>>Welcome back to HP discover 2021 My name is Dave Volonte and you're watching the cubes, virtual coverage of H. P. S. Big customer event. Of course, the virtual edition, we're gonna dig into transformations the role of technology in the role of senior technology leadership. Look, let's face it, H P. E. Has gone through a pretty dramatic transformation itself in the past few years. So it makes a great example in case study and with me is rashmi kumari who is the senior vice president and C. I. O. At HP rashmi welcome come on inside the cube. >>Dave Nice to be here. >>Well, it's been almost a year since Covid changed the world as we know it. How would you say the role of the CEO specifically and generally it has changed. I mean you got digital Zero Trust has gone from buzzword to >>mandate >>digital. Everybody was complacent about digital in many ways and now it's really accelerated remote work hybrid. How do you see it? >>Absolutely. As I said in the last discover that Covid has been the biggest reason to accelerate digital transformation in the company's I. C. C. I O. S role has changed tremendously in the last 15 months. It's no more just keep the operations running that's become a table stick. Our roles have become not only to create digital customer experience engaged with our customers in different ways, but also to transform the company operations from inside out to be able to give that digital experience from beginning to end off the customer engagement going forward. We have also become responsible for switching our strategies around the companies as the Covid. Covid hit in different parts of the world at different times and how companies structured their operations to go from one region to another. A global company like H. B had to look into its supply chain differently. Had to look into strategies to mitigate the risk that was created because of the supply chain disruptions as well as you go to taking care of our employees. How do you create this digital collaboration experience where teams can still come together and make the work happen for our end customers? How do we think about future employee engagement when people are not coming into these big buildings and offices and working together, But how to create the same level of collaboration coordination as well as delivery or faster uh goods and services which is enabled by technology going forward. So see I. O. And I. T. S. Role has gone from giving a different level of customer experience to a different level of employee experience as well as enabling day to day operations of the company's. Ceos have realized that digital is the way to go forward. It does not matter what industry you are in and now see a as have their seat at the table to define what the future of every company now, which is a technology company respective you are in oil and gas or mining or a technical product or a card or a mobility company. End of the day you have to act and behave like a technology company. >>So I want to ask you about that because you've you've been a Ceo and uh you know, leading technology provider now for the last three years and you've had previous roles and where you know non technical technology, you know, selling to I. T. Companies and as you point out those worlds are coming together, everybody is a technology company today. How do you think that changes the role of the C. I. O. Because it would always seem to me that there was a difference between A C. I. O. And a tech company. You know what I mean by that? And the C. I. O. It's sort of every other company is those two worlds converging. >>Absolutely. And it's interesting you pointed out that I have worked in many different industries from healthcare and pharma to entertainment to utilities. Um And now at a technology company end of the day um The issues that I. T. Deals with are pretty similar across the organization. What is different here is now my customers are people like me in other industries and I have a little bit of an advantage because just having the experience across various ecosystem. Even at H. B. Look I was fortunate um at H. B. Because of Antonio's leadership, we have topped out mandate to transform how we did business. And I talked about my next gen IT program in last year's cube interview. But at the same time while we were changing our customer partners experience from ordering to order processing to supply chain to finance. Uh We decided this pivot of becoming as a service company. And if you think about that pivot it's pretty common if it was a technology company or non technology company at HP. We were very used to selling a product and coming back three years later at the time of refresh of infrastructure or hardware. That's no more true for us now we are becoming as a service or a subscription company and I. T. Played a major role to enable that quote to cash experience. Which is very different than the traditional experience around how we stay connected with our customer, how we proactively understand their behavior. I always talk about this term. Um Digital exhaust which results into data which can result into better insight and you can not only Upsell cross l because now you have more data about your product usage, but first and the foremost give what your customer wants in a much better way because you can proactively understand their needs and wants because you are providing a digital product versus a physical product. So this is the change that most of the companies are now going through. If you look at Domino's transition, there are pills a sellers but they did better because they had better digital experience. If you look at Chipotle, these are food service companies I. K which is a furniture manufacturer across the board. We have helped our customers and industries to understand how to become a more digital provider. And and remember when uh hp says edge to cloud platform as a service edges the product, the customers who we deal with and how do we get that? Help them get their data to understand how the product is behaving and then get the information to cloud for further analysis. Um and understanding from the data that comes out of the products that gets up, >>I think you've been HP now think around three years and I've been watching of course for decades. Hp. Hp then HP is I feel like it's entering now the sort of third phase of its transformation, your phase one was okay, we gotta figure out how to deal or or operate as a separate companies. Okay. That took some time and then it was okay. Now how do we align our resources and you know, what are the waves that we're gonna ride? And how do we how do we take our human capital, our investments and what bets do we place and and all in on as a service. And now it's like okay how do we deliver on all those promises? So pretty massive transformations. You talked about edge to cloud as a service so you've got this huge pivot in your in your business. What's the technology strategy to support that transformation? >>Yeah that's a that's a great question. So as I mentioned first your second phase which was becoming a stand alone company was the next N. I. T. Program very broad and um S. Four and 60 related ecosystem application. We're even in the traditional business there was a realization that we were 100 20 billion company. We are 30 billion company. We need different types of technologies as well as more integrated across our product line across the globe. And um we I'm very happy to report that we are the last leg of next in I. T. Transformation where we have brought in new customer experience through low touch or not touch order pressing. A very strong as four capabilities. Where we are now able to run all global orders across all our hardware and services business together. And I'm happy to report that we have been able to successfully run through the transformation which a typical company of our size would take five or six years to do in around close to three years. But at the same time while we were building this foundation and the capabilities to be able to do other management, supply chain and data and analytics platforms. We also made the pivot to go to as a service now for as a service and subscription selling. It needs a very different quote to Kazakh cash experience for our customers and that's where we had to bring in um platforms like brim to do um subscription building, convergent charging and a whole different way to address. But we were lucky to have this transformation completed on which we could bolt on this new capability and we had the data and another X platform built which now these as a service products can also use to drive better insight into our customer behavior um as well as how they're using our product a real time for our operations teams. >>Well they say follow the money in the cube. We love to say follow the day to day is obviously a crucial component of competitive advantage business value. So you talk a little bit more about the role of data. I'm interested I'm interested in where I. T. Fits uh you know a lot of companies that have a Chief data officer or Ceo sometimes they're separate. Sometimes they they work you know for each other or Cdo works for C. I. O. How do you guys approach the whole data conversation? >>Yeah that's a that's a great question and has been top of the mind of a lot of C E O C I O S. Chief digital officers in many different companies. The way we have set it up here is do we do have a chief data officer and we do have a head of uh technology and platform and data within I. T. Look. The way I see is that I call the term data torture if we have multiple data lakes, if we have multiple data locations and the data is not coming together at one place at the first time that it comes out of the source system, we end up with data swamps and it's very difficult to drive insights. It's very difficult to have a single version of truth. So HP had two pronged approach. First one was as part of this next gen i. T. Transformation we embarked upon the journey first of all to define our customers and products in a very uniform way across the globe. It's called entity Master Data and Product Master Data Program. These were very very difficult program. We are now happy to report that we can understand the customer from code stage to servicing stage beginning to end across all our system. It's been a tough journey but it was a effort well spent at the same time while we were building this message capability, we also invest the time in our analytics platform because we are generating so much data now globally as one footprint. How do we link our data link to R. S. A. P. And Salesforce and all these systems where our customer data flows through and create analytics and insight from it from our customers or our operations team. At the same time, we also created a chief data officer role where the responsibility is really to drive business from understanding what decision making an analytics they need around product, around customer, around their usage, around their experience to be able to drive better alignment with our customers and products going forward. So this creates efficiencies in the organization. If you have a leader who is taking care of your platforms and data building single source of truth and you have a leader who is propagating this mature notion of handling data as enterprise data and driving that focus on understanding the metrics and the insight that the businesses need to drive better customer alignment. That's when we gain those efficiencies and behind the scenes, the chief data officer and the data leader within my organization worked very, very closely to understand each other needs sometimes out of the possible where do we need the data processing? Is it at the edge? Is it in the cloud? What's the best way to drive the technology and the platform forward? And they kind of rely on each other's knowledge and intelligence to give us give us superior results. And I have done data analytics in many different companies. This model works where you have focused on insight and analytics without because data without insight is of no value, but at the same time you need clean data. You need efficient, fast platforms to process that insight at the functional nonfunctional requirements that are business partners have and that's how we have established in here and we have seen many successes recently. As of now, >>I want to ask you a kind of a harder maybe it's not harder question. It's a weird question around single version of the truth because it's clearly a challenge for organizations and there's many applications workloads that require that single version of the truth. The operational systems, the transaction systems, the HR the salesforce. Clearly you have to have a single version of the truth. I feel like however we're on the cusp of a new era where business lines see an opportunity for whatever their own truth to work with a partner to create some kind of new data product. And it's early days in that. But I want to and maybe not the right question for HP. But I wonder if you see it with in your ecosystems where where it's it's yes, single version of truth is sort of one class of data and analytics gotta have that nail down data quality, everything else. But then there's this sort of artistic version of the data where business people need more freedom. They need more latitude to create. Are you seeing that? And maybe you can help me put that into context. >>Uh, that's a great question. David. I'm glad you asked it. So I think tom Davenport who is known in the data space talks about the offensive and the defensive use cases of leveraging data. I think the piece that you talked about where it's clean, it's pristine, it's quality. It's all that most of those offer the offensive use cases where you are improving company's operations incrementally because you have very clean that I have very good understanding of how my territories are doing, how my customers are doing how my products are doing. How am I meeting my sls or how my financials are looking? There's no room for failure in that area. The other area is though, which works on the same set of data. It's not a different set of data, but the need is more around finding needles in the haystack to come up with new needs, new ones and customers or new business models that we go with. The way we have done it is we do take this data take out what's not allowed for everybody to be seen and then what we call is a private space. But that's this entire data available to our business leader, not real time because the need is not as real time because they're doing more what we call this predictive analytics to be able to leverage the same data set and run their analytics. And we work very closely with business in its we educate them. We tell them how to leverage this data set and use it and gather their feedback to understand what they need in that space to continue to run with their with their analytics. I think as we talk about hindsight insight and foresight hindsight and insight happens more from this clean data lakes where you have authenticity, you have quality and then most of the foresight happens in a different space where the users have more leverage to use data in many different ways to drive analytics and insights which is not readily available. >>Thank you for that. That's interesting discussion. You know digital transformation. It's a journey and it's going to take many years. A lot of ways, not a lot of ways 2020 was a forced March to digital. If you weren't a digital business, you were out of business and you really didn't have much time to plan. So now organizations are stepping back saying, okay let's really lean into our strategy the journey and along the way there's gonna be blind spots, there's bumps in the road when you look out what are the potential disruptions that you see maybe in terms of how companies are currently approaching their digital transformations? That's a great question. >>Dave and I'm going to take a little bit more longer term view on this topic. Right in what's top of my mind um recently is the whole topic of E. S. G. Environmental, social and governance. Most of the companies have governance in place, right? Because they are either public companies or they're under some kind of uh scrutiny from different regulatory bodies or what not. Even if you're a startup, you need to do things with our customers and what not. It has been there for companies. It continues to be there. We the public companies are very good at making sure that we have the right compliance, right privacy, right governance in in in place. Now we'll talk about cyber security. I think that creates a whole new challenge in that governance space. However, we have the set up within our companies to be able to handle that challenge. Now, when we go to social, what happened last year was really important. And now as each and every company, we need to think about what are we doing from our perspective to play our part in that. And not only the bigger companies leaders at our level, I would say that Between last March and this year, I have hired more than 400 people during pandemic, which was all virtual, but me and my team have made sure that we are doing the right thing to drive inclusion and diversity, which is also very big objective for h P E. And Antonio himself has been very active in various round tables in us at the world Economic forum level and I think it's really important for companies to create that opportunity, remove that disparity that's there for the underserved communities. If we want to continue to be successful in this world too, create innovative products and services, we need to sell it to the broader cross section of populations and to be able to do that, we need to bring them in our fold and enable them to create that um, equal consumption capabilities across different sets of people. Hp has taken many initiatives and so are many companies. I feel like uh, The momentum that companies have now created around the topic of equality is very important. I'm also very excited to see that a lot of startups are now coming up to serve that 99% versus just the shiny ones, as you know, in the bay area to create better delivery methods of food or products. Right. The third piece, which is environmental, is extremely important as well as we have seen recently in many companies and where even the dollar or the economic value is flowing are around the companies which are serious about environmental HP recently published its living Progress report. We have been in the forefront of innovation to reduce carbon emissions, we help our customers, um, through those processes. Again, if we do, if our planet is on fire, none of us will exist, right. So we all have to do that every little part to be able to do better. And I'm happy to report, I myself as a person, solar panels, battery electric cars, whatever I can do, but I think something more needs to happen right where as an individual I need to pitch in, but maybe utilities will be so green in the future that I don't need to put panels on my roof, which again creates a different kind of uh waste going forward. So when you ask me about disruptions, I personally feel that successful company like ours have to have E. S. G. Top of their mind and think of products and services from that perspective, which creates equal opportunity for people, which creates better environment sustainability going forward. And, you know, our customers are investors are very interested in seeing what we are doing to be able to serve that cause uh for for bigger cross section of companies, and I'm most of the time very happy to share with my C I. O cohort around how are H. P E F s capabilities creates or feeds into the circular economy, how much e waste we have recycled or kept it off of landfills are green capabilities, How it reduces the evils going forward as well as our sustainability initiatives, which can help other, see IOS to be more um carbon neutral going forward as well. >>You know, that's a great answer, rashmi, thank you for that because I gotta tell you hear a lot of mumbo jumbo about E S G. But that was a very substantive, thoughtful response that I think, I think tech companies in particular are have to lead in our leading in this area. So I really appreciate that sentiment. I want to end with a very important topic which is cyber. It's obviously, you know, escalated in, in the news the last several months. It's always in the news, but You know, 10 or 15 years ago there was this mentality of failure equals fire. Now we realize, hey, they're gonna get in, it's how you handle it. Cyber has become a board level topic, you know? Years ago there was a lot of discussion, oh, you can't have the sec ops team working for the C. I. O. Because that's like the Fox watching the Henhouse, that's changed. Uh it's been a real awakening, a kind of a rude awakening. So the world is now more virtual, you've gotta secure physical uh assets. I mean, any knucklehead can now become a ransomware attack, er they can, they can, they can buy ransomware as a services in the dark, dark web. So that's something we've never seen before. You're seeing supply chains get hacked and self forming malware. I mean, it's a really scary time. So you've got these intellectual assets, it's a top priority for organizations. Are you seeing a convergence of the sea? So roll the C. I. O. Roll the line of business roles relative to sort of prior years in terms of driving security throughout organizations. >>This is a great question. And this was a big discussion at my public board meeting a couple of days ago. It's as as I talk about many topics, if you think digital, if you think data, if you think is you, it's no more one organizations, business, it's now everybody's responsibility. I saw a Wall Street Journal article a couple of days ago where Somebody has compared cyber to 9-11-type scenario that if it happens for a company, that's the level of impact you feel on your on your operations. So, you know, all models are going to change where C so reports to see IO at H P E. We are also into products or security and that's why I see. So is a peer of mine who I worked with very closely who also worked with product teams where we are saving our customers from a lot of pain in this space going forward. And H. B. E. Itself is investing enormous amount of efforts in time in coming out of products which are which are secured and are not vulnerable to these types of attacks. The way I see it is see So role has become extremely critical in every company and the big part of that role is to make people understand that cybersecurity is also everybody's responsibility. That's why in I. T. V. Propagate def sec ups. Um As we talk about it, we are very very careful about picking the right products and services. This is one area where companies cannot shy away from investing. You have to continuously looking at cyber security architecture, you have to continuously look at and understand where the gaps are and how do we switch our product or service that we use from the providers to make sure our companies stay secure The training, not only for individual employees around anti phishing or what does cybersecurity mean, but also to the executive committee and to the board around what cybersecurity means, what zero trust means, but at the same time doing drive ins, we did it for business continuity and disaster recovery. Before now at this time we do it for a ransomware attack and stay prepared as you mentioned. And we all say in tech community, it's always if not when no company can them their chest and say, oh, we are fully secured because something can happen going forward. But what is the readiness for something that can happen? It has to be handled at the same risk level as a pandemic or earthquake or a natural disaster. And assume that it's going to happen and how as a company we will behave when when something like this happen. So I'm here's believer in the framework of uh protect, detect, govern and respond um as these things happen. So we need to have exercises within the company to ensure that everybody is aware of the part that they play day today but at the same time when some event happen and making sure we do very periodic reviews of I. T. And cyber practices across the company. There is no more differentiation between I. T. And O. T. That was 10 years ago. I remember working with different industries where OT was totally out of reach of I. T. And guess what happened? Wanna cry and Petra and XP machines were still running your supply chains and they were not protected. So if it's a technology it needs to be protected. That's the mindset. People need to go with invest in education, training, um awareness of your employees, your management committee, your board and do frequent exercises to understand how to respond when something like this happen. See it's a big responsibility to protect our customer data, our customers operations and we all need to be responsible and accountable to be able to provide all our products and services to our customers when something unforeseen like this happens, >>Russian, very generous with your time. Thank you so much for coming back in the CUBA is great to have you again. >>Thank you. Dave was really nice chatting with you. Thanks >>for being with us for our ongoing coverage of HP discover 21 This is Dave Volonte, you're watching the virtual cube, the leader in digital tech coverage. Be right back. >>Mm hmm, mm.

>> Narrator: Live from Anaheim, California, it's The CUBE covering Nutanix .NEXT 2019. Brought to you by Nutanix. >> Cameraman: Izzy! >> Welcome back, everyone, to The CUBES's live coverage of Nutanix .NEXT here in Anaheim, California. I'm your host, Rebecca Knight, along with my co-host, John Furrier. We have two guests for this segment, we have Phil Davis, he is the president of Hybrid IT Hewlett Packard Entrerprise. Thanks so much for coming on The CUBE, Phil? >> Great to be here. >> And we have Chris Kaddaras, he is the SVP America's Nutanix. Thank you so much, Chris. >> Right, thanks for having me. >> So, two weeks, this partnership between Nutanix and HPE, two weeks old, newly announced. Chris, I wanna ask you, explain to our viewers a little bit about it and how it came about. What is the partnership? >> Sure, now I think the way the partnership came about was really around customer and partner demand, right? The marketplace was really looking for two great companies to get together and provide a solution for what they wanted to kind of cure their problems. The two components of the partnership effectively is, one component is the Nutanix sales teams are gonna be selling their Nutanix solutions and appliances with a great HPE computing infrastructure involved in that appliance. So, that's the first big group part, and I'll let Phil talk about the second part of the relationship. >> Yeah, and the second part is really around how do we enable a consumption model for our customers? I mean, if you think about what's going on with the public cloud, customers wanna be able to scale up or scale down and kind of pay as they go. And so, HPE has been leading with an offering we call Green Lake. It's a couple-billion-dollar business growing over 50% a year, so it kind of shows you the interest in it, and we also, therefore, offer the Nutanix solution on our infrastructure and then wrap that with a consumption model service that allows customers that flexibility. So, those are the two elements of the partnership. >> So, you're selling Nutanix with your Green Lake. >> Embedded in the Green Lake offering, that's correct. >> And Nutanix has selling Compute with their sales worth. >> Phil: Exactly right. >> Chris: Yeah, so with our DX solution, yeah with HPE Compute. >> Got it. Now, you guys have indirect and direct sales, both sides, channel play, is it a channel partnership or both, can you just explain the go-to market? >> Yeah, and I think that what you'll see is there's just a lot of alignment, a lot of synergy. Both companies are very, very channel friendly. I mean, HPE's a 75 plus year old company and our very first sale as a company went through the channel, right? So, our whole DNA is wired towards the channel. Over 70% of our business goes through the channel. So, what we've really made sure is that we make this very, very easy for the channel to consume and also, be paid and compensated on. So, it flows through all the standard HPE channel compensation and programs that we have in play. So, absolutely, very friendly for the channel. >> Yeah, and I think this will work really well for both channel communities that we have. We have a lot of Nutanix channel partners that have not been, for whatever reason, have not been selling HPE and now, they have a perfect opportunity to sell HPE Compute platforms with our DX appliance. We also have a lot of great channel partners who want a better consumption model where customers are looking to flex up and down. We have not been able to provide that for Nutanix software solutions. So, to adopt Green Lake for some of these partners will be a fantastic offering for their customers. >> Maybe just a dove-tail on that comment, one of the things we've worked really hard in the last year is to make Green Lake more channel friendly. Channel reps tend to get paid as the margin comes in. So, if you spread that out over time, they don't make the same money. So, we've changed the rebate 17% up front for the channel partners, we've simplified the offering, we made it quicker, so we're doing a lot to make Green Lake much easier for our channel partners and a lot of excitement about being able to offer Nutanix with Green Lake as well. >> What's the timing on the channel rollout? Is it rolling out now? Is it instantly growing out? Is there timing on-- >> Phil: Instantly. >> Instantly? >> So, we've already briefed the channel, we are making it available, we're providing all the quotes, we have a ton of material available online through our online portals and tools for the channel partners, we have FAQs, we have marketing materials, we have, actually, letters already built up for the channel. So, it's now. >> So, I gotta ask the hard question here because I think one of the things I see that's really awesome is the channel's gonna love this because Nutanix has a channel generated opportunity. Their challenge in that opportunity is when they do a POC, they usually win the business. That's kind of a direct sales model that's favored Nutanix for their success. This is gonna bring a lot of mojo to the channel bringing HPE and Nutanix together for this unique solution. I'm sure the reaction's been positive. Are they seeing an up-step in more POCs and more action with customers? >> Phil: You wanna take that? >> Yeah, we're seeing a lot, actually. So, I was just there actually reviewing my team yesterday. We have a list of now starting to get towards 100 customers that we think we can align with together, right? And multiple go to markets. We have Green Lake opportunities, we have DX opportunities, which is Nutanix on HPE. We also have a lot of opportunities around Nutanix software only on HPE Compute that a lot of customers wanna consume as well in a different way. So, we're seeing that really start to scale. We haven't done the first POC of DX because it hasn't released to the market yet, right? We are doing POCs on software only on HPE servers, but the DX solution will be releasing in the next few months. So Phil, I know the HPE channel pretty well and they love services, wrapping services around an offering. Can you talk about how this impacts from the services side because I gotta be looking at my chops if I'm a dealer partner because I can bring this new solution in and I can wrap cloud-like capabilities around it. >> Yeah, and you look at a lot of our partners, the hardware-only business is getting pressure. And so, a lot of our partners are doing exactly what you just described. They're trying to move more and more into services. And you're right, there's a whole sweep of services the partners can wrap around this. Everything from advisory, upfront, because all of these workloads run on some sort of legacy environment. So, when they do bring in a hyperconverged, they need to move the workloads. So partners can help with that, supporting maintenance, implementation, all the way through to kind of day-to-day break fix. So, there's a range on services. Obviously, HPE has a pretty big services capability. We make those available through our channel partner as well, so if they wanna sell to HPE services they can do that, or if they wanna deliver 'em themselves, they can do that as well. >> I wanna ask you about the customers. You made this point on main stage that you, sort of, likened back to the Henry Ford quote where you can have any color, as long as it's black and the current marketplace was anything you want as long as it's in my stack, and this is how we're gonna do it. So, giving them more choice, more flexibility, what are you hearing so far? What was the problem in terms of their workload and why things were stiffeled or stunted, and now what do you hope this is going to do? >> Well, as I mentioned on main stage, everybody wants to make it easy to get on to their stack and really, really hard to move off of their stack, right? Whether you're a public cloud company, you want all your microservices, you want all the data trapped there, so it's not easy to move and some of our joint competitors are actually trying to lock you into the complete top-down stack. So, the feedback, so far, from customers and partners has been very, very, very positive because one of the things, I've been in the industry 29 years. One of the things that I can tell you is no one company is gonna out-innovate the entire industry. And so, what customers want is to be able to pick and choose the solutions that best meet their needs. And that's really what this partnership, I think, really embodies is the ability to give customers choice at multiple levels within that stack. Choice in the public cloud, choice on prem, choice of hypervisors, and that's really resonating. >> Yeah, and that's really Nutanix's design point, right? Is around choice, right? Choice at every level of a stack that you can have. And this provides us with the biggest choice in the marketplace at this point and time that was missing from our portfolio. The other piece that you mentioned that I'd like to point out is that the thing that a lot of people haven't been talking about is the services component. You know, Nutanix is a great company, we've grown a lot. But one place that we haven't grown to an extent is in the services side. We have a small services organization that really helps our customers, but we really need a services organization that can help our customers transform. And help our customers through a transformation of their underlying infrastructure and reduce the risk of change. And this HPE relationship will help us do that as well. >> And the other thing, too, that's interesting with Cloud and you guys are in the middle of demodernizing the data center, HPE's been there forever in the data center, is the private cloud has shown that the data center's still relevant. However, if you start going cloud-based stuff, integration's huge. So integrating, not just packaging our solutions, customers need to integrate all this stuff. This has been a key part of Nutanix and HPE. How do you guys see this going forward from an integration standpoint? Because on the product side, it's gotta integrate, and then in the customer environment you mentioned the consumption piece. Can you guys just expand on what that means? >> Sure. Yeah, we saw Dheeraj's presentation this morning, right? And Sunil's, our entire design point is how do we make everything invisible, right? How do we make those integration points invisible? Now, we all know that there's a traditional architecture you need to migrate from to take advantage of some of these things. And that's where the risk is, how do you get from A to B into these environments? As I mentioned, we do have a services organization that helps there, but we could use, now we have one of the largest partners in the industry that could help us do that. I think that's a key component. We will always try to innovate being Nutanix, we will always try to innovate in software, right? Let's try to figure out how we can make this so much easier, move it up the stack to make sure this is the easiest thing to migrate and have choice for customers. >> Yeah, and I think, maybe, just to add to that, if you think about it from a customer view in, right? A lot of customers moved a lot of things very quickly to the public cloud and the public cloud will continue to grow fast, but they're also learning some things. It's not quite as cheap as they thought it was gonna be, like twice as expensive. Moving data around is very expensive. The public cloud is charging you to get your own data back out. Data sovereignty matters a lot more than it used to with things like GDPR in Europe. More and more of the data's getting created at the edge. It's not in the cloud or the data center. And so, what we're seeing is customers are now thinking about things as you mentioned, we're kind of hybrid, and they're talking about the right mix. What's the right mix of public? What's the right mix of private? Where should the data live? And that's a tough story and that's a tough journey for them to go on, so they want help up front with the advisory services, they want help in being able to architect that, implement it, and then, in many cases, even kind of run that. And with nearly 25,000 services professionals around the globe, we have a unique footprint to help customers along that journey. >> It's an interesting deal, it's very, I think, gonna be pretty big. So, congratulations. >> Phil: Thank you. >> It was great having you both on The Cube, Phil and Chris. >> Thank you very much, thanks. >> Thanks for having us. >> I'm Rebecca Knight for John Furrier, we will have so much more from Nutanix .NEXT here in Anaheim, California, so stay with us. (electronic dance music)

>> Announcer: Live from San Francisco, it's theCUBE covering Sparks Summit 2017 brought to you by Databricks. >> You are watching theCUBE at Sparks Summit 2017. We continue our coverage here talking with developers, partners, customers, all things Spark, and today we're honored now to have our next guest Dr. Jisheng Wang who's the Senior Director of Data Science at the CTO Office at Hewlett Packard Enterprise. Dr. Wang, welcome to the show. >> Yeah, thanks for having me here. >> All right and also to my right we have Mr. Jim Kobielus who's the Lead Analyst for Data Science at Wikibon. Welcome, Jim. >> Great to be here like always. >> Well let's jump into it. At first I want to ask about your background a little bit. We were talking about the organization, maybe you could do a better job (laughs) of telling me where you came from and you just recently joined HPE. >> Yes. I actually recently joined HPE earlier this year through the Niara acquisition, and now I'm the Senior Director of Data Science in the CTO Office of Aruba. Actually, Aruba you probably know like two years back, HP acquired Aruba as a wireless networking company, and now Aruba takes charge of the whole enterprise networking business in HP which is about over three billion annual revenue every year now. >> Host: That's not confusing at all. I can follow you (laughs). >> Yes, okay. >> Well all I know is you're doing some exciting stuff with Spark, so maybe tell us about this new solution that you're developing. >> Yes, actually my most experience of Spark now goes back to the Niara time, so Niara was a three and a half year old startup that invented, reinvented the enterprise security using big data and data science. So what is the problem we solved, we tried to solve in Niara is called a UEBA, user and entity behavioral analytics. So I'll just try to be very brief here. Most of the transitional security solutions focus on detecting attackers from outside, but what if the origin of the attacker is inside the enterprise, say Snowden, what can you do? So you probably heard of many cases today employees leaving the company by stealing lots of the company's IP and sensitive data. So UEBA is a new solution try to monitor the behavioral change of the enterprise users to detect both this kind of malicious insider and also the compromised user. >> Host: Behavioral analytics. >> Yes, so it sounds like it's a native analytics which we run like a product. >> Yeah and Jim you've done a lot of work in the industry on this, so any questions you might have for him around UEBA? >> Yeah, give us a sense for how you're incorporating streaming analytics and machine learning into that UEBA solution and then where Spark fits into the overall approach that you take? >> Right, okay. So actually when we started three and a half years back, the first version when we developed the first version of the data pipeline, we used a mix of Hadoop, YARN, Spark, even Apache Storm for different kind of stream and batch analytics work. But soon after with increased maturity and also the momentum from this open source Apache Spark community, we migrated all our stream and batch, you know the ETL and data analytics work into Spark. And it's not just Spark. It's Spark, Spark streaming, MLE, the whole ecosystem of that. So there are at least a couple advantages we have experienced through this kind of a transition. The first thing which really helped us is the simplification of the infrastructure and also the reduction of the DevOps efforts there. >> So simplification around Spark, the whole stack of Spark that you mentioned. >> Yes. >> Okay. >> So for the Niara solution originally, we supported, even here today, we supported both the on-premise and the cloud deployment. For the cloud we also supported the public cloud like AWS, Microsoft Azure, and also Privia Cloud. So you can understand with, if we have to maintain a stack of different like open source tools over this kind of many different deployments, the overhead of doing the DevOps work to monitor, alarming, debugging this kind of infrastructure over different deployments is very hard. So Spark provides us some unified platform. We can integrate the streaming, you know batch, real-time, near real-time, or even longterm batch job all together. So that heavily reduced both the expertise and also the effort required for the DevOps. This is one of the biggest advantages we experienced, and certainly we also experienced something like the scalability, performance, and also the convenience for developers to develop a new applications, all of this, from Spark. >> So are you using the Spark structured streaming runtime inside of your application? Is that true? >> We actually use Spark in the steaming processing when the data, so like in the UEBS solutions, the first thing is collecting a lot of the data, different account data source, network data, cloud application data. So when the data comes in, the first thing is streaming job for the ETL, to process the data. Then after that, we actually also develop the some, like different frequency like one minute, 10 minute, one hour, one day of this analytics job on top of that. And even recently we have started some early adoption of the deep learning into this, how to use deep learning to monitor the user behavior change over time, especially after user gives a notice what user, is user going to access like most servers or download some of the sensitive data? So all of this requires very complex analytics infrastructure. >> Now there were some announcements today here at Spark Summit by Databricks of adding deep learning support to their core Spark code base. What are your thoughts about the deep learning pipelines, API, that they announced this morning? It's new news, I'll understand if you don't, haven't digested it totally, but you probably have some good thoughts on the topic. >> Yes, actually this is also news for me, so I can just speak from my current experience. How to integrate deep learning into Spark actually was a big challenge so far for us because what we used so far, the deep learning piece, we used TensorFlow. And certainly most of our other stream and data massaging or ETL work is done by Spark. So in this case, there are a couple ways to manage this, too. One is to set up two separate resource pool, one for Spark, the other one for TensorFlow, but in our deployment there is some very small on-premise department which has only like four node or five node cluster. It's not efficient to split resource in that way. So we actually also looking for some closer integration between deep learning and Spark. So one thing we looked before is called the TensorFlow on Spark which was open source a couple months ago by Yahoo. >> Right. >> So maybe this is certainly more exciting news for the Spark team to develop this native integration. >> Jim: Very good. >> Okay and we talked about the UEBA solution, but let's go back to a little broader HPE perspective. You have this concept called the intelligent edge, what's that all about? >> So that's a very cool name. Actually come a little bit back. I come from the enterprise background, and enterprise applications have some, actually a lag behind than consumer applications in terms of the adoption of the new data science technology. So there are some native challenges for that. For example, collecting and storing large amount of this enterprise sensitive data is a huge concern, especially in European countries. Also for the similar reason how to collect, normally weigh developer enterprise applications. You're lack of some good quantity and quality of the trending data. So this is some native challenges when you develop enterprise applications, but even despite of this, HPE and Aruba recently made several acquisitions of analytics companies to accelerate the adoption of analytics into different product line. Actually that intelligent age comes from this IOT, which is internet of things, is expected to be the fastest growing market in the next few years here. >> So are you going to be integrating the UEBA behavioral analytics and Spark capability into your IOT portfolio at HP? Is that a strategy or direction for you? >> Yes. Yes, for the big picture that certainly is. So you can think, I think some of the Gartner Report expected the number of the IOT devices is going to grow over 20 billion by 2020. Since all of this IOT devices are connected to either intranet or internet, either through wire or wireless, so as a networking company, we have the advantage of collecting data and even take some actions at the first of place. So the idea of this intelligent age is we want to turn each of these IOT devices, the small IOT devices like IP camera, like those motion detection, all of these small devices as opposed to the distributed sensor for the data collection and also some inline actor to do some real-time or even close to real-time decisions. For example, the behavior anomaly detection is a very good example here. If IOT devices is compromised, if the IP camera has been compromised, then use that to steal your internal data. We should detect and stop that at the first place. >> Can you tell me about the challenges of putting deep learning algorithms natively on resource constrained endpoints in the IOT? That must be really challenging to get them to perform well considering that there may be just a little bit of memory or flash capacity or whatever on the endpoints. Any thoughts about how that can be done effectively and efficiently? >> Very good question >> And at low cost. >> Yes, very good question. So there are two aspects into this. First is this global training of the intelligence which is not going to be done on each of the device. In that case, each of the device is more like the sensor for the data collection. So we are going to build a, collect the data sent to the cloud, or build all of this giant pool, like computing resource to trend the classifier, to trend the model, but when we trend the model, we are going to ship the model, so the inference and the detection of the model of those behavioral anomaly really happen on the endpoint. >> Do the training centrally and then push the trained algorithms down to the edge devices. >> Yes. But even like, the second as well even like you said, some of the device like say people try to put those small chips in the spoon, in the case of, in hospital to make it like more intelligent, you cannot put even just the detection piece there. So we also looking to some new technology. I know like Caffe recently announced, released some of the lightweight deep learning models. Also there's some, your probably know, there's some of the improvement from the chip industry. >> Jim: Yes. >> How to optimize the chip design for this kind of more analytics driven task there. So we are all looking to this different areas now. >> We have just a couple minutes left, and Jim you get one last question after this, but I got to ask you, what's on your wishlist? What do you wish you could learn or maybe what did you come to Spark Summit hoping to take away? >> I've always treated myself as a technical developer. One thing I am very excited these days is the emerging of the new technology, like a Spark, like TensorFlow, like Caffe, even Big-Deal which was announced this morning. So this is something like the first go, when I come to this big advanced industry events, I want to learn the new technology. And the second thing is mostly to share our experience and also about adopting of this new technology and also learn from other colleagues from different industries, how people change life, disrupt the old industry by taking advantage of the new technologies here. >> The community's growing fast. I'm sure you're going to receive what you're looking for. And Jim, final question? >> Yeah, I heard you mention DevOps and Spark in same context, and that's a huge theme we're seeing, more DevOps is being wrapped around the lifecycle of development and training and deployment of machine learning models. If you could have your ideal DevOps tool for Spark developers, what would it look like? What would it do in a nutshell? >> Actually it's still, I just share my personal experience. In Niara, we actually developed a lot of the in-house DevOps tools like for example, when you run a lot of different Spark jobs, stream, batch, like one minute batch verus one day batch job, how do you monitor the status of those workflows? How do you know when the data stop coming? How do you know when the workflow failed? Then even how, monitor is a big thing and then alarming when you have something failure or something wrong, how do you alarm it, and also the debug is another big challenge. So I certainly see the growing effort from both Databricks and the community on different aspects of that. >> Jim: Very good. >> All right, so I'm going to ask you for kind of a soundbite summary. I'm going to put you on the spot here, you're in an elevator and I want you to answer this one question. Spark has enabled me to do blank better than ever before. >> Certainly, certainly. I think as I explained before, it helped a lot from both the developer, even the start-up try to disrupt some industry. It helps a lot, and I'm really excited to see this deep learning integration, all different road map report, you know, down the road. I think they're on the right track. >> All right. Dr. Wang, thank you so much for spending some time with us. We appreciate it and go enjoy the rest of your day. >> Yeah, thanks for being here. >> And thank you for watching the Cube. We're here at Spark Summit 2017. We'll be back after the break with another guest. (easygoing electronic music)