(corporate electronic xylophone jingle intro) >> Good afternoon and welcome back to our very last segment of Tuesday's live broadcast here on theCUBE from AWS re:Invent in fabulous Las Vegas, Nevada. My name is Savannah Peterson and I am joined here by the brilliant Paul Gillin. Paul, end of our first day. You holding up, are you still feeling overwhelmed with fire hose... >> Savannah, yet my feet are killing me. (savannah laughs) >> Yeah, we've done so much walking in these chairs. >> 14,000 steps already today. It's not even dinner time. >> Hey, well, at least you've earned your dinner, Paul. I love that. I love that. I'm very excited about our next guests. We have Krishna and Sowmya joining us from Tata Consultancy Services. Now, I was impressed when I was doing my background research on you all. The Tata Group has locations in 150 different spots, 46 different countries. You have over 600,000 employees on the team. We are talking about absolutely massive scale here but, today we're going to be focused specifically on the Tata Consultancy Services. Sowmya, can you tell me what you all do? What is that team specifically in charge of? >> Yeah, TCS, first of all, thank you very much for inviting us. >> Savannah: Our pleasure. >> Maybe the last session but, we'll make it very lively. >> Savannah: It's going to be the best session. That's the best part of the day. >> Yes, that's the attitude. From a company standpoint, we are a 50 plus year old company. Part of the Tata group. We focus on IT services. We are categorized as industry verticals and we have horizontal services where AWS is one of the horizontal services that we have. And, when I talk about TCS, we focus a lot more on growth and transformation of our customers. That is one of the key objectives of the current company's growth, I would say. So, that is TCS in a nutshell. >> Extraordinarily important topic to be focused on right now. Growth, transformation, pretty much the core topics of the show. I know you're on the hospitality and transportation side of the business, which is very exciting. And, we're going to dig into that a little bit more. Krishna, you're overseeing the world. Tell us a little bit more about your role within the whole ecosystem. >> Yeah, thank you for the opportunity. Great meeting all of you. It's been awesome experience here. re:Invent is coming back, catching up, right? 50,000 people compared to 25,000 last year. So, great to see and meet all of you. Coming to my role, I am responsible for AWS Business Unit within TCS. That means I am responsible for anything that happens on cloud, on AWS. It's a Full Stack unit. I have the global responsibility. That's whether it's a applications, data, infrastructure, transformation that happens, as well as OT at the edge. So, that's my responsibility. >> Savannah: Well, I love talking about the edge. One of my favorite. >> Transformation is a theme of what you do. We heard that the pandemic accelerated digital transformation initiatives at many companies. How did you see the pandemic affecting your business, affecting the customers you were working with? >> Pandemic definitely kind of accelerated a lot of cloud adoption, right? A lot of companies initially focused on resiliency, coming back to handling the pandemic, the situation. But, it also drove a lot of innovation in the business models. They had to think on their feet, re-look at their business models, change the channels and that continued. Pandemic is thankfully gone by but, the transformation actually continued. The way that we actually see on cloud, especially transformation, it has evolved. What we call as Cloud 2.0. Now, cloud is actually more focused on future-proofing the businesses. And, the initial days it was more about future-proofing the technology and technology architecture. But, it has evolved to future-proofing businesses. That means implementing new business models, bringing in agility, measuring the business value. And, that's where we see a significant traction. >> So, it's not about technology then. It's not about infrastructure. >> It is about technology but, really delivering business value. It's about, how can I improve the customer experience? >> Well, can you give us a couple of examples of companies you work with that embody this idea? >> I can imagine in the travel and hospitality zone. Probably few communities more sensitive than when someone's having a disruption or frustration within that process. And, perhaps few time periods less chaotic than the last few years. Tell us about your experience and what you've seen. >> Absolutely. To answer your question, first of all, coming out of pandemic, right? Many customers in the travel and hospitality industry where legacy, did not modernize for the last decade or so because, there have been many ups and downs in the industry. So, during pandemic, post-pandemic, one of the the way they wanted to rebound was, can we do the transformation? First of all, cloud as a technology adoption, but, beyond that, how do customers derive value, business value? That is one of the key aspects of the old transformation. And, if you take, I can give a couple of examples. Avis Car Rental, they had monolith mainframe applications and, that was there for almost couple of decades, right? But, over a period of time, they were not able to have the availability of those applications. There were many outages. As a result, businesses could not do the bookings. Like OTAs, customers could not do the bookings, the application was not available most of the time. And, it's all legacy, right? So, that is where we all came in, TCS. How do we first of all, simplify the complexity of the landscape? That is one. Then, second is, modernize the legacy application. That's the second thing. Third is, how do you scale it? Because, everyone wants to go faster, right? How do you scale it? That is where we partnered with AWS as well, to bring in some specific solutions. One example for Avis', their Rent Shop. Because, of the lack of availability, because, it's monolith application and legacy application. It was not available. So, as a result, we partnered and we brought in our contextual knowledge of the car rental industry to kind of transform, move it to cloud. And, today, as a result of it, Avis was able to save millions of dollars from a MIB standpoint. Second, in terms of availability, that was 99.9% availability. As a result, they had a pick in their business revenue as well. So, this is one of the ways that its helped. The second example I want to quote is, United Airlines. Here again, we've been present for a long time. We have a deep industry knowledge of the airline industry. So, we brought in our airline contextual knowledge and the United landscape to bring in a TCS's solution that we developed. It's called the Aviana. It's an intelligent operations solution for the airline industry, which we have developed. It's on AWS as well, that is being implemented in United. As a result, the ground staff, they have to take decisions on the moment when there is a irregular operation. That could be flight delays, as a result, customers connections will be lost. >> Savannah: Baggage. >> Baggage, right? Baggage delays. >> So many variables. The complexity... >> exactly >> in this matrix is wild. >> So, leveraging the Aviana solution, the ground staff were able to take decisions based on exceptions. They were able to take decisions quickly so that, they improved the customer experience. I think that was one of the key successes for United in the recent times. So, those two are the examples that I would call where customers have the right business value. So, cloud was not just for technology. They all are deriving a lot of business value as well. I would say. >> How important do you think it is for companies facing these unique challenges and scaling to work with partners like TCS? And, I'm sure you would say very important, but, tell me a little bit more why it's so important and those core benefits that they're going to get. Krishna, let's start off with you. Yeah, let me take again the AWS cloud transformation, right? TCS has formed AWS Business Unit two years back. So, we are a covid baby in a way. We have been working with the AWS for more than a decade but, we formed a dedicated Full-Stack Unit to drive cloud transformation on AWS. In these last two years, we've grown three X and customers we have added 400 new customers we have added. >> Nicely done. Just want to see you there. That's huge. Especially during these times. Congratulations. >> So, it's basically about the scale that we bring in. What we have done as a differentiation is, if you look at the entire cloud journey, right from taking a decision which cloud is, right, all the way to the cloud migration modernization and running operations. So, we have built complete platform. AML based platforms, where we have taken our delivery wisdom and codified it onto these platforms. So, we support around thousand plus customers on AWS in varying capacity. All of that knowledge is codified and, that is what we bring to the table, to the customers. And, so, customers obviously appreciate that value that best practices that are coming. And, coupled with that, the industry knowledge that we have on banking, life sciences, healthcare, automotive. So, it's partly the IT, it is the industry transformation as well. Because, we are working on connected cars, for example, in automotive. We are working on accelerated drug development platforms. We're working on complete banks as a platform that we have. TCS has built on AWS. So, 400 customers are there. It's the complete banking and insurance platform. So, this is the combination of the technical expertize that is digitized using platforms, as well as the industry knowledge, is the reason why customers work with us on the cloud transformation. >> So, we're seeing you talk about the vertical industry knowledge. AWS also has its own vertical industry plays. How do you, I guess, coordinate with them or, do you compete with them or, do you stay out of each other's way? >> No, we actually collaborate aggressively. >> Savannah: I like that (laughs) >> Right, so, it's not.. >> Savannah: With vigor. >> With vigor. TCS supports approximately 14 verticals. With AWS, we went with the focused industry play. We said we look at financial services, travel, transportation, hospitality, healthcare, life sciences and automotive, to start with. And, we have Go Big plans with AWS. very focused. The collaboration is actually at the industry solutions because, AWS is a great platform, ever evolving, keeps you on on your toes to really adapt it. But, that is always going on, the collaboration. But, the industry, I'm actually glad AWS last year took a pivot on focusing on industries. Now, we talk the same language when we go in front of a board or a CEO or COO. Present it. We are talking about the future of the industry not just the future of the technology. So, it's a win-win. >> You are also developing products on top of AWS that are not industry verticals, that build on the platform. What kinds of products are those? >> For cloud transformation, for example, consulting. We have a product called Cloud Counsell. We have a decision engine on the data side. We have something called Cloud Foundation, Mason. CloudMason. It's just the foundation, right? And, entire migration and modernization factory. And, the last one on cloud operations is actually Cloud Exponence. So, these are time tested. You have Fortune 500 customers using this regularly actively leveraging that. And, these are all AWS in a well architecture framework certified. So, they work well and they're designed to work on cloud, not only in the native environment, but, also legacy environment. Because, enterprises is not just only native, cloud-native. There is a lot of legacy. Sowmya spoke about the mainframe model... >> So much legacy, we were talking about it. >> So, you have to have a combination of solutions. So, the platforms that we're building, the products we're building, work in both the environments. >> Yeah, and that agility and ability to help customers navigate that prioritization. I mean, there's so many options. We talk about how many new companies there are every year. New solutions. Our adoption of technology is accelerating. As, McKinsey said, we went through 10 years of technological evolution and workplace evolution over the first six months of the pandemic. So, really everything's moving at unprecedented velocity unlike ever before. We have a new game here on theCUBE specifically for this show. And, we are challenging our guests, prompting our guests, to give us a 30 second sizzly sound bite with your hot take on the most important themes of this year's show. Think of it as a thought leadership moment. Opportunity to plug if you really want it. Krishna, you've just given me the nod. I'm going to start with you first and then we'll then we'll pass it along, yeah >> Sure. I think on thought leadership, the way that on cloud, business value is the focus, not the technology. Technology is important, but business value is the focus. And, the way that I see it evolving is with quantum computing coming out more and more, becoming relevant, and Edge is actually becoming quite active as well. All this while on cloud, we focused on business value at the centralized place at the corporate. But, I think the real value of cloud is when you deliver the results, business results, where the customers consume it, that is at the edge. I think that's basically the combination of centralized and the edge is where the real value of cloud is, right. And, I also loud, I know you said 30 seconds but, give me 30 more seconds. >> I like your answer right now. So, I'm going to give you a little more time. Yeah, thank you. >> You've earned more time. (laughs) >> So, I like the way Adam said in the keynote, if you look at it broadly, I categorizes two things. There are a lot of offerings that are becoming comprehensive, like AWS Connect, bringing in workforce management into it, making it a complete end to end product. Similarly, Security Lake, all bringing in the entire security and compliance under one, similarly data. So, there are lot of things that he announced where it is an end to end comprehensiveness of the thing. But, what I love about is, what Amazon is known for, supply chain. So, they rolled out AWS Supply Chain offering. Walk Out technology. So, the Amazon proposition is actually being brought to AWS as a core proposition. I think that's very futuristic and I think we can see more and more customers, enterprise customers, adopting AWS more to drive transformation >> Badly needed right now. Supply chain resiliency. >> Supply chain really having its moment the last two years. File under two words. No one knew, many of us did who worked in it before this. And, here we are, soon as we lost our toilet paper, everyone's freaked out. I love that you talked about business value and also that the end customer is on the edge and, everyone kind of forgets we are essentially the edge device. This is the edge device, it's all around us. And, all the technology that we're all using that you're even talking about is built right inside here from my airlines app to my car rentals to all of it. All right Sowmya, give us your 30 second hot take, roughly. >> Taking the cue from Krishna, right? Today, things are available on AWS Marketplace. So, tomorrow, somebody wants to start an airline, they just have to come and plug and play the apps that are available in the marketplace. Especially your supply chain. The Amazon is known for that. And, a small and medium business they want to start something, right, a .com. It's very easy. So, that's something that we are all looking for. The future is going to be very, very bright and great for the businesses, is what I would say because, most of it could be plug and play with all the solutions. >> Paul: It's already been built. >> On the cloud, so, we are looking forward to it. The second thing I would talk about is, we have to take it to scale. How more and more people can leverage AWS, right? The talent is very important and, that is where partners like us focus on re-scaling our talent. We have 600,000 people, right? We are not just... >> 600,000 people! That's basically as many people live in the San Francisco Bay area for contexts for our listeners. It's how many people work for Walmart? >> It's 1.2 million in Walmart? >> Is it really? >> It is, yes, yes. That's work for Walmart, sidebar. >> So from that standpoint, as the company, we are focusing on re-skilling, up-skilling our talent in order to work AWS cloud and so on, so, that they can go and support our customers. That is something that is very important and that's going to be the future as well. Bring it to scale, go faster. >> I love that you just touched on the fact that you essentially have to practice what you preach because, you've got to think about those 600,000 people in a 100 locations across 40 plus different countries. I love it. Sowmya, I'm going to close on that note. The future is bright, just like your fabulous blazer. >> Thank you so much. Krishna, Sowmya, thank you so much for being here with us. We can't wait to see what happens next, who you help next, and how Tata continues to transform. Thank all of you for tuning in today. A full jam packed day of coverage live here from Las Vegas, Nevada. We are at AWS re:Invent with Paul Gillin. I'm Savannah Peterson. We're theCUBE, the leader in High-Tech Coverage. (corporate electronic xylophone jingle outro)

>>Welcome back to HP discover 2021 the virtual version. My name is Dave Volonte and you're watching the cube. We're here with Manav said Donna, who is the global head of sales and market development for cognitive business operations at Tata consultancy services Tcs. And we're gonna dig in to digital transformation and take a deeper dive into the customer journeys. Welcome Manav, >>thank you. Dave, thank you for inviting me to this. Uh appreciate and looking forward to have an intriguing dialogue. You Me too. >>Me too. I mean we talk about digital transformation all the time prior to the pandemic. You know, a lot of it was kind of buzz wordy um and there's a lot of complacency around it. But as we know if you weren't digital during the pandemic you're out of business but people were forced into it. They were rushed into I called the force marched the digital so you really didn't have time to be planned full. And now people are stepping back and saying, okay now we have an opportunity to get digital right and put that in air quotes. How do you think about digital transformation? What do you mean by that? >>Okay, see I think uh the way we look at it at this, yes, I will, I will probably take a step back where in um while the digital transformation has been in play, not just over the last year since the pandemic began, but um even before then uh where the shift uh in the customer organization that we have been seeing is largely from being product centric to be purpose centric, wherein the whole focus of the entire existence is to be able to serve the purpose for their consumers, their customers and so on and so forth. And and if you look at it, for example, total energies right? The looking to sell or produce fuel. They are looking to be responsible energy company producing, reliable, affordable and clean energy for the consumers. Right? Similarly, there are other examples damaged shipyards who are looking to be more of a maritime solutions provider rather than just a shipbuilding company. Uh, so, so what's really happening when the purpose is being the driving force behind any organizations agenda or even reason of existence? That purpose is actually the driving force also followed the digital transformation. That is basically shifting the pace of the way businesses are looking to drive consumer experiences, time to market and so on, so forth. Right? And if you see our we launched our new brand positioning in the last quarter, that's building on belief and and that's basically centered around this whole purpose driven mindset. What that means is that we believe that and then the technology is enabling digital transformation are going to be the pillar of the whole shift of the re imagination of the business models wearing businesses are coming together across industries and driven by the key goal of serving the customer in terms of driving the enhanced experience rather than just selling a product. So that's basically is really happening. And having said that now in the last year or so, what pandemic has done is basically accelerated the pace by a condom. Deep right? So so in that sense, some of the organizations that were not ready at that point, they are also kind of transformation and and and taking that leap frog, I would say so from that perspective and going by again by our brand positioning statement, building on belief, right? That's really helping towards that pretty good thing, the overall journey, three horizon business and I'll come to that in a minute, but I hope it is answering your question of what digital transformation and how pandemic has really helped it. >>I just want to get 1 um point of clarification you said and you cut out there for a second, you said go from product centric too, >>but to centric >>platform centric, got it, >>but centric >>purpose centric uh building on belief, got it. Okay, so something else you said they picked up on, you talked about um actually you know crossing industries and this is something that's new and that's enabled by digital. I want to get your thoughts on it. I mean if you look at industry structures historically, whether it's manufacturing or automotive or financial services or healthcare or media and entertainment, whatever it is, there was a value chain, there is a value chain that's built up in that business might be uh it might be R. And D. Sales and marketing, service, manufacturing, etcetera. And if you are in that industry, you largely stayed in that industry forever. And now you're seeing these, a lot of big company, a lot of big tech companies having a dual disruption agenda, not only horizontally to from a technical standpoint, but you're seeing amazon get into grocery, you know, they're they're buying studios, you're seeing your Apple get into finance. And so the enabler is data in digital and that talks to the business model re imagination that you're talking about. >>Absolutely and absolutely exactly what is happening, that's what I'm really talking about. And we are firmly believing that boundaries or those boundaries are going to be blood even more so going forward, as I took a few examples and you also talked about Apple, or or even amazon all the for example. Right, so all these technology companies are just being disrupted. So, having, having said that, that data being the new fuel at the same time, Cloud being the new er now cloud as a technology that is enabling the business model. Re imagination is not just on the outside, but also on the red side. And and that's where the boundaries are becoming so closer between edge and the cloud. And how how do we give that flexibility for to the customers, to people to adopt those digital technologies across the enterprise? Right. That's what, that's what the ship that we have been seeing. >>How do you see ecosystems playing in this? I mean it's kind of, I know it's an overused term but it seems to me to be increasingly important, its power of many versus the resources of one or a few. How do you see ecosystems driving? You know, this, this purpose driven business you talk about? >>Um very, very closely I would say, and I'll give you examples also in that sense. Right faster. Um if I talk about the journey I mentioned briefly earlier about three horizon based journey, right. The first and foremost being the setting up the digital foundation that basically could be through the combination of cloud, iOT analytics, artificial intelligence and so on so forth. Right? And then eventually moving on to re imagination of business models and then leveraging the purpose led ecosystem. Now in the Horizon one, when we are setting up the digital foundation, that is where the whole ecosystem comes into play. Where and where and if I talk about our co innovation network partners like HP, where we are working together to really bring in that flexibility for the customers, even in on premise environment, giving them that kind of uh features that they can experience also in the cloud to be really able to leverage the whole our beat at the edge or in the cloud. So that's where the kind of ecosystem coming together and and and those are also some of the challenges that we have seen that customers are facing today to be able to achieve the first horizon in that journey. The challenges like accelerated or all the time to market challenges. Like are they able to achieve the flexibility to be able to offer to the business and and challenges? Like are they able to achieve transformation at scale or is it just appointed um pointed poc sort of thing? Right so bringing the ecosystem together is able to help customers address those challenges, be it in terms of consumption driven, addressing the flexibility needs, be it in terms of the pre integrated solutions addressing the challenges related to time to market and so on and so forth. >>Can we stay on? The challenges for a minute? As I said, pre pandemic, there was a lot of complacency. We've all seen that meme of the wrecking ball coming in and kind of a tongue in cheek joke, but but the complacency is gone, so so there's there also, but still organizational challenges. It's not complacency anymore, but what's the right regime? What's the right approach? Uh everybody wants to get digital right, but a lot of people, you know, that's a do you see that as a challenge? Actually, not knowing where to prioritize it and you know, how can you help in that regard? >>Yeah, So, and I would also like to like to talk about what we have done in in certain with certain customer with challenges. Um some of the things I'll introduce TCS Cognex here, this is our platform which basically brings together the capabilities in a pre integrated uh, for, of predefined solutions accelerators of our value builders as we call it, um, for customers to be able to just integrate their environments to be able to manage the whole infrastructure or of the landscape in a completely automated and analytics driven manner. Right, so that's that's one way of addressing those challenges. What it also does is it gives that um power to the stakeholders in the organization to be able to address the key challenge of time to market because it is giving out or coming out in a pre integrated manner and be able to achieve that benefits or realize the benefits of transformation In in an accelerated time frame instead of waiting for 18-24 months, how can it be done in 3-6 months, for example. Right. That's that's that's one set and and similarly, uh if I talk about the flexibility, right, consumption driven manner is extremely, extremely important. And if I talk about hybrid cloud, so to say right today, About 1-2% of the on premise infrastructure is actually in a consumption driven manner while cloud is always gonna consumption to a manner. The trends that we're seeing is that by next year about minimum 15% of the on premise infrastructure in a hybrid cloud environment will be about or will be delivering a consumption-driven manner and and that's what is going to address the various the opportunity as well as the challenge to address that particular aspect of flexibility and that's where the ecosystem with the likes of us, teachers and HP coming together to provide solutions that are addressing those needs of our consumers. >>And when you talk about the consumption driven, obviously talking about things like HP Green Lake, that's a model that enables that kind of consumption model. You know, I feel like, I mean, I feel like that's kind of table stakes to be honest with, you, pointed out 1 to 2% of it. I said wow, clouds been around for a long time and now, but now we're seeing the rapid adoption 15% and we're also seeing, I mean I think I'll give H PE some props on this because they've got their whole company behind it, but there has to be a complimentary shift in the mindset of OK, we're not now selling boxes anymore and I think HP has done a pretty good job of this. They've made some announcements recently to that effect. They're doing an HPC. We just saw some storage announcements, so it's no longer, hey, here's a box to sell it and this is where a company like Tcs comes to play. You, you've, you've never had that box mentality, you have a solutions mentality and so, so the industry is moving in a very rapid pace now. My question is, are the customers ready for it? Are they ready for it? Because they have the cloud experience, are they ready for it on prem and what do they need to do to get ready for that? >>See um, to answer your first question already and what really is the trigger point for them being ready? The answer is yes. Okay. Um, I would say a large percentage of the customer base was ready even before pandemic, but pandemic has really made it even more prominent in the customer and that has become a need. We are seeing so many customers today. I mean, uh, in my global role, I'm seeing across industries and across markets right from north America to Australia Japan. We're in, we're in the need for having consumption. Everyone is even at on premise while cloud is definitely there, but even at on premise is so much so that really is the trigger um, at the same time now what is really driving that trigger apart from pandemic is to be able to offer that flexibility to their business. Businesses are basically reimagining, reimagining their whole uh where they are reaching out to their customers, where they are expanding into the newer markets and the speed is extremely, extremely important and that's what is really being the whole consumption, let's >>peel the onion on that. Somebody asked me this the other day why why as reserves. I said the same thing, flexibility and they're like, yeah, okay, but give me some examples. And so I said, well, first of all, they're paying by the drink. So it's a much fairer for the customer model instead of okay, charge them for what they're not even going to use or what they might use for a day or two or a month. The other is experimentation. It just seems to me that in the digital world you got to fail fast, You don't know, you don't know what, you don't know. And so these consumption models allow you to spin up experiments very quickly and cheaply and only pay for what you use is, am I, am I getting that right? >>Absolutely, Absolutely. And and and that that's exactly what the model is, that we as uh as a partner together, that we are offering. Only one thing that I would want to highlight here is, um while that's the foundation, as I said, it is setting up the digital foundation, giving the customers the flexibility. And if I talk about example, uh one of our british large, I am who really is leveraging this technology for them to be able to bring more resilience and boring traing and scales departments uh to be able to, you know, on the manufacturing line and ultimately driving to the sales value chain. So those are the things that are happening. And you took an example of basically talked about consuming purely as a service what you use. This model is basically expanding everywhere very recently. I mean I saw an out of bicycle as a service. I mean instead of buying a new bicycle, I'm just able to get one bicycle, you use it for a month, return it back to the to the owner to be able to use it only when I need it, let's say for example, so that's what is really happening even in the digital transformation, I just needed for a time basis for a particular purpose. I served that purpose, ultimately driving the business resilience, agility and then ultimately serving that purpose. Yeah, >>I think I'd love your thoughts on this. I think the real opportunity here is to for for technology companies like HP. E working with TCS to create a layer I called a layer that spans on prem name your favorite cloud or multiple clouds goes across clouds goes out to the edge. That's a layer that that hides all the underlying complexity. You're going to take care of that for me uh because it's complicated. No question about it, the bigger the universe gets, the more complicated gets. But as as a customer, I want to hide that complexity because I don't want people doing plumbing, I want people focus on on strategic initiatives and that to me, seems to be the killer app, if you will of infrastructure in the future. Is that that abstraction layer? Do you see it that way? >>Absolutely. And that's where the easiest Cognex comes into play very strongly. Right? As I said earlier, it's basically it said actually uh an air driven human machine collaboration suite. So what that really means, it is bringing together the capabilities from analytics to ai with our machine first principles and and really giving that obstructing player in a pre integrated manner from edged right up to the cloud and bringing it all together for the customers. So that that's exactly what how we are really helping the customers, um a team that, again, addressing those challenges of exploration, time to market flexibility and more importantly unifying the entire landscape into one single view if I am a C I O, or if I am a CFO, I want to see what is important to me, rather than going through multiple different dashboards support, so to say, Right, so that's what pieces Cognex, there's an important role in obstructing everything and presenting, identified you and in a draft formed service delivery model for the customers. >>So the history of TCS is pretty amazing. You guys have, I mean, the, the ascendancy of the company over the decades is actually so, so impressive now and your relationship with HP and now, of course, HP goes back, I think it goes back to the 90s. Maybe you could talk a little bit about that relationship, where it's come from, how it's evolving and where you want to see it going. >>So I think it's a um uh when you go back so long, right? Uh the only way you're able to sustain that long relationship when there is a value that we have been able to deliver to each other, and more importantly, the value that we have been able to deliver to our customers, right? And that has always been the, the mantra of the whole relationship and that continues to be going forward as well. So, so in that regard, I mean, while I would rather focus more on the future, history is definitely good, but I think going forward, um the kind of work that we're doing together to be able to solve some of our customers globally across the base across the industries is extremely valuable, both to us as well as two HP, I'm sure. And and that's where we are really looking to have uh, providing real value to our customers, not just from the technology perspective, ultimately elevating that value. How do we help them solve the business problems and not just the technology solutions? >>Well, I think we've learned that that's the 11 big thing we learned from the cloud is if you just shove all your stuff in the cloud lifted and shifted it. So what, uh, it's that operating model that you talked about earlier, that really is how you, you, you drop, you know, if you're a large company, you're talking about billions, uh, to the bottom line, not, you know, hundreds of thousands or millions, but that's, that's a game changer. I'll give you a final word enough. >>Absolutely. Absolutely. I mean, as they said, I think, um, I hope I would not end up repeating my mistake, but, but that, um, solving the business problems, leveraging technology and, and irrespective of the location where the technology is based being on edge or on the cloud. It's the whole model of addressing the customer demands and the customers need is extremely, extremely important. So that's that's what the whole mantra is and that's what is really were driving us forward together in the journey, >>major shifts in industry. Digital is is the driver and and Manav. Thanks so much for being on the cube. Really appreciate your time. >>Sure, thank you. Thank you for having me >>And thanks for being with us for HP Discover 2021 the virtual version. You're watching the Cube, the leader in digital tech coverage. Keep it right there.

(upbeat music) >> Welcome back to HPE Discover 2021, the virtual version. My name is Dave Vellante and you're watching theCUBE. We're here with Manav Sadana who is the Global Head of Sales and Market Development for Cognitive Business Operations at Tata Consultancy Services, TCS. And we're going to dig in to digital transformation and take a deeper dive into the customer journeys. Welcome Manav. >> Thank you Dave. Thank you for inviting me to this, appreciate and looking forward to have an intriguing dialogue with you-- >> Me too. >> And David. >> Me too, I mean, we talk about digital transformation all the time prior to the pandemic, a lot of it was kind of buzz wordy and there was a lot of complacency around it. But as we know, if you weren't digital during the pandemic you were out of business, but people were forced into it. They were rushed into, I call it a forced march to digital. So you really didn't have time to be planful. And now people are stepping back and saying, "Okay, now we have an opportunity to get digital right." I'll put that in air quotes. How do you think about digital transformation? What do you mean by that? >> Okay, see, I think the way we look at it at TCS, I will probably take a step back wherein while the digital transformation has been in play not just over the last year, since the pandemic began but even before then, where the shift in the customer organization that we have been seeing is largely from being product-centric to be purpose-centric wherein the whole focus of the entire existence is to be able to solve the purpose for their consumers, their customers, and so on so forth. And if you look at it, for example, TotalEnergies, they're looking to sell or produce fuel. They are looking to be a responsible energy company producing reliable, affordable, and clean energy for the consumers. Similarly, there are other examples, Damen Shipyards who are looking to be more of a maritime solutions provider rather than just a ship building company. So what's really happening when the purpose is being the driving force behind any organization's agenda or even a reason of existence. That purpose is actually the driving force also for the digital transformation that is basically shifting the pace of the way businesses are looking to drive consumer experiences, time to market and so on, so forth. And if you see our, we launched our new brand positioning in the last quarter, that's building on belief and that's basically centered around this whole purpose-driven mindset. What that means is that we believe that even the technologies enabling digital transformation are going to be the pillar of the whole shift of the re-imagination of the business models wherein businesses are coming together across industries and driven by the key goal of serving the customer in terms of driving the enhanced experience rather than just selling a product. So that basically is really happening. And having said that now in the last year or so, what pandemic has done is basically accelerated the pace by a quantum leap. So in that sense, some of the organizations that were not ready at that point, they are also end of transformation and taking that leapfrog, I would say. So from that perspective, and then going by, again, our brand positioning statement, building on belief. That's really helping towards that particular thing. The overall journey is three horizon bases. And I'll come to that in a minute, but I hope it is answering your question of what digital transformation and how pandemic has really helped it. >> I just want to get one point of clarification, Manav. You said, and you cut out there for a second. You said, go from product-centric to? >> Purpose-centric. >> Platform-centric, got it. >> Purpose-centric, purpose-centric. >> Well, oh, purpose-centric. Ah, building on belief, got it. So something else you said that I picked up on, you talked about actually, you know crossing industries and this is something that's new and it's enabled by digital. I want to get your thoughts on it. I mean, if you look at industry structures historically whether it's manufacturing or automotive or financial services or healthcare or media and entertainment, whatever it is, there was a value chain. There is a value chain that's built up in that business might be, it might be R and D, sales and marketing, service, manufacturing, et cetera. And if you were in that industry you largely stayed in that industry forever. And now you're seeing these a lot of big companies, a lot of big tech companies having a dual disruption agenda not only horizontally tech, from a technical standpoint but you're seeing Amazon get into grocery. You know, they're buying studios. You're seeing you Apple get into finance. And so the enabler is data and digital. And that talks to the business model re-imagination that you're talking about. >> Absolutely and absolute, exactly what is happening. That's what I'm really talking about. And we are firmly believing that boundaries or those boundaries are waiting to be blurred even more so going forward. As I took few examples and you also talked about Apple or even Amazon, or the (indistinct), for example. So all these technology companies are just being disruptors. So having said that, that data being the new fuel at the same time Cloud being the new ERP. Now Cloud as a technology that is enabling the business model re-imagination is not just on the Cloud side, but also on the Edge side. And that's where the boundaries are becoming so closer between Edge and the Cloud. And how do we give that flexibility to the customers to be able to adopt those digital technologies across the enterprise? That's what the shift that we've been seeing. >> How do you see ecosystems playing in this? I mean, it's kind of, I know it's an overused term but it seems to me to be increasingly important. It's the power of many versus the resources of one or a few. How do you see ecosystems driving this purpose-driven business that you talk about? >> Very, very closely, I would say. And I'll give you examples also in that sense. First and if I talk about the journey, I mentioned briefly earlier about three horizon based journey, right? The first and foremost being the setting up the digital foundation that basically could be through the combination of Cloud, IoT, analytics, artificial intelligence, and so on for forth. And then eventually moving on to re-imagination of business models and then leveraging the purpose led ecosystem. Now in the horizon one when we are setting up the digital foundation, that is where the whole ecosystem comes into play. Wherein if I talk about our co-innovation network partners like HPE, we're working together to really bring in that flexibility for the customers even in On-premise environment, giving them that kind of features that they can experience also on the Cloud to be really able to leverage the whole power, be it at the Edge or the Cloud. So that's where the kind of ecosystem coming together. And those are also some of the challenges that we have seen that customers are facing today to be able to achieve the first horizon in that journey. The challenges like accelerated or the time to market, challenges like are they able to achieve the flexibility to be able to offer to the business and challenges like are they able to achieve transformation at scale, or is it just appointed, pointed POC sort of thing. So bringing the ecosystem together is able to help customers address those challenges, be it in terms of consumption-driven, addressing the flexibility needs, be it in terms of the pre-integrated solutions, addressing the challenges related to time to market and so on, so forth. >> Can we stay on the challenges for a minute? Like, as I said, pre-pandemic there was a lot of complacency. We've all seen that meme of the wrecking ball coming in and sort of a tongue-in-cheek joke, but the complacency has gone. There are also but still organizational challenges is not complacency anymore, but what's the right regime? What's the right approach? Everybody wants to get digital right. But a lot of people, you know, that's, do you see that as a challenge actually not knowing where to prioritize it and you know, how can you help in that regard? >> Yeah, so, and I would also like to like to talk about what we have done with certain customer-- >> Great, perfect. >> Challenges. Some of the things I'll introduce TCS CogniX here this is our platform which basically brings together the capabilities in a pre-integrated at for, of predefined solutions accelerators of value or value builders as we call it for customers to be able to just integrate their environments, to be able to manage the whole infrastructure of the landscape in a completely automated and analytics-driven manner. So that's one way of addressing those challenges. What it also does is it gives that power to the stakeholders in the organization to be able to address that key challenge of time to market, because it is giving out or coming out in a pre-integrated manner and be able to achieve that benefits or realize the benefits of transformation in a accelerated timeframe instead of waiting for 18 to 24 months, how can it be done in three to six months, for example. That that's one set. And similarly, if I talk about the flexibility. Consumption-driven manner is extremely, extremely important. And if I talk about hybrid Cloud, so to say. Today about 1-2% of the On-premise infrastructure is actually in a consumption-driven manner. While Cloud is always going to consumption-driven manner. The trends that we're seeing is that in by next year thereabout minimum 15% of the On-premise infrastructure in a hybrid Cloud environment will be about or will be delivered in a consumption-driven manner. And that's what is going to address the various the opportunity as well as the challenge to address that particular aspect of flexibility. And that's where the ecosystem with the likes of us TCS and HPE coming together to provide solutions that are addressing those needs of our consumers. >> And when you talk about the consumption-driven obviously you're talking about things like HPE GreenLake that's a model that enables that type of consumption model. You know, I feel like, I mean I feel like that's kind of table stakes, to be honest with you. I mean, you pointed out at 1-2% then I said, "Wow." Cloud's been around for a long time and now, but now we're seeing the rapid adoption 15%. And we're also seeing, I mean I think I I'll give HPE some props on this 'cause they've got their whole company behind it but there has to be a complimentary shift in the mindset of, "Okay, we're not now selling boxes anymore." And I think HPE has done a pretty good job with this. They've made some announcements recently to that effect. They're doing an HPC, we just saw some storage announcements. So it's no longer, "Hey, here's a box to sell." It's and this is where a company like TCS comes to play. You've never had that box mentality. You have a solutions mentality. And so the industry is moving at a very rapid pace now, my question is, are the customers ready for it? Are they ready for it because they have the Cloud experience? Are they ready for it On-prem and what do they need to do to get ready for that? >> See, to answer your first question are the ready and what really is the trigger point for them being ready? The answer is yes. I would say a large percentage of the customer base was ready even before pandemic, but the pandemic has really made it even more prominent in the customer. And that has become a need. We are seeing so many customers today. I mean, in my global role, I'm seeing across industries and across markets, right from north America to Australia, Japan, we're in the need for having consumption-driven is even at On-premise while Cloud is definitely there, but even at On-premise is so much so that's really the trigger. At the same time, now, what is really driving that trigger apart from pandemic is to be able to offer that flexibility to their business. Businesses are basically re-imagining their whole, where they are reaching out to their customers, where they are expanding into the newer markets. And the speed is extremely, extremely important. And that's what is really bringing the whole consumption-driven. >> Let's peel the onion on that. Somebody asked me this the other day, why as a service? I said the same thing, flexibility. And they're like, "Yeah, okay, but give me some examples." So I said, "Well, first of all they're paying by the drink. So it's a much fairer for the customer model instead of okay charge them for what they're not even going to use or what they might use for a day or two or a month." The other is experimentation. It's just seems to me that in the digital world you got to fail fast. You don't know, you don't know what you don't know. And so these consumption models allow you to spin up experiments very quickly and cheaply and only pay for what you use, am I getting that right? >> Absolutely. Absolutely. And that's exactly what the model is, that we as the partner together, that we are offering only one thing that I would want to highlight here is while that's the foundation, as I said, it is setting up the digital foundation, giving the customers the flexibility. And if I talk about example, one of our British large OEM who really is leveraging this technology. So for them to be able to bring more resilience and more (indistinct) and sales departments to be able to, you know, on their manufacturing line and ultimately driving to the sales value chain. So those are the things that are happening. And you took an example of basically, talked about consuming, purely as a service what you use. This model is basically expanding everywhere. Very recently, I mean, I saw a lot of bicycle as a service. I mean, instead of buying a new bicycle I'm just able to get one bicycle, use it for a month return it back to the owner to be able to use it only when I need it. Let's say for example. So that's what was really happening even in the digital transformation. I just need it for a time basis, for a particular purpose, I serve that purpose, ultimately driving the business' resilience, agility, and ultimately serving the purpose, yeah. >> I think I'd love your thoughts on this. I think the real opportunity here is to for technology companies like HPE working with TCS to create a layer, I call it a layer that spans On-prem name your favorite Cloud, or multiple Clouds goes across Clouds goes out to the Edge. That's the layer that hides all the underlying complexity. You're going to take care of that for me. 'Cause it's complicated. No question about it. The bigger the universe gets, the more complicated it gets. But as a customer, I want to hide that complexity 'cause I don't want people doing plumbing. I want people focused on strategic initiatives. And that's to me seems to be the killer app, if you will of infrastructure in the future, is that, that abstraction layer, do you see it that way? >> Absolutely. And that's where TCS CogniX comes into play very strongly. As I said earlier, it's basically it said, actually and everyone, human machine collaboration suite. So what that really means it is bringing together the capabilities from analytics to AI with our machine first principles and really giving that obstructing layer in a pre-integrated manner, from Edge right up to the Cloud and bringing it all together for the customers. So that that's exactly what, how we are really helping the customers achieve that, again addressing those challenges of accelerated time to market, flexibility, and more importantly, unifying the entire landscape into one single view. If am a CIO or if I'm a CFO, I want to see what is important to me rather than going to multiple different dashboards, so to say. So that's what TCS CogniX plays important role in abstracting everything and presenting that unified view and in a transformed service delivery model for the customers. >> So the history of TCS is pretty amazing. You guys have, I mean the ascendancy of the company over the decades is actually so impressive. Now in your relationship with HPE and now of course, HPE, it goes back. I think it goes back to the 90s. Maybe you could talk a little bit about that relationship. Where it's come from, how it's evolving and where you want to see it going. >> I think it's a, when you go back so long, right? The only way you are able to sustain that long relationship when then there is a value that we have been able to deliver to each other. And more importantly, the value that we have been able to deliver to our customers. And that has always been the mantra of the whole relationship and that continues to be going forward as well. So in that regard, I mean, while I would rather focus more on the future, it's three years, it's definitely good. But I think going forward, the kind of work that we are doing together to be able to serve some of our customers globally across the base, across the industries is extremely valuable both to us as well as to HPE, I'm sure. And that's where we are really looking to have providing real value to our customers. Not just from the technology perspective ultimately elevating that value. How do we help them solve the business problems and not just the technology solutions? >> Well, I think we've learned that. That's over the one, one big thing we learned from the Cloud is if you just shove all your stuff in the Cloud lifted and shifted, so what? It's that operating model that we talked about earlier, that really is how you drop, you know, if you're a large company you're talking about billions to the bottom line, not, you know, hundreds of thousands or millions, but that's a game changer. I'll give you a, your final word Manav. >> Absolutely. Absolutely. I mean, as I said I think, I hope I would not end up repeating my message but that solving the business problems, leveraging technology, and irrespective of the location where the technology is based be it on Edge or on the Cloud. It's the whole model of addressing the customer demands and the customer's need is extremely, extremely important. So that's what the whole mantra is. And that's what is really driving us forward together in this journey. >> Major shifts in industry, digital is the driver. And Manav thanks so much for being on theCUBE, really appreciate your time. >> Sure, thank you. Thank you for having me. >> And thanks for being with us for HPE Discover 2021, the virtual version. You're watching theCUBE, the Leader in Digital Tech Coverage. Keep it right there. (upbeat music)

>>Welcome back to HP discover 2021 the virtual version. My name is Dave Volonte and you're watching the cube. We're here with Manav said Donna, who is the global head of sales and market development for cognitive business operations at Tata consultancy services Tcs. And we're gonna dig in to digital transformation and take a deeper dive into the customer journeys. Welcome Manav, >>thank you. Dave, thank you for inviting me to this. Uh appreciate and looking forward to have an intriguing dialogue. You Me too. >>Me too. I mean we talk about digital transformation all the time prior to the pandemic. You know, a lot of it was kind of buzz wordy um and there's a lot of complacency around it. But as we know if you weren't digital during the pandemic you're out of business. But people were forced into it. They were rushed into I called the force marched to digital so you really didn't have time to be planned full. And now people are stepping back and saying, okay now we have an opportunity to get digital right and put that in air quotes. How do you think about digital transformation? What do you mean by that? >>Okay. See I think uh the way we look at it at this, yes, I will, I will probably take a step back where in um while the digital transformation has been in play, not just over the last year since the pandemic began, but um even before then uh where the shift in the customer organization that we have been seeing is largely from being product centric to be purpose centric wearing the whole focus of the entire existence is to be able to serve the purpose for their consumers, their customers and so on and so forth. And and if you look at it, for example, total energies right? The looking to sell or produce fuel, they are looking to be responsible energy company producing, reliable, affordable and clean energy for the consumers. Right? Similarly, there are other examples damaged shipyards who are looking to be more of a maritime solutions provider rather than just a shipbuilding company. Uh, so, so what's really happening when the purpose is being the driving force behind any organizations agenda or even reason of existence? That purpose is actually the driving force also followed the digital transformation. That is basically shifting the pace of the way businesses are looking to drive consumer experiences time to market and so on, so forth. Right? And if you see our we launched our new brand positioning in the last quarter, that's building on belief and and that's basically centered around this whole purpose driven mindset. Uh, what that means is that we believe that and the technology is enabling digital transformation are going to be the pillar of the whole shift of the re imagination of the business models where in businesses are coming together across industries and driven by the key goal of serving the customer in terms of driving the enhanced experience rather than just selling a product. So that's basically is really happening. And having said that now in the last year or so, what pandemic has done is basically accelerated the pace by a condom leap. Right? So, so in that sense, some of the organizations that were not ready at that point, they are also kind of transformation and and and taking that leap frog, I would say so from that perspective and going by again by our brand positioning statement, building on belief, right? That's really helping towards that pretty good thing, the overall journey, three horizon business and I'll come to that in a minute, but I hope it is answering your question of what digital transformation and how pandemic has really helped it. >>I just want to get 1 um point of clarification you said and you cut out there for a second, you said go from product centric too, >>but to centric >>platform centric, got it, >>but centric >>purpose centric uh building on belief, got it. Okay, so something else you said they picked up on, you talked about um actually you know crossing industries and this is something that's new and that's enabled by digital. I want to get your thoughts on it. I mean if you look at industry structures historically, whether it's manufacturing or automotive or financial services or healthcare or media and entertainment, whatever it is, there was a value chain, there is a value chain that's built up in that business might be uh it might be R. And D. Sales and marketing, service, manufacturing, etcetera. And if you are in that industry, you largely stayed in that industry forever. And now you're seeing these, a lot of big company, a lot of big tech companies having a dual disruption agenda, not only horizontally to from a technical standpoint, but you're seeing amazon get into grocery, you know, they're they're buying studios, you're seeing your Apple get into finance, and so the enabler is data and digital and that talks to the business model re imagination that you're talking about. >>Absolutely and absolutely exactly what is happening, that's what I'm really talking about. And we are firmly believing that boundaries or those boundaries are going to be blood even more so going forward as I took a few examples and you also talked about Apple, or or even amazon all the for example. Right, so all these technology companies are just being disrupted. So, having, having said that, that data being the new fuel at the same time, cloud being the new er now cloud as a technology that is enabling the business model re imagination is not just on the outside, but also on the edge side. And and that's where the boundaries are becoming so closer between edge and the cloud. And how how do we give that flexibility for to the customers to be able to adopt those digital technologies across the enterprise? Right. That's what, that's what the ship that we have been seeing. >>How do you see ecosystems playing in this? I mean it's kind of, I know it's an overused term but it seems to me to be increasingly important, its power of many versus the resources of one or a few. How do you see ecosystems driving? You know, this, this purpose driven business you talk about? >>Um very, very closely I would say, and I'll give you examples also in that sense. Right faster. Um if I talk about the journey I mentioned briefly earlier about three horizon based journey, right? The first and foremost being the setting up the digital foundation that basically could be through the combination of cloud, iOT analytics, artificial intelligence and so on, so forth. Right? And then eventually moving on to re imagination of business models and then leveraging the purpose let ecosystem Now in the Horizon one when we are setting up the digital foundation that is where the whole ecosystem comes into play. Where and where and if I talk about our co innovation network partners like HP, where we are working together to to really bring in that flexibility for the customers even in on premise environment, giving them that kind of uh features that they can experience also in the cloud to be really able to leverage the whole our beat at the edge or at the clouds. So that's where the kind of ecosystem coming together and and and those are also some of the challenges that we have seen that customers are facing today to be able to achieve the first horizon in that journey. The challenges like accelerated or or the time to market challenges. Like are they able to achieve the flexibility to be able to offer to the business and and challenges? Like are they able to achieve transformation at scale or is it just appointed um pointed poc sort of thing? Right. So bringing the ecosystem together is able to help customers address those challenges, be it in terms of consumption driven, addressing the flexibility needs be it in terms of the pre integrated solutions addressing the challenges related to time to market and so and so forth. >>Can we stay on the challenges for a minute? As I said, pre pandemic. There was a lot of complacency. We've all seen that meme of the wrecking ball coming in and kind of a tongue in cheek joke, but but the complacency is gone, so so there's there also, but still organizational challenges. It's not complacency anymore, but what's the right regime, what's the right approach? Uh everybody wants to get digital right, but a lot of people, you know, that's a do you see that as a challenge? Actually not knowing where to prioritize it and you know, how can you help in that regard? >>Yeah, So, and I would also like to like to talk about what we have done in in certain with certain customer with challenges. Um, some of the things I'll introduce TCS Cognex here, this is our platform which basically brings together the capabilities in a pre integrated uh, for of predefined solutions accelerators of our value builders as we call it, um, for customers to be able to just integrate their environments to be able to manage the whole infrastructure or of the landscape in a completely automated and analytics driven manner. Right, so that's that's one way of addressing those challenges. What it also does is it gives that um power to the stakeholders in the organization to be able to address that key challenge of time to market because it is giving out or coming out in a pre integrated manner and be able to achieve that benefits or realize the benefits of transformation In in an accelerated time frame instead of waiting for 18-24 months, how can it be done in 3-6 months, for example. Right, that's that's that's one set and and similarly, uh if I talk about the flexibility, right, consumption driven manner is extremely, extremely important. And if I talk about hybrid cloud, so to say right today, about 1 to 2% of the on premise infrastructure is actually in a consumption driven manner while cloud is always gonna consumption driven manner, The trends that we're seeing is that by next year about minimum 15% of the on premise infrastructure in a hybrid cloud environment will be about or will be delivering a consumption-driven manner and that's what is going to address the various the opportunity as well as the challenge to address that particular aspect of flexibility and that's where the ecosystem with the likes of us pcs and HP coming together to provide solutions that are addressing those needs of our consumers. >>And when you talk about the consumption driven, obviously talking about things like HP Green Lake, that's a model that enables that kind of consumption model. You know, I feel like, I mean, I feel like that's kind of table stakes to be honest with, you, pointed out 1 to 2% of it. I said wow, clouds been around for a long time and now, but now we're seeing the rapid adoption 15% and we're also seeing, I mean I think I'll give H PE some props on this because they got their whole company behind it, but there has to be a complimentary shift in the mindset of OK, we're not now selling boxes anymore and I think HP has done a pretty good job of this. They've made some announcements recently to that effect. They're doing an HPC. We just saw some storage announcements so it's no longer, hey, here's a box to sell it and this is where a company like Tcs comes to play. You, you've, you've never had that box mentality, you have a solutions mentality and so, so the industry is moving in a very rapid pace now. My question is, are the customers ready for it? Are they ready for it? Because they have the cloud experience, are they ready for it on prem and what do they need to do to get ready for that? >>See um, to answer your first question already and what really is the trigger point for them being ready? The answer is yes. Okay. Um, I would say a large percentage of the customer base was ready even before pandemic, but pandemic has really made it even more prominent in the customer and that has become a need, We are seeing so many customers today, I mean, uh, in my global role, I'm seeing across industries and across markets right from north America to Australia japan. We're in, we're in the need for having consumption. Everyone is even at on premise while cloud is definitely there, but even at on premise is so much so that really is the trigger um, at the same time now what is really driving that trigger apart from pandemic is to be able to offer that flexibility to their business. Businesses are basically reimagining, reimagining their whole uh where they are reaching out to their customers where they are expanding into the nuclear markets and the speed is extremely, extremely important. And that's what is really putting the whole, let's >>peel the onion on that. Somebody asked me this the other day why why as reserves? I said the same thing, flexibility and they're like, yeah, okay, but give me some examples. And so I said, well, first of all, they're paying by the drink. So it's a much fairer for the customer model instead of okay, charge them for what they're not even gonna use or what they might use for a day or two or a month. The other is experimentation. It just seems to me that in the digital world you got to fail fast, you don't know, you don't know what, you don't know. And so these consumption models allow you to spin up experiments very quickly and cheaply and only pay for what you use is. Am I am I getting that right? >>Absolutely, Absolutely. And and and that that's exactly what the model is, that we as well as the partner together, that we are offering. Only one thing that I would want to highlight here is um while that's the foundation, as I said, it is setting up the digital foundation, giving the customers the flexibility. And if I talk about example, uh one of our british large, uh I am who really is leveraging this technology for them to be able to bring more resilience and boring the lettering and scales, departments uh to be able to, you know, on the manufacturing line and ultimately driving to the sales value chain. So those are the things that are happening. And you took an example of basically talked about consuming purely as a service. What you use. This model is basically expanding everywhere very recently. I mean I saw an out of bicycle as a service. I mean instead of buying a new bicycle, I'm just able to get one bicycle, you use it or for a month, return it back to the to the owner to be able to use it only when I need it, let's say for example, so that's what is really happening even in the digital transformation, I just need it for a time basis for a particular purpose. I served that purpose, ultimately driving the business resilience, agility and then ultimately serving that purpose. Yeah, >>I think I'd love your, your thoughts on this. I think the real opportunity here is to for for technology companies like HP, working with TCS to create a layer I called a layer that spans on prem name your favorite cloud or multiple clouds goes across clouds goes out to the edge, that's the layer that that hides all the underlying complexity. You're going to take care of that for me uh because it's complicated. No question about it, the bigger the universe gets, the more complicated gets. But as as a customer, I want to hide that complexity because I don't want people doing plumbing, I want people focus on on strategic initiatives and that's, to me, seems to be the killer app if you will of infrastructure in the future. Is that that abstraction layer? Do you see it that way? >>Absolutely. And that's where the easiest Cognex comes into play very strongly. Right? As I said earlier, it's basically it said actually uh an air driven human machine collaboration suite. So what that really means, it is bringing together the capabilities from analytics to ai with our machine first principles and and really giving that obstructing layer in a pre integrated manner from edged right up to the cloud and bringing it all together for the customers. So that that's exactly what how we are really helping the customers, um a team that again, addressing those challenges of exploration, time to market flexibility and more importantly unifying the entire landscape into one single view. If I am a C I O, or if I am a CFO, I want to see what is important to me, rather than going to multiple different dashboard support so to save. Right? So that's where pieces Cognex plays an important role in obstructing everything and presenting that unified do and in a transformed service delivery model for the customers. >>So the history of TCS is pretty amazing. You guys have, I mean, the, the ascendancy of the company over the decades is actually so, so impressive. Now in your relationship with HP and now, of course, HP goes back, I think it goes back to the 90s, maybe you could talk a little bit about that relationship, where it's come from, how it's evolving and where you want to see it going. >>So I think it's uh, when you go back so long, right? Uh the only way you're able to sustain that long relationship when there is a value that we have been able to deliver to each other, and more importantly, the value that we have been able to deliver to our customers, right? And that has always been the, the mantra of the whole relationship and that continues to be going forward as well. So, so in that regard, I mean, while I would rather focus more on the future, history is definitely good, but I think going forward, um the kind of work that we're doing together to be able to solve some of our customers globally across the base across the industries is extremely valuable, both to us as well as two HP, I'm sure, and that's where we are really looking to have uh, providing real value to our customers, not just from the technology perspective, ultimately elevating that value. How do we help them solve the business problems and not just the technology solutions? >>Well, I think we've learned that that's the 11 big thing we learned from the cloud is if you just shove all your stuff in the cloud lifted and shifted it. So, what, um, it's that operating model that you talked about earlier, that really is how you, you you drop, you know, if you're a large company, you're talking about billions to the bottom line, not hundreds of thousands or millions, but that's that's a game changer. I'll give you a final word enough. >>Absolutely, Absolutely. I mean, as they said, I think, um, I hope I will not end up repeating my mistake, but, but that, um, solving the business problems, leveraging technology and, and irrespective of the location where the technology is based being on edge or on the cloud. It's the whole model of addressing the customer demands and the customers need is extremely, extremely important. So that's that's what the whole mantra is and that's what is really driving us forward together in the journey. >>Major shifts in industry digital is is the driver and and Manav thanks so much for being on the cube. Really appreciate your time. >>Sure, thank you. Thank you for having me >>And thanks for being with us for HP Discover 2021 the virtual version. You're watching the Cube, the leader in digital tech coverage. Keep it right there. >>Mhm.

>> From theCUBE studios in Palo Alto and Boston, Bringing you data-driven insights from theCUBE and ETR. This is "Breaking Analysis" with Dave Vellante. >> Recent survey data from ETR shows that enterprise tech spending is tracking with projected US GDP growth at six to 7% this year. Many markers continue to point the way to a strong recovery, including hiring trends and the loosening of frozen IT Project budgets. However skills shortages are blocking progress at some companies which bodes well for an increased reliance on external IT services. Moreover, while there's much talk about the rotation out of work from home plays and stocks such as video conferencing, VDI, and other remote worker tech, we see organizations still trying to figure out the ideal balance between funding headquarter investments that have been neglected and getting hybrid work right. In particular, the talent gap combined with a digital mandate, means companies face some tough decisions as to how to fund the future while serving existing customers and transforming culturally. Hello everyone, and welcome to this week's Wikibon CUBE's Insights powered by ETR. In this "Breaking Analysis", we welcome back Erik Porter Bradley of ETR who will share fresh data, perspectives and insights from the latest survey data. Erik, great to see you. Welcome. >> Thank you very much, Dave. Always good to see you and happy to be on the show again. >> Okay, we're going to share some macro data and then we're going to dig into some highlights from ETR's most recent March COVID survey and also the latest April data. So Erik, the first chart that we want to show, it shows CIO and IT buyer responses to expected IT spend for each quarter of 2021 versus 2020, and you can see here a steady quarterly improvement. Erik, what are the key takeaways, from your perspective? >> Sure, well, first of all, for everyone out there, this particular survey had a record-setting number of participation. We had a 1,500 IT decision makers participate and we had over half of the Fortune 500 and over a fifth of the Global 1000. So it was a really good survey. This is seventh iteration of the COVID Impact Survey specifically, and this is going to transition to an overlarge macro survey going forward so we can continue it. And you're 100% right, what we've been tracking here since March of last year was, how is spending being impacted because of COVID? Where is it shifting? And what we're seeing now finally is that there is a real re-acceleration in spend. I know we've been a little bit more cautious than some of the other peers out there that just early on slapped an eight or a 9% number, but what we're seeing is right now, it's at a midpoint of over six, about 6.7% and that is accelerating. So, we are still hopeful that that will continue, and really, that spending is going to be in the second half of the year. As you can see on the left part of this chart that we're looking at, it was about 1.7% versus 3% for Q1 spending year-over-year. So that is starting to accelerate through the back half. >> I think it's prudent to be cautious (indistinct) 'cause normally you'd say, okay, tech is going to grow a couple of points higher than GDP, but it's really so hard to predict this year. Okay, the next chart here that we want to show you is we asked respondents to indicate what strategies they're employing in the short term as a result of coronavirus and you can see a few things that I'll call out and then I'll ask Erik to chime in. First, there's been no meaningful change of course, no surprise in tactics like remote work and holding travel, however, we're seeing very positive trends in other areas trending downward, like hiring freezes and freezing IT deployments, a downward trend in layoffs, and we also see an increase in the acceleration of new IT deployments and in hiring. Erik, what are your key takeaways? >> Well, first of all, I think it's important to point out here that we're also capturing that people believe remote work productivity is still increasing. Now, the trajectory might be coming down a little bit, but that is really key, I think, to the backdrop of what's happening here. So people have a perception that productivity of remote work is better than hybrid work and that's from the IT decision makers themselves, but what we're seeing here is that, most importantly, these organizations are citing plans to increase hiring, and that's something that I think is really important to point out. It's showing a real following, and to your point right in the beginning of the intro, we are seeing deployments stabilize versus prior survey levels, which means early on, they had no plans to launch new tech deployments, then they said, "Nope, we're going to start." and now that stalling, and I think it's exactly right, what you said, is there's an IT skills shortage. So people want to continue to do IT deployments 'cause they have to support work from home and a hybrid back return to the office, but they just don't have the skills to do so, and I think that's really probably the most important takeaway from this chart, is that stalling and to really ask why it's stalling. >> Yeah, so we're going to get into that for sure, and I think that's a really key point, is that accelerating IT deployments, it looks like it's hit a wall in the survey, but before we get deep into the skills, let's take a look at this next chart, and we're asking people here how our return to the new normal, if you will, and back to offices is going to change spending with on-prem architectures and applications. And so the first two bars, they're Cloud-friendly, if you add them up, it's 63% of the respondents, say that either they'll stay in the Cloud for the most part, or they're going to lower their on-prem spend when they go back to the office. The next three bars are on-prem friendly. If you add those up it's 29% of the respondents say their on-prem spend is going to bounce back to pre-COVID levels or actually increase, and of course, 12% of that number, by the way, say they've never altered their on-prem spend. So Erik, no surprise, but this bodes well for Cloud, but isn't it also a positive for on-prem? We've had this dual funding premise, meaning Cloud continues to grow, but neglected data center spend also gets a boost. What's your thoughts? >> Really, it's interesting. It's people are spending on all fronts. You and I were talking in the prep, it's like we're in battle and I've got naval, I've got air, I've got land, I've got to spend on Cloud and digital transformation, but I also have to spend for on-prem. The hybrid work is here and it needs to be supported. So this is spending is going to increase. When you look at this chart, you're going to see though, that roughly 36% of all respondents say that their spending is going to remain mostly on Cloud. So that is still the clear direction, digital transformation is still happening, COVID accelerated it greatly, you and I, as journalists and researchers already know this is where the puck is going, but spend has always lagged a little bit behind 'cause it just takes some time to get there. Inversely, 27% said that their on-prem spending will decrease. So when you look at those two, I still think that the trend is the friend for Cloud spending, even though, yes, they do have to continue spending on hybrid, some of it's been neglected, there are refresh cycles coming up, so, overall it just points to more and more spending right now. It really does seem to be a very strong backdrop for IT growth. >> So I want to talk a little bit about the ETR taxonomy before we bring up the next chart. We get a lot of questions about this, and of course, when you do a massive survey like you're doing, you have to have consistency for time series, so you have to really think through what the buckets look like, if you will. So this next chart takes a look at the ETR taxonomy and it breaks it down into simple-to-understand terms. So the green is the portion of spending on a vendor's tech within a category that is accelerating, and the red is the portion that is decelerating. So Erik, what are the key messages in this data? >> Well, first of all, Dave, thank you so much for pointing that out. We used to do, just what we call a Net score. It's a proprietary formula that we use to determine the overall velocity of spending. Some people found it confusing. Our data scientists decided to break this sector, break down into what you said, which is really more of a mode analysis. In that sector, how many of the vendors are increasing versus decreasing? So again, I just appreciate you bringing that up and allowing us to explain the reasoning behind our analysis there. But what we're seeing here goes back to something you and I did last year when we did our predictions, and that was that IT services and consulting was going to have a true rebound in 2021, and that's what this is showing right here. So in this chart, you're going to see that consulting and services are really continuing their recovery, 2020 had a lot of the clients and they have the biggest sector year-over-year acceleration sector wise. The other thing to point out on this, which we'll get to again later, is that the inverse analysis is true for video conferencing. We will get to that, so I'm going to leave a little bit of ammunition behind for that one, but what we're seeing here is IT consulting services being the real favorable and video conferencing having a little bit more trouble. >> Great, okay, and then let's take a look at that services piece, and this next chart really is a drill down into that space and emphasizes, Erik, what you were just talking about. And we saw this in IBM's earnings, where still more than 60% of IBM's business comes from services and the company beat earnings, in part, due to services outperforming expectations, I think it had a somewhat easier compare and some of this pent-up demand that we've been talking about bodes well for IBM and other services companies, it's not just IBM, right, Erik? >> No, it's not, but again, I'm going to point out that you and I did point out IBM in our predictions when we did in late December, so, it is nice to see. One of the reasons we don't have a more favorable rating on IBM at the moment is because they are in the process of spinning out this large unit, and so there's a little bit of a corporate action there that keeps us off on the sideline. But I would also want to point out here, Tata, Infosys and Cognizant 'cause they're seeing year-over-year acceleration in both IT consulting and outsourced IT services. So we break those down separately and those are the three names that are seeing acceleration in both of those. So again, at the Tata, Infosys and Cognizant are all looking pretty well positioned as well. >> So we've been talking a little bit about this skills shortage, and this is what's, I think, so hard for forecasters, is that in the one hand, There's a lot of pent up demand, Scott Gottlieb said it's like Woodstock coming out of the COVID, but on the other hand, if you have a talent gap, you've got to rely on external services. So there's a learning curve, there's a ramp up, it's an external company, and so it takes time to put those together. So this data that we're going to show you next, is really important in my view and ties what we were saying at the top. It asks respondents to comment on their staffing plans. The light blue is "We're increasing staff", the gray is "No change" and the magenta or whatever, whatever color that is that sort of purplish color, anyway, that color is decreasing, and the picture is very positive across the board. Full-time staff, offshoring, contract employees, outsourced professional services, all up trending upwards, and this Erik is more evidence of the services bounce back. >> Yeah, it's certainly, yes, David, and what happened is when we caught this trend, we decided to go one level deeper and say, all right, we're seeing this, but we need to know why, and that's what we always try to do here. Data will tell you what's happening, it doesn't always tell you why, and that's one of the things that ETR really tries to dig in with through the insights, interviews panels, and also going direct with these more custom survey questions. So in this instance, I think the real takeaway is that 30% of the respondents said that their outsourced and managed services are going to increase over the next three months. That's really powerful, that's a large portion of organizations in a very short time period. So we're capturing that this acceleration is happening right now and it will be happening in real time, and I don't see it slowing down. You and I are speaking about we have to increase Cloud spend, we have to increase hybrid spend, there are refresh cycles coming up, and there's just a real skills shortage. So this is a long-term setup that bodes very well for IT services and consulting. >> You know, Erik, when I came out of college, somebody told me, "Read, read, read, read as much as you can." And then they said, "Read the Wall Street Journal every day." and so I did it, and I would read the tech magazines and back then it was all paper, and what happens is you begin to connect the dots. And so the reason I bring that up is because I've now taken a bath in the ETR data for the better part of two years and I'm beginning to be able to connect the dots. The data is not always predictive, but many, many times it is. And so this next data gets into the fun stuff where we name names. A lot of times people don't like it because they're either marketing people at organizations, say, "Well, data's wrong." because that's the first thing they do, is attack the data. But you and I know, we've made some really great calls, work from home, for sure, you're talking about the services bounce back. We certainly saw the rise of CrowdStrike, Okta, Zscaler, well before people were talking about that, same thing with video conferencing. And so, anyway, this is the fun stuff and it looks at positive versus negative sentiment on companies. So first, how does ETR derive this data and how should we interpret it, and what are some of your takeaways? >> Sure, first of all, how we derive the data, are systematic survey responses that we do on a quarterly basis, and we standardize those responses to allow for time series analysis so we can do trend analysis as well. We do find that our data, because it's talking about forward-looking spending intentions, is really more predictive because we're talking about things that might be happening six months, three months in the future, not things that a lot of other competitors and research peers are looking at things that already happened, they're looking in the past, ETR really likes to look into the future and our surveys are set up to do so. So thank you for that question, It's a enjoyable lead in, but to get to the fun stuff, like you said, what we do here is we put ratings on the datasets. I do want to put the caveat out there that our spending intentions really only captures top-line revenue. It is not indicative of profit margin or any other line items, so this is only to be viewed as what we are rating the data set itself, not the company, that's not what we're in the game of doing. So I think that's very important for the marketing and the vendors out there themselves when they take a look at this. We're just talking about what we can control, which is our data. We're going to talk about a few of the names here on this highlighted vendors list. One, we're going to go back to that you and I spoke about, I guess, about six months ago, or maybe even earlier, which was the observability space. You and I were noticing that it was getting very crowded, a lot of new entrants, there was a lot of acquisition from more of the legacy or standard players in the space, and that is continuing. So I think in a minute, we're going to move into that observability space, but what we're seeing there is that it's becoming incredibly crowded and we're possibly seeing signs of them cannibalizing each other. We're also going to move on a little bit into video conferencing, where we're capturing some spend deceleration, and then ultimately, we're going to get into a little bit of a storage refresh cycle and talk about that. But yeah, these are the highlighted vendors for April, we usually do this once a quarter and they do change based on the data, but they're not usually whipsawed around, the data doesn't move that quickly. >> Yeah, so you can see some of the big names in the left-hand side, some of the SAS companies that have momentum. Obviously, ServiceNow has been doing very, very well. We've talked a lot about Snowflake, Okta, CrowdStrike, Zscaler, all very positive, as well as several others. I guess I'd add some things. I mean, I think if thinking about the next decade, it's Cloud, which is not going to be like the same Cloud as the last decade, a lot of machine learning and deep learning and AI and the Cloud is extending to the edge and the data center. Data, obviously, very important, data is decentralized and distributed, so data architectures are changing. A lot of opportunities to connect across Clouds and actually create abstraction layers, and then something that we've been covering a lot is processor performance is actually accelerating relative to Moore's law. It's probably instead of doubling every two years, it's quadrupling every two years, and so that is a huge factor, especially as it relates to powering AI and AI inferencing at the edge. This is a whole new territory, custom Silicon is really becoming in vogue and so something that we're watching very, very closely. >> Yeah, I completely, agree on that and I do think that the next version of Cloud will be very different. Another thing to point out on that too, is you can't do anything that you're talking about without collecting the data and organizations are extremely serious about that now. It seems it doesn't matter what industry they're in, every company is a data company, and that also bodes well for the storage goal. We do believe that there is going to just be a huge increase in the need for storage, and yes, hopefully that'll become portable across multi-Cloud and hybrid as well. >> Now, as Erik said, the ETR data, it's really focused on that top-line spend. So if you look on the right side of that chart, you saw NetApp was kind of negative, was very negative, right? But it is a company that's in transformation now, they've lowered expectations and they've recently beat expectations, that's why the stock has been doing better, but at the macro, from a spending standpoint, it's still stout challenged. So you have big footprint companies like NetApp and Oracle is another one. Oracle's stock is at an all time high, but the spending relative to sort of previous cycles are relative to, like for instance, Snowflake, much, much smaller, not as high growth, but they're managing expectations, they're managing their transition, they're managing profitability. Zoom is another one, Zoom looking negative, but Zoom's got to use its market cap now to transform and increase its TAM. And then Splunk is another one we're going to talk about. Splunk is in transition, it acquired SignalFX, It just brought on this week, Teresa Carlson, who was the head of AWS Public Sector. She's the president and head of sales, so they've got a go-to-market challenge and they brought in Teresa Carlson to really solve that, but Splunk has been trending downward, we called that several quarters ago, Erik, and so I want to bring up the data on Splunk, and this is Splunk, Erik, in analytics, and it's not trending in the right direction. The green is accelerating spend, the red is in the bars is decelerating spend, the top blue line is spending velocity or Net score, and the yellow line is market share or pervasiveness in the dataset. Your thoughts. >> Yeah, first I want to go back. There's a great point, Dave, about our data versus a disconnect from an equity analysis perspective. I used to be an equity analyst, that is not what we do here. And the main word you said is expectations, right? Stocks will trade on how they do compare to the expectations that are set, whether that's buy-side expectations, sell-side expectations or management's guidance themselves. We have no business in tracking any of that, what we are talking about is the top-line acceleration or deceleration. So, that was a great point to make, and I do think it's an important one for all of our listeners out there. Now, to move to Splunk, yes, I've been capturing a lot of negative commentary on Splunk even before the data turns. So this has been a about a year-long, our analysis and review on this name and I'm dating myself here, but I know you and I are both rock and roll fans, so I'm going to point out a Led Zeppelin song and movie, and say that the song remains the same for Splunk. We are just seeing recent spending attentions are taking yet another step down, both from prior survey levels, from year ago levels. This, we're looking at in the analytics sector and spending intentions are decelerating across every single group, and we went to one of our other slide analysis on the ETR+ platform, and you do by customer sub-sample, in analytics, it's dropping in every single vertical. It doesn't matter which one. it's really not looking good, unfortunately, and you had mentioned this is an analytics and I do believe the next slide is an information security. >> Yeah, let's bring that up. >> And unfortunately it's not doing much better. So this is specifically Fortune 500 accounts and information security. There's deep pockets in the Fortune 500, but from what we're hearing in all the insights and interviews and panels that I personally moderate for ETR, people are upset, that they didn't like the strong tactics that Splunk has used on them in the past, they didn't like the ingestion model pricing, the inflexibility, and when alternatives came along, people are willing to look at the alternatives, and that's what we're seeing in both analytics and big data and also for their SIM and security. >> Yeah, so I think again, I pointed Teresa Carlson. She's got a big job, but she's very capable. She's going to meet with a lot of customers, she's a go-to-market pro, she's going to to have to listen hard, and I think you're going to see some changes there. Okay, so sorry, there's more bad news on Splunk. So (indistinct) bring this up is Net score for Splunk and Elastic accounts. This is for analytics, so there's 106 Elastic accounts in the dataset that also have Splunk and it's trending downward for Splunk, that's why it's green for Elastic. And Erik, the important call out from ETR here is how Splunk's performance in Elastic accounts compares with its performance overall. The ELK stack, which obviously Elastic is a big part of that, is causing pain for Splunk, as is Datadog, and you mentioned the pricing issue, well, is it pricing in your assessment or is it more fundamental? >> It's multi-level based on the commentary we get from our ITDMs teams that take the survey. So yes, you did a great job with this analysis. What we're looking at is the spending within shared accounts. So if I have Splunk already, how am I spending? I'm sorry if I have Elastic already, how am I spending on Splunk? And what you're seeing here is it's down to about a 12% Net score, whereas Splunk overall, has a 32% Net score among all of its customers. So what you're seeing there is there is definitely a drain that's happening where Elastic is draining spend from Splunk and usage from them. The reason we used Elastic here is because all observabilities, the whole sector seems to be decelerating. Splunk is decelerating the most, but Elastic is the only one that's actually showing resiliency, so that's why we decided to choose these two, but you pointed out, yes, it's also Datadog. Datadog is Cloud native. They're more dev ops-oriented. They tend to be viewed as having technological lead as compared to Splunk. So a really good point. Dynatrace also is expanding their abilities and Splunk has been making a lot of acquisitions to push their Cloud services, they are also changing their pricing model, right? They're trying to make things a little bit more flexible, moving off ingestion and moving towards consumption. So they are trying, and the new hires, I'm not going to bet against them because the one thing that Splunk has going for them is their market share in our survey, they're still very well entrenched. So they do have a lot of accounts, they have their foothold. So if they can find a way to make these changes, then they will be able to change themselves, but the one thing I got to say across the whole sector is competition is increasing, and it does appear based on commentary and data that they're starting to cannibalize themselves. It really seems pretty hard to get away from that, and you know there are startups in the observability space too that are going to be even more disruptive. >> I think I want to key on the pricing for a moment, and I've been pretty vocal about this. I think the old SAS pricing model where you essentially lock in for a year or two years or three years, pay up front, or maybe pay quarterly if you're lucky, that's a one-way street and I think it's a flawed model. I like what Snowflake's doing, I like what Datadog's doing, look at what Stripe is doing, look at what Twilio is doing, you mentioned it, it's consumption-based pricing, and if you've got a great product, put it out there and damn, the torpedoes, and I think that is a game changer. I look at, for instance, HPE with GreenLake, I look at Dell with Apex, they're trying to mimic that model and apply it to infrastructure, it's much harder with infrastructure 'cause you've got to deploy physical infrastructure, but that is a model that I think is going to change, and I think all of the traditional SAS pricing is going to come under disruption over the next better part of the decades, but anyway, let's move on. We've been covering the APM space pretty extensively, application performance management, and this chart lines up some of the big players here. Comparing Net score or spending momentum from the April 20th survey, the gray is, sorry, the gray is the April 20th survey, the blue is Jan 21 and the yellow is April 21, and not only are Elastic and Datadog doing well relative to Splunk, Erik, but everything is down from last year. So this space, as you point out, is undergoing a transformation. >> Yeah, the pressures are real and it's sort of that perfect storm where it's not only the data that's telling us that, but also the direct feedback we get from the community. Pretty much all the interviews I do, I've done a few panels specifically on this topic, for anyone who wants to dive a little bit deeper. We've had some experts talk about this space and there really is no denying that there is a deceleration in spend and it's happening because that spend is getting spread out among different vendors. People are using a Datadog for certain aspects, they are using Elastic where they can 'cause it's cheaper. They're using Splunk because they have to, but because it's so expensive, they're cutting some of the things that they're putting into Splunk, which is dangerous, particularly on the security side. If I have to decide what to put in and whatnot, that's not really the right way to have security hygiene. So this space is just getting crowded, there's disruptive vendors coming from the emerging space as well, and what you're seeing here is the only bit of positivity is Elastic on a survey-over-survey basis with a slight, slight uptick. Everywhere else, year-over-year and survey-over-survey, it's showing declines, it's just hard to ignore. >> And then you've got Dynatrace who, based on the interviews you do in the (indistinct), one-on-one, or one-on-five, the private interviews that I've been invited to, Dynatrace gets very high scores for their roadmap. You've got New Relic, which has been struggling financially, but they've got a really good product and a purpose-built database just for this APM space, and then of course, you've got Cisco with AppD, which is a strong business for them, and then as you mentioned, you've got startups coming in, you got ChaosSearch, which Ed Walsh is now running, leave the data in place in AWS and really interesting model, Honeycomb is getting really disruptive, Jeremy Burton's company, Observed. So this space is it's becoming jumped ball. >> Yeah, there's a great line that came out of one of them, and that was that the lines are blurring. It used to be that you knew exactly that AppDynamics, what they were doing, it was APM only, or it was logging and monitoring only, and a lot of what I'm hearing from the ITDM experts is that the lines are blurring amongst all of these names. They all have functionality that kind of crosses over each other. And the other interesting thing is it used to be application versus infrastructure monitoring, but as you know, infrastructure is becoming code more and more and more, and as infrastructure becomes code, there's really no difference between application and infrastructure monitoring. So we're seeing a convergence and a blurring of the lines in this space, which really doesn't bode well, and a great point about New Relic, their tech gets good remarks. I just don't know if their enterprise level service and sales is up to snuff right now. As one of my experts said, a CTO of a very large public online hospitality company essentially said that he would be shocked that within 18 months if all of these players are still standalone, that there needs to be some M and A or convergence in this space. >> Okay, now we're going to call out some of the data that really has jumped out to ETR in the latest survey, and some of the names that are getting the most queries from ETR clients, many of which are investor clients. So let's start by having a look at one of the most important and prominent work from home names, Zoom. Let's look at this. Erik is the ride over for Zoom? >> Ah, I've been saying it for a little bit of a time now actually. I do believe it is, and we'll get into it, but again, pointing out, great, Dave, the reason we're presenting today Splunk, Elastic and Zoom, they are the most viewed on the ETR+ platform. Trailing behind that only slightly is F5, I decided not to bring F5 to the table today 'cause we don't have a rating on the data set. So then I went one deep, one below that and it's pure. So the reason we're presenting these to you today is that these are the ones that our clients and our community are most interested in, which is hopefully going to gain interest to your viewers as well. So to get to Zoom, yeah, I call Zoom the pandemic bull market baby. This was really just one that had a meteoric ride. You look back, January in 2020, the stock was at $60 and 10 months later, it was like 580, that's in 10 months. That's cooled down a little bit into the mid-300s, and I believe that cooling down should continue, and the reason why is because we are seeing huge deceleration in our spending intentions. They're hitting all-time lows, it's really just a very ugly dataset. More importantly than the spending intentions, for the first time, we're seeing customer growth in our survey flatten. In the past, we knew that the deceleration of spend was happening, but meanwhile, their new customer growth was accelerating, so it was kind of hard to really make any call based on that. This is the first time we're seeing flattening customer growth trajectory, and that in tandem with just dominance from Microsoft in every sector they're involved in, I don't care if it's IP telephony, productivity apps or the core video conferencing, Microsoft is just dominating. So there's really just no way to ignore this anymore. The data and the commentary state that Zoom is facing some headwinds. >> Well, plus you've pointed out to me that a lot of your private conversations with buyers says that, "Hey, we're, we're using the freebie version of Zoom, and we're not paying them." And that combined with Teams, I mean, it's... I think, look, Zoom, they've got to figure out how to use their elevated market cap to transform and expand their TAM, but let's move on. Here's the data on Pure Storage and we've highlighted a number of times this company is showing elevated spending intentions. Pure announced it's earnings in May, IBM just announced storage, it was way down actually. So still, Pure, more positive, but I'll on that comment in a moment, but what does this data tell you, Erik? >> Yeah, right now we started seeing this data last survey in January, and that was the first time we really went positive on the data set itself, and it's just really continuing. So we're seeing the strongest year-over-year acceleration in the entire survey, which is a really good spot to be. Pure is also a leading position among its sector peers, and the other thing that was pretty interesting from the data set is among all storage players, Pure has the highest positive public Cloud correlation. So what we can do is we can see which respondents are accelerating their public Cloud spend and then cross-reference that with their storage spend and Pure is best positioned. So as you and I both know, digital transformation Cloud spending is increasing, you need to be aligned with that. And among all storage sector peers, Pure is best positioned in all of those, in spending intentions and adoptions and also public Cloud correlation. So yet again, to start another really strong dataset, and I have an anecdote about why this might be happening, because when I saw the data, I started asking in my interviews, what's going on here? And there was one particular person, he was a director of Cloud operations for a very large public tech company. Now, they have hybrid, but their data center is in colo, So they don't own and build their own physical building. He pointed out that during COVID, his company wanted to increase storage, but he couldn't get into his colo center due to COVID restrictions. They weren't allowed. You had 250,000 square feet, right, but you're only allowed to have six people in there. So it's pretty hard to get to your rack and get work done. He said he would buy storage, but then the colo would say, "Hey, you got to get it out of here. It's not even allowed to sit here. We don't want it in our facility." So he has all this pent up demand. In tandem with pent up demand, we have a refresh cycle. The SSD depreciation cycle is ending. SSDs are moving on and we're starting to see a new technology in that space, NVMe sorry, technology increasing in that space. So we have pent up demand and we have new technology and that's really leading to a refresh cycle, and this particular ITDM that I spoke to and many of his peers think this has a long tailwind that storage could be a good sector for some time to come. >> That's really interesting, thank you for that extra metadata. And I want to do a little deeper dive on storage. So here's a look at storage in the industry in context and some of the competitive. I mean, it's been a tough market for the reasons that we've highlighted, Cloud has been eating away that flash headroom. It used to be you'd buy storage to get more spindles and more performance and we're sort of forced to buy more, flash, gave more headroom, but it's interesting what you're saying about the depreciation cycle. So that's good news. So ETR combines, just for people's benefit here, combines primary and secondary storage into a single category. So you have companies like Pure and NetApp, which are really pure play primary storage companies, largely in the sector, along with Veeam, Cohesity and Rubrik, which are kind of secondary data or data protection. So my quick thoughts here that Pure is elevated and remains what I call the one-eyed man in the land of the blind, but that's positive tailwinds there, so that's good news. Rubrik is very elevated but down, it's big competitor, Cohesity is way off its highs, and I have to say to me, Veeam is like the Steady Eddy consistent player here. They just really continue to do well in the data protection business, and the highs are steady, the lows are steady. Dell is also notable, they've been struggling in storage. Their ISG business, which comprises servers and storage, it's been softer in COVID, and during even this new product rollout, so it's notable with this new mid range they have in particular, the uptick in Dell, this survey, because Dell is so large, a small uptick can be very good for Dell. HPE has a big announcement next month in storage, so that might improve based on a product cycle. Of course, the Nimble brand continues to do well, IBM, as I said, just announced a very soft quarter, down double digits again, and they're in a product cycle shift. And NetApp, it looks bad in the ETR data from a spending momentum standpoint, but their management team is transforming the company into a Cloud play, which Erik is why it was interesting that Pure has the greatest momentum in Cloud accounts, so that is sort of striking to me. I would have thought it would be NetApp, so that's something that we want to pay attention to, but I do like a lot of what NetApp is doing, and other than Pure, they're the only big kind of pure play in primary storage. So long-winded, intro there, Erik, but anything you'd add? >> No, actually I appreciate it as long-winded. I'm going to be honest with you, storage is not my best sector as far as a researcher and analyst goes, but I actually think that a lot of what you said is spot on. We do capture a lot of large organizations spend, we don't capture much mid and small, so I think when you're talking about these large, large players like NetApp not looking so good, all I would state is that we are capturing really big organization spending attention, so these are names that should be doing better to be quite honest, in those accounts, and at least according to our data, we're not seeing it in. It's longterm depression, as you can see, NetApp now has a negative spending velocity in this analysis. So, I can go dig around a little bit more, but right now the names that I'm hearing are Pure, Cohesity. I'm hearing a little bit about Hitachi trying to reinvent themselves in the space, but I'll take a wait-and-see approach on that one, but pure Cohesity are the ones I'm hearing a lot from our community. >> So storage is transforming to Cloud as a service. You've seen things like Apex in GreenLake from Dell and HPE and container storage. A little, so not really a lot of people paying attention to it, but Pure bought a company called Portworx which really specializes in container storage, and there's many startups there, they're trying to really change the way. David Flynn, has a startup in that space, he's the guy who started Fusion-io. So a lot of transformations happening here. Okay, I know it's been a long segment, we have to summarize, and let me go through a summary and then I'll give you the last word, Erik. So tech spending appears to be tracking US GDP at 6 to 7%. This talent shortage could be a blocker to accelerating IT deployments, so that's kind of good news actually for services companies. Digital transformation, it remains a priority, and that bodes, well, not only for services, but automation. UiPath went public this week, we profiled that extensively, that went public last Wednesday. Organizations that sit at the top face some tough decisions on how to allocate resources. They're running the business, growing the business, transforming the business, and we're seeing a bifurcation of spending and some residual effects on vendors, and that remains a theme that we're watching. Erik, your final thoughts. >> Yeah, I'm going to go back quickly to just the overall macro spending, 'cause there's one thing I think is interesting to point out and we're seeing a real acceleration among mid and small. So it seems like early on in the COVID recovery or COVID spending, it was the deep pockets that moved first, right? Fortune 500 knew they had to support remote work, they started spending first. Around that in the Fortune 500, we're only seeing about 5% spend, but when you get into mid and small organizations, that's creeping up to eight, nine. So I just think it's important to point out that they're playing catch up right now. I also would point out that this is heavily skewed to North America spending. We're seeing laggards in EMEA, they just don't seem to be spending as much. They're in a very different place in their recovery, and I do think that it's important to point that out. Lastly, I also want to mention, I know you do such a great job on following a lot of the disruptive vendors that you just pointed out, with Pure doing container storage, we also have another bi-annual survey that we do called Emerging Technology, and that's for the private names. That's going to be launching in May, for everyone out there who's interested in not only the disruptive vendors, but also private equity players. Keep an eye out for that. We do that twice a year and that's growing in its respondents as well. And then lastly, one comment, because you mentioned the UiPath IPO, it was really hard for us to sit on the sidelines and not put some sort of rating on their dataset, but ultimately, the data was muted, unfortunately, and when you're seeing this kind of hype into an IPO like we saw with Snowflake, the data was resoundingly strong. We had no choice, but to listen to what the data said for Snowflake, despite the hype. We didn't see that for UiPath and we wanted to, and I'm not making a large call there, but I do think it's interesting to juxtapose the two, that when snowflake was heading to its IPO, the data was resoundingly positive, and for UiPath, we just didn't see that. >> Thank you for that, and Erik, thanks for coming on today. It's really a pleasure to have you, and so really appreciate the collaboration and look forward to doing more of these. >> Yeah, we enjoy the partnership greatly, Dave. We're very happy to have you on the ETR family and looking forward to doing a lot, lot more with you in the future. >> Ditto. Okay, that's it for today. Remember, these episodes are all available as podcasts wherever you listen. All you have to do is search "Breaking Analysis" podcast, and please subscribe to the series. Check out ETR website it's etr.plus. We also publish a full report every week on wikibon.com and siliconangle.com. You can email me, david.vellante@siliconangle.com, you can DM me on Twitter @dvellante or comment on our LinkedIn posts. I could see you in Clubhouse. This is Dave Vellante for Erik Porter Bradley for the CUBE Insights powered by ETR. Have a great week, stay safe, be well and we'll see you next time. (bright music)

>> Narrator: From around the globe, it's "theCUBE" with digital coverage of Smart Data Marketplaces brought to you by Io-Tahoe. >> We're back. We're talking about smart data and have been for several weeks now. Really it's all about injecting intelligence and automation into the data life cycle of the data pipeline. And today we're drilling into Smart Data Marketplaces, really trying to get to that self-serve, unified, trusted, secured, and compliant data models. And this is not trivial. And with me to talk about some of the nuances involved in actually getting there with folks that have experienced doing that. They'd send a series of digital evangelist with Tata Consultancy Services, TCS. And Ajay Vohora is back, he's the CEO of Io-Tahoe. Guys, great to see you, thanks so much for coming on. >> Good to see you, Dave. >> Hey Dave. >> Ajay, let's start with you. Let's set up the sort of smart data concept. What's that all about? What's your perspective? >> Yeah, so I mean, our way of thinking about this is you you've got data, it has latent value, and it's really about discovering what the properties of that data. Does it have value? Can you put that data to work? And the way we go about that with algorithms and machine learning, to generate signals in that data identified patterns, that means we can start to discover how can we apply that data to down stream? What value can we unlock for a customer and business? >> Well, so you've been on this, I mean, really like a laser, why? I mean, why this issue? Did you see a gap in the marketplace in terms of talking to customers and maybe you can help us understand the origin? >> Yeah, I think that the gap has always been there. They've been, it's become more apparent over recent times with big data. So the ability to manually work with volumes of data in petabytes is prohibitively complex and expensive. So you need the different routes, you need different set of tools and methods to do that. Metadata are data that you can understand about data. That's what we at Io-Tahoe focus on, discovering and generating that metadata. That ready, that analogy to automate those data ops processes. So the gap David, is being felt by a business owner prizes and all sectors, healthcare, telecoms, and putting that data to work. >> So Ved, Let's talk a little bit about your role. You work with a lot of customers. I see you as an individual in a company who's really trying to transform what is a very challenging industry. That's sort of ripe for transformation, but maybe you could give us your perspective on this, what kind of signals you're looking for from the data pipeline and we'll get into how you are helping transform healthcare? >> Thanks, David. You know I think this year has been one of those years where we've all realized about this idea of unknown unknowns, where something comes around the corner that you're completely not expecting. And that's really hard to plan for obviously. And I think what we need is the ability to find early signals and be able to act on things as soon as you can. Sometimes, and you know, the COVID-19 scenario of course, is hopefully once in a generation thing, but most businesses struggle with the idea that they may have the data there in their systems, but they still don't know which bit of that is really valuable and what are the signals they should be watching for. And I think the interesting thing here is the ability for us to extract from a massive data, the most critical and important signals. And I think that's where we want to focus on. >> And so, talk a little bit about healthcare in particular and sort of your role there, and maybe at a high level. How Tata and your eco-system are helping transform healthcare? >> So if you look at healthcare, you've got the bit where people need active intervention from a medical professional. And then you've got this larger body of people, typically elderly people who aren't unwell, but they have frailties. They have underlying conditions and they're very vulnerable, especially in the world that we're in now in the post-COVID-19 scenario. And what we were trying to look at is how do we keep people who are elderly, frail and vulnerable? How can we keep them safe in their own homes rather than moving to care homes, where there has been an incredibly high level of infection for things like COVID-19. So the world works better if you can keep people safe in their own homes, if you can see the slide we've got. We're also talking about a world where care is expensive. In most Western countries, especially in Western Europe, the number of elderly people is increasing as a percentage of the population, quite significantly, and resources just are not keeping up. We don't have enough people. We don't have enough funding to look after them effectively. And the care industry that used to do that job has been struggling of late. So it's kind of a perfect storm for the need for technology intervention there. And in that space, what we're saying is the data signal that we want to receive are exactly what as a relative, or a son or daughter you might want from a parent to say, "Everything's okay. "We know that today's been just like every other day "there are no anomalies in your daily living." If you could get the signals that might tell us that something's wrong, something not quite right. We don't need very complex diagnostics. We just need to know something's not quite right, that my dad hasn't woken up as has always at seven o'clock, but till nine o'clock there's no movement. Maybe he's a bit unwell. It's that kind of signal that if we can generate, can make a dramatic difference to how we can look out for these people, whether through professional carers or through family members. So what we're looking to do is to sensor-enable homes of vulnerable people so that those data signals can come through to us in a curated manner, in a way that protects privacy and security of the individual, but gives the right people, which is carers or chosen family members the access to the signals, which is alerts that might tell you there was too much movement at night, or the front door was been left open, things like that that would give you a reason to call him and check. Everybody has spoken to in this always has an example of an uncle or a relative or parent that they've looked after. And all they're looking for is a signal. Even stories like my father's neighbor calls me when he doesn't open his curtain by 11 o'clock, that actually, if you think about it is a data signal that something might be all right. And I think what we're trying to do with technology is create those kinds of data signals because ultimately, the healthcare system works much better if you can prevent rather than cure. So every dollar that you put into prevention saves maybe $3 to $5 downstream. The economic summit also are working our favor. >> And those signals give family members the confidence to act. Ajay, it is interesting to hear what Ved was talking about in terms of the unknowns, because when you think about the early days of the computer industry, there were a lot of knowns, the processes were known. It was like the technology was the big mystery. Now, I feel like it's flipped. We've certainly seen that with COVID. The technology is actually quite well understood and quite mature and reliable. One of the examples is automated data discovery, which is something that you guys have been been focused on at Io-Tahoe. Why is automated data discovery such an important component of a smart data life cycle? >> Yeah. I mean, if we look David at the schematic and this one moves from left to right where right at the outset with that latent data, the value is late because you don't know. Does it have? Can it be applied? Can that data be put to work or not? And the objective really is about driving some form of exchange or monetization of data. If you think about it in insurance or healthcare, you've got lots of different parties, providers, payers, patients, everybody's looking to make some kind of an exchange of information. The difficulty is in all of those organizations, that data sits within its own system. So data discovery, if we drill into the focus itself that, it's about understanding which data has value, classifying that data so that it can be applied and being able to tag it so that it can then be put to use it's the real enabler for DataOps. >> So maybe talk a little bit more about this. We're trying to get to self-service. It's something that we hear a lot about. You mentioned putting data to work. It seems to me that if the business can have access to that data and serve themselves, that's the way to put data to work. Do you have thoughts on that? >> Yeah, I mean, thinking back in terms of what IT and the IT function in a business could provide, there have been limitations around infrastructure, around scaling, around compute. Now that we're in an economy that is digital driven by API's your infrastructure, your data, your business rules, your intelligence, your models, all of those on the back of an API. So the options become limitless. How you can drive value and exchange that data. What that allows us to do is to be more creative, if we can understand what data has value for what use case. >> Ved, Let's talk a little bit about the US healthcare system. It's a good use case. I was recently at a chief data officer conference and listening to the CDO of Johns Hopkins, talk about the multiple different formats that they had to ingest to create that COVID map. They even had some PDFs, they had different definitions, and that's sort of underscored to me, the state of the US healthcare industry. I'm not as familiar with the UK and Europe generally, but I am familiar with the US healthcare system and the diversity that's there, the duplication of information and the like, maybe you could sort of summarize your perspectives and give us kind of the before and your vision of the after, if you will? >> The use of course, is particularly large and complex system. We all know that. We also know, I think there is some research that suggests that in the US the per-capita spend on healthcare is among the highest in the world. I think it's like 70%, and that compares to what just under 9%, which is going to be European, typical European figure. So it's almost double of that, but the outcomes are still vastly poor. When Ajay and I were talking earlier, I think we believe that there is a concept of a data friction. When you've got multiple players in an eco-system, trying to provide a single service as a patient, you're receiving a single health care service. There are probably a dozen up to 20 different organizations that have to collaborate to make sure you get that top of the line health care service. That kind of investment deserves. And what prevents it from happening very often is what we would call data friction, which is the ability to effectively share data. Something as simple as a healthcare record, which says, "This is Dave, this is Ved, this is Ajay." And when we go to hospital for anything, whatever happens, that healthcare record can capture all the information and tie to us as an individual. And if you go to a different hospital, then that record will follow you. This is how you would expect that to be implemented, but I think we're still on that journey. There are lots and lots of challenges. I've seen anecdotal data around people who suffered because they weren't carrying a card when they went into hospital, because that card has the critical elements of data, but in today's world, should you need to carry a piece of paper or can the entire thing be a digital data flow that can easily be, can certainly navigate through lack of paper and those kinds of things. So the vision that I think we need to be looking at is an effective data exchange or marketplace back with a kind of a backbone model where people agree and sign off a data standard, where each individual's data is always tied to the individual. So if you were to move States, if you would move providers, change insurance companies, none of that would impact your medical history, your data, and the ability to have the other care and medical professionals to access the data at the point of need and at the point of healthcare delivery. So I think that's the vision we're looking at, but as you rightly you said that there are enormous number of challenges, partly because of the history, of healthcare, I think it was technology enablement of healthcare started early. So there's a lot of legacy as well. So we shouldn't trivialize the challenges that the industry faces, but that I think is the way we want to go. >> Well, privacy is obviously a huge one, and a lot of the processes are built around non-digital processes and what you're describing as a flip for digital first. I mean, as a consumer, as a patient, I want an app for that. So I can see my own data. I can see price, price transparency, give access to people that I think need it. And that is a daunting task, isn't it? >> Absolutely. And I think the implicit idea and what you just said, which is very powerful is also on the app you want to control. >> Yes. >> And sometimes you want to be able to change access on data at that point. Right now, I'm at the hospital. I would like to access my data. And when I walk away or maybe three days later, I want to revoke that access. It's that level of control. And absolutely, it is by no means a trivial problem, but I think that's where you need the data automation tools. If you try to do any of this manually, we'd be here for another decade trying to solve this, but that's where tools like Io-Tahoe come in because to do this, a lot of the heavy lifting behind the scenes has to be automated. There has to be a machine churning that and presenting the simpler options. And I know you were talking about it just a little while ago Ajay. I was reminded of the example of a McDonald's or a Coke, because the sales store idea that you can go in and you can do your own ordering off a menu, or you can go in and select five different flavors from a Coke machine and choose your own particular blend of Coke. It's a very trivial example, but I think that's the word we want to get to with access of data as well. If it was that simple for consumers, for enterprise, business people, for doctors, then that's where we ultimately want to be able to arrive. But of course, to make something very simple for the end-user, somebody has to solve for complexity behind the scenes. >> So Ajay, it seems to me Ajay there're two major outcomes here. One is of course, the most important I guess, is patient outcomes, and the other is cost. I mean, they talked about the cost issues, we all, US especially understand the concerns about rising costs of healthcare. My question is this, how does a Smart Data Marketplace fit into achieving those two very important outcomes? >> When we think about how automation is enabling that, where we've got different data formats, the manual tasks are involved, duplication of information. The administrative overhead of that alone and the work, the rework, and the cycles of work that generates. That's really what we're trying to help with data is to eliminate that wasted effort. And with that wasted effort comes time and money to employ people to work through those siloed systems. So getting to the point where there is an exchange in a marketplace just as they would be for banking or insurance is really about automating the classification of data to make it available to a system that can pick it up through an API and to run a machine learning model and to manage a workflow, a process. >> Right, so you mentioned backing insurance, you're right. I mean, we've actually come a long way and just in terms of, know the customer and applying that to know the patient would be very powerful. I'm interested in what you guys are doing together, just in terms of your vision. Are you going to market together, kind of what you're seeing in terms of promoting or enabling this self-service, self-care. Maybe you could talk a little bit about Io-Tahoe and Tata, the intersection at the customer? >> Sure. I think we've been very impressed with the TCS vision of 4.0, how the re-imagining traditional industries, whether it's insurance, banking, healthcare, and bringing together automation, agile processes, robotics, AI, and once those enablers, technology may have brought together to re-imagine how those services can be delivered digitally. All of those are dependent on data. So we see that there's a really good fit here to enable understanding the legacy, the historic situation that has built up over time in an organization, a business and to help shine a light on what's meaningful in that to migrate to the cloud or to drive a digital twin, data science project. >> Ved, anything you can add to that? >> Sure. I mean, we do take the business 4.0 model quite seriously in terms of a lens with which you look at any industry, and what I talked about in healthcare was an example of that. And for us business 4.0, means a few very specific things. The technology that we use in today's verse should be agile, automated, intelligent, and cloud-based. These have become kind of hygiene factors now. On top of that, the businesses we build should be mass customized. They should be risk embracing. They should engage ecosystems, and they should strive for exponential value, not 10% growth year on year, but doubling, tripling every three, four years, because that's the competition that most businesses are facing today. And within that, the Tata group itself, is an extremely purpose-driven business. We really believe that we exist to serve communities, not just one specific set, i.e. shareholders, but the broader community in which we live and work. And I think this framework also allows us to apply that to things like healthcare, to education and to a whole vast range of areas where, everybody has a vision of using data science or doing really clever stuff at the gradients. But what becomes clear is, to do any of that, the first thing you need is a foundational piece. And as a foundation isn't right, then no matter how much you invest in the data science tools you won't get the answers you want. And the work we're doing with the Io-Tahoe really, for me, is particularly exciting because it sorts out that foundational piece. And at the end of it, to make all of this, again, I will repeat that, to make it simple and easy to use for the end user, whoever that is. And I realized that I'm probably the first person who's used fast food as a shining example for healthcare in this discussion, but you can make a lot of different examples. And today, if you press a button and start a car, that's simplicity, but someone has solved for that. And that's what we want to do with data as well. >> Yeah, that makes a lot of sense to me. We talk a lot about digital transformation and a digital business, and I would observe that a digital business puts data at the core. And you can certainly be the best example. There is, of course, Google is an all digital business, but take a company like Amazon, Who's got obviously a massive physical component to its business. Data is at the core. And that's exactly my takeaway from this discussion. Both of you are talking about putting data at the core, simplifying it, making sure that it's compliant, and healthcare it's taking longer, 'cause it's such a high risk industry, but it's clearly happening, COVID I guess, was an accelerant. Guys, Ajay, I'll start with you. Any final thoughts that you want to leave the audience with? _ Yeah, we're really pleased to be working with TCS. We've been able to explore how we're able to put dates to work in a range of different industries. Ved has mentioned healthcare, telecoms, banking and insurance are others. And the same impact they speak to whenever we see the exciting digital transformations that are being planned, being able to accelerate those, unlock the value from data is where we're having a purpose. And it's good that we can help patients in the healthcare sector, consumers in banking realize a better experience through having a more joined up marketplace with their data. >> Ved, you know what excites me about this conversation is that, as a patient or as a consumer, if I'm helping loved ones, I can go to the web and I can search, and I can find a myriad of possibilities. What you're envisioning here is really personalizing that with real time data. And that to me is a game changer. Your final thoughts? >> Thanks, David. I absolutely agree with you that the idea of data centricity and simplicity are absolutely forefront, but I think if we were to design an organization today, you might design it very differently to how most companies today are structured. And maybe Google and Amazon are probably better examples of that because you almost have to think of a business as having a data engine room at its core. A lot of businesses are trying to get to that stage, whereas what we call digital natives, are people who have started life with that premise. So I absolutely agree with you on that, but extending that a little bit. If you think of most industries as eco-systems that have to collaborate, then you've got multiple organizations who will also have to exchange data to achieve some shared outcomes. Whether you look at supply chains of automobile manufacturers or insurance companies or healthcares we've been talking about. So I think that's the next level of change we want to be able to make, which is to be able to do this at scale across organizations at industry level or in population scheme for healthcare. >> Yeah, Thank you for that. Go ahead Ajay. >> David that's where it comes back to again, the origination where we've come from in big data. The volume of data combined with the specificity of individualizing, personalizing a service around an individual amongst that massive data from different providers is where is exciting, that we're able to have an impact. >> Well, and you know Ajay, I'm glad you brought that up because in the early days of big data, there were only a handful of companies, the biggest financial institutions. Obviously, the internet giants who had all these engineers that were able to take advantage of it. But with companies like Io-Tahoe and others, and the investments that the industry has made in terms of providing the tools and simplifying that, especially with machine intelligence and AI and machine learning, these are becoming embedded into the tooling so that everybody can have access to them, small, medium, and large companies. That's really, to me, the exciting part of this new era that we're entering. >> Yeah, and we have placed those, take it down to the level of not-for-profits and smaller businesses that want to innovate and leapfrog into, to growing their digital delivery of their service. >> And I know a lot of time, but Ved, what you were saying about TCS's responsibility to society, I think is really, really important. Large companies like yours, I believe, and you clearly do as well, have a responsibility to society more than just a profit. And I think, Big Tech it's a better app in a lot of cases, but so thank you for that and thank you gentlemen for this great discussion. I really appreciate it. >> Thanks David. >> Thank you. >> All right, keep it right there. I'll be right back right after this short break. This is Dave Vellante for theCUBE. (calm music)

>> Narrator: From around the globe, it's theCUBE. With digital coverage of smart data marketplaces. Brought to you by Io-Tahoe. >> Digital transformation has really gone from a buzzword to a mandate, but digital business is a data business. And for the last several months we've been working with Io-Tahoe on an ongoing content series, focused on smart data and automation to drive better insights and outcomes, essentially putting data to work. And today we're going to do a deeper dive on automating data discovery. And one of the thought leaders in this space is Ajay Vohora, who's the CEO of Io-Tahoe. Once again, joining me, Ajay good to see you. Thanks for coming on. >> Great to be here, David, thank you. >> So let's, let's start by talking about some of the business realities and what are the economics that are driving automated data discovery? Why is that so important? >> Yeah, on this one, David it's a number of competing factors. We've got the reality of data which may be sensitive. So there's control. Three other elements wanting to drive value from that data to innovation. You can't really drive a lot of value without exchanging data. So the ability to exchange data and to manage those cost overheads and data discovery is at the root of managing that in an automated way to classify that data and set some policies to put that automation in place. >> Yeah, look, we have a picture of this. If we could bring it up guys, cause I want to, Ajay, help the audience understand kind of where data discovery fits in here. This is, as we talked about, this is a complicated situation for a lot of customers. They've got variety of different tools and you've really laid it out nicely here in this diagram. So, take us through sort of where that piece fits. >> Yeah, I mean, we're at the right hand side of this exchange, you know. We're really now in a data driven economy that is everything's connected through APIs that we consume online through mobile apps. And what's not apparent is the chain of activities and tasks that have to go into serving that data to an API at the outset. They may be many legacy systems, technologies, platforms On-premise, in cloud, hybrid, you name it and across those silos, getting to a unified view is the heavy lifting. I think we've seen some, some great impacts that BI tools, such as Power BI, Tableau, Looker, and so on, and Qlik have had, and they're in our ecosystem on visualizing Data and, you know, CEOs, managers, people that are working in companies day-to-day get a lot of value from saying, "What's the real time activity? "What was the trend over this month versus last month?" The tools to enable that, you know, we hear a lot of good things that we're doing with Snowflake, MongoDB on the public Cloud platforms, GCP Azure about enabling building those pipelines to feed into those analytics. But what often gets hidden is how do you source that data that could be locked into a mainframe, a data warehouse, IOT data, and pull over all of that together. And that is the reality of that is it's a lot of heavy lifting. It's hands on work that can be time consuming. And the issue there is that data may have value. It might have potential to have an impact on the top line for a business, on outcomes for consumers, but you're never really sure unless you've done the investigation, discovered it, unified that, and be able to serve that through to other technologies. >> Guys, if you would bring that picture back up again, because Ajay you made a point and I want to land on that for a second. There's a lot of manual curating. An example would be the data catalog. You know, data scientists complain all the time that they're manually wrangling data. And so you're trying to inject automation into the cycle. And then the other piece that I want you to address is the importance of APIs. You really can't do this without an architecture that allows you to connect things together that sort of enables some of the automation. >> Yep, I mean, I'll take that in two parts, David, the APIs, so virtual machines connected by APIs, business rules, and business logic driven by APIs, applications, so everything across the stack from infrastructure down to the network, hardware is all connected through APIs and the work of serving data through to an API, building those pipelines, is often miscalculated, just how much manual effort that takes and that manual effort, we've got a nice list here of what we automate down at the bottom, those tasks of indexing, labeling, mapping across different legacy systems, all of that takes away from the job of a data scientist or data engineer, looking to produce value, monetize data, and to help that business convey to consumers. >> Yeah, it's that top layer that the business sees, of course, there's a lot of work that has to go into achieving that. I want to talk about some of the key tech trends that you're seeing. And one of the things that we talk about a lot is metadata. The importance of metadata, you know, can't be understated. What are some of the big trends that you're seeing metadata and others? >> Yeah, I'll summarize it as five. There's a trend now look at metadata more holistically across the enterprise. And that really makes sense from trying to look across different data silos and apply a policy to manage that data. So that's the control piece. That's that lever. The other side, sometimes competing with that control around sensitive data around managing the cost of data is innovation. Innovation being able to speculate and experiment and try things out where you don't really know what the outcome is if you're a data scientist and engineer, you've got a hypothesis and therefore you've got that tension between control over data and innovation and driving value from it. So enterprise wide metadata management is really helping to unlock where might that latent value be across that sets of data. The other piece is adaptive data governance. Those controls that stick from the data policemen, data stewards, where they're trying to protect the organization, protect the brand, protect consumers data necessary, but in different use cases, you might want to nuance and apply a different policy to govern that data relevant to the context where you might have data that is less sensitive, that can be used for innovation and adapting the style of governance to fit the context is another trend that we're seeing coming up here. A few others is where we're sitting quite extensively in working with automating data discovery. We're now breaking that down into what can we direct? What do we know is a business outcome is a known upfront objective and direct that data discovery to towards that. And that means applying our algorithms around technology and our tools towards solving a known problem. The other one is autonomous data discovery. And that means, you know, trying to allow background processes to understand what changes are happening with data over time, flagging those anomalies. And the reason that's important is when you look over a length of time to see different spikes, different trends and activity, that's really giving a data ops team the ability to manage and calibrate how they're applying policies and controls the data. And the last two, David, that we're seeing is this huge drive towards self-service. So re-imagining how to apply policy data governance into the hands of a data consumer inside a business, or indeed the consumer themselves, to self-service if they're a banking customer or healthcare customer and the policies and the controls and rules, making sure that those are all in place to adaptively serve those data marketplaces that when are involved in creating. >> I want to ask you about the autonomous data discovering, the adaptive data governance, is the problem we're addressing there one of quality, in other words, machines are better than humans are at doing this? Is it one of scale? That humans just don't don't scale that well? Is it both? Can you add some color to that? >> Yeah, honestly, it's the same equation that existed 10 years ago, 20 years ago, it's being exacerbated, but it's that equation of how do I control all the things that I need to protect? How do I enable innovation where it is going to deliver business value? How do I exchange data between a customer, somebody in my supply chain safely, and do all of that whilst managing the fourth leg, which is cost overheads. There's not an open checkbook here. I've got to figure out if I'm the CIO and CDO, how I do all of this within a fixed budget. So those aspects have always been there, now with more choices, infrastructure in the Cloud, API driven applications, On-premises, and that is expanding the choices that a business has and how they put their data to work. It's also then creating a layer of management and data governance that really has to now manage those four aspects, control, innovation, exchange of data, and the cost overhead. >> That top layer of the first slide that we showed was all about the business value. So, I wonder if we could drill into the business impact a little bit. What are your customers seeing specifically in terms of the impact of all this automation on their business? >> Yeah, so we've had some great results. I think a few of the biggest have been helping customers move away from manually curating their data and their metadata. It used to be a time where if data initiatives or data governance initiatives, there'd be teams of people manually feeding a data catalog. And it's great to have that inventory of classified data to be able to understand single version of the truth, but having 10, 15 people manually process that, keep it up to date, when it's moving feet, the reality of it is what's true about data today, add another few sources and a few months time to your business, start collaborating with new partners, suddenly the landscape has changed. The amount of work has gone up, but what we're finding is through automating, creating that data discovery, feeding our data catalog, that's releasing a lot more time for our customers to spend on innovating and managing their data. A couple of others is around self service data analytics, moving the choices of what data might have business value into the hands of business users and data consumers to have faster cycle times around generating insights. And we're really helping them by automating the creation of those data sets that are needed for that. And the last piece, I'd have to say where we're seeing impacts more recently is in the exchange of data. There are a number of marketplaces out there who are now being compelled to become more digital, to rewire their business processes and everything from an RPA initiative to automation involving digital transformation is having CIOs, chief data officers and enterprise architects rethink how do they, how do they rewire the pipelines for their data to feed that digital transformation? >> Yeah, to me, it comes down to monetization. Now, of course, that's for a for-profit industry. For non-profits, for sure, the cost cutting or in the case of healthcare, which we'll talk about in a moment, I mean, it's patient outcomes, but the job of a Chief Data Officer has gone from data quality and governance and compliance to really figuring out how data can be monetized, not necessarily selling the data, but how it contributes to the monetization of the company. And then really understanding specifically for that organization, how to apply that. And that is a big challenge. We sort of chatted about 10 years ago, the early days of a dupe. And then 1% of the companies had enough engineers to figure it out, but now the tooling is available. The technology is there and the practices are there. And that really, to me is the bottom line, Ajay, is it's show me the money. >> Absolutely. It's definitely is focusing in on the single view of that customer and where we're helping there is to pull together those disparate, siloed sources of data to understand what are the needs of the patient, of the broker of the, if it's insurance? What are the needs of the supply chain manager, if it's manufacturing? And providing that 360 view of data is helping to see, helping that individual unlock the value for the business. So data's providing the lens provided, you know which data it is that can assist in doing that. >> And, you know, you mentioned RPA before, I had an RPA customer tell me she was a Six Sigma expert and she told me, "We would never try to apply Six Sigma "to a business process, "but with RPA we can do so very cheaply." Well, what that means is lower costs. It means better employee satisfaction and really importantly, better customer satisfaction and better customer outcomes. Let's talk about healthcare for a minute because it's a really important industry. It's one that is ripe for disruption and has really been, up until recently, pretty slow to adopt a lot of the major technologies that have been made available. But what are you seeing in terms of this theme we're using a putting data to work in healthcare specifically? >> Yeah, I mean, health care's has had a lot thrown at it. There's been a lot of change in terms of legislation recently, particularly in the U.S. market, in other economies, healthcare is on a path to becoming more digital. And part of that is around transparency of price. So, to be operating effectively as a healthcare marketplace, being able to have that price transparency around what an elective procedure is going to cost before taking that step forward. It's super important to have an informed decision around that. So if we look at the U.S., for example, we've seen that healthcare costs annually have risen to $4 trillion, but even with all of that cost, we have healthcare consumers who are reluctant sometimes to take up healthcare even if they have symptoms. And a lot of that is driven through not knowing what they're opening themselves up to. And, you know, I think David, if you or I were to book travel a holiday, maybe, or trip, we'd want to know what we're in for, what we're paying for upfront. But sometimes in healthcare that choice, the option might be the plan, but the cost that comes with it isn't. So recent legislation in the U.S. is certainly helpful to bring forward that price transparency. The underlying issue there though is the disparate different format types of data that are being used from payers, patients, employers, different healthcare departments to try and make that work. And where we're helping on that aspect in particular related to price transparency is to help make that data machine readable. So, sometimes with data, the beneficiary might be a person, but in a lot of cases, now we're seeing the ability to have different systems interact and exchange data in order to process the workflow to generate online lists of pricing from a provider that's been negotiated with a payer is really an enabling factor. >> So guys, I wonder if you could bring up the next slide, which is kind of the nirvana. So, if you saw the previous slide that the middle there was all different shapes and presumably to disparate data, this is the outcome that you want to get, where everything fits together nicely. And you've got this open exchange. It's not opaque as it is today. It's not bubble gum, band-aids and duct tape, but describe this sort of outcome that you're trying to achieve and maybe a little bit about what it's going to take to get there. >> Ajay: Yeah, that that's the culmination of a number of things. It's making sure that the data is machine readable, making it available to APIs, that could be RPA tools. We're working with technology companies that employ RPA for healthcare, and specifically to manage that patient and payer data to bring that together. In our data discovery, what we're able to do is to classify that data and have it made available to a downstream tool technology or person to apply that, that workflow to the data. So this looks like nirvana, it looks like utopia, but it's, you know, the end objective of a journey that we can see in different economies, that are at different stages of maturity in turning healthcare into a digital service even so that you can consume it from where you live, from home with telemedicine and tele care. >> Yeah, so, and this is not just for healthcare, but you know, you want to achieve that self-service data marketplace in virtually any industry. You're working with TCS, Tata Consulting Services to achieve this. You know, a company like Io-Tahoe has to have partnerships with organizations that have deep industry expertise. Talk about your relationship with TCS and what you guys are doing specifically in this regard. >> Yeah, we've been working with TCS now for a long while and we'll be announcing some of those initiatives here where we're now working together to reach their customers where they've got a brilliant framework of business, 4.0, where they're re-imagining with the clients, how their business can operate with AI, with automation and become more agile and digital. Our technology, now, the reams of patients that we have in our portfolio, being able to apply that at scale, on a global scale across industries, such as banking, insurance and healthcare is really allowing us to see a bigger impact on consumer outcomes, patient outcomes. And the feedback from TCS is that we're really helping in those initiatives remove that friction. They talk a lot about data friction. I think that's a polite term for the image that we just saw with the disparate technologies that the legacy that has built up. So if we want to create a transformation, having that partnership with TCS across industries is giving us that reach and that impact on many different people's day-to-day jobs and lives. >> Let's talk a little bit about the Cloud. It's a topic that we've hit on quite a bit here in this content series. But, but you know, the Cloud companies, the big hyper-scalers, they've put everything into the Cloud, right? But customers are more circumspect than that. But at the same time, machine intelligence, ML, AI, the Cloud is a place to do a lot of that. That's where a lot of the innovation occurs. And so what are your thoughts on getting to the Cloud, putting data to work, if you will, with machine learning, stuff that you're doing with AWS, what's your fit there? >> Yeah, we, David, we work with all of the Cloud platforms, Microsoft Azure, GCP, IBM, but we're expanding our partnership now with AWS. And we're really opening up the ability to work with their Greenfield accounts, where a lot of that data, that technology is in their own data centers at the customer. And that's across banking, healthcare, manufacturing, and insurance. And for good reason, a lot of companies that have taken the time to see what works well for them with the technologies that the Cloud providers are offering, and a lot of cases, testing services or analytics using the Cloud to move workloads to the Cloud to drive data analytics is a real game changer. So there's good reason to maintain a lot of systems On-premise. If that makes sense from a cost, from a liability point of view and the number of clients that we work with that do have, and will keep their mainframe systems when in Cobra is no surprise to us, but equally they want to tap into technologies that AWS has such as SageMaker. The issue is as a Chief Data Officer, I didn't have the budget to move everything to the Cloud they want, I might want to show some results first upfront to my business users and work closely with my Chief Marketing Officer to look at what's happening in terms of customer trends and customer behavior> What are the customer outcomes, patient outcomes and partner outcomes that you can achieve through analytics, data science? So, working with AWS and with clients to manage that hybrid topology of some of that data being in the Cloud, being put to work with AWS SageMaker and Io-Tahoe being used to identify where is the data that needs to be amalgamated and curated to provide the dataset for machine learning, advanced analytics to have an impact for the business. >> So what are the critical attributes of what you're looking at to help customers decide what to move and what the keep if you will? >> Well, one of the quickest outcomes that we help customers achieve is to buy that business glossary, you know, that the items of data, that means something to them across those different silos and pull all of that together into a unified view. Once they've got that data engineer working with a business manager to think through, how do we want to create this application? Now, what is the churn model, the loyalty or the propensity model that we want to put in place here? How do we use predictive analytics to understand what needs for a patient that sort of innovation is what we're unlocking, applying a tools such as SageMaker on AWS to then do the computation and to build those models to deliver that outcome is across that value chain. And it goes back to the first picture that we put up, David, you know, the outcome is that API on the back of it, you've got a machine learning model that's been developed in a tool such as Databricks or Jupiter notebook. That data has to be sourced from somewhere. Somebody has to say that, "Yep, "You've got permission to do what you're trying to do without falling foul "of any compliance around data." And it all goes back to discovering that data, classifying it, indexing it in an automated way to cut those timelines down to hours and days. >> Yeah, it's the innovation part of your data portfolio, if you will, that you're going to put into the Cloud, apply tools like SageMaker and others, your tool Azure. I mean, whatever your favorite tool is, you don't care. The customer's going to choose that. And you know, the Cloud vendors, maybe they want you to use their tool, but they're making their marketplaces available to everybody, but it's that innovation piece, the ones that you, where you want to apply that self-service data marketplace to, and really drive, as I said before, monetization, All right, give us your final thoughts. Ajay, bring us home. >> So final thoughts on this, David, is at the moment, we're seeing a lot of value in helping customers discover their data using automation, automatically curating a data catalog. And that unified view is then being put to work through our API is having an open architecture to plug in whatever tool technology our clients have decided to use. And that open architecture is really feeding into the reality of what CIOs and Chief Data Officers are managing, which is a hybrid On-premise Cloud approach to use best of breed. But business users wanting to use a particular technology to get their business outcome, having the flexibility to do that no matter where your data is sitting On-premise, on Cloud is where self-service comes in so that sales service view of what data I can plug together, jive exchange, monetizing that data is where we're starting to see some real traction with customers. Now accelerating, becoming more digital to serve their own customers. >> Yeah, we really have seen a cultural mind shift going from sort of complacency, and obviously COVID has accelerated this, but the combination of that cultural shift, the Cloud machine intelligence tools give me a lot of hope that the promises of big data will ultimately be lived up to in this next 10 years. So Ajay Vohora, thanks so much for coming back on theCUBE. You're a great guest and appreciate your insights. >> Appreciate it, David. See you next time. >> All right, keep it right there, everybody, right back after this short break. 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>> Narrator: From around the globe, it's the CUBE with digital coverage of Smart Data Marketplaces, brought to you by Io-Tahoe. >> Hello this is Dave Vellante of the CUBE inviting you to join me for a special drill down presentation on the importance of automated data migration. Along with our friends from Io-Tahoe, we're going to explore the recent trends of automated data discovery, adaptive data governance, and just how far we've come from manually curating an enterprise data catalog. Ajay Vahora is the CEO of Io-Tahoe, as well as Stuti Deshpande of AWS and the digital evangelist Ved Sen of TCS, Tata Consultancy Services, will be there as well. Hope you can join us on Thursday, September 17th, at 9:00 a.m. Pacific for Smart Data Marketplaces. For more details, click on theCUBE.net. (upbeat music)

>>from around the globe. It's the Cube with digital coverage of smart data. Marketplace is brought to You by Io Tahoe Digital transformation is really gone from buzzword to a mandate. Additional businesses, a data business. And for the last several months, we've been working with Iot Tahoe on an ongoing content. Serious, serious, focused on smart data and automation to drive better insights and outcomes, essentially putting data to work. And today we're gonna do a deeper dive on automating data Discovery. And one of the thought leaders in this space is a J ahora who is the CEO of Iot. Tahoe's once again joining Me A J Good to see you. Thanks for coming on. >>A great to be here, David. Thank you. >>So let's start by talking about some of the business realities. And what are the economics that air? That air driving, automated data Discovery? Why is that so important? >>Yeah, and on this one, David, it's It's a number of competing factors we've got. The reality is data which may be sensitive, so this control on three other elements are wanting to drive value from that data. So innovation, you can't really drive a lot of value without exchanging data. So the ability to exchange data and to manage those costs, overheads and data discovery is at the roots of managing that in an automated way to classify that data in sets and policies to put that automation in place. >>Yeah. Okay, look, we have a picture of this. We could bring it up, guys, because I want oh, A j help the audience. Understand? Unaware data Discovery fits in here. This is as we talked about this, a complicated situation for a lot of customers. They got a variety of different tools, and you really laid it out nicely here in this diagram. So take us through. Sort of where that he spits. >>Yeah. I mean, where at the right hand side, This exchange. You know, we're really now in a data driven economy that is, everything's connected through AP, eyes that we consume on mine free mobile relapse. And what's not a parent is the chain of activities and tasks that have to go into serving that data two and eight p. I. At the outset, there may be many legacy systems, technologies, platforms on premise and cloud hybrids. You name it. Andi across those silos. Getting to a unified view is the heavy lifting. I think we've seen Cem some great impacts that be I titles such as Power Bi I tableau looker on DSO on in Clear. Who had Andi there in our ecosystem on visualising Data and CEO's managers, people that are working in companies day to day get a lot of value from saying What's the was the real time activity? What was the trend over this month? First his last month. The tools to enable that you know, we here, Um, a lot of good things are work that we're doing with snowflake mongo db on the public cloud platforms gcpd as your, um, about enabling building those pay planes to feed into those analytics. But what often gets hidden is have you sauce that data that could be locked into a mainframe, a data warehouse? I ot data on DPA, though, that all of that together that is the reality of that is it's it's, um, it's a lot of heavy lifting It z hands on what that, um, can be time consuming on the issue There is that data may have value. It might have potential to have an impact on the on the top line for a business on outcomes for consumers. But you never any sure unless you you've done the investigation discovered it unified that Onda and be able to serve that through to other technologies. >>Guys have. You would bring that picture back up again because A. J, you made a point, and I wanna land on that for a second. There's a lot of manual curating. Ah, an example would be the data catalogue if they decide to complain all the time that they're manually wrangling data. So you're trying to inject automation in the cycle, and then the other piece that I want you to addresses the importance of AP eyes. You really can't do this without an architecture that allows you to connect things together. That sort of enables some of the automation. >>Yeah, I mean, I don't take that in two parts. They would be the AP eyes so virtual machines connected by AP eyes, um, business rules and business logic driven by AP eyes applications. So everything across the stack from infrastructure down to the network um, hardware is all connected through AP eyes and the work of serving data three to an MP I Building these pipelines is is often, um, miscalculated. Just how much manual effort that takes and that manual ever. We've got a nice list here of what we automate down at the bottom. Those tasks of indexing, labeling, mapping across different legacy systems. Um, all of that takes away from the job of a data scientist today to engineer it, looking to produce value monetize data on day two to help their business day to conceive us. >>Yes. So it's that top layer that the business sees, of course, is a lot of work that has to go went into achieving that. I want to talk about some of the key tech trends that you're seeing and one of the things that we talked about a lot of metadata at the importance of metadata. It can't be understated. What are some of the big trends that you're seeing metadata and others? >>Yeah, I'll summarize. It is five. There's trains now, look, a metadata more holistically across the enterprise, and that really makes sense from trying. Teoh look across different data silos on apply, um, a policy to manage that data. So that's the control piece. That's that lever the other side's on. Sometimes competing with that control around sense of data around managing the costs of data is innovation innovation, being able to speculate on experiment and trying things out where you don't really know what the outcome is. If you're a data scientist and engineer, you've got a hypothesis. And now, before you got that tension between control over data on innovation and driving value from it. So enterprise wide manage data management is really helping to enough. Where might that latent value be across that sets of data? The other piece is adaptive data governance. Those controls that that that stick from the data policemen on day to steer its where they're trying to protect the organization, protect the brand, protect consumers data is necessary. But in different use cases, you might want to nuance and apply a different policy to govern that data run of into the context where you may have data that is less sensitive. Um, that can me used for innovation. Andi. Adapting the style of governance to fit the context is another trend that we're seeing coming up here. A few others is where we're sitting quite extensively and working with automating data discovery. We're now breaking that down into what can we direct? What do we know is a business outcome is a known up front objective on direct that data discovery to towards that. And that means applying around with Dems run technology and our tools towards solving a known problem. The other one is autonomous data discovery. And that means, you know, trying to allow background processes do winds down what changes are happening with data over time flagging those anomalies. And the reason that's important is when you look over a length of time to see different spikes, different trends and activity that's really giving a day drops team the ability to to manage and calibrate how they're applying policies and controls today. There, in the last two David that we're seeing is this huge drive towards self service so reimagining how to play policy data governance into the hands off, um, a day to consumer inside a business or indeed, the consumer themselves. The South service, um, if their banking customer or healthcare customer and the policies and the controls and rules, making sure that those are all in place to adaptive Lee, um, serve those data marketplaces that, um when they're involved in creating, >>I want to ask you about the autonomous data discovering the adaptive data. Governance is the is the problem where addressing their one of quality. In other words, machines air better than humans are doing this. Is that one of scale that humans just don't don't scale that well, is it? Is it both? Can you add some color to that >>yet? Honestly, it's the same equation that existed 10 years ago, 20 years ago. It's It's being exacerbated, but it's that equation is how do I control both things that I need to protect? How do we enable innovation where it is going to deliver business value? Had to exchange data between a customer, somebody in my supply chains safely. And all of that was managing the fourth that leg, which is cost overheads. You know, there's no no can checkbook here. I've got a figure out. If only see io and CDO how I do all of this within a fixed budget so that those aspects have always been there. Now, with more choices. Infrastructure in the cloud, um, NPR driven applications own promise. And that is expanding the choices that a a business has and how they put mandated what it's also then creating a layer off management and data governance that really has to now, uh, manage those full wrath space control, innovation, exchange of data on the cost overhead. >>That that top layer of the first slide that we showed was all about business value. So I wonder if we could drill into the business impact a little bit. What do your customers seeing you know, specifically in terms of the impact of all this automation on their business? >>Yeah, so we've had some great results. I think view the biggest Have Bean helping customers move away from manually curating their data in their metadata. It used to be a time where for data quality initiatives or data governance initiative that be teams of people manually feeding a data Cavallo. And it's great to have the inventory of classified data to be out to understand single version of the trees. But in a having 10 15 people manually process that keep it up to date when it's moving feet. The reality of it is what's what's true about data today? and another few sources in a few months. Time to your business on start collaborating with new partners. Suddenly the landscape has changed. The amount of work is gonna But the, um, what we're finding is through automating creating that data discovery feeding a dent convoke that's releasing a lot more time for our CAS. Mr Spend on innovating and managing their data. A couple of others is around cell service data and medics moving the the choices of what data might have business value into the hands of business users and and data consumers to They're faster cycle times around generating insights. Um, we really helping that by automating the creation of those those data sets that are needed for that. And in the last piece, I'd have to say where we're seeing impacts. A more recently is in the exchange of data. There are a number of marketplaces out there who are now being compelled to become more digital to rewire their business processes. Andi. Everything from an r p a initiative. Teoh automation involving digital transformation is having, um, see iose Chief data officers Andi Enterprise architects rethink how do they how they re worthy pipelines? But they dated to feed that additional transformation. >>Yeah, to me, it comes down to monetization. Of course, that's for for profit in industry, from if nonprofits, for sure, the cost cutting or, in the case of healthcare, which we'll talk about in a moment. I mean, it's patient outcomes. But you know, the the job of ah, chief data officer has gone from your data quality and governance and compliance to really figuring out how data and be monetized, not necessarily selling the data, but how it contributes for the monetization of the company and then really understanding specifically for that organization how to apply that. And that is a big challenge. We chatted about it 10 years ago in the early days of a Duke. And then, you know, 1% of the companies had enough engineers to figure it out. But now the tooling is available, the technology is there and the the practices air there, and that really to me, is the bottom line. A. J is it says to show me the money. >>Absolutely. It's is definitely then six sing links is focusing in on the saying over here, that customer Onda, where we're helping there is dio go together. Those disparities siloed source of data to understand what are the needs of the patient of the broker of the if it's insurance? Ah, one of the needs of the supply chain manager If its manufacturing onda providing that 3 60 view of data, um is helping to see helping that individual unlock the value for the business. Eso data is providing the lens, provided you know which data it is that can God assist in doing that? >>And you know, you mentioned r p A. Before an r p A customer tell me she was a six Sigma expert and she told me we would never try to apply six segment to a business process. But with our P A. We can do so very cheaply. Well, what that means is lower costs means better employee satisfaction and, really importantly, better customer satisfaction and better customer outcomes. Let's talk about health care for a minute because it's a really important industry. It's one that is ripe for disruption on has really been up until recently, pretty slow. Teoh adopt ah, lot of the major technologies that have been made available, but come, what are you seeing in terms of this theme, we're using a putting data to work in health care. Specific. >>Yeah, I mean, healthcare's Havlat thrown at it. There's been a lot of change in terms of legislation recently. Um, particularly in the U. S. Market on in other economies, um, healthcare ease on a path to becoming more digital on. Part of that is around transparency of price, saying to be operating effectively as a health care marketplace, being out to have that price transparency, um, around what an elective procedure is going to cost before taking that that's that forward. It's super important to have an informed decision around there. So we look at the US, for example. We've seen that health care costs annually have risen to $4 trillion. But even with all of that on cost, we have health care consumers who are reluctant sometimes to take up health care if they even if they have symptoms on a lot of that is driven through, not knowing what they're opening themselves up to. Andi and I think David, if you are, I want to book, travel, holiday, maybe, or trip. We want to know what what we're in for what we're paying for outfront, but sometimes in how okay, that choice, the option might be their plan, but the cost that comes with it isn't so recent legislation in the US Is it certainly helpful to bring for that tryst price, transparency, the underlying issue there? There is the disparity. Different formats, types of data that being used from payers, patients, employers, different healthcare departments try and make that make that work. And when we're helping on that aspect in particular related to track price transparency is to help make that date of machine readable. So sometimes with with data, the beneficiary might be on a person. I've been a lot of cases now we're seeing the ability to have different systems, interact and exchange data in order to process the workflow. To generate online at lists of pricing from a provider that's been negotiated with a payer is, um, is really a neighboring factor. >>So, guys, I wonder if you bring up the next slide, which is kind of the Nirvana. So if you if you saw the previous slide that the middle there was all different shapes and presumably to disparage data, this is that this is the outcome that you want to get. Everything fits together nicely and you've got this open exchange. It's not opaque as it is today. It's not bubble gum band aids and duct tape, but but but described this sort of outcome the trying to achieve and maybe a little bit about what gonna take to get there. >>Yeah, that's a combination of a number of things. It's making sure that the data is machine readable. Um, making it available to AP eyes that could be our ph toes. We're working with technology companies that employ R P. A full health care. I'm specifically to manage that patient and pay a data. Teoh, bring that together in our data Discovery. What we're able to do is to classify that data on having made available to eight downstream tour technology or person to imply that that workflow to to the data. So this looks like nirvana. It looks like utopia. But it's, you know, the end objective of a journey that we can see in different economies there at different stages of maturity, in turning healthcare into a digital service, even so that you could consume it from when you live from home when telling medicine. Intellicast >>Yes, so And this is not just health care but you wanna achieve that self service doing data marketplace in virtually any industry you working with TCS, Tata Consultancy Services Toe Achieve this You know, if you are a company like Iota has toe have partnerships with organizations that have deep industry expertise Talk about your relationship with TCS and what you guys are doing specifically in this regard. >>Yeah, we've been working with TCS now for room for a long while. Andi will be announcing some of those initiatives here where we're now working together to reach their customers where they've got a a brilliant framework of business for that zero when there re imagining with their clients. Um, how their business cause can operate with ai with automation on, become more agile in digital. Um, our technology, the dreams of patients that we have in our portfolio being out to apply that at scale on the global scale across industries such as banking, insurance and health care is is really allowing us to see a bigger impact on consumer outcomes. Patient outcomes And the feedback from TCS is that we're really helping in those initiatives remove that friction. They talk a lot about data. Friction. Um, I think that's a polite term for the the image that we just saw with the disparity technologies that the legacy that has built up. So if we want to create a transformation, Um, having a partnership with TCS across Industries is giving us that that reach and that impacts on many different people's day to day jobs and knives. >>Let's talk a little bit about the cloud. It's It's a topic that we've hit on quite a bit here in this in this content Siri's. But But you know, the cloud companies, the big hyper scale should put everything into the cloud, right? But but customers are more circumspect than that. But at the same time, machine intelligence M. L. A. The cloud is a place to do a lot of that. That's where a lot of the innovation occurs. And so what are your thoughts on getting to the cloud? Ah, putting dated to work, if you will, with machine learning stuff you're doing with aws. What? You're fit there? >>Yeah, we we and David. We work with all of the cloud platforms. Mike stuffed as your G, c p IBM. Um, but we're expanding our partnership now with AWS Onda we really opening up the ability to work with their Greenfield accounts, where a lot of that data that technology is in their own data centers at the customer, and that's across banking, health care, manufacturing and insurance. And for good reason. A lot of companies have taken the time to see what works well for them, with the technologies that the cloud providers ah, are offered a offering in a lot of cases testing services or analytics using the cloud to move workloads to the cloud to drive Data Analytics is is a real game changer. So there's good reason to maintain a lot of systems on premise. If that makes sense from a cost from a liability point of view on the number of clients that we work with, that do have and we will keep their mainframe systems within kobo is is no surprise to us, but equally they want to tap into technologies that AWS have such a sage maker. The issue is as a chief data officer, I don't have the budget to me, everything to the cloud day one, I might want to show some results. First upfront to my business users Um, Onda worked closely with my chief marketing officer to look at what's happening in terms of customer trains and customer behavior. What are the customer outcomes? Patient outcomes and partner at comes I can achieve through analytics data signs. So I, working with AWS and with clients to manage that hybrid topology of some of that data being, uh, in the cloud being put to work with AWS age maker on night, I hope being used to identify where is the data that needs to bay amalgamated and curated to provide the data set for machine learning advanced and medics to have an impact for the business. >>So what are the critical attributes of what you're looking at to help customers decide what what to move and what to keep, if you will. >>Well, what one of the quickest outcomes that we help custom achieve is to buy that business blustery. You know that the items of data that means something to them across those different silos and pour all of that together into a unified view once they've got that for a data engineer working with a a business manager to think through how we want to create this application. There was the turn model, the loyalty or the propensity model that we want to put in place here. Um, how do we use predictive and medics to understand what needs are for a patient, that sort of innovation is what we're looking applying the tools such a sagemaker, uh, night to be west. So they do the the computation and to build those models to deliver the outcome is is across that value chain, and it goes back to the first picture that we put up. David, you know the outcome Is that a P I On the back of it, you've got the machine learning model that's been developed in That's always such as data breaks. But with Jupiter notebook, that data has to be sourced from somewhere. Somebody has to say that yet you've got permission to do what you're trying to do without falling foul of any compliance around data. Um, it'll goes back to discovering that data, classifying it, indexing it in an automated way to cut those timelines down two hours and days. >>Yeah, it's the it's the innovation part of your data portfolio, if you will, that you're gonna put into the cloud. Apply tools like sage maker and others. You told the jury. Whatever your favorite tool is, you don't care. The customer's gonna choose that and hear the cloud vendors. Maybe they want you to use their tool, but they're making their marketplaces available to everybody. But it's it's that innovation piece, the ones that you where you want to apply that self service data marketplace to and really drive. As I said before monetization. All right, give us your final thoughts. A. J bring us home. >>So final thoughts on this David is that at the moment we're seeing, um, a lot of value in helping customers discover that day the using automation automatically curating a data catalogue, and that unified view is then being put to work through our A B. I's having an open architecture to plug in whatever tool technology our clients have decided to use, and that open architecture is really feeding into the reality of what see Iose in Chief Data Officers of Managing, which is a hybrid on premise cloud approach. Do you suppose to breed Andi but business users wanting to use a particular technology to get their business outcome having the flexibility to do that no matter where you're dating. Sitting on Premise on Cloud is where self service comes in that self service. You of what data I can plug together, Dr Exchange. Monetizing that data is where we're starting to see some real traction. Um, with customers now accelerating becoming more digital, uh, to serve their own customers, >>we really have seen a cultural mind shift going from sort of complacency. And obviously, cove, it has accelerated this. But the combination of that cultural shift the cloud machine intelligence tools give give me a lot of hope that the promises of big data will ultimately be lived up to ah, in this next next 10 years. So a J ahora thanks so much for coming back on the Cube. You're you're a great guest. And ah, appreciate your insights. >>Appreciate, David. See you next time. >>All right? And keep it right there. Very right back. Right after this short break

>> Narrator: From around the globe, it's "theCUBE" with digital coverage of Smart Data Marketplaces brought to you by Io-Tahoe. >> We're back. We're talking about smart data and have been for several weeks now. Really it's all about injecting intelligence and automation into the data life cycle of the data pipeline. And today we're drilling into Smart Data Marketplaces, really trying to get to that self-serve, unified, trusted, secured, and compliant data models. And this is not trivial. And with me to talk about some of the nuances involved in actually getting there with folks that have experienced doing that. They'd send a series of digital evangelist with Tata Consultancy Services, TCS. And Ajay Vohora is back, he's the CEO of Io-Tahoe. Guys, great to see you, thanks so much for coming on. >> Good to see you, Dave. >> Hey Dave. >> Ajay, let's start with you. Let's set up the sort of smart data concept. What's that all about? What's your perspective? >> Yeah, so I mean, our way of thinking about this is you you've got data, it has latent value, and it's really about discovering what the properties of that data. Does it have value? Can you put that data to work? And the way we go about that with algorithms and machine learning, to generate signals in that data identified patterns, that means we can start to discover how can we apply that data to down stream? What value can we unlock for a customer and business? >> Well, so you've been on this, I mean, really like a laser, why? I mean, why this issue? Did you see a gap in the marketplace in terms of talking to customers and maybe you can help us understand the origin? >> Yeah, I think that the gap has always been there. They've been, it's become more apparent over recent times with big data. So the ability to manually work with volumes of data in petabytes is prohibitively complex and expensive. So you need the different routes, you need different set of tools and methods to do that. Metadata are data that you can understand about data. That's what we at Io-Tahoe focus on, discovering and generating that metadata. That ready, that analogy to automate those data ops processes. So the gap David, is being felt by a business owner prizes and all sectors, healthcare, telecoms, and putting that data to work. >> So Ved, Let's talk a little bit about your role. You work with a lot of customers. I see you as an individual in a company who's really trying to transform what is a very challenging industry. That's sort of ripe for transformation, but maybe you could give us your perspective on this, what kind of signals you're looking for from the data pipeline and we'll get into how you are helping transform healthcare? >> Thanks, David. You know I think this year has been one of those years where we've all realized about this idea of unknown unknowns, where something comes around the corner that you're completely not expecting. And that's really hard to plan for obviously. And I think what we need is the ability to find early signals and be able to act on things as soon as you can. Sometimes, and you know, the COVID-19 scenario of course, is hopefully once in a generation thing, but most businesses struggle with the idea that they may have the data there in their systems, but they still don't know which bit of that is really valuable and what are the signals they should be watching for. And I think the interesting thing here is the ability for us to extract from a massive data, the most critical and important signals. And I think that's where we want to focus on. >> And so, talk a little bit about healthcare in particular and sort of your role there, and maybe at a high level. How Tata and your eco-system are helping transform healthcare? >> So if you look at healthcare, you've got the bit where people need active intervention from a medical professional. And then you've got this larger body of people, typically elderly people who aren't unwell, but they have frailties. They have underlying conditions and they're very vulnerable, especially in the world that we're in now in the post-COVID-19 scenario. And what we were trying to look at is how do we keep people who are elderly, frail and vulnerable? How can we keep them safe in their own homes rather than moving to care homes, where there has been an incredibly high level of infection for things like COVID-19. So the world works better if you can keep people safe in their own homes, if you can see the slide we've got. We're also talking about a world where care is expensive. In most Western countries, especially in Western Europe, the number of elderly people is increasing as a percentage of the population, quite significantly, and resources just are not keeping up. We don't have enough people. We don't have enough funding to look after them effectively. And the care industry that used to do that job has been struggling of late. So it's kind of a perfect storm for the need for technology intervention there. And in that space, what we're saying is the data signal that we want to receive are exactly what as a relative, or a son or daughter you might want from a parent to say, "Everything's okay. "We know that today's been just like every other day "there are no anomalies in your daily living." If you could get the signals that might tell us that something's wrong, something not quite right. We don't need very complex diagnostics. We just need to know something's not quite right, that my dad hasn't woken up as has always at seven o'clock, but till nine o'clock there's no movement. Maybe he's a bit unwell. It's that kind of signal that if we can generate, can make a dramatic difference to how we can look out for these people, whether through professional carers or through family members. So what we're looking to do is to sensor-enable homes of vulnerable people so that those data signals can come through to us in a curated manner, in a way that protects privacy and security of the individual, but gives the right people, which is carers or chosen family members the access to the signals, which is alerts that might tell you there was too much movement at night, or the front door was been left open, things like that that would give you a reason to call him and check. Everybody has spoken to in this always has an example of an uncle or a relative or parent that they've looked after. And all they're looking for is a signal. Even stories like my father's neighbor calls me when he doesn't open his curtain by 11 o'clock, that actually, if you think about it is a data signal that something might be all right. And I think what we're trying to do with technology is create those kinds of data signals because ultimately, the healthcare system works much better if you can prevent rather than cure. So every dollar that you put into prevention saves maybe $3 to $5 downstream. The economic summit also are working our favor. >> And those signals give family members the confidence to act. Ajay, it is interesting to hear what Ved was talking about in terms of the unknowns, because when you think about the early days of the computer industry, there were a lot of knowns, the processes were known. It was like the technology was the big mystery. Now, I feel like it's flipped. We've certainly seen that with COVID. The technology is actually quite well understood and quite mature and reliable. One of the examples is automated data discovery, which is something that you guys have been been focused on at Io-Tahoe. Why is automated data discovery such an important component of a smart data life cycle? >> Yeah. I mean, if we look David at the schematic and this one moves from left to right where right at the outset with that latent data, the value is late because you don't know. Does it have? Can it be applied? Can that data be put to work or not? And the objective really is about driving some form of exchange or monetization of data. If you think about it in insurance or healthcare, you've got lots of different parties, providers, payers, patients, everybody's looking to make some kind of an exchange of information. The difficulty is in all of those organizations, that data sits within its own system. So data discovery, if we drill into the focus itself that, it's about understanding which data has value, classifying that data so that it can be applied and being able to tag it so that it can then be put to use it's the real enabler for that per day drops. >> So maybe talk a little bit more about this. We're trying to get to self-service. It's something that we hear a lot about. You mentioned putting data to work. It seems to me that if the business can have access to that data and serve themselves, that's the way to put data to work. Do you have thoughts on that? >> Yeah, I mean, thinking back in terms of what IT and the IT function in a business could provide, there have been limitations around infrastructure, around scaling, around compute. Now that we're in an economy that is digital driven by API's your infrastructure, your data, your business rules, your intelligence, your models, all of those on the back of an API. So the options become limitless. How you can drive value and exchange that data. What that allows us to do is to be more creative, if we can understand what data has value for what use case. >> Ved, Let's talk a little bit about the US healthcare system. It's a good use case. I was recently at a chief data officer conference and listening to the CDO of Johns Hopkins, talk about the multiple different formats that they had to ingest to create that COVID map. They even had some PDFs, they had different definitions, and that's sort of underscored to me, the state of the US healthcare industry. I'm not as familiar with the UK and Europe generally, but I am familiar with the US healthcare system and the diversity that's there, the duplication of information and the like, maybe you could sort of summarize your perspectives and give us kind of the before and your vision of the after, if you will? >> The use of course, is particularly large and complex system. We all know that. We also know, I think there is some research that suggests that in the US the per-capita spend on healthcare is among the highest in the world. I think it's like 70%, and that compares to what just under 9%, which is going to be European, typical European figure. So it's almost double of that, but the outcomes are still vastly poor. When Ajay and I were talking earlier, I think we believe that there is a concept of a data friction. When you've got multiple players in an eco-system, trying to provide a single service as a patient, you're receiving a single health care service. There are probably a dozen up to 20 different organizations that have to collaborate to make sure you get that top of the line health care service. That kind of investment deserves. And what prevents it from happening very often is what we would call data friction, which is the ability to effectively share data. Something as simple as a healthcare record, which says, "This is Dave, this is Ved, this is Ajay." And when we go to hospital for anything, whatever happens, that healthcare record can capture all the information and tie to us as an individual. And if you go to a different hospital, then that record will follow you. This is how you would expect that to be implemented, but I think we're still on that journey. There are lots and lots of challenges. I've seen anecdotal data around people who suffered because they weren't carrying a card when they went into hospital, because that card has the critical elements of data, but in today's world, should you need to carry a piece of paper or can the entire thing be a digital data flow that can easily be, can certainly navigate through lack of paper and those kinds of things. So the vision that I think we need to be looking at is an effective data exchange or marketplace back with a kind of a backbone model where people agree and sign off a data standard, where each individual's data is always tied to the individual. So if you were to move States, if you would move providers, change insurance companies, none of that would impact your medical history, your data, and the ability to have the other care and medical professionals to access the data at the point of need and at the point of healthcare delivery. So I think that's the vision we're looking at, but as you rightly you said that there are enormous number of challenges, partly because of the history, of healthcare, I think it was technology enablement of healthcare started early. So there's a lot of legacy as well. So we shouldn't trivialize the challenges that the industry faces, but that I think is the way we want to go. >> Well, privacy is obviously a huge one, and a lot of the processes are built around non-digital processes and what you're describing as a flip for digital first. I mean, as a consumer, as a patient, I want an app for that. So I can see my own data. I can see price, price transparency, give access to people that I think need it. And that is a daunting task, isn't it? >> Absolutely. And I think the implicit idea and what you just said, which is very powerful is also on the app you want to control. >> Yes. >> And sometimes you want to be able to change access on data at that point. Right now, I'm at the hospital. I would like to access my data. And when I walk away or maybe three days later, I want to revoke that access. It's that level of control. And absolutely, it is by no means a trivial problem, but I think that's where you need the data automation tools. If you try to do any of this manually, we'd be here for another decade trying to solve this, but that's where tools like Io-Tahoe come in because to do this, a lot of the heavy lifting behind the scenes has to be automated. There has to be a machine churning that and presenting the simpler options. And I know you were talking about it just a little while ago Ajay. I was reminded of the example of a McDonald's or a Coke, because the sales store idea that you can go in and you can do your own ordering off a menu, or you can go in and select five different flavors from a Coke machine and choose your own particular blend of Coke. It's a very trivial example, but I think that's the word we want to get to with access of data as well. If it was that simple for consumers, for enterprise, business people, for doctors, then that's where we ultimately want to be able to arrive. But of course, to make something very simple for the end-user, somebody has to solve for complexity behind the scenes. >> So Ajay, it seems to me Ajay there're two major outcomes here. One is of course, the most important I guess, is patient outcomes, and the other is cost. I mean, they talked about the cost issues, we all, US especially understand the concerns about rising costs of healthcare. My question is this, how does a Smart Data Marketplace fit into achieving those two very important outcomes? >> When we think about how automation is enabling that, where we've got different data formats, the manual tasks are involved, duplication of information. The administrative overhead of that alone and the work, the rework, and the cycles of work that generates. That's really what we're trying to help with data is to eliminate that wasted effort. And with that wasted effort comes time and money to employ people to work through those siloed systems. So getting to the point where there is an exchange in a marketplace just as they would be for banking or insurance is really about automating the classification of data to make it available to a system that can pick it up through an API and to run a machine learning model and to manage a workflow, a process. >> Right, so you mentioned backing insurance, you're right. I mean, we've actually come a long way and just in terms of, know the customer and applying that to know the patient would be very powerful. I'm interested in what you guys are doing together, just in terms of your vision. Are you going to market together, kind of what you're seeing in terms of promoting or enabling this self-service, self-care. Maybe you could talk a little bit about Io-Tahoe and Tata, the intersection at the customer? >> Sure. I think we've been very impressed with the TCS vision of 4.0, how the re-imagining traditional industries, whether it's insurance, banking, healthcare, and bringing together automation, agile processes, robotics, AI, and once those enablers, technology may have brought together to re-imagine how those services can be delivered digitally. All of those are dependent on data. So we see that there's a really good fit here to enable understanding the legacy, the historic situation that has built up over time in an organization, a business and to help shine a light on what's meaningful in that to migrate to the cloud or to drive a digital twin, data science project. >> Ved, anything you can add to that? >> Sure. I mean, we do take the business 4.0 model quite seriously in terms of a lens with which you look at any industry, and what I talked about in healthcare was an example of that. And for us business 4.0, means a few very specific things. The technology that we use in today's verse should be agile, automated, intelligent, and cloud-based. These have become kind of hygiene factors now. On top of that, the businesses we build should be mass customized. They should be risk embracing. They should engage ecosystems, and they should strive for exponential value, not 10% growth year on year, but doubling, tripling every three, four years, because that's the competition that most businesses are facing today. And within that, the Tata group itself, is an extremely purpose-driven business. We really believe that we exist to serve communities, not just one specific set, i.e. shareholders, but the broader community in which we live and work. And I think this framework also allows us to apply that to things like healthcare, to education and to a whole vast range of areas where, everybody has a vision of using data science or doing really clever stuff at the gradients. But what becomes clear is, to do any of that, the first thing you need is a foundational piece. And as a foundation isn't right, then no matter how much you invest in the data science tools you won't get the answers you want. And the work we're doing with the Io-Tahoe really, for me, is particularly exciting because it sorts out that foundational piece. And at the end of it, to make all of this, again, I will repeat that, to make it simple and easy to use for the end user, whoever that is. And I realized that I'm probably the first person who's used fast food as a shining example for healthcare in this discussion, but you can make a lot of different examples. And today, if you press a button and start a car, that's simplicity, but someone has solved for that. And that's what we want to do with data as well. >> Yeah, that makes a lot of sense to me. We talk a lot about digital transformation and a digital business, and I would observe that a digital business puts data at the core. And you can certainly be the best example. There is, of course, Google is an all digital business, but take a company like Amazon, Who's got obviously a massive physical component to its business. Data is at the core. And that's exactly my takeaway from this discussion. Both of you are talking about putting data at the core, simplifying it, making sure that it's compliant, and healthcare it's taking longer, 'cause it's such a high risk industry, but it's clearly happening, COVID I guess, was an accelerant. Guys, Ajay, I'll start with you. Any final thoughts that you want to leave the audience with? _ Yeah, we're really pleased to be working with TCS. We've been able to explore how we're able to put dates to work in a range of different industries. Ved has mentioned healthcare, telecoms, banking and insurance are others. And the same impact they speak to whenever we see the exciting digital transformations that are being planned, being able to accelerate those, unlock the value from data is where we're having a purpose. And it's good that we can help patients in the healthcare sector, consumers in banking realize a better experience through having a more joined up marketplace with their data. >> Ved, you know what excites me about this conversation is that, as a patient or as a consumer, if I'm helping loved ones, I can go to the web and I can search, and I can find a myriad of possibilities. What you're envisioning here is really personalizing that with real time data. And that to me is a game changer. Your final thoughts? >> Thanks, David. I absolutely agree with you that the idea of data centricity and simplicity are absolutely forefront, but I think if we were to design an organization today, you might design it very differently to how most companies today are structured. And maybe Google and Amazon are probably better examples of that because you almost have to think of a business as having a data engine room at its core. A lot of businesses are trying to get to that stage, whereas what we call digital natives, are people who have started life with that premise. So I absolutely agree with you on that, but extending that a little bit. If you think of most industries as eco-systems that have to collaborate, then you've got multiple organizations who will also have to exchange data to achieve some shared outcomes. Whether you look at supply chains of automobile manufacturers or insurance companies or healthcares we've been talking about. So I think that's the next level of change we want to be able to make, which is to be able to do this at scale across organizations at industry level or in population scheme for healthcare. >> Yeah, Thank you for that. Go ahead Ajay. >> David that's where it comes back to again, the origination where we've come from in big data. The volume of data combined with the specificity of individualizing, personalizing a service around an individual amongst that massive data from different providers is where is exciting, that we're able to have an impact. >> Well, and you know Ajay, I'm glad you brought that up because in the early days of big data, there were only a handful of companies, the biggest financial institutions. Obviously, the internet giants who had all these engineers that were able to take advantage of it. But with companies like Io-Tahoe and others, and the investments that the industry has made in terms of providing the tools and simplifying that, especially with machine intelligence and AI and machine learning, these are becoming embedded into the tooling so that everybody can have access to them, small, medium, and large companies. That's really, to me, the exciting part of this new era that we're entering. >> Yeah, and we have placed those, take it down to the level of not-for-profits and smaller businesses that want to innovate and leapfrog into, to growing their digital delivery of their service. >> And I know a lot of time, but Ved, what you were saying about TCS's responsibility to society, I think is really, really important. Large companies like yours, I believe, and you clearly do as well, have a responsibility to society more than just a profit. And I think, Big Tech it's a better app in a lot of cases, but so thank you for that and thank you gentlemen for this great discussion. I really appreciate it. >> Thanks David. >> Thank you. >> All right, keep it right there. I'll be right back right after this short break. This is Dave Vellante for theCUBE. (calm music)

you live from Las Vegas it's the cube covering you I pat forward America's 2019 brought to you by uipath welcome back everyone to the cubes live coverage of UI path forward here at the Bellagio in Las Vegas Nevada I'm your host Rebecca night co-hosting alongside Dave Volante we are joined by Gavin Jackson he is the senior vice president and managing director amia at uipath thanks so much for coming you are brand spanking new to brands thanking you AWS for four years yeah joined UI paths in September yeah I want to start this conversation by having you talk a little bit about what what appealed to you about UI path and what more do you want to make the leap after four years at AWS yeah so I had the privilege to be west of really having a really close proximity to enterprise customers and getting the opportunity to listen to what they really wanted when they were talking about their digital transformation journeys and as it turns out the sort of cloud first in the automation first eras if you will are operating models at to two sides of the same coin if you think about what the that the cloud proposition has been over the last number of years it's really been about sort of reducing or eliminating the undifferentiated heavy lifting so that builders can build and then that turned into an operating model principle and it became sort of cloud first it's the same thing for the automation world you know we are reducing and eliminating the undifferentiated heavy lifting of Tata a product of business processes and tasks and everything else whether they're complex tasks or simple tasks removing that so that builders can build and business people can innovate and given them the freedom to do what they need to do as business owners think about AWS we obviously follow them very closely yeah anybody but it strikes you didn't thank you such are filters yeah what's the analog so what I think we again I would say that we are we are providing tools so the builders could build but at the same time our our products that works across the entire business stack whether that is sort of automation first as an operating principle across all businesses or whether it's across a business persona whether it's a CFO or somebody in accounts or a salesperson or whatever might be we're building tools that take the mundane tasks away from those users so that they have the freedom to go and serve their customers or or innovate within finance or do the do the job that they really love doing and that's really important for the business it turns out there's not a lot of value and a lot of the work that people do every day so if we can remove some of that then innovation will have an exponential curve of progress and that's what we're focused on today yes yeah again there are similarities there so if I understand the you're shifting one date asked allowing people freeing them up to do so that they can have a strategic impact in their business yes yeah yeah I think it is so if you look at even the technology paradigms and how cloud and AWS evolved and then also the layer on how uipath is evolving in the same way so you have computing and compute power started really with the mainframe and went to distributed servers and then to virtual machines and then from virtual machines it went to hosted virtual machines in the cloud and then from then it went to containers and now we're in this world of server lists we're in the cloud right so effectively the logic lives in server lists and the infrastructure sort of disappears and that provides massive scale in the automation world you started off with big monolithic processes you then had sort of network processes with software and data in the middle of all of that networked RPA really came in as an early sort of tool to help automate a lot of that a lot of processes and now in the realms of sort of automation as a function where in the end like the end game really is where automation is the application and the the applications themselves the data sources the processes really disappear so that the best done analogy I can come up with a metaphor acting um up with is I'm a Marvel fan I'm a geeky kind of Marvel fan of my favorite character is his Iron Man or Tony Stark and more specifically the Jarvis AI so what's happening all the time with with Tony Stark in the Jarvis a is he's interacting with his AI user interface all the time and what's happening in the background is that Java she's working with probably you know a hundred different applications and a hundred different data sources and everything else and rather than having you know a human go and do what the integration work that robots are doing that for him and it's just coming back as a as an outcome yeah I'm gonna keep pushing on this yeah similarities and differences because where it seems to break down is where our PA is focusing on the citizen developer the the end-user I'm afraid of AWS I won't go near it I see that console I call it my techies hey you know AWS is you know you got to be you know pretty technical to actually leverage it at the same time I'm thinking well maybe not maybe my builders are building things that I can touch but help us square that circle yeah so I think you the world is trending towards as much automation as possible so if it can be automated or if you can reduce the the burden to get to innovation I think you know technology is moving that way even in coding I think the transit we're seeing whether it's AWS or anyone else is low to no code and so we we occupy a world within the RPA space or the intelligent automation space where we're providing tools for people that don't need a requirement or or a skill set to code and they can still manufacture a few world their own automations and particularly with a release that we're just announcing today which is Studio X it really kind of reduces the friction from a business user where's zero understanding of how to code to build their own automations whether it's kind of recording a process or just dragging and dropping different components into a process even like even I could do that and that's saying something I can tell you yes exactly yeah this idea of democratizing the the automation the building that you said yeah very much so what will this mean I mean what what does what does that bode for the future of how work gets done because that is at the core of what you're doing is typically understanding how and where work gets done or the bottlenecks where the challenges and how can our PA fix this so I think ultimately like a lot of technologies it's really about the the exponential curve of productivity and whether you're looking at a national level a global level a company level a human level every level productivity has declined really over the last number of years and technology hasn't done a great job to improve that and you can say that some technologies have done a good job again I'd use a TBS is a good job in terms of the proliferation or the how prolific you can get more code out and more more progress there but overall productivity has declined so our sort of view of the world is if you can democratize automation if you can use or add a digital workforce to your to your to your teams then you'll have an exponential curve of productivity which a human level is important company level is important a national level is important and probably at global level is important you know you guys might be right place right time as well yeah because I remember you know all the spending in the 80s said receive growth everywhere except the Nobel prize-winning economist Robert Solow yeah [Laughter] [Music] you guys are hitting it right at the right time yeah you be able to take credit for a lot of it but yeah your thoughts on that in terms of productivity depending yeah I think it is pent up I think that is where where we're at right now and it's ready to be unleashed and I think that these technologies are are the technologies that will unleash it I think really what's happened over the last number of decades probably is that the six trillion dollar IT industry they exist today has largely kind of increased productivity or performance of other technologies it hasn't really increased output so whether it's sort of you know the core networking when Cisco started core networking there was a big increase I would imagine in connectivity and outputs then the technologies that were laid on top of that maybe less so and it was just really kind of putting bad band-aids on problems so it was really technology solving technology problems rather than technology solving human output problems and so I think that this is now the most tangible technology category that really is turning technology into value and productivity for technology really unlocking a lot of value one of the things that your former boss Jeff Bezos said was bet on dreamy businesses that have unlimited upside these these dreamy businesses customers love them they grow to very large sizes they have strong returns on capital and they can endure for decades I wonder if you could put you iPad in that context of a dreamy business what does he know right I mean nobody right I mean so and this is one of the reasons I was attracted by the way to DUI path because I think I think that the robots themselves if you can just kind of look at the subcategory of the robot I think it's on a similar curve to how Gordon Moore was talking about the Intel microprocessor in 1965 and the exponential curve of progress I think we were on that similar curve so when I sort of project five years from now I just think that the amount the robots will be able to do the cognitive kind of capabilities it will be able to do are just phenomenal so and customers customers give us feedback all the time about to two things they love and they value what we do the value is important because it's very empirical for the first time they can actually deploy a technology and see almost an immediate return on their technology whether it's a point technology solving one process or a group of processes they can see an immediate empirical return the other thing that I like to measure I quite like is that they value it so they think they love it they love and value it so they love it meaning it actually induces an emotion so when you when you watch the robots in action and they watch something that has been holding your team back or there's been stifling productivity or whatever it is people get giddy about it it's quite fascinating to see comment about Gordon Moore and Ty that's a digital transformation when I think of digital transformation I think of data yeah what's the difference in a business in a digital business it's how they use data yeah they put data at the core and four years we march to the cadence of Moore's law and that's changed its that that's not what the innovation the engine is today it's it's machine intelligence it's data and it's cloud for scale where do you guys fit I mean obviously AI is a piece of that but but maybe you could add some color to where our PA fits in that equation so I think that's an important point because there's a lot of miscommunication I think about really what it means when you talk about digital transformation and what it means to be digitally transformed and really to see transformed you're really talking about a category of customers which are large more institutional enterprises and governments because they have something to transform what they're transforming into is more of a digital native sort of set of attributes more insurgent mindsets and these companies are to your point they're very data hungry they harvest as much data as they can from from value from data they're very customer centric they focus on the customer experience they use other people's resources oh the cloud being one great example of that and the missing point from what you said is they automate everything they've to meet it so part of the digital transformation journey is if it can be automated it will be automated and anything that's new will be born automated so let me ask a follow-up on that is there a cultural difference in amia versus what you're seeing in North America in terms of the receptivity to automation I mean there are certain parts of of Europe which are you know more protective of jobs do you see a cultural difference or are they kind of I mean we do see even some resistance here but when you talk to customers they're like no it's it's wonderful I love it what are you seeing in Europe so I don't I don't see much of a cultural difference there and I see don't I don't see yet I haven't seen any feedback yes Peres I'm very new still but I haven't seen anybody talk about really that this technology is a technology to take jobs out I think most people see this technology as a way of getting better performance out of humans you know pivoting them towards more so I would say like in some markets in my in my in my prior life in in many prior lives I would say that there's some countries like France for example that would have been a little bit more stayed within their approach to new technologies and adoption not so with regards to automation they see this as a real and game productivity increase thank you I think that's true for people who have tasted it yeah but I do think there's still some reticence in the ranks until they actually experience it that's why we'll talk to some customers about it they'll have bought a Thon's and just a yeah to educate people and what's possible to let them try to build their own robots and then people then the light bulbs go off that it's taking away the aggravations the frustrations the mundi the drudgery and then you said people get giddy about those things you don't have to do that yeah but then the question is also so so what creative things are you doing now so how are you spending your time what are you doing differently that makes your job more interesting more compelling yeah and and and I think that's the real question - so what is the okay yes receiving some money and people aren't having to do those mundane tasks but then what are what is the value add that the employees are now bringing to the table yeah so in actually sit and it takes made the right point as well in terms of the mechanism for doing that is the the part of the battle here is to spark the imagination just like anything really just let you like it back in the Amazon wild it's all of our spark in the imagination if you can if you can imagine it you can build it it's the same thing really with within our world now is figuring out with customers what think what tasks do they do that they hate doing either a user level or a downstream level what are the things that they really want to do that they need our help to harvest and so we do the same sort the same sort of things that we would have done with AWS where we did lots of hackathons and you bought lots of technology partners in with us and we would sort of building all of this we do exactly the same thing with the RP a space it's exactly the same this is really important because creativity is going to become an increasingly important because if productivity goes up it means you can do the same amount of work with less people so it is going to impact jobs and people are gonna have to be comfortable to get out of their comfort zone and become creative and find ways to apply these technologies to really advance but you know drive value to their organizations and actually I look at this as well as a long term technology whereas a long term technology is something that's important for my children I've three and they're still very young so twelve ten and six but eventually they will go into the workplace with these skills embedded they will just know the how you get work done is you have your robot do a whole load of tasks for you here and your your job is to build and to be creative and to harvest data and to manipulate data and and serve customers and focus on the customer experience that's really what it's all about the real brain works I've been a pleasure having you on the show at uipath thank you so much appreciate it i'm rebecca night for j4 day Volante please stay tuned for more from the cubes live coverage of uipath coming up in just a little bit

>> Announcer: Live from Boston, Massachusetts, it's theCUBE. Covering IFS World Conference 2019. Brought to you by IFS. >> Welcome back to Boston everybody, you're watching theCUBE, the leader in live tech coverage. My name is Dave Vellante, I'm here with my co-host Paul Gillin. This is IFS World Conference 2019, theCUBE's second year covering this conference. Michael Ouissi is here. He's the Chief Customer Officer at IFS. And Raul Sahas. Industry Partner, Enterprise Application Services at TCS, a platinum partner at IFS World. Gents, welcome to theCUBE. >> Thank you. >> Thank you for having us. >> You're very welcome. So last night I poked around the customer event and I was impressed with the number of partners here. I think the number is 400, is the public number. What is it about the ecosystem that's attracted to IFS? >> Well, first of all, I think the ecosystem has now understood that we have renewed our commitment to the ecosystem. That is something a shift in mindset in IFS that is demanded by our customers, that our customers actually ask of us especially while we're moving into also more global corporations, and win more business there. They appreciate the choice of either IFS or our partners, or a combination of our partners and IFS actually helping them deliver the value that they expect from an ERP solution. >> So Rahul, from your perspective, so TCS you're obviously platinum partner so you're making a big investment. Why, what's happening in the market place? Where's the momentum with the tailwind? >> If you look at TCS, TCS is obviously helping customers to become business 4.0 organization, which is all about harnessing the abundance of possibilities around digital technologies and getting more intelligent, better, lean, harmonized, standardized. And so that's where we believe we are partnering with, and we are trying to leverage the ecosystem and one of the ecosystem obviously partners are IFS, which is a strategy partnership for us. And we believe that the investments that IFS has made and some of the unique last-mile solutions are going to help us to deliver those different shaded offerings to the customer, and create newer partnerships with them. >> Michael your role is a net new role at IFS, did you get to write your own job description? I guess, what does a Chief Customer Officer do? >> Well, first of all, well, in a sense yes. We actually did specify exactly what that role is, and we did discuss what the best is for the journey we want to get on, when Darren asked me to take on the role. And what a Chief Customer Officer does, and there's a specific reason why we're doing it that way, a Chief Customer Officer really is heading up, and that's what I'm doing, is I'm heading up all customer-facing functions within IFS. So from sales, to pre-sales, to support, to services. So it's all the customer-facing functions, coming from how do we engage with a customer, pre-sales, and after sales. And the reason why we did it that way is we wanted to have complete ownership and accountability for the transformation that we underwent and that we wanted to go through because we really needed to make sure that all parts of the business were aligning around this transformation, and pulling in the same direction. And that's why this role got created newly. >> So what's the nature of the partnership, what the history of the partnership? How did it start, and where do you guys want to take it? >> Well I think we have a obviously longstanding partnership with IFS. And I think both of the organizations have a deep mutual respect. And I think that one thing that we are trying to see the centricity around our partnership is all about the customer. We keep the customer and we want to ensure that we help our customers. We're customer-first organizations. And obviously the investments that IFS made, especially in the field services area, ERP area. I guess those are the areas which is helping, because ERP, if you see, one of the strategic lever for an organization to elevate their digital agenda, and get the right infrastructure in place, the right partner in place, to ensure that they create a differentiation and create exponential value for the customer. And that's exactly where IFS and TCS are looking at the market, and ensuring that we are helping our customer create exponential value for themselves in the market. >> Michael: Yeah and I think that maybe adding to that, we share the same belief as well that actually the time of the monolithic ERP, one solution for a huge enterprise- >> Who are you talking about? (Laughter) >> They are gone, those days are gone. I think it's about blended solutions where the ERP is much more agile, it has to be much more open and allow for much more agile deployments and much more agile development around the core ERP. So that actually customers can digitally transform, because it's all about speed. And TCS sees it the same way so we've got the same view. >> But the cloud mindset has changed that right Paul? >> Absolutely. And Rahul I'm interested the companies like Tata historically have done a lot of custom development work for customers that we have been hearing from Darren on down today is no customization. What value do you add to a customer bringing in an IFS solution? >> See there are two things here, very simple. One is basically customers are moving from best in class to the sub-breed, that's quite evident. And secondly, while IFS brings the software expertise, we bring the industry expertise. We bring the domain expertise. We bring the SI, system integration expertise. And that's where, it's a very strategic combination. Strategic combination is helping the customer to get the right software, the right domain expertise, the right industry expertise. And together they're helping them to address their business requirements, business need, and last mile critical mile needs that they need to differentiate themselves in the marketplace. And, as a result, create exponential value, and also, a great customer experience for the customers. >> Paul: So, how does that engage and differ from a more traditional one where you would come in and you would build custom screens and custom processes? You're not doing that. Now, what does that relationship look like? >> Yeah so I think if you see the scratch approach, obviously it has really transformed over the course of time. Customers are wanting off the shelf, out of the box products. Best of the beat products to help them differentiate their business function, create exponential value for the customer for that business function as a matter of say, service. If I look at fin services as an example, and you talk about telcos, you talk about utilities. Where last mile delivery, last mile solution for that customer is very very important to create the positive customer experience. And the investments that IFS have made in there makes them a premium choice. And that's where I believe that developing something with scratch means you know you're boarding the entire ocean again. And whereas we have got softwares like, IFS build softwares which have invested their years of expertise, the years of, I would say, competency in building that. Getting the best of the breed solution, get the best KPIs into there in this solution, gives the customer a choice. A ready choice to take, to expedite their time to reality, time to value, and time to production reality. >> So, a few times now, Raoul, you've mentioned last mile solutions. I like that term, I think it has meaning. Especially deep in specific industries. And I think the intent is so that you don't have to do customizations. And I asked Aaron about tailoring, which he said, I wouldn't use that word. That wasn't my word, by the way, that was Christian's word. He used that in his keynote. So I'm trying to understand here. I think what Christian meant is look, we got this API platform to allow people to bring in whatever solutions they want, if it's a RPA solution, or a blockchain solution, or some AI module, they can bring that in and tailor it for their needs, as opposed to customizing the software. Is that correct? >> I think when you listen to Darren, what he's talking about is customizing the core, which very often has happened in the past, where customizations have gone into the core, have been mandated to be on the core platform, which then actually has customers being stuck at some stage on the platform upgrades becoming paid for. So with Christian's talk track around the APIs, API enabling the whole solution so that the core actually remains untouched. There will always be customizations, because customers need to differentiate. But they will be outside the core. There will be a level that you can upgrade the core solutions, you will have those maintained either application services, which will be custom out of the box solutions, best in breed, that actually tap into what we're doing. Or actually you'll have bespoke solutions that you will write yourself, and that is then a choice a customer can make, but without actually having the pain of not being able to upgrade the very stable, very performant transactional backbone. >> So the API announcements give you guys a real opportunity to do integrations, right? And it's been harder to do integrations. But that now, to your previous question, opens up I would think a whole new tam for you all. Can you comment? >> Oh absolutely. As I said, bringing exponential value means integrating and delivering a frictionless business. And that's where it'll fit in, rightly fit in, and obviously that would result in creating exponential value for the customer. Not only they can differentiate themselves from the market but also get their product faster to the market, and ensure that also focus on custom centers as we are. >> So the core can be, it should be, Evergreen. We want people to get the new version as soon as possible. Bug fixes, security updates, et cetera. >> New functionality. >> New functionality, avoid custom mods, but rely on service providers and partners to do further integrations that make sense. >> Rahul, I want to ask you the same question we just asked Melissa Di Donato about digital transformation. I'm sure your company does a lot of that kind of consulting work. What are the mistakes that companies make that we hear that these transformation products, most of them fail. What are the biggest mistakes that companies make? >> Let me put it this way. I think there are three elements to it. I think digital transformation, see I think creating the agenda for the digital transformation, what you're expecting out of it is very very important. Creating a charter, what you want to expect, what is the output of it. Where do you want to take it. What does a futuristic organization on a digital platform means? It's very very important. I think if you look at TCS, our vision has been helping the customer get into a business 4.0 enterprise. I think we have made the agenda very very very clear. Now how we can mass personalize the experience for the customer, how you can leverage the ecosystem, how you can basically help the customer embrace the risk, and obviously harness the abundance. I believe these are the pillars of any transformation, or digital transformation, that customers are taking. I believe if we can stick to these agendas, I think getting to the production reality, seeing the success has become more evident. If you're going to go to the nitty gritty, I think there are many things, looking at the processes, making sure that they are harmonized, standardized and rationalized, getting the right KPIs in the business. So I think these are things that is very very important as a precursor to our digital transformation. Once we do that, we know that roads ahead will be much smoother than what it looks like. >> Is it more important to do a transformation with the customer at the center, with operational efficiency at the center, or can it be either? >> The customer centricity is very very key to all our organization at this point of time, because if you look at any organization at this point of time, they're looking at the customer experience as the top most agenda. Keeping the customer experience on the agenda, when you're trying to keep that agenda, it means that you are trying to bring up a customer first organization. So customer first organization, it just doesn't mean that you have a very intelligent front office, but also have a very intelligent back office. And gluing this two together, very intelligent mid office. So I guess customer centricity has to be on the top of the agenda, and then you have to ensure that your processes are streamlined, harmonized, standardized, lean, to meet that objective. >> Makes sense. >> So I think, for customer centricity, so I feel as though, but part of that's cultural, you know? And it's true, you said this earlier this morning. Some companies are customer centrics, some are product centric, some are competitive. And you can kind of tell the difference, especially when you're a customer. But I think true customer centricity mandates data access as central to the philosophy, the core. And I think the role that ERP provider or vendor provides is you have a data pipeline that gives access to an organization such that a digital transformation allows them to put data at their core, and then build whatever processes around it. I think that's a real challenge for incumbents especially where data's all over the place, in different stove pipes and silos. But your thoughts on the role of data in terms of digital transformation, and IFS's role in that regard? >> Okay. >> A long-winded question, but I haven't heard enough about data I guess. >> Okay, (laughs) I'll try it, sweet and short. I think data is absolutely key to anything we do. Once you have and when you go into a digital transformation, what you need to start with in my humble view is you need to start with what business outcome do you want to achieve? Most of the time it's customer centricity, it's something centered around the customer which you want to achieve. That will define both the digital transformation agenda, the KPI's you're measuring to, but also the flow of data and processes. So you will need to build your digital transformation agenda around the targets you have, and then define where does data need to reside, which data do I need to fulfill on that outcome? And I think that consistency going through that whole chain is actually something that very often isn't at the moment taken into account, but it's very often isolated efforts to do something fast without actually looking at the implications of what kind of transactional engine do I need, what kind of data exits do I need, and how do I get through the process to the KPI that I want to influence? >> Okay, and let me peel the onion on that, and I'd love for your thoughts. To me when you talk to a C-suite executive, what that business outcome ultimately comes down to is I want to increase revenue, so I want to cut my cost. Now of course if you're in a different hospital, you want to save lives. But generally in a commercial business, increase revenue, cut cost. Now how I get there, I might want to have a better customer service organization to get cohort sales or follow on sales. I mean the strategy is different. But it comes back to data and how data affects the monetization of my organization, whether it's increasing revenue or cutting cost. Do you buy that premise, or am I just simplifying it too much? >> No, completely agreed. I think in a business world it's always either top line or bottom line, but the challenges are obviously very different from company to company and from industry to industry. So if you're looking at manufacturing companies, trying to actually be less commoditized and getting into a situation where they stabilize revenue streams, increase margins, servitization is the name of the game. Very different value proposition to, for example in the finance industry, in banking and insurance. So there are very different models here where there it's about ease of use and speed of actually interacting and transacting as a customer with the company. So very different value propositions, very different data streams you need to tap into. And things you need to know about your customer, and know about the service you're providing. So completely agree with it is always about revenue and cost, that's what businesses are in for. But eventually, data is at the core, but how to get that data, which data you need, that is then specific to each. >> And bringing it back to IFS, your ability to go that last mile as you've been saying Rahul allows companies to think, construction and engineering, supply chain, contractors, just more efficiently managing their ecosystem, their resources to either cut costs or do more business and scale. >> Exactly. And that's really where the whole idea of API, enabling the whole suite came from, enabling the reuse of services, the reuse of data within those services, exposing it transparently, making it available for customers to then use in their digital transformation effort. Whatever they need. We can't predict and we can't actually preempt what a customer will need, we'll just need to make it all available, and then with partners like TCS, make sure we actually go on to the right journey with a customer to digitally transform and use the right data streams. We can make it easy and accessible. >> And that's the different between a platform and a product. To the extent that you can deliver an API-enabled system, it becomes a platform that you can evolve versus a product that you install and manage. Final thoughts, Rahul? >> I think what we discussed obviously, I fully agree on that. And as I mentioned that our take is to ensure that we have the customer built future systems enterprises, and we believe our partnership with IFS is a very key and strategic partnership for us to achieve the same, and we have some early success, and we want to ensure that we scale that, we ensure we go to the market together, and create a differentiation for our customers. >> Michael, your thoughts. Where do you want to see this ecosystem go? >> Where do I want to see it go? Well I want to see it thrive. I want partners to be successful with their customers on IFS implementations. That's what our ambition is. We need to provide world class technology, a world class platform, as you said, that actually then can be used to help the digital transformation that all our customers will have to go through in one or the other way. >> Success is outcome driven. Good outcomes mean people come back, more business? >> Absolutely, absolutely. >> Exactly. >> That's core to our DNA, I'm sure core to DNA to IFS as well. Repeat customers. >> Congratulations on the partnerships, and good luck going forward. >> Thank you very much. >> Appreciate you coming on theCUBE, you're welcome. >> Thank you very much. >> Thank you. >> All right thank you for watching everybody, we'll be right back with our next guest, Paul Gillan and Dave Vellante. You're watching theCUBE. (electronic jingle)

>> From Cambridge, Massachusetts, it's theCUBE covering MIT Chief Data Officer and Information Quality Symposium 2019 brought to you by SiliconANGLE Media. (upbeat techno music) >> Hi everybody, welcome back to Cambridge, Massachusetts. You're watching theCUBE, the leader in tech coverage. We go out to the events. We extract the signal from the noise, and we're here at the MIT CDOIQ Conference, Chief Data Officer Information Quality Conference. It is the 13th year here at the Tang building. We've outgrown this building and have to move next year. It's fire marshal full. Gokula Mishra is here. He is the Senior Director of Global Data and Analytics and Supply Chain-- >> Formerly. Former, former Senior Director. >> Former! I'm sorry. It's former Senior Director of Global Data Analytics and Supply Chain at McDonald's. Oh, I didn't know that. I apologize my friend. Well, welcome back to theCUBE. We met when you were at Oracle doing data. So you've left that, you're on to your next big thing. >> Yes, thinking through it. >> Fantastic, now let's start with your career. You've had, so you just recently left McDonald's. I met you when you were at Oracle, so you cut over to the dark side for a while, and then before that, I mean, you've been a practitioner all your life, so take us through sort of your background. >> Yeah, I mean my beginning was really with a company called Tata Burroughs. Those days we did not have a lot of work getting done in India. We used to send people to U.S. so I was one of the pioneers of the whole industry, coming here and working on very interesting projects. But I was lucky to be working on mostly data analytics related work, joined a great company called CS Associates. I did my Master's at Northwestern. In fact, my thesis was intelligent databases. So, building AI into the databases and from there on I have been with Booz Allen, Oracle, HP, TransUnion, I also run my own company, and Sierra Atlantic, which is part of Hitachi, and McDonald's. >> Awesome, so let's talk about use of data. It's evolved dramatically as we know. One of the themes in this conference over the years has been sort of, I said yesterday, the Chief Data Officer role emerged from the ashes of sort of governance, kind of back office information quality compliance, and then ascended with the tailwind of the Big Data meme, and it's kind of come full circle. People are realizing actually to get value out of data, you have to have information quality. So those two worlds have collided together, and you've also seen the ascendancy of the Chief Digital Officer who has really taken a front and center role in some of the more strategic and revenue generating initiatives, and in some ways the Chief Data Officer has been a supporting role to that, providing the quality, providing the compliance, the governance, and the data modeling and analytics, and a component of it. First of all, is that a fair assessment? How do you see the way in which the use of data has evolved over the last 10 years? >> So to me, primarily, the use of data was, in my mind, mostly around financial reporting. So, anything that companies needed to run their company, any metrics they needed, any data they needed. So, if you look at all the reporting that used to happen it's primarily around metrics that are financials, whether it's around finances around operations, finances around marketing effort, finances around reporting if it's a public company reporting to the market. That's where the focus was, and so therefore a lot of the data that was not needed for financial reporting was what we call nowadays dark data. This is data we collect but don't do anything with it. Then, as the capability of the computing, and the storage, and new technologies, and new techniques evolve, and are able to handle more variety and more volume of data, then people quickly realize how much potential they have in the other data outside of the financial reporting data that they can utilize too. So, some of the pioneers leverage that and actually improved a lot in their efficiency of operations, came out with innovation. You know, GE comes to mind as one of the companies that actually leverage data early on, and number of other companies. Obviously, you look at today data has been, it's defining some of the multi-billion dollar company and all they have is data. >> Well, Facebook, Google, Amazon, Microsoft. >> Exactly. >> Apple, I mean Apple obviously makes stuff, but those other companies, they're data companies. I mean largely, and those five companies have the highest market value on the U.S. stock exchange. They've surpassed all the other big leaders, even Berkshire Hathaway. >> So now, what is happening is because the market changes, the forces that are changing the behavior of our consumers and customers, which I talked about which is everyone now is digitally engaging with each other. What that does is all the experiences now are being captured digitally, all the services are being captured digitally, all the products are creating a lot of digital exhaust of data and so now companies have to pay attention to engage with their customers and partners digitally. Therefore, they have to make sure that they're leveraging data and analytics in doing so. The other thing that has changed is the time to decision to the time to act on the data inside that you get is shrinking, and shrinking, and shrinking, so a lot more decision-making is now going real time. Therefore, you have a situation now, you have the capability, you have the technology, you have the data now, you have to make sure that you convert that in what I call programmatic kind of data decision-making. Obviously, there are people involved in more strategic decision-making. So, that's more manual, but at the operational level, it's going more programmatic decision-making. >> Okay, I want to talk, By the way, I've seen a stat, I don't know if you can confirm this, that 80% of the data that's out there today is dark data or it's data that's behind a firewall or not searchable, not open to Google's crawlers. So, there's a lot of value there-- >> So, I would say that percent is declining over time as companies have realized the value of data. So, more and more companies are removing the silos, bringing those dark data out. I think the key to that is companies being able to value their data, and as soon as they are able to value their data, they are able to leverage a lot of the data. I still believe there's a large percent still not used or accessed in companies. >> Well, and of course you talked a lot about data monetization. Doug Laney, who's an expert in that topic, we had Doug on a couple years ago when he, just after, he wrote Infonomics. He was on yesterday. He's got a very detailed prescription as to, he makes strong cases as to why data should be valued like an asset. I don't think anybody really disagrees with that, but then he gave kind of a how-to-do-it, which will, somewhat, make your eyes bleed, but it was really well thought out, as you know. But you talked a lot about data monetization, you talked about a number of ways in which data can contribute to monetization. Revenue, cost reduction, efficiency, risk, and innovation. Revenue and cost is obvious. I mean, that's where the starting point is. Efficiency is interesting. I look at efficiency as kind of a doing more with less but it's sort of a cost reduction, but explain why it's not in the cost bucket, it's different. >> So, it is first starts with doing what we do today cheaper, better, faster, and doing more comes after that because if you don't understand, and data is the way to understand how your current processes work, you will not take the first step. So, to take the first step is to understand how can I do this process faster, and then you focus on cheaper, and then you focus on better. Of course, faster is because of some of the market forces and customer behavior that's driving you to do that process faster. >> Okay, and then the other one was risk reduction. I think that makes a lot of sense here. Actually, let me go back. So, one of the key pieces of it, of efficiency is time to value. So, if you can compress the time, or accelerate the time and you get the value that means more cash in house faster, whether it's cost reduction or-- >> And the other aspect you look at is, can you automate more of the processes, and in that way it can be faster. >> And that hits the income statement as well because you're reducing headcount cost of your, maybe not reducing headcount cost, but you're getting more out of different, out ahead you're reallocating them to more strategic initiatives. Everybody says that but the reality is you hire less people because you just automated. And then, risk reduction, so the degree to which you can lower your expected loss. That's just instead thinking in insurance terms, that's tangible value so certainly to large corporations, but even midsize and small corporations. Innovation, I thought was a good one, but maybe you could use an example of, give us an example of how in your career you've seen data contribute to innovation. >> So, I'll give an example of oil and gas industry. If you look at speed of innovation in the oil and gas industry, they were all paper-based. I don't know how much you know about drilling. A lot of the assets that goes into figuring out where to drill, how to drill, and actually drilling and then taking the oil or gas out, and of course selling it to make money. All of those processes were paper based. So, if you can imagine trying to optimize a paper-based innovation, it's very hard. Not only that, it's very, very by itself because it's on paper, it's in someone's drawer or file. So, it's siloed by design and so one thing that the industry has gone through, they recognize that they have to optimize the processes to be better, to innovate, to find, for example, shale gas was a result output of digitizing the processes because otherwise you can't drill faster, cheaper, better to leverage the shale gas drilling that they did. So, the industry went through actually digitizing a lot of the paper assets. So, they went from not having data to knowingly creating the data that they can use to optimize the process and then in the process they're innovating new ways to drill the oil well cheaper, better, faster. >> In the early days of oil exploration in the U.S. go back to the Osage Indian tribe in northern Oklahoma, and they brilliantly, when they got shuttled around, they pushed him out of Kansas and they negotiated with the U.S. government that they maintain the mineral rights and so they became very, very wealthy. In fact, at one point they were the wealthiest per capita individuals in the entire world, and they used to hold auctions for various drilling rights. So, it was all gut feel, all the oil barons would train in, and they would have an auction, and it was, again, it was gut feel as to which areas were the best, and then of course they evolved, you remember it used to be you drill a little hole, no oil, drill a hole, no oil, drill a hole. >> You know how much that cost? >> Yeah, the expense is enormous right? >> It can vary from 10 to 20 million dollars. >> Just a giant expense. So, now today fast-forward to this century, and you're seeing much more sophisticated-- >> Yeah, I can give you another example in pharmaceutical. They develop new drugs, it's a long process. So, one of the initial process is to figure out what molecules this would be exploring in the next step, and you could have thousand different combination of molecules that could treat a particular condition, and now they with digitization and data analytics, they're able to do this in a virtual world, kind of creating a virtual lab where they can test out thousands of molecules. And then, once they can bring it down to a fewer, then the physical aspect of that starts. Think about innovation really shrinking their processes. >> All right, well I want to say this about clouds. You made the statement in your keynote that how many people out there think cloud is cheaper, or maybe you even said cheap, but cheaper I inferred cheaper than an on-prem, and so it was a loaded question so nobody put their hand up they're afraid, but I put my hand up because we don't have any IT. We used to have IT. It was a nightmare. So, for us it's better but in your experience, I think I'm inferring correctly that you had meant cheaper than on-prem, and certainly we talked to many practitioners who have large systems that when they lift and shift to the cloud, they don't change their operating model, they don't really change anything, they get a bill at the end of the month, and they go "What did this really do for us?" And I think that's what you mean-- >> So what I mean, let me make it clear, is that there are certain use cases that cloud is and, as you saw, that people did raise their hand saying "Yeah, I have use cases where cloud is cheaper." I think you need to look at the whole thing. Cost is one aspect. The flexibility and agility of being able to do things is another aspect. For example, if you have a situation where your stakeholder want to do something for three weeks, and they need five times the computing power, and the data that they are buying from outside to do that experiment. Now, imagine doing that in a physical war. It's going to take a long time just to procure and get the physical boxes, and then you'll be able to do it. In cloud, you can enable that, you can get GPUs depending on what problem we are trying to solve. That's another benefit. You can get the fit for purpose computing environment to that and so there are a lot of flexibility, agility all of that. It's a new way of managing it so people need to pay attention to the cost because it will add to the cost. The other thing I will point out is that if you go to the public cloud, because they make it cheaper, because they have hundreds and thousands of this canned CPU. This much computing power, this much memory, this much disk, this much connectivity, and they build thousands of them, and that's why it's cheaper. Well, if your need is something that's very unique and they don't have it, that's when it becomes a problem. Either you need more of those and the cost will be higher. So, now we are getting to the IOT war. The volume of data is growing so much, and the type of processing that you need to do is becoming more real-time, and you can't just move all this bulk of data, and then bring it back, and move the data back and forth. You need a special type of computing, which is at the, what Amazon calls it, adds computing. And the industry is kind of trying to design it. So, that is an example of hybrid computing evolving out of a cloud or out of the necessity that you need special purpose computing environment to deal with new situations, and all of it can't be in the cloud. >> I mean, I would argue, well I guess Microsoft with Azure Stack was kind of the first, although not really. Now, they're there but I would say Oracle, your former company, was the first one to say "Okay, we're going to put the exact same infrastructure on prem as we have in the public cloud." Oracle, I would say, was the first to truly do that-- >> They were doing hybrid computing. >> You now see Amazon with outposts has done the same, Google kind of has similar approach as Azure, and so it's clear that hybrid is here to stay, at least for some period of time. I think the cloud guys probably believe that ultimately it's all going to go to the cloud. We'll see it's going to be a long, long time before that happens. Okay! I'll give you last thoughts on this conference. You've been here before? Or is this your first one? >> This is my first one. >> Okay, so your takeaways, your thoughts, things you might-- >> I am very impressed. I'm a practitioner and finding so many practitioners coming from so many different backgrounds and industries. It's very, very enlightening to listen to their journey, their story, their learnings in terms of what works and what doesn't work. It is really invaluable. >> Yeah, I tell you this, it's always a highlight of our season and Gokula, thank you very much for coming on theCUBE. It was great to see you. >> Thank you. >> You're welcome. All right, keep it right there everybody. We'll be back with our next guest, Dave Vellante. Paul Gillin is in the house. You're watching theCUBE from MIT. Be right back! (upbeat techno music)

>> Live from Las Vegas, it's theCUBE covering Dell Technology's World 2019. Brought to you by Dell Technologies and it's ecosystem partners. >> Hi, welcome to theCUBE Lisa Martin with Stu Miniman and we are live at Dell Technologies World 2019 in Las Vegas with about 15,000 or so other people. There's about 4,000 of the Dell Technologies community of partners here as well. Day one as I mentioned, we're very pleased to welcome back one of our cube alumni, Karen Quintos, EVP and Chief Customer Officer from Dell Technologies, Karen, welcome back to theCUBE. >> Thank you, thank you. Always great to be with you all. >> So one of the things you walk down on stage this morning with Michael Dell and and the whole gang and you started to share a story that I'd love for you to share with our audience about this darling little girl, Phoebe from Manchester, England that has to do with this Dell Technologies partnership with Deloitte Detroit and 3D prosthetics. Can you share this story and what it meant about this partnership. >> Well we wanted to tell this story about Phoebe because we really wanted the audience to understand the innovation and all of what's done it with social good is really about the individual, You know, technology plays a key role but the face behind the technology and the innovation are people and you know, as you mention Phoebe is from Manchester, U.K. Her father wrote this blog about Phoebe's experience. Phoebe's aunt, Claire works for Deloitte. She had access to a lot of what they could do in terms of 3D printing and basically came to Dell and we were able to take it and scale it and accelerate it and speed it up with a engineer by the name of Seamus who saw what the precision workstation could do. So it was this small idea to help an amazing little girl like this that has now turned into this movement around how do we more rapidly, quickly scale 3D prosthetics so these children and adults can have a chance at a normal life so. >> What kind of prosthetics did you guys build for her? >> It's an arm, so the very first arm that we built for her when she was about five years old had the frozen Disney theme painted on it. I asked her father Keith what is the one that she's wearing now because she's now this like really super cool seven-year-old that goes to school and all of her classmates and friends around her see her as this rock star and the one that she has today is printed with unicorns and rainbows. So if you know anything about seven-year-old girls, it's all about unicorns and rainbows and she's done an amazing thing and she's inspired so many other people around the world, individuals, customers, partners like Deloitte and others that we're working with to really take this to a whole new level. >> Karen, I think back to Dell you know, if you think back a couple of decades ago you know, drove a lot of the some of the waves of technology change you know, think back to the PC, but in the early days it was you know supply chain and simple ordering in all these environments and when I've watched Dell move into the enterprise, a lot of that is, I need to be listening to my customer, I need to be much closer to them because it's not just ordering your SKU and having it faster and at a reasonable price but there's a lot more customization. Can you talk about how you're kind of putting that center, that customer in the center of the discussion and that feedback loops that you have with them, how that's changed in Dell. >> Yeah sure, so all of the basic fundamentals around you got to order, deliver, make the supply chain work to deliver for our customers still matters but it's gone beyond that to your point and probably the best way to talk about it is these six customer award winners that we recognized last night. I've gotten to know all six of those over the last year and while they are doing amazing things from a digital transformation using technology in the travel business, the automotive business, banking, financial services, insurance, kind of across the board, the thing that they say consistently is look, we didn't always have the answer in terms of what we needed but you came in, you listened, you rolled up your sleeves to try to figure out how you could design a solution that would meet the needs that we have and they said, that's why you're one of the most strategic partners that we have. Now you can do all those other things, right? You can supply chain ride and build and produce and all that but it's the design of a solution that helps us do the things that will allow us to be differentiated and you look at that list of six customers and brands that they represent, right, Carnival Cruise Lines, USAA, Bradesco, McLaren I mean, the list kind of goes on, they are the differentiators out there and we're really honored to be able to be working with them. >> So we're only a day one and it's only just after lunchtime but one of the things I think somatically that I heard this morning in the keynote with Michael and Pat and Jeff and Satya and yourself is, it's all about people. A couple interviews I did earlier today, same sort of thing, it's like we had the city of Las Vegas on. This is all driven by the people in for the people so that sense of community is really strong. I also noticed this year's theme of real transformation, parlays off last year's theme of make it real, it being digital transformation, IT, security, workforce transformation, what are some of the things that were like at Dell Technologies. Cloud this morning for example, VMware Cloud on Dell EMC that you guys specifically heard say from last year's attendees that are manifesting in some of the announcements today and some of the great things the 15 or so thousand people here are going to get to see and feel and touch at this year's event? >> Well, Lisa you nailed it. What you heard on stage today is what customers have been telling us over the last year. We unveiled about a month ago with a very small group of CIOs in Amia, our cloud strategy, our portfolio, the things that we're going to be able to do and one customer in particular immediately chimed in and said, we need you in the cloud and we need you in there now because you offer choice, you offer open, you offer simplicity, you offer integration and they're like, there's just too many choices and a lot of them are expensive. So what you heard on stage is absolutely a manifestation of what they told us. The other pieces, look, I think I think the industry and CIOs are very quickly realizing their workforce matters, making them happy and productive matters having them enabled that they can work flexibly wherever they want to really, really matters and you know, our Unified Workspace ONE solution is all about how we help them simplify, automate, streamline that experience with their workforce so their employees stick around. I mean, there's a war on talent and everybody's dealing with it and that experience is really, really important in particular to the gensies and the millennials. >> Karen, I love that point. Actually, I was really impressed this morning. In the press and analyst session this morning, there was a discussion of diversity and inclusion and the thing that I heard is, it's a business imperative, it's not, okay it's nice to do it or we should do it but no, this is actually critical to the business. Can you talk about what that means and what you hear from your customers and partners. >> Yes, yes, well, we're seeing it in spades and all of these technology jobs that are open, right. So look, all the research has shown that if you build a diverse team, you'll get to a more innovative solution and people generally get that but what they really get today is here in the U.S. alone, there's 1.1 million open technology jobs by the year 2024, half of them, half of them are going to be filled by the existing workforce. So there is this war in talent that is going to get bigger and bigger and bigger and I think that's what really has given a wake-up call to corporations around why this matters. I think the other piece that we're starting to see, not just around diversity but in our other social impact priorities around the environment as well as how we use our technology for good, look, customers want to do business with a corporation that has a soul and they stand for something and they're doing something, not just a bunch of talking heads but where it's really turning into action and they're being transparent about the journeys and where they're at with it. So it matters now to the current generation, the next generation, it matters to business leaders, matters to the financial services community, which you start to see you know, some of the momentum around you know, the black stones and state street. So it's really exciting that we're part of it and we're leading the way in a lot of number of areas. >> And it's something to that we talked about a lot on theCUBE, diversity and inclusion from many different levels, one of them being the business imperative that you talked about, the workforce needing to compete for this talent, but also how much different products and technologies and apps and APS and things can be with just thought diversity in and of itself and I think it's refreshing to what Stu was saying, hey, we're hearing this is a business imperative but you're also seeing proof in the pudding. This isn't just, we've got an imperative and we're going to do things nominally, you're seeing the efforts manifest. One of the, Draper Labs who was one of the customer award winners. That video that was shown this morning struck probably everyone's heart with the campfire in Paradise California. >> Tragic. >> I grew up close to there and that was something that only maybe, I get goosebumps, six months ago, so massively devastating and we think you know, that was 2018 but seeing how Dell Technologies is enabling this laboratory to investigate the potential toxins coming from all of this chart debris and how they're working to understand the social impact to all of us as they rebuild, I just thought it was a really nice manifestation of a social impact but also the technology breadth and differentiation that Dell has enabling. >> That was also why this story today was so great about Phoebe, right because it's where you can connect the human spirit with technology and scale and have an even bigger impact and there's so much that technology can help with today. You know, that that story about Phoebe. From the time that her aunt from Deloitte identified, you know, what we could do, all the way to the time that Phoebe got her first arm was less than seven months, seven months and you think about you know, some of the other prototypes that were out there, times would take years to be able to do it. So I love that you know, connection of human need with the human spirit and connecting and inspiring and motivating so many children and adults around the world. >> And what what are some of the next, speaking of Phoebe and the Deloitte digital 3D prosthetics partnership, what are some of the other areas we're going to see this technology that this little five-year-old from Manchester spurned. >> Well, I'll give you another example. So we, there was an individual in India, actually an employee of ours that designed an application to help figure out how to deploy healthcare monitoring in some of the remote villages in India where they don't have access to basic things that we take for granted. Monitoring your blood pressure, right, checking your cholesterol level and he created this application that a year later now, we have given kind of the full range of the Dell portfolio technology suite. So it is you know our application plus Pivotal plus VMware plus Dell EMC combined with the partnering that we've done with Tata Trust and the State of India, we've now deployed this healthcare solution called Life Care Solution to nearly 37 million rural residents, citizens in India. >> Wow 37 million. >> 37 million, so a small idea, you take from a really passionate individual, a person, a human being and figure out how you can really leverage that across the full gamut of what Dell can do, I think the results are incredible. >> Awesome, you guys also have a Women in Technology Executive Summit that you're hosting later this week. Let's talk about that in conjunction of what we talked a minute ago about, it's a business imperative as Stu pointed out, there are tangible, measurable results, tell us about this. >> Well, I'm kind of done honestly with a lot of the negativity around, oh, we're not making any progress, oh, we need to be moving fast and if you look at the amount of effort, energy and focus that is going into this space by so many companies and the public sector, it's remarkable and I've met a number of these CIOs over the last year or two, so we basically said let's invite 20 of them, let's share our passion, have made progress, care about solving this across their organization. A lot of us are working on the same things so if we simply got in a room and figured out, are their power in numbers and if we worked collectively together, could we accelerate progress. So that's what it's all about. So we have about 15 or 20 CEOs, both men and women and we'll be spending you know, six or seven hours together and we want to walk away with one or two recommendations on some things that we could collaborate on and have a faster, bigger impact. >> And I heard that, you mentioned collaboration, that's one of the vibes I also got from the keynote this morning when you saw Michael up there with Pat and Jeff and Satya, the collaboration within Dell Technologies, I think even talking with Stu and some of the things that have come out and that I've read, it seems to be more symbiosis with VMware but even some the, like I said, we're only in, I wouldn't even say halfway through day one and that is the spirit around here. We talk about people influence, but this spirit of collaboration is very authentic here. You are the first chief customer officer for Dell, if you look back at your tenure in this role, could you have envisioned where you are now? >> No, because it was like the first ever chief customer officer at Dell and you know, it really gave me a unique opportunity to build something from scratch and you know, there's been a number of other competitors as well as other companies that have announced in the last year or so the need to have a chief customer officer, the need to figure out how, which is a big remit of mine across Dell Technologies, how do we how do we eliminate the silos and connect the seams because that's where the value is going to be unlocked for our customers. That's what you saw on stage today. You saw the value of that with Jeff, with Pat, with Satya, some you know, one of our most important partners out there. Our customers don't want point solutions, they want them to be integrated, they want it to be streamlined, they don't be automated, they want us to speed time to value, they want us to streamline a lot of the back-office kind of mundane things that they're like, I don't want my people spending their time anymore and doing that and that's where we see Dell Technologies being so much more differentiated from other choices in the market. >> Yep, I agree with you. Well Karen, thank you so much for joining Stu and me on theCUBE this afternoon, sharing some of the stories, look forward to hearing next year what comes out of this year's as Women in Tech Exec Summit. Thank you so much for your time. >> Thank you very much, thank you. >> with Stu Miniman, I'm Lisa Martin, you're watching theCUBE, live day one of Dell Technology World from Las Vegas, thanks for watching. (light electronic music)

>> Live. From San Francisco, it's theCUBE. Covering Google Cloud Next 2018. Brought to you by Google Cloud and its ecosystem partners. (techno music) >> Hello, everyone, welcome back to our day two of live coverage here in San Francisco, California for Google Next's conference called Next 2018, Google Next 2018 is the hashtag. I'm John Furrier with Dave Vellante. We're kickin' off day two. We just heard the keynotes, they're finishing up. Most of the meat of the keynote is out there, so we're going to just dive in and start the analysis. We got a tight schedule again, great guests, we have all the cloud-native folks comin' up from Google. We're going to hear from customers, and from partners. We're going to hear all the action. We're going to break it down for you. But first we want to do kind of a breakdown on the keynote, do analyze it and give some critical analysis, and also, things we think Google's doing great. Dave, day two, we've got three days of wall-to-wall coverage, go to the siliconangle.com for special journalism cloud series, a lot of articles hitting, a lot of CUBE videos, go to theCube.net, just check out those videos. That's our site, where all the videos are. Dave, day one, we had a great close yesterday; I thought it was phenomenal. But I thought we nailed it, today, too. And one of the things we were talkin' about in the first day close, editorially, was saying, hey, you know, this AI is super important. Today, in the keynote, more AI, more under the covers, more speed of announcements. Google kind of taking a playbook out of Amazon, let's get some announcements out there, I wouldn't say that the pace of announcements meets AWS, in terms of the announcements, but the focus is on a very few core things: AI, RollaData, Cloud-Native, Cloud Functions, Cloud Services Platform. This is the Google, that they're lifting the curtain. We're startin' to see some action. Your thoughts on the keynote... >> Well, I think you're absolutely right, I think Google realizes that it's got to compete with Amazon, from the keynote standpoint, demonstrating innovations, putting out a lot of function. I will say this, maybe it doesn't match Amazon's pace of innovation and announcements, but when you compare what these cloud-guys do with the traditional enterprise shows that we go to, there's no comparison. Even this morning, keynote day two, was drinking from a fire hose, there are dozens of announcements that Google made today. I would say just a couple of things, critical analysis, Google, everything is very scripted, as is all these shows, Amazon is very scripted as well, but they're reading everything, which I don't like, I would rather see them have a little bit more teleprompter, friendly, sort of presentation. So that's just sort of a little side comment. But the content is very good. The big themes I took away today, even though they didn't use this term, is really they're treating infrastructure as code. They're deploying infrastructure and microservices from code, as developers. So that was a theme that cut through the entire morning. Big announcement was the GA of Cloud Functions. It's been in beta, now it's Serverless, it's been in beta for a long time. And then a number of other announcements that we're going to go through and talk about, but those were some of the big highlights. But AutoML, I want to talk about that a little bit, talk a lot about developer agility. Threw out a couple of examples of customers, we heard from Chevron, we heard from Twitter, so they're starting to give examples, again, not as many Amazon, but real customers in the enterprise, customers like Mastercard, so, they're dropping some names... You're starting to see their belief manifest into actual adoption. But I'd like to ask you, John, what's your sense of the adoption bell curve, and the maturity curve, of the Google customer? >> Great question, I think for me, just kind of squinting through all of the noise, and looking at the announcements specifically, and how the portfolio of the show's going, it's very clear that Google is saying, we are here to play, we are here to win, we're going to take the long game on this cloud business. We have a ton to bring to the table, I call it the "bring out the Howitzers, the big guns." And they're doing that, they're bringing major technology, BigQuery, BigTable, Spanner, and a variety of other things, from the core Google business, bringing that out there and making it consumable; said that yesterday. Today, we looked at what's goin' on. You're seeing AI within G Suite. Leading by example, by demonstrating, look at it, this is how we use AI, you could use it, too, but not jamming AI and G Suite down the throats of the customer. AI and BigTable, I thought was pretty significant, because you can now bring machine learning and artificial intelligence, so to speak, into a data warehouse-like environment, where there's not a lot of data movement, data prep, it just happens. And then the Cloud Services Platform, the CSP, that Eyal Menor, the Vice President of Engineering, rolled out, I found interesting. The key move there was Cloud Functions. They now need to have Serverless up and running, and obviously Lambda's AWS. The uptake on the enterprise with Lambda has been significant, more than they thought. We heard that from Amazon, so I expect that Cloud Functions, and having this foundational layer with Kubernetes doubling down. The Kubernetes, Istio, and these Cloud Functions, represent that foundation. Knative open source projects, again, another arrow in their quiver around their open source contribution. This is Google, they're bringing the goods to the party, the open source party. This is an under-appreciated value proposition, in my opinion; I think a lot of people don't understand the implications of what's going to go on with this. This upstream contribution, and the downstream benefits that's going to come from their contra open source, is highly strategic. We used to call it, in the old days, "Kool-Aid injection." That's the way you ingratiate into the community with your software, ultimately the best software should win. There's not a lot of politics in open source, as there was once was, so I think that's fine. Now, to the question of migration, Google Cloud is showin' some customers up there, but I don't think they're going to, they're a long ways away from winning enterprises. What you see Google winning now is the AlphaTechies. The guys who were, and gals, who know tech, they know scale, and they can come in and appreciate the goodness of Google, they can appreciate the 10x advantages we heard from Danielle, with Spanner. These are what I call people with massive tech chops. They understand the tech, they've had problems, they need an aspirin, they need a steroid, and they need a growth hormone, right? They don't just need a pain-killer, they need solutions. These guys can make it happen. They jump in, take the machinery, and make that scale. The second level on the trajectory of their growth, on the adoption curve, is what I call, "Smart SMB, Smart enterprises." These are enterprises that have really strong technical people, where the internal conversations is not "if we should go to cloud," it's "how should we go to cloud?" And the DNA of the makeup of the technical people will decide the cloud they go with. And if it's engineering-led, meaning they have strong network operations, strong dev-team, then they have people who know what they're doing, they gravitate to Google Cloud. The third phase, which I think is not yet attainable, although aspirational, for Google, is the classic enterprise. "Man, I've been buying IT for years, oh my god, I'm like a straight-jacket of innovation, nothing's happening!" They're like, "we got to go to the cloud, how do we do it?" It's a groping for a strategy, right? So, Amazon gets those guys, because there's some things that shadow IT that Amazon can deliver, in more options, than what Google has. So I think I don't see Google knockin' that down in the short term, anytime soon. They can do plenty of business. Again, this is a trajectory that has an economy of scale to it, as an advantage, as a competitive advantage, by doing that. If Google tries to become Amazon, and meet their trajectory, the diseconomies of scale plays against Google. This is critical, Google does not want to do that, and they're not doing that, so I think the strategy of Google is right on the money. Nail the early adopters, the alpha geeks. Hit the engineering teams within the smartest companies, or small businesses, and then wait to hit that mainstream market, two, three years from now. So I think there's a multi-year journey for Google. Again, this diseconomies of scale is not what they want, they have tons of leverage in the tech, and the data, and the AI. So to me, they're right on track. They're now getting into the phase two. Smart. I give them credit for that. >> Let me pick up on a couple of things you said, and tie it into the keynotes from this morning. But I want to start with some of the conversations that you and I had last night, and around the show, with some of the GCP users. So, we've been asking them, okay, well how do you like GCP? Whaddya like? What don't you like? How does it compare with Azure? How does it compare with Amazon? And the feedback has been consistent. Tech is great, a lot of confidence in the tech. Obviously what Google's doing is they're using the tech internally, and then they're pointing it to the external world. It comes out in beta, and then they harden it, like they did today with Serverless and GOGA. The tech's great. Documentation has a little bit to be desired; we heard that as a consistence theme. Functionality not as rich in the infrastructure side as AWS, and not as enterprise app friendly as Azure, but very, very solid capabilities. This comes from people in financial services, people in healthcare, people from oil and gas. So, it's been consistent feedback that we've heard across the user base. You mentioned Knative; Knative is a new open source project, that brings Serverless to Kubernetes, and it was brought forth by Pivotal, IBM, RedHat, SAP, obviously Google, and others. Again, a big theme of the keynotes this morning was developer agility, bringing microservices, and services, and things like Kubernetes, to the developer community. Now, I want to talk about another example of a customer, Chevron. Is Google crushing it in traditional enterprise IT in the cloud? Well, no, you're bringing up the point that they're not. But, what they are doing, is doing well in places where people are solving data-oriented business problems with technology. Is that IT? It's not a traditional IT, but it's technology. Let me give you an example, Chevron was up on stage today, and they gave an example of they have thousands and thousands of docs, of topographical data points, and they use this thing called AutoML to ingest all the data into a model that they built, and visualize that data, to identify high-probability drilling zones and sites in the Gulf of Mexico. Dramatically compressed the time that it would have taken. In fact, they wouldn't have been able to do this. So they ingested the data, auto-categorized all the data to simplify it, put it into buckets, and then mapped it into their model, which was tuned over time, and identified the higher probability of sites for drilling. That's using tech to solve a business problem, drive productivity; Google crushes it with those type of data applications, really good example. >> And AutoML drives that, and this is where, again, a machine learning, AutoML, AI operation, we mentioned that yesterday, the IT operations sector is going to be decimated. But I think the big tell sign for me is when I look at the cloud shows, Amazon definitely has competition with Google, so that anyone who says Google's way far back in the market share, which you know I think is bastardized, I think those market share numbers don't mean anything because there's so much sandbagging going on; I could look at any one and say Microsoft's just sandbagging the numbers, and Amazon not really, if Amazon could probably sandbag the numbers even more by putting revenue from their partner ecosystem. Google throws G Suite in there, but they could throw AdWords in there and say technically that's running on their cloud, and be the number one cloud. What is a good cloud? When you have a cloud, if you can make a situation where you can take a customer and get them on the cloud easily, in a simplified, accelerated way, that is a success formula. What you heard on stage today was kind of, naw, I won't say underplayed, they certainly played it up and got some applause, is Velostrata and these services. They bought a company called Velostrata in May of this past year, and what they do is essentially the migration. We had a guest on, a user yesterday, migrating from Oracle to Spanner, 10x value, major reduction in price. They didn't say 10x, but significant; we'll try to get those numbers, she wouldn't say. But what Velostrata does is allows you to migrate to existing apps in a very easy, non-disruptive way, from on-prem to the cloud. This is the killer app for the leading clouds. They need tools to move workloads and databases to their cloud, because as clients and enterprises start to do taste tests, kick the tires in cloud, they're going to want to know what's the better cloud. So, the sales motto is simply go try it before you buy it. It's cloud. You can rent it. This is the value of the cloud. So, Amazon's done an extremely awesome job at this, Google has to step up, and I think Velostrata's one of many. I think the Kubernetes piece is critical, around managing legacy workloads, and adding new cloud natives. Between Velostrata, and the Knative, and the Cloud Functions, I think Google is shoring up their offerings, and it makes them a formidable competitor for certain workloads, and those early adopters, and that Stage Two, small, medium, or Smart enterprise, as a foundational element. I think that is a tell sign, and I got to give them props for that, and again, you can get an Oracle database into cloud, you're going to win a lot of business. If you can get an app workload running on Google Cloud seamlessly, in a very easy, meaningful way, it's just going to rain money. >> So let's talk about something we just talked about, how Google's not crushing it in traditional enterprise apps, but let's talk about some-- >> For now. >> of things we heard today, where they're trying to get into that space. So they announced today support on GCP for Oracle RAC, real application clusters, and exit data, and then SAP, via a partnership with Accenture. So Accenture does crush it with Oracle and SAP. Now, here's the problem: Oracle will play its licensing games, we've seen this with Amazon, where essentially, Oracle's license costs are double in AWS, they'll do the same thing for Google, I guarantee it, than they are in Oracle's cloud. So, 2x. It's already incredibly expensive. So, Oracle's going to use its pricing strategy to lock out competitors. So, that's a big deal, but we also saw some stuff on security: Cloud Armor, automatically defending against DDoS attacks, that's a big deal. We heard about shielded VMs, so secure VMs within GCP. These are things that traditional enterprises, it's going to resonate with traditional enterprises. >> Yeah, but here's the thing, then, we have one final point. I know we're going to run over a little bit of time, here, but I wanted to get it out there. You mentioned Oracle and the licenses. It's not just about Oracle, and their costs, and that disadvantage that could happen for a lot of people, and what cloud clearly has some benefits on a lot of cost. Here's the problem, like any Mafia business, Dave, we always talk about the cloud Mafias, and the on-premise Mafias. Oracle has an ecosystem of people who make a boatload of money around these licenses. So, you have a lot of perverse incentives around keeping the old stuff around, okay? So, as the global SIs, you mentioned Accenture, Deloitte, and others, those guys may salute the Google Cloud flag and the ecosystem, but at the end of the day, it's going to come down to money for them. So, if the perverse incentive is to stay in the old ways, saying "hey, okay, if we keep the license in there I get more better billing hours and I can roll out more deployments." Because what clouds do, and what Google's actually enabling, is enabling for the automation of those systems and those services, so you're going to see a future, very quickly, where half of the work that Accenture and Deloitte get paid on is going to be gone. From weeks to minutes; months, to weeks, to minutes. This is not a good monetization playbook for Accenture, and those guys. >> Well. >> So Google has to shift a ecosystem strategy that's smart and makes people money. At the end of the day-- >> No doubt. >> That's going to be a healthy ecosystem for every dollar of Google spend, it has to be at least 5 to 15x ecosystem dollars. I just don't see it right now. >> The big consultancies love to eat at the trough, as we like to say. But let's talk about the ecosystem, because you and I, we've walked the floor a couple times now. We mentioned Accenture, Cognizant is here, RedHead is here, KPMG, Salesforce, Marketo, Tata, everybody's here. UiPath, a startup in RPA; Cohesity's here. Rubrik's here, Intel's here, everybody's here, except AWS isn't here. >> Obviously. >> (chuckles softly) And Microsoft's not here. The other point that I think is worth mentioning, is again, big theme here is internally tested and then we point it at the market. Chevron, Autotrader, Mastercard, you're starting to see these names trickle out, other traditional enterprise. They announced today a partnership with NetApp for file sharing, for NFS workloads. So you're seeing NetApp lean in to the cloud in a big way. NetApps, back! You know you were seein' that. You saw Twitter on the Google Cloud. So you're seeing more and more examples of real companies, real businesses. >> I'll just end this segment by saying one thing quickly, the high IQ people in the industry, whether it's customers, partners, or vendors, are going to have to increase their 3D chess game, because as the money shifts around, the zero-sum game in my mind, it's going to shift to the value. Things are going to get automated either way, and that could be core businesses. So, the innovative dilemma is in play for many, many people. You got to be smart, and you got to land in a position, you got to know where the puck is going to be, skate to where the puck is going to be. It's going to require the highest IQ: tech IQ, and also business IQ, to make sure that you are making money as the world turns, because those dollars are up for grabs. The dollars are shifting as the new ecosystem rolls out. If you're relying on old ways to make money, you are in for a world of hurt if you don't have a plan. So, to me, that's the big story, I think, in the cloud that Google's driving. Google's driving massive acceleration, massive value creation, massive ecosystem opportunities, but it's not your grandfather's ecosystem, it's different. So we're going to see, we're going to test people, we're going to challenge it, we're going to have conversations here in TheCube. The day two of three days of live coverage. I'm John Furrier with Dave Vellante. Stay with us as we kick off day two. We'll be right back. (techno music)

>> Narrator: Live from Las Vegas, it's theCUBE, covering HPE discover, 2017, brought to you by Hewlett Packard Enterprise. >> Everyone, we are live here in Las Vegas with SiliconANGLE Media's, theCUBE, our flagship program where we go out to the events, and strike the cylinders, talk to the thought leaders the experts, folks making it happen. I'm John Furrier with my cohost Dave Vellante. Our next guest is Pete Murray, worldwide Vice President of OEM sales and IoT go to market for HP enterprise. Pete welcome to theCUBE. >> Thank you. >> So OEM people basically, Original Equipment Manufacturing they basically take your stuff and put it in their solutions. Why are they interested in doing that? Obviously you have a good product and IoT's hot. This is a new journey and a lot of people are figuring it out. What's the premise behind the growth and the business opportunity for you guys? >> We see IoT as a great opportunity. Whichever analyst you talk to, they're all consistent on one thing and that is, there are going to be billions of devices connected. If you talk to some of the estimates they're anything between 20 and 30 billion by 2020. All that does is create great opportunities and really exciting things can happen when you connect the unconnected, which is today. We're working with OEMs and we've got a successful program for many many years and a lot of our OEMs are starting to look at the marketplace and see great potential to enhance what they offer to their customers. And ultimately deliver additional business value. >> We would agree with you, we think it's hot, in fact Dave and I are coming in Meg Whitman's key note. We think the numbers she was stating in terms of date in IoT understated. We think our numbers show a little higher but that speaks to the pressure for folks to add value, solutions, to providers to go to market with an IoT solution. What is the profile of your customer that's OEMing the HPE products? Is it apps, is it striving? Is it the driver on the app size, is it verticals? Can you share some insight into the landscape? >> Yeah, sure, by the way, our data figure we use is about 44 zeta bytes by 2020. But who knows it could be much bigger. We're focused mainly by industry, and we're working with a lot of our OEMs in industries such as, the healthcare business, telecommunications, transportation. We basically spend time allowing them to focus on what they're really good at. Bringing their intellectual property to solve business problems in their industry. What we bring is what we're really good at which is providing an innovative, quality based, compute based solution with a world class supply chain and global support. We think that's a really really good combination. And it naturally extends in the IoT world, because a lot of our OEMs are operational technology partners who have got something to say in that marketplace. And usually they've got the expertise in an industry segment to enable IoT, enable benefits to be seen and we want to really help them to do just that. >> Can you give an example and specifically the issue of why HPE versus the potentially other choices out there, or growing their own? What are the reasons why they come to you guys? What's the benefits? >> Well first of all, we think we've got a great OEM program, so it's a great base to start. Offering quality innovation and global presence. But on top of that when you look at the IoT world, we think we've got some really compelling assets. We've got assets around conductivity, security, location based capability, we've got the ability to computer the edge where we think there's a lot of significant reasons and benefits to do so. And lastly, we've got our own IoT platform called the universal IoT platform, and that can also deliver great benefits. If you put that together with a partnering co-system to be able to solve problems, we think it's pretty compelling. >> So Pete, take us through the cycle OEM sales cycles tend to be very long, they beat you up and stress test you a million different ways. What's it like, in your IoT world you mentioned healthcare, tel co and some others, what's that qualification cycle look like? >> Well we usually start with a business problem, whatever the OEM is trying to solve. And then we work out how we can best work with them to help them deliver it. Ultimately, the most important focus is their customer to deliver a good solution. So we go through the technology cycles, make sure that we can deliver to the service levels that they're interested in, and then we start thinking about the technology if there's additional innovation that's required. So our technology teams will be working closely together, and then we start looking at where they plan to deploy from a geography prospective, which region, which customers, which targets. And then we figure out how we can support them in that how we can obviously supply and ultimately, make sure that we can provide a great service to their clients. So the cycle can take a while but planning is critical, because when you actually start ramping volume, you want to make sure you've got the right plan in place. >> Well a company like yours has some advantages there like you said, your global distribution. How much of the work that you're doing and expect to be doing is custom activity? >> I'm sorry? >> Custom, how much is custom versus selling the same solution multiple times? And how does that business scale? >> What we tend to find is, we've actually got some pretty strong offerings that our customers use off the shelf and so, in a lot of cases customization is relatively small. But as we're moving into the IoT world a lot of the fundamental business problems we're trying to tackle are the same but each implementation is just slightly different. So we're seeing a little bit more customization as a result of that, but a lot of the time our customers are really interested in our core offerings, because we think that they're both industry leading and also solid. >> So it's maybe some special enabler? As opposed to some heavy engineering effort right? >> Yeah, I mean, typically in the OEM program we'll work with customers if they want to rebadge or rebrand or they're looking for the equipment to be in a certain different format. Or they want the packaging or the distribution documentation to be different, it's those sort of customizations as well as the base technology, if there is a requirement to do that. >> And how do you go to market? Do you have sort of an OEM sales force? And is it direct to those OEMs? There's not sort of a two-tier? I was wondering if you could describe that a little bit. >> So we've got an OEM sales force worldwide. We break it down by the three regions, we work with our NU's as sales teams. We also work with partners that are dedicated to sell OEM based solutions as well. So it's both a direct and indirect route to market our OEM sales teams will be working with our NUs sales teams also. Because there's a certain amount of knowledge and expertise that's needed. And our NUs sales teams won't necessarily have that. That's what we bring to the table. And we've got many many years of experience of doing just that, so it's a combination but we do have dedicated resources for a sales side. The second thing we have is, we've got program managers and technologists that are dedicated to OEM, so when we start working with an OEM customer we make sure that we can bring in people who understand, the product life cycles, they also understand the technology so that we can go through that innovation curve with them as well. >> So talk about the life cycles a little bit I said the sales cycles tend to be very long which is generally true of OEM business but the life cycle times are often times very compressed, so you're under a lot of pressure to keep innovating. So, talk about that. Is that the case in sort of the used cases that you're entering and how are you dealing with that? >> With IoT it can be very varied to a product cycle that can be down to six to 12 months to some cycles that can be 10 years or more. So if you think about it, if a customer's designing a piece of sophisticated equipment and they want an embedded computer solution within it what they don't want to do is see lots and lots of change. So sometimes the design can be current for five, 10, even 15 years. We're asked to support for those types of life cycles. So actually it's quite a mix, and as long as the product is competitive in the marketplace, we're really really happy to work with our OEMs and support that. >> And you need a scalable architecture, you've got to support the head room. What's your observation on that? And how are your customers on the OEM side, approaching that because they have to also put a compelling product out there allows the head room. What's the current state of the art, if you will, in terms of the tech? >> Well, one of the things is once they build a solution they don't really want to change it too many times unless it's innovating and offering more to their clients base directly. And so what we try to do is, we work to change management cycle to allow that to be as easy as possible. But when we bring new generations of technology along, so here at discover we're talking about generation 10 as our new offering on our compute service side, which I'm sure you've heard about. We work with our OEM customers to actually plan when they will implement it in their life cycle. And obviously what they try to do is to marry it up to providing additional innovation and benefit to their clients. So it needs to be planned, but when it's planned correctly it really can make the difference. >> So take us through a conversation, I think this is interesting because you guys have a lot to bring to the table, portfolio wise, you've got Aruba. >> Male: Yep. >> You've got the hardware, you've got the converged software, infrastructure, all that great stuff. When you talk with the customers, what are they comparing you to? I mean, competition wise, there's a lot of noise out there, certainly in IoT. We heard from DeLloyd, talking about some of the things that their customers are facing on the joint solutions. There's a lot of decisions, there's a lot of obstacles there. How do you guys compare and what are those conversations like? >> The conversations we have, they start with, what's the business problem? What are we trying to solve? And the usual areas that people focus on are how do you drive efficiency as cost saving? Number one business challenge. The second is how do you innovate and drive additional differentiation against your competition? So we start there, and then we start looking at potential ways to solve those problems. So we start looking at used cases around things like preventive maintenance, condition monitoring, location based functionality, we're looking at things like smart city solutions. And then what we try to do is come down to the assets that we've got and the capabilities we've got as a company to solve those problems. We never start with the technology, we always start with the business problem that we're trying to solve. >> And how do you compare, at the end of the day, when the customer lays out the solution vis-a-vis the competition, where do you guys shine? >> We think we shine really well. We think we've got a compelling proposition, we've got some great IoT assets, we've got some innovation that we're bringing, particularly when you look at some of the security features of our connectivity, when you look at our ability to compute at the edge. We think that we've actually got a strong message to say, compared to some of our competitors on the block, so we think we've got a strong story. And we think we've got a reason to have customers come talk to us. >> We talked in Intel recently at Mobile World Congress and then at South by Southwest and they have the pillars of societal changes. Autonomous vehicles, smart cities, music and entertainment, smart homes. They're kind of corpulous for the five G and how all this network transformation is happening. Where do you guys, outside of media entertainment which you guys do do business in. But those are, other areas like smart cities, autonomous vehicles and intelligent home. Those are I0o havens, right? I mean, you guys see those as really big markets? >> Yeah we do, I guess the biggest market that we're looking at is really around manufacturing right now because we see opportunities to drive, as I mentioned earlier, on efficiencies and cost savings out by collecting up and using the data which their currently generating but their actually not looking at the business insights within it. So manufacturing is a key opportunity for us. We're working with some really interesting customers to drive some great business outcomes. We're also looking at smart city, this week we're announcing some work we've been doing with Tata Communications in India. Connecting over 400 million of their citizens, and delivering additional service value on top of the platforms that we build around security, around healthcare and other things. But we think one of the biggest markets right now is around manufacturing. And that's where we're trying to put a lot of energy. >> I wanted to as you, Pete, about the data because data's abundant but the insights around that data are very scarce. And so when you think about an OEM business how do you think about the data play? It sounds like, I inferred from what you said that you're helping people get value out of the data. Are you also utilizing that data in other ways in your business? Whether it's predictive maintenance, or some kind of aggregate or talk about that data. >> So, the answer is yes in all counts. The data is absolutely critical. When you're building a preventive maintenance solution in order to get to condition monitoring you've got to collect enough data, look at the trends, and then be able to take action based on it. We're working with companies that are really really experts at doing that. So we've got relationships with the likes of GE digital, with their predicts platform. So we're doing a lot of ghost market activities with those. We're working with other customers like Natural Instruments and PTC that have got that data insight and that history and that level of industry touch and expertise. But when you work with them in partnership you can actually drive some significant data insights for customers. So for us it's about getting the right partnerships in those areas to generate the business insights and ultimately address the business challenges associated with them. >> Pete, we really appreciate you coming on theCUBE and we're going to keep monitoring the progress. Certainly, customer adoption there's always a great metric. And IoT is hot, low hanging fruit, manufacturing, some of these industries are ripe 'cause they're all set up for it, but it certainly the network transformation that's happening and congratulations on great progress. Thanks for coming on theCUBE. More CUBE action, live, here at HPE Discover 2017 in Las Vegas. I'm John Furrier with Dave Vellante. Stay with us, for more day one coverage after this short break. (techno music)