>>We're back at Supercomputing 22 in Dallas, winding down day four of this conference. I'm Paul Gillan, my co-host Dave Nicholson. We are talking, we've been talking super computing all week and you hear a lot about what's going on in the United States, what's going on in China, Japan. What we haven't talked a lot about is what's going on in Europe and did you know that two of the top five supercomputers in the world are actually from European countries? Well, our guest has a lot to do with that. Florian, bearish, I hope I pronounce that correctly. My German is, German is not. My strength is the operations director for price, ais, S B L. And let's start with that. What is price? >>So, hello and thank you for the invitation. I'm Flon and Price is a partnership for Advanced Computing in Europe. It's a non-profit association with the seat in Brussels in Belgium. And we have 24 members. These are representatives from different European countries dealing with high performance computing in at their place. And we, so far, we provided the resources for our European research communities. But this changed in the last year, this oral HPC joint undertaking who put a lot of funding in high performance computing and co-funded five PET scale and three preis scale systems. And two of the preis scale systems. You mentioned already, this is Lumi and Finland and Leonardo in Bologna in Italy were in the place for and three and four at the top 500 at least. >>So why is it important that Europe be in the top list of supercomputer makers? >>I think Europe needs to keep pace with the rest of the world. And simulation science is a key technology for the society. And we saw this very recently with a pandemic, with a covid. We were able to help the research communities to find very quickly vaccines and to understand how the virus spread around the world. And all this knowledge is important to serve the society. Or another example is climate change. Yeah. With these new systems, we will be able to predict more precise the changes in the future. So the more compute power you have, the better the smaller the grid and there is resolution you can choose and the lower the error will be for the future. So these are, I think with these systems, the big or challenges we face can be addressed. This is the climate change, energy, food supply, security. >>Who are your members? Do they come from businesses? Do they come from research, from government? All of the >>Above. Yeah. Our, our members are public organization, universities, research centers, compute sites as a data centers, but But public institutions. Yeah. And we provide this services for free via peer review process with excellence as the most important criteria to the research community for free. >>So 40 years ago when, when the idea of an eu, and maybe I'm getting the dates a little bit wrong, when it was just an idea and the idea of a common currency. Yes. Reducing friction between, between borders to create a trading zone. Yes. There was a lot of focus there. Fast forward to today, would you say that these efforts in supercomputing, would they be possible if there were not an EU super structure? >>No, I would say this would not be possible in this extent. I think when though, but though European initiatives are, are needed and the European Commission is supporting these initiatives very well. And before praise, for instance 2008, there were research centers and data centers operating high performance computing systems, but they were not talking to each other. So it was isolated praise created community of operation sites and it facilitated the exchange between them and also enabled to align investments and to, to get the most out of the available funding. And also at this time, and still today for one single country in Europe, it's very hard to provide all the different architectures needed for all the different kind of research communities and applications. If you want to, to offer always the latest technologies, though this is really hardly possible. So with this joint action and opening the resources for other research groups from other countries, you, we, we were able to, yeah, get access to the latest technology for different communities at any given time though. And >>So, so the fact that the two systems that you mentioned are physically located in Finland and in Italy, if you were to walk into one of those facilities and meet the people that are there, they're not just fins in Finland and Italians in Italy. Yeah. This is, this is very much a European effort. So this, this is true. So, so in this, in that sense, the geography is sort of abstracted. Yeah. And the issues of sovereignty that make might take place in in the private sector don't exist or are there, are there issues with, can any, what are the requirements for a researcher to have access to a system in Finland versus a system in Italy? If you've got a EU passport, Hmm. Are you good to go? >>I think you are good to go though. But EU passport, it's now it becomes complicated and political. It's, it's very much, if we talk about the recent systems, well first, let me start a praise. Praise was inclusive and there was no any constraints as even we had users from US, Australia, we wanted just to support excellence in science. And we did not look at the nationality of the organization, of the PI and and so on. There were quotas, but these quotas were very generously interpreted. So, and if so, now with our HPC joint undertaking, it's a question from what European funds, these systems were procured and if a country or being country are associated to this funding, the researchers also have access to these systems. And this addresses basically UK and and Switzerland, which are not in the European Union, but they were as created to the Horizon 2020 research framework. And though they could can access the systems now available, Lumi and Leono and the Petascale system as well. How this will develop in the future, I don't know. It depends to which research framework they will be associated or not. >>What are the outputs of your work at price? Are they reference designs? Is it actual semiconductor hardware? Is it the research? What do you produce? >>So the, the application we run or the simulation we run cover all different scientific domains. So it's, it's science, it's, but also we have industrial let projects with more application oriented targets. Aerodynamics for instance, for cars or planes or something like this. But also fundamental science like the physical elementary physics particles for instance or climate change, biology, drug design, protein costa, all these >>Things. Can businesses be involved in what you do? Can they purchase your, your research? Do they contribute to their, I'm sure, I'm sure there are many technology firms in Europe that would like to be involved. >>So this involving industry though our calls are open and is, if they want to do open r and d, they are invited to submit also proposals. They will be evaluated and if this is qualifying, they will get the access and they can do their jobs and simulations. It's a little bit more tricky if it's in production, if they use these resources for their business and do not publish the results. They are some, well, probably more sites who, who are able to deal with these requests. Some are more dominant than others, but this is on a smaller scale, definitely. Yeah. >>What does the future hold? Are you planning to, are there other countries who will be joining the effort, other institutions? Do you plan to expand your, your scope >>Well, or I think or HPC joint undertaking with 36 member states is quite, covers already even more than Europe. And yeah, clearly if, if there are other states interest interested to join that there is no limitation. Although the focus lies on European area and on union. >>When, when you interact with colleagues from North America, do you, do you feel that there is a sort of European flavor to supercomputing that is different or are we so globally entwined? No. >>So research is not national, it's not European, it's international. This is also clearly very clear and I can, so we have a longstanding collaboration with our US colleagues and also with Chap and South Africa and Canada. And when Covid hit the world, we were able within two weeks to establish regular seminars inviting US and European colleagues to talk to to other, to each other and exchange the results and find new collaboration and to boost the research activities. So, and I have other examples as well. So when we, we already did the joint calls US exceed and in Europe praise and it was a very interesting experience. So we received applications from different communities and we decided that we will review this on our side, on European, with European experts and US did it in US with their experts. And you can guess what the result was at the meeting when we compared our results, it was matching one by one. It was exactly the same. Recite >>That it, it's, it's refreshing to hear a story of global collaboration. Yeah. Where people are getting along and making meaningful progress. >>I have to mention you, I have to to point out, you did not mention China as a country you were collaborating with. Is that by, is that intentional? >>Well, with China, definitely we have less links and collaborations also. It's also existing. There, there was initiative to look at the development of the technologies and the group meet on a regular basis. And there, there also Chinese colleagues involved. It's on a lower level, >>Yes, but is is the con conversations are occurring. We're out of time. Florian be operations director of price, European Super Computing collaborative. Thank you so much for being with us. I'm always impressed when people come on the cube and submit to an interview in a language that is not their first language. Yeah, >>Absolutely. >>Brave to do that. Yeah. Thank you. You're welcome. Thank you. We'll be right back after this break from Supercomputing 22 in Dallas.

(soft electronic music) >> Hey, everyone. Welcome to Miami. I feel like I should be singing that song. Lisa Martin here live with theCUBE at IFS Unleashed. We've been here all day having great conversations with IFS executives, their customers, their partners, lots a... You can hear probably the buzz behind me at the vibe here. Lot of great folks, 1500 plus here. People are excited to be back and to see what IFS has been up to the last few years. I'm pleased to welcome back one of our alumni who was here with us last time we covered IFS, Marne Martin joins us. The president, Service Management, EAM and Global Industry at IFS. Marne, it's great to have you back on theCUBE. >> Yeah, I'm so happy to be here, and thanks for joining us in Miami. Last time it was Boston. >> That's right. >> So definitely much warmer climate this time. >> Much warmer. (Marne laughs) Yes, much warmer. And people here are just smiles on faces. People are excited to be back. There's... But I shouldn't elude that IFS slow down at all during the pandemic. You did not. I was looking at the first half, 2022 financials that came out over the summer and AR are up 33%. So much recurring revenue as well. So your... The business is doing incredibly well. You've pivoted beautifully during the pandemic. Customers are happy. There's a lot of customers here. You guys talk a lot about the moment of service. I love that. Talk to the audience about what that is, and how you're enabling your customers to deliver that to their customers. >> Definitely. So, you know, it's amazing when you have these inflection points and it's a good opportunity, world conference to world conference to celebrate that. We've grown a lot, and the number of customers we've brought in, in tier one global customers as well as in our variety of the various regions around the world and different industry verticals is amazing. And, you know, the participation is what's making IFS be a better company, a better technology vendor as we focus on these industries. So is understanding moment of service. You know, we talk a lot, and certainly CIOs and IT buyers will talk about technology, but putting the technology to work has to be meaningful, not only to the returns that go to shareholders, but what it matters, what matters to the end customers, of our customers. And when we started thinking about the new branding of IFS, because we also rebranded in this time, we thought, "How does that mission crystallize in what we're doing for our customers, and how do we really start put bringing technology to life?" And that is where moment of service came. So it's very rare in our world that you actually come up with a sort of slogan or an objective as a company that not only mobilizes what we do internally here at IFS, delivering great moments of service to our customers, but also that tells a story of the customers to the end customer. You know, service, an area that I work in a lot, it's very obvious that you... We all know when we get a great moment of service, or sometimes a bad moment of service. So if you talk to service organizations, field service organizations, they understand what a moment of service is. But it's also thinking about how we enable the people delivering that great moment of service. Not just like doing a survey or what have you, but what are the digital tools that help them to deliver better moments of service proactively. >> Right. >> One of my pet peeves was always that even like, if you have a voice of the customer program or what have you, that you may get that reactive feedback perhaps to a CMO in an organization, but the insights don't really get actioned. So here, across the line of business applications that we sell, ERP Service Management, EAM, ITSM, or ESM, we're really thinking about with that moment of service, the objective of putting the technology to work. How do we facilitate that alongside the business growth of our customers, but also how do we take the insights they get from their end customers into the business models as well as the functional design, what we develop. So moment of service has become, say the heart of IFS as well as a way of understanding our customers better. >> Really understanding them at much deeper level- >> Correct. Correct. >> And a lot of organizations. Give me some examples of some of the insights that IFS has gleaned from its customers. How you've brought them internally to really evolve the technology. >> So I think what's important is a lot of times technology vendors may say they know their customers, right? If you think about what technology vendor we know with the 360 view of the customer. You know, understanding the customer is a lot more than understanding their renewal date as a software vendor. >> Yeah. (laughs) >> So we have to really think about the moments of service on what matters most at that point of service, right? And it will vary certainly by industry, but there also will be certain things that are very much the same. Like for example, if we, as a customer, can have an asset or a piece of equipment that never breaks, we're a happier customer. If it does break, we, of course, want it to be fixed the first time someone shows up. So those are the obvious things. But how you then fix or manifest that into a different way of utilizing and implementing the technology. Thinking also about taking the operational insights that you have on driving, what we call preventative or predictive maintenance, or maximizing what's called a first time fixed resolution. You know, being able to marry best practices with at times artificial intelligence and machine learning information, with also the operational and personal insights of the people doing the work really enriches the quality of the insights you have around that moment of service and how to recreate a great moment of service, or lessen a poor moment of service. >> Yeah. >> And it also changes a view of what are often IT-driven projects into what's the user feedback that also matters most to enable that. You know, with the talent shortage that we're seeing, you know, customer expectations have only increased. >> Yes. >> So we all know, and customers want great moments of service, but how do we enable the frontline workers, whether they're field service workers or others, to deliver against these expectations when they might be harried, and you know, having to do a lot more work because of talent shortage. So we want to think about what their needs are in a way that's more focused towards delivering that moment of service, that great customer experience. And of course, that always feeds back into brand loyalty, selling more profits, but really getting into it. And you know, the advantage of IFS is that we understand the domain expertise to do things from a UI UX, a business process, but also thinking about how we're developing, to answer your question, the artificial intelligence machine learning. Even thinking about how you put IoT to work in ways that really matter, because there's a lot of money spent on IT projects that actually don't deliver great moments of service, let alone actual business value. >> Right. I love the vertical specialization that IFS has. I was interviewing Darren Roos, your CEO, a little bit earlier today and I said, "You know, we see so many companies... So many vendors, like some of your competitors in the ERP Space, which whom you're outgrowing or growing faster than, or horizontally focused. And the vertical specialization that he was kind of describing how long it's been here really allows IFS to focus on its core competencies. But another thing that I'm hearing throughout the interviews I'm having today, and you just said the same thing, is that you're not just, "We need to meet the customer where they are." Everyone talks about that. You've actually getting the... You're developing and fostering the domain expertise. >> Yes. >> So whether you're talking with an energy company, aerospace and defense company, manufacturing, there's that one to one knowledge within IFS and its customer, or based in that industry that it can only imagine is maybe part of what's leading to, you know, that big increase in ARR that I talked about, the recurring revenue being so high. That domain expertise seems to be a differentiator from my lens. >> Well, let's even talk about how people build relationships, right? You know, we're having a conversation, so we're already having a higher value relationship, right? And that comes through with how vendors engage with their customers. You know, when you have seen your executives like Darren and myself, and Michael and Christian, who still care and really focus on what is most impactful. What is that moment of service? I'm sure Darren talked about the great moment of service book that we just released. >> Yes. >> So understanding at a more visceral and may I say, intimate moment with the customers, what matters most to them. And really working with what are developing, what we call the digital dream team within these customers that understand enough of where they're going in the objective, enables us to do a better job. And it's also where then, it's not only how we're partnering in the sales process implementation in the conventional ways, but product management. What is the most meaningful? How can we prioritize what makes the most impact? Obviously, there's cool stuff we want to do too, but you know, we really think about understanding the verticals and understanding where they're going. And you see that, for example, we're an absolute leader in mobile workforce management specifically, where we have what's called real time optimization. Super hard to do. No one else does it anymore except us. Great. There's other things where you'd say that, "Hey, some of the other vendors talk about this, right?" APM as a performance management or other things, but because they lack the true vertical specialization and the use cases and the ease to put it in, the adoption rate is low. >> Yeah. >> So, you know, in that case, APM might not be something we do only, but if we can actually help commercialize this, something that has a great deal of value in a superior way in that focus verticals, that's what it means to have industry specialization. Because if you spread yourself too thin, you know then, you'll end up with an AI or machine learning platform or something like that that you know, most companies don't have five years to try and configure, build out a Watson or something like that. I mean, most companies in this day and age, with the requirements of competitive pressure and supply chain pressures have to be nimble and have to be getting results fast. So the closest with the customers, the domain expertise, the understanding of what matters most, helps us to be faster to the value outcomes that our customers needs. It helps us to be more focused in what we're developing and also how we're developing. And ultimately, that does benefit us that, you know, we want to make sure that we're not only leading today, but you know, staying ahead of the game in the next 5 to 10 years, which will help us to grow. You know, we're certainly not a small company anymore. We're at a billion in revenue looking to be 2 billion and eventually 5 billion in revenue. >> Okay. >> So that already, you know, puts us well beyond unicorn status into one of the very few. But, you know, we want to take a different track even of how a service now or a sales force or SAP or even, you know, to some degree workday grew by making sure that we remain focused on these key verticals and not lose our focus. And they're plenty big enough verticals for us to achieve our growth goals. >> Well the growth has been impressive, as I mentioned the ARR app in the first half, and I was chatting with Darren earlier as I said, and I said, "Can you gimme any nuggets for a second half?" I imagine the trajectory is up onto the right. And he alluded to the fact that things are going quite well, but the focus there that you have with customers. Also, you talked about this and I had several customers on the program today. Rolls-Royce was here. Aston Martin was here. And it's very obvious that there is a... There was a uniqueness about the relationship that I saw- >> Yes. >> Especially with Rolls-Royce that I thought was quite, I mean, you talked about kind of that customer intimacy and that personalization, which people used to tolerate fragmented experiences. We don't tolerate those anymore. >> No. >> Nobody has the patience for that. >> No. And it's also, you know, this business isn't easy for a lot of these customers to stay ahead, right? You know, especially if you think about a tier one customer that's at the top of their category. How did they continue to innovate? And Rolls Royce and Aston Martin are really cool customers. You know, but we're also thinking about, you know, what are the up-and-comers? Or you know, we also get customers that have come to us because they've started falling behind in their sector because they haven't been able to digitalize and grow forward. You know, we work a lot with SAP customers. Darren, of course, came from SAP. But in that ecosystem and especially in the areas I work in a lot with service management, SAP customers, you know, that are focusing on ERP, you know, SAP hasn't been a great enabler of service management for them. So the SAP customers have actually fallen behind. And the ability to come to a lot of these new type of digitally based value-based service offerings really make aftermarket service revenues a lifeblood of their company. So even there where, you know, we might have in a different ERP choice, we're able to provide what's really the missing link for these tier one companies that they can't get anywhere else. And we see this also, you know, you've obviously Salesforce and CRM. A lot of Salesforce CRM customers. Microsoft with Dynamics also primarily ERP. But the focus and the specialization that we have is rare in the industry, but it's so impactful. >> Yeah. >> And you know, I would even venture to say that there's not a tier one company that has a lot of aftermarket service revenue, or attention on service revenue, or even that is trying to monetize their connected asset or IoT investment that can ignore IFS. >> Yeah. >> Because we are unique enough in our focus verticals that if they want to continue growing and that is a cornerstone of their growth, their customer, their moment of service, then they definitely need to look at IFS. >> Absolutely. Does IFS care that it's not as well known of a brand? I mean, I mentioned you guys are growing. Maybe I didn't mention this, number three in ERP, you are growing faster than the top two biggest competitors, which you mentioned SAP, Oracle as well, but those implementations can be quite complex. Does IFS care that you're doing so well? Darren talked about where you're winning, how you're being competitive, where you went. Do they care about being a big name brand, or is that really kind of not as important nearly as delivering those moments of service? >> So, you know, it's a mirrored question that you asked me, and therefore, I'll give you a multifaceted answer. (Lisa laughs) You know, ERP, we're very proud to be a top three vendor and I think over time we'll continue to dislodge SAP and Oracle in ERP, where companies want to make a different ERP choice, or they're consolidating or whatever. I think already in field service management, we're by far the number one and will continue to be that. And you actually see a lot of our ERP competitors that are dropping down and you seem a... There's not really a lot of what I'd call best-of-breed options other than IFS as well. So... And then enterprise asset management, I really think the opportunity for IFS is how we put technology to work in some of these advanced capabilities in ways that can be automated that is, for example, in IBM Maximo or Watson or what have you haven't been able to be. And then you have some other best-of-breed EAM customers that have kind of not continued innovating and things like that. So the lines where we are really building the brand recognition with the largest companies in the world might be anchored for now more around field service management, enterprise asset management. But of course that brand recognition comes back into ERP. >> Yeah. >> And there will be, you know, as we continue to innovate, as people make ERP decisions every 5, 7, 10 years as those buying cycles are, then it's important that we're using the leadership positions we have. And especially, you know, thinking about these verticals where the asset centric service nature is paramount to them either to meet their moment of service, or to meet their aftermarket service revenue goals that we get the recognition of IFS as being the leader. And all the, you know... And this is where I'll go to the next layer of your question that building that is something I pride myself on and I'll say that we're building the IFS brand recognition at three different levels. >> Okay. >> There's the C-level and the board level, which I'd say my top participation in Darren's keynote this morning was more targeted to messages that would go, you know, "How are you a smarter digital business? How does IFS help you to be that?" >> Yeah. >> Okay. Then we have the operational or kind of the doers in a digital dream team that are below C-level, maybe VPs or directors or SVPs, that actually have the objective of bringing in the new business models, the operational change, the new technology, putting it to work. And there, you know, you have aspects of what do they need now versus how do they change and how do they continue innovating in a way that is easy as possible. >> Yeah. >> And then you definitely need to focus also on the people that are hands-on with those end customers. >> The practitioners. Yeah. >> The people that not only are told about the moment of service, but live the moment of service, right? The actual users in the field. Maybe the dispatchers, you know, the people that are doing the maintenance or the service or things like that. So the domain expertise in how we build the brand recognition has to be in all those three constituencies. We want to make sure that the CEO and the board members know who IFS is. We want to make sure that the operational leaders and the IT leaders who actually are delivering the project trust us to deliver. >> Right. >> And are confident in our ability to deliver with our ecosystem. And then we want to make sure that we're delighting those users of the software that they can deliver the moment of service, not just the business value that we all want from technology, but really that we're enabling them to have a solution that they love. That they can enjoy doing their job, or at least feel that they're doing their job in a way that's helpful to them. >> Right. >> And that ties into the end customers getting the moment of service that we all want. >> Absolutely. Well, very much aligned with what I heard today. It sounds like there's a rock solid strategy across the board at IFS and you... Congratulations on the work that you've done to help put that in place and how it's been evolving. I can only imagine that those second half numbers are going to be fantastic. So we'll have to have you back on the show next year (Marne laughs) to see what else is new. >> Yeah, I can't wait. It's an absolute pleasure and- >> Likewise. >> You know, and really, we're so passionate about what we do here. >> Yes. >> You know, I think just as a final note, as we grow, we want to make sure that doubling the company, doubling the number of customers, that our customers still feel that intimacy and that care. >> Yes. >> Right? >> Yes. >> That they can access senior executives that aren't clueless about their used cases and their vertical and actually have the ability to help them. You know, one of the things I pride myself on is that we... Okay, ideally people choose IFS in the first instance. We have successful projects and move on. Sometimes though, we're taking failed projects from other vendors. >> Yes, right. >> And what I pride myself on, and we all do here at IFS, is that we get those projects live, with those customers live. You know, we have the grit. We have the domain expertise, we see it through. And that even if customers have failed to get the business value or the transformation, you know, in the areas that we specialize at IFS, they can come here and we get it done. >> Right, you got a trusted partner. >> And that's something- Yes, and that, you know, I know every vendor says that- >> They do, but- >> But the reality is that we live it. >> Yeah. >> And it doesn't mean we're perfect. No vendor's perfect. But you know, we have the dedication and the focus and the domain expertise to get it done. And that's what's ultimately driving us into these leadership positions, changing how IFS is viewed. You know, we have people now that are coming to IFS that are saying, "IFS is the only choice in service management if you really want to do this work." And, you know, again, we have to keep earning it. But that's great. >> Exactly. Well, congratulations on all of that. That customer intimacy is a unique differentiator, and it's something that is... It's very... It's a flywheel, right? It's very synergistic. We appreciate your time and your insights for joining us on the program today. Thank you, Marne. >> Absolutely a pleasure. Thank you so much for coming. >> Mine as well. For Marne Martin, I'm Lisa Martin. No relation. (Marne laughs) You're watching theCUBE live from Miami at IFS Unleashed. I'll be back after a short break, so don't go too far. (soft electronic music) (soft electronic music continues)

>>from around the >>globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. Welcome back to the Cubes Coverage Cube Virtual coverage of AWS reinvent 2020 which is also virtual. We're not in person this year. We're doing the remote interviews. But of course, getting all the stories, of course, reinvented, full of partnerships full of news. And we've got a great segment here with Salesforce and AWS. Eileen Schneider Win, who is the senior vice president of strategic partnerships, and Maureen Lundergan, director of worldwide training and certification address. Maureen Eileen. Great to see you. Thanks for coming on. And nice keynote. What's up with the partnership? Give us a quick over your lien. What's what's the Salesforce? A day was partnership. Take a minute to explain it. >>Sure, thank you. I think I'll start out by talking about how sales were thinks about strategic partnerships. So for us, it's really it starts with the customer and being where they want us to be. And we've been so fortunate to be in this relationship with AWS for over five years now. It really started out as an infrastructure based partnership as we were seeing customers start their digital transformation journeys and moved to the cloud. But what has been really exciting as we've spent more time working together and working with our customers, we have now started to move into emotion of really bringing some differentiated solutions between the number one CRM and the most broadly adopted cloud platform to market for customers, uh, in areas like productivity, security and training and certification which will talk more about in a bit Onda. Specifically, some of those solutions are service Cloud Voice Product, which we launched this summer, announced last fall, a dream force as well as our private connect product which creates great security between the AWS platform and Salesforce. >>What? Some of the impact area is actually the two clouds you mentioned CRM and Amazon. We're seeing data obviously being a part of the equation ai machine learning. Um, what's been the impact I lean to your customer specifically >>Yeah, so specifically I'd call out to areas what one is really that foundation of security. Specifically, as government regulations and data security has become more critical, we've really been able to partner together there and and that's been crucial for certain customers in certain regions as well a certain industries like government. Uh, in addition, I would call out again that service cloud voice partnership, a zoo. We see the world moving more digital. This really allows customers to go quickly and, uh, turn on. There are solutions from anywhere at any time. >>You know, I love that any time, anywhere kind of philosophy. Now more than ever. With the pandemic collaborations required more than ever, and some people are used to it. You know, I've seen more technical developers have used to working at home, but not everyone else. The workforce still needs to get the job done. So this idea of collaboration, what is the impact in for your customers and how are you guys helping them? Because I think this is a big theme of this year That's gonna not only carry over, even when the pandemics over this idea of anywhere is all about collaboration. >>Yeah, I totally agree. I mean, the exciting thing about the partnership is we've been talking digital transformation with customers for years, but I think what we saw at the beginning of this year, as we were all thrown home and forced Thio, you know, fire up our jobs from our bedrooms or our garages. It really came down to our ability to work quickly and turn on our solutions. It's and these unprecedented times, while we're going through this now, everything we're building really is the future. So it's not just the tools and technology, it's also the processes and how work is getting done that's really come into play. But again, I'll anchor back to that service blood voice solution. So for us, call centers were completely disrupted. You think of call centers and you know, pre 2020 everyone sitting in a room together, agent side by side managers, having the ability to pop over and assist with a call or managing escalation. Now that's been completely disrupted. And it's been very exciting for us to work with our customers, to reimagine what that looks like again both from a technology perspective but also from a process perspective. And along with that, you had to reimagine how employees are learning these solutions and being trained. So we're very grateful for the partnership with AWS, and we're doing some really amazing things together. >>You know this is one of my favorite things about the enablement of Cloud. But in Salesforce has been a pioneer. As you pointed out, this connectedness feature has always been there. Now more than ever, it's highlighted with call centers, not the call center more. It's the connected center. People are connecting. And I think, Maureen, I think last time you're in the Cube. A few years ago, we were talking about virtual training online, and that was pre pet pandemic. Now you're seeing surge of online training not only because people's jobs are changing and being displaced or even shut down. New roles are emerging, right? So the virtual space Virtual world digital world, there's everyone's getting more digital faster now. How has the cove in 19 changed the landscape for training and skills demand? From your perspective, I >>mean at AWS, we've been working on our virtual capabilities for a while, so we had a digital platform out. We had a great partnership, have a great partnership with Salesforce and putting content on trailhead. We had to pivot very rapidly to virtual instructor led training and also our certifications right. We were lucky that our vendors partnered with us rapidly to pivot certification toe proctor environment. And this actually has helped to expand our ability to deliver the both training and certification in locations that we may not have been able to do before. And we have seen while it slowed. Initially, we have seen such an uptake and training over the last, um, 6 to 8 months. It's been incredible. We've been working with our customers. We've been working with our partnerships like Salesforce. We've been pushing more content out. I think customers and partners air really looking for how toe upscale their employees, uh, in a in a way, that is easy for them. And so it's actually been a great surprise to see the adoption of all of our curriculum over the last couple months. >>Well, congratulations knows a lot more work to do. It's gonna get more engaging, more virtual, more rich media. But this idea of connecting lean I wanna get back to the your your thoughts earlier, um, mentioned trailhead. Maury mentioned trailhead. You guys were doing some work with the virtual training there. What? Can you tell us more about that? And how that's going so far? >>Sounds great. So trailhead is our free online learning platform. And it really started because we have a commitment to democratizing anyone's ability to enter our industry s so you could go there and both online or with our trail head go app and experience what we call trails, which our paths for learning again on different areas of knowledge and skills and technology. And late last year, we announced an incredible partnership with AWS, where we're bringing the AWS learning content and certification to trailhead. And this is really again driven by our customers to are asking us to do our part in bringing mawr of these skilled resource is into the ecosystem. But something I also wanna highlight is I feel like this moment that we're in right now has also forced everyone to reimagine how they're doing learning even businesses, how they're training their employees and again having this free platform. And the partnership with AWS has really helped us go very quickly and create a lot of impact with customers. >>I just want to say I love the trailhead metaphor because, you know, learnings nonlinear. It's asynchronous. You've got digital. So you want to take a shortcut? You gotta know the maps And I think that's, you know, people wanna learn versus the linear, you know, tracks on. And I think that's how people have been learning online. And AWS has got a data driven strategy. Marine, I want to get your take on this because as you bring content on the trailhead, can you talk about how that works? And how you working with Railhead? >>Yeah. I mean, we started conversations a couple of years ago, and I think the interesting thing is that Salesforce and AWS have a very similar philosophy about bringing education to anybody who wants it. You'll hear me talk a lot about that in my leadership talk at reinvent, but, um, we really believe that we wanna provide content where learners learn and salesforce and trailhead have this amazing captured audience. And, um, you know, we're really looking at exploring. How do we bring education to people that might not otherwise have access to it? On DSO, we started with really foundational level content, a ws Cloud, Practitioner Essentials and AWS Cloud for technical professionals. And the interesting thing is, both of those courses have been consumed. ITT's not enough to just put it out there you want people to complete the trails and we've seen such an amazing uptake on the courses with, like 85% completion rate on one of the trails and 95% completion rate on the other one. And to keep customers engage is really a credit toe. How trailhead is designed. >>You know, it's interesting. The certification people don't lose sight of the fact that that's kind of the in the end state. Then you start a new trail. I mean, this >>is >>the this is really what it's all about. Can you just share some observations that you've seen for people that are coming into this now to say, Hey, okay, what do I expect? And what are some of the outcomes? >>Yeah, I mean, first, what we're seeing is our customers are being very clear that they need more of these skills. So we're also seeing the need for Salesforce administrators out in our ecosystem. And I think with everything going on this year, it's also an opportunity for people who are looking to pivot. Their careers were moving to tech and again, this free learning platform and the content that we're bringing has been really powerful and again for us. The need for salesforce administrators and cloud practitioners out in our ecosystem are in more demand than ever. >>Maureen. From your perspective on AWS, you see a lot of the new new jobs cybersecurity, Brazilian openings. Where do you see the most needs on for training and certification? Can you highlight some of the areas that are emerging and trending, if you will? >>I would say it's interesting because what we're seeing is is both ends of the spectrum. People that are really trying to just really understand who cloud is, whether it's, ah, business leader within an organization, a finance person, a marketing person. So cloud practitioner, you know, we're seeing huge adoption and consumption on both our platform in on Salesforce. But also some other areas are security and machine learning machine learning. We have five learning paths on our digital platform. We've also extended that content out to other platforms and the consumption rate is significant. And so, you know, I think we're seeing, uh, customers consume that. But the other thing that we're doing is we're really focused on looking at who doesn't have access to education and making sure that's available. So I think the large adoption of Cloud Practitioner in Practitioner is is largely due to the other things that we're doing with programs like Restart our academic programs >>to close it out, Alina want to get your thoughts and final thoughts on the relationship and how people can find more information about this partnership and what it means. Take, take it home. >>Thank you for asking. So just like everything else we've been talking about today, we've had to reimagine how we're showing up at this event together and very exciting thing that my team has created is the AWS Virtual Park. And anyone can access that at salesforce dot com slash aws. So please go check it out. You can experience our products here from our experts and experience its innovation on your own. >>Great insight. Thanks for coming on and participating. Really appreciate Salesforce and AWS two big winning leading clouds working together Trail had great great offering. Thanks for coming on sharing the news. Appreciate >>it. Thank you. >>It's the Cube virtual covering. It was reinvent virtual. Of course. Check out all the information here All three weeks. Walter Wall coverage. I'm John Fury with the Cube. Thanks for watching

>> Live from Stanford University. It's the Cube covering Global Women and Data Science Conference brought to you by Silicon Angle media. >> Welcome back to the Cubes Coverage of the fourth annual Women in Data Science Conference. This global winds event is the fourth annual our fourth year here, covering it for the Cuban Lisa Martin, joined by Gianluca Pecorino, the director on the Stanford Institute for Computational and Mathematical Engineering. Gianluca, it's a pleasure to have you on the program. Thank you. So the Institute for Computational and Mathematical Engineering. I see M e. Tell us a little bit about that and its involvement in wins. >> Yes, so the status has. Bean was funded fifteen years ago at Stanford as a really hard before computation of mathematics at Stanford. The intention was to connect computations and in general, the disciplines around campus towards using computing for evolution, for starting new ideas for pursuing new endeavors. And I think it's being extremely successful over the years in creating a number of different opportunities. Now weeds started four years ago. As you mentioned, it's part of an idea that the prior director advising me, Margo Garretson, had with few others, and I think the position of I see me at the center of campus really helped bring these events sort of across different fields and this different disciplines. And I think, has Bean extremely successful in expanding and creating a new, a completely new movement, a completely new way of off off engaging with with a large, very large community. And I think I seem, has Bean very happy to play this role? And I'm continuing to be excited about the opportunities >> you mentioned expansion and movement to things that jump out. Expansion way mentioned fourth annual on Lee started This Is three and a half years ago knew that twenty fifteen and we were had the pleasure of having Margo Garrett send one of the co founders of Woods on the Cube last year at wigs. And I loved how she actually said. Very cheeky winds really started sort of as a revenge conference for her and the co founders, looking at all of the technology, events and industry events and single a lack of diversity. But in terms of expansion, this there are one hundred fifty plus regional winds events this year in fifty plus countries. They're expecting over one hundred thousand people to engage this expansion. In this movement that you mentioned, it's palpable. Tell us about your Where's the impetus for you to be involved in the woods movement. >> Well, I think my interest in in data science and which particular is because of the role that I seem years in the education at Stanford. We obviously have a very important opportunity toe renew and remodel our curriculum and provide new opportunities for for education off the new generations and clearly starting with with the opportunity off being such an audience and reaching so many different discipline. It's a very different fields. Helps us understand exactly how to put that curriculum together. And so my focus of my interest has been mostly on making sure that I see me alliance with these new directions. And when we establish the institute, computational mathematics didn't really not have data is a very, very critical component, but we are adjusting to that clearly is becoming more and more important. We want to make sure we are ready for it, and we make sure that the students through our curriculum are ready for the world out there. >> So let's talk about this. The students and the curriculum. You've been a professor at Stanford for a very long time before we get into the specifics of today's curriculum. Tell me a little bit about how you have seen that evolve over time as we know that. You know, we're sort of in terms of where the involvement and women and technology and stump field words in the eighties and how that's dropped off. Tell me a little bit about the evolution in that curriculum that you've seen and where the ice Amy is today with that adaptation. >> Yes, certainly. The evolution has bean very quick. In the last few years, we have seen, um in a number of opportunity emerging because of the technology that is out there. The fact that certainly for data science, both the software and the artwork and the technology, the methodology, the algorithms are all in the open so that there is no real barrier into sort of getting started. And I think that helps everybody sort of getting excited about the idea and the opportunity very, very quickly. So we don't really need to goto an extensive curriculum to be ableto ready, solve problems and have an impact. And I think that, perhaps is one one other reason why we are sort of in a level playing field right. Everything is is available to everybody with relatively minor investment at the beginning. And so I think that certainly a difference with respect what the disciplines, where instead, it was much more laborious process to go through before you can actually start having an impact. Suffering every o opportunity, toe change world to toe come, you know, sort of your your vision's sort of impact in the world. So I think that's That's definitely something that the data science and the recent development into the science have created. And so I think, in terms of our role, sort of continuing role in this is tow Pet Shop six. You know, expand the view ofthe data. Science is not just the algorithm, the technology, the statistical learning that you need to accomplish. A student is a new comet into the field, but also is other other elements. And I would say certainly the challenges that we are that are opposed to data. Since they are challenges that have to do with the attics with privacy on DSO, these are clear, clearly difficult to handle because they require knowledge across disciplines the typical air not related to stem in In a traditional sense. But then, on the other hand, I think is the opportunity to be really creative. Data is not analyzing on its own right. He needs the input are sort of help in creating a story. And I think that's that's another element that he makes data science a little bit different. Another stem disciplines intend to be much more ascetic, much more sort of a cold if you like. I think >> that's where the things to you that I find really interesting is if you look at all the statistical and computational skills as you mentioned, that a good data scientist needs to have as we look at some of the challenges with the amount of data being created. So you mentioned privacy, ethics, cybersecurity issues. The create creative element is key for the analysis. Other things, too. That interest me, and I'd love to get your thoughts on how you see this being developed on the curriculum. Helping is is empathy, collaboration, communication skills. Where is that in the curriculum and how important you are? Those other skills to the hard skills >> that that's That's a great question. And I think where is in the curriculum? I think we're lagging behind that. This is one of the opportunities that we have to actually connect to our other places on campus, where instead the education is built much more closely around some of these topics is that you mentioned. So I think you know, again, I the real advantage in the real opportunity we have is that the data science in general reaches out to all these different disciplines in a very, very new way if you like. I think it's it's probably one of the reasons why so attractive toe younger generation is the fact that it's not just the art skills. You do need to have a lot off understanding of the technology, the foundational statistics and mathematics and so on. But it's much more than that. Communication is very important. Teamwork is extremely important. Transparency is very important. There are there are really all these elements that do not really make that they really didn't have a place in some of the more traditional dissidents. And I think that that's definitely a great way off. Sort of refreshing are way off, even considering education and curriculum. >> When you talk to some like the next to the younger generations. Is that one of the things that they find are they pleasantly surprised, knowing that I need to actually be pretty well rounded to me? A successful data scientists? It's how I analyzed the data. How I tell a story, is that something that you still find that excites but surprises this younger generation of well, that >> certainly is a component, very important component of the excitement of the sea. Are there the fact that you can really build the story, tell a story, communicated story and oven, in fact, immediately, quickly, I think is a is something that the newer generation really see it assess a great opportunity and, you know, and it tried to me. So I mean, it has been very difficult for more traditional disciplines to have the same level of impact, partly because the communities tend to be very close, very limited with with a lot of scrutiny. I think what we have in India, the scientists, that is really a lot off you no can do attitude the lot off, Really. You know, creative force that is >> behind, you know, >> basically this movement, but in general data science, I think that >> you write. The impacts is so potent and we've seen it and we're seeing it in every industry across the globe. But it's such an exciting time with Gianluca. We thank you so much for sharing some of your time on the program this morning and look forward to hearing more great things that the ice Amy is helping with prospective women in Stem over the next year. >> Absolutely. Thank you very much. >> My pleasure. We want to thank you. You're watching the Cube live from the fourth annual Women and Data Science Conference here at Stanford University. I'm Lisa Martin. Stick around. My next guest will join me in just a moment.

>> From the Aria resort in Las Vegas. It's the Cube! (upbeat music) Covering AWS Marketplace. Brought to you by Amazon Web Services. Hey, welcome back everybody. Jeff Frick here with the Cube. We're at AWS Reinvent 2018. I don't know how many people are here, 60 000, 70 000, your guess is as good as mine. I'm sure we'll get an official number shortly. We're kicking things of here. Three days of coverage. Monday, Tuesday, Wednesday, Thursday, that's four days. We're at the AWS Marketplace and Service Catalog Experience here at the Aria. We're excited to be kicking stuff of with Rajeev Dutt. He is making AI that makes AI. We're going to get into it. He is the CEO president and co-founder of DimensionalMechanics. Rajeev, great to see you. >> It's great to meet ya. >> How many Reinvents have you been to? >> This would actually be my second. >> You're second? >> My second. Yeah, it's like- it's- I always feel really energized after coming here. It's like- last year was like heavy AI centered. >> Right, right. >> It was just really all these sessions in AI was really exciting. >> Let's get in to it for the folks that aren't familiar with DimensionalMechanics. What are you guys all about? >> So DimensionalMechanics is about lowering the bar for entry like to most people. So that's kind of our first focus. Our second focus is to make sure that deployment strategies allow you to deploy across any end device. So it's basically intended to be a complete end-to-end capability. >> Around AI? >> Around AI. >> The Artificial Intelligence. >> The Artificial Intelligence. >> Yeah, yeah, yeah. >> Most important part. >> Okay. >> Yeah, so, it's about reducing the bar for entry for Artificial Intelligence so that anybody without even a machine learning background can build very sophisticated models on our platform. In sometimes as little as 14 lines of code. It's just incredibly easy. We've had high school students use us, we've had university professors, who have nothing to do with AI, use us without any problems. And, really the way we do that is that we have an AI that we call the Oracle. We are all Matrix fans. (Jeff laughs) And so what this- the Oracle does is it has a vast knowledge base, has a lot of additional machine learning components and things like that. That essentially allow it adapt and learn based on the kind of problem you're trying to solve. So, every time it solves the same problem, it gets better and better at what it's doing. >> So, so, um... Is it, is it libraries, is it pre-configured, are there specific type of application that it works better on? What's kind of your go to market? >> So basically, think about AI studio as a full server application. So it, what you essentially do- we created our own language called the NeoPulse Modeling language. And the NeoPulse Modeling language, think about it as sort of the SQL for Artificial Intelligence. It does a lot of very complicated things in just a couple of lines. So essentially what you do is you compile it on the machine so when you write the NML code, the NeoPulse Modeling language code. You compile it on the machine, it looks at your data which is sitting in a bucket. It starts training the model. Once the model is ready, you can export the model as a PIM object, so Portable Inference Model object which is one of our creations. And that allows you then to deploy it on to any end target as long as it's running on runtime. And on runtime can be basically sitting in the cloud or on a device. Sometimes we're also looking at right down to FPGA kind of device levels as well. So, extremely low power devices as well as cloud computing, but gives you that flexibility, but it also, which is really important, it makes AI accessible. So anybody without like any background in it- My wife is a radiologist and she's actually looking at using it for her own internal usage... >> And how much do you have to learn? You have to learn the NeoPulse language, right? >> The NML language is really easy to learn. So we had a high school student who spent about a week learning it and so a week later she was ready to start coding and she has built her first models using that. And the way it does that is that you actually, we have a keyword auto inside NML which is context aware, and so when the compiler sees auto it goes out to the Oracle and says hey, I've seen- this person needs help building an architecture or figuring out what function to use or what hyperparameters to use and so on and so on. And the Oracle will come back and say hey, use this architecture, use these hyperparameters, use these settings or functions or these optimizations in your model and... >> So is that doin' that when I'm setting up the model in the first place to give me directions or is looking at the model once I've spun it a couple times and saying wait, this looks like one of these, maybe you should do some of this. >> So what it will look at is your data. So it will actually look in to your data, the type of data, how much data you have, the kind of problem you're trying to solve, how many, for example, if it's a classification problem, how many classes you have, and all of that basically determines the kind of model that it will use. You can also specify the level of complexity that you're interested in, like, are you interested in a very simple model, a complex model, is over fitting a risk at all It will determine all these things behind the scenes >> Right, right. >> based on the kind of problem that you're trying to solve. And the first time it solves it, it will give you a pretty good answer. It's usually very good, but then the second time you solve it or a third time you solve it, it gets better and better and better, because it's able to learn from its mistakes. So, and eventually it gets really good at its job so. >> But it's still, but it's a still a model that I built for that application. You're not drawing kind of pre-configured models down from the Oracle. >> No no, you're basically training it from scratch. >> Right. >> It's entirely intended for custom models. So companies that are- have highly customized data, like radiology or for example, looking at wind stress patterns like in polarized light and stuff like that. So things that are not normally covered by the standard image recognition and so, using things like transfer learning or fine tuning doesn't help in this particular case because if you've trained a model in dogs and cats then like, training it to recognize stress patterns, is just not- >> It's not going to work. >> It's not going to work. >> So you got to prepare for your interviews, looking through your website. You list a really dramatic example of where using your guys technology was like, I don't know, a tenth of the price >> Yes, yeah. >> And I think one month versus six. >> Yeah. >> I wonder if you could share some couple examples that, you know, people are putting this to use. >> Okay, so, we have actually a few. So one of them is with a company. They're focused on kind of a resume matching, so we built them- they were initially quoted by another company at around 450 000 and they were warned that they would not be able to exceed 40% accuracy given the data that they had. We managed to get to about 83/84% accuracy for about under 10 000. So that was like a huge huge reduction. Then the second one was just recently, another company had been spending quite a bit of time and resources on building out a technology to measure heart rate. We were able to look at that and produce, instead of spending like their 20 000 a month or so, we could bring it down to 4000 in total. So these are the kind of sort dramatic reductions in cost that our platform can offer. Stanford University, another great example. These are physicians that we're working with. None of them have any engineering background like, for them, Linux is in itself- That was the hardest thing for them to do was to get used to Linux and so once they start building on our platform it was like they actually built a model that was good enough that they were able to publish at the RSNA, which is like one of the biggest radiology conferences in the world. In this case it was for Pet CT, which is a three-dimensional model because there's a three-dimensional image if you will >> Okay. >> of the human body and so was able to determine whether somebody had a tumor or not and I think they mananged to get, with a very limited data set, about 74/75% accuracy and this was actually at Stanford, so it's a pretty, pretty big name. >> Right. So, Rajeev we're here at AWS Marketplace Experience. You're still a relatively small company. I think you said you had a good size C round, gettin' ready to go out and get a decent A round. >> Right. >> What does it mean to work with a company like Amazon? I mean, as a small company, just to get, just to get an approved vendor set up at Stanford, probably not an easy thing, right. There's all kinds of legal Ts and Cs. >> Exactly. >> As a startup their always worried about whether you're going to be around tomorrow. >> Exactly. >> So your part doin' AWS, so how's that been workin' with AWS and the Marketplace . >> Well firstly, it's definitely given us the Amazon backing in a way, so when people see you're on AWS, they see that connected to you, that automatically gives them a little bit more confidence. >> They vetted you so you must be good. >> Exactly, exactly. And the second is that it gives access to a market that we otherwise wouldn't have had like, if I'm thinking about like producing software that you have to download on our website, that's a very very limited market. You have to attract people to your website and so on and so on. Now it's like we're on the Amazon- there's a machine learning hub on AWS. We're on that, so which means that when people search for machine learning, our name does come up. >> Right, right >> It means it's very easy to launch. You don't have to worry about setting up a machine, worrying about how to configure it. Everything is done automatically, makes life really easy. >> Right. >> On top of that, the AWS team has been- the Marketplace team has been really extremely helpful connecting us with end customers. So very often they will refer people to us. In fact, one of our largest customers came through an AWS referral, so for us it's been nothing but a win-win. >> Right. What about the potential downside? Not to rain on the parade but the old joke used to be if you're a start-up makin' widgets, you know, you just got your first order with Walmart the good news. Bad news is you just got your first order with Walmart. That's opening up a huge global distribution opportunity, I mean in theory, you know, say you got a 1000 customers tomorrow, that might be a little bit of a challenge. >> Yeah, so we actually are starting to hit that. So, we- so our version two was really our go to market version and- which came out earlier this year, and so we've been trying to like wrap up the sales on that side and literally in the last three months. It's like I have not been home for six weeks now because I've been in the far East and traveling and, it' like- because of this heavy customer interaction at this point. So we have a very good story to tell the investors now, like, this has also helped with the investments rounds that we're actually looking at. So we have a very good story to tell the investors that you know, our like invoice list and so on is huge at this point so we need help now. It's actually more about raising, like building up a team now than it is about can we get orders. >> Right. It's really delivering more than sales. >> Exactly. >> I see what you're saying. And so we need to build up a delivery team, we need to- I mean, it's fairly intuitive, but at the same time it's a new technology which means, as with any platform, you're building up a team of evangelist, support individuals and so on. And there's going to be a marketing component as well, so we haven't really driven marketing that much. AWS has been great in kind of doing some of that for us, but we need to of course very actively go out and market. We haven't had that capacity yet. >> All right. We look forward to watching the story unfold and thanks for spending a few minutes with us. >> My pleasure. Thanks, thank you very much. All right, he's Rajeev Dutt, I'm Jeff. Thank you for watching the Cube. We're at the AWS Marketplace and Service Catalog Experience at the Aria, come on by. Thanks for watching. (upbeat music)

>> Announcer: Live from Las Vegas, it's theCUBE! Covering Dell Technologies World 2018. Brought to you by Dell EMC, and it's ecosystem partners. >> And welcome back to Las Vegas, as thCUBE continues our coverage here of Dell Technologies World 2018. So glad to have you along here for our Day Three coverage. Along with Stu Miniman, I'm John Walls. It's now a pleasure to welcome David Comroe with us. David is the Senior Director of Client Technology Services at the Wharton School of Business, at the University of Pennsylvania. David, thanks for being with us. >> No problem. Glad to be here. >> Thank for sharing your time with us. First off let's just talk about, about the scope of your work. Again, you take care of all the obviously IT needs for the largest business school faculty in the world. Right? No pressure on you there. But talk about day to day, those responsibilities. >> As you mentioned my title is Senior Director for Client Technology Services. I'm essentially responsible for providing the support and services to four very distinct user groups that we happen to have at a university. That's of course our wonderful faculty, our staff that make everything happen, our incredible students, and of course our alumni group, which is about 100,000 people strong at this point. Just Wharton alums that are again, very important. Give back to the school. Provide mentorship and job opportunities for our graduates. Again very distinct needs for each of those four groups. We provide a high quality, and all the buzzwords. You know, secure, safe, efficient, highly available services to these groups. That's kind of what I do all day. >> One of the cool things, I love acronyms. Not that this industry doesn't have a few, as you know Stu. But WHOOPPEE. I absolutely love making whoopie. But not what you might think. But walk us through that and what it stands for, and what you did in it. It really was groundbreaking. >> You're putting me on the spot with this one. So WHOOPPEE is the Wharton, let's see if I can get this, Online Ordinal Peer Performance Evaluation Engine. One of our incredible faculty, Pete Fader, came up with this idea. It's no secret that grading is kind of bad. Faculty grading students. There's all kinds of challenges. >> It's tedious. >> Well it's tedious. There's inherit biases when you're, the larger the class. And when you have to grade 80 papers, or 100 papers or 200 papers. It's really hard to keep consistency across when your grading paper one through paper 100 through paper 200. Plus when you start divvying up the work between TA's and different faculty teaching the same class. Again fraught with bias. A number of people, again Pet Fader's idea, to come up with basically an algorithm that helps the grading process. And basically what happens is, is students are grading themselves. What we'll do is we'll give them five papers or five projects to grade. And they don't actually grade. All they have to do is rank it. You know, this is the best one. This is number one. This is the worst one. This is number five. And then there's this magic behind the scenes that that runs in our local infrastructure, in our cloud infrastructure. That basically runs an algorithm. And that algorithm is the secret sauce that some of our statistical geniuses at the Wharton school, of which we have many, came up with. And it has all kinds of cool features. You can say, well this batch of five papers might be harder. I might have the five best papers in the class. That's not fair. They still have to rank one the worst. You know, five. You can't say these two are the best. And this one's third. You actually, the students have to read the paper, and just rank it. I like this one the best. I like second, third, fourth, fifth. The algorithm takes into account difficulty of batches of papers. You could literally have the five best or the five worst papers in the class. And that's still going to provide meaningful data to the algorithm. So when you have 50, 100, 500 batches of five. They all start to figure it out. And the algorithm will actually figure out what the best paper is in the class. And what the maybe again at the Wharton. But not so great, greatest paper in the class. >> But not the worst. Just not so great. Again cause our students are brilliant. It basically goes on the fact that if you do a quality paper. If the algorithm says you're the best. Your weight means more than someone who might not have done such a good job on the paper. And you're considered a better grader. And it's weighted towards the better graders. There's all kinds of really cool stuff in there that we think is going to change... Get rid of some of that bias that I spoke about before. And help provide. And the data we've seen is, frankly the students like doing it. They don't like the additional work involved with it. We're seeing some empirical evidence, and some in person interviews. That they're learning more. They're reading five other student's papers. They're getting five other perspectives. They're saying, hey I didn't think about that. Or even, hey they're all wrong here. My paper was much better than theirs. But again that doesn't necessarily matter when we start running the ranks. And we're getting much better, much better grading, which is hard to quantify, but the folks that are on the academic team that are doing that, have some really great data. With the data. Yup, mm-hm. >> David, one of the themes we keep hearing in this show is about transformation. Is change happening? You're talking about IT, how it's working with the business more and more. Bring us inside university life in general and specifically. You work with one of the ancient eight. How does cutting edge technology fit in with - >> That's really interesting. I do have a couple thoughts on that. My boss has a picture in his office, of a Penn classroom from I think it's like 1908 or 1910. And there's literally a bunch of students sitting around. There's a faculty member standing up. And there's a candle-powered projector, which I didn't know is a thing but it's in the picture, projecting an image onto the wall. From over 100 years ago. What's different about our classrooms today? Everything's the same, except the projector's now in LED. Or a L3D projector. We still got people sitting around the room, standing up. I think what we're seeing now in probably the previous ten years from now and to the next ten years is education's probably going to change more in those 20 years than it has in 2,000 years since Socrates was standing around with a stone tablet or whatever they were doing. Things like globalization, online courses, the MOOC space, where Wharton is huge in the MOOC space. Wharton online programs. Where students can take, not even students, anybody! If you're in China or Africa or South America. You can take an introduction to Wharton, introduction to marketing class from a Wharton professor for free. I mean we're a business school. We sell some of that content as well. But you can get verified certificates. We're seeing a lot of stuff change. The students today expect more. We can get into, we won't though, we can get into the whole millennial issue and short attention span and all that kind of stuff. Students today expect their faculty to be technology savvy. They expect content to be online. They expect to use devices. The expect to use... We got tablets, and laptops and phones. They want to be able to consume this content on multiple devices. We're seeing significant transformations in education. Which is, hasn't necessarily changed much in 2,000 years. Or even 200 years, right? So there's that. Speaking specifically about Wharton, one of the things I really thought is interesting, is I've been there 13 years now. When I first started working there, I'm going to make some generalizations here, a lot of our student wanted to go work in iBanking. They wanted to go work for the big banks. They wanted to go work for Goldman Sachs and things like that. In the last five, seven, ten years ago. They wanted to create their own company. Start up their own company. Be entrepreneurial. Have their app. Have their their big idea. Start the next whatever dot com. And be successful that way. Now in the last two or three, four years. We're seeing a lot of our students analytics. We're putting analytics with everything. Companies, businesses, organizations, no matter what you are, we have huge amounts of data available. How can we make meaningful decisions based on that data? Our dean. I guess I can't call him our new dean. He's been there three or four years at this point. Really wants to position Wharton as the analytics school. Every company in the world is trying to hire these kinds of people. There just frankly aren't enough of them out there. The thing we're trying to teach our students is, or one of the many things, is how to analyze data. How to make meaningful decisions based on that data. And of course when you have more data, you need more storage. You need more infrastructure. You need more processing. All the stuff that you know, Dell and Nutanix are providing us, with their hyper convergence infrastructure. Their cloud offerings. Whether private cloud, public cloud, hybrid cloud. All that kind of stuff is... Positioning us as the analytics school requires a significant amount of technology on the backend. And again working with our trusted partners like Dell and Nutanix we can provide that seamlessly in the backend. They don't necessarily know, is it in our data center? Is it in the cloud? And they don't care. They shouldn't care. But as they're collecting huge amounts of data, running these reports, and creating it, and going back to creating these algorithms that do incredible things. And these secret sauces. We need the infrastructure to run that kind of stuff. That's I think one of the greatest things that Wharton Computing provides the Wharton School of Business, and their business, which is creating and disseminating knowledge. >> David, I think you've encapsulated something that I've been hearing from lot's of users over the last year or so. The vendors sometimes, it's private, it's hybrid, it's public. From the user standpoint it's like, no well we have a cloud strategy that we're working on. Can you bring us inside a little bit? How did you get to where you are today? How do you choose who you're partnering with? What leads to some of those decisions? >> I love the word partner. I hate the word vendor. One of the great things about working at Wharton is, is we get to have these awesome partners. I want someone... When we're going to make an IT spend, we want someone who cares about our business. We don't want somebody who just, will come in, give you a dog and pony show, write us a check. And when you want more stuff call us. We want folks that are going to provide the support. You know, pre-sales during installation. Post-sales when they're coming out with new features. We want them to be invested in what we do. I can truly say that Nutanix is a fantastic partner of ours. Dell-Nutanix are great partners. Dell is a great partner of Wharton and Penn as well. That's what we really look for, is someone who is willing to invest their time, their smart people. Tell us about the new features and functionality that are coming out. Call on us and say, hey how are thing going? It's not just the little things. But those little things really mean a lot to us as we're picking an IT partner. Because when you're working for the best business school in the world. Having the best students, the brightest faculty, the best, hardest working staff. We want to provide them a very, very high quality IT support. We need high quality partners. And not just vendors who care about the transaction. That's really the bottom line for us. When we're choosing our partners. >> When you were talking about analytics, and Wharton being the school of data analytics. What are your measuring sticks? In terms of what are you looking at? You're talking about four very separate groups of constituencies. What are you doing to evaluate your performance? And what's critical? >> I think it all comes down to, what do our business units think about us? We're a service organization. Almost all IT shops are. If the business units aren't successful, they don't need an IT department. If we're not providing them high quality IT services, we're not going to get the best faculty. We're not going to get the brightest students. We're not going to get the alumni engagement. They want to be wowed by their IT support. That's a big part of my job, is providing that quality of support. Helping train. Technology breaks, right? How do you deal with the problem? Nobody runs at rock solid 100% infrastructure. Murphy's Law always comes into play. Problems always happen. How do you deal with the cracks in the armor as they come off? I think that's what our business units want. I think we're fortunate that we're computing. Our team, our staff, our CIO. My colleagues, my peers, my team. Our team, right? They're very well thought of, hopefully, by our clients. And that's how we're measured is by their success. We want to help them, empower them to do their job at the highest level. We are playing in pretty rare air, when it comes to the faculty, staff, students and alumni, that we attract to Penn and Wharton. We want to keep doing that. One of the things I love best, and I tell our wonderful faculty when we meet with them, is don't tell me we did a great job. Here's what I want you to tell me. I want you to say, three years ago I was at, I'm not going to name drop schools, but I was at this school and I asked them to do this thing, that you said, sure, no problem to. And they couldn't do it, wouldn't do it, didn't have the ability, the infrastructure in place to do that. But you guys with a smile on your face just made it happen. Stuff like WHOOPPEE. Stuff like the analytics stuff. All the, tying it back to why we're here today, is our partners and our technology partners that help us provide scalable, flexible solutions. That's how we're measured. >> Higher learning. >> Higher learning, absolutely. >> David, thanks for being with us. >> No problem, it was great. >> David Comroe from the Wharton School of Business, University of Pennsylvania. Back with more live coverage here from Dell Technologies World 2018. Right after this break. You're watching theCUBE.

>> Announcer: Live from Berlin, Germany, it's theCUBE, covering NetApp Insight 2017. Brought to you by NetApp. (upbeat music) >> Welcome back to theCUBE's live coverage of NetApp Insight 2017, here in Berlin, Germany. I'm your host, Rebecca Knight, along with my co-host, Peter Burris. We are joined by Shelia Fitzpatrick, she is the Chief Privacy Officer of NetApp, and Paul Stringfellow who is a Technical Director at Gardner Systems. Shelia, Paul, thanks so much for joining us. >> Thank you. >> Thank you for inviting us. >> So, I want to talk about data privacy. The general data protection regulation, the EU's forthcoming laws, GDPR, are going to take effect in May of next year. They represent a huge fundamental change about the way that companies use data. Can you just set the scene for our viewers and explain what these changes mean? >> Sure, happy to. As you said, GDPR is the newest regulation, it will replace the current EU directive, goes into effect May 25th of 2018. It has some fundamental changes that are massively different than any other data privacy laws you've ever seen. First and foremost, it is a legal, compliance and business issue as opposed to a technology issue. It's also the first extra-territorial regulation, meaning, it will apply to any organization anywhere in the world, regardless of whether or not they have a presence in Europe. But if they provide goods and services to an EU resident, or they have a website that EU residents would go to to enter data, they are going to have to comply with GDPR, and that is a massive change for companies. Not to mention the sanctions, the sanctions can be equal to 20 million Euro or 4% of a company's annual global turnover, pretty phenomenal sanctions. There are a lot of fundamental changes, but those are probably the biggest right there. >> What are some of the biggest challenges that companies are... I mean, you talked about the threat of sanctions and just the massive implications of what companies need to do to prepare? >> To really prepare, as I'm talking to customers, they really need, unfortunately a lot of companies are just thinking about security. And they're thinking, well as long as we have encryption, as long as we have tokenization, as long as we're locking down that data, we're going to be okay. I'm saying, no. It first and foremost starts with building that legal compliance program. What does your data privacy program look like? What personal data are you collecting? Why are you collecting it? Do you have the legal right to collect it? Part of GDPR requires unambiguous, explicit, freely-given consent. Companies can no longer force or imply consent. A lot of times when you go on to websites the terms and conditions are so impossible to understand that people just tick the box (laughs). Well, under GDPR, that will no longer be valid because it has to be very transparent, very easily understandable, very readable. And people have to know what organizations are doing with their data. And it puts ownership and more control of data back into the hands of the data subject, as opposed to the organizations that are collecting data. SO those are some of the fundamental changes. For the Cloud environment, for instance, for a lot of big hyperscalers, GDPR now puts obligations on data processors which is very different from the current regulation. SO that's going to be a fundamental change of business for a lot of organizations. >> Now, is it just customers or is it customers and employees as well? >> It's customers, employees, suppliers, it's any personal data that an organization collects, regardless of the relationship. >> SO what does it mean? Does it mean that I'm renting your data? Does it mean that I, 'cause you now own it, it's not me owning it. >> I own it, that's right. >> What are some of the implications of how folks are going to monetize some of these resources? >> SO what it actually means is, as an organization that's collecting data, you have to have a legal and valid business reason for needing that data. SO part of GDPR requires what's called, data minimization. You should only be collecting the minimal amount of data you need in order to provide the service you're going to provide, or manage the relationship you're going to manage. And you are never, as an organization, the owner of that data, you're the data steward. I am giving you permission to use my data for a very specific reason. You can't take liberties with that data. You can't do, what I call, scope-creep which is, once you have the data, "Oh, I can do whatever I want "with that data," no you can't. Unless I have consented to it, you cannot use that data. And so, that is going to be a major change for organizations to deal with and it doesn't matter if it's your employee data, your customer data, your partner data, your alternative worker data, your supplier data. Whose ever data you have, you better be transparent about that data. >> Shelia, you haven't once mentioned technology. Paul, what does this mean from a technology perspective? >> I suppose it's my job to mention technology? >> As Shelia will tell you, the GDPR, it should not be driven by IT. Because it's not an IT problem, it's absolutely a legal and compliance issue. However, I think there's a technology problem in there. So for lots of things that Shelia is talking about, in terms of understanding your data, in terms of being able to find data, being able to remove data when you no longer need to use it, that's absolutely a technology problem. And I think, actually, maybe something you won't hear said very often, I'm a real fan of GDPR, I think a it's long overdue it's probably because Shelia's been beating me round the head for the last 12 months >> I have. >> about it. But, I think it's one of those things that's long overdue to all of us within enterprises, within business, who hold and look after data. Because what we've done, traditionally, is that we just collected tons and tons of data and we bought storage 'cause storage could be relatively cheap, we're moving things to the Cloud. And, we've got absolutely no control, no management, no understanding of what the data is, where it is, who has access to it? Does anybody even access it, I'm paying for it, does anybody even use it? And I think what this is, for me, if GDPR wasn't a regulatory thing that we had to do, I think it's a set of really good practices that, as organizations, we should be looking to follow anyway. And technology plays a small part in that, it will enable organizations to understand the data better, it will enable those organizations to be able to find information as and when they need it. When somebody makes a subject access request, how are you going to find that data without appropriate technology? And I think, first and foremost, it's something that is forcing organizations to look at the way they culturally look after data within their business. This is no longer about, "Let me just keep things forever and I won't worry about it." This is a cultural shift that says data is actually an asset in your business. And as Shelia actually mentioned before, and something I'll pinch in future, the data is not mine, I'm just the custodian of that data while you allow me to be so. So I should treat that like anything else I'm looking after on your behalf. SO I think it's those kind of fundamental shifts that will drive technology adoption, no doubt, to allow you to do that, but actually, it's much more of a cultural shift in the way that we think of data and the way that we manage data in our businesses. >> Well you're talking about it as this regulation that is long overdue, and it will cause this cultural shift. So what will be different in the way that companies do business and the way that they treat their customer data, and their customer's privacy? And their employee's privacy, too, as you pointed out? >> Well, and part of the difference is going to be that need for transparency. So companies are going to have to be very upfront about what they're doing with the data, as Paul said. You know, why are they collecting that data, and they need to think differently about the need for data. Instead of collecting massive amounts of data that you really don't need, they need to take a step back and say, "This is the type of relationship "I'm trying to manage." Whether it's an employment relationship, whether it's a customer relationship, whether it's a partner relationship. What is the minimum amount of information I need in order to manage that relationship? So if I have an employee, for instance, I don't need to know what my employee does on their day off. Maybe that's a nice thing to know because I think well, maybe we can offer them a membership to a gym because they like to work out? That's not a must-have, that's a nice-to-have. And GDPR is going to force must-haves. In order to manage the employment relationship I have to be able to pay you, I have to be able to give you a job, I have to be able to provide benefits, I have to be able to provide performance evaluations and other requirements, but if it's not legally required, I don't need that data. And so it's going to change the way companies think about developing programs, policies, even technology. As they start to think about how they're developing new technology, what data do they need to make this technology work? And technology has actually driven the need for more privacy laws. If you think about IoT, artificial intelligence, Cloud. >> Mobile. >> Absolutely. Great technology, but from a privacy perspective, the privacy was never a part of the planning process. >> In fact, in many respects it was the exact opposite. There were a whole bunch of business models, I mean if you think about it in the technology industry, there's two fundamental business models. There's the ad-based business model, which is, "Give us all your data "and we'll figure out a way to monetize it." >> Absolutely. >> And there's a transaction-based business model which says, "We'll provide you a service "and you pay us, and we promise to do something "and only something with your data." >> Absolutely. >> It's the difference between the way Google and Facebook work, and say, Apple and Microsoft work. SO how is this going to impact these business models in ways of thinking about engaging customers at least where GDPR is the governing model? >> Well, it is going to force a fundamental change in their business model. SO the companies that you mentioned, that their entire business model is based on the collection and aggregation of data, and in some cases, the selling of personal data. >> Some might say screwing you. >> Some might definitely say that, especially if you're a privacy attorney, you might say that. They offer fabulous services and people willingly give up their privacy, that's part of the problem, is that they're ticking the box to say, "I want to use Facebook, I want to use Twitter, "I want to use LinkedIn "because these are great technologies." But, it's the scope-creep. It's what you're doing behind the scenes that I don't know how you're using my data. SO transparency is going to become more and more critical in the business model and that's going to be a cultural, as Paul said, a cultural shift for companies that their entire business model's based on personal data. They're struggling because they're the companies that, no matter what they do, they're going to have to change. They can't just make a simple, change their policy or procedure, they have to change their entire business model to meet the GDPR obligations. >> And I think from, like Shelia says there, and obviously GDPR's very much around, kind of, private data. Well, the conversation we're having with our customers is, is a much wider scope than that, it is all of the data that you own. And it's important, I think, organizations need to stop being fast and loose with the information that they hold because not only is the private information about those people there that, you know, me and you, and that we don't want that necessarily leaked across the well to somebody who might look to exploit that for some other reason. But, that might be, business confidential information, that might be price list, it might be your customer list. And, at the moment, I think in lots of organizations we have a culture where people from top to bottom in an organization don't necessarily understand that. SO they might be doing something where, we had a case in UK recently where some records, security arrangements for Heathrow Airport were found on a bus. So somebody copied them to a USB stick, no encryption, somebody copied it to a USB stick, thought it was okay to take home and leave in the back of, probably didn't think it was okay to leave in the back of the taxi, but certainly thought it was okay to take that information home. And you look at that and think, well, what other business asset that that organization held would they have treated with such disdain, almost to say "I just don't care, this is just ones and zeroes, "why would I care about it?" It's that shift that I think we're starting to see. And I think it's that shift that organizations should have taken a long time ago. We talk to customers, and you hear of events like this all the time, data is the new gold, data is the new precious material of your choice. >> Which it really isn't. It really isn't, here's why I say that because this is the important thing and leads to the next question I was going to ask you. Every asset that's ever been conceived follows the basic laws in economic scarcity. Take gold, you can apply to that purpose, you can make connectors for a chip, or you can use it as a basis for making jewelry or some other purpose. But, data is fungible in so many ways. You can connect it and in many respects, we talked about it a little bit earlier, the act of making it private is, in many respects, the act of turning it into an asset. SO one of the things I want to ask you about, if you think about it, is that, there will still be a lot of net new ways to capture data that's associated with a product or service in a relationship. SO we're not saying that GDPR is going to restrict the role that data plays, it's just going to make it more specific. We're still going to see more IoT, we're still going to see more mobile services, as long as the data that's being collected is in service to the relationship or the product that's being offered. >> Yeah, you're absolutely right. I mean, one of the things that I always say is that, GDPR's intent is not stop organizations from collecting data, data is your greatest asset, you need data to manage any kind of relationship. But, you're absolutely right in what it's going to do is force transparency, so instead of doing things behind the scenes where nobody has any idea what you're doing with my data, companies are going to have to be extremely transparent about it and think about how it's being used. You talked about data monetization, healthcare data today is ten times more valuable than financial data. It is the data that all hackers want. And the reason is, is because you take even aggregate and statistical information through, say trial clinics, information that you think there's no way to tie it back to a person, and by adding just little elements to it, you have now turned that data into greater value and you can now connect it back to a person. SO data that you think does not have value, the more we add to it and the more, sort of, profiling we do, the more valuable that data is going to become. >> But it's even more than that, right? Because not only are you connecting it back to a person, you're connecting it back to a human being. Whereas financial data is highly stylized, it's defined, it's like this transaction defining, and there's nothing necessarily real about it other than that's the convention that we used to for example, do accounting. But, healthcare data is real. It ties back to, what am I doing, what drugs am I taking, why am I taking them, when am I visiting somebody? This is real, real data that provides deep visibility into the human being, who they are, what they face, and any number of other issues. >> Well, if you think about GDPR, too, they expanded the definition of personal data under GDPR. SO it now includes data, like biometric and genetic information that is heavily used in the healthcare industry. It also includes location data, IP information, unique identifiers. SO a lot of companies say, "Well, we don't collect personal data "but we have the unique identifiers." Well, if you can go through any kind of process to tie that back to a person, that's now personal data. SO GDPR has actually the first entry into the digital age as opposed to the old fashioned processing. Where you can now take different aspects of data and combine it to identify a human being, as you say. >> So, I got one more question. This is something of a paradox, sorry for jumping in, but I'm fascinated by this subject. Something of a paradox. Because the act of making data private, at least to the corporation, is an act of creating an asset, and because the rules of GDPR are so much more specific and well thought through than most rules regarding data, does it mean that companies that follow GDPR are likely, in the long run, to be better at understanding, taking advantage of, and utilizing their data assets? That's the paradox. Most people say, "I need all the data." Well, GDPR says, "Maybe you need to be more specific "about how you handle your data assets." What do you think, is this going to create advantages for certain kinds of companies? >> I think it absolutely is going to create advantages in two ways. One, I see organizations that comply with GDPR as having a competitive advantage. Because, number one it goes down to trust. If I'm going to do business with Company A or Company B, I'm going to do business with the company that actually takes my personal data seriously. But, looking' at it from your point of view, absolutely. As companies become more savvy when it comes to data privacy compliance, not just GDPR, but data privacy laws around the world, they're also going to see more of that value in the data, be more transparent about it. But, that's also going to allow them to use the data for other purposes, because they're going to get very creative in how having your data is actually going to benefit you as an individual. SO they're going to have better ways of saying, "But, by having your data I can offer you these services." >> GDPR may be a catalyst for increased data maturity. >> Absolutely. >> Well, I wanna ask you about the cultural shift. We've been talking so much about it from the corporate standpoint, but will it actually force a cultural shift from the customer standpoint, too? I mean, this idea of forcing transparency and having the customer understand why do you need this from me, what do you want? I mean, famously, Europeans are more private than Americans. >> Oh much so. As you've said, "Just click accept, okay, fine, "tell me what I need to know, "or how can I use this website?" >> Well, the thing is that, it's not necessarily from a consumer point of view, but I do think it's from a personal point of view from everybody. SO whether you work inside an organization that keeps data, that's starting to understand just how valuable that data might be. And just to pick up on something, that just to pop at something you were saying before, I think one of the other areas where this has business benefit is that that better and increased management and maturity, actually I think is actually a great way, that better maturity around how we look after our data, has huge impact. Because, it has huge impact in the cost of storing' it, if we want to use Cloud services why am I putting things there that nobody looks at? And then, looking at maintaining this kind of cultural shift that says, "If I'm going to have data in my organization, "I'm no longer going to have it on a USB stick "and leave it in the back of a cab "when it's got security information "of a global major airport on it. "I'm going to think about that "because I'm now starting to understand." And this big drive about, people starting to understand how the information that people keep about you has a potential bigger impact, and it has a potential bigger impact if that data, yeah, we've seen data breach, after data breach after data breach. You can't look at the news any day of the week without some other data breach and that's partly because, a bit like health and safety legislation, GDPR's there because you can't trust all those organizations to be mature enough with the way that we look after our data to do these things. SO legislation and regulations come across and said, "Well, actually this stuff's really important "to me and you as individuals, "so stop being fast and loose with it, "stop leaving it in the back of taxis, "stop letting it leak out your organization "because nobody cares." And that's driving a two-way thing, here, it's partly we're having to think more about that because actually, we're not trusting organizations who are looking after our data. But, as Shelia said, if you become an organization that has a reputation for being good with the way they lock their data, and look after data, that will give you a competitive edge alongside, actually I'm being much more mature, I'm being much more controlled and efficient with how I look after my data. That's got big impact in how I deliver technology and certainly, within a company. Which is why I'm enthusiastic about GDPR, I think it's forcing lots and lots of long-overdue shift in the way that we, as people, look after data, architect technology, start to think about the kind of solutions and the kind of things that we do in the way that we deliver IT into business and enterprise across the globe. >> I think one of the things, too, and Paul brought it up, is he mentioned security several times. And, as Paul knows, one of my pet peeves is when companies say, "We have world-class security, "therefore we're compliant with GDPR." And I go, "Really, so you're basically locking down data "you're not legally allowed to have? That's "what you're telling me." >> Like you said earlier, it's not just about having encryption everywhere. >> Exactly, and it's funny how many companies say "Well, we're compliant with GDPR "because we encrypt the data." And I go, "Well, if you're not legally allowed "to have that data, that's not going to help you at all." And, unfortunately, I think that's what a lot of companies think, that as long as we're looking at the security side of the house, we're good. And they're missing the whole boat on GDPR. >> It's got to be secure. >> It's got to be secure. >> But-- >> You got to legally have it first. >> Exactly. The chicken and the egg. >> But, what's always an issue with security, around data and the stuff that Shelia talked about is quite a lot, is that one of the risks you have, is you can have all the great security in the world but, if the right person with the right access to the right data has all the things that they should have, that doesn't mean that they can't steal that data, lose that data, do something with that data that they shouldn't be doing, just because we've got it secured. SO we need to have policies and procedures in place that allow us to manage that better, a culture that understands the risk of doing those kinds of things, and maybe, alongside technologies that identify, unusual use of data are important within that. >> Well, Paul, Shelia, thank you so much for coming on the show, it's been a fascinating conversation. >> Thank you very much, appreciate it. >> Yeah, thanks for having us on, appreciate it. >> I'm Rebecca Knight for Peter Burris, we will have more from NetApp Insight here in Berlin in just a little bit. (upbeat music)

>> Hey, welcome back everybody, Jeff Frick here with the Cube. We are here in Denver, Colorado at the DJI AirWorks show, it's their second show; about 600 people talking about commercial applications for the DJI drone platform. Really exciting agriculture, construction, public safety, no fun stuff, well, it's all kind of fun, really about the commercial applications, and we're excited to have Chris Boots with us, he is the chief engineer of Quadrocopter. Chris, good to see you. >> Good to see you. >> So we talked a little bit about what Quadrocopter does, and you're really into the enterprise space, these are not platforms that are generally available, you've got to get them through a dealer, they're expensive, they're complicated pieces of equipment, and that's a place you guys have been playing for a long time. >> Absolutely. For example, the Wind Series was unveiled today, the 4 and the 8; AirWorks 2016 introduced the Wind 1 and 2, and what these are, are basically universal platforms that allow customers to put various different, whether it be gimbals or sensors, it's kind of just a blank slate DJI product. That way you're not constrained to the limitations of an M200 or an Aspire or anything like that. When Quadrocopter began almost a decade ago, we prided ourselves on delivering custom-tailored systems to various different customer needs, so we felt right at home when DJI unveiled the Wind series. >> So really what you mean is it's kind of stripped down to its bare bones components so that you can design it at whatever payloads you want for the specific application, and they're also big, heavy lifters, right? We saw the agricultural one, I think it holds like two and a half gallons, 22 pounds of liquid, so these are also heavy lift machines, these are not little Mavics or Sparks. >> Yeah, precisely, yeah. If you need to lift something lightweight, there's the Wind 1. If you need to lift something extremely heavy, there's the Wind 4 and the Wind 8 which can lift well over 20 to 25 pounds of payload, so you're lifting some big stuff with this. >> So when you talk to enterprise customers, and kind of their journey into getting into and using a drone platform for their business process, how do they get started, you know, what do you see as kind of their first steps where people have some success and then you know, build into more of a fleet if you will, integrate it more to their processes? How do most companies get started? Do they say yeah this looks like a cool platform, how do we use it? >> That's kind of exactly how it happens. It just all starts with an idea. Most of our customers if they're not already existing UAS corporations and companies, they can be just somebody like you or I that comes up with an interesting UAV solution and you know, they do some Google searching, they do some research, they find something like this doesn't exist. Where do I go from here? So it doesn't take them very long to start making phone calls, and more often than not they call us at Quadrocopter, and one of my pet peeves is I don't like saying no to a customer when they have an idea, so that basically takes their idea, it takes our resources whether it be DJI or third party integrations, and making their dream a reality, so it's not always cinematography and cameras, it can be sensors or you name it, so yeah! >> So what are some of the more innovative uses that you've seen people use the DJI platform for that you would have never thought of, most people on the street would never have an idea that this is a useful application for this platform? >> Sure, well, I'll talk a little bit about the latest Wind application that we designed this year. We utilized the larger of the four copters, the Wind 8, which is an octocopter, and the client had the idea of inspecting methane pipelines. Now these pipelines need to be inspected every six months per governmental regulation. Currently, the only way that most companies like BP and other gas industries are doing this is by foot, by ATV, with handheld sensors, or on a large scale with rotorcraft like helicopters and people hanging off the sides of them, again with handheld devices. >> And what, they've got specialty sensors that they're looking for leaks and this and that, it's not really visual inspection I take it, or is it both probably? >> A lot of times they use either a laser-based or a thermal-based handheld sensor, so like a flare thermal camera. In our case, we didn't want to be constrained to the environmental influences that thermal can sometimes have, whether it's cold or it's dark or bright out, it can really skew the results, so in our case, it was our goal to find something that isn't influenced by the external environments. So we officially landed on a laser-based methane detector and paired that with the Wind 8, which then flies the pipeline route in 10 to 20 foot segments, comes back, and that data is used in mapping software to find out what the results were along that pipeline. If it is found that something is leaking, that file that is pulled off the aircraft will say exactly where it was, how concentrated it was at that exact point, at which point somebody can on the ground inspect that further. It totally gets rid of the whole safety issue of somebody on the ground or in the air and the expensive part of man power, of walking a pipeline. We can do it more efficiently, we can do it way more safer, and we get if not better results. >> The 10 to 20 feet doesn't sound like very long. Is that just because of, >> 20 miles. >> Oh 20 miles. You said feet. So it's 10 to 20 mile runs, then in parts they take the data and run it again. And what was the weight of that payload? >> The sensor itself doesn't really weigh much, I'd say two or three pounds. Most of the payload on the Wind 8 is actually the batteries. So the whole all-up weight of the craft is somewhere around 30 pounds. It's not extremely heavy, but for endurance sake, she'll fly for well over an hour. So at 10, 15 miles per hour, you can really cover some pipeline with battery to spare. >> So was that an initial trial for this customer, to try this solution? >> Yeah, this particular combination of sensor and copter had never been tried before, so it very much is an industry first in this regard, at least with DJI and the sensor. >> So where do they want to go next? I mean, it begs the question. The whole theme of today's keynote was like scale, no longer single operator, single machine, single data, but really starting to think in terms of fleets and multi-units, so is that somewhere where this particular customer wants to go, or how do you see it progressing for them? >> This particular client is a third party, so they aren't directly with BP, but BP often, I don't want to speak on behalf of BP, but a lot of gas companies outsource their inspection services to other different companies, so this particular land surveying company will use this and meet their demands of inspecting whatever section of pipeline that they're designated every six months. >> Yeah, that's great, alright, Chris, thank you for spending a few minutes, I mean that's a great case study and using the big heavy lift stuff, much more fun probably than the Spark! >> Absolutely, yeah, if you guys have any questions, hit me up at quadrocopter.com! >> Alright, he's Chris Boots, I'm Jeff Frick, you are watching the Cube. We're at DJI AirWorks 2017 in Denver. Catch you next time; thanks for watching.

(electronic music) >> Host: Live from Midtown Manhattan it's The Cube! Covering Big Data New York City 2017, brought to you by Silicon Angle Media, and its Ecosystem sponsors. >> Okay, welcome back everyone. We are here live, The Cube in New York City for Big Data NYC, this is our fifth year, doing our own event, not with O'Reilly or Cloud Era at Strata Data, which as Hadoop World, Strata Conference, Strata Hadoop, now called Strata Data, probably called Strata AI next year, we're The Cube every year, bringing you all the great data, and what's going on. Entrepreneurs, VCs, thought leaders, we interview them and bring that to you. I'm John Furrier with our next guest, Greg Sands, who's the managing director and founder of Costa Nova ventures in Palo Alto, started out as an entrepreneur himself, then single shingle out there, now he's a big VC firm on a third fund. >> On the third fund. >> Third fund. How much in that fund? >> 175 million dollar fund. >> So now you're a big firm now, congratulations, and really great to see your success. >> Thanks very much. I mean, we're still very much an early stage boutique focused on companies that change the way the world does business, but it is the case that we have a bigger team and a bigger fund, to go do the same thing. >> Well you've been great to work with, I've been following you, we've known each other for a while, watched you left Sir Hill and start Costanova, but what's interesting is that, I can kind of joke and kid you, the VC inside joke about being a big firm, because I know you want to be small, and like to be small, help entrepreneurs, that's your thing. But it's really not a big firm, it's a few partners, but a lot of people helping companies, that's your ethos, that's what you're all about at your firm. Take a minute to just share with the folks the kinds of things you do and how you get involved in companies, you're hands on, you roll up your sleeves. You get out of the way at the right time, you help when you can, share your ethos. >> Yeah, absolutely so the way we think of it is, combining the craft of old school venture capital, with a modern operating team, and so since most founder these days are product-oriented, our job is to think like product people, not think like investors. So we think like product people, we do product level analysis, we do customer discovery, we do, we go ride along on sales calls when we're making investment decisions. And then we do the things that great venture capitalists have done for years, and so for example, at Alatian, who I know has been on the show today, we were able to incubate them in our office for a year, I had many conversations with Sathien after he'd sold the first two or three customers. Okay, who's the next person we hire? Who isn't a founder? Who's going to go out and sell? What does that person look like? Do you go straight to a VP? Or do you hire an individual contributor? Do you hire someone for domain, or do you hire someone for talent? And that's the thing that we love doing. Now we've actually built out an operating team so marketing partner, Martino Alcenco, and Jim Wilson as a sales partner, to really help turn that into a program, so that they can, we can take these founders who find product market fit, and say, how do we help you build the right sales process and marketing process, sales team and marketing team, for your company, your customer, your product? >> Well it's interesting since you mention old school venture capital, I'll get into some of the dynamics that are going on in Silicon valley, but it's important to bring that forward, because now with cloud you can get to critical mass on the fly wheel, on economics, you can see the visibility faster now. >> Greg: Absolutely. >> So the game of the old school venture capitalist is all the same, how do you get to cruising altitude, whatever metaphor you want to use, the key was getting there, and sometimes it took a couple of rounds, but now you can get these companies with five million, maybe $10 million funding, they can have unit economics visibility, scales insight, then the scale game comes in, so that seems to be the secret trick right now in venture is, don't overspend, keep the valuation in range and allows you to look for multiple exits potentially, or growth. Talk about that dynamic, because this is like, I call it the hour glass. You get through the hour glass, everyone's down here, but if you can sneak through and get the visibility on the economics, then you grow quickly. >> Absolutely. I mean, it's exactly right an I haven't heard the hour glass metaphor before but I like it. You want to basically get through the narrows of product market fit and the beginnings of scalable sales and marketing. You don't need to know all the answers, but you can do that in a capital-efficient way, building really solid foundations for future explosive growth, look, everybody loves fast growth and big markets, and being grown into. But the number of people who basically don't build those foundations and then say, go big or go home! And they take a ton of money, and they go spend all the money, doing things that just fundamentally don't work, and they blow themselves up. >> Well this is the hourglass problem. You have, once you get through that unique economics, then you have true scale, and value will increase. Everybody wins there so it's about getting through that, and you can get through it fast with good mentoring, but here's the challenge that entrepreneurs fall into the trap. I call it the, I think I made it trap. And what happens is they think they're on the other side of the hourglass, but they still haven't even gone through the straight and narrow yet, and they don't know it. And what they do is they over fund and implode. That seems to be a major trap I see a lot of entrepreneurs fall into, while I got a 50 million pre on my B round, or some monster valuation, and they get way too much cash, and they're behaving as if they're scaling, and they haven't even nailed it yet. >> Well, I think that's right. So there's certainly, there are stages of product market fit, and so I think people hit that first stage, and they say, oh I've got it. And they try to explode out of the gates. And we, in fact I know one good example of somebody saying, hey, by the way, we're doing great in field sales, and our investors want us to go really fast, so we are going to go inside and we, my job was to hire 50 inside people, without ever having tried it. And so we always preach crawl, walk, run, right? Hire a couple, see how it works. Right, in a new channel. Or a new category, or an adjacent space, and I think that it's helpful to have an investor who has seen the whole picture to say, yeah, I know it looks like light at the end of the tunnel, but see how it's a relatively small dot? You still got to go a little farther, and then the other thing I say is, look, don't build your company to feed your venture capitalist ego. Right? People do these big rounds of big valuations, and the big dog investors say, go, go, go! But, you're the CEO. Your job is analyze the data. >> John: You can find during the day (laughs). >> And say, you know, given what we know, how fast should we go? Which investments should we make? And you've got to own that. And I think sometimes our job is just to be the pulling guard and clear space for the CEO to make good decisions. >> So you know I'm a big fan, so my bias is pretty much out there, love what you guys are doing. Tim Carr is a Pivot North doing the same thing. Really adding value, getting down and dirty, but the question that entrepreneurs always ask me and talk privately, not about you, but in general, I don't want the VC to get in the way. I want them, I don't want them to preach to me, I don't want too many know-it-alls on my board, I want added value, but again, I don't want the preaching, I don't want them to get in the way, 'cause that's the fear. I'm not saying the same about VCs in general, but that's kind of the mentality of an entrepreneur. I want someone who's going to help me, be in the boat with me, but not be in my way. How do you address that concern to the founders who think, not think like that, but might have a fear. >> Well, by the way, I think it's a legitimate fear, and I think it actually is uncorrelated with added value, right? I think the idea that the board has certain responsibilities, and management has certain responsibilities, is incredibly important. And I think, I can speak for myself in saying, I'm quite conscious of not crossing that line, I think you talk. >> John: You got to build a return, that's the thing. >> But ultimately I would say to an entrepreneur, I'd just say, hey look, call references. And by the way, here are 30 names and phone numbers, and call any one of them, because I think that people who are, so a venture capital know-it-all, in the board room, telling CEOs what to do, destroys value. It's sand in the gears, and it's bad for the company. >> Absolutely, I agree 100% >> And some of my, when I talk about being a pulling guard for the CEO, that's what I'm talking about, which is blocking people who are destructive. >> And rolling the block for a touchdown, kind of use the metaphor. Adding value, that's the key, and that's why I wanted to get that out there because most guys don't get that nuance, and entrepreneurs, especially the younger ones. So it's good and important. Okay, let's talk about culture, obviously in Silicon Valley, I get, reading this morning in the Wymo guy, and they're writing it, that's the Silicon Valley, that's not crazy, there's a lot of great people in Silicon Valley, you're one of them. The culture's certainly an innovative culture, there's been some things in the press, inclusion and diversity, obviously is super important. This whole brogrammer thing that's been kind of kicked around. How are you dealing with all that? Because, you know, this is a cultural shift, but I think it's being made out more than it really is, but there's still our core issues, your thoughts on the whole inclusion and diversity, and this whole brogrammer blowback thing. >> Yeah, well so I think, so first of all, really important issues, glad we're talking about them, and we all need to get better. And to me the question for us has been, what role do we play? And because I would say it is a relatively small subset of the tech industry, and the venture capital industry. At the same time the behavior of that has become public is appalling. It's appalling and totally unacceptable, and so the question is, okay, how can we be a part of the stand-up part of the ecosystem, and some of which is calling things out when we see them. Though frankly we work with and hang out with people and we don't see them that often, and then part of which is, how do we find a couple of ways to contribute meaningfully? So for example this summer we ran what we called the Costanova Access Fellowship, intentionally, trying to provide first opportunity and venture capital for people who traditionally haven't had as much access. We created an event in the spring called, Seat at the Table, really, particularly around women in the tech industry, and it went so well that we're running it in New York on October 19th, so if you're a woman in tech in New York, we'd love to see you then. And we're just trying to figure-- >> You're doing it in an authentic way though, you're not really doing it from a promotional standpoint. It's legit. >> Yeah, we're just trying to do, you know, pick off a couple of things that we can do, so that we can be on the side of the good guys. >> So I guess what you're saying is just have high integrity, and be part of the solution not part of the problem. >> That's right, and by the way, both of these initiatives were ones that were kicked off in late 2016, so it's not a reaction to things like binary capital, and the problems at uper, both of which are appalling. >> Self-awareness is critical. Let's get back to the nuts and bolts of the real reason why I wanted you to come on, one was to find out how much money you have to spend for the entrepreneurs that are watching. Give us the update on the last fund, so you got a new fund that you just closed, the new fund, fund three. You have your other funds that are still out there, and some funds reserved, which, what's the number amount, how much are you writing checks for? Give the whole thesis. >> Absoluteley. So we're an early stage investor, so we lead series A and seed financing companies that change the way the world does business, so up and down the stack, a business-facing software, data-driven applications. Machine-learning and AI driven applications. >> John: But the filter is changing the way the world works? >> The way, yes, but in particularly the way the world does business. You can think of it as a business-facing software stack. We're not social media investors, it's not what we know, it's not what we're good at. And it includes security and management, and the data stack and-- >> Joe: Enterprise and emerging tech. >> That's right. And the-- >> And every crazy idea in between. >> That's right. (laughs) Absolutely, and so we're participate in or leave seed financings as most typically are half a million to maybe one and a quarter, and we'll lead series A financing, small ones might be two or two and a half million dollars at the outer edge is probably a six million dollar check. We were just opening up in the next couple of days, a thousand square feet of incubation space at world headquarters at Palo Alto. >> John: Nice. >> So Alation, Acme Ticketing and Zen IQ are companies that we invested in. >> Joe: What location is this going to be at? >> That's, near the Fills in downtown Palo Alto, 164 staff, and those three companies are ones where we effectively invested at formation and incubated it for a year, we love doing that. >> At the hangout at Philsmore and get the data. And so you got some funds, what else do you have going on? 175 million? >> So one was a $100 million fund, and then fund two was $135 million fund, and the last investment of fund two which we announced about three weeks ago was called Roadster, so it's ecommerce enablement for the modern dealerships. So Omnichannel and Mobile First infrastructure for auto-dealers. We have already closed, and had the first board meeting for the first new investment of fund three, which isn't yet announced, but in the land of computer vision and deep learning, so a couple of the subjects that we care deeply about, and spend a lot of time thinking about. >> And the average check size for the A round again, seed and A, what do you know about the? The lowest and highest? >> The average for the seed is half a million to one and a quarter, and probably average for a series A is four or five. >> And you'll lead As. >> And we will lead As. >> Okay great. What's the coolest thing you're working on right now that gets you excited? It doesn't have to be a portfolio company, but the research you're doing, thing, tires you're kicking, in subjects, or domains? >> You know, so honestly, one of the great benefits of the venture capital business is that I get up and my neurons are firing right away every day. And I do think that for example, one of the things that we love is is all of the adulant infrastructure and so we've got our friends at Victor Ops that are in the middle of that space, and the thinking about how the modern programmer works, how everybody-- >> Joe: Is security on your radar? >> Security is very much on our radar, in fact, someone who you should have on your show is Asheesh Guptar, and Casey Ella, so she's just joined Bug Crowd as the CEO and Casey moves over to CTO, and the word Bug Bounty was just entered into the Oxford Dictionary for the first time last week, so that to me is the ultimate in category creation. So security and dev ops tools are among the things that we really like. >> And bounties will become the norm as more and more decentralized apps hit the scene. Are you doing anything on decentralized applications? I'm not saying Blockchain in particular, but Blockchain like apps, distributing computing you're well versed on. >> That's right, well we-- >> Blockchain will have an impact in your area. >> Blockchain will have an impact, we just spent an hour talking about it in the context our off site in Decosona Lodge in Pascadero, it felt like it was important that we go there. And digging into it. I think actually the edge computing is actually more actionable for us right now, given the things that we're, given the things that we're interested in, and we're doing and they, it is just fascinating how compute centralizes and then decentralizes, centralizes and then decentralizes again, and I do think that there are a set of things that are fascinating about what your process at the edge, and what you send back to the core. >> As Pet Gelson here said in the QU, if you're not out in front of that next wave, you're driftwood, a lot of big waves coming in, you've seen a lot of waves, you were part of one that changed the world, Netscape browser, or the business plan for that first project manager, congratulations. Now you're at a whole nother generation. You ready? (laughs) >> Absolutely, I'm totally ready, I'm ready to go. >> Greg Sands here in The Cube in New York City, part of Big Data NYC, more live coverage with The Cube after this short break, thanks for watching. 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>> Announcer: Live, from Washington, DC, it's theCUBE. Covering .cof2017. Brought to you by Splunk. (upbeat techno music) >> Welcome back to the nation's capital, theCUBE coming to you here from the Walter Washington Convention Center at .conf2017, Splunk's annual get-together, along with Dave Vellante, I'm John Walls. Good to have you with us here on theCUBE and how's your flying experience these days here in the States? Baggage, security, you happy? Well we're going to make you a little less... (laughs) Dubai Airports has just an exceptional network of operations that are going on right now, from soup to nuts and Michael Ibbitson is the VP of Technology and Infrastructure at Dubai. He joins us now here on theCUBE, and Michael, first off, glad to have you here in the States. >> Thank you. Good to be here. >> Good to see you, sir. You ran through on the key note stage a litany of checks that we all go through here in the States of, yes we'd love... better security, better baggage, even the golden bathroom, which I can't wait to hear about. But tell me about your focus with technology and Dubai, and what you're bringing to the job and how you're trying to revolutionize the travel experience. >> Yeah so, in Dubai we're really, really pushing the envelope in terms of volume, numbers of people going through the airport, but also we want to make it the best passenger experience we possibly can. We're already the biggest international airport in the world, going to be doing nearly 90 million passengers this year, growing to 100 million by the end of the decade, but we want to drive experience as well. And the airport is constrained, so we've got a limited site, so we now have to figure out how to do it to greater efficiency, automation, making the passenger experience better. You can get much better throughput in an airport if you take out all the queues. So that's a better experience. So you get both at the same time. >> Well, tell us about the security lines then, because Dave and I both relate to this here in the States. Sometimes they can be tedious to work through. So how are you addressing that through technology. >> Well, through lots of different ways. I mean, we put sensors all over the airport for lots of different things, and one of the key areas we've done it is in security. So we have some sensors that measure the queue length for us, which is really important. It allows us to understand what's happening now, in real time, deploy additional staff to support that, but also predicts what's happening over the next few hours, so we can be ready for whatever's coming next. On top of that, we then take data out of the lane itself, in real time, so we can see how many people are passing through, how many alarms they're setting off, and then we can use that data over time to understand the behavior of passengers. Certain destinations drive more security alarms, so we can now understand that and then try and pre-inform those passengers about what to do so everybody gets through faster. >> So kind of, like a way, is in reverse for the security line. >> Yeah, exactly. >> Love it, that's great. >> So, you mentioned the golden bathroom, I got to ask you-- (laughter) We saw some data that only 10 percent of the people admit that they don't wash their hands when they leave the bathroom, but your data suggests its 25 percent of the people do not. I wonder if part of that reason is the reason that I often get frustrated is, when you put your hands underneath, nothing comes out. (laughter) >> John: You're waving underneath, right? >> In modern Dubai, airport bathrooms must actually give me water when I ask for it, is that right? >> Yeah, well, we like to think we've got pretty efficiently working bathrooms, that's for sure, but I think the challenge with the bathroom one, we wanted to understand how to make bathrooms cleaner and a nicer environment for everybody, and when you're doing 90 million passengers a year, that's a lot of people going to the bathroom. We put sensors all over the bathrooms, not CCTV, want to make sure that's clear. It's all like presence sensors, door lock sensors, when the faucets are on or off, people stood at basins, and that's just given us so much insight into how people actually use the bathroom. So we know that at peak hours, the number are quite low in terms of people who wash their hands after using the bathroom, but off-peak when it's quiet, the number goes right up to 100 percent. So, we think we've got some work to do on capacity, and understanding how people use the bathroom, and also maybe on the cleanliness. Maybe people are leaving because it's the lesser of two evils. Do I wash my hands, which doesn't look like a nice environment to wash my hands, or do I just walk out? >> So, some of the stats. 90 million passengers a year go through your airport and that'll be 100 million, over 100 million by 2020, is that right? >> Michael: On the current growth, yeah. >> And then 150 million bags, you handle, each year. >> Michael: That's correct. >> So there's a lot of data that you're collecting. So hence we're here at .conf. How do you use Splunk to sort of manage all this data? >> So we have two Splunk instances. We have one that does all of our IT stuff, and then we have one that's focused on all the business services, operations, if you like. And it's the business one that is kind of the most interesting because it drives the most debate and discussions about the future, and how we should plan the airport, and how we should drive performance. We have about four and a half billion data points in our Splunk, in our business Splunk instance, and it grows by somewhere around 12 to 14 million data points a day. Just baggage alone, every bag generates about 200 data points. Now, people don't probably think that from the outside, when you put the bag in, you drop the bag at the check-in desk and then you don't see it again til you to the other end, but there's so many check points that it passes, security screening that it goes through. It gets transferred in terms of jurisdiction between airline, airport, ground handler, and then it gets loaded onto the aircraft. All of these things, we create data points for all of those. So we can track it through your whole journey. I think these are fantastic opportunities for us to start thinking about how we might share that data the consumer in the future. We'd like to get to a point where your bag journey is just as well-informed as your own journey. >> Yeah, so, a little bit more on that then, I mean, just in terms of what your real life experience, what you hope it will be, in terms of your baggage, You were talking about taking down baggage arrival to a matter of seconds? >> Yeah so, you as a passenger, you arrive at the airport. You've got a process to go through before you're going to get reunited with your baggage, and that might be 10 minutes or 30 minutes, depending on the size and the nature of the airport that you arrive at. But as we know now, based on the data we have in Splunk, and we've been analyzing this data over the last four or five months, we know exactly how long it takes to get a bag from any aircraft stand to any point where you pick it up. And we can average that over a serious period of time. So if we can do that historically, we can start to predict that into the future. Based on the current conditions of the airport, we should be able to give you and exact time that your bag's going to arrive on that carousel. Maybe it will be down to a few seconds, maybe it'll be in the next 30 seconds your bag will arrive, type of message, but we want to give you that message to your phone. >> Think how nice that would be, Dave, if you're waiting at the baggage carousel, with another 150 of your best friends, and everybody's crowding around, watching for their bag to come out, but you know your bags about to come out in 20 seconds. >> Well, I always say it's one of my pet peeves everybody crowds around, and you can't see. Take three steps back and we'll all be better off. I wanted to ask you Michael, though, as a consumer of airline products and services, there seems to be a difference between the airport and the airline in terms of their data. You have a lot of data, the airlines obviously have a lot of data. Of course, they're competitive with each other. What kind of collaboration do you have with the airline, what kind of data do you share? >> So, I mean it really depends on the nature of your airport. Are you a hub for a big carrier, or do you have lots of small airlines all operating there, to how you might go about doing that. In both the airports that I've worked at recently, we've run projects to integrate the airline data into our systems. Cause we're just so much more well informed about what's happening and what's going to happen in the future when we do that. We spent the last couple of years working with Emirates, who's our biggest airline, to integrate their data, but we also have FlyDubai, who've got a huge flying program with us as well, and integrate their data so that we can start to combine the two data sets. And we do that within Splunk, so we know what's going on. The baggage data that I talked about, the 200 data points, I mean that comes from three different entities in reality. It's the airline at check-in, and the passengers data about their booking and everything else, the baggage system itself, and the security process it goes through, which is our data, and then the ground handler, which again is another set of data, because that bag then onto the aircraft, and inform the airline of where it is. And then that all gets combined back again at the point where you board the aircraft to make sure that that passenger and the bag are all on the same flight. So we've been pulling all that data into our systems and then sharing that back across the teams, to provide people with a lot more insight. So the airline wants to know the bags are going through successfully, the ground handler wants to know how many more they've got to come. So by sharing that data through a platform like Splunk, we're hopefully making a lot of breakthroughs. >> I think that's huge, because the mobile app is a game changer for an airline passenger. But the diversity of mobile apps, and the quality of the mobile apps is the function of the data model that each airline and their back-end processes, and you can tell some of the airlines that have sort of antiquated back-end processes, and those that don't have as much baggage, right? No pun intended. And so, my question is, with tools like Splunk and some innovation on your end, are you able to sort of unify those disparities? >> Yeah, and you've also got to remember something about the passenger, right? No passenger comes to an airport for an airport tour. They're coming because their going to fly somewhere, right? (laughs) And this is important. So they book a ticket to an airline, we might be able to integrate that data from all these different organizations at the airport, but who are you as the passenger really going to get that information from at the last moment? Probably from the airline because you're going to use their app, because you bought your ticket through it, and you're going to check in through it, and you maybe have a car service booked through it. So we would rather... we could be the combiner of that data, but then pass it back to the airline to display to you as the passenger, cause that makes more sense. But what's important for the passenger is that data is consistent at every point in the journey, whether you find it out from the airport, or whether you find it out from the airline, you want it to be the same. You don't want conflicting information. So that's what we can do by deciding to join these things together, but make sure that the consumer interface is the right one for the right time. Now that wouldn't work for us with Emirates because they're so huge and they have so many passengers for us, but for some of the smaller airlines, like British Airways, Virgin Atlantic, you know they have two, three flights a day with us, it might make more sense for their passengers to use our app in that situation. So it really depends who you are and what you're flying for, but we see that there's opportunity across that space, but what would be important is that every app tells the same story and has the same data >> John: It's like uniformity, right? >> Yeah, because that gives you so much confidence as a customer if that flight screen changes at the same time that your app pushes a notification to you, and it's exactly the same data, that's a huge amount of confidence that this is all really accurate and timely, and then you get to make decisions off that. >> I was struck by the comment that you guys are out of space and I think the way you phrase it is the city grew up around the airport. You'd think Dubai, I have not been, but you'd think Dubai, planning ahead, has lots of resources, but they're subject to the whims of metropolitan growth. Your challenge then is to use efficiency to squeeze more out of that fixed space. What are you doing in that regard? I mean that's a major CIO challenge. How do you deal with that? >> Yeah, I have to admit, that was the challenge that attracted me to the role, like how do you take this airport... when I joined it was about 78 million, couple of years back, and now pushing 90, pushing 100 by the end of the decade. That was the challenge for me, and that was the focus of the CEO, he said the only way we're going to grow this business is to figure out how to do more people, or more planes, through the same space. And that's really exciting, and the only way to do that is looking cutting out the waste wherever you can. Redefining the processes in areas, and removing all of the queues and all of the bottlenecks in the airport, whether that be in the airspace, on the airfield, in the terminal buildings for the passengers, in the baggage area for the bags. You've got to remove all those bottlenecks and I think, as a passenger, queuing up just wastes time and space. If we can make sure nobody ever queues, then everybody will get through the airport faster, which means we can do more people. We can take more people through the airport. So that's really the focus, and we have an internal project that we call queue-busting and it's literally just about busting the queues, busting the lines, as you call them here, and getting rid of them, because they're the thing that creates the capacity constraint-- >> Yeah, you talk about all these sensors you have around the airport, you talk about all the data that you're gathering, billions and billions of data points, so what don't you know that wish you did, or that you hope you can, relatively soon? >> I mean one of the things, so we know, like, the queuing time, all the major touch points, and that's been fantastic and we've, in our transfer security areas, in the last two years, we've lowered transfer security queuing from over eight minutes to an average of four minutes and 47 seconds, so we're really precise on this stuff now, it's great. But what we don't know is, the people's entire journey. So, we know that you queued in a certain place for four minutes, and you might queued up at check-in for maybe 10 minutes as well, but what we don't know is how long it took you to get between those points, which route you took, what's the most efficient, how to get you to spend more money in the airport because we... that's our business model, right? So that is where we need to learn a lot more, and I think there's a lot of work going on in that space, and we're doing some trials on some cool technology to figure out how to help you find your journey, make the most efficient overall journey through the airport, not just at the key check points. And obviously give you more time to enjoy the experience, we have shops and restaurants, we've got spas and swimming pools and hotels inside our airport, which we'd love for people to use more of, and I think we can do that if we can help them plan their journey better, so, I think there's still a lot of data out there. >> Well and, when you look at your strategic planning road map, how much runway do you have? I mean, you're using efficiency to utilize your space better, drive more revenue, customer satisfaction, avoiding the huge cutbacks of building another airport, which is not going to be as convenient. How much, again no pun intended, how much runway do you have in terms of that strategic plan? >> Well based on our current expectations, predictions that we have, we're looking at this site being able to do about 120 million, maybe we can squeeze a bit more out of it, >> Decade, plus? >> Yeah, I mean there's lots of exciting things we might have to do with the airfield to try and land more planes. We do about 65 flights an hour, off our two runways. We don't have the luxury of really wide-space runways, so we may have to come with some new ideas on that front. But about 120 million we think, which would be easily the biggest airport in the world. It's helped by the enormous fleet of A380s that Emirates uses. Of course we get a lot more passengers for every flight. But that's probably about as far as we can go. But the airport was designed for 90 to 95 million, so we're already going to bust that by about 30 million. So yeah, hopefully we can extract that, and then you never know what we might be able to do. >> Great, great story. >> Hopefully go further. >> Well it's fascinating, it really was. Great job on the key note stage today and certainly wish you continued success down the road here, I think we've run out of puns. (laughter) So, I'll leave it at that, but safe travels, if you will, home, and thanks for being with us here on theCUBE. >> Michael: Thanks very much. >> Michael Ibbitson from Dubai airports. Back with more from theCUBE here in just a bit. Washington, DC coming to you live. Back with more in a bit. (upbeat techno music)