>>Hello. And we're here at the cube startup showcase made possible by a Ws. Thanks so much for joining us today. You know when Jim McDaid Ghani was formulating her ideas around data mesh, She wasn't the only one thinking about decentralized data architecture. Hello, Fresh was going into hyper growth mode and realized that in order to support its scale, it needed to rethink how it thought about data. Like many companies that started in the early part of last decade, Hello Fresh relied on a monolithic data architecture and the internal team. It had concerns about its ability to support continued innovation at high velocity. The company's data team began to think about the future and work backwards from a target architecture which possessed many principles of so called data mesh even though they didn't use that term. Specifically, the company is a strong example of an early but practical pioneer of data mission. Now there are many practitioners and stakeholders involved in evolving the company's data architecture, many of whom are listed here on this on the slide to are highlighted in red are joining us today, we're really excited to welcome into the cube Clements cheese, the Global Senior Director for Data at Hello Fresh and christoph Nevada who's the Global Senior Director of data also, of course. Hello Fresh folks. Welcome. Thanks so much for making some time today and sharing your story. >>Thank you very much. Hey >>steve. All right, let's start with Hello Fresh. You guys are number one in the world in your field, you deliver hundreds of millions of meals each year to many, many millions of people around the globe. You're scaling christoph. Tell us a little bit more about your company and its vision. >>Yeah. Should I start or Clements maybe maybe take over the first piece because Clements has actually been a longer trajectory yet have a fresh. >>Yeah go ahead. Climate change. I mean yes about approximately six years ago I joined handle fresh and I didn't think about the startup I was joining would eventually I. P. O. And just two years later and the freshman public and approximately three years and 10 months after. Hello fresh was listed on the German stock exchange which was just last week. Hello Fresh was included in the Ducks Germany's leading stock market index and debt to mind a great great milestone and I'm really looking forward and I'm very excited for the future for the future for head of fashion. All our data. Um the vision that we have is to become the world's leading food solution group and there's a lot of attractive opportunities. So recently we did lounge and expand Norway. This was in july and earlier this year we launched the U. S. Brand green >>chef in the U. K. As >>well. We're committed to launch continuously different geographies in the next coming years and have a strong pipe ahead of us with the acquisition of ready to eat companies like factor in the U. S. And the planned acquisition of you foods in Australia. We're diversifying our offer now reaching even more and more untapped customer segments and increase our total addressable market. So by offering customers and growing range of different alternatives to shop food and consumer meals. We are charging towards this vision and the school to become the world's leading integrated food solutions group. >>Love it. You guys are on a rocket ship, you're really transforming the industry and as you expand your tam it brings us to sort of the data as a as a core part of that strategy. So maybe you guys could talk a little bit about your journey as a company specifically as it relates to your data journey. You began as a start up. You had a basic architecture like everyone. You made extensive use of spreadsheets. You built a Hadoop based system that started to grow and when the company I. P. O. You really started to explode. So maybe describe that journey from a data perspective. >>Yes they saw Hello fresh by 2015 approximately had evolved what amount of classical centralized management set up. So we grew very organically over the years and there were a lot of very smart people around the globe. Really building the company and building our infrastructure. Um This also means that there were a small number of internal and external sources. Data sources and a centralized the I team with a number of people producing different reports, different dashboards and products for our executives for example of our different operations teams, christian company's performance and knowledge was transferred um just via talking to each other face to face conversations and the people in the data where's team were considered as the data wizard or as the E. T. L. Wizard. Very classical challenges. And those et al. Reserves indicated the kind of like a silent knowledge of data management. Right? Um so a central data whereas team then was responsible for different type of verticals and different domains, different geographies and all this setup gave us to the beginning the flexibility to grow fast as a company in 2015 >>christoph anything that might add to that. >>Yes. Um Not expected to that one but as as clement says it right, this was kind of set up that actually work for us quite a while. And then in 2017 when L. A. Freshman public, the company also grew rapidly and just to give you an idea how that looked like. As was that the tech department self actually increased from about 40 people to almost 300 engineers And the same way as a business units as Clemens has described, also grew sustainable, sustainably. So we continue to launch hello fresh and new countries launching brands like every plate and also acquired other brands like much of a factor and with that grows also from a data perspective the number of data requests that centrally we're getting become more and more and more and also more and more complex. So that for the team meant that they had a fairly high mental load. So they had to achieve a very or basically get a very deep understanding about the business. And also suffered a lot from this context switching back and forth, essentially there to prioritize across our product request from our physical product, digital product from the physical from sorry, from the marketing perspective and also from the central reporting uh teams. And in a nutshell this was very hard for these people. And this that also to a situation that, let's say the solution that we have became not really optimal. So in a nutshell, the central function became a bottleneck and slowdown of all the innovation of the company. >>It's a classic case, isn't it? I mean Clements, you see you see the central team becomes a bottleneck and so the lines of business, the marketing team salesman's okay, we're going to take things into our own hands. And then of course I I. T. And the technical team is called in later to clean up the mess. Uh maybe, I mean was that maybe I'm overstating it, but that's a common situation, isn't it? >>Yeah. Uh This is what exactly happened. Right. So um we had a bottleneck, we have the central teams, there was always a little of tension um analytics teams then started in this business domains like marketing, trade chain, finance, HR and so on. Started really to build their own data solutions at some point you have to get the ball rolling right and then continue the trajectory um which means then that the data pipelines didn't meet the engineering standards. And um there was an increased need for maintenance and support from central teams. Hence over time the knowledge about those pipelines and how to maintain a particular uh infrastructure for example left the company such that most of those data assets and data sets are turned into a huge step with decreasing data quality um also decrease the lack of trust, decreasing transparency. And this was increasing challenge where majority of time was spent in meeting rooms to align on on data quality for example. >>Yeah. And and the point you were making christoph about context switching and this is this is a point that Jemaah makes quite often is we've we've we've contextualized are operational systems like our sales systems, our marketing system but not our our data system. So you're asking the data team, Okay. Be an expert in sales, be an expert in marketing, be an expert in logistics, be an expert in supply chain and it start stop, start, stop, it's a paper cut environment and it's just not as productive. But but on the flip side of that is when you think about a centralized organization you think, hey this is going to be a very efficient way, a cross functional team to support the organization but it's not necessarily the highest velocity, most effective organizational structure. >>Yeah, so so I agree with that. Is that up to a certain scale, a centralized function has a lot of advantages, right? That's clear for everyone which would go to some kind of expert team. However, if you see that you actually would like to accelerate that and specific and this hyper growth, right, you wanna actually have autonomy and certain teams and move the teams or let's say the data to the experts in these teams and this, as you have mentioned, right, that increases mental load and you can either internally start splitting your team into a different kind of sub teams focusing on different areas. However, that is then again, just adding another peace where actually collaboration needs to happen busy external sees, so why not bridging that gap immediately and actually move these teams and to end into into the function themselves. So maybe just to continue what, what was Clements was saying and this is actually where over. So Clements, my journey started to become one joint journey. So Clements was coming actually from one of these teams to build their own solutions. I was basically having the platform team called database housed in these days and in 2019 where basically the situation become more and more serious, I would say so more and more people have recognized that this model doesn't really scale In 2019, basically the leadership of the company came together and I identified data as a key strategic asset and what we mean by that, that if we leverage data in a proper way, it gives us a unique competitive advantage which could help us to, to support and actually fully automated our decision making process across the entire value chain. So what we're, what we're trying to do now or what we should be aiming for is that Hello, Fresh is able to build data products that have a purpose. We're moving away from the idea. Data is just a by problem products, we have a purpose why we would like to collect this data. There's a clear business need behind that. And because it's so important to for the company as a business, we also want to provide them as a trust versi asset to the rest of the organization. We say there's the best customer experience, but at least in a way that users can easily discover, understand and security access high quality data. >>Yeah, so and and and Clements, when you c J Maxx writing, you see, you know, she has the four pillars and and the principles as practitioners you look at that say, okay, hey, that's pretty good thinking and then now we have to apply it and that's and that's where the devil meets the details. So it's the four, you know, the decentralized data ownership data as a product, which we'll talk about a little bit self serve, which you guys have spent a lot of time on inclement your wheelhouse which is which is governance and a Federated governance model. And it's almost like if you if you achieve the first two then you have to solve for the second to it almost creates a new challenges but maybe you could talk about that a little bit as to how it relates to Hello fresh. >>Yes. So christophe mentioned that we identified economic challenge beforehand and for how can we actually decentralized and actually empower the different colleagues of ours. This was more a we realized that it was more an organizational or a cultural change and this is something that somebody also mentioned I think thought words mentioned one of the white papers, it's more of a organizational or cultural impact and we kicked off a um faced reorganization or different phases we're currently and um in the middle of still but we kicked off different phases of organizational reconstruct oring reorganization, try unlock this data at scale. And the idea was really moving away from um ever growing complex matrix organizations or matrix setups and split between two different things. One is the value creation. So basically when people ask the question, what can we actually do, what shall we do? This is value creation and how, which is capability building and both are equal in authority. This actually then creates a high urge and collaboration and this collaboration breaks up the different silos that were built and of course this also includes different needs of stuffing forward teams stuffing with more, let's say data scientists or data engineers, data professionals into those business domains and hence also more capability building. Um Okay, >>go ahead. Sorry. >>So back to Tzemach did johnny. So we the idea also Then crossed over when she published her papers in May 2019 and we thought well The four colors that she described um we're around decentralized data ownership, product data as a product mindset, we have a self service infrastructure and as you mentioned, Federated confidential governance. And this suited very much with our thinking at that point of time to reorganize the different teams and this then leads to a not only organisational restructure but also in completely new approach of how we need to manage data, show data. >>Got it. Okay, so your business is is exploding. Your data team will have to become domain experts in too many areas, constantly contact switching as we said, people started to take things into their own hands. So again we said classic story but but you didn't let it get out of control and that's important. So we actually have a picture of kind of where you're going today and it's evolved into this Pat, if you could bring up the picture with the the elephant here we go. So I would talk a little bit about the architecture, doesn't show it here, the spreadsheet era but christoph maybe you can talk about that. It does show the Hadoop monolith which exists today. I think that's in a managed managed hosting service, but but you you preserve that piece of it, but if I understand it correctly, everything is evolving to the cloud, I think you're running a lot of this or all of it in A W. S. Uh you've got everybody's got their own data sources, uh you've got a data hub which I think is enabled by a master catalog for discovery and all this underlying technical infrastructure. That is really not the focus of this conversation today. But the key here, if I understand it correctly is these domains are autonomous and not only that this required technical thinking, but really supportive organizational mindset, which we're gonna talk about today. But christoph maybe you could address, you know, at a high level some of the architectural evolution that you guys went through. >>Yeah, sure. Yeah, maybe it's also a good summary about the entire history. So as you have mentioned, right, we started in the very beginning with the model is on the operation of playing right? Actually, it wasn't just one model is both to one for the back end and one for the for the front and and or analytical plane was essentially a couple of spreadsheets and I think there's nothing wrong with spreadsheets, right, allows you to store information, it allows you to transform data allows you to share this information. It allows you to visualize this data, but all the kind of that's not actually separating concern right? Everything in one tool. And this means that obviously not scalable, right? You reach the point where this kind of management set up in or data management of isn't one tool reached elements. So what we have started is we've created our data lake as we have seen here on Youtube. And this at the very beginning actually reflected very much our operational populace on top of that. We used impala is a data warehouse, but there was not really a distinction between borders, our data warehouse and borders our data like the impala was used as a kind of those as the kind of engine to create a warehouse and data like construct itself and this organic growth actually led to a situation as I think it's it's clear now that we had to centralized model is for all the domains that will really lose kimball modeling standards. There was no uniformity used actually build in house uh ways of building materialized use abuse that we have used for the presentation layer, there was a lot of duplication of effort and in the end essentially they were missing feedbacks, food, which helped us to to improve of what we are filled. So in the end, in the natural, as we have said, the lack of trust and that's basically what the starting point for us to understand. Okay, how can we move away and there are a lot of different things that you can discuss of apart from this organizational structure that we have said, okay, we have these three or four pillars from from Denmark. However, there's also the next extra question around how do we implement our talking about actual right, what are the implications on that level? And I think that is there's something that we are that we are currently still in progress. >>Got it. Okay, so I wonder if we could talk about switch gears a little bit and talk about the organizational and cultural challenges that you faced. What were those conversations like? Uh let's dig into that a little bit. I want to get into governance as well. >>The conversations on the cultural change. I mean yes, we went through a hyper growth for the last year since obviously there were a lot of new joiners, a lot of different, very, very smart people joining the company which then results that collaboration uh >>got a bit more difficult. Of course >>there are times and changes, you have different different artifacts that you were created um and documentation that were flying around. Um so we were we had to build the company from scratch right? Um Of course this then resulted always this tension which I described before, but the most important part here is that data has always been a very important factor at l a fresh and we collected >>more of this >>data and continued to improve use data to improve the different key areas of our business. >>Um even >>when organizational struggles, the central organizational struggles data somehow always helped us to go through this this kind of change. Right? Um in the end those decentralized teams in our local geography ease started with solutions that serve the business which was very very important otherwise wouldn't be at the place where we are today but they did by all late best practices and standards and I always used sport analogy Dave So like any sport, there are different rules and regulations that need to be followed. These rules are defined by calling the sports association and this is what you can think about data governance and compliance team. Now we add the players to it who need to follow those rules and bite by them. This is what we then called data management. Now we have the different players and professionals, they need to be trained and understand the strategy and it rules before they can play. And this is what I then called data literacy. So we realized that we need to focus on helping our teams to develop those capabilities and teach the standards for how work is being done to truly drive functional excellence in a different domains. And one of our mission of our data literacy program for example is to really empower >>every employee at hello >>fresh everyone to make the right data informs decisions by providing data education that scaled by royal Entry team. Then this can be different things, different things like including data capabilities, um, with the learning paths for example. Right? So help them to create and deploy data products connecting data producers and data consumers and create a common sense and more understanding of each other's dependencies, which is important, for example, S. S. L. O. State of contracts and etcetera. Um, people getting more of a sense of ownership and responsibility. Of course, we have to define what it means, what does ownership means? But the responsibility means. But we're teaching this to our colleagues via individual learning patterns and help them up skill to use. Also, there's shared infrastructure and those self self service applications and overall to summarize, we're still in this progress of of, of learning, we are still learning as well. So learning never stops the tele fish, but we are really trying this um, to make it as much fun as possible. And in the end we all know user behavior has changed through positive experience. Uh, so instead of having massive training programs over endless courses of workshops, um, leaving our new journalists and colleagues confused and overwhelmed. >>We're applying um, >>game ification, right? So split different levels of certification where our colleagues can access, have had access points, they can earn badges along the way, which then simplifies the process of learning and engagement of the users and this is what we see in surveys, for example, where our employees that your justification approach a lot and are even competing to collect Those learning path batteries to become the # one on the leader board. >>I love the game ification, we've seen it work so well and so many different industries, not the least of which is crypto so you've identified some of the process gaps uh that you, you saw it is gloss over them. Sometimes I say paved the cow path. You didn't try to force, in other words, a new architecture into the legacy processes. You really have to rethink your approach to data management. So what what did that entail? >>Um, to rethink the way of data management. 100%. So if I take the example of Revolution, Industrial Revolution or classical supply chain revolution, but just imagine that you have been riding a horse, for example, your whole life and suddenly you can operate a car or you suddenly receive just a complete new way of transporting assets from A to B. Um, so we needed to establish a new set of cross functional business processes to run faster, dry faster, um, more robustly and deliver data products which can be trusted and used by downstream processes and systems. Hence we had a subset of new standards and new procedures that would fall into the internal data governance and compliance sector with internal, I'm always referring to the data operations around new things like data catalog, how to identify >>ownership, >>how to change ownership, how to certify data assets, everything around classical software development, which we know apply to data. This this is similar to a new thinking, right? Um deployment, versioning, QA all the different things, ingestion policies, policing procedures, all the things that suffer. Development has been doing. We do it now with data as well. And in simple terms, it's a whole redesign of the supply chain of our data with new procedures and new processes and as a creation as management and as a consumption. >>So data has become kind of the new development kit. If you will um I want to shift gears and talk about the notion of data product and, and we have a slide uh that we pulled from your deck and I'd like to unpack it a little bit. Uh I'll just, if you can bring that up, I'll read it. A data product is a product whose primary objective is to leverage on data to solve customer problems where customers, both internal and external. So pretty straightforward. I know you've gone much deeper and you're thinking and into your organization, but how do you think about that And how do you determine for instance who owns what? How did you get everybody to agree? >>I can take that one. Um, maybe let me start with the data product. So I think um that's an ongoing debate. Right? And I think the debate itself is an important piece here, right? That visit the debate, you clarify what we actually mean by that product and what is actually the mindset. So I think just from a definition perspective, right? I think we find the common denominator that we say okay that our product is something which is important for the company has come to its value what you mean by that. Okay, it's it's a solution to a customer problem that delivers ideally maximum value to the business. And yes, it leverages the power of data and we have a couple of examples but it had a fresh year, the historical and classical ones around dashboards for example, to monitor or error rates but also more sophisticated ways for example to incorporate machine learning algorithms in our recipe recommendations. However, I think the important aspects of the data product is a there is an owner, right? There's someone accountable for making sure that the product that we are providing is actually served and is maintained and there are, there is someone who is making sure that this actually keeps the value of that problem thing combined with the idea of the proper documentation, like a product description, right that people understand how to use their bodies is about and related to that peace is the idea of it is a purpose. Right? You need to understand or ask ourselves, Okay, why does this thing exist does it provide the value that you think it does. That leads into a good understanding about the life cycle of the data product and life cycle what we mean? Okay from the beginning from the creation you need to have a good understanding, we need to collect feedback, we need to learn about that. We need to rework and actually finally also to think about okay benefits time to decommission piece. So overall, I think the core of the data product is product thinking 11 right that we start the point is the starting point needs to be the problem and not the solution and this is essentially what we have seen what was missing but brought us to this kind of data spaghetti that we have built there in in Russia, essentially we built at certain data assets, develop in isolation and continuously patch the solution just to fulfill these articles that we got and actually these aren't really understanding of the stakeholder needs and the interesting piece as a result in duplication of work and this is not just frustrating and probably not the most efficient way how the company should work. But also if I build the same that assets but slightly different assumption across the company and multiple teams that leads to data inconsistency and imagine the following too narrow you as a management for management perspective, you're asking basically a specific question and you get essentially from a couple of different teams, different kind of grass, different kind of data and numbers and in the end you do not know which ones to trust. So there's actually much more ambiguity and you do not know actually is a noise for times of observing or is it just actually is there actually a signal that I'm looking for? And the same is if I'm running in a B test right, I have a new future, I would like to understand what has it been the business impact of this feature. I run that specific source in an unfortunate scenario. Your production system is actually running on a different source. You see different numbers. What you've seen in a B test is actually not what you see then in production typical thing then is you're asking some analytics tend to actually do a deep dive to understand where the discrepancies are coming from. The worst case scenario. Again, there's a different kind of source. So in the end it's a pretty frustrating scenario and that's actually based of time of people that have to identify the root cause of this divergence. So in a nutshell, the highest degree of consistency is actually achieved that people are just reusing Dallas assets and also in the media talk that we have given right, we we start trying to establish this approach for a B testing. So we have a team but just providing or is kind of owning their target metric associated business teams and they're providing that as a product also to other services including the A B testing team, they'll be testing team can use this information defines an interface is okay I'm joining this information that the metadata of an experiment and in the end after the assignment after this data collection face, they can easily add a graph to the dashboard. Just group by the >>Beatles Hungarian. >>And we have seen that also in other companies. So it's not just a nice dream that we have right. I have actually worked in other companies where we worked on search and we established a complete KPI pipeline that was computing all this information. And this information was hosted by the team and it was used for everything A B test and deep dives and and regular reporting. So uh just one of the second the important piece now, why I'm coming back to that is that requires that we are treating this data as a product right? If you want to have multiple people using the things that I am owning and building, we have to provide this as a trust mercy asset and in a way that it's easy for people to discover and actually work with. >>Yeah. And coming back to that. So this is to me this is why I get so excited about data mesh because I really do think it's the right direction for organizations. When people hear data product they say well, what does that mean? Uh but then when you start to sort of define it as you did, it's it's using data to add value, that could be cutting costs, that could be generating revenue, it could be actually directly you're creating a product that you monetize, So it's sort of in the eyes of the beholder. But I think the other point that we've made is you made it earlier on to and again, context. So when you have a centralized data team and you have all these P NL managers a lot of times they'll question the data because they don't own it. They're like wait a minute. If they don't, if it doesn't agree with their agenda, they'll attack the data. But if they own the data then they're responsible for defending that and that is a mindset change, that's really important. Um And I'm curious uh is how you got to, you know, that ownership? Was it a was it a top down with somebody providing leadership? Was it more organic bottom up? Was it a sort of a combination? How do you decide who owned what in other words, you know, did you get, how did you get the business to take ownership of the data and what is owning? You know, the data actually mean? >>That's a very good question. Dave I think this is one of the pieces where I think we have a lot of learnings and basically if you ask me how we could start the feeling. I think that would be the first piece. Maybe we need to start to really think about how that should be approached if it stopped his ownership. Right? It means somehow that the team has a responsibility to host and self the data efforts to minimum acceptable standards. This minimum dependencies up and down string. The interesting piece has been looking backwards. What what's happening is that under that definition has actually process that we have to go through is not actually transferring ownership from the central team to the distributor teams. But actually most cases to establish ownership, I make this difference because saying we have to transfer ownership actually would erroneously suggests that the data set was owned before. But this platform team, yes, they had the capability to make the changes on data pipelines, but actually the analytics team, they're always the ones who had the business understands, you use cases and but no one actually, but it's actually expensive expected. So we had to go through this very lengthy process and establishing ownership. We have done that, as in the beginning, very naively. They have started, here's a document here, all the data assets, what is probably the nearest neighbor who can actually take care of that and then we we moved it over. But the problem here is that all these things is kind of technical debt, right? It's not really properly documented, pretty unstable. It was built in a very inconsistent over years and these people who have built this thing have already left the company. So there's actually not a nice thing that is that you want to see and people build up a certain resistance, e even if they have actually bought into this idea of domain ownership. So if you ask me these learnings, but what needs to happen as first, the company needs to really understand what our core business concept that they have, they need to have this mapping from. These are the core business concept that we have. These are the domain teams who are owning this concept and then actually link that to the to the assets and integrated better with both understanding how we can evolve actually, the data assets and new data build things new in the in this piece in the domain. But also how can we address reduction of technical death and stabilizing what we have already. >>Thank you for that christoph. So I want to turn a direction here and talk about governance and I know that's an area that's passionate, you're passionate about. Uh I pulled this slide from your deck, which I kind of messed up a little bit sorry for that, but but by the way, we're going to publish a link to the full video that you guys did. So we'll share that with folks. But it's one of the most challenging aspects of data mesh, if you're going to decentralize you, you quickly realize this could be the Wild West as we talked about all over again. So how are you approaching governance? There's a lot of items on this slide that are, you know, underscore the complexity, whether it's privacy, compliance etcetera. So, so how did you approach this? >>It's yeah, it's about connecting those dots. Right. So the aim of the data governance program is about the autonomy of every team was still ensuring that everybody has the right interoperability. So when we want to move from the Wild West riding horses to a civilised way of transport, um you can take the example of modern street traffic, like when all participants can manoeuvre independently and as long as they follow the same rules and standards, everybody can remain compatible with each other and understand and learn from each other so we can avoid car crashes. So when I go from country to country, I do understand what the street infrastructure means. How do I drive my car? I can also read the traffic lights in the different signals. Um, so likewise as a business and Hello Fresh, we do operate autonomously and consequently need to follow those external and internal rules and standards to set forth by the redistribution in which we operate so in order to prevent a car crash, we need to at least ensure compliance with regulations to account for society's and our customers increasing concern with data protection and privacy. So teaching and advocating this advantage, realizing this to everyone in the company um was a key community communication strategy and of course, I mean I mentioned data privacy external factors, the same goes for internal regulations and processes to help our colleagues to adapt to this very new environment. So when I mentioned before the new way of thinking the new way of um dealing and managing data, this of course implies that we need new processes and regulations for our colleagues as well. Um in a nutshell then this means the data governance provides a framework for managing our people the processes and technology and culture around our data traffic. And those components must come together in order to have this effective program providing at least a common denominator, especially critical for shared dataset, which we have across our different geographies managed and shared applications on shared infrastructure and applications and is then consumed by centralized processes um for example, master data, everything and all the metrics and KPI s which are also used for a central steering. Um it's a big change day. Right. And our ultimate goal is to have this noninvasive, Federated um ultimatum and computational governance and for that we can't just talk about it. We actually have to go deep and use case by use case and Qc buy PVC and generate learnings and learnings with the different teams. And this would be a classical approach of identifying the target structure, the target status, match it with the current status by identifying together with the business teams with the different domains have a risk assessment for example, to increase transparency because a lot of teams, they might not even know what kind of situation they might be. And this is where this training and this piece of illiteracy comes into place where we go in and trade based on the findings based on the most valuable use case um and based on that help our teams to do this change to increase um their capability just a little bit more and once they hand holding. But a lot of guidance >>can I kind of kind of trying to quickly David will allow me I mean there's there's a lot of governance piece but I think um that is important. And if you're talking about documentation for example, yes, we can go from team to team and tell these people how you have to document your data and data catalog or you have to establish data contracts and so on the force. But if you would like to build data products at scale following actual governance, we need to think about automation right. We need to think about a lot of things that we can learn from engineering before. And that starts with simple things like if we would like to build up trust in our data products, right, and actually want to apply the same rigor and the best practices that we know from engineering. There are things that we can do and we should probably think about what we can copy and one example might be. So the level of service level agreements, service level objectives. So that level indicators right, that represent on on an engineering level, right? If we're providing services there representing the promises we made to our customers or consumers, these are the internal objectives that help us to keep those promises. And actually these are the way of how we are tracking ourselves, how we are doing. And this is just one example of that thing. The Federated Governor governance comes into play right. In an ideal world, we should not just talk about data as a product but also data product. That's code that we say, okay, as most as much as possible. Right? Give the engineers the tool that they are familiar basis and actually not ask the product managers for example to document their data assets in the data catalog but make it part of the configuration. Have this as a, as a C D C I, a continuous delivery pipeline as we typically see another engineering task through and services we say, okay, there is configuration, we can think about pr I can think about data quality monitoring, we can think about um the ingestion data catalog and so on and forest, I think ideally in the data product will become of a certain templates that can be deployed and are actually rejected or verified at build time before we actually make them deploy them to production. >>Yeah, So it's like devoPS for data product um so I'm envisioning almost a three phase approach to governance and you kind of, it sounds like you're in early phases called phase zero where there's there's learning, there's literacy, there's training, education, there's kind of self governance and then there's some kind of oversight, some a lot of manual stuff going on and then you you're trying to process builders at this phase and then you codify it and then you can automate it. Is that fair? >>Yeah, I would rather think think about automation as early as possible in the way and yes, there needs to be certain rules but then actually start actually use case by use case. Is there anything that small piece that we can already automate? It's as possible. Roll that out and then actually extended step by step, >>is there a role though that adjudicates that? Is there a central Chief state officer who is responsible for making sure people are complying or is it how do you handle that? >>I mean from a from a from a platform perspective, yes, we have a centralized team to uh implement certain pieces they'll be saying are important and actually would like to implement. However, that is actually working very closely with the governance department. So it's Clements piece to understand and defy the policies that needs to be implemented. >>So Clements essentially it's it's your responsibility to make sure that the policy is being followed. And then as you were saying, christoph trying to compress the time to automation as fast as possible percent. >>So >>it's really it's uh >>what needs to be really clear that it's always a split effort, Right? So you can't just do one thing or the other thing, but everything really goes hand in hand because for the right automation for the right engineering tooling, we need to have the transparency first. Uh I mean code needs to be coded so we kind of need to operate on the same level with the right understanding. So there's actually two things that are important which is one its policies and guidelines, but not only that because more importantly or even well equally important to align with the end user and tech teams and engineering and really bridge between business value business teams and the engineering teams. >>Got it. So just a couple more questions because we gotta wrap I want to talk a little bit about the business outcome. I know it's hard to quantify and I'll talk about that in a moment but but major learnings, we've got some of the challenges that you cited. I'll just put them up here. We don't have to go detailed into this, but I just wanted to share with some folks. But my question, I mean this is the advice for your peers question if you had to do it differently if you had a do over or a Mulligan as we like to say for you golfers, what would you do differently? Yeah, >>I mean can we start with from a from the transformational challenge that understanding that it's also high load of cultural change. I think this is this is important that a particular communication strategy needs to be put into place and people really need to be um supported. Right? So it's not that we go in and say well we have to change towards data mesh but naturally it's in human nature, you know, we're kind of resistance to to change right? Her speech uncomfortable. So we need to take that away by training and by communicating um chris we're gonna add something to that >>and definitely I think the point that I have also made before right we need to acknowledge that data mesh is an architecture of scale, right? You're looking for something which is necessary by huge companies who are vulnerable, data productive scale. I mean Dave you mentioned it right, there are a lot of advantages to have a centralized team but at some point it may make sense to actually decentralized here and at this point right? If you think about data Mash, you have to recognize that you're not building something on a green field. And I think there's a big learning which is also reflected here on the slide is don't underestimate your baggage. It's typically you come to a point where the old model doesn't doesn't broke anymore and has had a fresh right? We lost our trust in our data and actually we have seen certain risks that we're slowing down our innovation so we triggered that this was triggering the need to actually change something. So this transition implies that you typically have a lot of technical debt accumulated over years and I think what we have learned is that potentially we have decentralized some assets to earlier, this is not actually taking into account the maturity of the team where we are actually distributed to and now we actually in the face of correcting pieces of that one. Right? But I think if you if you if you start from scratch you have to understand, okay, is are my team is actually ready for taking on this new uh, this news capabilities and you have to make sure that business decentralization, you build up these >>capabilities and the >>teams and as Clements has mentioned, right, make sure that you take the people on your journey. I think these are the pieces that also here, it comes with this knowledge gap, right? That we need to think about hiring and literacy the technical depth I just talked about and I think the last piece that I would add now which is not here on the flight deck is also from our perspective, we started on the analytical layer because that's kind of where things are exploding, right, this is the thing that people feel the pain but I think a lot of the efforts that we have started to actually modernize the current state uh, towards data product towards data Mash. We've understood that it always comes down basically to a proper shape of our operational plane and I think what needs to happen is is I think we got through a lot of pains but the learning here is this need to really be a commitment from the company that needs to happen and to act. >>I think that point that last point you made it so critical because I I hear a lot from the vendor community about how they're gonna make analytics better and that's that's not unimportant, but but through data product thinking and decentralized data organizations really have to operationalize in order to scale. So these decisions around data architecture an organization, their fundamental and lasting, it's not necessarily about an individual project are why they're gonna be project sub projects within this architecture. But the architectural decision itself is an organizational, its cultural and what's the best approach to support your business at scale. It really speaks to to to what you are, who you are as a company, how you operate and getting that right, as we've seen in the success of data driven driven companies is yields tremendous results. So I'll ask each of you to give give us your final thoughts and then we'll wrap maybe >>maybe it quickly, please. Yeah, maybe just just jumping on this piece that you have mentioned, right, the target architecture. If we talk about these pieces right, people often have this picture of mind like OK, there are different kind of stages, we have sources, we have actually ingestion layer, we have historical transformation presentation layer and then we're basically putting a lot of technology on top of that kind of our target architecture. However, I think what we really need to make sure is that we have these different kind of viewers, right? We need to understand what are actually the capabilities that we need in our new goals. How does it look and feel from the different kind of personas and experience view? And then finally, that should actually go to the to the target architecture from a technical perspective um maybe just to give an outlook but what we're what we're planning to do, how we want to move that forward. We have actually based on our strategy in the in the sense of we would like to increase that to maturity as a whole across the entire company and this is kind of a framework around the business strategy and it's breaking down into four pillars as well. People meaning the data, cultural, data literacy, data organizational structure and so on that. We're talking about governance as Clements has actually mentioned that, right, compliance, governance, data management and so on. You talk about technology and I think we could talk for hours for that one. It's around data platform, better science platform and then finally also about enablement through data, meaning we need to understand that a quality data accessibility and the science and data monetization. >>Great, thank you christophe clement. Once you bring us home give us your final thoughts. >>Can't can just agree with christoph that uh important is to understand what kind of maturity people have to understand what the maturity level, where the company where where people organization is and really understand what does kind of some kind of a change replies to that those four pillars for example, um what needs to be taken first and this is not very clear from the very first beginning of course them it's kind of like Greenfield you come up with must wins to come up with things that we really want to do out of theory and out of different white papers. Um only if you really start conducting the first initiatives you do understand. Okay, where we have to put the starts together and where do I missed out on one of those four different pillars? People, process technology and governance. Right? And then that kind of an integration. Doing step by step, small steps by small steps not boiling the ocean where you're capable ready to identify the gaps and see where either you can fill um the gaps are where you have to increase maturity first and train people or increase your text text, >>you know Hello Fresh is an excellent example of a company that is innovating. It was not born in Silicon Valley which I love. It's a global company. Uh and I gotta ask you guys, it seems like this is an amazing place to work you guys hiring? >>Yes, >>definitely. We do >>uh as many rights as was one of these aspects distributing. And actually we are hiring as an entire company specifically for data. I think there are a lot of open roles serious. Please visit or our page from better engineering, data, product management and Clemens has a lot of rules that you can speak about. But yes >>guys, thanks so much for sharing with the cube audience, your, your pioneers and we look forward to collaborations in the future to track progress and really want to thank you for your time. >>Thank you very much. Thank you very much. Dave >>thank you for watching the cubes startup showcase made possible by A W. S. This is Dave Volonte. We'll see you next time. >>Yeah.

momentum is gathering [Music] business is evolving more and more quickly moving through one transformation to the next because change never stops it only accelerates this is a world that demands a new kind of compute deployed from edge to core to cloud compute that can outpace the rapidly changing needs of businesses large and small unlocking new insights turning data into outcomes empowering new experiences compute that can scale up or scale down with minimum investment and effort guided by years of expertise protected by 360-degree security served up as a service to let it control own and manage massive workloads that weren't there yesterday and might not be there tomorrow this is the compute power that will drive progress giving your business what you need to be ready for what's next this is the compute power of hpe delivering your foundation for digital transformation welcome to accelerating next thank you so much for joining us today we have a great program we're going to talk tech with experts we'll be diving into the changing economics of our industry and how to think about the next phase of your digital transformation now very importantly we're also going to talk about how to optimize workloads from edge to exascale with full security and automation all coming to you as a service and with me to kick things off is neil mcdonald who's the gm of compute at hpe neil always a pleasure great to have you on it's great to see you dave now of course when we spoke a year ago you know we had hoped by this time we'd be face to face but you know here we are again you know this pandemic it's obviously affected businesses and people in in so many ways that we could never have imagined but in the reality is in reality tech companies have literally saved the day let's start off how is hpe contributing to helping your customers navigate through things that are so rapidly shifting in the marketplace well dave it's nice to be speaking to you again and i look forward to being able to do this in person some point the pandemic has really accelerated the need for transformation in businesses of all sizes more than three-quarters of cios report that the crisis has forced them to accelerate their strategic agendas organizations that were already transforming or having to transform faster and organizations that weren't on that journey yet are having to rapidly develop and execute a plan to adapt to this new reality our customers are on this journey and they need a partner for not just the compute technology but also the expertise and economics that they need for that digital transformation and for us this is all about unmatched optimization for workloads from the edge to the enterprise to exascale with 360 degree security and the intelligent automation all available in that as a service experience well you know as you well know it's a challenge to manage through any transformation let alone having to set up remote workers overnight securing them resetting budget priorities what are some of the barriers that you see customers are working hard to overcome simply per the organizations that we talk with are challenged in three areas they need the financial capacity to actually execute a transformation they need the access to the resource and the expertise needed to successfully deliver on a transformation and they have to find the way to match their investments with the revenues for the new services that they're putting in place to service their customers in this environment you know we have a data partner called etr enterprise technology research and the spending data that we see from them is it's quite dramatic i mean last year we saw a contraction of roughly five percent of in terms of i.t spending budgets etc and this year we're seeing a pretty significant rebound maybe a six to seven percent growth range is the prediction the challenge we see is organizations have to they've got to iterate on that i call it the forced march to digital transformation and yet they also have to balance their investments for example at the corporate headquarters which have kind of been neglected is there any help in sight for the customers that are trying to reduce their spend and also take advantage of their investment capacity i think you're right many businesses are understandably reluctant to loosen the purse strings right now given all of the uncertainty and often a digital transformation is viewed as a massive upfront investment that will pay off in the long term and that can be a real challenge in an environment like this but it doesn't need to be we work through hpe financial services to help our customers create the investment capacity to accelerate the transformation often by leveraging assets they already have and helping them monetize them in order to free up the capacity to accelerate what's next for their infrastructure and for their business so can we drill into that i wonder if we could add some specifics i mean how do you ensure a successful outcome what are you really paying attention to as those sort of markers for success well when you think about the journey that an organization is going through it's tough to be able to run the business and transform at the same time and one of the constraints is having the people with enough bandwidth and enough expertise to be able to do both so we're addressing that in two ways for our customers one is by helping them confidently deploy new solutions which we have engineered leveraging decades of expertise and experience in engineering to deliver those workload optimized portfolios that take the risk and the complexity out of assembling some of these solutions and give them a pre-packaged validated supported solution intact that simplifies that work for them but in other cases we can enhance our customers bandwidth by bringing them hpe point next experts with all of the capabilities we have to help them plan deliver and support these i.t projects and transformations organizations can get on a faster track of modernization getting greater insight and control as they do it we're a trusted partner to get the most for a business that's on this journey in making these critical compute investments to underpin the transformations and whether that's planning to optimizing to safe retirement at the end of life we can bring that expertise to bayer to help amplify what our customers already have in-house and help them accelerate and succeed in executing these transformations thank you for that neil so let's talk about some of the other changes that customers are seeing and the cloud has obviously forced customers and their suppliers to really rethink how technology is packaged how it's consumed how it's priced i mean there's no doubt in that to take green lake it's obviously a leading example of a pay as pay-as-you-scale infrastructure model and it could be applied on-prem or hybrid can you maybe give us a sense as to where you are today with green lake well it's really exciting you know from our first pay-as-you-go offering back in 2006 15 years ago to the introduction of green lake hpe has really been paving the way on consumption-based services through innovation and partnership to help meet the exact needs of our customers hpe green lake provides an experience that's the best of both worlds a simple pay-per-use technology model with the risk management of data that's under our customers direct control and it lets customers shift to everything as a service in order to free up capital and avoid that upfront expense that we talked about they can do this anywhere at any scale or any size and really hpe green lake is the cloud that comes to you like that so we've touched a little bit on how customers can maybe overcome some of the barriers to transformation what about the nature of transformations themselves i mean historically there was a lot of lip service paid to digital and and there's a lot of complacency frankly but you know that covered wrecking ball meme that so well describes that if you're not a digital business essentially you're going to be out of business so neil as things have evolved how is hpe addressed the new requirements well the new requirements are really about what customers are trying to achieve and four very common themes that we see are enabling the productivity of a remote workforce that was never really part of the plan for many organizations being able to develop and deliver new apps and services in order to service customers in a different way or drive new revenue streams being able to get insights from data so that in these tough times they can optimize their business more thoroughly and then finally think about the efficiency of an agile hybrid private cloud infrastructure especially one that now has to integrate the edge and we're really thrilled to be helping our customers accelerate all of these and more with hpe compute i want to double click on that remote workforce productivity i mean again the surveys that we see 46 percent of the cios say that productivity improved with the whole work from home remote work trend and on average those improvements were in the four percent range which is absolutely enormous i mean when you think about that how does hpe specifically you know help here what do you guys do well every organization in the world has had to adapt to a different style of working and with more remote workers than they had before and for many organizations that's going to become the new normal even post pandemic many it shops are not well equipped for the infrastructure to provide that experience because if all your workers are remote the resiliency of that infrastructure the latencies of that infrastructure the reliability of are all incredibly important so we provide comprehensive solutions expertise and as a service options that support that remote work through virtual desktop infrastructure or vdi so that our customers can support that new normal of virtual engagements online everything across industries wherever they are and that's just one example of many of the workload optimized solutions that we're providing for our customers is about taking out the guesswork and the uncertainty in delivering on these changes that they have to deploy as part of their transformation and we can deliver that range of workload optimized solutions across all of these different use cases because of our broad range of innovation in compute platforms that span from the ruggedized edge to the data center all the way up to exascale and hpc i mean that's key if you're trying to affect the digital transformation and you don't have to fine-tune you know be basically build your own optimized solutions if i can buy that rather than having to build it and rely on your r d you know that's key what else is hpe doing you know to deliver things new apps new services you know your microservices containers the whole developer trend what's going on there well that's really key because organizations are all seeking to evolve their mix of business and bring new services and new capabilities new ways to reach their customers new way to reach their employees new ways to interact in their ecosystem all digitally and that means app development and many organizations of course are embracing container technology to do that today so with the hpe container platform our customers can realize that agility and efficiency that comes with containerization and use it to provide insights to their data more and more that data of course is being machine generated or generated at the edge or the near edge and it can be a real challenge to manage that data holistically and not have silos and islands an hpe esmerald data fabric speeds the agility and access to data with a unified platform that can span across the data centers multiple clouds and even the edge and that enables data analytics that can create insights powering a data-driven production-oriented cloud-enabled analytics and ai available anytime anywhere in any scale and it's really exciting to see the kind of impact that that can have in helping businesses optimize their operations in these challenging times you got to go where the data is and the data is distributed it's decentralized so i i i like the esmerel of vision and execution there so that all sounds good but with digital transformation you get you're going to see more compute in in hybrid's deployments you mentioned edge so the surface area it's like the universe it's it's ever-expanding you mentioned you know remote work and work from home before so i'm curious where are you investing your resources from a cyber security perspective what can we count on from hpe there well you can count on continued leadership from hpe as the world's most secure industry standard server portfolio we provide an enhanced and holistic 360 degree view to security that begins in the manufacturing supply chain and concludes with a safeguarded end-of-life decommissioning and of course we've long set the bar for security with our work on silicon root of trust and we're extending that to the application tier but in addition to the security customers that are building this modern hybrid are private cloud including the integration of the edge need other elements too they need an intelligent software-defined control plane so that they can automate their compute fleets from all the way at the edge to the core and while scale and automation enable efficiency all private cloud infrastructures are competing with web scale economics and that's why we're democratizing web scale technologies like pinsando to bring web scale economics and web scale architecture to the private cloud our partners are so important in helping us serve our customers needs yeah i mean hp has really upped its ecosystem game since the the middle of last decade when when you guys reorganized it you became like even more partner friendly so maybe give us a preview of what's coming next in that regard from today's event well dave we're really excited to have hp's ceo antonio neri speaking with pat gelsinger from intel and later lisa sue from amd and later i'll have the chance to catch up with john chambers the founder and ceo of jc2 ventures to discuss the state of the market today yeah i'm jealous you guys had some good interviews coming up neil thanks so much for joining us today on the virtual cube you've really shared a lot of great insight how hpe is partnering with customers it's it's always great to catch up with you hopefully we can do so face to face you know sooner rather than later well i look forward to that and uh you know no doubt our world has changed and we're here to help our customers and partners with the technology the expertise and the economics they need for these digital transformations and we're going to bring them unmatched workload optimization from the edge to exascale with that 360 degree security with the intelligent automation and we're going to deliver it all as an as a service experience we're really excited to be helping our customers accelerate what's next for their businesses and it's been really great talking with you today about that dave thanks for having me you're very welcome it's been super neal and i actually you know i had the opportunity to speak with some of your customers about their digital transformation and the role of that hpe plays there so let's dive right in we're here on the cube covering hpe accelerating next and with me is rule siestermans who is the head of it at the netherlands cancer institute also known as nki welcome rule thank you very much great to be here hey what can you tell us about the netherlands cancer institute maybe you could talk about your core principles and and also if you could weave in your specific areas of expertise yeah maybe first introduction to the netherlands institute um we are one of the top 10 comprehensive cancers in the world and what we do is we combine a hospital for treating patients with cancer and a recent institute under one roof so discoveries we do we find within the research we can easily bring them back to the clinic and vis-a-versa so we have about 750 researchers and about 3 000 other employees doctors nurses and and my role is to uh to facilitate them at their best with it got it so i mean everybody talks about digital digital transformation to us it all comes down to data so i'm curious how you collect and take advantage of medical data specifically to support nki's goals maybe some of the challenges that your organization faces with the amount of data the speed of data coming in just you know the the complexities of data how do you handle that yeah it's uh it's it's it's challenge and uh yeah what we we have we have a really a large amount of data so we produce uh terabytes a day and we we have stored now more than one petabyte on data at this moment and yeah it's uh the challenge is to to reuse the data optimal for research and to share it with other institutions so that needs to have a flexible infrastructure for that so a fast really fast network uh big data storage environment but the real challenge is not not so much the i.t bus is more the quality of the data so we have a lot of medical systems all producing those data and how do we combine them and and yeah get the data fair so findable accessible interoperable and reusable uh for research uh purposes so i think that's the main challenge the quality of the data yeah very common themes that we hear from from other customers i wonder if you could paint a picture of your environment and maybe you can share where hpe solutions fit in what what value they bring to your organization's mission yeah i think it brings a lot of flexibility so what we did with hpe is that we we developed a software-defined data center and then a virtual workplace for our researchers and doctors and that's based on the hpe infrastructure and what we wanted to build is something that expect the needs of doctors and nurses but also the researchers and the two kind of different blood groups blood groups and with different needs so uh but we wanted to create one infrastructure because we wanted to make the connection between the hospital and the research that's that's more important so um hpe helped helped us not only with the the infrastructure itself but also designing the whole architecture of it and for example what we did is we we bought a lot of hardware and and and the hardware is really uh doing his his job between nine till five uh dennis everything is working within everyone is working within the institution but all the other time in evening and and nights hours and also the redundant environment we have for the for our healthcare uh that doesn't do nothing of much more or less uh in in those uh dark hours so what we created together with nvidia and hpe and vmware is that we we call it video by day compute by night so we reuse those those servers and those gpu capacity for computational research jobs within the research that's you mentioned flexibility for this genius and and so we're talking you said you know a lot of hard ways they're probably proliant i think synergy aruba networking is in there how are you using this environment actually the question really is when you think about nki's digital transformation i mean is this sort of the fundamental platform that you're using is it a maybe you could describe that yeah it's it's the fundamental platform to to to work on and and and what we see is that we have we have now everything in place for it but the real challenge is is the next steps we are in so we have a a software defined data center we are cloud ready so the next steps is to to make the connection to the cloud to to give more automation to our researchers so they don't have to wait a couple of weeks for it to do it but they can do it themselves with a couple of clicks so i think the basic is we are really flexible and we have a lot of opportunities for automation for example but the next step is uh to create that business value uh really for for our uh employees that's a great story and a very important mission really fascinating stuff thanks for sharing this with our audience today really appreciate your time thank you very much okay this is dave vellante with thecube stay right there for more great content you're watching accelerating next from hpe i'm really glad to have you with us today john i know you stepped out of vacation so thanks very much for joining us neil it's great to be joining you from hawaii and i love the partnership with hpe and the way you're reinventing an industry well you've always excelled john at catching market transitions and there are so many transitions and paradigm shifts happening in the market and tech specifically right now as you see companies rush to accelerate their transformation what do you see as the keys to success well i i think you're seeing actually an acceleration following the covet challenges that all of us faced and i wasn't sure that would happen it's probably at three times the paces before there was a discussion point about how quickly the companies need to go digital uh that's no longer a discussion point almost all companies are moving with tremendous feed on digital and it's the ability as the cloud moves to the edge with compute and security uh at the edge and how you deliver these services to where the majority of applications uh reside are going to determine i think the future of the next generation company leadership and it's the area that neil we're working together on in many many ways so i think it's about innovation it's about the cloud moving to the edge and an architectural play with silicon to speed up that innovation yes we certainly see our customers of all sizes trying to accelerate what's next and get that digital transformation moving even faster as a result of the environment that we're all living in and we're finding that workload focus is really key uh customers in all kinds of different scales are having to adapt and support the remote workforces with vdi and as you say john they're having to deal with the deployment of workloads at the edge with so much data getting generated at the edge and being acted upon at the edge the analytics and the infrastructure to manage that as these processes get digitized and automated is is so important for so many workflows we really believe that the choice of infrastructure partner that underpins those transformations really matters a partner that can help create the financial capacity that can help optimize your environments and enable our customers to focus on supporting their business are all super key to success and you mentioned that in the last year there's been a lot of rapid course correction for all of us a demand for velocity and the ability to deploy resources at scale is more and more needed maybe more than ever what are you hearing customers looking for as they're rolling out their digital transformation efforts well i think they're being realistic that they're going to have to move a lot faster than before and they're also realistic on core versus context they're they're their core capability is not the technology of themselves it's how to deploy it and they're we're looking for partners that can help bring them there together but that can also innovate and very often the leaders who might have been a leader in a prior generation may not be on this next move hence the opportunity for hpe and startups like vinsano to work together as the cloud moves the edge and perhaps really balance or even challenge some of the big big incumbents in this category as well as partners uniquely with our joint customers on how do we achieve their business goals tell me a little bit more about how you move from this being a technology positioning for hpe to literally helping your customers achieve their outcomes they want and and how are you changing hpe in that way well i think when you consider these transformations the infrastructure that you choose to underpin it is incredibly critical our customers need a software-defined management plan that enables them to automate so much of their infrastructure they need to be able to take faster action where the data is and to do all of this in a cloud-like experience where they can deliver their infrastructure as code anywhere from exascale through the enterprise data center to the edge and really critically they have to be able to do this securely which becomes an ever increasing challenge and doing it at the right economics relative to their alternatives and part of the right economics of course includes adopting the best practices from web scale architectures and bringing them to the heart of the enterprise and in our partnership with pensando we're working to enable these new ideas of web scale architecture and fleet management for the enterprise at scale you know what is fun is hpe has an unusual talent from the very beginning in silicon valley of working together with others and creating a win-win innovation approach if you watch what your team has been able to do and i want to say this for everybody listening you work with startups better than any other company i've seen in terms of how you do win win together and pinsando is just the example of that uh this startup which by the way is the ninth time i have done with this team a new generation of products and we're designing that together with hpe in terms of as the cloud moves to the edge how do we get the leverage out of that and produce the results for your customers on this to give the audience appeal for it you're talking with pensano alone in terms of the efficiency versus an amazon amazon web services of an order of magnitude i'm not talking 100 greater i'm talking 10x greater and things from throughput number of connections you do the jitter capability etc and it talks how two companies uniquely who believe in innovation and trust each other and have very similar cultures can work uniquely together on it how do you bring that to life with an hpe how do you get your company to really say let's harvest the advantages of your ecosystem in your advantages of startups well as you say more and more companies are faced with these challenges of hitting the right economics for the infrastructure and we see many enterprises of various sizes trying to come to terms with infrastructures that look a lot more like a service provider that require that software-defined management plane and the automation to deploy at scale and with the work we're doing with pinsando the benefits that we bring in terms of the observability and the telemetry and the encryption and the distributed network functions but also a security architecture that enables that efficiency on the individual nodes is just so key to building a competitive architecture moving forwards for an on-prem private cloud or internal service provider operation and we're really excited about the work we've done to bring that technology across our portfolio and bring that to our customers so that they can achieve those kind of economics and capabilities and go focus on their own transformations rather than building and running the infrastructure themselves artisanally and having to deal with integrating all of that great technology themselves makes tremendous sense you know neil you and i work on a board together et cetera i've watched your summarization skills and i always like to ask the question after you do a quick summary like this what are the three or four takeaways we would like for the audience to get out of our conversation well that's a great question thanks john we believe that customers need a trusted partner to work through these digital transformations that are facing them and confront the challenge of the time that the covet crisis has taken away as you said up front every organization is having to transform and transform more quickly and more digitally and working with a trusted partner with the expertise that only comes from decades of experience is a key enabler for that a partner with the ability to create the financial capacity to transform the workload expertise to get more from the infrastructure and optimize the environment so that you can focus on your own business a partner that can deliver the systems and the security and the automation that makes it easily deployable and manageable anywhere you need them at any scale whether the edge the enterprise data center or all the way up to exascale in high performance computing and can do that all as a service as we can at hpe through hpe green lake enabling our customers most critical workloads it's critical that all of that is underpinned by an ai powered digitally enabled service experience so that our customers can get on with their transformation and running their business instead of dealing with their infrastructure and really only hpe can provide this combination of capabilities and we're excited and committed to helping our customers accelerate what's next for their businesses neil it's fun i i love being your partner and your wingman our values and cultures are so similar thanks for letting me be a part of this discussion today thanks for being with us john it was great having you here oh it's friends for life okay now we're going to dig into the world of video which accounts for most of the data that we store and requires a lot of intense processing capabilities to stream here with me is jim brickmeyer who's the chief marketing and product officer at vlasics jim good to see you good to see you as well so tell us a little bit more about velocity what's your role in this tv streaming world and maybe maybe talk about your ideal customer sure sure so um we're leading provider of carrier great video solutions video streaming solutions and advertising uh technology to service providers around the globe so we primarily sell software-based solutions to uh cable telco wireless providers and broadcasters that are interested in launching their own um video streaming services to consumers yeah so this is this big time you know we're not talking about mom and pop you know a little video outfit but but maybe you can help us understand that and just the sheer scale of of the tv streaming that you're doing maybe relate it to you know the overall internet usage how much traffic are we talking about here yeah sure so uh yeah so our our customers tend to be some of the largest um network service providers around the globe uh and if you look at the uh the video traffic um with respect to the total amount of traffic that that goes through the internet video traffic accounts for about 90 of the total amount of data that uh that traverses the internet so video is uh is a pretty big component of um of how people when they look at internet technologies they look at video streaming technologies uh you know this is where we we focus our energy is in carrying that traffic as efficiently as possible and trying to make sure that from a consumer standpoint we're all consumers of video and uh make sure that the consumer experience is a high quality experience that you don't experience any glitches and that that ultimately if people are paying for that content that they're getting the value that they pay for their for their money uh in their entertainment experience i think people sometimes take it for granted it's like it's like we we all forget about dial up right those days are long gone but the early days of video was so jittery and restarting and and the thing too is that you know when you think about the pandemic and the boom in streaming that that hit you know we all sort of experienced that but the service levels were pretty good i mean how much how much did the pandemic affect traffic what kind of increases did you see and how did that that impact your business yeah sure so uh you know obviously while it was uh tragic to have a pandemic and have people locked down what we found was that when people returned to their homes what they did was they turned on their their television they watched on on their mobile devices and we saw a substantial increase in the amount of video streaming traffic um over service provider networks so what we saw was on the order of 30 to 50 percent increase in the amount of data that was traversing those networks so from a uh you know from an operator's standpoint a lot more traffic a lot more challenging to to go ahead and carry that traffic a lot of work also on our behalf and trying to help operators prepare because we could actually see geographically as the lockdowns happened [Music] certain areas locked down first and we saw that increase so we were able to help operators as as all the lockdowns happened around the world we could help them prepare for that increase in traffic i mean i was joking about dial-up performance again in the early days of the internet if your website got fifty percent more traffic you know suddenly you were you your site was coming down so so that says to me jim that architecturally you guys were prepared for that type of scale so maybe you could paint a picture tell us a little bit about the solutions you're using and how you differentiate yourself in your market to handle that type of scale sure yeah so we so we uh we really are focused on what we call carrier grade solutions which are designed for that massive amount of scale um so we really look at it you know at a very granular level when you look um at the software and and performance capabilities of the software what we're trying to do is get as many streams as possible out of each individual piece of hardware infrastructure so that we can um we can optimize first of all maximize the uh the efficiency of that device make sure that the costs are very low but one of the other challenges is as you get to millions and millions of streams and that's what we're delivering on a daily basis is millions and millions of video streams that you have to be able to scale those platforms out um in an effective in a cost effective way and to make sure that it's highly resilient as well so we don't we don't ever want a consumer to have a circumstance where a network glitch or a server issue or something along those lines causes some sort of uh glitch in their video and so there's a lot of work that we do in the software to make sure that it's a very very seamless uh stream and that we're always delivering at the very highest uh possible bit rate for consumers so that if you've got that giant 4k tv that we're able to present a very high resolution picture uh to those devices and what's the infrastructure look like underneath you you're using hpe solutions where do they fit in yeah that's right yeah so we uh we've had a long-standing partnership with hpe um and we work very closely with them to try to identify the specific types of hardware that are ideal for the the type of applications that we run so we run video streaming applications and video advertising applications targeted kinds of video advertising technologies and when you look at some of these applications they have different types of requirements in some cases it's uh throughput where we're taking a lot of data in and streaming a lot of data out in other cases it's storage where we have to have very high density high performance storage systems in other cases it's i gotta have really high capacity storage but the performance does not need to be quite as uh as high from an io perspective and so we work very closely with hpe on trying to find exactly the right box for the right application and then beyond that also talking with our customers to understand there are different maintenance considerations associated with different types of hardware so we tend to focus on as much as possible if we're going to place servers deep at the edge of the network we will make everything um maintenance free or as maintenance free as we can make it by putting very high performance solid state storage into those servers so that uh we we don't have to physically send people to those sites to uh to do any kind of maintenance so it's a it's a very cooperative relationship that we have with hpe to try to define those boxes great thank you for that so last question um maybe what the future looks like i love watching on my mobile device headphones in no distractions i'm getting better recommendations how do you see the future of tv streaming yeah so i i think the future of tv streaming is going to be a lot more personal right so uh this is what you're starting to see through all of the services that are out there is that most of the video service providers whether they're online providers or they're your traditional kinds of paid tv operators is that they're really focused on the consumer and trying to figure out what is of value to you personally in the past it used to be that services were one size fits all and um and so everybody watched the same program right at the same time and now that's uh that's we have this technology that allows us to deliver different types of content to people on different screens at different times and to advertise to those individuals and to cater to their individual preferences and so using that information that we have about how people watch and and what people's interests are we can create a much more engaging and compelling uh entertainment experience on all of those screens and um and ultimately provide more value to consumers awesome story jim thanks so much for keeping us helping us just keep entertained during the pandemic i really appreciate your time sure thanks all right keep it right there everybody you're watching hpes accelerating next first of all pat congratulations on your new role as intel ceo how are you approaching your new role and what are your top priorities over your first few months thanks antonio for having me it's great to be here with you all today to celebrate the launch of your gen 10 plus portfolio and the long history that our two companies share in deep collaboration to deliver amazing technology to our customers together you know what an exciting time it is to be in this industry technology has never been more important for humanity than it is today everything is becoming digital and driven by what i call the four key superpowers the cloud connectivity artificial intelligence and the intelligent edge they are super powers because each expands the impact of the others and together they are reshaping every aspect of our lives and work in this landscape of rapid digital disruption intel's technology and leadership products are more critical than ever and we are laser focused on bringing to bear the depth and breadth of software silicon and platforms packaging and process with at scale manufacturing to help you and our customers capitalize on these opportunities and fuel their next generation innovations i am incredibly excited about continuing the next chapter of a long partnership between our two companies the acceleration of the edge has been significant over the past year with this next wave of digital transformation we expect growth in the distributed edge and age build out what are you seeing on this front like you said antonio the growth of edge computing and build out is the next key transition in the market telecommunications service providers want to harness the potential of 5g to deliver new services across multiple locations in real time as we start building solutions that will be prevalent in a 5g digital environment we will need a scalable flexible and programmable network some use cases are the massive scale iot solutions more robust consumer devices and solutions ar vr remote health care autonomous robotics and manufacturing environments and ubiquitous smart city solutions intel and hp are partnering to meet this new wave head on for 5g build out and the rise of the distributed enterprise this build out will enable even more growth as businesses can explore how to deliver new experiences and unlock new insights from the new data creation beyond the four walls of traditional data centers and public cloud providers network operators need to significantly increase capacity and throughput without dramatically growing their capital footprint their ability to achieve this is built upon a virtualization foundation an area of intel expertise for example we've collaborated with verizon for many years and they are leading the industry and virtualizing their entire network from the core the edge a massive redesign effort this requires advancements in silicon and power management they expect intel to deliver the new capabilities in our roadmap so ecosystem partners can continue to provide innovative and efficient products with this optimization for hybrid we can jointly provide a strong foundation to take on the growth of data-centric workloads for data analytics and ai to build and deploy models faster to accelerate insights that will deliver additional transformation for organizations of all types the network transformation journey isn't easy we are continuing to unleash the capabilities of 5g and the power of the intelligent edge yeah the combination of the 5g built out and the massive new growth of data at the edge are the key drivers for the age of insight these new market drivers offer incredible new opportunities for our customers i am excited about recent launch of our new gen 10 plus portfolio with intel together we are laser focused on delivering joint innovation for customers that stretches from the edge to x scale how do you see new solutions that this helping our customers solve the toughest challenges today i talked earlier about the superpowers that are driving the rapid acceleration of digital transformation first the proliferation of the hybrid cloud is delivering new levels of efficiency and scale and the growth of the cloud is democratizing high-performance computing opening new frontiers of knowledge and discovery next we see ai and machine learning increasingly infused into every application from the edge to the network to the cloud to create dramatically better insights and the rapid adoption of 5g as i talked about already is fueling new use cases that demand lower latencies and higher bandwidth this in turn is pushing computing to the edge closer to where the data is created and consumed the confluence of these trends is leading to the biggest and fastest build out of computing in human history to keep pace with this rapid digital transformation we recognize that infrastructure has to be built with the flexibility to support a broad set of workloads and that's why over the last several years intel has built an unmatched portfolio to deliver every component of intelligent silicon our customers need to move store and process data from the cpus to fpgas from memory to ssds from ethernet to switch silicon to silicon photonics and software our 3rd gen intel xeon scalable processors and our data centric portfolio deliver new core performance and higher bandwidth providing our customers the capabilities they need to power these critical workloads and we love seeing all the unique ways customers like hpe leverage our technology and solution offerings to create opportunities and solve their most pressing challenges from cloud gaming to blood flow to brain scans to financial market security the opportunities are endless with flexible performance i am proud of the amazing innovation we are bringing to support our customers especially as they respond to new data-centric workloads like ai and analytics that are critical to digital transformation these new requirements create a need for compute that's warlord optimized for performance security ease of use and the economics of business now more than ever compute matters it is the foundation for this next wave of digital transformation by pairing our compute with our software and capabilities from hp green lake we can support our customers as they modernize their apps and data quickly they seamlessly and securely scale them anywhere at any size from edge to x scale but thank you for joining us for accelerating next today i know our audience appreciated hearing your perspective on the market and how we're partnering together to support their digital transformation journey i am incredibly excited about what lies ahead for hp and intel thank you thank you antonio great to be with you today we just compressed about a decade of online commerce progress into about 13 or 14 months so now we're going to look at how one retailer navigated through the pandemic and what the future of their business looks like and with me is alan jensen who's the chief information officer and senior vice president of the sawing group hello alan how are you fine thank you good to see you hey look you know when i look at the 100 year history plus of your company i mean it's marked by transformations and some of them are quite dramatic so you're denmark's largest retailer i wonder if you could share a little bit more about the company its history and and how it continues to improve the customer experience well at the same time keeping costs under control so vital in your business yeah yeah the company founded uh approximately 100 years ago with a department store in in oahu's in in denmark and i think in the 60s we founded the first supermarket in in denmark with the self-service and combined textile and food in in the same store and in beginning 70s we founded the first hyper market in in denmark and then the this calendar came from germany early in in 1980 and we started a discount chain and so we are actually building department store in hyber market info in in supermarket and in in the discount sector and today we are more than 1 500 stores in in three different countries in in denmark poland and germany and especially for the danish market we have a approximately 38 markets here and and is the the leader we have over the last 10 years developed further into online first in non-food and now uh in in food with home delivery with click and collect and we have done some magnetism acquisition in in the convenience with mailbox solutions to our customers and we have today also some restaurant burger chain and and we are running the starbuck in denmark so i can you can see a full plate of different opportunities for our customer in especially denmark it's an awesome story and of course the founder's name is still on the masthead what a great legacy now of course the pandemic is is it's forced many changes quite dramatic including the the behaviors of retail customers maybe you could talk a little bit about how your digital transformation at the sawing group prepared you for this shift in in consumption patterns and any other challenges that that you faced yeah i think uh luckily as for some of the you can say the core it solution in in 19 we just roll out using our computers via direct access so you can work from anywhere whether you are traveling from home and so on we introduced a new agile scrum delivery model and and we just finalized the rolling out teams in in in january february 20 and that was some very strong thing for suddenly moving all our employees from from office to to home and and more or less overnight we succeed uh continuing our work and and for it we have not missed any deadline or task for the business in in 2020 so i think that was pretty awesome to to see and for the business of course the pandemic changed a lot as the change in customer behavior more or less overnight with plus 50 80 on the online solution forced us to do some different priorities so we were looking at the food home delivery uh and and originally expected to start rolling out in in 2022 uh but took a fast decision in april last year to to launch immediately and and we have been developing that uh over the last eight months and has been live for the last three months now in the market so so you can say the pandemic really front loaded some of our strategic actions for for two to three years uh yeah that was very exciting what's that uh saying luck is the byproduct of great planning and preparation so let's talk about when you're in a company with some strong financial situation that you can move immediately with investment when you take such decision then then it's really thrilling yeah right awesome um two-part question talk about how you leverage data to support the solid groups mission and you know drive value for customers and maybe you could talk about some of the challenges you face with just the amount of data the speed of data et cetera yeah i said data is everything when you are in retail as a retailer's detail as you need to monitor your operation down to each store eats department and and if you can say we have challenge that that is that data is just growing rapidly as a year by year it's growing more and more because you are able to be more detailed you're able to capture more data and for a company like ours we need to be updated every morning as a our fully updated sales for all unit department single sku selling in in the stores is updated 3 o'clock in the night and send out to all top management and and our managers all over the company it's actually 8 000 reports going out before six o'clock every day in the morning we have introduced a loyalty program and and you are capturing a lot of data on on customer behavior what is their preferred offers what is their preferred time in the week for buying different things and all these data is now used to to personalize our offers to our cost of value customers so we can be exactly hitting the best time and and convert it to sales data is also now used for what we call intelligent price reductions as a so instead of just reducing prices with 50 if it's uh close to running out of date now the system automatically calculate whether a store has just enough to to finish with full price before end of day or actually have much too much and and need to maybe reduce by 80 before as being able to sell so so these automated [Music] solutions built on data is bringing efficiency into our operation wow you make it sound easy these are non-trivial items so congratulations on that i wonder if we could close hpe was kind enough to introduce us tell us a little bit about the infrastructure the solutions you're using how they differentiate you in the market and i'm interested in you know why hpe what distinguishes them why the choice there yeah as a when when you look out a lot is looking at moving data to the cloud but we we still believe that uh due to performance due to the availability uh more or less on demand we we still don't see the cloud uh strong enough for for for selling group uh capturing all our data we have been quite successfully having one data truth across the whole con company and and having one just one single bi solution and having that huge amount of data i think we have uh one of the 10 largest sub business warehouses in global and but on the other hand we also want to be agile and want to to scale when needed so getting close to a cloud solution we saw it be a green lake as a solution getting close to the cloud but still being on-prem and could deliver uh what we need to to have a fast performance on on data but still in a high quality and and still very secure for us to run great thank you for that and thank alan thanks so much for your for your time really appreciate your your insights and your congratulations on the progress and best of luck in the future thank you all right keep it right there we have tons more content coming you're watching accelerating next from hpe [Music] welcome lisa and thank you for being here with us today antonio it's wonderful to be here with you as always and congratulations on your launch very very exciting for you well thank you lisa and we love this partnership and especially our friendship which has been very special for me for the many many years that we have worked together but i wanted to have a conversation with you today and obviously digital transformation is a key topic so we know the next wave of digital transformation is here being driven by massive amounts of data an increasingly distributed world and a new set of data intensive workloads so how do you see world optimization playing a role in addressing these new requirements yeah no absolutely antonio and i think you know if you look at the depth of our partnership over the last you know four or five years it's really about bringing the best to our customers and you know the truth is we're in this compute mega cycle right now so it's amazing you know when i know when you talk to customers when we talk to customers they all need to do more and and frankly compute is becoming quite specialized so whether you're talking about large enterprises or you're talking about research institutions trying to get to the next phase of uh compute so that workload optimization that we're able to do with our processors your system design and then you know working closely with our software partners is really the next wave of this this compute cycle so thanks lisa you talk about mega cycle so i want to make sure we take a moment to celebrate the launch of our new generation 10 plus compute products with the latest announcement hp now has the broadest amd server portfolio in the industry spanning from the edge to exascale how important is this partnership and the portfolio for our customers well um antonio i'm so excited first of all congratulations on your 19 world records uh with uh milan and gen 10 plus it really is building on you know sort of our you know this is our third generation of partnership with epic and you know you are with me right at the very beginning actually uh if you recall you joined us in austin for our first launch of epic you know four years ago and i think what we've created now is just an incredible portfolio that really does go across um you know all of the uh you know the verticals that are required we've always talked about how do we customize and make things easier for our customers to use together and so i'm very excited about your portfolio very excited about our partnership and more importantly what we can do for our joint customers it's amazing to see 19 world records i think i'm really proud of the work our joint team do every generation raising the bar and that's where you know we we think we have a shared goal of ensuring that customers get the solution the services they need any way they want it and one way we are addressing that need is by offering what we call as a service delivered to hp green lake so let me ask a question what feedback are you hearing from your customers with respect to choice meaning consuming as a service these new solutions yeah now great point i think first of all you know hpe green lake is very very impressive so you know congratulations um to uh to really having that solution and i think we're hearing the same thing from customers and you know the truth is the compute infrastructure is getting more complex and everyone wants to be able to deploy sort of the right compute at the right price point um you know in in terms of also accelerating time to deployment with the right security with the right quality and i think these as a service offerings are going to become more and more important um as we go forward in the compute uh you know capabilities and you know green lake is a leadership product offering and we're very very you know pleased and and honored to be part of it yeah we feel uh lisa we are ahead of the competition and um you know you think about some of our competitors now coming with their own offerings but i think the ability to drive joint innovation is what really differentiate us and that's why we we value the partnership and what we have been doing together on giving the customers choice finally you know i know you and i are both incredibly excited about the joint work we're doing with the us department of energy the oak ridge national laboratory we think about large data sets and you know and the complexity of the analytics we're running but we both are going to deliver the world's first exascale system which is remarkable to me so what this milestone means to you and what type of impact do you think it will make yes antonio i think our work with oak ridge national labs and hpe is just really pushing the envelope on what can be done with computing and if you think about the science that we're going to be able to enable with the first exascale machine i would say there's a tremendous amount of innovation that has already gone in to the machine and we're so excited about delivering it together with hpe and you know we also think uh that the super computing technology that we're developing you know at this broad scale will end up being very very important for um you know enterprise compute as well and so it's really an opportunity to kind of take that bleeding edge and really deploy it over the next few years so super excited about it i think you know you and i have a lot to do over the uh the next few months here but it's an example of the great partnership and and how much we're able to do when we put our teams together um to really create that innovation i couldn't agree more i mean this is uh an incredible milestone for for us for our industry and honestly for the country in many ways and we have many many people working 24x7 to deliver against this mission and it's going to change the future of compute no question about it and then honestly put it to work where we need it the most to advance life science to find cures to improve the way people live and work but lisa thank you again for joining us today and thank you more most importantly for the incredible partnership and and the friendship i really enjoy working with you and your team and together i think we can change this industry once again so thanks for your time today thank you so much antonio and congratulations again to you and the entire hpe team for just a fantastic portfolio launch thank you okay well some pretty big hitters in those keynotes right actually i have to say those are some of my favorite cube alums and i'll add these are some of the execs that are stepping up to change not only our industry but also society and that's pretty cool and of course it's always good to hear from the practitioners the customer discussions have been great so far today now the accelerating next event continues as we move to a round table discussion with krista satrathwaite who's the vice president and gm of hpe core compute and krista is going to share more details on how hpe plans to help customers move ahead with adopting modern workloads as part of their digital transformations krista will be joined by hpe subject matter experts chris idler who's the vp and gm of the element and mark nickerson director of solutions product management as they share customer stories and advice on how to turn strategy into action and realize results within your business thank you for joining us for accelerate next event i hope you're enjoying it so far i know you've heard about the industry challenges the i.t trends hpe strategy from leaders in the industry and so today what we want to do is focus on going deep on workload solutions so in the most important workload solutions the ones we always get asked about and so today we want to share with you some best practices some examples of how we've helped other customers and how we can help you all right with that i'd like to start our panel now and introduce chris idler who's the vice president and general manager of the element chris has extensive uh solution expertise he's led hpe solution engineering programs in the past welcome chris and mark nickerson who is the director of product management and his team is responsible for solution offerings making sure we have the right solutions for our customers welcome guys thanks for joining me thanks for having us krista yeah so i'd like to start off with one of the big ones the ones that we get asked about all the time what we've been all been experienced in the last year remote work remote education and all the challenges that go along with that so let's talk a little bit about the challenges that customers have had in transitioning to this remote work and remote education environment uh so i i really think that there's a couple of things that have stood out for me when we're talking with customers about vdi first obviously there was a an unexpected and unprecedented level of interest in that area about a year ago and we all know the reasons why but what it really uncovered was how little planning had gone into this space around a couple of key dynamics one is scale it's one thing to say i'm going to enable vdi for a part of my workforce in a pre-pandemic environment where the office was still the the central hub of activity for work uh it's a completely different scale when you think about okay i'm going to have 50 60 80 maybe 100 of my workforce now distributed around the globe um whether that's in an educational environment where now you're trying to accommodate staff and students in virtual learning uh whether that's uh in the area of things like uh formula one racing where we had uh the desire to still have events going on but the need for a lot more social distancing not as many people able to be trackside but still needing to have that real-time experience this really manifested in a lot of ways and scale was something that i think a lot of customers hadn't put as much thought into initially the other area is around planning for experience a lot of times the vdi experience was planned out with very specific workloads or very specific applications in mind and when you take it to a more broad-based environment if we're going to support multiple functions multiple lines of business there hasn't been as much planning or investigation that's gone into the application side and so thinking about how graphically intense some applications are one customer that comes to mind would be tyler isd who did a fairly large roll out pre-pandemic and as part of their big modernization effort what they uncovered was even just changes in standard windows applications had become so much more graphically intense with windows 10 with the latest updates with programs like adobe that they were really needing to have an accelerated experience for a much larger percentage of their install base than than they had counted on so in addition to planning for scale you also need to have that visibility into what are the actual applications that are going to be used by these remote users how graphically intense those might be what's the login experience going to be as well as the operating experience and so really planning through that experience side as well as the scale and the number of users uh is is kind of really two of the biggest most important things that i've seen yeah mark i'll i'll just jump in real quick i think you you covered that pretty comprehensively there and and it was well done the couple of observations i've made one is just that um vdi suddenly become like mission critical for sales it's the front line you know for schools it's the classroom you know that this isn't a cost cutting measure or a optimization nit measure anymore this is about running the business in a way it's a digital transformation one aspect of about a thousand aspects of what does it mean to completely change how your business does and i think what that translates to is that there's no margin for error right you really need to deploy this in a way that that performs that understands what you're trying to use it for that gives that end user the experience that they expect on their screen or on their handheld device or wherever they might be whether it's a racetrack classroom or on the other end of a conference call or a boardroom right so what we do in in the engineering side of things when it comes to vdi or really understand what's a tech worker what's a knowledge worker what's a power worker what's a gp really going to look like what's time of day look like you know who's using it in the morning who's using it in the evening when do you power up when do you power down does the system behave does it just have the it works function and what our clients can can get from hpe is um you know a worldwide set of experiences that we can apply to making sure that the solution delivers on its promises so we're seeing the same thing you are krista you know we see it all the time on vdi and on the way businesses are changing the way they do business yeah and it's funny because when i talk to customers you know one of the things i heard that was a good tip is to roll it out to small groups first so you could really get a good sense of what the experience is before you roll it out to a lot of other people and then the expertise it's not like every other workload that people have done before so if you're new at it make sure you're getting the right advice expertise so that you're doing it the right way okay one of the other things we've been talking a lot about today is digital transformation and moving to the edge so now i'd like to shift gears and talk a little bit about how we've helped customers make that shift and this time i'll start with chris all right hey thanks okay so you know it's funny when it comes to edge because um the edge is different for for every customer in every client and every single client that i've ever spoken to of hp's has an edge somewhere you know whether just like we were talking about the classroom might be the edge but but i think the industry when we're talking about edge is talking about you know the internet of things if you remember that term from not to not too long ago you know and and the fact that everything's getting connected and how do we turn that into um into telemetry and and i think mark's going to be able to talk through a couple of examples of clients that we have in things like racing and automotive but what we're learning about edge is it's not just how do you make the edge work it's how do you integrate the edge into what you're already doing and nobody's just the edge right and and so if it's if it's um ai mldl there's that's one way you want to use the edge if it's a customer experience point of service it's another you know there's yet another way to use the edge so it turns out that having a broad set of expertise like hpe does to be able to understand the different workloads that you're trying to tie together including the ones that are running at the at the edge often it involves really making sure you understand the data pipeline you know what information is at the edge how does it flow to the data center how does it flow and then which data center uh which private cloud which public cloud are you using i think those are the areas where where we really sort of shine is that we we understand the interconnectedness of these things and so for example red bull and i know you're going to talk about that in a minute mark um uh the racing company you know for them the the edge is the racetrack and and you know milliseconds or partial seconds winning and losing races but then there's also an edge of um workers that are doing the design for for the cars and how do they get quick access so um we have a broad variety of infrastructure form factors and compute form factors to help with the edge and this is another real advantage we have is that we we know how to put the right piece of equipment with the right software we also have great containerized software with our esmeral container platform so we're really becoming um a perfect platform for hosting edge-centric workloads and applications and data processing yeah it's uh all the way down to things like our superdome flex in the background if you have some really really really big data that needs to be processed and of course our workhorse proliance that can be configured to support almost every um combination of workload you have so i know you started with edge krista but but and we're and we nail the edge with those different form factors but let's make sure you know if you're listening to this this show right now um make sure you you don't isolate the edge and make sure they integrate it with um with the rest of your operation mark you know what did i miss yeah to that point chris i mean and this kind of actually ties the two things together that we've been talking about here but the edge uh has become more critical as we have seen more work moving to the edge as where we do work changes and evolves and the edge has also become that much more closer because it has to be that much more connected um to your point uh talking about where that edge exists that edge can be a lot of different places but the one commonality really is that the edge is is an area where work still needs to get accomplished it can't just be a collection point and then everything gets shipped back to a data center or back to some some other area for the work it's where the work actually needs to get done whether that's edge work in a use case like vdi or whether that's edge work in the case of doing real-time analytics you mentioned red bull racing i'll i'll bring that up i mean you talk about uh an area where time is of the essence everything about that sport comes down to time you're talking about wins and losses that are measured as you said in milliseconds and that applies not just to how performance is happening on the track but how you're able to adapt and modify the needs of the car uh adapt to the evolving conditions on the track itself and so when you talk about putting together a solution for an edge like that you're right it can't just be here's a product that's going to allow us to collect data ship it back someplace else and and wait for it to be processed in a couple of days you have to have the ability to analyze that in real time when we pull together a solution involving our compute products our storage products our networking products when we're able to deliver that full package solution at the edge what you see are results like a 50 decrease in processing time to make real-time analytic decisions about configurations for the car and adapting to to real-time uh test and track conditions yeah really great point there um and i really love the example of edge and racing because i mean that is where it all every millisecond counts um and so important to process that at the edge now switching gears just a little bit let's talk a little bit about some examples of how we've helped customers when it comes to business agility and optimizing their workload for maximum outcome for business agility let's talk about some things that we've done to help customers with that mark yeah give it a shot so when we when we think about business agility what you're really talking about is the ability to to implement on the fly to be able to scale up to scale down the ability to adapt to real time changing situations and i think the last year has been has been an excellent example of exactly how so many businesses have been forced to do that i think one of the areas that that i think we've probably seen the most ability to help with customers in that agility area is around the space of private and hybrid clouds if you take a look at the need that customers have to to be able to migrate workloads and migrate data between public cloud environments app development environments that may be hosted on-site or maybe in the cloud the ability to move out of development and into production and having the agility to then scale those application rollouts up having the ability to have some of that some of that private cloud flexibility in addition to a public cloud environment is something that is becoming increasingly crucial for a lot of our customers all right well i we could keep going on and on but i'll stop it there uh thank you so much uh chris and mark this has been a great discussion thanks for sharing how we helped other customers and some tips and advice for approaching these workloads i thank you all for joining us and remind you to look at the on-demand sessions if you want to double click a little bit more into what we've been covering all day today you can learn a lot more in those sessions and i thank you for your time thanks for tuning in today many thanks to krista chris and mark we really appreciate you joining today to share how hpe is partnering to facilitate new workload adoption of course with your customers on their path to digital transformation now to round out our accelerating next event today we have a series of on-demand sessions available so you can explore more details around every step of that digital transformation from building a solid infrastructure strategy identifying the right compute and software to rounding out your solutions with management and financial support so please navigate to the agenda at the top of the page to take a look at what's available i just want to close by saying that despite the rush to digital during the pandemic most businesses they haven't completed their digital transformations far from it 2020 was more like a forced march than a planful strategy but now you have some time you've adjusted to this new abnormal and we hope the resources that you find at accelerating next will help you on your journey best of luck to you and be well [Music] [Applause] [Music] 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(upbeat music) >> We just compressed about a decade of online commerce progress into about 13 or 14 months. So now we're going to look at how one retailer navigated through the pandemic and what the future of their business looks like. And with me is Alan Jensen who is the chief information officer and senior vice president of the Salling Group. Hello, Alan, how are you? >> Fine, thank you. >> Good to see you. Look, you know, when I look at the hundred year history plus of your company, I mean, it's a marked by transformations and some of them are quite dramatic. So you're Denmark's largest retailer. I wonder if you could share a little bit more about the company its history and how it continues to improve the customer experience while at the same time keeping costs under control so vital in your business. >> Yeah, the company founded approximately 100 year ago with a department store in Denmark. And I think in the 60s we founded the first supermarket in Denmark with the self-service and combined textile and food in the same store. And in the beginning 70s, we found that the first hypermarket in Denmark and then the discounter came from Germany early in 1980 and we started a discount chain. And so we are actually building department store in hypermarket in supermarket, and in the discount sector. And today we are more than 1,500 stores in three different countries in Denmark, Poland, and Germany. And especially for the Danish market we have a approximately 38% market share and it is the leader. We have over the last 10 years developed further into online first in non-food and now in food with home delivery with Clayton Calais. And we have done some acquisition in the convenience with me box solutions to our customers. And we have today also some restaurant burger chain and we are running the Starbucks in Denmark. So you can see a full plate of different opportunities for our customer in especially Denmark. >> It's an awesome story. And of course the founder's name is still on the masthead. What a great legacy. Now, of course the pandemic has forced many changes quite dramatic including the behaviors of retail customers. Maybe you could talk a little bit about how your digital transformation at the Salling Group prepared you for this shift in consumption patterns and any other challenges that you faced. >> I think luckily as for some of the you can say the coati solution in 19 we just roll out using our computers. We are direct access, so you can work from anywhere whether you are traveling from home and so on. We introduced a new age from delivery model and we just finalized the rolling out teams in January, February 20. And that was some very strong thing for suddenly moving all our employees from office to home and more or less overnight we succeed continuing our work and for IT We have not missed any deadline or task for the business in 2020. So I think that was a pretty awesome to see. And for the business, of course the pandemic changed a lot as the change in customer behavior, more or less overnight with plus 50, 80% on the online solution forced us to do some different priorities as we were looking at food home delivery and originally expected to start rolling out in 2022 but took a fast decision in April last year to launch immediately. And we have been developing that over the last eight months and has been live for the last three months now in the market. So you can say the pandemic really front-loaded some of our strategic actions for two to three years. >> What's that saying? Luck is the by-product of great planning and preparation. So let's talk about... what happened? >> And when you are in a company with some strong financial situation that you can move immediately with investment when you take such a decision, then it's really failing yeah. >> Right, awesome. Two-part question. Talk about how you leverage data to support the Solent group's mission and you know drive value for customers. And maybe you could talk about some of the challenges you face with just the amount of data, the speed of data, et cetera. >> Yeah, I said data is everything when you are in retail, as retail is detail as you need to monitor your operation down to each store each department. And if you can say, we have challenged that data is just growing rapidly as a year by year it's growing more and more because you're able to be more detailed, you're able to capture more data. And for a company like ours we need to be updated every morning as our fully updated sales for all unit department single skew selling in the stores is updated three o'clock in the night and send out to all top management and our managers all over the company. It's actually 8,000 reports going out before six o'clock every day in the morning. We have introduced a loyalty program and we are capturing a lot of data on customer behavior. What is their preferred of us? What is their preferred time in the week for buying different things. And all these data is now used to personalize our offers to our value customers. So we can be exactly hitting the best time and convert it to sales. Data is also now used for what we call intelligent price reductions so instead of just reducing prices with 50% if it's a close to running out of date now the system automatically calculate whether a store has just enough to finish with full price before end of day, or actually have too much and need to maybe reduce by 80% before. So being able to sell. So these automated solutions build on data is bringing efficiency into our operation. >> Wow, you make it sound easy. These are non-trivial items. So congratulations on that. I wonder if we could close HPE was kind enough to introduce us, tell us a little bit about the infrastructure of the solutions you're using how they differentiate you in the market. And I'm interested in you know why HPE what distinguishes them, why they choose there. >> When you look out a lot is looking at moving data to the cloud, but we still believe that due to performance, due to the availability, more or less on demand, we still don't see the cloud strong enough for Salling Group capturing all our data. We have been quite successfully having one data truth across the whole company and having one just one single BI solution and having that huge amount of data. I think we have one of the 10 largest sub business warehouses global. And on the other hand we also want to be agile and want to scale when needed. So getting close to a cloud solution, we saw it be GreenLake as a solution, getting close to the cloud but still being on-prem and could deliver what we need to have fast performance on data, but still in a high quality and still very secure for us to run. >> Great, thank you for that. Alan thanks so much for your time really appreciate your insights and congratulations on the progress and best of luck in the future. >> Thank you. >> All right, keep it right there. We have tons more content coming. You're watching Accelerating Next from HPE. (upbeat music)

>> Well, quick introductions for everybody kind of out there watching in the Data Summit. I'm Ali Tierney. I am the GVP. I run EMEA Sales for Snowflake, and I'm joined today with Michael Gillespie. Quick, just to introduce himself, what he does, and the DPE come structure as it goes. Go ahead, Micheal. >> Thanks, Ali. So as you said, I'm CDTO at Domino's Pizza Enterprises. So the company that I work for, we have the franchise rights and run Australia and New Zealand, France, Belgium, Netherlands, Germany, Japan, Luxembourg, and Denmark. And that's obviously Domino's Pizza for those markets. I look after four different verticals within the business. IT for the group, Strategy and Insights where our BI team resides and has a lot to do with Snowflake. Our Store Innovations Team, our Store Innovation Operations team which look at everything from robotics in store, how to use data better in store to be working at optimum level, and our digital team which is where I started in, actually, 13 years ago. And they're guiding our digital platform at a global level and how we localize it with the local marketing teams. >> Brilliant, I'm American and I grew up with Domino's Pizza, so help me understand, kind of, from a high structure. You've been there 13 years. My growing up experience was picking up a phone and pushing buttons and calling Domino's, and clearly a ton of modernization has come in the last 20 years, and you've been with the company for 13. What have you seen as you've grown into the DPE digital kind of space and you're driving that market? How are you guys using data? What have you seen happen over the last 13 years? >> Domino is itself, or at least DPE as well, has always been a data-driven business. What we've seen, though, as we've become more of a business that utilizes digital and technology to enhance, whether the customer experience or our store operations or our enterprise team. Is the availability of data to make decisions or to actually find insights. And if I look back, I've been lucky to go on a journey of 13 years with DPE. The power of analytics and data was apparent in a digital space. And it gave us a level of insight over a purchase that we never had before. So a great example of our first use of real data in a customer experience outside callbacks people are late, where we could give real-time feedback to a customer around their progression of their order through something called Pizza Tracker, which is shared across all and used across most Domino's in the world. And they're most common for most purchasing processes. Since then, we've gone from, I could count, very easily in between this call, how many orders would make in a day online, to now over 70% of our businesses online. We have a huge amount of data coming in from different, different areas of business. And now the challenge for myself and my team is how do we make this data readily available? To the local marketing teams, local operations teams. To really get better insights on the local market. So we've just gone from having a small pool of data to a tremendous quantum of data. >> So as you look to kind of localize your markets, right? I think you just mentioned seven or eight different markets that you're in. And I would assume then you have some data sharing that goes on within DPE, right? So Belgium wants something that's different than the Netherlands that was different than Japan, right? So how are you right now democratizing that data and giving it to your customers so that your end users can see how to use that, right? In local marketing in local, kind of, business uses. >> Correct. So, we have, we have nine markets now within DPE and all those markets, every market has unique needs and wants and challenges that they're trying to solve for. So our goal is to really try to simplify the access. And that's what we talk about democratizing data. We have a series of reports so we can build customized reports so that we don't have to do as many ad hoc requests. Then when giving those dashboards having the ability to customize and benchmark where you need to. And then when it comes down to a unique customer experience that's obviously going to be a localized marketing on them because different customers bought certain, certain volumes of pizza or sides and different market that's different. So we need to make the tools that each of them and or allow our marketing teams around the world to get access to the data that they can really help them make the most informed decisions to support their franchisees and stores. >> How much of your technology has moved in general to the cloud? And then secondarily to that question, as you've moved there, and I assume significant multi-clouds because you've got so many different regions and locations, how are using Snowflake to help move data into the cloud? >> I would say from a cloud perspective we're well advanced in being clouded for a majority of our platforms or at least moving in that direction. And we're being cloud friendly economic solution and some of that data solutions for quite a while. We still have some on-premise data, like most companies, and we're in the process of migrating. And we have to be aware that we operate within markets like Europe, where GDPR is there. And we have to, we have to be well across requirements from that ability that perspective. But regardless of GDPR or not with any form of customer data or employee data or any personal data we have, we know it's a privilege to hold. So anytime we are working with data we always want to make sure that we're storing it and accessing it in the most secure way. And then beyond that, we want to make sure that, as I talked about, we want to democratize data and make it more accessible. So, you know, I'm really looking forward to seeing as we build out and continue to build out our data strategy, how we continue to work with the likes of Snowflake to just bring faster and more insightful, you know, visibility into each particular market and at a global level as well. So that our global leaders can understand how the business is performing but also get micro where they need to. >> How, as you go through your cloud journey and then and with Snowflake specifically, how did you guys look to governance and how did you look to ensure your security around data? >> Yeah. So know for us, it's all about making sure we've got the right governance and controls and processes. So working with our security team, working with the right architects on data flow and processes, working with our legal team and representatives in each market and that's vital. You know, having policies and governance around any form of activity whether it be data or around changes on the website or changes even in any operational processes is important. So. >> Yeah >> And the greatest thing is if he can, you know, through, if you're making dashboards that are unquantifiable non-personal data, you know that's a lot easier to manage, as well. Because that's giving you a representation of groups not actually down to the particular customer. >> That makes perfect sense. How have you found migrating to Snowflake? Talk through that journey a little bit and I know you're relatively early in the journeys but talk at your experience has its been so far. >> You know, the BI team, my BI team and Strategy and Insights Team have definitely been huge fans of Snowflake and the support from the team there and and the partners we're using for integration. You know, one thing that I know that, that excites me from a strategic level, it's Snowflake's ability to be cloud agnostic and for us everything we build in the future we have chosen partners that we work with in the cloud space. We shouldn't be, we should always be having that ability to be flexible or we're always going to have some fragmented data sets and the ability to utilize a solution that can stretch out into those is very important. So you know, from a strategic level that's a great level of flexibility and from a micro level, and to look at how the team operate when they're coming with stories around greater efficiency, greater flexibility, reduced processing time, reduce, reduce time, reduction in costs and certain activities. That's a great story to be told. That's what I like about this story is that they were all wins. You know, I'm getting from the team that I can run more intensive workloads now. You know, that they can they can do more immediate action. You know, they are cutting down time, as I said, something down from hours to minutes down getting some early results and that's so important. >> So, tell me what kind of business insights you're delivering back to your stakeholders when you get through this process? The quick wins. >> Yeah, well I guess it's just us being able to get reports out faster. Get information out faster, Get access to any acts, build, build bespoke things quicker. It's all about Domino's as a business that's quite an entrepreneurial fast moving. So if you can find efficiencies that, like any business, that's, that's the point. But if we can find efficiencies within our team what it means is we've got a quantum of work the team can do or a service can do, or a bucket of costs can do. If we can reduce that quantum of whether it be cost or time and human effort, that means we can output more. One thing that we're also looking at is we talked about democratizing data earlier, but how can we empower, empower teams to get insights faster? Or to go, I always think there should be no one key holder. There should be key holders of obviously the security of the data and the, and the safety and the and the rules around it. But, in regards to broad insight data or in visibility of results, we should be trying to make that as accessible as possible so that teams can find the reading sites. You've got then thousands or hundreds of people that are looking. Whether it be franchisees at store or team members that had offices in different departments. If they can get greater visibility at a top level data and drill in micro and performance, imagine the insights you continue to do or if you can get reports in their hands faster. Time in a fast moving business a day or two of lost opportunity is huge. So how do you get to make those decisions faster? And how do you stay ahead of your game? >> So as you think of data cloud and as you think of how you're going to build out a DPE specific data cloud, where do you see that going? How, where do you get where's your nirvana and end goal from your data club? >> How do we make better use of that data? So, how do we win? We know that our data repositories are only going to continue to grow. You know, we're a business that was growing at a relatively strong rate. If you look at our previous results, we have a multitude of countries. We have 2,600 stores around the world pumping out pieces every night. And that's creating different forms of data. We have 70% of our customers online. When you're capturing a continuous amount of data. One thing that we want to do is not only manage it efficiently We know that capturing data is a privilege as well, so that we're capturing the right data. And then when you're capturing the right data we still know that the quantum of that will increase. So then how we are storing it and making sure that as we add more data to our repositories we are not actually making its harder to access or it's slower to access. So it's bringing down our reports that we're continuing to optimize and what we're seeing and I touched on when you're bringing time down from hours to minutes with a tool. We're doing that. We're bringing down those solutions. So being able to manage the increasing volume of data we're getting in a more efficient way. Being able to democratize the access of it in a safe, secure, but insightful way. But, you know, having the backing of a service like Snowflake in the background, supporting access and functioning about data. Hopefully, this just means that it will give us more ability to be nimble and do more in the future. >> As you've broken down data silos with using Snowflake and started to democratize data and put it all in one spot your ML becomes richer and more able to make better decisions because you got it all out of silos at this point. >> Yeah.We've got a better floral collection about data. And we can make those data repositories more accessible or no more efficient in accessing them. It's only going to enrich our models and it's going to challenge us. I can challenge and the business can challenge the strategy and insights and BI team to look at a multitude of ways as part of supporting the business. Because they've always got a backlog of reports or solutions they want to deliver. So, we had started a journey of being a data driven company. We have started the journey of a digital company many, many years ago. >> So as we leave today Michael and we wrap up. Last question I have for you is, as you know, everybody's coming and saying do the next bread is coolest next thing. What would you recommend the users of our conference? What would you say? Like how would you, how would you say to go to market and do it the right way? >> Yeah. Let's say the main thing is for those people to reflect upon their own business and understand the challenges at hand. it's very easy to be asked, why aren't we doing AI? Why aren't we doing machine learning? Why aren't we? But those are just solutions. You should be trying to take time to say okay, but what are some of that challenges? And then can we apply those technologies to it? or could a rudimentary approach, approach of just a simple report or a very basic algorithm solve for that. But if you could take your system to the next level with ML, don't do it for ML's sake or if you could take it with a complex data extract. Make sure you've got an angle inside of what you want to deliver. And then know, once you go down the path of anything more complicated, especially with things like machine learning, that it's a never-ending story. And you're probably not going to get the result you like in the first couple of weeks or month because that's what it is. It's a learning solution. It's a ever evolving beast and you can't just throw it out there and say, "Oh, everyone will be happy." So make sure you've got a fair commitment to getting into that game. And that you've got an envision in hand, and that envision will, I can tell you, usually move once you achieve it. Because you're only going to unlock more realities or more alternative solutions that'll grow from it. >> Absolutely. >> So be strong and want the challenges. >> I love that, and it's how we like to think about the data cloud in general, right? Is we are delivering to the business. At the end of the day, data is useless if you're not giving insights and ability for your business to make decisions and move forward. So I completely agree and I really appreciate the time you took today to sit down with me and educate me on Domino's and educate the world on how you're using data to make better decisions in the business. Thanks, Michael. >> Thanks for your time.

>> Narrator: From around the globe, it's theCUBE with digital coverage of AWS Public Sector Online. Brought to you by Amazon Web Services. >> Welcome back to the coverage of AWS Public Sector Summit virtual. I'm John for host of theCUBE. We're here in theCUBE studios, quarantine crew here talking to all the guests remotely as part of our virtual coverage of AWS Public Sector. So I've got a great guest here talking about data science, weather predictions, accurate climate modeling, really digging into how cloud is helping science. Dr. Chelle Gentemann, who is a senior scientist at Farallon Institute is my guest. Chelle, thank you for joining me. >> Thank you. >> So tell us a little about your research. It's fascinating how, I've always joked in a lot of my interviews, 10, 15, 20 years ago, you need super computers to do all these calculations. But now with cloud computing, it opens up so much more on the research side and the impact is significant. You're at an awesome Institute, the Farallon Institute, doing a lot of stuff in the sea and the ocean and a lot of your things. What's your focus? >> I study the ocean from space, and about 71% was covered by ocean. 40% of our population in the globe actually lives within 100 kilometers of the coast. The ocean influences our weather, it influences climate, but it also provides fisheries and recreational opportunities for people. So it's a really important part of the earth system. And I've been focused on using satellites. So from space, trying to understand how the ocean influences weather and climate >> And how new is this in terms of just state of the art? Fairly new, been around for a while? What's some of the progress for the state of the art we're involved in. >> I started working on satellite data in the 90s during school, and I liked the satellite data cause it's the interface of sort of applied math, computer science and physics. The state of the art is that we've really had remote sensing around for about 20, 30 years. But things are changing because right now we're having more sensors and different types of instruments up there and trying to combine that data is really challenging. To use it, our brain is really good in two and three dimensions, but once you get past that, it's really difficult for the human brain to try and interpret the data. And that's what scientists do. Is they try and take all these multidimensional data sets and try to build some understanding of the physics of what's going on. And what's really interesting is how cloud computing is impacting that. >> It sounds so exciting. The confluence of multiple disciplines kind of all right there, kind of geek out big time. So I've got to ask you, in the past you had the public data set program. Are you involved in that? Do you take advantage that research? How is some of the things that AWS is doing help you and is that public data set part of it? >> It's a big part of it now. I've helped to deploy some of the ocean temperature data sets on the cloud. And the way that AWS public data sets as sort of has potential to transform science is the way that we've been doing science, the way that I was trained in science was that you would go and download the data. And most of these big institutions that do research, you start to create these dark repositories where the institutions or someone in your group has downloaded data sets. And then you're trying to do science with these data, but you're not sure if it's the most recent version. It makes it really hard to do reproducible science, because if you want to share your code, somebody also has to access that data and download it. And these are really big data sets. So downloading it could take quite a long time. It's not very transparent, it's not very open. So when you move to a public data set program like AWS, you just take all of that download out of the equation. And instantly when I share my code now, people can run the code and just build on it and go right from there, or they can add to it or suggest changes. That's a really big advantage for trying to do open science. >> I had a dinner with Teresa Carlson who is awesome. She runs the Public Sector Summit for AWS. And I remember this was years ago and we were dreaming about a future where we would have national parks in the cloud or this concept of a Yosemite-like beautiful treasure. Physical place you could go there. And we were kind of dreaming that, wouldn't it be great to have like these data sets or supercomputer public commons. It sounds like that's kind of the vibe here where it's shareable and it's almost like a digital national park or something. Is that it's a shared resource. Is that kind of happening? First of all, what do you react to that? And what's your thoughts around that dream? And does this kind of tie to that? >> Yeah, I think it ties directly to that. When I think about how science is still being done and has been done for the past sort of 20 years, we had a real change about 20 years ago when a lot of the government agencies started requiring their data to be public. And that was a big change. So then we got, we actually had public data sets to work with. So more people started getting involved in science. Now I see it as sort of this fortress of data that in some ways have prevented scientists from really moving rapidly forward. But with moving onto the cloud and bringing your ideas and your compute to the data set, it opens up this entire Pandora's box, this beautiful world of how you can do science. You're no longer restricted to what you have downloaded or what you're able to do because you have this unlimited compute. You don't have to be at a big institution with massive supercomputers. I've been running hundreds of workers analyzing in my realm. Over two or 300 gigabytes of data on a $36 Raspberry Pi that I was playing around with my kids. That's transformative. That allows anyone to access data. >> And if you think about what it would have to do to do that in the old days, stack and spike servers. Call, first of all, you'll get the cash, buy servers, rack them and stack them, connect to a download of nightmare. So I got to ask you now with all this capability, first of all, you're talking to someone who loves the cloud. So I'm pretty biased. What are you doing now with the cloud that you couldn't do before? So certainly the old way from a provisioning standpoint, check, done. Innovation, bars raised. Now you're creative, you're looking at solutions, you're building enabling device like a Raspberry Pi, almost like a switch or an initiation point. How has the creativity changed? What can you do now? What are some of the things that are possible that you're doing? >> I think that you can point to within some of the data sets that have already gone on the cloud are being used in these really new, different ways. Again, it points to this, when you don't have access to the data, just simply because you have to download it. So that downloading the data and figuring out how to use it and figuring out how to store it is a big barrier for people. But when things like the HF Radar data set went online. Within a couple of months, there was a paper where people were using it to monitor bird migration in ways that they'd never been able to do before, because they simply hadn't been able to get the data. There's other research being done, where they've put whale recordings on the cloud and they're using AI to actually identify different whales. It's using one data set, but it's also the ability to combine all these different data sets and have access to them at the same time and not be limited by your computer anymore. Which for a lot of science, we've been limited by our access to compute. And that when you take away that, it opens all these new doors into doing different types of research with new types of data, >> You could probably correlate the whale sounds with the temperature and probably say, hey, it's cold. >> Chelle: Exactly. >> I'm making that up. But that's the kind of thing that wouldn't be possible before because you'd have to get the data set, do some math. I mean, this is cool stuff with the ocean. I mean, can you just take a minute to share some, give people an insight in some of the cool projects that are being either thought up or dreamed up or initiated or done or in process or in flight, because actually there's so much data in the ocean. So much things to do, it's very dynamic. There's a lot of data obviously. Share, for the folks that might not have a knowledge of what goes on. What are you guys thinking about? >> A lot of what we're thinking about is how to have societal impact. So as a scientist, you want your work to be relevant. And one of the things that we found is that the ocean really impacts weather at scales that we simply can't measure right now. So we're really trying to push forward with space instrumentation so that we can monitor the ocean in new ways at new resolutions. And the reason that we want to do that is because the ocean impacts longterm predictability in the weather forecast. So a lot of weather forecasts now, if you look out, you can go on to Weather Underground or whatever weather site you want. And you'll see the forecast goes out 10 days and that's because there's not a lot of accuracy after that. So a lot of research is going into how do we extend into seasonal forecast? I'm from Santa Rosa, California. We've been massively impacted by wildfires. And being able to understand how to prepare for the coming season is incredibly important. And surprisingly, I think to a lot of people, the ocean plays a big role in that. The ocean can impact how much storm systems, how they grow, how they evolve, how much water they actually got. Moisture they pick up from the ocean and then transport over land. So if you want to talk about, it's really interesting to talk about how the ocean impacts our weather and our seasonal weather. So that's an area where people are doing a lot of research. And again, you're talking about different data sets and being able to work together in a collaborative environment on the cloud is really what's starting to transform how people are working together, how they're communicating and how they're sharing their science. >> I just hope it opens up someone's possibilities. I want to get your vision of what you think the breakthroughs might be possible with cloud for research and computing. Because you have kind of old school and new school. Amazon CEO, Andy Jassy calls it old guard, new guard. The new guard is really more looking for self provisioning, auto-scaling, all that. Super computer on demand, all that stuff at your fingertips. Great, love that. But is there any opportunity for institutional change within the scientific community? What's your vision around the impact? It's not just scientific. It also can go to government for societal impact. So you start to see this modernization trend. What's your vision on the impact of the scientific community with cloud? >> I think that the way the scientific community has been organized for a long time is that scientists that are at an institute. And a lot of the research has been siloed. And it's siloed in part because of the way the funding mechanism works. But that inhibits creativity and inhibits collaboration. And it inhibits the advancement of science. Because if you hold onto data, you hold on to code. You're not allowing other people to work on it and to build on what you do. The traditional way that scientists have moved forward is you make a discovery, you write up a paper, you describe it in a journal article, and then you publish that. Then if someone wants to build on your research, they get your journal article, they read it. Then they try to understand what you did. They maybe recode all of your analysis. So they're redoing the work that you did, which is simply not efficient. Then they have to download the data sets that you access. This slows down all of science. And it also inhibits bringing in new data sets again because you don't have access to them. So one of the things I'm really excited about with cloud computing is that by bringing our scientific ideas and our compute to the data, it allows us to break out of these silos and collaborate with people outside of our institution, outside of our country, and bring new ideas and new voices and elevate everyone's ideas to another level. >> It brings the talent and the ideas together. And now you have digital and virtual worlds, cause we've been virtualized with COVID-19. You can create content as a community building capability or your work can create a network effect with other peers. And is a flash mobbing effect of potential collaboration. So work, work forces, workplaces, work loads, work flows, kind of are interesting or kind of being changed in real time. You were just talking about speed, agility. These are technical concepts being applied to kind of real world scenarios. I mean your thoughts on that. >> I now work with people like right now, I'm working with students in Denmark, Oman, India, France, and the US. That just wasn't possible 10 years ago. And we're able to bring all these different voices together, which it really frees up science and it frees up who can participate in science, which is really fun. I mean, I'm a scientist. I do it because it's really, really fun. And I love working with other people. So this new ability that I've gained in the last couple of years by moving onto the cloud has really accelerated all the different types of collaborations I'm involved with. And hopefully accelerating science as a whole. >> I love this topic. It's one of my passion areas where it's an issue I've been scratching for over a decade too. Is that content and your work is an enabler for community engagement because you don't need to publish it to a journal. It's like waterfall mentality. It's like you do it. But if you can publish something or create something and show it, demo it or illustrate it, that's better than a paper. If you're on video, you can talk about it. It's going to attract other people, like-minded peers can come together. That's going to create more collaboration data. That's going to create more solidarity around topics and accelerate the breakthroughs. >> For our last paper, we actually published all the software with it. We got a digital firewall for the software, published the software and then containerized it so that when you read our paper, at the bottom of the paper, you get a link. You go to that link, you click on a button and you're instantly in our compute environment, you can reproduce all of our results. Do the error propagation analysis that we did. And then if you don't like something, go ahead and change it or add onto it or ask us some questions. That's just magical. >> Yeah, it really is. And Amazon has been a real investor and I got to give props to Teresa Carlson and her team and Andy Jassy, the CEO, because they've been investing in credits and collaborating with groups like Jet Propulsion Lab, you guys, everyone else. Just space has been a big part of that. I see Bezos love space. So they've been investing in that and bringing that resource to the table. So you've got to give Amazon some props for that. But great work that you're doing. I'm fascinated. I think it's one of those examples where it's a moonshot, but it's doable. It's like you can get there. >> Yeah, and it's just so exciting. I'm the lead on a proposal for a new science mission to NASA. And we are going all in with the cloud computing. So we're going to do all the processing on the cloud. We want to do the entire science team on the cloud and create a science data platform where we're all working together. That's just never happened before. And I think that by doing this, we multiply the benefits of all of our analysis. We make it faster and we make it better and we make it more collaborative. So everyone wins. >> Sure, you're an inspiration to many. I'm so excited to do this interview with you. I love what you said earlier at the beginning about your focus of being in computer science, physics, space. That confluence is multiple disciplines. Not everyone can have that. Some people just get a computer science degree. Some people get, I'm premed, or I'm going to do biology. I'm going to do this. This notion of multiple disciplines coming together is really what society needs now. Is we're converging or virtualizing or becoming a global society. And that brings up my final question. Is something I know that you're passionate about creating a more inclusive scientific community because you don't have to be the, just the computer science major. Now, if you have all three, it's a multi-tool when you're a multiple skill player. But you don't have to be something to get into this new world. Because if you have certain disciplines, whether it's math, maybe you don't have computer science but it's quick to learn. There's frameworks out there, no code, low code. So cloud computing supports this. What's your vision and what's your opinion of how more inclusivity can come into the scientific community? >> I think that, when you're at an institution or at a commercial company or a nonprofit, if you're at some sort of organized institution, you have access to things that not everyone has access to. And in a lot of the world, there's trouble with internet connectivity. There is trouble downloading data. They simply don't have the ability to download large data sets. So I'm passionate about inclusivity because I think that, until we include global voices in science, we're not going to see these global results that we need to. We need to be more interdisciplinary. And that means working with different scientists in different fields. And if we can all work together on the same platform that really helps explode interdisciplinary science and what can be done. A lot of science has been quite siloed because you work at an institution. So you talked to the people one door down, or two doors down or on the same floor. But when you start working in this international community and people don't have to be online all the time, they can write code and then just jump on and upload it. You don't need to have these big, powerful resources or institutions behind you. And that gives a platform for all types of scientists, that all types of levels to start working with everyone. >> This is why I love the idea of the content and the community being horizontally scalable. Because if you're stuck around a physical institution or space, you kind of like have group think, or maybe you have the same kind of ideas being talked about. But here, when you pull back the remote work with COVID-19, as an example, it highlights it. The remote scientist could be anywhere. So that's going to increase access. What can we do to accept those voices? Is there a way or an idea or formula you see that people could, assuming there's access, which I would say, yes. What do we do? What do you do? >> I think you have to be open and you have to listen. Because, if I ask a question into the room where my colleagues work, we're going to come up with an answer. But we're going to come up with an answer that's informed by how we were trained in science and what fields we know. So when you open up this box and you allow other voices to participate in science, you're going to get new and different answers. And as a scientist, you need to be open to allowing those voices to be heard and to acting on them and including them in your research results and thinking about how they may change what you think and bring you to new conclusions. >> Machine learning has been a part. I know your work in the past, obviously cloud you're a big fan, obviously can tell. Proponent of it. Machine learning and AI can be a big part of this too, both on not only sourcing new voices and identifying what's contextually relevant at any given time, but also on the science-side machine learning. Because if we can take a minute to give your thoughts on the and relevance of machine learning and AI, because you still got the humans and you got machines augmenting each other, that relationship is going to be a constant conversation point going forward. Is there data about the data and what's the machines doing? What's your thoughts on all of these? Machine learning and AI as an impact. >> It's funny you say impact. So I work with this NASA IMPACT project, which is this interdisciplinary team that tries to advance science, and it's really into machine learning and AI. One of the difficulties when you start to do science is you have an idea like, okay, I want to study tropical storms. And then you have to go and wade through all these different types of data to identify when events happened and then gather all the data from those different events and start to try and do some analysis. They're working and they've been really successful in using AI to actually do this sort of event identification. So what's interesting and how can we use AI and machine learning to identify those interesting events and gathering everything together for scientists to then try and bring for analysis? So AI is being used in a lot of different ways in science. It's being used to look at these multi-dimensional problems that are just a little bit too big for our brains to try and understand. But if we can use AI and machine learning to gather insights into certain aspects of them, it starts to lead to new conclusions and it starts to allow us to see new connections. AI and machine learning has this potential to transform how we do science. Cloud computing is part of that because we have access to so much more data now. >> It's a real enabling technology. And when you have enabling technology, the power is in the hands of the creative minds. And it's really what you can think up and what you can dream up and that's going to come from people. Phenomenal. Final question for you, to kind of end on a light note. Dr. Chelle Gentemann here, senior scientist at the Farallon Institute. You're doing a lot of work on the ocean, space, ocean interaction. What's the coolest thing you're working on right now? Or you you've worked on that you think would be worth sharing. >> There's a couple of things. I have to think about what's the most fun. Right now, I'm working on doing some analysis with data. We had a big, huge international field campaign this winter off of Barbados, there were research festival, rustles and aircraft. There were sail drones involved, which are these autonomous robotic vehicles that go along the ocean surface and measure air-sea interactions. Right now we're working on analyzing that data. So we have all of this ground truth data. We're bringing in all the satellite observations to see how we can better understand the earth system in that region with a specific focus on air-sea interactions over the ocean where when it rains, you get the salinity stratification. When there's strong solar, you get diurnal stratification. So you have upper ocean stratification and heat and salinity. And how those impact the fluxes and how the ocean impacts the heat and moisture transport into the atmosphere, which then affects weather. So again, this is this multidimensional data set with all these different types of both ground truth data, satellite data that we're trying to bring together and it's really exciting. >> It could shape policy, it could shape society. Maybe have a real input into global warming. Our behaviors in the world, sounds awesome. Plus, I love the ground truth and the observational data. It sounds like our media business algorithm, we got to get the observation, get the truth, report it. Sounds like there's something in there that we could learn from. (both giggling) >> Yeah, it's very interesting cause you often find what you see from a distance is not quite true up close. >> I can tell you that we as in media as we do a lot of investigative journalism. So we appreciate that. Dr. Chelle Gentemann, senior scientist at the Farallon Institute, here as part of AWS Public Sector Summit. Thank you so much for time. What a great story. We'll keep in touch. Love the sails drone. Great innovation. And continue the good work, I'm looking forward to checking in later. Thanks for joining. >> Thanks so much. It was nice talking to you. >> I'm John Furrier with theCUBE. We're here in our studios covering the Amazon Web Services Public Sector Summit virtual. This is theCUBE virtual bringing you all the coverage with Amazon and theCUBE. Thanks for watching. (upbeat music)

>>from Menlo Park, California In the heart of Silicon Valley, it's the Cube covering cloud now. Awards 2020 Brought to you by Silicon Angle Media. Now here's Sonia category. >>Hi, and welcome to the Cube. I'm your host Sonia category, and we're on the ground at Facebook headquarters in Menlo Park, California covering Cloud now's top women entrepreneurs in Cloud Innovation Awards. >>Joining us today is Get the Schmidt CEO of Human. Get that. Welcome to the Cube. >>Thank you. Thanks for having me. >>So just give us a brief overview of your background and more about Humira. All right, A brief >>overview. Let's see. Um, I'll start off that I've been in the industry for some time now. Um, since ah, 97 which I used to actually work at this campus that we're here today at when it used to be Sun Microsystems. So I started out in technology in product management and marketing. Mainly, um, when java was coming out so early days and really learned a lot about what it takes to take a product or a concept out to market very exciting in those early days and sort of, you know, move towards looking at Industries and Sister focused on financial services into the lot around financial services marketing. Also it son. >>And then I moved >>to Denmark, which is sort of a surprise, But I'm married to a day and we decided we would try something different. So I moved to Denmark, working at a consulting company software consulting company based in Denmark, fairly small and Ah, and was part of sort of building out of the conference and business development business they had over there. And ah, and that was a way for us, for me to understand a completely other side of the business consulting aspects where you really build software for a customer and really understand, you know, sort of the customer solution needs that are required versus when you're working at a large enterprise company kind of are separated away from the customers. And that was there where I met the two founding team members of Humi Oh, Christian and Trust in at Tri Fork into you. Essentially, we've been working together for 10 years, and, uh, we sort of all felt like we could really come out with the world's best logging solution and, ah, this was out of some of the pain we were running into by running other solutions in the market. And so we took a leap into building our own product business. And so we did that in 2016. And so that's really what brought me here into the CEO role. So we have a three person leisure leadership or executive team, our founding team, which is to verily technical folks. So the guys that really built the product and and, uh, and keep it running and take it to the next level every single day. But what was missing was really that commercial kind of leader that was ready to take that role, and that's where I came in. So they were very supportive and and bringing me on board. So that was into 2016 where I started that >>that's awesome. So how do you think having like a business and marketing background versus a technical background has helped you become a successful CEO? Um, I >>think it's really, really hard if you don't have different profiles on your founding team to be able to run a successful tech business. So there's technology that you could have the world's greatest technology like an example would be my you know, my co founders were building an amazing product, but until they came into the room, they hadn't thought about going out and trying to get a customer to use it. And essentially, that is one of the issues there is that you can sit and build something and build the best product out there. But if you're not getting feedback really, really early in the design and the concepts of product development, then customers our search of it's not built in. And so a lot of the thought process around him. EOS We like to say customers are in our DNA. We build >>our product >>for people to use 6 to 8 hours a day, and they're in it every day. And so it keeps this feeling of a customer feedback loop. And even if you're technical, it's really exciting. You know that you build something that somebody uses every day. It looks at every day, and so that's the kind of energy that we've tried to, you know, instill. Or maybe I've tried to instill in Humi Oh, that you know, our customers really matter, and I think that's one of the ways that we've been able to move, Let's say really, really fast in building the right features the right functionality, um, and the right things for people are using it on the on the on, the on the other and essentially >>so okay. And, um so you're here to receive an award for being one of the top female entrepreneurs in cloud innovation. So congratulations and And how does it feel to win this award? Super >>exciting. I mean, I'm glad that there are organizations like Cloud now that are doing amazing things for women and and also, you know, making examples of folks that are doing interesting roles in our industry, especially around B two B software. I think that's a real area where there's not many CIOs or leaders in our space where there should be. And, uh, and I think part of it is actually kind of highlighting that. But, you know, the other side is sort of an event like this today is bringing together a lot of other profiles that are women or diverse profiles together to sort of, you know, talk about this problem and acknowledge and also take, let's say, more of an active stance around, you know, making this place not so scary. I mean, I think I remember one of my early events and I was raising our series A when I walked into a VC event where there were no other female CIOs out there. There's 100 CIOs and I was the only one. And I think one of the hard parts is I walked in there and, you know, it felt a bit uncomfortable, But there were some. There were two amazing VC partners at the company that I first started talking to, and that just really used the sort of like, you know, I guess. Uncomfortable, itty. So I think the main focus at things like today or, you know, the people that are here today. So I think we can help each other. And I think that's something that you know. That's something that I'd like to see more of, that we actively sort of create environments and communities for that to happen, and cloud now is one of them. >>So I think a lot of women have had that experience where they're the only woman in the room, you know, and it's just really hard to like. Figure out your path from there. So as the company as Julio, how do you What's your strategy for inclusion? >>Um, so, like I like to call it active inclusion. I think part of this is like having a diverse workforce, which is, you know, obviously including women and different backgrounds. Other things. But >>one of >>the big things we think about at Hume Eo is we really like to, let's say, celebrate people's differences so like that you're able to be yourself and almost eccentric is a good thing. And be able to feel safe in that environment to feel safe, that you can express your opinions, feel comfortable and safe when you're, you know, coming with a opposite viewpoint. Because the diversity of thought is really what we're trying to include in our company. So it means bringing together folks that don't look like each other where exactly, the same clothes and do the exact same hobbies and come from the same countries like we have. Ah, very, you know, global workforce. So we have folks, you know in Denmark of an office in Denmark. We have an office in the UK, and we have folks all over the U. S. We have a lot of backgrounds that have come from different cultures, and I think there's a beauty to that. There's a beauty to actually combining a lot of ways to solve problems. Everyone from a different culture has different ways of solving those. And so I think part of this is all around making that. Okay, right. So, you know, active inclusion is a way to to sort of put it into terms. So So we're definitely looking for people, Actively, that would like to join something like >>this. So I love that. Um, So if you were personally, if you were to have your own board of directors, like, who would they be? Um, it's not really >>the who. It's almost like the profiles or the people. I mean, we already have a personal board like I call it. I mean, it's something that I actively started doing. Um, once I once I started with a company board, I realized, you know, I probably need my own personal board, my own sort of support infrastructure That includes folks like my family, my sisters and my mom. It also includes you know, some younger junior folks that are actually much younger >>than me. >>But I learned so much from so um, to one of my good friend Cindy, who's who is brilliant at describing technology concepts. And and I think just some of the conversations I've had with her just opened my eyes to something that I hadn't seen before. And I think that's the area where I like to say the personal board isn't exactly you know people. It's it's profile. So along the way, as you grow, you're looking for new types of profiles. Let's say you want to learn about a new concept or a new technology or, you know, get better at running or something. So it's part of bringing those profiles in tow, learn about it and then back to this board concept. It's It's not as though it's a linked in network or it's actually sort of a group of people that you sort of rely on. And then it's a It's a two way street. So essentially, you know, there could be things that the other person could gain from knowing me, and ideally, that those were the best relationships in a personal board. So so I encourage alive women to do this because it builds a support infrastructure that is not related to your job. It's not your manager. It's not your co worker. You kind of feel some level of freedom having those discussions because those people aren't looking at your company. They're looking at helping you. So So that's That's sort of the concepts around >>the personal board idea and anything as women like having a sport system is so necessary, especially in this, like male dominated industry. Well, I think it's back >>to that whole feeling like you're the one person in the room, right? Right, so you're not the one person in the room, and I think we need to change that. And I think that's like some you know, all of our kind of roles that for all the women intact. I mean, it's sort of like something that we could help each other with right, and and if we don't do it actively, I mean, you know the numbers and we know you know the percentages of these things. If we want to change that, it does require some active interest on on our part to make that happen. And I think those are the areas where I see, like, the support infrastructures, the events like this really kind of engaging, um, us to be aware and doing something about the >>problem. Thank you so much for being on the key of love having you here. Thanks for >>having me. I really appreciate it. >>I'm Sonia to Garry. Thanks for watching the Cube. Stay tuned for more. >>Yeah, yeah.

>>live from Las Vegas. It's the Q covering AWS executive. Something >>brought to you by Accenture. >>Welcome back, everyone. We are kicking off day two of the cubes. Live coverage of the ex center Executive Summit here at AWS. Reinvent, I'm your host, Rebecca Knight. We have three guests for this panel. We have some bad meta. He is the chief information officer at Putnam based in Boston. Where? Boston People together. Thank you so much for coming on the show. Nitin Gupta. He's the partner and solutions lead. Financial service is at AWS Welcomed and Shale Jane back again for more. Who leads the data business group in North America. Thanks >>so much the last time. >>Yes. We can't get enough of each other. So thank you so much for coming on the show. We're talking about the data data journey and financial service is so I'm gonna start with you, Sam. It tell us. Tell our viewers a little bit about Putnam. That your assets under management. Your employees? >>Sure. So you know, problem is a global firm. We are a leader in mutual funds in the mutual fund business. We're in 84 year old organization. We based in Boston on, and we are known for innovation. We've done a lot of firsts in our industry on our focus has always bean looking after the needs of our shareholders. So even as we launch digital transformation, we launch it with the lens off, making sure we're covering the needs of our shareholders. >>So what was the impetus? What was the driving force to it? To embark on this cloud journey? >>Sure, So you look recovered. The financial markets recover industries. We look at our own industry as well. Things are changing rather rapidly, right, if I may just turn it around a little bit. Last year's letter from our CEO Bob Reynolds, said That problem now has Maur increasingly Maur four and five star funds, according to Morningstar, then we've had it as a percent of total funds ever. Before we had inflows, when the rest of the industry were having outflows, we built a digital platform and we said digital technology at problem is how we gonna view the internal technology department who will help enable our company to go and provide the investment insights directly to our advisors and to our shareholders so that they can benefit from the performance that we're we're delivering, right? We can only do that through a change. What's really going on in our industry is that there's more choice that's now available to shareholders than ever before. So while we talk about where there's outflows in in in our world, there's actually a lot of flow happening, right, So So it's for us to figure out how. How are the tastes changing right? What are people buying would do advisors need? When do they need them and can reposition ourselves to service them at scale, and so that those are the things that are driving our business? For us to continue to serve the shareholders needs. We really need to be in tune with where the market is. So we're helping do that at Putnam through technology, >>so shale in it. And I mean, what he's just described is thin. This enormously changing landscape and financial service is disrupted by a lot of new entrance. A lot of financial text in tak, a lot of different kinds of technologies. A lot of industries are experiencing this rapid pace of change. How do u ex ensure in AWS work with Putnam amidst this tremendous change, and how do you sit down with the client and sort of work out? Where do we go from here? >>So you know, I want to touch upon a couple of things that made you said And Rebecca You said, So no one is the cloud of their journey. It's It's not a destination that you're trying to get to, And then the other thing that you talked about, it's change. So we had in the cycle right now. But there's a lot of change happening at an industry we had in the cycle Where you nothing, that $38 trillion or something, which is a generator, you know, they're just getting transferred from one generation to the other. I'm not getting any off it. Unfortunately, you know >>all of >>this change that is happening in the industry. What is really required is you need something up in terms of technology, a platform that allows you to move quickly on adapt really quickly to this change. And I think that's where cloud comes in when we talk about all the new generation technologies like data machine learning, artificial intelligence, how >>do you >>leverage all of those. How do you fail quickly? How do you test experiment? Run thousands of not millions of experiments and see what will work in what will not work and do that in a very cost effective way and cloud of a very easy. It's an effective way to do it. And the weight of Louis is helping our customers. Obviously. You know, we we announced a bunch of service is yes, today way have the widest and the deepest tack that is dead in the industry today. You know the strength of our partners. Accenture. So you know, Accenture has Bean one of our longest standing partners altar and financial firm on, you know, working with them, working with our partners to enable our customers. But then we're also investing very heavily in building our industry capabilities. Are accounting solution architects? Professional service is security professionals helping our customers answer all the questions that they would need to answer as they go in this journey with us. So it's, you know, we are in this with them for for the long haul on dhe, you know, super excited about parking trip. >>So from our perspective, I think where we view the world as at a point where we're post digital, where digital was to put a front end that made your engagement with the customers much better. But now we're talking about intelligent enterprise, which is to really digitize the company from the inside out. So not only you need cloud for agility and all the other benefits that cloud offers, but you also need to look at data is the vehicle that would actually not only transform the culture of the company but also be able to integrate with your partners. For example, Cement talked about, you know, getting mind share from the advisers. But if you can exchange data, integrate data much better, faster with them and serve data to them in shapes and speeds that they need, they'll be more amenable to put you on their roster as well. So I think we're seeing a change that's mostly driven by the fintech industry disruption. That's that's happening as well. And it is no better time than now with the cloud and data to really help transform companies like >>the's tons of innovation, right, it's We heard Andy Jassy talk about the Let's roll Sweet the Sweets that are available to us. Our job is to learn what they are and how does it apply to our business because at the end of the game you said it's about our shareholders. It's about the value that we can bring. But we want to harness the power off all of the innovation, and we can't even though we've Bean an innovator, we're not going to innovate alone, all right, so it's really helpful to have to surround yourself with partners who have done this before, to be learning from others and bringing in the right tools at the right time, so so we can turn things around quickly, right? This is way are obviously very conservative and risk averse when it comes to managing other people's money. So we have to be very, very careful. Having said that, you know, we want to learn about all the guardrails we can put in place so we can go faster. >>I want to actually do something about what Shayla brought up, and that is the cultural change within the organization, because change is hard and so many people are resistant, particularly when things are going relatively well and they say Why mess that up with the new technology? So how is hard? Maybe >>is the understatement of the week very hard, and as you guys know, you know where it's not. It's not hard because people don't just want changes. They are experts in things that they've been doing for the last 15 years. 20 years. They've bean at our firm for a really long time. They really know how everything works from front to back. What happens, though? Now, when we get a changing need from the market and people want to buy things differently and we want to sell different products and maybe wanna introduce new products to the market, we can create bottlenecks that slow things down if we're not careful. So this is where we want to learn about the two pizza teams and how you can do things faster. How can we apply that to our world? Which means business partners working with technology, co located in small teams, being completely empowered to deliver solutions, right, working with our risk and compliance people, making sure that everyone's doing things that there were supposed to be doing right? How do we put that to work in the financial service is industry. So where we're learning as we go, we're learning to break down the sidles in the organization, and it's hot all the way around because we're experts in our areas. We know what we've done really well. But fortunately we have a leader in our CEO who's basically said that Let's transform problem so that we become leaders in the digital era for financial service is so with his support waken. Get the executive team align, and as the executive team aligns, then you find that people in the organization they want to work in this model, right but way don't know yet what we don't know, right? It's so we know how to do things from yesterday. Now we're learning and working together. So you guys have come in and this is where we've said, Bring in the people who have done this before and let's hold a session with 40 50 people that Putnam and let's just learn about what that transformation looked like at other places, so we don't make the same mistakes. >>Well, that's what Andy Jassy said in his fireside chat this morning. He was talking about how he had surgery recently in the question you need to ask your surgeon is how many times have you done this surgery? Because that is the critical thing. And so having a trusted partner is so important. So how how does it work that we're working together, collaborating on this relationship? How are you ensuring that Putnam doesn't make mistakes and does do the right tool for the right job shell? >>So, um, earlier this year, we actually launched an offering. A devious lighthouse with eight of us and what it is is a is a collection off. All of our assets are thought, leadership and architectures that we have garnered over the years, having worked with plants like Putnam and have them through the journey. So we put them all together and we bring Bring that Fourth Putnam is one of the first clients actually take advantage of it Abuse Data Lighthouse and, for example, we have a methodology that is specially customized for doing data on on eight of us. So things like that is what we bring to the table to help eliminate the risk that they may encounter. >>And data is critical to us, right? It's we manage a set of data assets, and that's the engine off the organization. So when we look at cloud migration way, look at what's our data strategy? How are rebuilding the so called you guys introduce the terminology for confirmed data sets? And then can we gallon eyes the rest of the organization around it, from investment professionals to operational professionals who used that data every day. Manager governent Make sure that it is what it's supposed to be. And to do that in a cloud environment where their user experience becomes a lot simpler, a lot easier almost takes I t a little away from the day to day. We don't have to be in the report writing business because we can make them more self service right that will create efficiencies in our organization. Our clients are asking us to do things at a lower cost than ever before and introduce more products and more tools and more service is right, so >>I would just tie with Samantha, just said with your question about culture. So if you can make it easy for people, for example, making things self service and data that's discovered through a catalog, so you have a place where you can go and find all the data sets it available. What is the quality? What is the veracity of data and then be able to take a piece of that and try some experiments with it? I think that would enable the cultural change much faster >>because they are able to basically do their jobs better. >>Yes, yes, >>it is. A is a more productive implement. Will highly >>engaged employees, right? We don't want to be in a situation where we find a lot of those disengagement moving employees and the mission for company. We want high engagement. We own people committed to what they're doing. We want to remove hurdles, and technology is they can produce great efficiencies, but it's not done right. It can also be a big hurdle. So we want to learn how to deliver the right tools, the right products to make it easier for way like to say, bring delightful experiences for our clients and our employees. >>Delightful. Another were another Jeff Bezos favorite word of his Obviously Putnam is, is a real innovator and really on the vanguard of this new technology. What are you seeing in the greater financial service is landscape. I mean, how how what are the what is the corporate mind set when it comes to this kind of change? >>So you know, when we look across our financial service is customer base across banking, capital markets, insurance pretty much every customer today. The question is not, you know if we should move to the cloud or when should we move to the cloud? But I think every every CEO and see io is asking the question, How do I move too loud? And what applications do I move over? How do I start on this journey of transformation? Whether it's a digital or it's reducing costs are improving my risk. Posher whatever that end goal is on dhe, you know, when we look at use cases across the industry, risk and data is with one of the easiest use cases to get started with, say, on Ben Field. They were looking at Solvent E to calculations for 25 million other policy holders, and they reduce that time from 10 days to 10 minutes. That is a, you know, really good use case off getting moving to the cloud. You know, if Indra is a great example. They're very public customer analyzing 38 building over market records in the stock market and looking in on alive in all of the data. On it up with data and risk is one of the core use cases that companies start with but then >>has to >>get more as they learn more about the cloud. As they get more get a deeper understanding, they start looking at other things, like Transforming Corp core applications. Today we have core creating applications, scored insurance application score, banking applications that are running running on the cloud. And then they start looking and innovation. You know, how do we look at artificial intelligence? How do we look at machine learning? How do we look at the new technologies to really transform our business and one of the great use case? And we thought so. You know, a lot off insurance companies Liberty Mutual using Lexx as part of their there was a conversational agent for their customers. But one of the interesting examples I have is it's ah, it's a reinsurer in Denmark, Italy insurer in Denmark, and what they're doing is they're using image recognition from from Amazon to look at on accident in the field and then analyzing that, using the using our recognition service to see what that that actual damages and what the cost is and feeding that information to the underwriter really compressing the time that it takes two from a clean filing to processing and payment to a matter of a few few few hours on getting that payment to the to the customer. So really creating a very positive customer experience. >>So it speaking of customer experiences, what have you know? You said you thought you were in service to your shareholders. What have been some of the results that you've seen? >>So you have to look across the organization, right? So our advisers served the need on the retail side, so we were like a bee to be business, right? So we have to be cognizant of what's going on in their world. They're sitting down with clients and talking through the choices, and they have certain needs what they need to fulfill their obligations. They need to explain why they're doing what they're doing. If Putnam knows where each of the advisers are at in their journey with their clients, we can be more helpful to them in explaining why our funds are behaving the way they are right, that information can be had at the right time at the right moment when they need it. Need it, And that brings advisers closer to our our teams are retail distribution teams are marketing teams are investment teams are investment professionals, are using data and analytics to get information to. We're using technology to get information to them faster, so companies are doing releases. There's a ton of information out there these days. We're using technology to dig deeper into the press releases as well as the SEC filings, looking at the footnotes, really trying to understand what they're trying to say, what they said before and what are analysts should be focused on. And we can take a 70 page document, condense it to seven pages and pinpoint what the technology tools say's are really insights. And the analysts will take the time and read the whole thing. But they'll also look at the insides and they'll add it into their process. So technology's additive to the investment process and really making a change help and then that's helping Dr performance. So at the end of the day, we're living good performance on our funds through data analytics technology, you know, give you another example. Some off the were were very strong in the in the mortgage analytics business and on the fixed income side. Our team's very well known. They've been together for many, many years now. They're starting to use data at scale, and we found that being able to go to the cloud to do these analytics right in hours instead of days has really made a material difference in the number of iterations we can run. So now the questions are, when we do risk management, can we do that a little differently and run more reiterations and get more accuracy? So we're seeing all of that benefit. That's direct user experience, that people are seeing people seeing how technology is helping them do a better job with their thesis. >>Excellent. Thank you so much for coming on. The Cube seem ed knitting and shale. A pleasure having you on. >>Thank you for being here. >>I'm Rebecca night. Stay tuned for more of the cubes. Live coverage of the Ex Center Executive Summit coming up in just a little bit

>>Live from Copenhagen, Denmark. It's the cube covering Nutanix dot. Next 2019 brought to you by Nutanix. >>Welcome back everyone to the cubes live coverage of next here in Copenhagen. We are of course here at the Nutanix show. We are wrapping up a fantastic today show. I'm your host, Rebecca Knight. Been Cosa hosting alongside of Stu Miniman. We are joined by Simon Taylor. He is the CEO of haiku, a good friend of the cube. Thank you so much for coming back on the show. It's a pleasure to be here. It's great to see you guys again. Final guest. Oh my gosh. It's a, it's a fare to stay interested in your energy. Yes. So for our viewers who are not as familiar with haiku, tell us a little bit about your business and how you are a strategic partner of Nutanix. >> Sure, sure. So haiku actually is a software company that focuses on data protection as a service. We actually started by spinning out of a much larger company called calm train that had about a thousand engineers and was doing all sorts of things, but they had an amazing talent for building backup and recovery software. >>Um, my vision was really that we can move up the value chain and we can establish ourselves as our own brand, as long as we could find a place in the market that was fast growing, building like a rocket ship and was really requiring a new kind of data protection and backup. And honestly, as soon as we fell, we saw Nutanix, we sort of fell in love. We realized that, you know, they had developed an entirely new category of business with hyperconverged and they were really a pioneer in that space. So we said is why don't we build the world's first purpose-built backup and recovery for Nutanix? And that's exactly what we did. And I think, you know, Stu was actually one of the first people to ever hear about it. Uh, we came on the cube and we talked about that. We've GA that in 2017 in July. I think@that.next, um, so just two and a half years later, we now have 1200 customers and we're in 62 countries around the world. So it's been absolutely astonishing. It's been wonderful growth. We're seeing 300% year over year growth. Uh, and really a lot of that is just based on our ability to protect the data of Nutanix customers around the world. >>Well and and Simon, right? That early question was, is new CanOx is going to be big enough to support ISV is that, you know, can run the, you know, grow their business underneath them before we get further and talk about mine and everything. Give us a little bit, you know, the state of the state for haiku because started with Nutanix, but that's not the only solution they are offering Dave. So just give us kind of the snapshot of the whole business. >>What we realized as we were building out high Q in this purpose build backup recovery for new TEDx. We said that's the on-prem, you know, but there's a lot of on prem that is still legacy three tier architecture. So we added a VMware product. But really the goal was to offer true multi-cloud data protection as a service. So what we did is we built the independent purpose-built backup and recovery service from Nutanix, one for VMware. Then we built the world's first purpose build backup as a service for Google cloud. And I'm really thrilled to announce the next month we're launching Azure backup as well. And the brilliant thing about our system and our solution is that we actually enabled customers to not only back up their data independently for that cloud, but that then migrate their data to whatever other cloud they want to use. So we actually becomes data protection as a service, data migration, and dr. >>So for, for customers, this is wonderful, but how is it to be strategic partners with all of these big players? >> Oh yeah, absolutely. I think you have to place your bets, right? So if you notice, I didn't say AWS and almost every company that I talked to says, why wouldn't you start with AWS? They're the biggest, you know, that's never been our philosophy. You know, I think the fact that we attach ourselves to Nutanix so early, not just because they were a rocket ship on fire, but also because we truly believed in their vision. We believe in the Nutanix products, we love Daraja entire philosophy around simplicity and customer delight and we felt like we could be students of Nutanix, we could actually build out our product with those same philosophies and principles in mind. You know? So I think really going deep with Nutanix is number one for us remains number one. I would also say though that you know, Google has been an excellent partner and Microsoft been an excellent partner. So with the large cloud providers you have to take a different approach. You cannot offer a downloadable product, right? All of our public cloud backup and recovery is a true managed service. You go into their app store, you turn it on rather than download it, you configure and you're able to perform all your backup and do all your recovery right from the console. >>All right, so Simon let, let's get into the kind of the, the, the guts of what's happening at Nutanix. Mine, of course is a partnership to extend for data protection, partnering with Veeam and haikus as a, as the first two partners. Uh, the other thing that everybody's pretty excited about is XY clusters. And that sounds like, and we've talked to Newtanics people, you know, as Nutanix brings their stack into the clouds, not just on the clouds, will that pull things like mine along with them. And so, so give us what you're seeing with mine first and maybe he's, I clusters along. >>Yeah. So maybe we start with mine, right? This whole concept that I think that these guys have pioneered and they've done a really terrific job of it. I think, you know, the, the vision there, and you know, I count marketing or Meyer in this group and Tim Isaacs and some wonderful folks on the product team in Nutanix. Their vision was, you know, there's rubric and there's Cohesity, there's these sort of large secondary storage platforms. Personally, when I look at them, what I see as Newtanics with a backup workload, right? And I think that, you know, Nutanix being the original is the best. It's the most complete solution. And it's very, very comprehensive. So I think the, the tannics folks understood this intuitively and their idea was instead of us building our own backup and going after that space, we've got amazing partners like haiku. Why don't we just natively integrate them into the mind platform and offer that sort of secondary storage workload, uh, as a key part of Nutanix is product proposition. >>So the really exciting thing for us is that we are skewed up with Nutanix. Nutanix, we'll be able to resell haiku as a part of mine. Uh, and I think that's gonna really complete their end tour tire story when it comes to being able to own the data center, uh, and really own the sort of cloud in general. You know. So I think your second question still was about clusters. And I think that the answer there is very simple. You know, multi Gloucester is, has become extremely important for Nutanix customers. They've done a great job of going after that. The simple fact is if you don't support XY clusters as a backup vendor, you really can't compete in this market. So I'm really thrilled to announce, of course, that haiku is the first backup recovery vendor that does support. Gluster. >>Okay. So interesting. We talked about how you hadn't done a solution for AWS. Sounds like this might be a path for you to get with Nutanix onto AWS. >>Absolutely, absolutely. And again, for us it's not about looking for some Trojan horse or backdoor into a go to market strategy. It's about making sure that the customers are truly delighted by the value that we provide. And I think that when we go after a specific market, we want to do it the best, you know, so we don't go shallow and just sort of check the box. We want to make sure, for example, when we build out Azure that we're not just dealing with, you know, the, the general principle of backing up and keeping things consistent. We want to make sure the applications people are running on Azure or supported by haiku. That's what we do with Nutanix. That's what we do with GCP. We want to always go as deep as possible so we can really compliment the platform in a really, really comprehensive way. >>One of the things you said earlier was that your philosophy is very much aligned with Nutanix, your your end goal to simplify and delight the customer, uh, this, this much more intuitive, uh, youth and user interface. So talk a little bit about how you, you said you wanted to become a student of Nutanix, yo, this, this cross company learning is very interesting to me. How, how, what have you learned? Yeah. What have you learned and how do you go about being tutored by your customers? >>No, I'm a very visual guy, right? And whenever I think about Nutanix, I always had this image in my head. All right. Whenever I thought about legacy, three-tier architecture and the move to hyperconverged, rather, I always pictured an 80 stereo system. Remember those big eighties boxes? And they have all the graphic equalizers and all the way down. And some kid would come and push them all down. You could never reset the darn things, you know? And then along comes, you know, automation and suddenly, you know, you press a button and you listen to jazz and it sounds like good jazz and the treble and the bass all fixed themselves. You know, I effectively think that Nutanix brought that same concept, funnily enough into the data center. They simplified so much that was impossible to handle for admins across the world. They made it so simple to use their product that actually the customers could start to enjoy their work more. >>And I really love that. That's a true, that's a really an intangible sort of value proposition that I think people don't talk about it enough. Yes, you want to save time. Yes, you want to save money, but if you could enjoy your job more as a result of getting a product, what's better than that? Um, so I think that philosophy is something we baked into haiku in the following ways. You know, the first is when we were designing the UI, we wanted it to look and feel like the platform it supports. So when you use haiku for Nutanix, it looks like prism, when you are using our console for GCP, you're gonna feel like you're using GCP. The idea is that backup and recovery should be an extension of that cloud expression, that platform, so that the customer who is an expert with that platform can easily manage this with no training at all. So again, driving that simplicity right there and in the platform. >>Yeah. So Simon, you know, one of the things we love to do is get hear from customers and what they're doing. Of course you've got 1200 customers that are Nutanix customers. So we'd love to hear, you know, any insights you have in a lot of discussion about AHV in the last 12 months has been about half of the deployment. Is there anything around HV or any of the, you know, new software features and products and experiences that Nutanix has been launching that you hear customers buzzing and talking to you about? >>I mean, I, I, the first thing I would say is it is truly a multicloud world now. Um, I think that legacy vendors are having a harder and harder time coping with the fact that cloud washing no longer works. You know, if you show up to the market and you say, Oh, this, now I can deploy an agent into this cloud, it's sort of stop, stop, don't say agent around me. You know? So I think, I think the ability to really natively integrate into any of these clouds and support all of these clouds equally is key. You know? So in the past a vendor would start with one thing and it would be great, right? And I won't use names here, but then they would do something else. They might move to another hypervisor and it was a little bit less great. Right. And I think that that notion has to change in a multicloud world, which brings me to the concept of HV. >>I think that HV has really grown. I mean, I would say that right now, you know, over half of our customers are HV customers. And I would say that that grows every single quarter and it not only grows in terms of net new logos, it also grows in terms of existing customers that we're finding SWAT to switch to HV and they want to switch fast. You know, they don't want to pay the V tax anymore, but more than that, I think they're seeing HV as a really robust enterprise hypervisor that really meets the complete need for the customer. And I think that's, that's been terrific to watch. So when you hear at.next, and this is not your first hot next, but what kinds of conversations are you having? What's been interesting to you? What are you going to take back to haiku? Yeah, head back to Brookline. Yeah. >>I mean obviously there's all the new stuff. I mean, Kubernetes, you know, containers. Um, I think these are all things we've been working on for some time. We'll have some surprises for you guys in Q4 at the end of Q four around that. Um, but you know, I think the big takeaway for me is we spent the first two years building our brand, getting the word out there, proving to companies and customers around the world that we were truly enterprise ready cause we were the new kid on the block. And you have to sort of start somewhere and show that. I think now we, you know, we added physical last year, we added tape support, we've really got all of the major applications covered at this point. I think that conversation, we've checked the box, right? So today's conversations are about what's next, how much more deeply will you integrate with Nutanix? >>How can I use Nutanix to then manage my data in the cloud and bring it back again? And can haikus support that or will it distract me? And you know, the simple answer is it will support that completely because it's so natively integrated. You know. And again, I think when you choose a platform at this stage, and this is something we've seen again and again and again, people do not want a second silo, right? In order to, you know, run their backup and recovery. You know, customers who are choosing Nutanix or choosing any platform want to run that platform and they want to make that one holistic experience. You know, they want to reduce the training required and they want to make sure they get the most out of their investment. So we're where I think two or three years ago, Stu, when we first met, everybody was trying new things, right? It was sort of, there were all these new platforms and it was all very exciting. I think now people are doubling, tripling, quadrupling down on the platforms they fundamentally believe in. And we're thrilled about that because we support those platforms and we'll continue to do so. >>Great. Excellent little. Simon, thank you so much for coming on the cube. It was a real pleasure talking to you and it's been great. Yes, no, absolutely. Thank you very much. Thank you so much. Thank you for having me. That wraps up two brilliant days in Copenhagen at the Bella center at Nutanix dot. Next. Thank you so much for joining us and we hope to see you next time.

>>live from Copenhagen, Denmark. It's the Q covering Nutanix dot next 2019. Brought to you by Nutanix >>Welcome back, everyone to the cubes Live coverage of Nutanix dot Next I'm your host Rebecca Knight alongside my co host Stew Minutemen. We have two guests for this segment we have. Mika will lose. She's the art director for Nutanix Thank you so much for coming on the show. >>Thank you for inviting me >>And we have Satish Ramachandran, Global head of design at Nutanix Thank you so much for coming on. So it's always so much fun to talk to really creative people, particularly in this technology world. I want to start the conversation by asking Michael first where you go for inspiration and who do you talk to? What he read? What kinds of things do you look at to inspire you to and then bring them back to your job here in Nutanix. So I strongly >>believe that inspiration come from everywhere. No matter where you go is an architecture or you go to the supermarket and you look on packaging or you read a book and you think about images or even just social media. And there is so much variety of different opinion and different cultures to get inspired from. Even from this conference, we took inspiration from Copenhagen, the city, and from Swiss design or from California and divide in the mid century. I put, like not in construction, but like architecture. Er, um, we created this really Sundwall the supreme the best day ever. And I was actually reading a book with my kids, the diary of a wimpy kid. And I was like, Okay, you know what? We can make something really fun out of it. We can take like a page from a diary and create Sabrina Best day, something like that. >>It was truly everywhere. >>It's really every. >>How about Yusa? Tish >>men? It's two parts, actually. I think one is the inspiration when it comes to the aesthetics of design. So to a large degree, I'm a huge fan off minimalism, everything from Japanese paintings, for example, where with two or three strokes, you have a stark on the water. The Bauhaus movement clean, elegant lines very minimal to the point, and even the Scandinavian architecture, for example, is quite minimalistic and very clean. So that is one angle on what we strive to do in terms off getting to minimal, clean, simple. But in the other portion of inspiration is actually comes from empathy because, you know, it's the you know, I care deeply about the human condition, even pre Nutanix sort of teenage angst that never left me right. And ah, so in a sense, is a lot of empathy. Toe what people are going through in terms of technology, how they're using it. How can we make their lives easier? How can we bring about some joys in their life and to a large degree, the secretary working? You know, I t, um, has bean sort of underserved design wise for many years on de. So there's a lot of inspiration that comes in the form of motivation in order to do something for people there. >>Well, yes, it's a teacher, I'm wondering, can help connect the dots with us. I think of minimalism and obviously ties to this simplicity Nutanix and remember in the early days, talking Nutanix to make something truly simple from a technology standpoint usually has a lot of work, and we've been talking to the executive team about, you know, in this multi cloud, highly disperse. Tear it even harder today. So how does some of those core design principles make their way into into Nutanix is world. >>You want me to talk about the process? You know, I >>think >>the process is quite straightforward. I mean, you start with understanding the space, understanding the experience that exists in the space. You don't start with the feature or the product. That's the first thing you start with the people. So you started with a very human centric manner on. Okay, What are they trying to do? What are they trying to achieve and how do you get them in the simplest possible manner to do that? So we have this thing that we use called intentional our design, which is one off our design principles. Very. How do you get someone who has an intention to fulfill their intention with the least amount of effort? And the effort in the middle is what we label less friction constantly. So we talk about trying to become friction less and so on. So the process for that is you start with the person what they're trying to get done, and >>from there you actually >>work all the Muslims in the organization. So design, basically at that point takes on the role of a facilitator by bringing in, you know, engineering product management design itself together and all in service off the user to create an experience, right? So it starts with, you know, formulating the requirements together with engineering and product management. It's address it, then converging on these things by creating prototypes than testing these things with users and so on and then figuring out really what is essential, what can be thrown out and how to keep it really simple. And that's how we build product, basically. >>So that's so. As you said, it starts with this point of empathy, and that is this collaborative process between the engineers and the artists and design team. How would you say that design is more part of the Nutanix philosophy, just rather than the simple, simple, easy, elegant products itself but the entire company? How would you say it's it's built into the philosophy? I actually think this is >>why Nutanix is so unique in our space because we don't just look at the technology we looking at a whole package of design and technology, the left brain and the right brain together. And it comes from our leadership because, dear, it is the great advocator for design. He's really believing in the importance of it, not just a pretty rap on something, but it's something that is meaningful and and really able to provide a full experience for our customers. >>Yeah, meet me how maybe I love to get you both of your commentary. There's a new AH advertising campaign that was launched. The video was in the keynote yesterday. >>It >>all together now it is very colorful, and it is very diverse and at the same time, even, you know, I'm a technology guy. I will often roll my eyes when I see a certain advertising, but to articulate to the world, it's like, Okay, how does my database and multi cloud and all these things play together? Well, way we anthropomorphized though those technology pieces into people on dhe. You've got photos that you can do there, so bring us inside a little bit as to how that you helped the messaging eso some, you know, pretty complex pieces underneath. >>Yes, we're very excited about this campaign. I have to tell you. We worked very hard to conceptualize it and bring it out to the world. And we were very excited to be able to share it here. That next the thinking behind it. Waas, you know I to world is complex and here in Nutanix, we really try to offer a simple way to remove this complexity. So what is a better way than just take those I t concept and business an application manners and personalize them and make them fun. And when you think about Public Cloud, what do you mean? What does it mean to you? How do you envision it when you think about a database? Do you think about the strongman that carrying the cylinder and you >>make it a >>campaign Maur You humanize it, you make it accessible to people and you make it fun And this is what we're trying to do We're trying to delight. Our customers were trying to empower them to be able to do their business in a better way, and that was our goals provide simplicity, choice and delights. >>And as you said, it's it's this ample anthropomorphizing of this. If you've a database where a person what would go with the database person look like it's the cloud Where Human? Yes, exactly. And it just I think they just >>make make it fun and you make it unique and you create something that is different in our scene. And nothing, That's what we're trying to do. >>How do you work together with the engineers? I mean, I know you said. You gather in a room and you are thinking about the end user. How does the customer experience this? But how do artists and engineers communicate? I mean, is that Is that ever a challenge or >>not? Really? No, not really. Actually, it's, Ah, it's a three legged stool. Basically, there's ah, and you know, if you put marketing in there as well for the awareness piece, which precludes anything that we you know the customer uses, it actually becomes a four legged stool. But in terms of building product, it's a three legged stool, which is product management, and they're trying to figure out what is the product market fit, and that's what they bring to the table. The engineer's coming and as we're dreaming up stuff, they're thinking, Is this stuff buildable or not? You know these guys dreaming way too much, right? And so it is a colonization. So and I think that's the crucible in which the best creativity actually comes out. It's not designing isolation where, you know, design dreams up something and the rest of the folks build it. It really isn't that so. We are, actually, in a sense, the way I see it, we have the glue and we formed the Crucible for the colonization. And and in that, you know, good things come out. >>So we hear you are in Denmark, which is design savvy, fashion forward, food obsessed and eyes cultivating that sense of well being in comfort and coziness. What kinds of things are you going to take with you from this conference itself? What are you seeing? What's interesting to you? And how are you gonna bring that back to Nutanix? >>Honestly, for me, I think it's just the warmth of the people in the community in here. They were so invasive and and and kind. And we got a chance to work with a lot of people when we were building this conference. And and to me it's all about the human connection and I think this is something that I will definitely carry with me when we go back to Nutanix. And we were trying to think about our next dock next conference. And you know how we can bring some of that too there as >>well? Yeah, it's to teach anything on dot next Copenhagen, and you know, you're from Berlin, so you're in Europe and get gets a different, you know, cultural input. I >>think they're still. I think >>there is still some stuff. I think around the accessibility mainly for me, like the hotel we're staying. And, you know, first thing I noticed was, you know, that's bringing on, you know, when you have to open the refrigerator, for example, or the closet door And it, I mean, that first thought was like, you know, they have already designed in the accessibility. And then I liberate that back to product, and I think you know how we doing on accessibility. And of course, you know, everything around you here is pretty inspiring in terms of architecture and so on and so forth. So that's a gimme, really. And you see that a lot of it in Germany so that it isn't as much new, but in terms of the conference, it's very heartening that will come this fire. You know, I don't know. Miami many years ago, which is my first conference, you know, we were like all of 600 people, and now we are 4500 here. So in a sense, it's very heartening. And people seem to embrace the, you know, the vision that we're putting foot. Yeah, you know, around convergence off many, many things. >>How deeply technical are both of you? Um, I understand. >>I understand the technology. I understand the struggle. I understand what we're trying to achieve is a company. It doesn't mean I can go and do a demo on stage, but I think it's important to understand the technology of the company that you work for in order to represent it truly and in order to convey the message that we're trying to tell because we are a storyteller. That's what we do. We take the message and the technology, and we bring it out to our customers. So it's important. >>I'm a dyed in the wool engineer s o. I was I mean, my cases where I was an engineer for a fleet to the kids. You know, you take running engineering teams, that kind of stuff. And then I stumbled upon design. So I have a very deep understanding off engineering and what it takes to build stuff. But I have another side of me which is generally around. Empathy, experiences, you know, human interaction, human behavior. What makes people take what frustrates them, those kinds of things. So for me that we design has beena synthesis off many off my interests, and that's why I fell in love with it and have stuck around. >>One of the biggest issues in Silicon Valley and in the technology industry at large is is the skills and the right people the talent gap? How much of an issue is that for the design teams within these technology companies? Because you are looking for so many different skills people who can grasp the technology but then also have this more creative spark Innis to them to how hard is it to find the right people? I think it's a little bit >>of a challenge, but I think we're very fortunate to have amazing teams that understand technology and design in the connection between them. So I know I feel very fortunate with the people I get to work with. Their very there are amazing. Yeah. >>I mean, it was hard in the beginning when we when Nutanix was 150 people or something on the brown. Nobody knew. So then it was very hard to find the right people and to also simplified the vision and to sell it. I still remember spending with every new hire. I would be the first guy they would talk to. And I spent two years in two hours on a whiteboard, talking of taking borders, a technology problem on translating it into an experiential problem. And speaking to really this is very hard to design for and that's where the challenge lies, right? But what a period of time we have successfully built a brand which is a Nutanix design brand. And we have done a ton of things that I'm actually very proud off establishing relationships with universities, even on the social media, having a website, having a proper blawg, various things. When Now we are recognized in the enterprise space as a place for designers to go and work. And there is a certain combination. I figured out where which makes for a good designer in the space. Because if you take people with too little off a technology background, then the ramp up is very high. S o. If you typically you find somebody who's got done some amount of technology than the prior company or in school. And there are people like that. There are plenty of them. And then they moved on to design. And that seems to be the right mix because they can understand the empathize both on the technology side and also on the design side of things. And that makes for the right combination. >>And it's not >>too bad to find people. >>And I think >>technology can be talked. But I think passion and carrying is that part of it is hard to find >>be innate skills. Yeah, exactly. Great. Well, Miguel and McHale and Satish thank you so much for coming on the Cuba and fun and enlightening a conversation. Thank you so >>much. It's great to be here. Thank you so much. >>Thank you, guys. >>I'm Rebecca Knight for stew Minutemen. Stay tuned for more of the cubes. Live coverage of Nutanix dot Next

>>live from Copenhagen, Denmark. It's the Q covering Nutanix dot next 2019. Brought to you by Nutanix >>Welcome back, everyone to the cubes. Live coverage of Nutanix dot Next here at the Bella Centre in the Copenhagen. I'm your host, Rebecca Knight, coasting along side of stew, Minutemen were joined by Bala Coochie bottler >>Bhola. He is the VP GM Nutanix era and business critical lapse at Nutanix. Thanks so much for coming on the island. >>It's an honor to come here and talk to guys. >>So you were up on the main stage this morning. You did a fantastic job doing some demos for us. But up there you talked about your data, your days gold. And you said there are four p's thio the challenges of mining the burning process you want >>you want to go through >>those for our viewers? >>Definitely. So for every business, critical lab data is gold likely anam bigness for a lot of people are anyone. Now the question is like similar to how the gore gets processed and there's a lot of hazardous mining that happens and process finally get this processed gold. To me, the data is also very similar for business could collapse. Little database systems will be processed in a way to get the most efficient, elegant way of getting the database back data back. No. The four pains that I see for managing data businesses started provisioning even today. Some of his biggest companies that I talkto they take about 3 to 5 weeks toe provisions. A database. It goes from Infrastructure team. The ticket passes from infrastructure team, computer, networking stories, toe database team and the database administration team. That's number one silo. Number two is like proliferation, and it's very consistent, pretty much every big company I talkto there. How about 8 to 10 copies of the data for other analytics que year development staging Whatever it is, it's like over you take a photo and put it on. What Step and your friends download it. They're basically doing a coffee data. Essentially, that Fordham be becomes 40 and in no time in our what's up. It's the same thing that happens for databases, data bits gets cloned or if it's all the time. But this seemingly simple, simple operation off over Clone Copy copy paste operation becomes the most dreaded, complex long running error prone process. And I see that dedicated Devi is just doing Tony. That's another thing. And then lineage problem that someone is cloning the data to somewhere. I don't know where the data is coming from. Canister in The third pain that we talk about is the protection. Actually, to me it's like a number one and number two problem, but I was just putting it in the third. If you're running daily basis, and if you're running it for Mission critical data basis, your ability to restore the rhythm is to any point in time. It's an absolute must write like otherwise, you're not even calling The database. Question is, Are the technologies don't have this kind of production technology? Are they already taken care? They did already, but the question is on our new town expert from Are on Cloud platform. Can they be efficient and elegant? Can we can we take out some of the pain in this whole process? That's what we're talking about. And the last one is, ah, big company problem. Anyone who has dozens of databases can empathize with me how painful it is to patch how painful it is to get up get your complaints going to it. Holy Manager instead driven database service, this kind of stuff. So these are the four things that we actually think that if you solve them, your databases are one step. Are much a lot steps closer to database service. That's what I see >>Bala. It's interesting. You know, you spent a lot of time working for, you know, the big database company out there. There is no shortage of options out there for databases. When I talked to most enterprises, it's not one database they now have, you know, often dozens of databases that they have. Um so explain line. Now you know, there's still an unmet need in the marketplace that Nutanix is looking to help fill there. >>So you're absolutely right on the dark that there are lots of date of this technology is actually that compounds the problem because all these big enterprise companies that are specially Steadman stations for Oracle Post Grace may really be my sequel sequel administrator. Now they're new breed of databases in no sequel monger leave. You know, it's it's like Hardy Man is among really be somebody manage the Marta logics and stuff like that so no, we I personally eating their databases need to become seemed like Alex City. Right? So >>most of >>these banks and telcos all the company that we talk about data this is just a means to an end for them. So there should focus on the business logic. Creating those business value applications and databases are more like okay, I can just manage them with almost no touch Aghanistan. But whether these technologies that were created around 20 years back are there, there it kind of stopped. So that is what we're trying to talk about when you have a powerful platform like Nutanix that actually abstracts the stories and solve some of the fundamental problems for database upstream technologies to take advantage of. We combine the date of this FBI's the render A P s as well as the strength of the new tenants platform to give their simplicity. Essentially. So that's what I see. We're not inventing. New databases were trying to simplify the database. If that's what >>you and help make sure we understand that you know, Nutanix isn't just building the next great lock in, you know, from top to bottom. You know, Nutanix can provide it. But Optionality is a word that Nutanix way >>live and time by choice and freedom for the customers. In fact, I make this as one of the fundamental design principles, even for era we use. AP is provided with the database vendors, for example, for our men, we just use our men. AP is. We start the database in the backup, using our many years where we take that one day. It is the platform. Once the database in the backup more we're taking snapshots of the latest visit is pretty much like our men. Regan back up with a Miss based backup, essentially alchemist, so the customer is not locked in the 2nd 1 is if the customer wants to go to the other clothes are even other technologies kind of stuff? We will probably appear just kind of migrate. So that's one of the thing that I want to kind of emphasize that we're not here to lock in any customer. In fact, your choice is to work. In fact, I emphasize, if the customer has the the computer environment on the year six were more than happy weaken. Some 40 year six are his feet both are equal for us. All we need is the air weighs on era because it was is something that we leverage a lot off platform patent, uh, repentance of Nutanix technology that we're passing on the benefits canister down the road where we're trying to see is we'll have cyclists and AWS and DCP. And as you and customers can move databases from unpromising private cloud platform through hybrid cloud to other clusters and then they can bring back the data business. That's what we can to protect the customers. Investment. >>Yeah. I mean, I'm curious. Your commentary. When you go listen, toe the big cloud player out there. It's, you know, they tell you how many hundreds of thousands of databases they've migrated. When I talk to customers and they think about their workload, migrations are gonna come even more often, and it's not a one way thing. It's often it's moving around and things change. So can we get there for the database? Because usually it's like, Well, it isn't it easier for me to move my computer to my data. You know, data has gravity. You know, there's a lot of, you know, physics. Tell General today. >>See what what is happening with hyper killers is. They're asking the applications. Toby return against clothed native databases, obviously by if you are writing an application again, it's chlorinated. Databases say there are Are are are even DCP big table. You're pretty much locked technical because further obligation to come back down from there is no view. There's no big table on and there's no one around. Where is what we're trying to say is the more one APS, the oracles the sequels were trying to clarify? We're trying to bring the simplicity of them, so if they can run in the clover, they condone an art crime. So that's how we protect the investment, that there is not much new engineering that needs to be done for your rafts as is, we can move them. Only thing is, we're taking or the pain off mobility leveraging all platform. So obviously we can run your APS, as is Oracle applications on the public lower like oracle, and if you feel like you want to do it on on from, we can do it on the impromptu canister so and to protect the investment for the customers, we do have grown feeling this man, That means that you can How did a bee is running on your ex editor and you can do capacity. Mediation means tier two tier three environments on Nutanix using our time mission technology. So we give the choicest customers >>So thinking about this truly virtualized d be what is what some of the things you're hearing from customers here a dot next Copenhagen. What are the things that you were they there, There there Pain points. I mean, in addition to those four peas. But what are some of the next generation problems that you're trying to solve here? >>So that first awful for the customers come in acknowledges way that this is a true database. Which letters? I don't know what happened is what tradition is all aboard compute. And when when he saw the computer watch logician problem you threw in database server and then try to run the databases. You're not really solving the problem of the data? No, With Nutanix, our DNA is in data. So we have started our pioneered the storage, which location and then extended to the files and objects. Now we're extending into database making that application Native Watch Ladies database for dilation, leveraging the story published Combining that with Computer. What's litigation? We think that we have made an honest effort to watch less data basis. Know the trend that I see is Everyone is moving. Our everyone wants cloudlike experience. It's not like they want to go to club, but they want the cloud like agility, that one click simplicity, consumer, great experience for the data basis, I would liketo kind of manage my data basis in self service matter. So we took both these dimensions. We made a great we made an honest effort to make. The databases are truly watch list. That's the copy data management and olive stuff and then coupled with how cloud works able to tow provisions. Self service way ability to manage your backups in self service. Weigh heavily to do patch self service fair and customers love it, and they want to take us tow new engines. One of the other thing that we see beget Bronte's with ERA is Chloe's. Olive or new databases generally are the post press and the cancer, but there's a lot of data on site because there's a lot of data on Mississippi. Honey, there's a lot of data on TV, too. Why don't we enjoy the same kind of experience for those databases? What? What did they do wrong? So can we >>give >>those experience the cloud like experience and then true? Watch allegation for those databases on the platform. That's what customers ask What kind of stuff. Obviously, they will have asked for more and more, um, br kind of facilities and other stuff that way there in the road map that we will be able to take it off. One >>of the questions we've had this week as Nutanix build out some of these application software not just infrastructure software pieces, go to market tends to be a little bit different. We had an interesting conversation with the Pro. They're wrapping the service for a row so that that seems like a really good way to be able to reach customers that might not even knew no Nutanix tell us, you know, how is that going? Is there an overlay? Salesforce's it? Some of the strategic channel and partnership engagements, you know, because this is not the traditional Nutanix, >>So obviously Nutanix is known. Andi made its name and fame for infrastructure as service. So it's really a challenge to talk about database language for our salespeople. But country that I heard the doubt when I kind of started my journey It Nutanix Okay, we will build a product. But how are you going to the city? And we get off this kind of sales for But believe me, we're making multimillion dollar deals mainly led by the application Native Miss our application centric nous so I could talk about federal governments. And yes, she made perches because it was a different station for them. We're talking about big telco company in Europe trying to replace their big Internet appliances because era makes the difference vanished. We're providing almost two X value almost half the price. So the pain point is real. Question is, can we translate their token reconnect with the right kind of customer? So we do have a cell so early for my division. They speak database language. Obviously we're very early in the game, so we will have selected few people in highly dense are important geographic regions who after that, but I also work with channels, work with apartments like geniuses like we prove head steal another kind of stuff and down the best people to leverage and take this holding and practice. This is the solution. In fact, companies like GE S D s is like people take an offer. Managed database seven. Right. So we have a product. People can build a cloud with it. But with the pro they can offer in a word, why do you want to go to public Lower? I can provide the same cloud. Man is database service more on our picks, Mortal kind of stuff. So we're kind of off fighting on all cylinders in this sense, but very selectively very focused. And I really believe that customers fill understand this, Mrs, that Nutanix is not just the infrastructure, but it's a cloud. It's a It's a club platform where I considered arise like Microsoft Office Suite on Microsoft's operating system. Think about that. That's the part off full power that we think that I can make make it happen >>and who are you know, you said you're going in very tight. Who are these Target customers without naming names? But what kinds of businesses are they? You know? How big are they? What kinds of challenges. Are >>they looking at all? The early customers were hardly in the third quarter of the business, but five. Financial sector is big. The pain point of data mismanagement is so acute there capacity limitation is a huge thing. They are spending hundreds of millions of dollars on this big. When that kind of stuff on can they run in the can extract efficiencies out of this hole all their investment. Second thing is manufacturing and tell Cole, and obviously federal is one of the biggest friend of Nutanix and I happened to pitch in and religions is loaded. And they said, Israel, let's do it real demo. And then let's make it happen. They actually tested the product and there are taking it. So the e r piece, where are they? Run Oracle, Where the run big sequence kind of stuff. This is what we're seeing. It >>followed. Wanna make sure there was a bunch of announcements about era tudo Otto, Just walk us through real quick kind of where we are today. And what should we be looking for? Directionally in the future. >>So we started out with four are five engines. Basically, Andi, you know that Oracle sequel and my sequel post this kind of stuff, and we attacked on four problems this provisioning patching copy, data management and then production. But when we talked to all these customers on, I talked to see Ables and City Walls. They love it. They wanted to say that Hey, Kanna, how around more engines? Right? So that's one will live. But more importantly, they do have practices. They have their closest vehicles that they want to have single pane of management, off era managing data basis across. So the multi cluster capability, what we call that's like equal and a prison central which manage multiple excesses. They weren't error to manage multiple clusters that manage daily basis, right? That's number one. That's big for a product with in one year that we regard to that stage. Second thing was, obviously, people and press customers expect rule rule based access control. But this is data, so it's not a simple privilege, and, uh, you would define the roles and religious and then get it over kind of stuff. You do want to know who is accessing the data, whether they can access the data and where they can accident. We want to give them freedom to create clones and data kind of act. Give the access to data, but in a country manor so they can clone on their cure. Clusters there need to file a huge big ticket with Wait for two weeks. They can have that flexibility, but they can manage the data at that particular fear class. So this is what we call D a M Data access management. It's like a dam on the like construct on the river, control flow of the water and then channel is it to the right place and right. But since Canister, so that's what we're trying to do for data. That's the second big thing that we look for in the attitude. Otto. Obviously, there's a lot off interest on engines. Expand both relation in Cecil has no sequel are We are seeing huge interest in recipe. Hannah. We're going to do it in a couple of months. You'll have take review monger. Dubious. The big big guy in no sequel space will expand that from long. Would it be to march logic and other stuff, But even D B two insiders There's a lot of interest. I'm just looking for committed Customers were, weren't They are willing to put the dollars on the table, and we're going to rule it out. That's the beauty of fair that we're not just talking about. Cloud native databases Just force Chris and kind of stuff. What? All this innovation that happened in 30 40 years, we can we can renew them to the New Age. Afghanistan. >>Great. Well, Bala, thank you so much for coming on. The Cuba was >>Thank you. >>I'm Rebecca Knight for stew minimum. Stay tuned. For more of the cubes. Live coverage of Nutanix dot next.

(upbeat music) >> Narrator: Live from Copenhagen, Denmark, it's theCUBE covering Nutanix.NEXT 2019. Brought to you by, Nutanix. >> Welcome back everyone to the cube's live coverage of Nutanix.NEXT here at the Bella Center in Copenhagen. I'm your host Rebecca Knight, alongside of my co-host Stu Miniman, Analyst. We have two guests for this segment. We have Angie Cusworth, she is the COO of Hardy Fisher Services. >> Hi. >> Thank you so much for coming on Angie. >> Hi. >> And we have David Cusworth SVP sales at Hardy Fisher Services. Thank you so much! >> Thank you. >> And husband and wife. >> And a husband and wife team! >> I believe we have done it before, I know we've had twins on the program. >> Right, yes. >> Uh, but uh, yeah. >> Couples who work, I like it! We'll get into how you make it all work. But David, I want to start with you. Describe Hardy Fisher Services for our viewers who may be unfamiliar with your company. >> Yeah, so we own and operate a large data center based in Leeds, so it's a 400 watt capacity data center previously built for BT house NHS patient records in the UK. And we operate that as a reseller base data center, so we are a very clear go-to market. We have our co-location, we have money services and then obviously cloud which is based on Nutanix. >> So, wait Angie what are the biggest business challenges that you face in your world. >> So I think it's trying to convince customers to move to the cloud. Obviously, you know, we've been doing cloud for some time now. I don't know how to-- >> Yeah, so David, we're talking about that move to cloud. It help it put where, you know, your services built both now Nutanix fit in the customers overall picture. Cause you know, you've SAS, you've got public cloud people are building private clouds off Nutanix or other type of hardware, so you know how do you play with some of those other components and position yourself? >> I think a lot of the challenges that we've seen is people are comfortable with Azure so a lot of resellers that we deal with. Azure is a safe bet. Nutanix is still quite a new name in the marketplace. There's people who don't want to move to the cloud because they don't understand it. So, a lot of the time, we show them the cloud platform in our data centers, and can touch and feel it they can actually see it. Which gives them a bit more confidence. And then, from our side it's the service wrap, so it's holding them the hands on the journey to the cloud. So it's given our technical ability to say, you know, we'll do it for you, we'll hold your hands, we'll get you working. And at the end of the day, the cloud is people's businesses. So if the cloud doesn't work, it affects their business and we're trying to put our hats on as a customer. >> Yeah, it's funny. It reminds me, we used to have the joke, there is no cloud, there is just you know, your computer somewhere else. Angie, bring us inside, a little bit? Your customers, it sounds like they're still a little bit of trepidation about them making changes there? >> Yeah, I think one of the reasons that we've been so successful, is that we follow IT Service Management very well. So we help our customers through the whole journey. So people that are new to cloud, we have excellent technical people, that can help them. We have a fantastic data center, as well. So, they know their kits are safe with us. >> Yeah, bring us inside a little bit. You talked about how many racks there. What differentiates your data center? There's you know, most companies, you know, we tell the average enterprise out there, you know. Friends don't let friends build data centers. There's other people that know what they're doing. So, give us a little bit of a virtual tour, if you would. >> Yeah, so our data center. Like I said, It was originally built for BT and for the NHS. And as they moved to cloud, the need for their data center shrunk. Leeds as a city is growing city and there's not many data centers in Leeds, so we took the opportunity to really re-launch the data center. We knew it was a very high spec data center, cause it cost a lot of money to build. And it gives the customers confidence that when they are going in there, it's very secure. It's very high resilience. And from a cloud platform, we've gone completely Nutanix. So it is literally, you can come in, you can touch Nutanix, you can play with it. And it's just the whole journey really, that to make sure they're in a safe pair of hands. >> Talk a little bit more about how Nutanix comes into play with your organization. >> We went with Nutanix because we're looking for something to be different. There's a lot of people who've got this UA to be WES in that V seller market. So we wanted something that was focused on SME. So we've got very, very much SME focus. And cost comes into it. Having that support, so being able to ring somebody up and not being in a big call center in Asia or in Europe. Somebody who can actually talk them through, what the issues are, also be very responsive, and put the customer first. >> Yeah, it's interesting, and when I think about kind of the traditional service provider. It's like they've build out their management stack, they build something at a scale, so that, you know, they can do something that their customer couldn't. It sounds like Nutanix is a different type of offering. We've been talking about it all week. It's not thriving in that complexity, but you know you just have a simple offering. And then, of course, you know price and easy to manage. Is something that service providers need, so, It sounds as if you built this ten years ago, you might have had to do something very different then how you do it today. >> Yeah, no, absolutely. It's given us a market that really hasn't been there in the past. You know, we can help resellers on the journey, we can give them a bit of a lift up, so. If their too small or they've just got going in cloud and they can't afford to get their own Nutanix platform, then we can get them going and then they can start going into Nutanix. But it's a real differentiate. It's like I say, to a lot of people, it's the safe bet it's your AWS. It's you know a Microsoft name. No one ever gets sacked for by Microsoft kind of conversation. >> I think one of the other compelling things is the cost of it as well. A lot of people think it's cheaper to go as your AWS. Actually it's mechanics are very cost effective for our customers and that's why it appeals for, you know the kind of smaller resellers that we deal with. >> You know, are you starting to do any connection now that you think about as your AWS have their direct connect. When you have people's environment, sometimes they might want to access those services or are you starting to look that, in that environment? Where some of the Nutanix hybrid solutions? >> Yeah, so what we do at the moment is we backup mainly to Azure. So we've, we've a central core platform with Nutanix and then, we're back up as a failover to Azure. But, again, customers don't like the complexity of even doing that as a back up. So it's been great coming to the event and seeing the Nutanix backup and the options there because our customers love Nutanix. >> So are you interested in the mine solution, that has been rolling out? >> Yes, absolutely. >> Yeah, yeah absolutely. That's one of the things that we're really looking forward to going back to explore. And that will be next on our road map. >> Are you starting to look out as to which solution with mine you're going to use or are you still under discussion? >> Yeah, we'll leave that to our technical director. I'm sure he'll point us in the right direction. >> One of the things we hear a lot about at this conference is Nutanix's culture. It's people first culture. It's humble, honest, hungry. How does that come into play in terms of your interactions with the company? >> I think for us, that's a culture that we have as well in our own business. And that really does shine through for every person that we've ever dealt with at Nutanix. There it's always customer first. I can't fault them, they're amazing. >> I think for us, it doesn't feel like you're a big company because it's such of a personal relationship. So it doesn't feel like you're talking to a big corporate company where you're not heard, you know, if you're not a a big customer. The relationships we've got with people work and just pick up the phone it might be a really senior position and they'll help us, and that's something that's really good in Nutanix. >> I'm wondering if you've had any experience with Nutanix support, so we know uptime is, is super critical. So what is your experience? >> Yeah, fantastic. I mean, from an operational perspective, I love the self healing, that's built into the platform. Anyway, I love the fact that my technical guys don't have to be uber technical to be able to operate. That's one of the other benefits in Nutanix for us. It ticks all the boxes from an operational perspective. >> I think from our side as well, the technical guys, so, our first and second line guys can understand Nutanix. They can get their head around it, so it's very easy to train and more with Nutanix as opposed to other platforms where it can take up to a year to really understand how the platform works. It is very, very simple for our support desk. Which means, it is less demand on the support that's got Angie then. >> Training in the skills gap is a hugely important issue in the technology world. It's in the United States and also in Europe. How are you finding it, what is it like to be a Leeds based company, are you finding the people you need to fill the roles you have open? >> We're really lucky actually, because our technical director is an ex-trainer, so we can do a lot of the training on site. But Nutanix training is something that we're definitely going to be tapping into. I've been speaking to the guys here, and that's another useful thing for us to take back to the UK. >> Give our audience a little bit of insight, so you know, what you get out of coming out to the Nutanix conference, you came last year to London, you came out here to Copenhagen. What were you hoping to accomplish? What are the conversations been, give us a little bit of a flavor. >> I think it's been good to network with other Nutanix customers to understand their journey. Definitely to learn about what Nutanix is doing now and in the future. When you're running a business it's kind of head down sometimes. Allowance, you know, you don't get time to really sit and look up what the market is doing. So for us, it's also to be part of our journey, you know, we went to event four or five years ago when it was much smaller, much newer name. And to see how fast Nutanix has gone is amazing. It really is. >> Absolutely, I think it's given us clarity on what we need to do next year. Like I say, you've helped us by coming here today and yesterday, seeing the presentations on how we can implement that into our own business. And how we can really take Nutanix forward. >> In terms of the future, you said you are going to, you're looking into Mine. You're thinking about using some of the Nutanix training, capabilities. >> Frames, Beam. >> So, there's a lot there. >> So yeah, we've really honestly taken so much back and I can't wait now. I think for me personally, it's re-energized me. I'm excited about going back and just working out where we can really take Nutanix forward. >> And what's next for Hardy Fisher? >> It's just growth, we're at an early journey now. So we're kind of at the start of our journey, over the next five years, it's all about growth. We see Leeds as a bit a city that's growing itself. We've had a lot of changes in Leeds as a city. It's still quite small. It's a digital city, but it's got massive focus on growing. We're having a big part of that because we're one of three data centers in Leeds. So, it's not a heavily populated area for data centers. And we're all about helping local resellers, you know, get on that ladder for Nutanix. >> So that will be a big driver for us, you know help the small MSPs. You know, let them touch and feel Nutanix in our data center. And then hopefully give them the leg up for them to buy their own boxes, and then co-locate that in the data centers as well. >> So, as as as devoted Nutanix customers, any advice for Dirige Pandey? He's got, he's under a lot pressure. It's a competitive landscape. You love Nutanix. >> Angie: He's nailed it. >> David: I think, just keep doing what they're doing. >> Rebecca: Stick to your knitting. >> Don't get sold to one of the bigger boys and keep the-- >> Yeah, absolutely, keep the culture. And the, everything that you're doing technically wise it's just unreal. We're blown away. >> I think the culture as well, keep it to grow as big as you are now, keep that culture which has been very hard. I mean, we try doing it in our businesses. You know we have a very hardworking ethic. But we want people to enjoy where they work. We want to have a good work flow, life balance. And it's very difficult to do in a big company. >> Is it, do you like working with each other, in your husband and wife team? >> Yeah, it has it's challenges. (laughing) It has it's challenges but we've worked together for 12 years now, so. >> It's gotten better at work. >> All right. >> It's very hard because, I sell it and I support it, so unless I sell it properly I get in trouble. (laughing) >> Dog house. >> I have to reign him in. >> Exactly, well David an Angie, thank you so much. It has been an absolute pleasure having you on the show. >> Thank you very much for having us. Thank you. >> I'm Rebecca Knight for Stu Miniman. We'll have more for Nutanix.NEXT in Copenhagen coming up in just a little bit.

>> Announcer: Live, from Copenhagen, Denmark, it's theCUBE! Covering Nutanix.NEXT 2019. Brought to you by Nutanix. >> Welcome back everyone to theCUBE's live coverage of Nutanix.NEXT. We are at the Bella Center in Copenhagen, Denmark. I'm your host, Rebecca Knight, alongside of Stu Miniman, of course. We are joined by a good friend of theCUBE, Ray Wang, principal analyst and CEO of Constellation Research. Thank you so much for returning to theCUBE. >> Hey, how you doing? Good morning! >> Good morning, good morning! >> Good morning! (laughing) >> Good morning! >> I don't know. I get all my accents wrong out here. >> (laughing) So, you got a shout out on the main stage this morning, from Monica Kumar, congratulations on that. She talked about you and your research on the infinite role of computing. You also do a lot with the future of work. I know that that is really right in your wheelhouse right now. What are you hearing, what are you seeing, what kinds of conversations are you having that are interesting you? >> Yeah, so, this infinite computing option, it's one of the that we're talking about, the fact that you can scale out forever, right? And the problem that's holding us back has been technical debt, right? So all that legacy that everyone's got to figure out. It's like, my connections, my server, my disk-rack recovery, my disaster recovery, my backup, everything. It's a pain in the butt. And I'm still trying to get onto the cloud. So on that end, we're like, okay, all this stuff is holding us back, how do we get there? Now, the future of work is a little bit different. We're seeing a very very different set of work. People have talked about where we are the gig economy, but that's just one aspect of it. Everything is being decomposed into microservices. Large processes are becoming smaller and smaller microservices, they're being reusable, well our work and tasks are following the same way. We're getting smaller and smaller tasks, some are more repetitive, some are going to be automated, and it's really about where we actually find the difference between augmentation of humanity, and full automation, and that's where the next battle's going to be. >> Yeah, Ray, some of the discussions we've been having this week, is how do we really simplify the environment? The balance I hear from customers, on the one hand, they're always like, I don't have enough money, I don't have enough personnel, on the other hand, oh my gosh, that full automation sounds like you're going to put me out of a job. We know we're not putting everybody out of work in the next couple of years. There are challenges; we worry about the hollowing out of the center of the economy, but here, what Nutanix is trying to do, of course, is, I don't want to have to thrive in that complexity anymore, I want to be able to drive innovation, keep up with that, take advantage of that unlimited resources out there, so, where do you see, you've been here at the show, what are you hearing from the customers here? Anything different in Europe versus back in North America that you'd share about that journey onto the changing roles? >> Oh it's a great point. It's about simplifying everything where you can, it's about areas of automation where they make sense. Here in Europe it's slightly different because a lot of the focus in Europe has been about cost and efficiency, followed by of course regulatory. Those have been the two drivers. And they've been battling that in order to be, even they will look at some level of innovation. Where in the US, people are head on doing innovation, regulatory and operational efficiency at the same time. So that creates a very very different environment. But what we have noticed are some patterns, especially when we look at automation and AI; there are four areas out of seven where we see a lot more automation that's happening. The first one is massively repetitive tasks, those are things, yeah, got to get that out of the way, we don't do this very very well. The second one is really thinking about massive nodes of interaction. When you're connected to multiple places, multiple organizations, multiple instances, that's something where we start to get overwhelmed, and then of course, there's lots of volume. If you've got lots of volume or requests that are coming through, you can't possibly handle that, and that's a place where we see a lot of machine scale. And the last piece is really when you have to scale, humans don't scale very well. However, it's actually not a hollowing out of the middle; it's actually a hollowing out of the ends in a very, very real end, because really really simple tasks go away, super complex tasks go away, and the middle actually remains, and the middle is things that are complex that cannot be recreated by math, they're also areas that require a lot of creativity, humans make the rules, we break the rules, and then the last part is really fine motor skills and presence, the machines still aren't as good. So we still have some hope. So the middle stays, it's the hollowing out of the ends, the high end jobs and the low end jobs are the ones where we're going to see a lot of risk. >> So what does that mean? So we have, leaving the middle there, and as you said, the high end jobs and the low end jobs go away, but what does that mean in terms of the skills? In terms of what employers are looking for, in terms of what they need in their prospective applicants and hirees. >> That's a great point. Soft skills are important; it's the qualitative skills that become even more important, it's also being able to manage and orchestrate the hard skills; because you don't necessarily have to know how to do the calculation, you have to just know which algorithm to apply. >> Okay, and then also, these soft skills of managing people, I'm assuming too? Because computers are not so good at that either. >> Yes. Soft skills are managing people, but also manage the human and machine equation that's going to happen. Because we have to train the machines, the machines aren't going to know that level of intuition, and there's a large amount of training that's going to happen over time. >> All right. So, Ray, one of the things Nutanix is doing is, as they've been transforming to not only subscription, software's always been at their core, but they're starting to do not just infrastructure software, but application software. I know you live in that world quite a lot, so when you hear Nutanix talking about building databases, delivering these services, it's something that I look at, Amazon does some of that, but for the most part they're infrastructure and build on top of us. How do you think, how is Nutanix doing, what are some of the challenges for them, going up against some of the bellwethers out there in tech, and all the open source projects that are out there. >> So the challenge is always going to be, there is a one dominant player in every market. And what they're providing is an alternative to allow the orchestration of not having that, not only that dominant player, but a choice. So in every single market, they're focused on giving users choice, and giving the ability to aggregate, and bring everything into one single plane. That is tough to do, right? And the fact that they see that as their big hairy audacious goal, that's impressive. If you said they were going to do this three years ago, I wouldn't have believed them. >> Well yeah, I think back to, remember almost 10 years ago, VMware tried to get into applications, they bought Zimbra, they bought a few others. Cisco did like 26 adjacencies, they were going to take over video and do all these things, and we've seen lots of failures over the years. They refocused on their core, was a big thing that I heard, that the users seem to be excited about. Are there areas that you're find especially interesting as to where Nutanix is poking? >> So, I would say that Nutanix three years ago was a little bit sleepy. They got comfortable, they did the stuff that they did really well, and it feels like, maybe about 12 months ago, Dheeraj had a different vision. Like something snapped, something hit, he said this isn't working, we're going to change things, and we've seen a whole bunch of new talent come into play. We've also seen a huge expansion of what they're trying to do, and a cleanup of all those side projects that were all going on before. So I think they've actually honed in on, okay, if we can simplify this piece, this is a money-winning business for some time, and they're talking about 80% margins last quarter, I mean that's huge, and that's just trying to save customers money, and make their lives simpler. >> Do you think that they have the messaging right? Because, I mean, they're going to this Thoreauvian/Emersonian idea of simplify, simplify, simplify, and it does resonate, of course! What customer doesn't want a simpler computing experience? But do you think that they are reaching the right people, and they have obviously very passionate customers, but are they getting into new businesses. >> I think they're getting to the businesses that their customers are asking them to, those adjacencies are huge, I think and when you think about cleaning up technical debt, all that legacy debt that you actually have to fix, I mean, this is where you begin. It's so hard to make that cloud journey to begin with, it's even harder to carry all that legacy with you. And we're going to see a lot more of this going forward. >> All right. So, Ray, talk a little bit about, I loved an event you did last year, the people's centered digital future. Help explain to our audience what this is about, and where you're taking it again this year. >> So that event was a one-time event. We were celebrating the 70th anniversary of the United Nations founding, we were celebrating almost 50 years of the internet, and 50% of the world being connected to the internet. And part of the reason that was an important event was, we really felt that there was a need to get back to the roots of where the internet had begun, and more importantly, talk about where we are today in the world of privacy. One of the biggest challenges we have in the a digital world is that your personal data, your genomics, all this information about you is being brokered for free. And what we have to do is take that back. And by taking that back, what I mean is, we've got to make all these rights, property right. If we can make that a property right, we can leverage the existing rules and legislation that's there, and we can actually start paying people for that data through consent, and giving people that ability, on consent to data, could create lots of things, from universal basic income, to a brand new set of data economy that equalizes the playing field, while keeping the large tech giants. >> There's some of those big journeys that we went on, you talk about the internet, this year's 50th anniversary of the first walking on the moon, and you look at how entire countries rallied together, so much technology was-- >> Yeah, look at India. >> Spun off of what they've done there, it's like we need some rallying cries in today's day and age to solve some of these big day and age. Is that AI? Where are some of the big areas that you see tech needing to drive forward in the next decade? >> I think the big area's going to be around decentralization, giving individuals more empowerment. We've got large, big tech companies, that are, I'd say, imbalanced. We start companies right away, building monopolies on day one, and we don't open up those markets. And the question is, how do we create a level playing field for the individual to be to compete, to bring a new idea, and to innovate, if that's continuously stifled by big technology companies without an opportunity, we're in trouble. And so that starts by making data a property right, to the personal data. It starts by also creating marketplaces for that data, and those marketplaces have to have regulations, similar to capital market flows. The way treat exchanges, we treat marketplaces, we need to do the same thing with the way we do with data, and then the third piece, there has to be some level of a tax, that goes to all these data economies, so that they can fund the infrastructure and the watch dogs that are there. Now this is coming from a free market, I'm a free market capitalist, okay? I can't stand regulation, but I also realize that it's so important that we have a fair market. >> But do you, we know so much about how Americans are so much more cavalier about their privacy than even Europeans, what will it take to galvanize Americans to care about those little crumbs that they're leaving on the internet, that is the data that you say should be a property right, that we should be paid for? >> I think it's going to start with companies actually take, and do the right thing, where they actually give them that opportunity to monetize that information. >> Will they do that? >> I think the new set of startups are starting to do that, because they're looking at the risk that's being posed, at Facebook and Google and Amazon, on the anti-trust, DOJ, FCC, they're all coming in at the same time, the FTC, they're all wondering, do we break these companies up or not? The short answer is, I don't think they're going to, because we're competing with China, and when you're looking at that scale of data, where Amazon's transactions are only 1/10 of Ali Baba's? That's huge. So the consolidation has to happen, but we need to create a layer that actually democratizes and creates a fair trading play. >> And those startups, you think, can compete with established players? >> I think once we set the roles, and the ground rules, I think people are going to be able to do that, but once you free that data, what are we competing on now? You have to pay for my consent, you have to earn my business, you can't trade it for free, or just say, "Hey look, you are the product." That changes everything. >> Rebecca: Yeah, that's a good point. >> Ray, I know you spend a lot of time talking to, and giving advice to some of the leaders in technology, you're welcome to get into some specifics about Nutanix, or some of the cloud players, but what are some of the key themes, what are people getting right, and what are they still doing wrong? >> Okay, so theme number one, this is going to be a multicloud hybrid world for a long time. Anybody that's bucking the multicloud trend, they've missed the point, right? Because we want portability in data, there's only two or three players in every single market, if I can't move my data, my workloads, and my IO in and out, then you've actually created vendor lock-in from hell. And I think customers are going to protest against that. The second one, and you guys are probably following this trend a lot, is really about AI ethics and design principles for AI. So what is ethical AI? We've got five things that are important: The first one is make sure it's transparent. See the algorithms, see what they write. Second one, make sure it's explainable. Hey, bias is not a bad thing, so if I'm discriminating against redheads, with, left-handed, and that happened to like, I don't know, Oracle, fine. But, if that was unintended, and you're discriminating against that, then we have to get rid of that, right? And so we have to figure out how to reduce that kind of bias, if it's unwanted bias. If you discover that you're discriminating, and not being inclusive, you've got to make sure that you address that. So then the next part is, it's got to be reversible. And once you have that reversibility, we also make sure that we can train these systems over time. And then the last piece is, Musk could be right! Musk could be right, the machines might take over, but if you insert a human at the beginning of the process, and at the end of the process, you won't get taken over. >> I want to hear about what the future of work looks like for Ray Wang. You are on the road constantly, you are (laughs) you are moving your data from one place, you are everywhere, all the time. So what do you have on next, what's exciting you about your professional life? >> I think the challenge's that we are living in a world where there's too much information, too much content. And you guys say this all the time, right? Separating the signal from the noise. And people are willing to pay for that signal. But that is a very very tough job, right? It's about the analysis, the insights, and when you have that, people don't want to read through your reports. They don't want to watch through the videos. They just want to call you up and say, "Hey, what's going on?" And get the short version of it. And that's what's making it very interesting, because you would expect this would be in a chat bot, it'd be in a robo advisor, doesn't work that way. People still want the human connection, especially given all that data out there, they want the analysis and insights that you guys provide, that's very very important, but even more important right now, it's really about getting back to those relationships. I think people are very careful about the relationships they're keeping, they're also curating those relationships, and coming back to spending more time. And so we're seeing a lot more of in-person meetings, in-person events, very very small, curated conversations, and I think that's coming back. I mean that's why we do our conference every year, as well, we try to keep 200 to 300 people intimately together. >> Those human connections, not going away. (laughs) >> Nope, not going away, in an automated, AI, digital world! This is our post-digital future. >> That's excellent. Well Ray, thanks you so much for coming on theCUBE, it's always so much fun to talk to you. >> Hey, thanks a lot. >> High energy guy (laughs). >> Low energy. >> I'm Rebecca Knight for Stu Miniman, we will have more from the Bella Center at Nutanix.NEXT coming up in just a little bit. (upbeat music)

>> Narrator: Live from Copenhagen, Denmark, it's theCUBE. Covering Nutanix.NEXT 2019 Brought to you by Nutanix. >> Welcome back everyone to theCUBE's live coverage of Nutanix .NEXT here at the Bella Center in Copenhagen, Denmark. I'm your host, Rebecca Knight, along with my co host, Stu Miniman. We're joined by two guests this segment. We have Mayur Shah. He is the Global Head, Data Center and Software Defined Everything SDx at Wipro. Thank you for coming on the show. >> Thank you. >> And Thenu Kittappa, Director GSI Sales at Nutanix. Thank you so much. >> Thank you for having me. >> So we're talking today about fluid ITs. Wipro, of course, is an Indian multinational corporation based in Bangalore. You gave us a talk yesterday here at Nutanix .NEXT. Tell our viewers a little bit about how you view fluid IT. >> Sure. So we believe that the kind of transition the industry is going through, the pressure businesses are getting in terms of having their offering aligned to the customer expectations, they're digital natives, and so and so forth have digital transformations. They are also under tremendous pressure of innovating much faster than they used to do before. And the same pressure has been put back to the IT. How IT support that kind of changes and agility, which business would need in general. We believe that now, previously we used to have a plan for five years and a roadmap and we used to forecast what kind of architecture mission may end. But now it's time for us to give that back to business. There are a lot of uncertainties and how we can handle those uncertainties that's main reason why we are thinking little out of box in terms of getting things fluid. >> Mayur, I like that comment because part of the transition used to be I bought a product and I thought about how many years did I depreciate that product for? So I want to get your, what are you seeing and how is it impacting your customers? Nutanix talks about building experiences, so are they meeting that goal? How is that helping with both what you're doing and ultimately your end customers? >> So, what we believe is as you rightly say the end user customer's experience, business agility, and their competitiveness for customers at the prime, right? So the way we are now aligning our offerings, aligning to customer needs, changing our models of measurement from SLS to business level BLS. Those are the things which we are doing for aligning to the businesses and ensuring that they benefit in terms of many of our offering are now experience-driven. So SLS and BLS are also experience-driven, so we in our virtual desk offering, we offer the customers based on the experience problem, the penalties are assigned. So we proactively manage the end user experience without them even knowing it. So those are the few examples. >> Thenu, I have to imagine this is a big piece of your job is the traditional channel used to be how do we get beyond selling boxes, selling services, consulting and everything, but the SI is more about that whole experience. >> It's actually a whole different experience. It's been a great show for us from that perspective. We have a lot of our partners starting up, giving us the support we need from the SI community. Wipro was a sponsor, so it's been great. And to be honest, that's exactly what we're trying to do with SIs here. We're taking the solution and outcome based approach. Let's talk to the customer, what their business needs are. Let's see what kind of solutions we build to fit that. It's not just Nutanix. How does Nutanix work with HPE? How does Nutanix work with the networking, SDN? Let's give them an outcome-based solution. And let's support it with the right level of experience. So essentially, just in time to market is the goal that we're trying to achieve with partners like Wipro. >> Thenu, can you give us some examples of what, the kinds of conversations that you're having and then how it influences you when you go back to your company and you go back to Nutanix and you are then in the war room trying to figure out what kind of next new architectures and designs you can provide. >> So normally when we work with customers and with GSIs, you start with the core problem of what are you trying to solve over here, right? You have a five year plan. Are you trying to grow to a certain extent? Are you looking for your VDI to cater a certain security needs or certain financial needs? And so, then, it comes down to what is the business requirement here? Is it scalability? Is it reliability? Is it security? Is it financial modeling? You might be sitting with a customer who says, this is a great option, but I don't have budget to do this. I want to transform myself to the next level of technology, but I don't have a budget. And when we have these joint customer conversations with partners like Wipro, they say, great, let's offer a solution. And here, by solution, we not only cater to the technology, but we're also looking at where you need to end up in five years, what kind of business models and commercial models we can do to support you and what are the right products we can bring to you so that you only concern yourself with the outcome. You don't care about the infrastructure stack underneath it. Let's make everything invisible for you. But they just take our invisible story to a whole different level. >> Mayur, when I think about the transformations that customers are going through, the education and training is often a big piece of that. Where does that fit in to what you're doing, what services Wipro offers, education there, and how much of it does the simplicity of Nutanix involve in that? >> It's a great questions. So what we actually, and it helps us a lot, when we bring in the complex technologies for our end customers, they also have the owners and they need to get appreciative of what we are offering. With Nutanix's simplicity it's all given. They know that things work and things work super simple. Now whatever we bring on top of that, that's where it adds a lot of value without missing too much of time for enabling our end customers, and that gives outcome. So we are, as a whole, as a solution, we are able to give that outcome confidence and experience to customers. >> So what kinds of conversations are you having at this conference, in terms of what kinds of learnings are going on? You're talking to fellow customers of Nutanix and able to say hey, what you're doing over there, maybe we could try something similar at Wipro. >> Yeah, so one good part what I've seen people are using platform for variety of use cases, variety of business applications. Now we at Wipro, we have mastered some of them, but not all of them. But we see a lot of customers speaking about how they are using massive scale for HyperCloud, for instance. They are using it for databases, applications, mission critical applications, and we feel now it's time for us to branch out into that. >> I'd actually like to add to that. All the conversations we've had is amazing with customers. You think you built a product to meet x use cases, and then the customer comes back and says, you guys did great with being on these X use cases, but guess what? I found out this X plus 1 use case, and it's perfect. And that is what we take back and say, okay, is there a market around this, which we can then commercialize and make it easy to consume? >> What would you say, so you're based in San Jose, and you've been with Nutanix for five years now. What would you say are some of the differences that you've seen from US customers versus here we are in Copenhagen, European customers, and also Indian customers? >> Oh, that's a difficult questions. You're really putting me in a difficult position here. But in general, I would, you know, our European customers look to innovation, but they also look to baked in solutions, and more tighter integration and collaboration with partners. The US customers want to be on the cutting edge of technology. They're very high risk-takers, so when you're defining a solution and a model that works for them, it's a completely different ball game in terms of how much risk they are willing to take, what price point they want to do, and then they're also very, very particular about I want Vendor A, B, and C to work together. Go make it happen. With a lot of the Indian and the Asian customers, and even our European customers, they're more SLA based. Mayur, what do you think? >> Absolutely. I think we see a clear, here in this area of Europe, they are much mature, the second and third level of outsourcing people. They are aware of SLAs, they are aware of the services. They expect a little more than what we do and we, let's say if you compare back to India and US in some time, they are the first time or second time outsourcers, but here's the difference, they clearly wonder about the outcome. >> Mayur, the announcements that we've had this week. Are there anything that you're looking to take back to your customers, or anything that either announced or some of the previews they've been giving that you're especially excited about? >> Sure. So I think there's a great timing. I was just talking last night. We are doing investments, innovation investments for three years, it's a three years plan. And exactly the synergies so well. The announcement, what we have heard here are kind of synergizing what we are doing in the road map. For example, we and the fluid IT what she told, is all about delivering those next generation future-proof architecture, leveraging those announcements. The era, we are working on databases as always, which covers the mission-critical application, and things in a much advanced way. We believe in our road map here, we calling it a service theater, which actually delivers the experience and outcome. So there are synergies they talked about insights. And we are talking about delivering those real time, predictable stuff, based on, and our vision is to give intent with everything, so you have to just define the intent and things will fall in place. So there are a lot of synergies and we definitely take back few of them, which is databases as a service, insights, IOTA, Edge, a few key things we will take from here. And of course the HyperCloud, the AWS migration. >> Well, Mayur's being very, very humble here. One of the announcements that we did make over here at the conference was Wipro has standardized with Nutanix on their virtual desk solution and we're going back to both our customers, their customers, and our field with this offering. So the virtual desk is their own IP. They've done very well in the past with virtual desk, but as they are looking to do more standardization, get in to the next generation solutions, we worked very closely with them to build a Nutanix and HPE-based stack with Centrix, to offer this as a turnkey solution, which they've already done, but with better economics and time to market. >> And do you see that as sort of the future? >> Yes. That pretty much becomes a fundamental building block based on which almost all of our other solutions are going to to get built. The next one coming up will be database as a service, similar constructs. How do you make database consumption and Ops transfer to the end user? Followed by IoT, now IoT is a real different ball game because everything is customized. A lot of customers like to go dabble in it, but at the end of the day you need to build a solution around it. >> Thenu, and actually one of the questions we've had is we look as Nutanix moves beyond just infrastructure software to some of the application software, seems that the GSIs would be a critical player for building services. >> Yes! We actually have this really funky graph, verticals, base our AoS, where do GSIs fit in. It's the solution and pulling everything together, and making it more of a customer business case based offering, as opposed to a customer piecing itself. It's becoming a big ask with G2Ks, right? They're not doing large RFPs, they're actually doing very business-based SLAs, and now the control lies with the business owners within large customers. So it fits very well with our story. >> Excellent. Well, thank you so much Thenu and Mayur. Thank you for coming on theCUBE. >> Thank you. >> Thank you, our pleasure. >> Thank you. >> Our pleasure. >> I'm Rebecca Knight for Stu Miniman. We will have more of theCUBE's live coverage of Nutanix .Next coming up in just a little bit. (upbeat electronic music)

(Upbeat Techno Music) >> Announcer: Live from Copenhagen, Denmark. It's theCUBE! Covering Nutatnix.Next 2019. Brought to you by Nutanix. >> Welcome back everyone to theCUBE's live coverage of Nutanix.Next. We are here at the Bella Center in Copenhagen. I'm your host, Rebecca Knight, alongside of Stu Miniman, the analyst for theCUBE. We have two guests for this segment. We have Manoj Agarwal. He is the SVP of Engineering at Nutanix. Thanks so much for coming on the show. >> Thank you Rebecca. That's good. >> And Gil Haberman. He is the Senior Director of Product Marketing at Nutanix. Thank you so much for coming on the show. >> Thanks for having me. So, our topic today is Xi Clusters. These were announced at Anaheim, at .Next back in Anaheim. Gil, why don't we start with you. Describe the business problems you were hearing from customers and how these Xi Clusters are designed to help solve them. >> Gil: Sure, first thanks for inviting me. I'm a big fan of theCUBE. It's so great to be here. To your question, at Nutanix, we've been working with customers on the vision of Hybrid Cloud for a number of years now. And the different challenges have evolved over time. Initially, there were pockets of public cloud adoption where customers wanted to simply find a way to operate across multiple clouds. But today, the challenges are different. Now, as customers are looking to adopt business critical applications that span private and public, bursting and migrating applications, there's a strong need for consistency across environments. And we gear around consistency around 3 aspects. The first is infrastructure. The second is operations. And the third is the consumption model itself. From an individual perspective, what we keep hearing is that the same VMs and applications must be able to work across environments, without significant replatforming or retooling. From an operation's perspective, cloud engineers truly need a way to utilize the same practices, integrations, in work that they have done on their applications for many years, across multiple clouds. So there's a need to sustain the same practices across these multiple clouds. And finally from a consumption model perspective, there's a need to have a platform that drives the same level of consistency in terms of licensing and software across different environments. And for that, we at Nutanix have to evolve to empower operators to be able to address all of these needs of consistency across private and public. >> Now, I would like to add something to it. You just think about three years ago. The entire world was talking about "Everything is going to be public cloud." And very soon, all these CIOs also realized that it's not going to be just public cloud or just private cloud. It's going to be Hybrid. And we ran a survey with 2,700 IT professionals who participated in the survey, and what we learned mainly 91% of them, they said hybrid is ideal. And the second thing that was not also a surprising thing was 94% of them, they said the app migration or app mobility is going to be the key. And then we look at that option like "How are you going to adopt?" And that was also strikingly similar, like what we see currently maybe 18% or so, that they are into the hybrid world and getting onto close to 41% or so in the next 24 months. >> Yeah, but Manoj, I'm glad you brought that up. When I talk to users, the thing that they're concerned the most about are their applications% and their data. And in IT forever, migrations have been a challenging thing to do and it was usually, you set up a migration and it takes you weeks or months to do it. Today, migrations aren't even going to be even a one time thing. If I'm moving from one cloud to another, if I'm moving from private to public, or even public to private. I need to have some flexibility to what I'm building. How has that informed how you're building your architectural designs? >> That's a great point. In fact, we always feel that architecture matters, and why the fundamental technologies that we are building should help. Two things that I'll say. One is the data replication technologies that we have built and strengthened over time. Plus the second thing is the network. If you get the network right, then you are very slowly there. And we had been reflecting on the data side, you know. 10 years of journey and data replication technologies like we have built. Networking we have been very hard at work on that front also in the last three years or so, with the building of Xi Cloud. We'll see and hear more and more, especially in the context of Xi Cluster. What you see is that we have done the ready integration with AWS ETCs. Thereby first of all all the services that exist in AWS. It's available to the customers with their app, running on XI Clusters without changing anything there. >> This is a competitive market so let's talk about differentiation. How do you see the product as completely different from your rivals and then how are you positioning it to your customers? >> Yeah. I'll go back to again the same thing. Architecture matters. We were not the first ones to go out with a hybrid converse like in 2013. There were a lot of competitive solutions that existed at the time. But we took our time. We wanted to make sure that we do it right. We do provide choice to our customers. That's where we matter. As we are building out solutions, again going back to the four principles. Applications sort of require change. You don't require an IPO presence to change, so when we are building the solution, we are making sure if you want to pay for private cloud, on-prem our service provider. Or you want a public cloud. Any of the big cloud players or this new cloud, that you have a common architecture underneath. You have the same management plain with the prism. You can really orchestrate, and manage the entire infrastructure. You have the flexibility in terms of the networking. Other services that you want to go and use, you have the choice of wahtever platform also. Like something that we don't want you to go and change if you don't need a change. Lastly, I would say, on the business side, we do want to give the smarty cloud world the flexibility for the customers to bring a cloud of their choice and if they want to switch, they should be able to switch with one click also. >> Yeah. Gil, I'm wondering if you can actually explain to our audience one of the challenges here is deploying unbared metal is not something that anybody can just do on the public clouds. For AWS, the first solution was actually VM ware on AWS. They had to develop that but they're now opening that to be able to use. Can you walk us through where we are with the cloud providers and that's I think part of the reason why this isn't yet generally available. Indeed, AWS has been the first to open bare metal and this is really the path for us at Nutanix to make clouds invisible as well. We worked with a number of platforms on Prem and now we want to extend that to public cloud and having an ability to actually access bare metal is the first step in doing so. Beyond that, what we've done is what we believe is the hard work of making things very simple to drive customer delight. And so what we've done is integrate into AWS rather than just running on top of AWS, inside existing accounts and VPCs of customers and the outcome has benefits on both technology and business perspective. From the technology perspective, cloud operators can see all bare metal as well as cloud native services in one place, one inventory. And we believe that this type of topology will provide better performance. And then on the business side, this allows us to do a couple of things. The first, if you are an AWS user like most of our customers, they can use AWS credits for that bare metal infrastructure. At Nutanix, we are now able to evolve our services to provide hybrid licenses, so our licenses would eventually be portable. And so you see how we are gradually building towards this portability across multiple clouds, AWS being the first cloud. >> Yeah, it's great to see Nutanix- We've seen a few other companies moving towards that model because if I'm software and truly agnostic, you should be able to have it across those environments. I believe Solidfire a couple of years ago started doing some of the things; A couple other companies. So the X in AWS sounds like it will be first. We know Google has been the partner of Nutanix for a while. Could you just give us where are we with Google and Azure? Kind of to round out the big three. >> Sure, so we have started to work with AWS and we have announced early access now inviting customers to sign up with us to get access. We are also actively working with Azure to figure out how to together bring better bare metal services and the type of software on top of that. And of course, we believe that other cloud vendors are going to open this up as well and Google Cloud being a close partner of ours is an important part of that strategy as well. >> And we are doing something with Google already as you know. We have integrated the entire stack using their nested vertilization technologies, like running on their vertilization the HB which is nested. Today, we run a lot of our customers prospect they run. The test, our experience the entire solution on Google test prime. We have brought out more than a thousand users every month, that they access it. So it's a journey, like when they have the full bare metal, you can see a lot more but we are very engaged with them. >> I want to talk about the future now and have you looked into your crystal ball a bit, 6, 10, years from now. What do you see- This is such a fast changing environment but how do you see the cloud evolving and then how do you see Nutanix? What role does Nutanix play? >> Last 10 years, it was all about how we bring public cloud into the private cloud, right? Next 5, 10 years when you think about it is all how do we really make it hybrid. The experience that what customers have come to expect in the last 10 years. You can go and pick any kind of platform on which you want to run the same stack. You won't need to worry about it. Something similar that needs to happen and the underlying architecture of technology which will go and drive that is going to be data mobility, same control plane that can go and extend this smarty cloud. This story by the way resonates very very well with the customers because it's not easy to get your IT for support, to get trained on different cloud technologies also because the talent things cost there. And if you can go and teach them one interface and have them run with the choice of infrastructure or the back form or the cloud, that's what we think we can make a huge difference for the customers. >> Yeah, so I want to make sure I understand when talking about your hybrid or multicloud strategy, we've got Xi Clusters help you get in and matches what you have on sight. Have you had a conversation about Kubernetes yet? Where does Carbon which is the Nutanix Kubernetes fit into this overall discussion? Is that just part of the platform that gets baked in and therefore we don't need to talk about it or am I missing a piece? >> That's a great question because the beauty of what we're talking about is that we bring the entire software and the entire platform with us wherever we go. Part of that stack is carbon and calm. We need the ability to have both traditional applications alongside modern applications with Kubernetes. Even hybrid applications that include some front end that might be containerized, maybe back end that is not yet containerized. And all that, everything that we've been doing on-prem, can now be moved into any other public cloud we provide. >> It's part of the compute, right? You got the VMs, now you got the containers. It's part of the backbone. >> So yeah, we've heard from some people say that Kubernetes is just the new containerized compute. We don't need to talk about it and I'm okay with that, because it's just in there. >> Yes. Absolutely. >> Excellent. Well Gil and Manoj, thank you so much for coming on theCUBE. >> Manoj: Thanks so much for hosting us. >> Gil: Thanks for having us. >> I'm Rebecca Knight for Stu Miniman. Stay tuned for more of theCUBE's live coverage of .Next. (Techno outro plays)