint on the target table in parallel as a sage because they will end up in two different growth containers salad in read committed requires in not rocket fuel and can run concurrently with insert selected because the Select will work on a snapshot of the catalog when the transaction start this is what we call snapshot isolation the kappa recovery because we never change our rows files are very simple and robust so we have a huge amount of bandages due to the fact that we never change the content of B rows files contain indiarose containers but on the other side believes and updates require a little attention so what about delete first when you believe in the ethica you basically create a new object able it back so it appeared a bit later in the Rose or in memory and this vector will point to the data being deleted so that when the feed is executed Vertica will just ignore the rules listed in B delete records and it's not just about the leak and updating vertical consists of two operations delete and insert merge consists of either insert or update which interim is made of the little insert so basically if we tuned how the delete work we will also have tune the update in the merge so what should we do in order to optimize delete well remember what we said that every time we please actually we create a new object a delete vector so avoid committing believe and update too often we reduce work the work for the merge out for the removal method out activities that are run afterwards and be sure that all the interested projections will contain the column views in the dedicate this will let workers directly after access the projection without having to go through the super projection in order to create the vector and the delete will be much much faster and finally another very interesting optimization technique is trying to segregate the update and delete operation from Pyrenean third workload in order to reduce lock contention beliefs something we are going to discuss and these contain using partition partition operation this is exactly what I want to talk about now here you have a typical that arouse architecture so we have data arriving in a landing zone where the data is loaded that is from the data sources then we have a transformation a year writing into a staging area that in turn will feed the partitions block of data in the green data structure we have at the end those green data structure we have at the end are the ones used by the data access tools when they run their queries sometimes we might need to change old data for example because we have late records or maybe because we want to fix some errors that have been originated in the facilities so what we do in this case is we just copied back the partition we want to change or we want to adjust from the green interior a the end to the stage in the area we have a very fast operation which is Tokyo Station then we run our updates or our adjustment procedure or whatever we need in order to fix the errors in the data in the staging area and at the very same time people continues to you with green data structures that are at the end so we will never have contention between the two operations when we updating the staging area is completed what we have to do is just to run a swap partition between tables in order to swap the data that we just finished to adjust in be staging zone to the query area that is the green one at the end this swap partition is very fast is an atomic operation and basically what will happens is just that well exchange the pointer to the data this is a very very effective techniques and lot of customer useless so why flops on table and live aggregate for injections well basically we use slot in table and live aggregate objection to minimize or avoid joint this is what flatten table are used for or goodbye and this is what live aggregate projections are used for now compared to traditional data warehouses better can store and process and aggregate and join order of magnitudes more data that is a true columnar database joint and goodbye normally are not a problem at all they run faster than any traditional data browse that page there are still scenarios were deficits are so big and we are talking about petabytes of data and so quickly going that would mean be something in order to boost drop by and join performances and this is why you can't reduce live aggregate projections to perform aggregations hard loading time and limit the need for global appear on time and flux and tables to combine information from different entity uploading time and again avoid running joint has query undefined okay so live aggregate projections at this point in time we can use live aggregate projections using for built in aggregate functions which are some min Max and count okay let's see how this works suppose that you have a normal table in this case we have a table unit sold with three columns PIB their time and quantity which has been segmented in a given way and on top of this base table we call it uncle table we create a projection you see that we create the projection using the salad that will aggregate the data we get the PID we get the date portion of the time and we get the sum of quantity from from the base table grouping on the first two columns so PID and the date portion of day time okay what happens in this case when we load data into the base table all we have to do with load data into the base table when we load data into the base table we will feel of course big injections that assuming we are running with k61 we will have to projection to projections and we will know the data in those two projection with all the detail in data we are going to load into the table so PAB playtime and quantity but at the very same time at the very same time and without having to do nothing any any particular operation or without having to run any any ETL procedure we will also get automatically in the live aggregate projection for the data pre aggregated with be a big day portion of day time and the sum of quantity into the table name total quantity you see is something that we get for free without having to run any specific procedure and this is very very efficient so the key concept is that during the loading operation from VDL point of view is executed again the base table we do not explicitly aggregate data or we don't have any any plc do the aggregation is automatic and we'll bring the pizza to be live aggregate projection every time we go into the base table you see the two selection that we have we have on in this line on the left side and you see that those two selects will produce exactly the same result so running select PA did they trying some quantity from the base table or running the select star from the live aggregate projection will result exactly in the same data you know this is of course very useful but is much more useful result that if we and we can observe this if we run an explained if we run the select against the base table asking for this group data what happens behind the scene is that basically vertical itself that is a live aggregate projection with the data that has been already aggregating loading phase and rewrite your query using polite aggregate projection this happens automatically you see this is a query that ran a group by against unit sold and vertical decided to rewrite this clearly as something that has to be collected against the light aggregates projection because if I decrease this will save a huge amount of time and effort during the ETL cycle okay and is not just limited to be information you want to aggregate for example another query like select count this thing you might note that can't be seen better basically our goodbyes will also take advantage of the live aggregate injection and again this is something that happens automatically you don't have to do anything to get this okay one thing that we have to keep very very clear in mind Brassica what what we store in the live aggregate for injection are basically partially aggregated beta so in this example we have two inserts okay you see that we have the first insert that is entered in four volts and the second insert which is inserting five rules well in for each of these insert we will have a partial aggregation you will never know that after the first insert you will have a second one so better will calculate the aggregation of the data every time irin be insert it is a key concept and be also means that you can imagine lies the effectiveness of bees technique by inserting large chunk of data ok if you insert data row by row this technique live aggregate rejection is not very useful because for every goal that you insert you will have an aggregation so basically they'll live aggregate injection will end up containing the same number of rows that you have in the base table but if you everytime insert a large chunk of data the number of the aggregations that you will have in the library get from structure is much less than B base data so this is this is a key concept you can see how these works by counting the number of rows that you have in alive aggregate injection you see that if you run the select count star from the solved live aggregate rejection the query on the left side you will get four rules but actually if you explain this query you will see that he was reading six rows so this was because every of those two inserts that we're actively interested a few rows in three rows in India in the live aggregate projection so this is a key concept live aggregate projection keep partially aggregated data this final aggregation will always happen at runtime okay another which is very similar to be live aggregate projection or what we call top K projection we actually do not aggregate anything in the top case injection we just keep the last or limit the amount of rows that we collect using the limit over partition by all the by clothes and this again in this case we create on top of the base stable to top gay projection want to keep the last quantity that has been sold and the other one to keep the max quantity in both cases is just a matter of ordering the data in the first case using the B time column in the second page using quantity in both cases we fill projection with just the last roof and again this is something that we do when we insert data into the base table and this is something that happens automatically okay if we now run after the insert our select against either the max quantity okay or be lost wanted it okay we will get the very last you see that we have much less rows in the top k projections okay we told at the beginning that basically we can use for built-in function you might remember me max sum and count what if I want to create my own specific aggregation on top of the lid and customer sum up because our customers have very specific needs in terms of live aggregate projections well in this case you can code your own live aggregate production user-defined functions so you can create the user-defined transport function to implement any sort of complex aggregation while loading data basically after you implemented miss VPS you can deploy using a be pre pass approach that basically means the data is aggregated as loading time during the data ingestion or the batch approach that means that the data is when that woman is running on top which things to remember on live a granade projections they are limited to be built in function again some max min and count but you can call your own you DTF so you can do whatever you want they can reference only one table and for bass cab version before 9.3 it was impossible to update or delete on the uncle table this limit has been removed in 9.3 so you now can update and delete data from the uncle table okay live aggregate projection will follow the segmentation of the group by expression and in some cases the best optimizer can decide to pick the live aggregates objection or not depending on if depending on the fact that the aggregation is a consistent or not remember that if we insert and commit every single role to be uncoachable then we will end up with a live aggregate indirection that contains exactly the same number of rows in this case living block or using the base table it would be the same okay so this is one of the two fantastic techniques that we can implement in Burtka this live aggregate projection is basically to avoid or limit goodbyes the other which we are going to talk about is cutting table and be reused in order to avoid the means for joins remember that K is very fast running joints but when we scale up to petabytes of beta we need to boost and this is what we have in order to have is problem fixed regardless the amount of data we are dealing with so how what about suction table let me start with normalized schemas everybody knows what is a normalized scheme under is no but related stuff in this slide the main scope of an normalized schema is to reduce data redundancies so and the fact that we reduce data analysis is a good thing because we will obtain fast and more brides we will have to write into a database small chunks of data into the right table the problem with these normalized schemas is that when you run your queries you have to put together the information that arrives from different table and be required to run joint again jointly that again normally is very good to run joint but sometimes the amount of data makes not easy to deal with joints and joints sometimes are not easy to tune what happens in in the normal let's say traditional data browser is that we D normalize the schemas normally either manually or using an ETL so basically we have on one side in this light on the left side the normalized schemas where we can get very fast right on the other side on the left we have the wider table where we run all the three joints and pre aggregation in order to prepare the data for the queries and so we will have fast bribes on the left fast reads on the Left sorry fast bra on the right and fast read on the left side of these slides the probability in the middle because we will push all the complexity in the middle in the ETL that will have to transform be normalized schema into the water table and the way we normally implement these either manually using procedures that we call the door using ETL this is what happens in traditional data warehouse is that we will have to coach in ETL layer in order to round the insert select that will feed from the normalized schema and right into the widest table at the end the one that is used by the data access tools we we are going to to view store to run our theories so this approach is costly because of course someone will have to code this ETL and is slow because someone will have to execute those batches normally overnight after loading the data and maybe someone will have to check the following morning that everything was ok with the batch and is resource intensive of course and is also human being intensive because of the people that will have to code and check the results it ever thrown because it can fail and introduce a latency because there is a get in the time axis between the time t0 when you load the data into be normalized schema and the time t1 when we get the data finally ready to be to be queried so what would be inverter to facilitate this process is to create this flatten table with the flattened T work first you avoid data redundancy because you don't need the wide table on the normalized schema on the left side second is fully automatic you don't have to do anything you just have to insert the data into the water table and the ETL that you have coded is transformed into an insert select by vatika automatically you don't have to do anything it's robust and this Latin c0 is a single fast as soon as you load the data into the water table you will get all the joints executed for you so let's have a look on how it works in this case we have the table we are going to flatten and basically we have to focus on two different clauses the first one is you see that there is one table here I mentioned value 1 which can be defined as default and then the Select or set using okay the difference between the fold and set using is when the data is populated if we use default data is populated as soon as we know the data into the base table if we use set using Google Earth to refresh but everything is there I mean you don't need them ETL you don't need to code any transformation because everything is in the table definition itself and it's for free and of course is in latency zero so as soon as you load the other columns you will have the dimension value valued as well okay let's see an example here suppose here we have a dimension table customer dimension that is on the left side and we have a fact table on on the right you see that the fact table uses columns like o underscore name or Oh the score city which are basically the result of the salad on top of the customer dimension so Beezus were the join is executed as soon as a remote data into the fact table directly into the fact table without of course loading data that arise from the dimension all the data from the dimension will be populated automatically so let's have an example here suppose that we are running this insert as you can see we are running be inserted directly into the fact table and we are loading o ID customer ID and total we are not loading made a major name no city those name and city will be automatically populated by Vertica for you because of the definition of the flood table okay you see behave well all you need in order to have your widest tables built for you your flattened table and this means that at runtime you won't need any join between base fuck table and the customer dimension that we have used in order to calculate name and city because the data is already there this was using default the other option was is using set using the concept is absolutely the same you see that in this case on the on the right side we have we have basically replaced this all on the school name default with all underscore name set using and same is true for city the concept that I said is the same but in this case which we set using then we will have to refresh you see that we have to run these select trash columns and then the name of the table in this case all columns will be fresh or you can specify only certain columns and this will bring the values for name and city reading from the customer dimension so this technique this technique is extremely useful the difference between default and said choosing just to summarize the most important differences remember you just have to remember that default will relate your target when you load set using when you refresh end and in some cases you might need to use them both so in some cases you might want to use both default end set using in this example here we'll see that we define the underscore name using both default and securing and this means that we love the data populated either when we load the data into the base table or when we run the Refresh this is summary of the technique that we can implement in birth in order to make our and other browsers even more efficient and well basically this is the end of our presentation thank you for listening and now we are ready for the Q&A session you

hi everybody thank you for joining us today for the virtual Vertica BBC 2020 today's breakout session is entitled Vertica and en mode at the trade desk my name is su LeClair director of marketing at Vertica and I'll be your host for this webinar joining me is Ron Cormier senior Vertica database engineer at the trade desk before we begin I encourage you to submit questions or comments during the virtual session you don't have to wait just type your question or comment in the question box below the slides and click submit there will be a Q&A session at the end of the presentation we'll answer as many questions as we're able to during that time any questions that we don't address we'll do our best to answer them offline alternatively you can visit vertical forums to post your questions there after the session our engineering team is planning to join the forums to keep the conversation going also a quick reminder that you can maximize your screen by clicking the double arrow button in the lower right corner of the slide and yes this virtual session is being recorded and will be available to view on demand this week we'll send you a notification as soon as it's ready so let's get started over to you run thanks - before I get started I'll just mention that my slide template was created before social distancing was a thing so hopefully some of the images will harken us back to a time when we could actually all be in the same room but with that I want to get started uh the date before I get started in thinking about the technology I just wanted to cover my background real quick because I think it's peach to where we're coming from with vertically on at the trade desk and I'll start out just by pointing out that prior to my time in the trade desk I was a tech consultant at HP HP America and so I traveled the world working with Vertica customers helping them configure install tune set up their verdict and databases and get them working properly so I've seen the biggest and the smallest implementations and everything in between and and so now I'm actually principal database engineer straight desk and and the reason I mentioned this is to let you know that I'm a practitioner I'm working with with the product every day or most days this is a marketing material so hopefully the the technical details in this presentation are are helpful I work with Vertica of course and that is most relative or relevant to our ETL and reporting stack and so what we're doing is we're taking about the data in the Vertica and running reports for our customers and we're an ad tech so I did want to just briefly describe what what that means and how it affects our implementation so I'm not going to cover the all the details of this slide but basically I want to point out that the trade desk is a DSP it's a demand-side provider and so we place ads on behalf of our customers or agencies and ad agencies and their customers that are advertised as brands themselves and the ads get placed on to websites and mobile applications and anywhere anywhere digital advertising happens so publishers are what we think ocean like we see here espn.com msn.com and so on and so every time a user goes to one of these sites or one of these digital places and an auction takes place and what people are bidding on is the privilege of showing and add one or more ads to users and so this is this is really important because it helps fund the internet ads can be annoying sometimes but they actually help help are incredibly helpful in how we get much much of our content and this is happening in real time at very high volumes so on the open Internet there is anywhere from seven to thirteen million auctions happening every second of those seven to thirteen million auctions happening every second the trade desk bids on hundreds of thousands per second um so that gives it and anytime we did we have an event that ends up in Vertica that's that's one of the main drivers of our data volume and certainly other events make their way into Vertica as well but that wanted to give you a sense of the scale of the data and sort of how it's impacting or how it is impacted by sort of real real people in the world so um the uh let's let's take a little bit more into the workload and and we have the three B's in spades late like many many people listening to a massive volume velocity and variety in terms of the data sizes I've got some information here some stats on on the raw data sizes that we deal with on a daily basis per day so we ingest 85 terabytes of raw data per day and then once we get it into Vertica we do some transformations we do matching which is like joins basically and we do some aggregation group buys to reduce the data and make it clean it up make it so it's more efficient to consume buy our reporting layer so that matching in aggregation produces about ten new terabytes of raw data per day it all comes from the it all comes from the data that was ingested but it's new data and so that's so it is reduced quite a bit but it's still pretty pretty high high volume and so we have this aggregated data that we then run reports on on behalf of our customers so we have about 40,000 reports per day oh that's probably that's actually a little bit old and older number it's probably closer to 50 or 55,000 reports per day at this point so it's I think probably a pretty common use case for for Vertica customers it's maybe a little different in the sense that most of the reports themselves are >> reports so they're not it's not a user sitting at a keyboard waiting for the result basically we have we we have a workflow where we do the ingest we do this transform and then and then once once all the data is available for a day we run reports on behalf of our customer to let me have our customers on that that daily data and then we send the reports out you via email or we drop them in a shared location and then they they look at the reports at some later point of time so it's up until yawn we did all this work on on enterprise Vertica at our peak we had four production enterprise clusters each which held two petabytes of raw data and I'll give you some details on on how those enterprise clusters were configured in the hardware but before I do that I want to talk about the reporting workload specifically so the the reporting workload is particularly lumpy and what I mean by that is there's a bunch of work that becomes available bunch of queries that we need to run in a short period of time after after the days just an aggregation is completed and then the clusters are relatively quiet for the remaining portion of the day that's not to say they are they're not doing anything as far as read workload but they certainly are but it's much less reactivity after that big spike so what I'm showing here is our reporting queue and the spike is is when all those reports become a bit sort of ailable to be processed we can't we can't process we can't run the report until we've done the full ingest and matching and aggregation for the day and so right around 1:00 or 2:00 a.m. UTC time every day that's when we get this spike and the spike we affectionately called the UTC hump but basically it's a huge number of queries that need to be processed sort of as soon as possible and we have service levels that dictate what as soon as possible means but I think the spike illustrates our use case pretty pretty accurately and um it really as we'll see it's really well suited for pervert icky on and we'll see what that means so we've got our we had our enterprise clusters that I mentioned earlier and just to give you some details on what they look like there they were independent and mirrored and so what that means is all four clusters held the same data and we did this intentionally because we wanted to be able to run our report anywhere we so so we've got this big queue over port is big a number of reports that need to be run and we've got these we started we started with one cluster and then we got we found that it couldn't keep up so we added a second and we found the number of reports went up that we needed to run that short period of time and and so on so we eventually ended up with four Enterprise clusters basically with this with the and we'd say they were mirrored they all had the same data they weren't however synchronized they were independent and so basically we would run the the tailpipe line so to speak we would run ingest and the matching and the aggregation on all the clusters in parallel so they it wasn't as if each cluster proceeded to the next step in sync with which dump the other clusters they were run independently so it was sort of like each each cluster would eventually get get consistent and so this this worked pretty well for for us but it created some imbalances and there was some cost concerns that will dig into but just to tell you about each of these each of these clusters they each had 50 nodes they had 72 logical CPU cores a half half a terabyte of RAM a bunch of raid rated disk drives and 2 petabytes of raw data as I stated before so pretty big beefy nodes that are physical physical nodes that we held we had in our data centers we actually reached these nodes so so it was on our data center providers data centers and the these were these these were what we built our business on basically but there was a number of challenges that we ran into as we as we continue to build our business and add data and add workload and and the first one is is some in ceremony can relate to his capacity planning so we had to prove think about the future and try to predict the amount of work that was going to need to be done and how much hardware we were going to need to satisfy that work to meet that demand and that's that's just generally a hard thing to do it's very difficult to verdict the future as we can probably all attest to and how much the world has changed and even in the last month so it's a it's a very difficult thing to do to look six twelve eighteen eighteen months into the future and sort of get it right and and and what people what we tended to do is we reach or we tried to our art plans our estimates were very conservative so we overbought in a lot of cases and not only that we had to plan for the peak so we're planning for that that that point in time that those number of hours in the early morning when we had to we had all those reports to run and so that so so we ended up buying a lot of hardware and we actually sort of overbought at times and then and then as the hardware were days it would kind of come into it would come into maturity and we have our our our workload would sort of come approach matching the demand so that was one of the big challenges the next challenge is that we were running on disk you can we wanted to add data in sort of two dimensions the only dimensions that everybody can think about we wanted to add more columns to our big aggregates and we wanted to keep our big aggregates for for longer periods of time so both horizontally and vertically we wanted to expand the datasets but we basically were running out of disk there was no more disk in and it's hard to add a disc to Vertica in enterprise mode not not impossible but certainly hard and and one cannot add discs without adding compute because enterprise mode the disk is all local to each of the nodes for most most people you can do not exchange with sands and other external rays but that's there are a number of other challenges with that so um adding in order to add disk we had to add compute and that basically meant kept us out of balance we're adding more compute than we needed for the amount of disk so that was the problem certainly physical nodes getting them the order delivered racked cables even before we even start such Vertica there's lead times there and and so it's also long commitment since we like I mentioned me Lisa hardware so we were committing to these nodes these physical servers for two or three years at a time and I mentioned that can be a hard thing to do but we wanted to least to keep our capex down so we wanted to keep our aggregates for a long period of time we could have done crazy things or more exotic things to to help us with this if we had to in enterprise mode we could have started to like daisy chain clusters together and that would have been sort of a non-trivial engineering effort because we would need to then figure out how to migrate data source first to recharge the data across all the clusters and we had to migrate data from one cluster to another cluster hesitation and we would have to think about how to aggregate run queries across clusters so if you assured data set spans two clusters it would have had to sort of aggregated within each cluster maybe and then build something on top the aggregated the data from each of those clusters so not impossible things but certainly not easy things and luckily for us we started talking about two Vertica about separation of compute and storage and I know other customers were talking to Vertica as we were people had had these problems and so Vertica inyeon mode came to the rescue and what I want to do is just talk about nyan mode really briefly for for those in the audience who aren't familiar but it's basically Vertigo's answered to the separation of computing storage it allows one to scale compute and or storage separately and and this there's a number of advantages to doing that whereas in the old enterprise days when you add a compute you added stores and vice-versa now we can now we can add one or the other or both according to how we want to and so really briefly how this works this slide this figure was taken directly from the verdict and documentation and so just just to talk really briefly about how it works the taking advantage of the cloud and so in this case Amazon Web Services the elasticity in the cloud and basically we've got you seen two instances so elastic cloud compute servers that access data that's in an s3 bucket and so three three ec2 nodes and in a bucket or the the blue objects in this diagram and the difference is a couple of a couple of big differences one the data no longer the persistent storage of the data the data where the data lives is no longer on each of the notes the persistent stores of the data is in s3 bucket and so what that does is it basically solves one of our first big problems which is we were running out of disk the s3 has for all intensive purposes infinite storage so we can keep much more data there and that mostly solved one of our big problems so the persistent data lives on s3 now what happens is when a query runs it runs on one of the three nodes that you see here and assuming we'll talk about depo in a second but what happens in a brand new cluster where it's just just spun up the hardware is the query will will run on those ec2 nodes but there will be no data so those nodes will reach out to s3 and run the query on remote storage so that so the query that the nodes are literally reaching out to the communal storage for the data and processing it entirely without using any data on on the nodes themselves and so that that that works pretty well it's not as fast as if the data was local to the nodes but um what Vertica did is they built a caching layer on on each of the node and that's what the depot represents so the depot is some amount of disk that is relatively local to the ec2 node and so when the query runs on remote stores on the on the s3 data it then queues up the data for download to the nodes and so the data will get will reside in the Depot so that the next query or the subsequent subsequent queries can run on local storage instead of remote stores and that speeds things up quite a bit so that that's that's what the role of the Depot is the depot is basically a caching layer and we'll talk about the details of how we can see your in our Depot the other thing that I want to point out is that since this is the cloud another problem that helps us solve is the concurrency problem so you can imagine that these three nodes are one sort of cluster and what we can do is we can spit up another three nodes and have it point to the same s3 communal storage bucket so now we've got six nodes pointing to the same data but we've you isolated each of the three nodes so that they act as if they are their own cluster and so vertical calls them sub-clusters so we've got two sub clusters each of which has three nodes and what this has essentially done it is it doubled the concurrency doubled the number of queries that can run at any given time because we've now got this new place which new this new chunk of compute which which can answer queries and so that has given us the ability to add concurrency much faster and I'll point out that for since it's cloud and and there are on-demand pricing models we can have significant savings because when a sub cluster is not needed we can stop it and we pay almost nothing for it so that's that's really really important really helpful especially for our workload which I pointed out before was so lumpy so those hours of the day when it's relatively quiet I can go and stop a bunch of sub clusters and and I will pay for them so that that yields nice cost savings let's be on in a nutshell obviously engineers and the documentation can use a lot more information and I'm happy to field questions later on as well but I want to talk about how how we implemented beyond at the trade desk and so I'll start on the left hand side at the top the the what we're representing here is some clusters so there's some cluster 0 r e t l sub cluster and it is a our primary sub cluster so when you get into the world of eon there's primary Club questions and secondary sub classes and it has to do with quorum so primary sub clusters are the sub clusters that we always expect to be up and running and they they contribute to quorum they decide whether there's enough instances number a number of enough nodes to have the database start up and so these this is where we run our ETL workload which is the ingest the match in the aggregate part of the work that I talked about earlier so these nodes are always up and running because our ETL pipeline is always on we're internet ad tech company like I mentioned and so we're constantly getting costly running ad and there's always data flowing into the system and the matching is happening in the aggregation so that part happens 24/7 and we wanted so that those nodes will always be up and running and we need this we need that those process needs to be super efficient and so what that is reflected in our instance type so each of our sub clusters is sixty four nodes we'll talk about how we came at that number but the infant type for the ETL sub cluster the primary subclusters is I 3x large so that is one of the instance types that has quite a bit of nvme stores attached and we'll talk about that but on 32 cores 240 four gigs of ram on each node and and that what that allows us to do I should have put the amount of nvme but I think it's seven terabytes for anything me storage what that allows us to do is to basically ensure that our ETL everything that this sub cluster does is always in Depot and so that that makes sure that it's always fast now when we get to the secondary subclusters these are as mentioned secondary so they can stop and start and it won't affect the cluster going up or down so they're they're sort of independent and we've got four what we call Rhian subclusters and and they're not read by definition or technically they're not read only any any sub cluster can ingest and create your data within the database and that'll all get that'll all get pushed to the s3 bucket but logically for us they're read only like these we just most of these the work that they happen to do is read only which it is which is nice because if it's read only it doesn't need to worry about commits and we let we let the primary subclusters or ETL so close to worry about committing data and we don't have to we don't have to have the all nodes in the database participating in transaction commits so we've got a for read subclusters and we've got one EP also cluster so a total of five sub clusters each so plus they're running sixty-four nodes so that gives us a 320 node database all things counted and not all those nodes are up at the same time as I mentioned but often often for big chunks of the days most of the read nodes are down but they do all spin up during our during our busy time so for the reading so clusters we've got I three for Excel so again the I three incidents family type which has nvme stores these notes have I think three and a half terabytes of nvme per node we just rate it to nvme drives we raid zero them together and 16 cores 122 gigs of ram so these are smaller you'll notice but it works out well for us because the the read workload is is typically dealing with much smaller data sets than then the ingest or the aggregation workbook so we can we can run these workloads on on smaller instances and leave a little bit of money and get more granularity with how many sub clusters are stopped and started at any given time the nvme doesn't persist the data on it isn't persisted remember you stop and start this is an important detail but it's okay because the depot does a pretty good job in that in that algorithm where it pulls data in that's recently used and the that gets pushed out a victim is the data that's least reasons use so it was used a long time ago so it's probably not going to be used to get so we've got um five sub-clusters and we have actually got to two of those so we've got a 320 node cluster in u.s. East and a 320 node cluster in u.s. West so we've got a high availability region diversity so and their peers like I talked about before they're they're independent but but yours they are each run 128 shards and and so with that what that which shards are is basically the it's similar to segmentation when you take those dataset you divide it into chunks and though and each sub cluster can concede want the data set in its entirety and so each sub cluster is dealing with 128 shards it shows 128 because it'll give us even distribution of the data on 64 node subclusters 60 120 might evenly by 64 and so there's so there's no data skew and and we chose 128 because the sort of ginger proof in case we wanted to double the size of any of the questions we can double the number of notes and we still have no excuse the data would be distributed evenly the disk what we've done is so we've got a couple of raid arrays we've got an EBS based array that they're catalog uses so the catalog storage location and I think we take for for EBS volumes and raid 0 them together and come up with 128 gigabyte Drive and we wanted an EPS for the catalog because it we can stop and start nodes and that data will persist it will come back when the node comes up so we don't have to run a bunch of configuration when the node starts up basically the node starts it automatically joins the cluster and and very strongly there after it starts processing work let's catalog and EBS now the nvme is another raid zero as I mess with this data and is ephemeral so let me stop and start it goes away but basically we take 512 gigabytes of the nvme and we give it to the data temp storage location and then we take whatever is remaining and give it to the depot and since the ETL and the reading clusters are different instance types they the depot is is side differently but otherwise it's the same across small clusters also it all adds up what what we have is now we we stopped the purging data for some of our big a grits we added bunch more columns and what basically we at this point we have 8 petabytes of raw data in each Jian cluster and it is obviously about 4 times what we can hold in our enterprise classes and we can continue to add to this maybe we need to add compute maybe we don't but the the amount of data that can can be held there against can obviously grow much more we've also built in auto scaling tool or service that basically monitors the queue that I showed you earlier monitors for those spikes I want to see as low spikes it then goes and starts up instances one sub-collector any of the sub clusters so that's that's how that's how we we have compute match the capacity match that's the demand also point out that we actually have one sub cluster is a specialized nodes it doesn't actually it's not strictly a customer reports sub clusters so we had this this tool called planner which basically optimizes ad campaigns for for our customers and we built it it runs on Vertica uses data and Vertica runs vertical queries and it was it was wildly successful um so we wanted to have some dedicated compute and beyond witty on it made it really easy to basically spin up one of these sub clusters or new sub cluster and say here you go planner team do what you want you can you can completely maximize the resources on these nodes and it won't affect any of the other operations that were doing the ingest the matching the aggregation or the reports up so it gave us a great deal of flexibility and agility which is super helpful so the question is has it been worth it and without a doubt the answer is yes we're doing things that we never could have done before sort of with reasonable cost we have lots more data specialized nodes and more agility but how do you quantify that because I don't want to try to quantify it for you guys but it's difficult because each eon we still have some enterprise nodes by the way cost as you have two of them but we also have these Eon clusters and so they're there they're running different workloads the aggregation is different the ingest is running more on eon does the number of nodes is different the hardware is different so there are significant differences between enterprise and and beyond and when we combine them together to do the entire workload but eon is definitely doing the majority of the workload it has most of the data it has data that goes is much older so it handles the the heavy heavy lifting now the query performance is more anecdotal still but basically when the data is in the Depot the query performance is very similar to enterprise quite close when the data is not in Depot and it needs to run our remote storage the the query performance is is is not as good it can be multiples it's not an order not orders of magnitude worse but certainly multiple the amount of time that it takes to run on enterprise but the good news is after the data downloads those young clusters quickly catch up as the cache populates there of cost I'd love to be able to tell you that we're running to X the number of reports or things are finishing 8x faster but it's not that simple as you Iran is that you it is me I seem to have gotten to thank you you hear me okay I can hear you now yeah we're still recording but that's fine we can edit this so if I'm just talking to the person the support person he will extend our recording time so if you want to maybe pick back up from the beginning of the slide and then we'll just edit out this this quiet period that we have sir okay great I'm going to go back on mute and why don't you just go back to the previous slide and then come into this one again and I'll make sure that I tell the person who yep perfect and then we'll continue from there is that okay yeah sound good all right all right I'm going back on yet so the question is has it been worth it and for us the answer has been a resounding yes we're doing things that we never could have done at reasonable cost before and we got more data we've got this Y note this law has nodes and in work we're much more agile so how to quantify that um well it's not quite as simple and straightforward as you might hope I mean we still have enterprise clusters we've got to update the the four that we had at peak so we've still got two of those around and we got our two yawn clusters but they're running different workloads and they're comprised of entirely different hardware the dependence has I've covered the number of nodes is different for sub-clusters so 64 versus 50 is going to have different performance the the workload itself the aggregation is aggregating more columns on yon because that's where we have disk available the queries themselves are different they're running more more queries on more intensive data intensive queries on yon because that's where the data is available so in a sense it is Jian is doing the heavy lifting for the cluster for our workload in terms of query performance still a little anecdotal but like when the queries that run on the enterprise cluster the performance matches that of the enterprise cluster quite closely when the data is in the Depot when the data is not in a Depot and Vertica has to go out to the f32 to get the data performance degrades as you might expect it can but it depends on the curious all things like counts counts are is really fast but if you need lots of the data from the material others to realize lots of columns that can run slower I'm not orders of magnitude slower but certainly multiple of the amount of time in terms of costs anecdotal will give a little bit more quantifying here so what I try to do is I try to figure out multiply it out if I wanted to run the entire workload on enterprise and I wanted to run the entire workload on e on with all the data we have today all the queries everything and to try to get it to the Apple tab so for enterprise the the and estimate that we do need approximately 18,000 cores CPU cores all together and that's a big number but that's doesn't even cover all the non-trivial engineering work that would need to be required that I kind of referenced earlier things like starting the data among multiple clusters migrating the data from one culture to another the daisy chain type stuff so that's that's the data point now for eon is to run the entire workload estimate we need about twenty thousand four hundred and eighty CPU cores so more CPU cores uh then then enterprise however about half of those and partly ten thousand of both CPU cores would only run for about six hours per day and so with the on demand and elasticity of the cloud that that is a huge advantage and so we are definitely moving as fast as we can to being on all Aeon we have we have time left on our contract with the enterprise clusters or not we're not able to get rid of them quite yet but Eon is certainly the way of the future for us I also want to point out that uh I mean yawn is we found to be the most efficient MPP database on the market and what that refers to is for a given dollar of spend of cost we get the most from that zone we get the most out of Vertica for that dollar compared to other cloud and MPP database platforms so our business is really happy with what we've been able to deliver with Yan Yan has also given us the ability to begin a new use case which is probably this case is probably pretty familiar to folks on the call where it's UI based so we'll have a website that our customers can log into and on that website they'll be able to run reports on queries through the website and have that run directly on a separate row to get beyond cluster and so much more latent latency sensitive and concurrency sensitive so the workflow that I've described up until this point has been pretty steady throughout the day and then we get our spike and then and then it goes back to normal for the rest of the day this workload it will be potentially more variable we don't know exactly when our engineers are going to deliver some huge feature that is going to make a 1-1 make a lot of people want to log into the website and check how their campaigns are doing so we but Yohn really helps us with this because we can add a capacity so easily we cannot compute and we can add so we can scale that up and down as needed and it allows us to match the concurrency so beyond the concurrency is much more variable we don't need a big long lead time so we're really excited about about this so last slide here I just want to leave you with some things to think about if you're about to embark or getting started on your journey with vertically on one of the things that you'll have to think about is the no account in the shard count so they're kind of tightly coupled the node count we determined by figuring like spinning up some instances in a single sub cluster and getting performance smaller to finding an acceptable performance considering current workload future workload for the queries that we had when we started and so we went with 64 we wanted to you want to certainly want to increase over 50 but we didn't want to have them be too big because of course it costs money and so what you like to do things in power to so 64 nodes and then the shard count for the shards again is like the data segmentation is a new type of segmentation on the data and the start out we went with 128 it began the reason is so that we could have no skew but you know could process the same same amount of data and we wanted to future-proof it so that's probably it's probably a nice general recommendation doubleness account for the nodes the instance type and and how much people space those are certainly things you're going to consider like I was talking about we went for they I three for Excel I 3/8 Excel because they offer good good Depot stores which gives us a really consistent good performance and it is all in Depot the pretty good mud presentation and some information on on I think we're going to use our r5 or the are for instance types for for our UI cluster so much less the data smaller so much less enter this on Depot so we don't need on that nvm you stores the reader we're going to want to have a reserved a mix of reserved and on-demand instances if you're if you're 24/7 shop like we are like so our ETL subclusters those are reserved instances because we know we're going to run those 24 hours a day 365 days a year so there's no advantage of having them be on-demand on demand cost more than reserve so we get cost savings on on figuring out what we're going to run and have keep running and it's the read subclusters that are for the most part on on demand we have one of our each sub Buster's is actually on 24/7 because we keep it up for ad-hoc queries your analyst queries that we don't know when exactly they're going to hit and they want to be able to continue working whenever they want to in terms of the initial data load the initial data ingest what we had to do and now how it works till today is you've got to basically load all your data from scratch there isn't a great tooling just yet for data populate or moving from enterprise to Aeon so what we did is we exported all the data in our enterprise cluster into park' files and put those out on s3 and then we ingested them into into our first Eon cluster so it's kind of a pain we script it out a bunch of stuff obviously but they worked and the good news is that once you do that like the second yon cluster is just a bucket copy in it and so there's tools missions that can help help with that you're going to want to manage your fetches and addiction so this is the data that's in the cache is what I'm referring to here the data that's in the default and so like I talked about we have our ETL cluster which has the most recent data that's just an injected and the most difficult data that's been aggregated so this really recent data so we wouldn't want anybody logging into that ETL cluster and running queries on big aggregates to go back one three years because that would invalidate the cache the depot would start pulling in that historical data and it was our assessing that historical data and evicting the recent data which would slow things out flow down that ETL pipelines so we didn't want that so we need to make sure that users whether their service accounts or human users are connecting to the right phone cluster and I mean we just created the adventure users with IPS and target groups to palm those pretty-pretty it was definitely something to think about lastly if you're like us and you're going to want to stop and start nodes you're going to have to have a service that does that for you we're where we built this very simple tool that basically monitors the queue and stops and starts subclusters accordingly we're hoping that that we can work with Vertica to have it be a little bit more driven by the cloud configuration itself so for us all amazon and we love it if we could have it have a scale with the with the with the eight of us can take through points do things to watch out for when when you're working with Eon is the first is system table queries on storage layer or metadata and the thing to be careful of is that the storage layer metadata is replicated it's caught as a copy for each of the sub clusters that are out there so we have the ETL sub cluster and our resources so for each of the five sub clusters there is a copy of all the data in storage containers system table all the data and partitions system table so when you want to use this new system tables for analyzing how much data you have or any other analysis make sure that you filter your query with a node name and so for us the node name is less than or equal to 64 because each of our sub clusters at 64 so we limit we limit the nodes to the to the 64 et 64 node ETL collector otherwise if we didn't have this filter we would get 5x the values for counts and some sort of stuff and lastly there is a problem that we're kind of working on and thinking about is a DC table data for sub clusters that are our stops when when the instances stopped literally the operating system is down and there's no way to access it so it takes the DC table DC table data with it and so I cannot after after my so close to scale up in the morning and then they scale down I can't run DC table queries on how what performed well and where and that sort of stuff because it's local to those nodes so we're working on something so something to be aware of and we're working on a solution or an implementation to try to suck that data out of all the notes you can those read only knows that stop and start all the time and bring it in to some other kind of repository perhaps another vertical cluster so that we can run analysis and monitoring even you want those those are down that's it um thanks for taking the time to look into my presentation really do it thank you Ron that was a tremendous amount of information thank you for sharing that with everyone um we have some questions come in that I would like to present to you Ron if you have a couple min it your first let's jump right in the first one a loading 85 terabytes per day of data is pretty significant amount what format does that data come in and what does that load process look like yeah a great question so the format is a tab separated files that are Jesus compressed and the reason for that could basically historical we don't have much tabs in our data and this is how how the data gets compressed and moved off of our our bidders the things that generate most of this data so it's a PSD gzip compressed and how you kind of we kind of have how we load it I would say we have actually kind of a Cadillac loader in a couple of different perspectives one is um we've got this autist raishin layer that's homegrown managing the logs is the data that gets loaded into Vertica and so we accumulate data and then we take we take some some files and we push them to redistribute them along the ETL nodes in the cluster and so we're literally pushing the file to through the nodes and we then run a copy statement to to ingest data in the database and then we remove the file from from the nodes themselves and so it's a little bit extra data movement which you may think about changing in the future assisting we move more and more to be on well the really nice thing about this especially for for the enterprise clusters is that the copy' statements are really fast and so we the coffee statements use memory but let's pick any other query but the performance of the cautery statement is really sensitive to the amount of available memory and so since the data is local to the nodes literally in the data directory that I referenced earlier it can access that data from the nvme stores and the kabhi statement runs very fast and then that memory is available to do something else and so we pay a little bit of cost in terms of latency and in terms of downloading the data to the nose we might as we move more and more PC on we might start ingesting it directly from s3 not copying the nodes first we'll see about that what's there that's how that's how we read the data interesting works great thanks Ron um another question what was the biggest challenge you found when migrating from on-prem to AWS uh yeah so um a couple of things that come to mind the first was the baculum the data load it was kind of a pain I mean like I referenced in that last slide only because I mean we didn't have tools built to do this so I mean we had to script some stuff out and it wasn't overly complex but yes it's just a lot of data to move I mean even with starting with with two petabytes so making sure that there there is no missed data no gaps making and moving it from the enterprise cluster so what we did is we exported it to the local disk on the enterprise buses and we then we push this history and then we ingested it in ze on again Allspark X oh so it's a lot of days to move around and I mean we have to you have to take an outage at some point stop loading data while we do that final kiss-up phase and so that was that was a challenge a sort of a one-time challenge the other saying that I mean we've been dealing with a week not that we're dealing with but with his challenge was is I mean it's relatively you can still throw totally new product for vertical and so we are big advantages of beyond is allow us to stop and start nodes and recently Vertica has gotten quite good at stopping in part starting nodes for a while there it was it was it took a really long time to start to Noah back up and it could be invasive but we worked with with the engineering team with Yan Zi and others to really really reduce that and now it's not really an issue that we think that we think too much about hey thanks towards the end of the presentation you had said that you've got 128 shards but you have your some clusters are usually around 64 nodes and you had talked about a ratio of two to one why is that and if you were to do it again would you use 128 shards ah good question so that is a reference the reason why is because we wanted to future professionals so basically we wanted to make sure that the number of stars was evenly divisible by the number of nodes and you could I could have done that was 64 I could have done that with 128 or any other multiple entities for but we went with 128 is to try to protect ourselves in the future so that if we wanted to double the number of nodes in the ECL phone cluster specifically we could have done that so that was double from 64 to 128 and then each node would have happened just one chart that it had would have to deal with so so no skew um the second part of question if I had to do it if I had to do it over again I think I would have done I think I would have stuck with 128 we still have I mean so we either running this cluster for more than 18 months now I think especially in USC and we haven't needed to increase the number of nodes so in that sense like it's been a little bit extra overhead having more shards but it gives us the peace of mind that we can easily double that and not have to worry about it so I think I think everyone is a nice place to start and you may even consider a three to one or four to one if if you're if you're expecting really rapid growth that you were just getting started with you on and your business and your gates that's a small now but what you expect to have them grow up significantly less powerful green thank you Ron that's with all the questions that we have out there for today if you do have others please feel free to send them in and we will get back to you and we'll respond directly via email and again our engineers will be available on the vertical forums where you can continue the discussion with them there I want to thank Ron for the great presentation and also the audience for your participation in questions please note that a replay of today's event and a copy of the slides will be available on demand shortly and of course we invite you to share this information with your colleagues as well again thank you and this concludes this webinar and have a great day you

>> Narrator: Live from Las Vegas, it's theCUBE. Covering UiPath Forward Americas, 2019. Brought to you by UiPath. >> Welcome back everyone to theCUBE's live coverage of UiPath Forward here at the Bellagio in Las Vegas, Nevada. I'm your host, Rebecca Knight, co-hosting alongside of Dave Vellante. We're joined by Cathy Tornbohm, she is the distinguished VP Analyst at Gartner. Thank you so much for coming on theCUBE. >> Very welcome, nice to be here. >> And Guy Kirkwood, he is the Chief Evangelist at UiPath. Thank you so much. >> Thanks Rebecca. >> So, we're hearing so much of these mantras, these catchphrases of UiPath. "automation first", "a robot for every person", "we're re-booting work", these are the theme's that Guy was touting up on the main stage, Cathy. Beyond that, I'd like to hear from you a little bit about what you're seeing in the RPA space at the moment. What are the trends and the themes that you think are most salient? >> I think the most fascinating thing about RPA right now is that it's really highlighting the problems the organizations have. All their accidents of history are really being brought up by RPA. And then you've got these digital darlings that they're trying to compete with, the Greenfield site kind of people. And some of those don't have beautiful back offices, but let's not go there for a minute. So, it, RPA is an opportunity for companies to link their digital dreams with their existing legacy nightmares. >> And those legacy nightmares include all of the things that Guy was talking about today: the drudgery, the dreariness, those mundane tasks that take up so much of our time. >> Absolutely, and really, if you think about it, in organizations, typically less than 15% of the applications that they're using have got some sort of application programming interface. So if you don't have a way of linking them, you end up with this long turn of applications that aren't linked together, with people literally being swivel-chair integration between the applications. >> Well, why can't you just string a bunch of API's together and automate that way? >> Well, in fact, there's a guy called Ian Barkin who works for Symphony, one of their organizations, it was set up to create automations for organizations. So one of the services businesses since been acquired by Sykes. And he describes it as process sediment, and it builds up in businesses in the same way that sedimentary rock builds up over millions of years. And digging through that, so that you can actually become more efficient is very difficult to do. So doing it on API level means you got to join up all those things individually. Whereas, using RPA, if system 'A' has a user interface, and system 'B' has a user interface, you can just use RPA. >> So, Cathy, you've been following process automation as a category for a number of years. Why RPA, why is it so hot, and why now? We've heard that it's the number one software category... >> Cathy: Fastest growing, yeah. Fastest growing, from Gartner. We've seen spending data that confirms that. Why now? (sighing) >> It's the digital competition that companies are facing, and the recognition that they cannot continue to be quite as bad at some of the things that they are bad at. So it's really that business transformation story back again, business process re-engineering, the same story that we had with BPO like ten years ago, but now, with robots instead. >> Yeah, it's interesting, I was at a, we had a show last weekend, it was the CEO of Suze, Suze... How do ya say it? Anyway, Suze, she said to me, "Well, you know, digital transformation's really about business transformation." And you kind of said the same thing. I mean, thoughts on that? >> I mean, you look at the start of the outsourcing market, the BPA market, twenty years ago. The very first deals were actually IT outsourcing deals that then transformed the business using IT as the enabler. So the first deal that I got involved with ever, in the outsourcing market, was Perot Systems with a British and Asian company. And we were putting in business process re-engineering consultants who actually transformed the business using IT as the enabler for that. There is no difference now, in fact one of the, one of the partners here, one of our original customers, actually put together a plan where we did the implementation, you know, soup to nuts, so that we could find out how we fit in to that whole transformation piece. And our team put together a whole package on all the learnings that we got out of that. And I had to laugh, because they're exactly the same things that every transformation program has had for the last thirty years. >> You know, if you look at kind of the history of certain segments, and I wonder if, Cathy, if you see RPA as one of them, like if you could've figured out who was implementing ERP the best, you didn't know SAP was going to become the leader, but if you could've figured out who was adopting ERP, you could've made a lot of money in the stock market, 'cause those companies had a huge productivity boost. Kind of same thing with Big Data, nobody really made any money in Big Data, so-called 'Big Data', a dupe. But the guys who applied it probably did pretty well. Do you see RPA as similar where the practitioners are going to actually be the ones that add more value to the industry than the new, the newly minted billionaires? >> It's almost the opposite. So the more RPA a company needs, it means the worse they did at managing their ERP in the first place. >> So they're kind of a mess? >> Yeah, yes. That need to be cleaned up, yeah. >> Yes, if you've got a hundred and twenty four ERP's that don't talk to each other, and you want to close your books in any kind of reasonable time frame, you're going to be a massive adopter of RPA, which basically means the more rubbish you are and activity, the more opportunity there is to automate more of it. >> So, what are the metrics that matter when you talk to your clients? >> Well, what I try and encourage clients to do is to really focus on business outcomes. So, much as Guy probably doesn't want me to say this, I don't really care how many 'scripts', aka robots, you've built, or how many run times you've deployed. What I care about is the business impact that you've managed to achieve. So, whatever KPI's are important to you, so are you managing to collect more revenue? Are you managing to make your customers happier because you're managing to decrease average handle times? or increase right first time activities. So anything that you're doing that actually improves the good old business metrics, is just going to be fantastic. So those are the sort of metrics that, really, companies should be focusing on. Not how many scripts they've built, that's absolutely pointless. >> I mean, are they focusing on that? I mean, when you... >> Yeah, lots of people are. >> Yeah? >> Yeah. >> In terms of ROI, we hear from customers that it has had them more accurate, they're more efficient, they're cost saving on human hours of the mundane tasks. But, when you were up on the main stage talking about how we're rebooting work, we're changing this moment, is it sparking the creativity, the imagination, the time spent on strategy in the more higher-level things? Is that, I mean that seems like that's the goal of return on investment. >> It is, within those organizations that are the most mature. So, what we're seeing, is the bifurcation, really, of the market between those organizations that are just starting and scaling up what they can, internal senses of excellence. Those organizations that are using the partners behind us. Those organizations that are using external parties to help them develop that. So Delight, for instance, they are sort of a managed service business. And instead of using people, they're using automation. So, Delight, by accident, has a BPA business in Spain, but then they'll turn that into an automation-heavy business and then providing that managed service. And then, the smartest customers, including SNBC, who we heard from yesterday, are actually turning their back office cost operations into a front office of revenue generator. Now, that is radically different from what we've seen prior. >> So Cathy, I got to ask you, when I was on a plane out here, somebody texted me a picture of the latest hype cycle. And they said, they knew I was going to UiPath, they said, "RPA has entered the trough of disillusionment." I said, "Oh, awesome, Gartner's, Cathy's coming on, and I can ask her about that." Well, what's your take on that? >> I think as Guy says, some people have already sailed through the trough, they've already gone through the challenges, or some of the challenges, and they've already found these fantastic productive things. I mean, we're estimating that people will save close to a million dollars for a large company, and just not having to do re-work of getting it wrong first time with re-keying that data. So, where there's some fantastic savings available, that you know, some of the ones have gone through the trough and done that, a lot of the other ones, they kind of, they don't understand the limitations of RPA and all those other partner tools that they need to put with it. So, don't understand it, can't handle unstructured data by itself. It needs a sister tool, so, what Gartner's talking about right now is this concept of hyper automation where you look across all the different activities that you would need to, sort of replace a person. So the people that are heading into the trough as sort of this second wave of adopters that Guy talked about, that will really struggle because they didn't understand the limitations in the first place. >> Well then, you know the, sometimes, things like the Magic Quadrant, and the trough of disillusionment, they're somewhat misunderstood sometimes, people, you know they see 'em, Gartner's very clever with the way it works things, but, so how should we think about that hype cycle? It's actually, in a way it's progress, isn't it? For an industry where they start... Entering that trough. >> Its, what Gartner says, is all industries have to go through that type of growing pains. And I think that we're seeing that, UiPath's expanded massively, and that's always a challenge for companies as they grow very rapidly. And as companies try and, as they say, take these wrong metrics. So I think things like UiPath buying ProcessGold is fantastic, it's a really, really good move for them. And I expect to see a lot of other process mining companies acquired, brought in to the RPA fold, because, there's four reasons why companies are going to go into this disillusionment, right? These are the main challenges with companies trying to use RPA properly. One is, they don't know what the processes are. So ProcessGold will give you a really good indication, they don't know about the microscopic level, and they don't know about the macro level. So things like digital twins will be something else that we would expect to see very closely partnered with companies like UiPath. And they don't know how to orchestrate their resources. So, other companies, like Innate, that can help you figure out how to do that will become... So its kind of like we're sort of breaking down a lot of what happened in other software categories and re-building them all up, in the way that the business can actually adopt them, hence, the AI Fabric sort of idea. So they don't know the processes, politics, people will lie to you about what they do all day, so they can sabotage your process, and there's a lot of silos within organizations that hate each other and throw things over the wall. So that all needs streamlining, and the more you can do across silos, the more successful any automation project would be. Then you've got, when you take a person out of a process, you take their eyes, their ears, the mouth, the nose. How are you going to replace that when you're trying to take them out, because you've got the keyboard fingers thing with the RPA tool? You need all these other activities replaced, replicated, supported. And then you've got the economics of production, so actually making sure that the scripts that you've built are actually worthwhile and are going to be cost-effective. It's something that we're studying at the moment. So you've got all these, all these different barriers, from all these different angles that are really going to push this thing into the trough for a little bit. And that's why it's great that RPA companies are looking at ways to mitigate that for their customers. >> Now, remember we said, as the understandings. So RPA is really good at dealing with structured data. Rule-spaced activities, deterministic things. That's why in regulatory, highly regulated environments, it's very effective, and the regulators love this sort of stuff. Because it's deterministic. When you look at AI, then we look at it in four ways. So you've got process understanding, which is the ProcessGold acquisition, you look at conversational understanding, 'cause ultimately robots are going to be controlled by voice. So you have to understand, the system has to understand that, let's say you're sitting in a bank, and the robot doesn't understand something, you say, "Okay, robot, stick that in the Well's account." It has to understand that Well's, in this case, means Well's Fargo. It does not mean a hole in the ground, water at the bottom, or a town in Somerset, in the UK, 'cause they're well's. So getting those ontologies correct is so important. So, that's conversational understanding. Document understanding. Because, as Cathy said, companies are still wading around in paper. So, understanding what those different documents are and how to action them is going to be really important. And finally, you're looking at visual understanding. So understanding and viewing things on the screen exactly the same way that humans do. So it's getting that combination right. >> So for RPA to live up to the hype, and there's a lot of hype, and it's a good thing, it's fun to track. It's got to go presumably beyond cleaning up the crime scene, if you will, to this new vision that you and Guy just laid out. What is the distance between, I dunno, sometimes I say 'paving the cow path', which gives you a nice hit, but as you say, it's 'cause companies... Ya know, they're messed up, to this vision of this, actually the guy from Pepsi today talked about it, this fabric of automation across the organization. How big of a gap is that? >> It's very different by every different company on the planet, really, in terms of their accidents of history, what their IT application landscape looks like, and what their business landscape looks like. And when you try and put the two things together, that's where you find the opportunities for any type of automation. >> Well come on, that's such an 'it depends' answer. (laughing) At the macro, will... In your expert opinion, will RPA live up to the hype? So many trends haven't, enterprise data warehousing, Big Data, Doob, all that stuff. You think RPA has the potential to crack through that. >> You mentioned a very good point. I think the most successful companies are the ones that actually will take the person that's managing the data and analytics of how their process is performing, and doing that with their automation strategy. And there are very few companies that've actually worked that out. They've still got totally two walls and they just meet up here at the CEO. So, unless companies actually take a more active business outcomes approach, and look at their end-to-end processes of order to cash and source to pay, these problems will carry on for some time. >> Well that's a great point, I mean, so it's data, it's machine intelligence, I guess Cloud for scale, you guys made a SAS announcement today, it's "automation first", to use your buzz word. >> Cathy: You need it all to come together. >> And it's really developing those best practices in your role as Chief Evangelist in helping understand what the most successful companies do, and then making sure that's implemented. >> Well that's why I spend more of my time listening than I do talking. Because the very nature of being a Chief Evangelist is the best job and the worst job title in the world. It's the best job because I spend my entire time talking to people like Cathy who know about what's happening within the market, and then feeding it back into our organization so we can make the right bets, so we can make the right acquisitions, but develop the right things. The bad thing about the job, is that I keep getting an inordinate number of people on LinkedIn saying, "So pleased that Jesus has entered your life." And I'm not that type of evangelist. (laughing) >> It's in the title. >> You know there's always this age-old debate in the industry of best of breed versus kind of a sweet approach. You see in SAP, for instance, acquired an RPA company, In Four talks about it. And then you get the specialist, UiPath. How do you see that shaking out, as the industry gets kind of more consolidated, how do you see a company like UiPath thriving, continuing to thrive? >> Gartner's going to predict coming in our new prediction series, but... Roughly 20 to 30% of enterprise adoption of AI, machine learning activities for process-based activities, will go through the RPA market. So, and with the IBPMS market, sort of combined together, that process management, because RPA has managed, cleverly, to capture the imagination of the business person. So, actually, there's a lot of IT departments that are talking to us about, how do we, how do we enshrine this activity, foreshadow IT, that's happening in the business, and make it successful, put governance plans in place so it will actually be successful in the way that it's actually now dealing with its own crime scene... (laughing) (mumbling) Its own rubbish, in a much better way. And I think that responsibility of business to understand how it can automate things and how it can manage things will really help a lot. So, I think the RPA players are well-placed to either be acquired into that bigger set of the established, large... Software providers, all to kind of keep blazing a trail for independence of the business. I'm not so sure about this idea that everybody should be programming their own scripts, I think that's a challenge. And I think the new interfaces will help mitigate some of the problems that we've seen with that approach, that hasn't been, haven't been very well done historically, so that's another area that will probably be a bit trough of disillusionment, but, actually, well-managed RPA projects have actually got a really good chance of delivering back very interesting benefits for businesses. >> Yeah, as a discreet innovation category, it does kind of feel that way, and often times, those markets are winner take most, the winner makes a ton of dough, number two makes a little bit of money, number three kind of breaks even, and everybody else gets consolidated or goes out of business, so, you guys go big or go home. That's kind of... Your posture. >> Tomorrow morning I'm doing, I'm doing my predictions for next year, and one of them is that the challenger RPA vendors, and indeed the service organizations that are small, are going to continue to consolidate and get acquired next year. So that's the 2020 prediction for us. >> Great. Well, Guy and Cathy, thank you both so much for coming on theCUBE. It was a great conversation. >> Oh, good, thank you. >> Thank you very much, indeed. Thanks Rebecca. >> Dave: Thanks you guys. >> I'm Rebecca Knight for Dave Vellante, stay tuned for more of theCUBES live coverage of UiPath. (techno music)

>> lie 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. >> Welcome back to the cubes. Live coverage here in San Francisco, California, for VM World 2019. I'm Jeff Davis Davis, our 10th year, 10 years covering the M world. Quite a run. Got a great stories. More stories coming, Emma days. A lot of organic growth. A lot of typos in the startup scene. Our next two guests Mike Adams, CIA Director bm wear and Ziv Kalman. Oh, vich product line manager here. Welcome to the Cube. Great to see you. Yes, Curtsy to you guys. Got a lot of activity happening around bit fusion. A lot of news to share. Exciting. I mean, in the M. And a story has been high on VM. Where we talking back? Elsie earlier. Continue to fill in on the strategy. >> Yeah, absolutely. Give us the update. Yeah, I think the key thing for us is we really want to become a key player in the A. I am l space and say that those workloads should come on visa. And with this acquisition we think, provides a great framework for a lot of the hardware accelerator devices. The best of you known of those his GP use. But we think there's four coming market with PG A's and also custom a six. So we're super excited about that. >> For the folks that don't know much about the acquisition, what was the motivation? What was the company's core product? What was the interest? Yeah, the >> company had a product called Flex Direct, and that particular product was really focused on taking, ah, similar concept that a lot of V m writes No, which was, Hey, we knew that computes space. We were trying to take these isolated islands and pull them together. Same type of thing. Here you had these expensive devices that people were buying and they were isolated. And now if we could take a single server, it's got a bunch of GP use on it. Why don't we share it? You see all these papers that come out around machine learning at the very end. It says she's I'm amazed that thes GP user so underutilized even when we're actually using them. It's kind of like buying a car and then using the radio only right? Doesn't. It just doesn't make sense. I >> got this trend of alternative processors just sort of exploding all over the place. I mean, obviously in video, sort of people know what's going on there, but but you've got arm. Now you've got the edge coming in, you know, Intel. Still dominant in the server space. But even even storage devices today use different type, not in the not Intel processors in there. It's a combination of our mo are Sometimes you know, G. P uses you say F g a Z, even though they're sort of a narrow use case. You're seeing a six make a comeback. So you got all this additional processing power, you know, going. So that's a tailwind. Absolutely, guys, and it's sort of the intersection of those to maybe talk about some of the trends you see in that regard and how you're taking advantage of them. >> Yeah, it reminds me of many moons ago when we had new chips that were coming out. We said, Jesus, hardware, flurry here, right? And now we're in a really similar spot. Ziv and I see a lot of different types of devices and acceleration devices, whether it's computer network or storage. And in this particular case, right, we just see a hotbed of all these customers that air seeing the same problem, right? And we've got great partnerships with Intel you mentioned in video and and many others. And we just want to really leverage those for these devices because you look at V sphere and say, OK, your traditional workloads. We've done those very, very well. But as we get into containers, KUBERNETES, machine Learning and I, we want these newer cloud native and newer workloads to come our way. And taking advantage of these new capabilities really helps accelerate that in a big way. >> Could you >> explain Maur on the the sphere impact? Because, you know, first of all, of'em, where community you get the feedback right away on Twitter and a lot of things. But sometimes you gotta dig in and find out what people are thinking and where there might. I think that could be future up opportunities or because it meets skepticism. Well, the the sphere native having a eye on the sphere, that's just mind blowing to me. But I mean, I can see I can see a data processor kind of vibe going on here where data needs to be processed. That seems to be a trend. What is it going on with the sphere with this? Is there what's the what's to customers? No. >> Well, I think the first thing to clarify here is that, you know, some often there is this question. Why would Iran m Ellery I work? Look specifically envy. Sphere is a platform. But then customers do run Emily and workers and public clouds. And those layers are not that different than the spirits virtualization layer, and they're running it in virtual machines. So the whole idea would be fusion specifically, is it? Actually, we can make it even more efficient to run these workloads on top of the sphere because the underlying infrastructure that you two actually, you have to accelerate these workloads there. Today they are mostly GP use, obviously, but in the futures, Michael so mentioned you a six are coming in and effigies are coming in. We are going to make those as well. That's the plan using the B fusion framework. Be more efficient to use. A lot >> of people are skeptical around running machine learning on these are not skeptical because, I mean, it's great for any time you have the opportunity to automate something or used software to make something go away. That's not the difference. You're undifferentiated, so it makes sense. But I just can't figure out where, specifically, within these fears of being targeted to use >> where envy sphere as in, Well, >> if I'm operating the sphere on top operator, I got Debs kicking around the corner. I got a cloud Mom reclaiming. Where's this fit in? Where >> this fits into essentially any place for a visa is running. It doesn't matter if it would run on via MacLeod and for any other for cloud partnerships or on the the edge of our Vesey runs. This is a core capability of the sphere, so it doesn't matter. You know where physically or infrastructure is, we would be able to expose this technology. The idea is also that you mentioned the trends in the A six as they're coming into the enterprise. There's an architectural changes also coming in, and in the server perspective, it's just it's the servers are actually getting more dense there, in there, in there in the accelerator infrastructure that they have in them. So you're seeing four to a GP using a single server. Those are very powerful machines. You can just move oil, represent a single machine again. That brings us back to be fusion and descend. The segregated model affects territory used, which is very similar by the way to centralize stories use. >> You guys are on something really big here. I think that hardware assists off load anything. Hardware system, harbor off load is gonna be a more of a bigger trend. And we saw it happen big time and hyper converge just for storage and everything. But I think as you want to stack where kubernetes gonna flourish? Yeah. I mean, imagine all the service is that he turned on Turned off. I mean, that's not I mean, men even know when it gets turned on or off. >> Absolutely offload for awhile with things like a raise, right, trying to push processing off to a bigger ray that you've got there. And then one other thing you said that I think was really important is the audience, right? If you look at a i n m l, we have traditionally haven't talked to the data, scientists of the machine learning folks. And we need to get to the I t. Folks that air supporting those workloads saying similar to some other workloads that were new and saying these were gonna come your way. And so we need to be prepared and you need to be able to leverage. So >> what's the What's the pitch to those folks? What's that? What's what you guys saying to them? Because it is a benefit for Debs and Dev Ops is to have an ops right. You got the ops down. Okay, see that and this change happening. But a dev, What's the pitch? But how do you get their attention? What's the value proposition? >> The the Actually, that's the beauty of it. It's exactly the same bottle proposition that the sphere in Vienna, where the Vienna state provides the developers and the only thing is that now we are letting the the office people to actually provide this doing this infrastructure as well in the same efficient manner. So it's your transformation. Basically, it's giving the exact same value proposition. >> Talk about the multi cloud tie in here. We've heard a lot about multi cloud and I think multi cloud in part anyway, is being able to run any application and workload anywhere. And one of things about your technology is the ability to not have to rewrite the application to take advantage of acceleration. Does it fit into multi cloud? And if so, how? >> Yeah, when we made the bet Fusion acquisition, if you look at their story, they had the any any any story as well, just like we do. And so, you know, we made announcement this week within video and eight of us and VM, where it's definitely possible of the technology that we have to extend that even further. And so, you know, the only thing I know with users going forward is they're gonna have more than one cloud, and so we just need to prepare for that and make sure that it works. And it works well across the board and the common layer. When you look at our multi cloud strategy is vey sphere is going to be at each of those layers. So if it's ties in disease here, it should be pretty easy to make it work in each of those environments. >> What was that What was the announcement you made you share? The big >> one was being able to use in video in the context of cloud in AWS. So's GPU capabilities and bring it to the service as we do on Prem. And so that was a big piece. And then we also obviously, in making that announcement talking about Hey, you know, this is a critical area for us because not only are we doing this, but we're also saying that your bit fusion will help enhance this because we think in video and bit fusion work very well together as well. >> And is that a product of service? Ah, go to market initiative. >> In the case of the coordinated us, it would be offered as part of the service. So when you can consume the compute, you know you want a GPU, it'll be there for you to help run that workload in the cloud. >> And that's available. When >> that's an nvidia in AWS kind of question. When they are making that infrastructure available, it's essentially going to be a nun. In another instance, type that the ember cloud in AWS will offer okay, I >> mean, it's a tech preview. >> What if some of the things that people should know about because again, in the pattern I'm seeing here of'em world is as in love to stack with kubernetes being that abstraction layer that guessing eyes promoting heavily on rightfully so. We're big fans communes with that for the beginning is that you're gonna have this this purpose built, um, native capability so that when you guys got this native vibe going on native to hype the sphere native TSX native, what does that actually mean? Native like Cooper, naked native on I. But what does it native mean? Explain to the audience what that actually means. >> I'll start up. Sure. You could >> elaborate 30 minutes if you want. But what is that >> true native native? The idea >> for us was used kubernetes really two ways. You know, most of the time when we were talking about Cooper Naser Containers, it's running that on top of these Fair right? What happens if you could take the DNA of that and put it actually inside of east here? Right, so not only you could run these clusters and native pods, but you could also leverage some of the value and one of the things that Cubans does really well is it handles workloads really well. So if we take an example where we have 145 e ems and they make up your app, right, normally you'd have to go to each one of those and figure out OK, let's make some changes in tweaks. And now what I can do is I can treat all of those is one workload and I can move them. I could do really interesting things with that. And that's the power one of the powers that you have with Kubernetes. >> And that's where the differentiation. Then you don't think that there's a >> Yeah, exactly. I mean you are essentially getting There are a lot of benefits our customers, our values value that the customer is getting today from V Sphere, generically speaking, and our longtime customers are familiar with the value propositions. And what we are saying is that when you're getting something as a native capability is that essentially ties into all the other capabilities that you already were know very well and you will be able to get those. But with on top on, sometimes on top orbit in conjunction with what >> is that gonna enable? Now let's talk about the enablement. >> So let's go back all the way. If you go all the way back to be fusion, for example, if you enable it is a native technology, then if you're running containers or viens on the sphere natively they can consume to be fusion technology. If you have cool, it is. It can orchestrate natively, the PM's and containers that are using the confusion to collision. Excited. Oh, so this is the whole thing, >> more efficient platform standpoint, >> and it's easier to manage as well, because you don't have to install a bunch of stuff on top of each other because it's needed. It's part of the first. >> A lot of hassle go away that people might >> take it in and you're gonna have to guess tomorrow they're going to go deep into it with >> you. Great, we're excited. So we're hearing a lot, obviously, but kubernetes at this event and and but most of the audience, they're not developers. So how can you use the sort of bit Fusion mojo to attract developers for some of these new workloads, that air come into the marketplace? >> Yeah, I mean it's all about acquiring new audiences in a case of infusions. More the data scientists. In the case of the communities, it's more around the developer. But I think let's use the kubernetes examples as a good one and what we announced with Project Pacific. Basically, the way it looks, the technology looks to them. It'll look like the kubernetes, a p I with a little bit of east for goodness from the operator perspective, the people that we know the 20,000 that are here, it looks to them like the sphere was from kubernetes Goodness. So that's the right mix is you've got to get it. So it looks exactly the smells and feels just like what they're used to. And I think that's a that's a key aspect. And then for the data Scientists with fusion, we really need to say Okay, you know you want to run these workloads, but she's you're paying really a lot of money for these expensive, isolated devices, and you could get more value by kind of grouping them up and making sure that they're used kind of in aggregate, right? >> So there's more leverage on the data science side So if I'm say hiring someone I know I'm or more to work with with >> exactly, essentially, it's it's the same story. They don't need to change their applications, their framework. Their models use the same could interface, which is the GPU interface for for the GPS computer. >> So So let's talk about that. So data scientist, you know, they always complain that most their time is spent wrangling data That's their, you know, bugaboo. And then there's a collaboration between data scientists and developers, which probably doesn't happen enough. What are you seeing in terms of the trends from the data science role? And can you help solve some of those problems? >> Well, what we are about to solve is really access access to infrastructure for them. Easy access to the infrastructure in their software stack. And the way to get there is to make the data engineers that serve these data scientists and the application administrators that surges data scientist to get easy access to the infrastructure Dany to provide the software, and that's where the sphere eventually comes in. So it's not the Celia direct relationship with the end users. It's more enabling the entire organization that actually served these end users and let them use as much infrastructure as your partners. And >> that and that and user organization. The buffer >> guys last question share what the plans are. What's next? What's your goals for the next 6 to 12 months? I'll see. Get the acquisition under your belt. Native in these fear, a lot of other cool things. I mean that I could talk about >> customers and maybe you can talk about product from a customer perspective. You know, we want engage in proof of concepts. So we want to bring them in, let them test out the software. It already works with the beast here, so I'll be running with multiple proof of concepts across the globe. We >> use cases in the U. S. Case or what? >> Yeah, I mean, it's it's pretty simple at the moment. It seems to be most people that are using GP use around ml. We have a great demo down the floor that shows people trying to run inception, three year resident 50 And how can we actually help those v EMs that are running that? So that's gonna be my focus. The next six >> years you want get some use cases come over here, bring him up to Mike. >> And from that perspective, I mean, obviously, we acquired occasion in an early stage. The technology works well. It works well enough to be product eyes. However, Veum, wherein the sphere has very high enterprise software stone standards in terms of security and management and governance. All this capabilities so that's going to be are focused on the next, you know, even almost a year to make sure that we bring it up to a level where we can confidently provide it and sell. It is a product >> you gotta engineering hye bar there absolutely thanks to Russia coming on keeping the update, the end world coverage Breaking it down. 2019. It's the Cuba job for David. Thanks for watching Be back with more after this short break.