>>Fly from Barcelona, Spain. It's the cube covering Cisco live 2020s brought to you by Cisco and its ecosystem partners. >>Welcome back everyone cubes live coverage from Barcelona, Spain. We are here for Cisco live 20 twists to keeps coverage. I'm Chomper with myself. It goes to minimum. This has been four days of coverage. We got another day tomorrow. A lot of action around application developers and programmable infrastructure and really at the heart of this is hybrid cloud and multi-cloud, which is the future of where the enterprises are going. And really it's at the center of it is the suppliers, the cloud service providers. I say Cisco power. They've got two great guests and cube alumni. David cope, senior director of cloud business development, Cisco, Benjamin MacLean, EMIA chief product officer for three D S outscale. Guys, welcome back. Good to see you again. Thanks for coming. Benjamin. We talked to two years ago here I think was what the early days when we started publicly riffing on the notion of cloud service providers going to start to be really more instrumental in how enterprises will deploy and manage workloads and applications. So we were right, it turns out we were right. We >>went actually even even further than that is. Um, so now I'll scale is not only a primary care provider or now we also have a, an on prem solution. So you can uh, we can deploy all stacks, uh, on your prem with hardware, software and services. And we actually, uh, start building locally compliance, uh, stacks. So in France we actually got the second class certification for the French government and we are also working for the ITI FedRAMP certification for the U S >>great. Take a minute to give an update of the busy. You just had an acquisition, you're now part of a different company. Explain that and the relationship to the bigger company. >>So, um, I'll scale was actually founded in 2010 and we actually started to provide to be called services starting 2012, something like this. And a decile system was always one of the big customers. Um, they were actually transforming themselves from being a software vendor to a software as a service company, which is a huge move for a company this size. And we are actually supporting them going this direction and they felt that they needed, uh, to intern to have an internal support, uh, phone call services, uh, within the group so that we actually part of the family now. >>Well congratulations. But I think this trust of the larger trend, David, we talked about how cloud service right are going to be merged emerging as more of a focal point. The global system integrators are already doing it. This is a tell sign for how enterprises, large enterprises, they start to be thinking they need people to support them with multiple, their own stacks, their own in house teams supporting these new workloads. What's your thoughts on, >>well, I mean I think these guys are a great example of sort of the evolution we've seen with the cloud. I think came out of beta in 2008 or something like that. And, and since then we've seen cloud go through sort of skepticism, >>experimentation, debate about private versus public. But today I think both desires and also tools have enabled companies to start focusing just on their business and realize now they can place and manage workloads wherever their business priorities drive them, not it constraints. And so you can get the best of both worlds. You can support this agility and yeah, you can also start to manage governance and policies across these very different private and public environments. Benjamin, bring us a little bit inside your really hybrid solution. You're helping with customers. Uh, we've had many years looking at this. I've seen some providers say, Oh, we're going to help put a stack on your environment, but if you let it touch it, Oh well I need to adjust something or make a change. And then you know, if you're helping manage it, Oh wait, you're, you're out of compliance. You've done something different from an application standpoint. We have seen, I, I might have my monolith in my data center, I have microservices in the public cloud or you know, in your service provider there. It makes sense to do that. But help us understand kind of what goes where, who manages what and what's really happening for your customers. So, >>uh, we try to come in with a very simple approach where basically the perimeter of responsibility is the same everywhere you go. So whether you're on prem or into the cloud, you should see your focus on your application and your area of expertise as a company and being able to deliver to your customers. And um, so we just want to make sure that's focused for our customers. Very easy to say, okay, it's not because I'm on prem, then I need to do it jobs. I'm still need to manage the application. And um, since Oscar is actually providing both public cloud and on premise solution, we want to provide it with as much as solution isolation as possible. And that's one of the reasons why else get actually, uh, was integrated within Cisco cloud center. So we can actually live rate, uh, the governance across the board, the, the immersion 80 of of deploy, application, deployment, whatever, wherever you are. And it's exactly the same thing for the customer. You don't have to sacrifice anything because you're on frame or you want it to be out. >>What specifically about Cisco is driving that? Because you said a couple of things that caught my attention. One is you're providing a platform so the apps could work anywhere. I heard you kind of tease that that is that one of the things that Cisco is bringing to the table. What's the, what's the Cisco value there? >>For me it's um, we, I mean it's been like 40 years that this goes around and they always, uh, worked, uh, to actually bring bridges between platforms, between solutions, between companies. And I feel that the, exactly why we're actually using the solution. So it's different for each. It's not a network bridge for this one, it's more an application ratio. Uh, I would say a pipeline application bridge and that's where we actually find the value for us. Your >>thoughts real quick, go off on tangent a little bit on the operating model of cloud, cause we were riffing on this two years ago. This is now the big conversation here. Hybrid really is all about having that operating model, whether it's on public or on premises. How do you guys serving your customers when they have an app? Hey I got a dad, I just want to build my app. I don't care where it is and I have my operation gotta be seamless across. How are you implementing that? >>To be honest, I don't feel like it's like it's a, we are still, we are not there yet. I feel companies still struggle to actually uh, build an app, being able to deploy whatever the tenants they choose, whether it's going to be a to be cloud provider or an American one. They under your plan one or even a Chinese one now. And uh, all on trend. And since the stacks are always different, they always have to pay for the difference within this platform on their side. And I feel like the tools are actually helping these companies. So it's not actually the cloud providers making the Fort is usually the tools and the ecosystem around these providers are actually providing more tools and more solutions. So it's easier for the companies that actually manage the application at the end. >>David, maybe you can help us dig in a little bit to the management and the software that Cisco's uh, working on and delivering here to help with these type of environments. You know, the way I look at the world is is businesses have applications, applications run on infrastructure in the state of the industry today is you should no longer care about where that application is running. It's just infrastructure. It's in my data center. It's in somebody else's data center called the cloud. So the state of the business today is how do I create sort of a declarative model which describes my application independent of having to know the nuances of each of the end points and then be able to manage the entire life cycle from optimizing cost, performance placement and then the ongoing policy based governance. And for us, that management platform is cloud center, which is a cloud management platform. There's others in the industry that take a similar approach. But that really is where this blurring of data centers and clouds supporting any apps, uh, is, is occurring because your, what's some of the workloads that you guys work on? Give some anecdotal feedback on some of the day to day things you're working on. Is it on premise driving the action? Is that the app developers, your customers, but you have, you're serving multiple, a big company, right? >>Yeah. Um, from what I seen is, uh, we have a lot of traction on OnPrem solution because historically it's been, uh, usual stacks, which are usually lack of usability for the customers. Um, they are now used to use it to the public cloud, the features, the capabilities, the agility, and then where you'll go by, you're going back on frame. You, you, you feel like you're traveling time, bike and backwards. And that's, that's usually an issue, uh, with our solution where we don't change the level of responsibility of the customer. So it doesn't have to have a data center, people, operation people. It's still the same guys that were actually working into the public out and they are going to operate exactly the same way on prem. So that's a huge premise for this for these companies right now. Yeah. Yeah. Actually. Great. So we deployed a one like the beginning of this year to last year and it's gonna continue to grow. Uh, especially if you're a dental assistant company, uh, as a, >>I forgot to ask you as an expert then Nirvana, the Holy grail or whatever word we want to use is to have applications just completely have programmable infrastructure. That's the dev ops, you know, Holy grail, which we're getting there. Yeah. Where are we in your mind, how far do we have to go to get the app developers just coding away in the progress of innovation? What's your thoughts on where the industry is and what we're dealing with here? >>I think you can already do it. If you sacrifice a part of your freedom or your part or part of your possibility. We can find tools that actually working pretty well with each other. But once you're in, you're going to be in for at once. The issue is more always going to become a more standardized way to actually work for this company. And that means also for us providers to provide kind of assemble level of interface and the same which works. So the company, and I mean so apart from code center, like the application actually being able to work across infrastructure platforms, whatever they are, I be cloud center for the cross platform work. Yeah. So customer is one of these tools that actually kind of, uh, leverage different platforms and don't really care. And as a user, you don't really care all the difference you can deploy, whether it's going to be on VMware, on to the cloud, and you don't expect the same level of capability in terms of infrastructure. But still you still deploy exactly the same pipelines and some workloads exactly the same way. >>What do I have to think about it? Whether it's, whether it's so managing all of its operating divisions or whether it's it ops trying to manage its developers is there's this sort of natural, some usually unspoken tension where it ops wants to support the agility that developers are looking for in business units are looking for, but at the same time it ops is torn because they have to ensure governance and security and all that. So today I think with these new platforms you do a little bit of judo frankly, is you are allowed developers or operating units to use the environment or tools of choice, but you still have these new cloud management platforms that allow you to apply and enforce governance. And those policies can either be exposed to them or it can be hidden from them. You get to choose, well that's the choice is key in the policy. >>It means automation. Yes, the policies nailed down the business logic. Get automation exactly as the Holy wishes even better, which I'm psyched to see more of that. But I got to ask you guys, I stopped at your Cisco booth, your multi-cloud with this. By the way, I love the demos over there. You get all the Cisco servers, provide everything else, but you guys got a multi cloud section. Of course there's a lot of Kubernetes being discussed there. So Benjamin, I got to get your take on this because Stu and I always joke, the joke is just broke containers around it. You can do anything. You're dealing with a lot of on premises legacy and enterprise stuff Coubernetties and as service meshes come down the pike and micro services, that seems to be really a great way to deal with it. How were you looking at that? What's your vision and how, what are some of the practitioner tools that are out there? What's your view on that? >>For me, the appeal of communities for, for the customers is, uh, less, uh, a way to work than the fact that it's actually is, is a standout. So we are talking about the fact that wherever you are, you're always a, I think different APA calls a different way to educate yourself differently. Policy management. And I feel that the appeal of communities is that you can use it over any cloud platform in the world. And he's always failed to send me, they always behave the same way and he's kind of the promise. The same is that you can get with containers, but you get it on the orchestration layer of these containers. Uh, and I feel that that's why people are quite rushing into it because they feel that if it doesn't work there, then it might work somewhere else. >>So are you dealing with some of these enterprise applications? What do you guys do? >>Um, so the interest for se, so we just, we provide, uh, the control plane or the master nodes and usually customers see or manage the resources or the, the resource pool, uh, on which they're going to deploy containers in whatever we S we still manage mostly VMs and block storage. So the, the basic breaks of any, uh, infrastructure as a service provider and um, and the customers start from there and actually build on the application and they can even reuse things that have been done somewhere else. Uh, in any other cloud platform. >>David, talk about the Cisco vision here because I think you guys have been seeing this now. I used the multi-cloud is kind of a future state that's out. See everyone has multicloud now, but hybrid is where the action is and this by getting this common operating model with you've got these Kubernetes trends and things coming down the pipe with micro services that really is impacting the momentum. How do you guys see that? What's your position on this? >> I think you're right. I mean when you look at Kubernetes specifically, I think it's obviously maturing from just developer centric activities now into production. Most Kubernetes today, it has been deployed on prem or in the cloud, but now that's the foundation that's going to enable the future of hybrid workloads where I can start again. Blurring the boundaries between data centers and clouds develop on the cloud, prod on prem, develop on prem, access to service on the cloud. >>So we're just starting to see sort of these hybrid Coobernetti's workflows. And Cisco has a container platform that's native Kubernetes but we've also, it runs on prem but it's also optimized to work with public clouds that support Kubernetes. And so it really becomes a single environment, a pool of resources for the application. >> I think it sets the table nicely for the app developers, the future because end of the day students just develop your app and yeah, things go and happen. Benjamin, final question while you're here. I want to get your expert opinion on this because I want to kind of go back to our 2018 and modernized our chat a little bit around cloud service providers because I think this is still going to be the hottest area because I think you are, you're a unique, you got acquired and you're still servicing a big customer base, but you're now part of the mother I guess. Um, which is good. You got a lot of work to do, but cloud service providers will still serve as a lot of customers and this is going to be a fast growing market. What's your advice for other cloud service providers out there that are really trying to understand how do I build my infrastructure? How do I deal with the clouds? Do I just go all in on one, do I build my own? How do I serve as the on premises? What's your advice? >>I think like if your company, a main area of expertise is not it, you shouldn't actually invest, uh, in house. Its, I think nowadays we, you, we have like, and I'm not talking only about our scale, but we have like a lot of different solution, a lot of, uh, technological partners such as Cisco and NetApp, uh, that have a great solution that actually proven, uh, there is solution as ourselves. So at scale. Um, so I feel like anything that you do try to be or from the ground, uh, would have a huge advantage in terms of, of time of technology. Um, and again, for any other cloud provider. I think also we're going to see kind of the separation we're talking about in 2018 is still going to continue to exist and I think it's going to even increase where we're going to see, um, local compliance or great regulation. I actually for the past two years, uh, dramatically increased in terms of of strengths and numbers and uh, and that, and I feel like the approach of Muti local cloud as we've been pushing for the past 10 years within our scale, it makes even more sense. >>Do you see specialty clouds emerging fast or are building on say Amazon, Google or other clouds or what do you see? >>Yeah, to be honest, I even think that the, the big three in the U S are even starting to find their own place, which is not the same. And I feel we're going to see the same thing with the Chinese and reopen actors as well. >>Awesome. Benjamin's great to have you on. Great to have your insight from the field. Appreciate David. Thanks for coming on. I appreciate that insight from Cisco as well. It's the cube coverage day. Three of our four days of coverage on shofar is do men and men stay with us for more coverage from Barcelona after this short break?

>> Announcer: Live from Barcelona, Spain, it's theCUBE! Covering Cisco Live 2018. Brought to you by Cisco, Veem, and theCUBE's ecosystem partners. >> Hey everyone, welcome back to the live CUBE coverage here in Barcelona, Spain for theCUBE's coverage of Cisco Live Europe 2018, kicking off the new year with the big event. I'm John Furrier with SiliconANGLE, cohost of theCUBE. Our next two guests, Alfred Manhart is a Senior Director Channel and System Integrators for NetApp, EMEA of Europe, Middle East and Africa, and Benjamin Laplane, EMEA Chief Sales and Solutions Officer with Outscale. You guys, welcome to theCUBE. >> Thank you. >> Hi. >> Love this partner segment. NetApp, you have a customer on, partner, and you guys have an interesting relationship. Would one of you like to talk about your relationship with Outscale, and why are you guys here? >> I think engaging not only with the typical resellers and distributors is pretty key for us. We engage with service providers and cloud providers from 2012, 2013 ongoing. It's mainly to be the foundation for the services they are going to market with, and Outscale is out of France, one of our predominant service providers we engage with on a local level. >> How has the channel changed, because as the cloud service providers, and cloud creates such great agility and speed. You can get products out faster, MVPs and those things can be very specialized. How has your go-to-market changed with the cloud, accelerated it, changed the makeup, what's NetApp- >> First of all, the market is demanding it, so some of our traditional players go the services way and some service providers go the typical, traditional way so engaging and broaden up the ecosystem was pretty critical for us. Different engagement models are needed because the customers require different kind of consumption models. >> Good leverage, sales model, always a good business. Benjamin, talk about what you guys do. I want to ask you some specific questions about your business, on how you guys are advising and implementing solutions with customers, but first, take a minute to explain your business. >> Outscale is a cloud service provider. We built the company in 2010 and we've been providing public cloud solution for worldwide, so implementing in the U.S., in Europe, and in Asia for the past five years now. The objective is to be able to provide sovereignty and reliable cloud solutions for our customers worldwide. It's based on NetApp and Cisco FlexPod architecture. >> So you guys actually have a cloud yourselves? >> Yeah, exactly. >> And you bring that to customers? >> Yeah for the past five years, what we've been doing is developing our own orchestration layer that allow us to actually use the whole FlexPod architecture to provide infrastructure as a service for our customers. What we've been doing for the past year is actually package all the technology that we've been developing for the past years into a unique solution, which is TINA On-Prem, which is a private cloud solution ready to be deployed wherever you need to. >> I'll get back to the FlexPod in a minute, but I want to drill down on this notion of serving the customers, because there's a thirst for customization and specialization, whether it's an application, or some regional challenge on the data, certainly you see that with GDPR, it's coming down like a freight train, like a ton of bricks on everybody. So there's design challenges that are now upon the customers. How are you guys bringing the customers' solutions to them? Is it rapid engagements, is it ongoing? What's your relationship with your customers? >> So if we talk specifically about GDPR, but I think it's true for most regulation that comes out, Outscale had the chance to be able to develop their software with security design first. That means that it's designed for security, but also for privacy, so that's kind of give us the edge when talking about regulation enforcement and also all the process that we put in place around infrastructure management that allows for us to provide the best services for our customer, always aligned with the regulation that comes out. >> What are the biggest challenges your customers face with the cloud? >> I think most of them, so things improved a lot for the past years, but the first thing was everyone wanted to do it because that was kind of the name, the thing that you want to go into, now it's more big data or AI. The idea behind this is a company knows that the cloud is not an option, they will go to the cloud, the question is how, and why and when and how. So we try to help all these companies to decide what's the best for public cloud or private cloud. >> Alfred and Benjamin, I want you guys both to answer this next question. We've been observing and reporting on theCUBE, and certainly Cisco's validated it, that everyone kind of has some cloud thing going on. Yeah I put an app in there, it might be low-hanging fruit, test dev, or something non-critical, but all the work and energy and money being spent is kind of getting their act together on-premise, because they got to get cloud operations going, move from the old operating model to cloud-ready on-premises, and then do some hybrid cloud. Do you guys see it the same way, and if so, what specifically are they doing on, is it DevOps, is it pure operational, what are your thoughts? Start with Benjamin. >> So from where I stand, what I can see is we've seen companies for the past year that went full public cloud, and then other company that always stay back and say, no, we won't go to the cloud and we kind of things going into a balance point where basically all companies now realize that they need to have a part of their infrastructure, such as private cloud, for security, politics, regulation sometimes. The other places to decide what's going to be the perimeter, they going to be allowed to put into the public cloud. That's why now we are more talking about hybrid between public and private cloud, and that's one of the first major design of the solution that we developed. >> Are you saying that you're seeing some customers move completely from on-premises to cloud, full migrations? >> No, I think what I've seen is people that have, so the cloud was not made for them, finally decided that maybe it could have been useful for some of their operations, so I don't think it's always like an all-in move. You need to decide where's it's going to be good, depending on the perimeter, the context, the data, the cre-dee-city of the data. >> Alfred, on-premise activity. >> Heavy on the one side. (laughing) On the other side, I think you talked about test dev. A lot of people play around with test dev, this is mainly on a local level, behind the scenes, but if it then goes to backup or a disaster recovery, it goes up the productive stack. They are more interested if it's really going well, if the data resides in their country, if all the legislations are held. We currently see getting out of the test dev, and on the other side we of course see a trend that the customers are forced by the software Windows to go to the cloud. So Microsoft is going cloud. SAP is also going cloud, so it's not only a market trend, it's also a trend from the software end that they are forced to do something, and they want to keep control of their data. That's why data's a little bit different from going to the cloud, it's computing with the apps. >> Data's a huge issue. So how are you guys using NetApp? Talk about the FlexPod, you mentioned that earlier. >> Outscale, we've been using NetApp for the past six years, something like that, which is a pretty long time compared to the lifetime of a company. The thing as far as the most important thing was to be able to provide the bridge services for our customers. Even if we abstract some of the features, some of the value of the NetApp that we buy, we just keep the value for ourself to be able to deliver more services, more value to the end customer. That's how we've been doing things. The second thing is also when you want to deploy private, on-prem solution, it's always better and it's more reassuring for the customer when you use and you partner with one of the leaders on the market, such as NetApp. >> So when I hear people use the term enterprise class architecture, what does that mean? Does that mean certain maybe arrays? Is it configuration, is it network? What is enterprise class architecture mean to you? >> For me it's two things. So the first thing you have the architecture, and you also have the hardware that you're going to use to apply to this architecture. The thing is, I was talking about reliability. I think that's one of the major things is how much maintenance is it going to require, how it's going to impact your permissions for the user or for the end customer, and when you see the architecture that we've deployed, it's everything is redundant, it's not fail-safe, it's failure-proof, which is even better because that means that you know things are going to fail at some point, and you can't even allow yourself to have a failure where you can't serve the service to your customer. >> What's the biggest thing that you've learned in doing the cloud migration, cloud service provider, with customers over the past two years? What's the big aha moment that you've had? >> I think that's when you realize that even if you have some pattern that you can recognize for a specific customer, or for a certain type of customer, you have no magic recipe. That means that you always need to take a step back, look at the problem of your customers and try to think what's the best for my customer, and how can I bring the right services to him so he can add value to his market and his business? >> Alfred, you mentioned regulation, so the question to Benjamin is how does the role of storage play in a world where data and sovereignty issues come into play? Does it change the strategy? What's goes on for the folks that are really trying to solve this problem? >> I think we see more and more movement where basically even the customer want more managed services. I think it's always important to give the customer the hands so he can do whatever he want with his data. We are here to support him, to give him the best advices, the best practices about data management, but at the end is he accountable and responsible for these data. So at the end I think it's just we need to give the right tools to our customers so they do exactly what they want to do with the data and they don't have hidden policies apply to their own data. For example, replication of your data for safety measures. Maybe they don't want it to be replicated abroad, they want it to stay on the territory, so that's kind of a thing that you need to rethink about and give the right tools to your customers. >> Alfred, what are the top use cases that you guys have seen at NetApp for cloud services providers, and just in general the partners, because they're on the front lines serving customers. They need to have low cost, high performance gear, great software, we heard reliability. What are the use cases now that you're seeing? Are they broader use cases, are they more narrow? What's your- >> So of course, when you come from a storage perspective, you mainly aim for the infrastructure and for the storage-related services, which we are not where we are stopping, because we are working with Cisco on this validated designs going up the stack, so if you are not going up the stack regarding different workloads, going after the IOT, going after the analytics, going after the application layer, we will fail. So having a fair balance of partner that can offer the services from bottom to the top, that's very important. Of course, use cases like intelligent business analytics, going after SAP, going after SAP HANA, going after Microsoft, this is obvious that the partners and the customers are going that way. >> Benjamin, talk about what it's like working with NetApp. You happy with them? Some things that they've done that you think other suppliers should adopt? What's the mode of support from NetApp, what's the overall experience like? >> I think I would describe it as a strong partnerships. They are our exclusive partner for the storage as Cisco can be on the other brinks of technology that we are using. We have a strong relationship, we have a booth on the on-stand today so that's one of the reason why we're here. We also pushing with them with the whole, we were talking about analytics, we are talking talking about big data also. We have a lot of use cases, pretty amazing use case in resales in Europe, and also we give them a lot of feedback about how we use the hardware, what could be improved, and I think that's the kind of communication that makes a strong partnerships and bring value to both sides. >> NetApp's a very engineering-oriented company, I know them very well living in Silicon Valley, so I give 'em props for that. Question for you is when you hear someone say data-driven storage, or data-driven analytics, what does that mean to you as a partner of a storage supplier? >> For us, it's another way to look at the way we're going to provide service to our customers in the years to come. I think that customers is going to expect more and more services, more and more value, from the service that we're going to provide them, whether it's going to be storage, computer network, or even security. I think that's always a good thing for us to have more tools to build new technology for tomorrow. >> Great, and NetApp's channels and partners, what's the message from NetApp these days to the partners? You're enabling them, obviously you help them make money obviously, but- >> I think the biggest challenge is that we drive the ecosystem in the right direction. If we just stick to the traditional players, we will not be successful, so we have to expand the ecosystem. Going up to different player that are currently probably not in our radar, going up to ISVs that help us to really embrace the data from a value perspective, so our biggest, let's say, message to the channel is don't stay where you currently are, develop the channel with ourself. >> And certainly the relationship with Cisco is blooming for NetApp. >> It is, it's probably since six years, we have now around 8,700 joint customers. We go up the stack, we talk about strategic engagements on a IT SP perspective, so it's going in the right direction. Very important. >> As your competitors get distracted, and do things or doing things, you guys eating their lunch? Is that, (laughs) you smiling? >> Eating their lunch is probably not the word. >> Maybe a little croissant. Breakfast, or was it dinner, what's going on? Are you eating the breakfast, lunch, or dinner of the competitors? >> Currently I would say in French, I think we are jointly engaging on a croissant perspective. (laughing) So we're heading in the right way. So these partnerships are very important. >> It's always a great, fun time. It's been fun watching the storage, been watching NetApp for many years, I remember when they went public back in the dot com A days, they still keep their roots. Great to see you having some great success. Congratulations on a great partnership. It's theCUBE live coverage, here with NetApp and their partner inside theCUBE here at Barcelona at Cisco Live 2018 in Europe. I'm John Furrier. We'll be back with more live coverage after this short break. (digital music)

>> live from the Mandalay Bay Convention Center in Las Vegas. It's the king covering via World 2016 brought to you by IBM Wear and its ecosystem sponsors. Now here's your host stool minimum, >> including I Welcome back to the Q bomb stew. Minuteman here with my co host for this segment, Mark Farley, and we'll get the emerald 2016 here in Las Vegas. It's been five years since we've been in Vegas, and a lot of changes in five years back Elsa do this morning was talking about five years from now. They expect that to be kind of a crossover between public Cloud becomes majority from our research. We think that flash, you know, capacities. You know, you really are outstripping, You know, traditional hard disk drives within five years from now. So the two guests I have for this program, Brian Vials, is the CEO of Day Tree. Um, it's been a year since we had you on when you came out of stealth on really excited cause your customer along. We love having customers on down from Alaska, you know, within sight view of of of Russia. Maybe on Did you know Ben Craig, who's the c i O of Northern Bank. Thank you so much for coming. All right, so we want to talk a lot to you, but real quick. Ryan, why do you give us kind of the update on the company? What's happened in the last year where you are with the product in customer deployments? >> Sure. Last year, when we talked, daydream was just coming out of stealth mode. So we were introducing the notion of what we're doing. Starting in kind of mid Q. One of this year, we started shipping and deploying. Thankfully, one of our first customers was Ben. And, uh, you know, our our model of, ah, sort of convergence is different from anything else that you'll see a v m world. I think hearing Ben tell about his experience in deployment philosophy. What changed for him is probably the best way to understand what we do. >> All right, so and great leading. Start with first. Can you tell us a little bit about north from bank? How many locations you have your role there. How long you've been there? Kind of a quick synopsis. >> Sure. Where we're growing. Bank one of three publicly traded publicly held companies in the state of Alaska. We recently acquired residential mortgage after acquiring the last Pacific Bank. And so we have locations all the way from Fairbanks, Alaska, where it gets down to negative 50 negative, 60 below Fahrenheit down to Bellevue, Washington. And to be perfectly candid, what's helped propel some of that growth has been our virtual infrastructure and our virtual desktop infrastructure, which is predicated on us being able to grow our storage, which kind of ties directly into what we've got going on with a tree and >> that that that's great. Can you talk to you know what we're using before what led you to day tree? Um, you know, going with the startup is you know, it's a little risky, right? I thought, Cee Io's you buy on risk >> Well, and as a very conservative bank that serves a commercial market, risk is not something that way by into a lot. But it's also what propels some of our best customers to grow with us. And in this case, way had a lot of faith in the people that joined the company. From an early start, I personally knew a lot of the team from sales from engineering from leadership on That got us interested. Once we kind of got the hook way learned about the technology and found out that it was really the I dare say we're unicorn of storage that we've been looking for. And the reason is because way came from a ray based systems and we have the same revolution that a lot of customers did. We started out with a nice, cosy, equal logic system. We evolved into a nimble solution the hybrid era, if you will, of a raise. And we found that as we grew, we ran into scalability problems. A soon as we started tackling beady eye, we found that we immediately needed to segregate our workloads. Obviously, because servers and production beauty, I have a completely different read right profile. As we started looking at some of the limitations as we grew our video structure, we had to consider upgrading all our processors, all of our solid state drives, all of the things that helped make that hybrid array support our VD infrastructure, and it's costly. And so we did that once and then we grew again because maybe I was so darn popular. within our organization. At that time, we kind of caught wind of what was going on with the atrium, and it totally turned the paradigm on top of its head for what we were looking for. >> How did it? Well, I just heard that up, sir. How did the date Reum solution impact the or what did you talk about? The reed, Right balance? What was it about the day trim solution that solved what was the reed right? Balance you there for the >> young when we ran out of capacity with our equal logic, we had to go out and buy a whole new member when he ran out of capacity with are nimble, had to go out and buy a whole new controller. When we run out of capacity with day tree, um, solution, we literally could go out and get commoditized solid state drives one more into our local storage and end up literally impacting our performance by a magnifier. That's huge. So the big difference between day trim and these >> are >> my words I'm probably gonna screw this up, Bryant, So feel free to jump in, and in my opinion day trip starts out with a really good storage area network appliance, and then they basically take away all of you. I interface to it and stick it out on the network for durable rights. Then they move all of the logic, all of the compression, all of the D duplication. Even the raid calculations on to software that I call a hyper driver that runs the hyper visor level on each host. So instead of being bound by the controller doing all the heavy lifting, you now have it being done by a few extra processors, a few extra big of memory out on their servers. That puts the data as close as humanly possible, which is what hyper converging. But it also has this very durable back end that ensures that your rights are protected. So instead of having to span my storage across all of my hosts, I still have all the best parts of a durable sand on all the best parts of high performance. By bringing that that data closer to where the host. So that's why Atrium enabled us to be able to grow our VD I infrastructure literally overnight. Whenever we ran out of performance, we just pop in another drive and go and the performances is insane. We just finished writing a 72 page white paper for VM, where we did our own benchmarking. Um, using my OMETER sprayers could be using our secondary data center Resource is because they were, frankly, somewhat stagnant, and we knew that we'd be able to get with most level test impossible. And we found that we were getting insane amounts of performance, insane amounts of compression. And by that I can quantify we're getting 132,000 I ops at a little bit over a gig a sec running with two 0.94 milliseconds of late and see that's huge. And one of the things that we always used to compare when it came to performance was I ops and throughput. Whenever we talk to any storage vendor, they're always comparing. But we never talked about lately because Leighton See was really network bound and their storage bender could do anything about that. But by bringing the the brain's closer to the hosts, it solves that problem. And so now our latent C that was like a 25 minutes seconds using a completely unused, nimble storage sand was 2.94 milliseconds. What that translated into was about re X performance increase. So when we went from equal logic to nimble, we saw a multiplier. There we went from nimble toed D atrium. We saw three Export Supplier, and that translated directly into me being able to send our night processors home earlier. Which means less FT. Larger maintenance window times, faster performance for all of our branches. So it went on for a little bit there. But that's what daydreams done for us, >> right? And just to just to amplify that part of the the approached atrium Staking is to assume that host memory of some kind or another flash for now is going to become so big and so cheap that reads will just never leave the host at some point. And we're trying to make that point today. So we've increased our host density, for example, since last year, flash to 16 terabytes per host. Raw within line di Dupin compression. That could be 50 a 100 terabytes. So we have customers doing fairly big data warehouse operations where the reeds never leave the host. It's all host Flash Leighton see and they can go from an eight hour job to, ah, one hour job. It's, you know, and in our model, we sell a system that includes a protected repositories where the rights go. That's on a 10 big network. You buy hosts that have flash that you provisions from your server vendor? Um, we don't charge extra for the software that we load on the host. That does all the heavy lifting. It does the raid compression d do cloning. What have you It does all the local cashing. So we encourage people to put as much flash and as many hosts as possible against that repositories, and we make it financially attractive to do that. >> So how is the storage provisioned? Is it a They're not ones. How? >> So It all shows up, and this is one of the other big parts that is awesome for us. It shows up his one gigantic NFS datastore. Now it doesn't actually use NFS. Itjust presents that way to be anywhere. But previously we had about 34 different volumes. And like everybody else on the planet who thin provisions, we had to leave a buffer zone because we'd have developers that would put a bm where snapshot on something patches. Then forget about it, Philip. The volume bring the volume off lying panic ensues. So you imagine that 30 to 40% of buffer space times each one of those different volumes. Now we have one gigantic volume and each VM has its performance and all of its protection managed individually at the bm level. And that's huge because no longer do you have to set protection performance of the volume level. You can set it right in the B m. Um, >> so you don't even see storage. >> You don't ever have to log into the appliance that all you >> do serve earless storage lists. Rather, this is what we're having. It's >> all through the place. >> And because because all the rights go off, host the rights, don't interrupt each other the host on interrupt together. So we actually going to a lot of links to make sure that happens. So there's an isolation host, a host. That means if you want a provisional particular host for a particular set of demands, you can you could have VD I next door to data warehouse and you know the level of intensity doesn't matter to each other. So it's very specifically enforceable by host configuration or by managing the VM itself. Justus, you would do with the M where >> it gets a lot more flexibility than we would typically get with a hyper converge solution that has a very static growth and performance requirements. >> So when you talk about hyper convergence, the you know, number one, number two and number three things that we usually talk about is, you know, simplicity. So you're a pretty technical guy. You obviously understand this. Well, can you speak to beyond the, you know, kind of ecological nimble and how you scale that house kind of the day's your experience. How's the ongoing, how much you after, you know, test and tweak and adjust things? And how much is it? Just work? >> Well, this is one of the reasons that we went with the atrium is well, you know, when it comes down to it with a hyper converge solution, you're spanning all of your storage across your host, right? We're trying to make use of those. Resource is, but we just recently had one of our server's down because it had a problem with his bios for a little over 10 days. Troubleshooting it. It just doesn't want to stay up. If we're in a full hyper converged infrastructure and that was part of the cluster, that means that our data would've had to been migrated off of that hostess. Well, which is kind of a big deal. I love the idea of having a rock solid, purpose built, highly available device that make sure that my rights are there for me, but allows me to have the elastic configuration that I need on my host to be able to grow them as I see fit. And also to be able to work directly with my vendors to get the pricing points that I need for each. My resource is so our Oracle Servers Exchange Server sequel servers. We could put in some envy Emmy drives. It'll screen like a scalded dog, and for all of our file print servers, I t monitoring servers. We can go with Cem Samsung 8 50 e b o. Drives pop him in a couple of empty days, and we're still able to crank out the number of I ops that we need to be able. Thio appreciate between those at a very low cost point, but with a maximum amount of protection on that data. So that was a big song. Points >> are using both envy. Emmy and Block. >> We actually going through a server? Refresh. Right now, it's all part of the white paper that way. Just felt we decided to go with Internal in Vienna drives to start with two two terabyte internal PC cards. And then we have 2.5 inch in Vienna ready on the front load. But we also plumbed it to be able to use solid state drive so that we have that flexibility in the future to be able to use those servers as we see fit. So again, very elastic architecture and allows us to be kind of a control of what performance is assigned to each individual host. >> So what APS beyond VD? I Do you expect to use this for? Are you already deploying it further? >> VD I is our biggest consumer of resource is our users have come to expect that instant access to all of their applications eventually way have the ability to move the entire data center onto the day trim and so One of the things that we're currently completing this year is the rollout of beady eye to the remaining 40% of our branches. 60% of them are already running through the eye. And then after that, we're probably gonna end up taking our core servers and migrating them off and kind of through attrition, using some of our older array based technology for testing death. All >> right, so I can't let you go without asking you a bit. Just you're in a relationship with GM Ware House Veum. We're meeting your needs. Is there anything from GM wear or the storage ecosystem around them that would kind of make your job easier? >> Yes. If they got rid of the the Sphere Web client, that would be great. I am not a fan of the V Sphere Web client at all, and I wish they'd bring back the C Sharp client like to get that on the record because I tried to every single chance I could get. No, the truth is the integration between the day tree, um and being where is it's super tight. It's something I don't have to think about. It makes it easy for me to be able to do my job at the end of the day. That's what we're looking for. So I think the biggest focus that a lot of the constituents that air the Anchorage being where user group leader of said group are looking for stability and product releases and trying to make sure that there's more attention given to que es on some of the recent updates that they have. Hyper visor Weber >> Brian, I'll give you the final word takeaways that you want people to know about your company, your customers coming out. >> Of'em World. We're thrilled to be here for the second year, thrilled to be here with Ben. It's a It's a great, you know, exciting period for us. As a vendor, we're just moving into sort of nationwide deployment. So check us out of here at the show. If you're not, check us out on the Web. There's a lot of exciting things happening in convergence in general and atriums leading the way in a couple of interesting ways. All >> right, Brian and Ben, thank you so much for joining us. You know, I don't think we've done a cube segment in Alaska yet. so maybe we'll have to talk to you off camera about that. Recommended. All right. We'll be back with lots more coverage here from the emerald 2016. Thanks for watching the Cube. >> You're good at this. >> Oh, you're good.

>>Mhm Yes. Hello and welcome back to the cube coverage of red hat summit 2021 Virtual. I'm john furrier host of the Q. We've got a great lineup here. We've got two great guests just bad padan, E. S. V. P. Of cloud platforms at red hat and Tracy ranking VP of open shift engineering at Red Hat folks. Thanks for coming on. Good to see. You got some big news, you guys have made some acquisitions. Uh stack rocks you guys bought into red hat was a really big deal. People want to know, what's the story? How's it going? What's the uptake? What's the integration, how's it going? >>Right, thanks john, thanks for having us on. Um so yeah, we're really excited with stack rocks acquisition being the team on board. Uh Well, the first thing to note before even why we did it uh was for for you and and then the beers have been following us closely. This is our first acquisition as red Hat being part of IBM. So, so, so quite big for us from that perspective as well. Right? Continue to maintain our independence um within uh IBM uh and I really appreciate that way of working together. Um but saying all of that aside, you know, as a company have always been focused on ensuring that were direct enterprise capabilities to just sort of doing that for two decades. With with Lennox, security has always been a big part of our story, right, ensuring that, you know, we're finding cbs updating uh and sending out patches to our customers and doing that in a reliable fashion running mission critical applications. We applied that same if you will um security mindset on the community side with the open ship platform. Um we've invested insecurity ourselves organically, right, you know, uh in various areas and making it more secure, all right, can't run containers uh as Root by default, uh investing in things like role based access control and so on. And we really felt like we want to deepen our commitment to security. Uh and so, you know, in conversations with stack rocks, we found just a great fit, just a great team building a really interesting approach to community security, right? You know, very declared of approach to it. Uh you know, focus on a vision around this notion of shift left. But you've probably been hearing from that because we're a little bit right. Which is this uh idea that, you know, we're in the world moving from devops to death setups. Uh and the approach that sack rocks were saying, so great team, great product, really great vision with regard to kind of weather going forward and finding a nice alignment between, you know what, you know, they've been thinking about the value that we want to bring >>Yeah, I want to dig into the depths cops, piece of it. But you brought up the IBM acquisition as part of now Red Hat bought IBM you know it's just you remember back in 2019 I interviewed Arvin on the cube when he was at IBM you guys were still independent and he had a smile on his face. He is pro cloud, he is all about cloud Native and even that interview I had no idea what was going on behind the scenes but I was kind of drilling him on some of the things that were important at that time which are now certainly relevant today which is cloud Native, Agile development Programmable infrastructure. I don't think we touched on security that much was kind of inherent in the conversation. He was like all smiling, he loves the cloud Native and and this is where it comes into the relevant, I have to ask you, what was it like to get this through? IBM where they're like girl green light or was it, was it different? What was different about this acquisition? >>John great, great question for you to ask. And you know, I will say that, uh, you know, everyone's heard the stories they're telling us. They get, you know, part of IBM, you know, it's definitely working on red hat jOHn the cube we've talked to you and several of your colleagues about that. Um, the great thing has been that, look, the redhead way of working, uh, are still pushing forward with regard to our commitment to open source, uh, and our culture, you know, is still the way it is. And I have to give huge credit not just to urban and his and his team, but definitely to orbit right. He's always champion, He's champion rather acquisition. He's champion kind of, you know, the independence that we've had and he takes very, very firm stance around it. Um, and look, IBM uh, story company uh, in the United States and really in the world, um, they have, there was working and you know, for redhead, they've kind of said, look, we'll give you a pass path, right? So, uh, getting the acquisition through, if you will, diarrhea processes, um, really was, was hugely supported by, you know, from mormon, but all the way down. Russian strategic >>strategic bet with the dollars involved trace, they want to get you in this because, you know, one of the things about shift left and getting security built in by default, which has always been part of red hat, that's never been an issue. It just extends as developers want to have native security built in. There's a technology angle to this as well. So, um, obviously cloud native is super important. What investments are you guys making with this acquisition and how does that translate to customer benefits? >>Yeah, I mean the one thing that is really important about the stock rocks acquisition and kind of, you know, key for us is, you know, this was a cube native solution and I think that's really, you know, was important piece as to why stock rocks might have been, you know, was a great fit for us. Um, and so you know, what we've been trying to do in the short time that that team has been on board with us is really, you know, taken a deep look and understanding where are the intersection points of some of the things that we have been trying to focus on, you know, just with inside of, you know, open shift in red hat in general and where do they have bring the additional value. Um, and really trying to make sure that when we create this solution and ultimately it is a solution that's cohesive across the board. Um, we don't add confusion too. You know what, some of the things that maybe we already do this team knows, you know, how to they know their customer base. They really know what the customers are looking for. And we are just trying to absorb, I would say so much of this information uh as we are trying to, you know, create what the right road map will be uh for stack rocks from a long term and infrared had ultimately in the security space. I mean, as the chef said, I mean we are red hats known for being, you know, security mind focus built on top of realm, you know, uh the leader and so we want to make sure that what we've got that actually serves, you know, the developers being able to not just secure the environment and the platform, but also the workloads, customers need that security from us. Um and build it in so that we have, you know, into the cube native >>controls. >>So stack rocks was known for reinventing and security enterprise security with cloud native. How is it complimentary? How does it fit in? Can you guys just quickly talk to that point because um like you said, you guys had security but as kubernetes and containers in general continue to rise up and and kubernetes continue to become a hybrid cloud kind of linchpin for applications. Um where's the synergy? Where's where does this connect? And what are some of the uh the part of the areas where it's it's fitting in nicely or or any overlaps that you can talk about as well? >>Yeah, I can start and then maybe Tracy if you want to add to that securities of it's a wide space. Right? So, you know, just saying security is like, well, you know what security you're talking about, you're talking about, you know, and use the security, like what your desktop are you talking about? You know, intrusion prevention? I mean, it's a huge, huge, you know, space. Uh you know, many companies devoted to the entire spectrum, you know, self has a very robust security business. We're very focused on uniting Tracy. Was talking about this, the Kubernetes Native security part of this. Right. You know, do we have the appropriate runtime uh, controls in place? Uh You know, our policies configured appropriately Well, if they're in one cluster, are they being applied consistently across, you know, every cluster? How do we make sure that, you know, we make security the domain, not just of the operators but also uh in in uh make it easier for it to be adopted at development time. So, you know, there's a, there's a, if you will, a very sort of uh a lot of surface area for security, we're trying to really think about the pieces that are most relevant for our enterprise customers and the ones that are deploying it at scale. And I'm sure we can build on it. Having said that, john what I do want to add also is that because expands even of Cuban any security is so large, there is a lot of room for our partners to play. Right? And so before you asked me that question, I want to say that there is space. Right? So you know, I've had conversations with you know, all the other folks in the cloud native security space. We know them well, we've been working with them over the years and we could do to look forward to ensure that they're building over and above the foundation of Berlin. >>So plenty of beachhead, what you're saying from a, from a security sample, you guys hit the table stakes added into the product, but there's so much surface area going on with this hybrid cloud and soon to be multi cloud that you're saying this room for partners to play. >>Exactly, right, >>okay. Tracy quick under the hood, you know, actually shift left. That's kind of the mindset for developers who are writing modern applications might not want to get under the hood, who just wanted all the program ability of security and not have to come back to it. I mean that seems to be the complaint that I hear. It's like okay I gotta come back and do a security, more security work. I just wrote the code that was last week or yesterday and that seems to be the developer productivity. Then there's also under the hood devops what how does this all fit? >>Yeah, so it's uh let's take a take a step back and this is how I kind of like to think about it. So we are trying to look at, you know, how do we just enable in some of the C. I. C. D. The tooling that we have? How do we actually take and enable some of the technology that was already available in stock rocks today and actually put it into those tools. Because if we can make it easy for you to not just develop your application and, you know, integrated in with what you're, the tooling is that you're trying to use for the entire life cycle of developing your application. It then becomes exactly what you didn't say, you know, what they're doing now is it's an after thought. We don't need it to be an afterthought. Um and I think, you know, we're seeing the changing from a customer mindset where um they're become customers are becoming a lot more aware of these things. So if we actually get this into, you know, some of the Argo and the ci cd pipe pipeline work, then it just becomes something natural and not a secondary thought because actually when it's a secondary thought, uh we have exposures and that's not what a customer wants when they're creating, you know, creating these workloads, they're trying to rapidly create the workloads, so we need to make it um to have those integration points in as quickly >>as possible. >>Totally nailed. I mean there's productivity issues and there's also the top line which is security. Great stuff. Congratulations on that acquisition. Security continues to be built in from the beginning. That's what people want. They want productivity want want security, great stuff, Great acquisition. Congratulations. Um Next next segment I want to get into is uh open shifts around telemetry. Tell us about telemetry for open shift. What is this about? >>Yeah, another big interesting topic for us. So over a year ago we released open Ship for and you know, we learned a lot of lessons, you know, shipping open ship three up and over the years and really getting feedback from hundreds of customers around the globe. One of the things obviously we heard from a lot was you know, make install the upgrade experience better. Right. But you know, we were thinking about how can we take that forward to the next level, which is is there a way for us to say, you know, let these clusters they connected up so we can get a better sense of cluster help and help with remote health monitoring will be able to proactively provide information back to our customers around, let's say, you know, if applications are healthy clusters healthy and how they're running and how we can help them um could figure them if they're not. Um And so that led us to introducing uh inflammatory remote health monitoring directly into open ship for as a value that we can provide to customers. Um And what that really starts doing is starts bringing this notion of a public cloud, like experience to customers with clusters run across the hybrid cloud. Right? So you have the expectation that, you know, your clusters are monitored and watched over in the public cloud and we want to make sure we can provide that to customers regardless of, you know, where they're running in. So, so that's just >>a quick question on that insights for open shit. That's what you're getting to. Is that on premise? And in the cloud? So it's hybrid environment, is that correct? >>Exactly. Right. So, the insights for open ship is all about that, Right? So how can be proactively, you know, uh identify risk helped remediated? How can we uh do things like, for example, give you recommendations, cost optimization, right insights around around around that. Uh and to your point, right? The goal is to make it completely hybrid. So, it's obviously a new area right for customers want Leslie used to that, you know, in an on premise environment, they're used to that in a public cloud or cloud native environment. And we're trying to make sure we bring that consistently across to our customers, you know, regardless of where they're running apart. >>Tracy. Talk about the the developer productivity involved because if you have telemetry and you have insight into what's going on in the infrastructure and the data, what's going on the application, you can be more proactive, You don't have to get pulled into these rabbit holes of troubleshooting. Oh, is a trace over here or something going on over here. Are clusters going down or should I could have caught that there's a lot of, you know, good intentions with with the code and then all of a sudden new code gets pushed and then also that triggers this to go off and you have all these kind of dependencies, day two operations, many people call this kind of that phenomenon where everything looks good and then you start pushing more stuff more code and then the cluster goes down and then it's like wait, that could have been avoided. That was a dumb error, we could have fixed that this is kind of the basic what I call human software error kind of stuff that's not intended. The telemetry help this area. >>Yeah, it does. And actually one point that even to take it further, that I think it's important is our customers can learn from each other not even having to talk to each other, which is the beauty of what telemetry is and what redhead insights, rope and shift is. You know, what we have been able to see is you know, there are certain characteristics that happen even across, you know, certain groups of customers but they don't know that they don't talk to each other, but the telemetry is giving us a night into what some of those patterns are. And so when a customer in one site starts to have, we start to see telemetry, you know, you know, maybe a. T. D. Is going down for a certain reason and and we can determine that we then have the ability to take that telemetry and you know, be able to send alerts back to all the other customers and say, hey we recognize this might be becoming an issue, You know, here's how you might re mediate it or hey we've already put a fix out for this issue that we're starting to see you having an issue, you should probably take action on. So it's an increasing the the efficiency of customers without them necessarily having to, you know, constantly be understanding, monitoring, you know, watching everything like they had had to do from of the three perspective, we're now giving them some of the insights of what we know as developers back to them, >>you know, that's interesting. I think that's really key because it's talking to a friend last night we just talked about cybersecurity and we're talking about how a lot of these things are patterns that have that are the same and people just don't talk to each other. There's no shared insights. I think this is an interesting dynamic where you can get the collective intelligence of other patterns and then share that. So the question that I mean that's that's a game changer in my opinion. So that's awesome. The question I have is can you guys push alerts and recommendations to the customers? So from this data? So how does that work? Is that built into the product? Can I get some proactive notifications and saying, hey, you know, your cluster might go down and we've seen this before, we've seen this movie. I mean she is that built in. >>Yeah, so john you're keeping it exactly where we're taking this, right? And I think Tracy started putting out some breadcrumbs for you there. So uh, first get comfortable with the foundation was laid out, get clusters connected right. Then information starts going, reported, we start getting exactly to what you said, john write a set of patterns that we can see Tracy, start talking about what we can, if we see pattern on one end, we can go off and help customers on other end. Now, if you take this forward interest for your viewers today, um introduce a I you know, into this, right? And then we can start almost starting to proactive now of saying, look, you know, following actions are going to be committed or we expect them to be committed. You know, here's what the outcome is a result of that. Here's what we recommend for you to do, right? So start proactive remediation along that. So that is exactly, you know, the surface that we're trying to lay down here and I think this is a huge, >>huge game changer. Well, great stuff, want to move on the next we're getting go on for hours on that one topic. I think telemetry is a super important trend. Uh you guys are on top of a great, great job to bring in the Ai piece. I think that's super cool. Let's get back to the end of blocking and tackling Tracy. You know, one of the things that we're seeing with devops as it goes mainstream now, you've got def sec apps in there too, is you've got the infrastructure and you've got the modern application development, modern application developers, just wanna code, be productive, all that security shifting left, everyone's all happy that things are going great under the hood. You have a whole set of developers working on infrastructure. The end of the customers don't want to manage their own infrastructure. How is red hat focused on these two groups? Because you got this SRE like cloud Ops persona developing in the enterprise and you got the developers, it's kind of like almost two worlds coming together, how you, how you helping customers, you know, control their infrastructure and manage it better. >>Yeah, so great question. And you know, this really plays to the strength of what, you know, we have been trying to champion here at red hat for for many years now around the hybrid cloud and this, you know, hopefully everybody's recently heard about the announcement we've made with our new offering Rosa in partnership with amazon. Um you know, we've got different offerings that enables customers to really focus, as you mentioned on the key aspects that they are concerned about, which is how do they drive their businesses, how do they create their applications, their workloads that they need to and offload, you know, the need for having to understand all of the I. T. Infrastructure that's underneath. Um We want to red hat to reduce the operational complexity that customers are having um and give them the ability to really focus on what's important for them. Um how can they be able to scale out their applications, their businesses and continue to add value where they need to have and so um I think it's great we're seeing a huge uptake right now and we've got customers and they understand completely this hybrid cloud model where they're, you know, purchasing open shift um for certain, you know, applications and workloads that they want to run inside their own data centers. And then for those that they know that they don't, you know, don't have to be inside their own data centers. They don't want to have all of that operational complexity. They want to utilize some of the clouds. That's when they're starting to look at other things like rosa or open shift dedicated and and really starting to find the right mix that works well for their business. >>So are you saying that you guys are going to the next level because the previous, I won't say generation but the current situation was okay, you're born in the cloud or you lift and shift to the cloud, You do that manually, then you go on premise to build that cloud operations. Now you're in a hybrid environment. So you're saying if I get this right that you guys are providing automation around standing up in building services on AWS and cloud, public cloud and hybrid, is that kinda what you're getting at? >>Yeah. So the to go to the higher multi cloud world, right? You want platform consistency, right? Running my application running on a platform consistently, you know, where we go. Right. Tracy started talking about this idea of in some cases you say, well I've got the infrastructure team, I've got the ops team, johnny talked about this notion of, well the dwarves can be hard, sometimes right to some groups. Um, and so hey, red hat or hey redhead, plus, you know, my hyper scale of choice, you know, take that off of my hands, Right. Run that for me consistently yourself. Right. So I focused on my application uh and the management of infrastructure is something that's on you Tracy talked about rosa, that's our joint uh first party service that you know, we've got with amazon were directly available in amazon's console, you can go pull that down, right. You'll see red hat open shift on AWS, right on their uh we've got a similar one with Microsoft Azure Tracy mentioned open dedicated, we stand up the platform, we have our own sorry team that manages it with IBM as well as with google. So you pick your cloud of choice and we'll make sure, you know, we'll give you a platform that if you as a customer so choose to self manage. Great, go for it. If you'd like for us to manage it directly ourselves or in conjunction with the cloud provider and provided to you as a native service, you know, we can do that for you as well. Right? So that day to obsolete, you know, challenge that we're talking about. You know, it's something that we can get your hands if you want us to. >>That's really cool. You gotta manage service. They can do it themselves whatever they want. They can do it on public cloud and hybrid. Great stuff. Yeah, I think that's the key. Um, and that's, that's, that's killer. Now, the next question is my favorite. I want to ask you guys both pretend I'm a customer and I'm like, okay, Tracy shit, tell me what's in it for me. What is open shifts and red hat doing for me is the customer? What are you bringing to the table for me? What are you gonna do for me? What is red hat doing for me today? So if you have the kind of bottom line we were in the elevator or probably I ask you, I like what I'm hearing. Why? Why are you cool? Why are you relevant? What's in it for me? >>You >>already start? Okay. Yeah, so I mean I think it's a couple of things that we let's just tie it back to the first initial blend. I mean we've got, we're enabling the customers to choose like where do they want to work that run their workloads, what do they want to focus on? I think that's the first thing. Um we're enabling them to also determine like what workloads do they want to put on there. We continue to expand the workloads that we are providing um capabilities to customers. You know most, you know one of the more recent ones we've had is you know, enablement of Windows containers a huge plus for us. Um, you know, it's just kind of talked about, dropped the buzzword ai you know, recently, you know, we're looking at that, we're talking about, you know, moving workloads need to go to the edge now. It's not just about being in the data centers, so it's about enablement. That's really what open shift as you know, bread and butter is, is, you know, let us, you know, create the ability for you to drive your workloads, whichever, whatever your workloads is, modernize those workloads um, in place them wherever you want to. >>Yes, your your answer. How would you say to that? >>I'll build on what Tracy said, right. She obviously took the, you know, build up tribal Benjamin perspective and I'll sort of talk about a business thing you're introducing, actually add threat at summit. So, you know, we go up and acquire stock rocks, you know, further deepen investment in communities or containment of security. Uh if you recall, john, we've talked to you about, you know, advanced cluster management team that we actually got from IBM incorporate that within red hat, um, to start providing, you know, those capabilities are consistent, you know, cluster policy, immigration management. Um, and you know, in the past we've made an acquisition of Core West, we've got a lot of technology from that incorporated the platform and also things like the quake container registry. What we're introducing address had some it is a way for us to package all of that together. So a customer doesn't say, look, you know, let me pick out a container platform here, let me go find, you know, somebody manage it over there. You let me see, you know what security you adhere. We introduced something called open shift platform plus right. Which is the packaging of, you know, core Open shift contain a platform uh, capabilities within uh, stack rocks, which we're calling advanced cluster security capabilities of cluster management, which is called advanced cluster management. And the quake container registry always want to make it much easier for customers to consume that. And again, you know, the goal is, you know, run that consistently in your hybrid multi club >>chef Tracy. Great, great segment, great insight. Um, here on the cloud platform and open shift under the hood. Uh, you guys are well positioned and I was talking about Arvin and idea who acquired red hat. You know, it's pretty clear that cloud native hybrid is the new cloud operating environment. That's clear. You guys are well positioned. And congratulations. Final question Chef. Take a minute to quickly put the plug in for open shift. What's next? Um, looking forward, what do you guys building on? Um, what's on the roadmap if you can negative share the road map, but yeah, tell us what you're thinking about. I mean you're innovating out in the open, love your shirt by the way and that's the red hat way, looking ahead. What's coming for? Open shift? >>So john I will say this, our roadmap is out in the open every quarter. Our product managers host the session right open to anybody, right? You know, customers prospect, competitors, anybody can can come on. Um, and uh, you hear about our road map, lots of interesting things they're working on uh, as you can imagine investments on the edge front, right? So that's across our portfolio, right on the open shift side, but also on learning platform as well as on the open stack front, make it easier to have, you know, slim down open shift. we'll run that you won't be able to run uh open ship in remote locations and then manage it. Um So expect for us uh you know, just to show you more work there, drinking things like uh ai and more workloads directly onto the platform, but you'll see what they're doing to get more Alex on what we're doing to take uh technologies that we've got called Open data hub to make it easier to run more data intensive, more ai ml types of frameworks directly a platform. Um And so that's a great interest, more workloads Tracy, start talking about that. Right, so Windows containers, support has G eight, uh and what's really awesome about that is that we've done that with Microsoft, right, so that offering is jointly supported by both us and our partners over at Microsoft uh virtualization, which is taking much machines and being able to run them as dangerous orchestrated by communities Um, and and doing more work, you know, on that front as well. So just a lot of different areas uh, were investigated and really, really excited to bring more workloads on 2:00. >>Well, Chef Tracy, great segment with a lot of data in there. Thanks for spending time in and providing that insight and uh, sharing the information. A lot of flowers blooming um, here in the cloud native environment, a lot of action. A lot of new stuff going on. Love the shift left. I think that's super relevant. You guys do a great job. Thanks for coming on. I appreciate it. >>Okay. >>This the cubes coverage of red hat summit. I'm john for a host of the cube. Thank you for watching.

>>Okay. Okay. Now we're gonna go into the Green Lake Power Panel. Talk about the cloud landscape hybrid cloud and how the partner ecosystem and customers are thinking about cloud hybrid cloud as a service and, of course, Green Lake. And with me or CR Houdyshell, president of Advise X. Ron Nemecek, Who's the business Alliance manager at C B. T s. Harry Zaric is president of competition, and Benjamin Clay is VP of sales and alliances at Arrow Electronics. Great to see you guys. Thanks so much for coming on the Cube. >>Thanks for having us >>would be here. >>Okay, here's the deal. So I'm gonna ask you guys each to introduce yourselves and your company's add a little color to my brief intro and then answer the following question. How do you and your customers think about hybrid cloud and think about it in the context of where we are today and where we're going? Not just the snapshot, but where we are today and where we're going. CR, why don't you start, please? >>Sure. Thanks a lot. They appreciate it. And, uh, again cr Howdy Shell President of advising. I've been with the company for 18 years the last four years as president. So had the great great opportunity here to lead a 45 year old company with a very strong brand and great culture. Uh, as it relates to advise X and where we're headed to with hybrid Cloud is it's a journey, so we're excited to be leading that journey for the company as well as HP. We're very excited about where HP is going with Green Lake. We believe it's it's a very strong solution when it comes to hybrid. Cloud have been an HP partner since since 1980. So for 40 years it's our longest standing OM relationship, and we're really excited about where HP is going with Green Lake from a hybrid cloud perspective. Uh, we feel like we've been doing the hybrid cloud solutions in the past few years with everything that we've focused on from a VM Ware perspective. But now, with where HP is going, we think really changing the game and it really comes down to giving customers at cloud experience with the on Prem solution with Green Lake, and we've had great response from our customers and we think we're gonna continue to see how that kind of increased activity and reception. >>Great. Thank you. Cr and yeah, I totally agree. It is. It is a journey. And we've seen it really come a long way in the last decade. Ron, I wonder if you could kick off your little first intro there, please? >>Sure. Dave, thanks for having me today. And it's a pleasure being here with all of you. My name is Ron Nemecek, business Alliance manager at C B. T. S. In my role, I am responsible for RHP Green Lake relationship globally. I've enjoyed a 33 year career in the I T industry. I'm thankful for the opportunity to serve in multiple functional and senior leadership roles that have helped me gather a great deal of education and experience that could be used to aid our customers with their evolving needs for business outcomes. The best position them for sustainable and long term success. I'm honored to be part of the C B. T s and Annex Canada Organization, C B T s stands for consult Bill transform and support. We have a 35 year relationship with HP or a platinum and inner circle partner. We're headquartered in Cincinnati Ohio. We service 3000 customers, generating over a billion dollars in revenue, and we have over 2000 associates across the globe. Our focus is partnering with our customers to deliver innovative solutions and business results through thought leadership. We drive this innovation VR team of the best and brightest technology professionals in the industry that have secured over 2800 technical certifications 260 specifically with HP and in our hybrid cloud business. We have clearly found the technology new market demands for instant responses and experiences evolving economic considerations with detailed financial evaluation and, of course, the global pandemic have challenged each of our customers across all industries to develop an optimal cloud strategy we have. We now play an enhanced strategic role for our customers as there Technology Advisor and their guide to the right mix of cloud experiences that will maximize their organizational success with predictable outcomes. Our conversations have really moved from product roadmaps and speeds and feeds to return on investment, return on capital and financial statements, ratios and metrics. We collaborate regularly with our customers at all levels and all departments to find an effective, comprehensive cloud strategy for their workloads and applications, ensuring proper alignment and costs with financial return. >>Great. Thank you, Ron. Yeah, Today it's all about the business value. Harry, please, >>I Dave. Thanks for the opportunity and greetings from the Great White North, where Canadian based company headquartered in Toronto, with offices across the country. We've been in the tech industry for a very long time. What we would call a solution provider hard for my mother to understand what that means. But our goal is to help our customers realize the business value of their technology investments just to give you an example of what it is we try and do. We just finished a build out of a new networking and point in data center technology for a brand new hospital is now being mobilized for covid high risk patients. So talk about are all being an essential industry, providing essential services across the whole spectrum of technology. Now, in terms of what's happening in the marketplace, our customers are confused. No question about it. They hear about cloud and cloud first, and everyone goes to the cloud. But the reality is there's lots of technology, lots of applications that actually still have to run on premises for a whole bunch of reasons. And what customers want is solid senior serious advice as to how they leverage what they already have in terms of their existing infrastructure but modernized and updated So it looks and feels a lot like a cloud. But they have the security. They have the protection that they need to have for reasons that are dependent on their industry and business to allow them to run on from. And so the Green Lake philosophy is perfect. That allows customers to actually have 1 ft in the cloud, 1 ft in their traditional data center, but modernize it so it actually looks like one enterprise entity. And it's that kind of flexibility that gives us an opportunity collectively, ourselves, our partners, HP to really demonstrate that we understand how to optimize the use of technology across all of the business applications they need to rest >>your hair. It's interesting about what you said is is cloud is it is kind of chaotic. My word not yours, but but there is a lot of confusion out there. I mean, it's what's cloud right? Is it Public Cloud is a private cloud the hybrid cloud. Now, now it's the edge. And of course, the answer is all of the above. Ben, what's your perspective on all this? >>Um, from a cloud perspective. You know, I think as an industry, you know, I think we we've all accepted that public cloud is not necessarily gonna win the day and were, in fact, in a hybrid world, there's certainly been some some commentary impress. Um, you know, that would sort of validate that. Not that necessarily needs any validation. But I think it's the linkages between on Prem, Um, and cloud based services have increased. Its paved the way for customers to more effectively deploy hybrid solutions in the model that they want that they desired. You know, Harry was commenting on that a moment ago. Um, you know, as the trend continues, it becomes much easier for solution providers and service providers to drive there services, initiatives, uh, you know, in particular managed services. So, you know, from from an arrow perspective, as we think about how we can help scale in particular from Greenland perspective, we've got the ability to stand up some some cloud capabilities through our aero secure platform. um that can really help customers adopt Green Lake. Uh, and, uh, benefit to benefit from, um, some alliances, opportunities as well. And I'll talk more about that as we go through >>that. I didn't mean to squeeze you on a narrow. I mean, you got arrows. Been around longer than computers. I mean, if you google the history of arrow, it'll blow your mind. But give us a little, uh, quick commercial. >>Yeah, absolutely. So, um, I've been with arrow for about 20 years. I've got responsibility for alliances, organization, North America for Global value, added distribution, business consulting and channel enablement Company. Uh, you know, we bring scope, scale and and, uh, expertise as it relates to the I t industry. Um, you know, I love the fast paced, the fast paced that comes with the market, that we're all all in, and I love helping customers and suppliers both, you know, be positioned for long term success. And, you know, the subject matter here today is just a great example of that. So I'm happy to be here and or to the discussion. >>All right, We got some good brain power in the room. Let's let's cut right to the chase. Ron, Where's the pain? What are the main problems that C B. T s. I love the what it stands for. Consult Bill Transform and support the What's the main pain point that that customers are asking you to solve when it comes to their cloud strategies. >>Third day of our customers' concerns and associated risk come from the market demands to deliver their products, services and experiences instantaneously. And then the challenges is how do they meet those demands because they have aging infrastructure processes and fiscal constraints. Our customers really need us now more than ever to be excellent listeners so we can collaborate on an effective map for the strategic placement of workloads and applications in that spectrum of cloud experiences, while managing their costs and, of course, mitigating risk to their business. This collaboration with our customer customers often identify significant costs that have to be evaluated, justified or eliminated. We find significant development, migration and egress charges in their current public cloud experience, coupled with significant over provisioning, maintenance, operational and stranded asset costs in their on premise infrastructure environment. When we look at all these costs holistically through our customized workshops and assessments. We can identify the optimal cloud experience for the respective workloads and applications through our partnership with HP and the availability of the HP Green Lake Solutions. Our customers now have a choice to deliver SLA's economics and business outcomes for their workloads and applications that best reside on premise in a private cloud and have that experience. This is a rock solid solution that eliminates, you know, the development costs at the experience and the egress charges that are associated with the public cloud while utilizing HP Green Lake to eliminate over provisioning costs and the maintenance costs on aging infrastructure hardware. Lastly, our customers only have to pay for actual infrastructure usage with no upfront capital expense. And now that achieves true utilization to cost economics. You know, with HP Green Lake solution from C B. T s. >>I love to focus on the business case because it's measurable. That sort of follow the money. That's where it's where the opportunity is. Okay, See, I got a question for you thinking about advise X customers. How are they? Are they leaning into Green Lake? You know, what are they telling you? Is the business impact when they when they experience Green Lake, >>I think it goes back to what Ron was talking about. We have to solve the business challenges first, and so far the reception's been positive. When I say that is, customers are open, everybody wants to. The C suite wants to hear about cloud and hybrid cloud fits, but what we're hearing, what we're seeing from our customers is we're seeing more adoption from customers that it may be their first put in, if you will. But as importantly, we're able to share other customers with our potentially new clients that that say, What's the first thing that happens with regard to Green like Well, number one, it works. It works as advertised and as a as a service. That's a big step. There are a lot of people out there dabbling today, but when you can say we have a proven solution, it's working in in in our environment today. That's key. I think the second thing is is flexibility. You know, when customers are looking for this, this hybrid solution, you've got to be flexible for again. I think Ron said it well, you don't have a big capital outlay but also what customers want to be able to. We're gonna build for growth, but we don't want to pay for it, so we'll pay as we grow. Not as not as we have to use because we used to do It was upfront of the capital expenditure, and I will just pay as we grow and that really facilitates. In another great examples, you'll hear from a customer, uh, this afternoon, but you'll hear where one of the biggest benefits they just acquired a $570 million company, and their integration is going to be very seamless because of their investment in Green Lake. They're looking at the flexibility to add the Green Lake as a big opportunity to integrate for acquisitions and finally is really we see it really brings the cloud experience and as a service to our customers bring. And with HP Green Lake, it brings best to breathe. So it's not just what HP has to offer. When you look at hyper converged, they have Nutanix kohi city, so I really believe it brings best to breathe. So, uh to net it out and close it out with our customers thus far, the customer experience has been exceptional with Green Lake Central has interface. Customers have had a lot of success. We just had our first customer from about a year and a half ago, just re up, and it was a highly competitive situation. But they just said, Look, it's proven it works and it gives us that cloud experience So I had a lot of great success thus far, looking forward to more. >>Thank you. So, Harry, I want to pick up on something, CR said, And get your perspectives. So when you when I talk to the C suite, they do all want to hear about, you know, Cloud, they have a cloud agenda and and what they tell me is it's not just about their I t transformation. They want, they want that. But they also want to transform their business. So I wonder if you could talk Harry about competence, perspective on the potential business impact of Green Lake, and and also, you know, I'm interested in how you guys are thinking about workloads, how to manage work, you know how to cost optimize in i t. But also the business value that comes out of that capability. >>Yes. So, Dave, you know, if you were to talk to CFO and I have the good fortune to talk to lots of CFOs, they want to pay the cost. When they generate the revenue, they don't want to have all the cost up front and then wait for the revenue to come through. A good example of where that's happening right now is related to the pandemic. Employees that used to work at the office have now moved to working from home, and now they have to. They have to connect remotely to run the same application. So use this thing called VD virtual interfacing to allow them to connect to the applications that they need to run in the off. Don't want to get into too much detail. But to be able to support that from an at home environment, they needed to buy a lot more computing capacity to handle this. Now there's an expectation that hopefully six months from now, maybe sooner than that people will start returning to the office. They may not need that capacity so they can turn down on the cost. And so the idea of having the capacity available when you need it, But then turning it off when you don't need it is really a benefit of a variable cost model. Another example that I would use is one in new development if a customer is going to implement and you, let's say, line of business application essay P is very, very popular, you know, it actually, unfortunately takes six months to two years to actually get that application setup installed, validated, test it and then moves through production. You know what used to happen before they would buy all that capacity at front and basically sit there for two years? And then when they finally went to full production, then they were really getting value out of that investment. But they actually lost a couple of years of technology, literally sitting almost idle. And so, from a CFO perspective, his ability to support the development of those applications as he scales it perfect Green Lake is the ideal solution that allows them to do that. >>You know, technology has saved businesses in this pandemic. There's no question about it and what Harry was just talking about with regard to VD. You think about that. There's the dialing up and dialing down piece, which is awesome from an i t perspective and then the business impact. There is the productivity of Of of the end users, and most C suite executives I've talked to said Productivity actually went up during covid with work from home, which is kind of astounding if you think about it. Ben, you know Ben, I We said Arrow has been around for a long, long time, certainly before all of us were born and it's gone through many, many industry transitions during our lifetimes. How does arrow and how do How do your partners think about building cloud experience experiences? And where does Green Lake fit in from your perspective? >>A great question. So from a narrow perspective, when you think about cloud experience and, of course, us taking a view as a distribution partner, we want to be able to provide scale and efficiency to our network of partners. So we do that through our aero screw platform. Um, just just a bit of a you know, a bit of a commercial. I mean, you get single quote single bill auto provision compared multi supplier, if you will Subscription management utilization reporting from the platform itself. So if we pivot that directly to HP, you're going to get a bit of a scoop here, Dave. So we're excited today to have Green Lake live in our platform available for our part of community to consume in particular the swift solutions that HP has announced. So we're very excited to to share that today, Um, maybe a little bit more on Green Lake. I think at this point in time, there it's differentiated, Um, in a sense that if you think about some of the other offerings in the market today and further with, um uh, having the solutions himself available in a row sphere So, you know, I would say, Do we identify the uniqueness, um, and quickly partner with HP to to work with our atmosphere platform? One other sort of unique thing is, you know, when you think about platform itself, you've got to give a consistent experience the different geographies around the world. So, you know, we're available in north of 20 countries. There's thousands of resellers and transacting on the platform on a regular basis, and frankly, hundreds of thousands and customers are leveraging today, so that creates an opportunity for both Arrow HP and our partner community. So we're excited. >>Uh, you know, I just want to open it up and we don't have much time left, but thoughts on on on differentiation. You know, when people ask me Okay, what's really different about H P E and Green Lake? As others you know are doing things that with with as a service to me, it's a I I always say cultural. It starts from the top with Antonio, and it's like the company's all in. But But I wonder from your perspective because you guys are hands on. Are there other differential factors that you would point to let me just open that up to the group? >>Yeah, if I could make a comment. You know, Green Lake is really just the latest invocation of the as a service model. And what does that mean? What that actually means is you have a continuous ongoing relationship with the customer. It's not a cell. And forget not that we ever forget about customers, but there are highlights. Customer buys, it gets installed, and then for two or three years, you may have an occasional engagement with them. But it's not continuous. When you move to a Green Lake model, you're actually helping them manage that you are in the core in the heart of their business. No better place to be if you want to be sticky and you want to be relevant, and you want to be always there for them. >>You know, I wonder if somebody else could add to and and and in your in your remarks from your perspective as a partner because, you know, Hey, a lot of people made a lot of money selling boxes, but those days are pretty much gone. I mean, you have to transform into a services mindset. But other thoughts, >>I think I think Dad did that day. I think Harry's right on right. What he the way he positioned Exactly. You get on the customer. Even another step back for us is we're able to have the business conversation without leading with what you just said. You don't have to leave with a storage solution to leave with a compute. You can really have step back, have a business conversation, and we've done that where you don't even bring up hp Green Lake until you get to the point of the customer says, So you can give me an on prem cloud solution that gives me scalability, flexibility, all the things you're talking about. How does that work then? Then you bring up. It's all through this HP Green link tool. It really gives you the ability to have a business conversation. And you're solving the business problems versus trying to have a technology conversation. And to me, that's clear differentiation for HP. Green length. >>All right, guys. CR Ron. Harry. Ben. Great discussion. Thank you so much for coming on the program. Really appreciate it. >>Thanks for having us, Dave. >>All >>right. Keep it right there for more great content at Green Lake Day. Right back? Yeah.

(bright upbeat music) >> Announcer: We are entering an age of insight where data moves freely between environments to work together powerfully, from wherever it lives. A new era driven by next generation cloud services. It's freedom that accelerates innovation and digital transformation, but it's only for those who dare to propel their business toward a new future that pushes beyond the usual barriers. To a place that unites all information under a fluid yet consistent operating model, across all your applications and data. To a place called HPE GreenLake. HPE GreenLake pushes beyond the obstacles and limitations found in today's infrastructure because application entanglements, data gravity, security, compliance, and cost issues simply aren't solved by current cloud options. Instead, HPE GreenLake is the cloud that comes to you, bringing with it, increased agility, broad visibility, and open governance across your entire enterprise. This is digital transformation unlocked, incompatibility solved, data decentralized, and insights amplified. For those thinkers, makers and doers who want to create on the fly scale up or down with a single click, stand up new ideas without risk, and view it all as a single agile system of systems. HPE GreenLake is here and all are invited. >> The definition of cloud is evolving and now clearly comprises hybrid and on-prem cloud. These trends are top of mind for every CIO and the space is heating up as every major vendor has been talking about as-a-Service models and making moves to better accommodate customer needs. HPE was the first to market with its GreenLake brand, and continues to make new announcements designed to bring the cloud experience to far more customers. Come here from HPE and its partners about the momentum that they're seeing with this trend and what actions you can take to stay ahead of the competition in this fast moving market. (bright soft music) Okay, we're with Keith White, Senior Vice President and General Manager for GreenLake at HPE, and George Hope, who's the Worldwide Head of Partner Sales at Hewlett Packard Enterprise. Welcome gentlemen, good to see you. >> Awesome to be here. >> Yeah. Thanks so much. >> You're welcome, Keith, last we spoke, we talked about how you guys were enabling high performance computing workloads to get green-late right for enterprise markets. And you got some news today, which we're going to get to but you guys, you put out a pretty bold position with GreenLake, basically staking a claim if you will, the edge, cloud as-a-Service all in. How are you thinking about its impacts for your customers so far? >> You know, the impact's been amazing and, you know, in essence, I think the pandemic has really brought forward this real need to accelerate our customer's digital transformation, their modernization efforts, and you know, frankly help them solve what was amounting to a bunch of new business problems. And so, you know, this manifests itself in a set of workloads, set of solutions, and across all industries, across all customer types. And as you mentioned, you know GreenLake is really bringing that value to them. It brings the cloud to the customer in their data center, in their colo, or at the edge. And so frankly, being able to do that with that full cloud experience. All is a pay per use, you know, fully consumption-based scenario, all managed for them so they get that as I mentioned, true cloud experience. It's really sort of landing really well with customers and we continue to see accelerated growth. We're adding new customers, we're adding new technology. And we're adding a whole new set of partner ecosystem folks as well that we'll talk about. >> Well, you know, it's interesting you mentioned that just cause as a quick aside it's, the definition of cloud is evolving and it's because customers, it's the way customers look at it. It's not just vendor marketing. It's what customers want, that experience across cloud, edge, you know, multiclouds, on-prem. So George, what's your take? Anything you'd add to Keith's response? >> I would, you've heard Antonio Neri say it several times and you probably saying it for yourself. The cloud is an experience, it's not a destination. The digital transformation is pushing new business models and that demands more flexible IT. And the first round of digital transformation focused on a cloud first strategy. For our customers we're looking to get more agility. As Keith mentioned, the next phase of transformation will be characterized by bringing the cloud speed and agility to all apps and data, regardless of where they live, According to IDC, by the end of 2021, 80% of the businesses will have some mechanism in place to shift the cloud centric, infrastructure and apps and twice as fast as before the pandemic. So the pandemic has actually accelerated the impact of the digital divide, specifically, in the small and medium companies which are adapting to technology change even faster and emerging stronger as a result. You know, the analysts agree cloud computing and digitalization will be key differentiators for small and medium business in years to come. And speed and automation will be pivotal as well. And by 2022, at least 30% of the lagging SMBs will accelerate digitalization. But the fair focus will be on internal processes and operations. The digital leaders, however, will differentiate by delivering their customers, a dynamic experience. And with our partner ecosystem, we're helping our customers embrace our as-a-Service vision and stand out wherever they are. on their transformation journey. >> Well, thanks for those stats, I always liked the data. I mean, look, if you're not a digital business today I feel like you're out of business only 'cause.... I'm sure there's some exceptions, but you got to get on the digital bandwagon. I think pre-pandemic, a lot of times people really didn't know what it meant. We know now what it means. Okay, Keith, let's get into the news when we do these things. I love that you guys always have something new to share. What do you have? >> No, you got it. And you know, as we said, the world is hybrid and the world is multicloud. And so, customers are expecting these solutions. And so, we're continuing to really drive up the innovation and we're adding additional cloud services to GreenLake. We just recently went to General AVailability of our MLOps, Machine Learning Operations, and our containers for cloud services along with our virtual desktop which has become very big in a pandemic world where a lot more people are working from home. And then we have shipped our SAP HEC, customer edition, which allows SAP customers to run on their premise whether it's the data center or the colo. And then today we're introducing our new Bare Metal capabilities as well as containers on Bare Metal as a Service, for those folks that are running cloud native applications that don't require any sort of hypervisor. So we're really excited about that. And then second, I'd say similar to that HPC as a Service experience we talked about before, where we were bringing HPC down to a broader set of customers. We're expanding the entry point for our private cloud, which is virtual machines, containers, storage, compute type capabilities in workload optimized systems. So again, this is one of the key benefits that HPE brings is it combines all of the best of our hardware, software, third-party software, and our services, and financial services into a package. And we've workload optimized this for small, medium, large and extra-large. So we have a real sort of broader base for our customers to take advantage of and to really get that cloud experience through HPE GreenLake. And, you know, from a partner standpoint we also want to make sure that we continue to make this super easy. So we're adding self-service capabilities we're integrating into our distributors marketplaces through a core set of APIs to make sure that it plugs in for a very smooth customer experience. And this expands our reach to over 100,000 additional value-added resellers. And, you know, we saw just fantastic growth in the channel in Q1, over 118% year over year growth for GreenLake Cloud Services through the channel. And we're continuing to expand, extend and expand our partner ecosystem with additional key partnerships like our colos. The colocation centers are really key. So Equinix, CyrusOne and others that we're working with and I'll let George talk more about. >> Yeah, I wonder if you could pick up on that George. I mean, look, if I'm a partner and and I mean, I see an opportunity here.. Maybe, you know, I made a lot of money in the old days moving iron. But I got to move, I got to pivot my business. You know, COVID's actually, you know, accelerating a lot of those changes, but there's a lot of complexity out there and partners can be critical in helping customers make that journey. What do you see this meaning to partners, George? >> So I completely agree with Keith and through and with our partners we give our customers choice. Right, they don't have to worry about security or cost as they would with public cloud or the hyperscalers. We're driving special initiatives via Cloud28 which we run, which is the world's largest cloud aggregator. And also, in collaboration with our distributors in their marketplaces as Keith mentioned. In addition, customers can leverage our expertise and support of our service provider ecosystem, our SI's, our ISV's, to find the right mix of hybrid IT and decide where each application or workload should be hosted. 'Cause customers are now demanding robust ecosystems, cloud adjacency, and efficient low latency networks. And the modern workload demands, secure, compliant, highly available, and cost optimized environments. And Keith touched on colocation. We're partnering with colocation facilities to provide our customers with the ability to expand bandwidth, reduce latency, and get access to a robust ecosystem of adjacent providers. We touched on Equinix a bit as one of them, but we're partnering with them to enable customers to connect to multiple clouds with private on-demand interconnections from hundreds of data center locations around the globe. We continue to invest in the partner and customer experience, you know, making ourselves easier to do business with. We've now fully integrated partners in GreenLake Central, and could provide their customers end to end support and managing the entire hybrid IT estate. And lastly, we're providing partners with dedicated and exclusive enablement opportunities so customers can rely on both HPE and partner experts. And we have a competent team of specialists that can help them transform and differentiate themselves. >> Yeah, so, I'm hearing a theme of simplicity. You know, I talked earlier about this being customer-driven. To me what the customer wants is they want to come in, they want simple, like you mentioned, self-serve. I don't care if it's on-prem, in the cloud, across clouds, at the edge, abstract, all that complexity away from me. Make it simple to do, not only the technology to work, you figure out where the workload should run and let the metadata decide and that's a bold vision. And then, make it easy to do business. Let me buy as-a-Service if that's the way I want to consume. And partners are all about, you know, reducing friction and driving that. So, anyway guys, final thoughts, maybe Keith, you can close it out here and maybe George can call it timeout. >> Yeah, you summed it up really nice. You know, we're excited to continue to provide what we view as the largest and most flexible hybrid cloud for our customers' apps, data, workloads, and solutions. And really being that leading on-prem solution to meet our customer's needs. At the same time, we're going to continue to innovate and our ears are wide open, and we're listening to our customers on what their needs are, what their requirements are. So we're going to expand the use cases, expand the solution sets that we provide in these workload optimized offerings to a very very broad set of customers as they drive forward with that digital transformation and modernization efforts. >> Right, George, any final thoughts? >> Yeah, I would say, you know, with our partners we work as one team and continue to hone our skills and embrace our competence. We're looking to help them evolve their businesses and thrive, and we're here to help now more than ever. So, you know, please reach out to our team and our partners and we can show you where we've already been successful together. >> That's great, we're seeing the expanding GreenLake portfolio, partners key part of it. We're seeing new tools for them and then this ecosystem evolution and build out and expansion. Guys, thanks so much. >> Yeah, you bet, thank you. >> Thank you, appreciate it. >> You're welcome. (bright soft music) >> Okay, we're here with Jo Peterson the VP of Cloud & Security at Clarify360. Hello, Jo, welcome to theCUBE. >> Hello. >> Great to see you. >> Thanks for having me. >> You're welcome, all right, let's get right into it. How do you think about cloud where we are today in 2021? The definitions evolve, but where do you see it today and where do you see it going? >> Well, that's such an interesting question and is so relevant because the labels are disappearing. So over the last 10 years, we've sort of found ourselves defining whether an environment was public or whether it was private or whether it was hybrid. Here's the deal, cloud is infrastructure and infrastructure is cloud. So at the end of the day cloud in whatever form it's taking is a platform, and ultimately, this enablement tool for the business. Customers are consuming cloud in the best way that works for their businesses. So let's also point out that cloud is not a destination, it's this journey. And clients are finding themselves at different places on that road. And sometimes they need help getting to the next milestone. >> Right, and they're really looking for that consistent experience. Well, what are the big waves and trends that you're seeing around cloud out there in the marketplace? >> So I think that this hybrid reality is happening in most organizations. Their actual IT portfolios include a mix of on-premise and cloud infrastructure, and we're seeing this blurred line happening between the public cloud and the traditional data center. Customers want a bridge that easily connects one environment to the other environment, and they want end-to-end visibility. Customers are becoming more intentional and strategic about their cloud roadmaps. So some of them are intentionally and strategically selecting hybrid environments because they feel that it affords them more control, cost, balance, comfort level around their security. In a way, cloud itself is becoming borderless. The major tech providers are extending their platforms in an infrastructure agnostic manner and that's to work across hybrid environments, whether they be hosted in the data center, whether it includes multiple cloud providers. As cloud matures, workload environments fit is becoming more of a priority. So forward thinking where the organizations are matching workloads to the best environment. And it's sort of application rationalization on this case by case basis and it really makes sense. >> Yeah, it does makes sense. Okay, well, let's talk about HPE GreenLake. They just announced some new solutions. What do you think it means for customers? >> I think that HPE has stepped up. They've listened to not only their customers but their partners. Customers want consumable infrastructure, they've made that really clear. And HPE has expanded the cloud service portfolio for clients. They're offering more choices to not only enterprise customers but they're expanding that offering to attract this mid-market client base. And they provided additional tools for partners to make selling GreenLake easier. This is all helping to drive channel sales. >> Yeah, so better granularity, just so it increases the candidates, better optionality for customers. And this thing is evolving pretty quickly. We're seeing a number of customers that we talked to interested in this model, trying to understand it better and ultimately, I think they're going to really lean in hard. Jo, I wonder if you could maybe think about or share with us which companies are, I got to say, getting it right? And I'm really interested in the partner piece, because if you think about the partner business, it's really, it's changing a lot, right? It's gone from this notion of moving boxes and there was a lot of money to be made over the decades in doing that, but they have to now become value-add suppliers and really around cloud services. And in the early days of cloud, I think the channel was a little bit freaked out, saying, uh-oh, they're going to cut out the middleman. But what's actually happened is those smart agile partners are adding substantial value, they've got deep relationships with customers and they're serving as really trusted advisors and executors of cloud strategies. What do you see happening in the partner community? >> Well, I think it's been a learning curve and everything that you said was spot on. It's a two way street, right? In order for VARs to sell residual services, monthly recurring services, there has to have been some incentive to do that and HPE really got it right. Because they, again listened to that partner community, and they said, you know what? We've got to incentivize these guys to start selling this way. This is a partnership and we expect it to be a partnership. And the tech companies that are getting right are doing that same sort of thing, they're figuring out ways to make it palatable to that VAR, to help them along that journey. They're giving them tools, they're giving them self-serve tools, they're incentivizing them financially to make that shift. That's what's going to matter. >> Well, that's a key point you're making, I mean, the financial incentives, that's new and different. Paying, you know, incentivizing for as-a-Service models versus again, moving hardware and paying for, you know, installing iron. That's a shift in mindset, isn't it? >> It definitely is. And HPE, I think is getting it right because I didn't notice but I learned this, 70% of their annual sales are actually transacted through their channel. And they've seen this 116% increase in HPE GreenLake orders in Q1, from partners. So what they're doing is working. >> Yeah, I think you're right. And you know, the partner channel it becomes super critical. It's funny, Jo, I mean, again, in the early days of cloud, the channel was feeling like they were going to get disrupted. I don't know about you, but I mean, we've both been analysts for awhile and the more things get simple, the more they get complicated, right? I mean the consumerization of IT, the cloud, swipe your credit card, but actually applying that to your business is not easy. And so, I see that as great opportunities for the channel. Give you the last word. >> Absolutely, and what's going to matter is the tech companies that step up and realize we've got this chance, this opportunity to build that bridge and provide visibility, end-to-end visibility for clients. That's what going to matter. >> Yeah, I like how you're talking about that bridge, because that's what everybody wants. They want that bridge from on-prem to the public cloud, across clouds, going to to be moving out to the edge. And that is to your point, a journey that's going to evolve over the better part of this coming decade. Jo, great to see you. Thanks so much for coming on theCUBE today. >> Thanks for having me. (bright soft music) >> Okay, now we're going to into the GreenLake power panel to talk about the cloud landscape, hybrid cloud, and how the partner ecosystem and customers are thinking about cloud, hybrid cloud as a Service and of course, GreenLake. And with me are C.R. Howdyshell, President of Advizex. Ron Nemecek, who's the Business Alliance Manager at CBTS. Harry Zarek is President of Compugen. And Benjamin Klay is VP of Sales and Alliances at Arrow Electronics. Great to see you guys, thanks so much for coming on theCUBE. >> Thanks for having us. >> Good to be here. >> Okay, here's the deal. So I'm going to ask you guys each to introduce yourselves and your companies, add a little color to my brief intro, and then answer the following question. How do you and your customers think about hybrid cloud? And think about it in the context of where we are today and where we're going, not just the snapshot but where we are today and where we're going. C.R., why don't you start please? >> Sure, thanks a lot, Dave, appreciate it. And again, C.R. Howdyshell, President of Advizex. I've been with the company for 18 years, the last four years as president. So had the great opportunity here to lead a 45 year old company with a very strong brand and great culture. As it relates to Advizex and where we're headed to with hybrid cloud is it's a journey. So we're excited to be leading that journey for the company as well as HPE. We're very excited about where HPE is going with GreenLake. We believe it's a very strong solution when it comes to hybrid cloud. Have been an HPE partner since, well since 1980. So for 40 years, it's our longest standing OEM relationship. And we're really excited about where HPE is going with GreenLake. From a hybrid cloud perspective, we feel like we've been doing the hybrid cloud solutions, the past few years with everything that we've focused on from a VMware perspective. But now with where HPE is going, we think, probably changing the game. And it really comes down to giving customers that cloud experience with the on-prem solution with GreenLake. And we've had great response for customers and we think we're going to continue to see that kind of increased activity and reception. >> Great, thank you C.R., and yeah, I totally agree. It is a journey and we've seen it really come a long way in the last decade. Ron, I wonder if you could kickoff your little first intro there please. >> Sure Dave, thanks for having me today and it's a pleasure being here with all of you. My name is Ron Nemecek, I'm a Business Alliance manager at CBTS. In my role, I'm responsible for our HPE GreenLake relationship globally. I've enjoyed a 33 year career in the IT industry. I'm thankful for the opportunity to serve in multiple functional and senior leadership roles that have helped me gather a great deal of education and experience that could be used to aid our customers with their evolving needs, for business outcomes to best position them for sustainable and long-term success. I'm honored to be part of the CBTS and OnX Canada organization. CBTS stands for Consult Build Transform and Support. We have a 35 year relationship with HPE. We're a platinum and inner circle partner. We're headquartered in Cincinnati, Ohio. We service 3000 customers generating over a billion dollars in revenue and we have over 2000 associates across the globe. Our focus is partnering with our customers to deliver innovative solutions and business results through thought leadership. We drive this innovation via our team of the best and brightest technology professionals in the industry that have secured over 2,800 technical certifications, 260 specifically with HPE. And in our hybrid cloud business, we have clearly found that technology, new market demands for instant responses and experiences, evolving economic considerations with detailed financial evaluation, and of course the global pandemic, have challenged each of our customers across all industries to develop an optimal cloud strategy. We now play an enhanced strategic role for our customers as their technology advisor and their guide to the right mix of cloud experiences that will maximize their organizational success with predictable outcomes. Our conversations have really moved from product roadmaps and speeds and feeds to return on investment, return on capital, and financial statements, ratios, and metrics. We collaborate regularly with our customers at all levels and all departments to find an effective comprehensive cloud strategy for their workloads and applications ensuring proper alignment and cost with financial return. >> Great, thank you, Ron. Yeah, today it's all about the business value. Harry, please. >> Hi Dave, thanks for the opportunity and greetings from the Great White North. We're a Canadian-based company headquartered in Toronto with offices across the country. We've been in the tech industry for a very long time. We're what we would call a solution provider. How hard for my mother to understand what that means but what our goal is to help our customers realize the business value of their technology investments. Just to give you an example of what it is we try and do. We just finished a build out of a new networking endpoint and data center technology for a brand new hospital. It's now being mobilized for COVID high-risk patients. So talk about our all being in an essential industry, providing essential services across the whole spectrum of technology. Now, in terms of what's happening in the marketplace, our customers are confused. No question about it. They hear about cloud, I mean, cloud first, and everyone goes to the cloud, but the reality is there's lots of technology, lots of applications that actually still have to run on premises for a whole bunch of reasons. And what customers want is solid senior serious advice as to how they leverage what they already have in terms of their existing infrastructure, but modernize it, update it, so it looks and feels a lot like the cloud. But they have the security, they have the protection that they need to have for reasons that are dependent on their industry and business to allow them to run on-prem. And so, the GreenLake philosophy is perfect. That allows customers to actually have one foot in the cloud, one foot in their traditional data center but modernize it so it actually looks like one enterprise entity. And it's that kind of flexibility that gives us an opportunity collectively, ourselves, our partners, HPE, to really demonstrate that we understand how to optimize the use of technology across all of the business applications they need to run. >> You know Harry, it's interesting about what you said is, the cloud it is kind of chaotic my word, not yours. But there is a lot of confusion out there, I mean, what's cloud, right? Is it public cloud, is it private cloud, the hybrid cloud? Now, it's the edge and of course the answer is all of the above. Ben, what's your perspective on all this? >> From a cloud perspective, you know, I think as an industry, I think we we've all accepted that public cloud is not necessarily going to win the day and we're in fact, in a hybrid world. There's certainly been some commentary and press that was sort of validate that. Not that it necessarily needs any validation but I think is the linkages between on-prem and cloud-based services have increased. It's paved the way for customers more effectively, deploy hybrid solutions in in the model that they want or that they desire. You know, Harry was commenting on that a moment ago. As the trend continues, it becomes much easier for solution providers and service providers to drive their services initiatives, you know, in particular managed services. >> From an Arrow perspective is we think about how we can help scale in particular from a GreenLake perspective. We've got the ability to stand up some cloud capabilities through our ArrowSphere platform that can really help customers adopt GreenLake and to benefit from some alliances opportunities, as well. And I'll talk more about that as we go through. >> And Ben, I didn't mean to squeeze you on Arrow. I mean, Arrow has been around longer than computers. I mean, if you Google the history of Arrow it'll blow your mind, but give us a little quick commercial. >> Yeah, absolutely. So I've been with Arrow for about 20 years. I've got responsibility for Alliance organization in North America, We're a global value added distribution, business consulting and channel enablement company. And we bring scope, scale and and expertise as it relates to the IT industry. I love the fast pace that comes with the market that we're all in. And I love helping customers and suppliers both, be positioned for long-term success. And you know, the subject matter here today is just a great example of that. So I'm happy to be here and look forward to the discussion. >> All right, we got some good brain power in the room. Let's cut right to the chase. Ron, where's the pain? What are the main problems that CBTS I love what it stands for, Consult Build Transform and Support. What's the main pain point that customers are asking you to solve when it comes to their cloud strategies? >> Sure, Dave. Our customers' concerns and associated risks come from the market demands to deliver their products, services, and experiences instantaneously. And then the challenge is how do they meet those demands because they have aging infrastructure, processes, and fiscal constraints. Our customers really need us now more than ever to be excellent listeners so we can collaborate on an effective map with the strategic placement of workloads and applications in that spectrum of cloud experiences while managing their costs, and of course, mitigating risks to their business. This collaboration with our customers, often identify significant costs that have to be evaluated, justified or eliminated. We find significant development, migration, and egress charges in their current public cloud experience, coupled with significant over provisioning, maintenance, operational, and stranded asset costs in their on-premise infrastructure environment. When we look at all these costs holistically, through our customized workshops and assessments, we can identify the optimal cloud experience for the respective workloads and applications. Through our partnership with HPE and the availability of the HPE GreenLake solutions, our customers now have a choice to deliver SLA's, economics, and business outcomes for their workloads and applications that best reside on-premise in a private cloud and have that experience. This is a rock solid solution that eliminates, the development costs that they experience and the egress charges that are associated with the public cloud while utilizing HPE GreenLake to eliminate over provisioning costs and the maintenance costs on aging infrastructure hardware. Lastly, our customers only have to pay for actual infrastructure usage with no upfront capital expense. And now, that achieves true utilization to cost economics, you know, with HPE GreenLake solutions from CBTS. >> I love focus on the business case, 'cause it's measurable and it's sort of follow the money. That's where the opportunity is. Okay, C.R., so question for you. Thinking about Advizex customers, how are they, are they leaning into GreenLake? What are they telling you is the business impact when they experience GreenLake? >> Well, I think it goes back to what Ron was talking about. We had to solve the business challenges first and so far, the reception's been positive. When I say that is customers are open. Everybody wants to, the C-suite wants to hear about cloud and hybrid cloud fits. But what we hear and what we're seeing from our customers is we're seeing more adoption from customers that it may be their first foot in, if you will, but as important, we're able to share other customers with our potentially new clients that say, what's the first thing that happens with regard to GreenLake? Well, number one, it works. It works as advertised and as-a-Service, that's a big step. There are a lot of people out there dabbling today but when you can say we have a proven solution it's working in our environment today, that's key. I think the second thing is,, is flexibility. You know, when customers are looking for this hybrid solution, you got to be flexible for, again, I think Ron said (indistinct). You don't have a big capital outlay but also what customers want to be able to do is we want to build for growth but we don't want to pay for it. So we'll pay as we grow not as we have to use, as we used to do, it was upfront, the capital expenditure. Now we'll just pay as we grow, and that really facilitates in another great example as you'll hear from a customer, this afternoon. But you'll hear where one of the biggest benefits they just acquired a $570 million company and their integration is going to be very seamless because of their investment in GreenLake. They're looking at the flexibility to add to GreenLake as a big opportunity to integrate for acquisitions. And finally is really, we see, it really brings the cloud experience and as-a-Service to our customers. And with HPE GreenLake, it brings the best of breed. So it's not just what HPE has to offer. When you look at Hyperconverged, they have Nutanix, they have Cohesity. So, I really believe it brings best of breeds. So, to net it out and close it out with our customers, thus far, the customer experience has been exceptional. I mean, with GreenLake Central, as interface, customers have had a lot of success. We just had our first customer from about a year and a half ago just reopened, it was a highly competitive situation, but they just said, look, it's proven, it works, and it gives us that cloud experience so. Had a lot of great success thus far and looking forward to more. >> Thank you, so Harry, I want to pick up on something C.R. said and get your perspectives. So when I talk to the C-suite, they do all want to hear about, you know, cloud, they have a cloud agenda. And what they tell me is it's not just about their IT transformation. They want that but they also want to transform their business. So I wonder if you could talk, Harry, about Compugen's perspective on the potential business impact of GreenLake. And also, I'm interested in how you guys are thinking about workloads, how to manage work, you know, how to cost optimize in IT, but also, the business value that comes out of that capability. >> Yeah, so Dave, you know if you were to talk to CFO and I have the good fortune to talk to lots of CFOs, they want to pay the costs when they generate the revenue. They don't want to have all the costs upfront and then wait for the revenue to come through. A good example of where that's happening right now is you know, related to the pandemic, employees that used to work at the office have now moved to working from home. And now, they have to connect remotely to run the same application. So use this thing called VDI, virtual interfacing to allow them to connect to the applications that they need to run in the office. I don't want to get into too much detail but to be able to support that from an an at-home environment, they needed to buy a lot more computing capacity to handle this. Now, there's an expectation that hopefully six months from now, maybe sooner than that, people will start returning to the office. They may not need that capacity so they can turn down on the costs. And so, the idea of having the capacity available when you need it, but then turning it off when you don't need it, is really a benefit of the variable cost model. Another example that I would use is one in new development. If a customer is going to implement a new, let's say, line of business application. SAP is very very popular. You know, it actually, unfortunately, takes six months to two years to actually get that application set up, installed, validated, tested, then moves through production. You know, what used to happen before? They would buy all that capacity upfront, and it would basically sit there for two years, and then when they finally went to full production, then they were really value out of that investment. But they actually lost a couple of years of technology, literally sitting almost sidle. And so, from a CFO perspective, his ability to support the development of those applications as he scales it, perfect. GreenLake is the ideal solution that allows him to do that. >> You know, technology has saved businesses in this pandemic. There's no question about it. When Harry was just talking about with regard to VDI, you think about that, there's the dialing up and dialing down piece which is awesome from an IT perspective. And then the business impact there is the productivity of the end users. And most C-suite executives I've talked to said productivity actually went up during COVID with work from home, which is kind of astounding if you think about it. Ben, we said Arrow's been around for a long, long time. Certainly, before all of us were born and it's gone through many many industry transitions during our lifetimes. How does Arrow and how do your partners think about building cloud experiences and where does GreenLake fit in from your perspective? >> Great question. So from an Arrow perspective, when you think about cloud experience in of course us taking a view as a distribution partner, we want to be able to provide scale and efficiency to our network of partners. So we do that through our ArrowSphere platform. Just a bit of, you know, a bit of a commercial. I mean, you get single quote, single bill, auto provision, multi supplier, if you will, subscription management, utilization reporting from the platform itself. So if we pivot that directly to HPE, you're going to get a bit of a scoop here, Dave. And we're excited today to have GreenLake live in our platform available for our partner community to consume. In particular, the Swift solutions that HPE has announced so we're very excited to share that today. Maybe a little bit more on GreenLake. I think at this point in time, that it's differentiated in a sense that, if you think about some of the other offerings in the market today and further with having the the solutions themselves available in ArrowSphere. So, I would say, that we identify the uniqueness and quickly partner with HPE to work with our ArrowSphere platform. One other sort of unique thing is, when you think about platform itself, you've got to give a consistent experience. The different geographies around the world so, you know, we're available in North of 20 countries, there's thousands of resellers and transacting on the platform on a regular basis. And frankly, hundreds of thousands end customers. that are leveraging today. So that creates an opportunity for both Arrow, HPE and our partner community. So we're excited. >> You know, I just want to open it up. We don't have much time left, but thoughts on differentiation. Some people ask me, okay, what's really different about HPE and GreenLake? These others, you know, are doing things with as-a-Service. To me, I always say cultural, it starts from the top with Antonio, and it's like the company's all in. But I wonder from your perspectives, 'cause you guys are hands on. Are there other differentiable factors that you would point to? Let me just open that up to the group. >> Yeah, if I could make a comment. GreenLake is really just the latest invocation of the as-a-Service model. And what does that mean? What that actually means is you have a continuous ongoing relationship with the customer. It's not a sell and forget. Not that we ever forget about customers but there are highlights. Customer buys, it gets installed, and then for two or three years you may have an occasional engagement with them but it's not continuous. When you move to our GreenLake model, you're actually helping them manage that. You are in the core, in the heart of their business. No better place to be if you want to be sticky and you want to be relevant and you want to be always there for them. >> You know, I wonder if somebody else could add to it in your remarks. From your perspective as a partner, 'cause you know, hey, a lot of people made a lot of money selling boxes, but those days are pretty much gone. I mean, you have to transform into a services mindset, but other thoughts? >> I think to add to that Dave. I think Harry's right on. The way he positioned it it's exactly where he did own the customer. I think even another step back for us is, we're able to have the business conversation without leading with what you just said. You don't have to leave with a storage solution, you don't have to lead with compute. You know, you can really have step back, have a business conversation. And we've done that where you don't even bring up HPE GreenLake until you get to the point where the customer says, so you can give me an on-prem cloud solution that gives me scalability, flexibility, all the things you're talking about. How does that work? Then you bring up, it's all through this HPE GreenLake tool. And it really gives you the ability to have a business conversation. And you're solving the business problems versus trying to have a technology conversation. And to me, that's clear differentiation for HPE GreenLake. >> All right guys, C.R., Ron, Harry, Ben. Great discussion, thank you so much for coming on the program. Really appreciate it. >> Thanks for having us, Dave. >> Appreciate it Dave. >> All right, keep it right there for more great content at GreenLake Day, be right back. (bright soft music) (upbeat music) (upbeat electronic music)

>>Yeah, yeah. >>Welcome back to our final session in cultivating a data fluent culture track earlier today, we heard from experts like Valerie from the Data Lodge who shared best practices that you can apply to build that data flew into culture in your organization and tips on how to become the next analyst of the future from Yasmin at Comcast and Steve at all Terex. Then we heard from a captivating session with Cindy Hausen and Ruhollah Benjamin, professor at Princeton, on how now is our chance to change the patterns of injustice that we see have been woven into the fabric of society. If you do not have a chance to see today's content, I highly recommend that you check it out on demand. There's a lot of great information that you could start applying today. Now I'm excited to introduce our next session, which will take a look at how the democratization of data is powering digital transformation in the insurance industry. We have two prestigious guests joining us today. First Jim Bramblett, managing director of North America insurance practice, lead at its center. Throughout Jim's career, he's been focused on large scale transformation from large to midsize insurance carriers. His direct experience with clients has traditionally been in the intersection of technology, platform transformation and operating remodel redesign. We also have Michael cast Onus, executive VP and chief operating officer at DNA. He's responsible for all information technology, analytics and operating functions across the organization. Michael has led major initiatives to launch digital programs and incorporating modern AP I architectures ER, which was primarily deployed in the cloud. Jim, please take it away. >>Great. Thanks, Paula E thought we'd cover a few things today around around data. This is some of the trends we see in data within the insurance sector. And then I'll hand it over to Michael Teoh, take you through his story. You know, I think at the macro level, as we think about data and we think about data in the context of the insurance sector, it's interesting because the entire history of the insurance sector has been built on data and yet, at the same time, the entire future of it relies on that same data or similar similar themes for data. But but different. Right? So we think about the history, what has existed in an insurance companies. Four walls was often very enough, very enough to compete, right? So if you think about your customer data, claims, data, CRM, data, digital data, all all the data that was yeah, contained within the four walls of your company was enough to compete on. And you're able to do that for hundreds of years. But as we we think about now as we think about the future and the ability to kind of compete on data, this data comes from many more places just than inside your four walls. It comes from every device, every human, every vehicle, every property, every every digital interaction. Um in upon this data is what we believe insurers need to pivot to. To compete right. They need to be able to consume this data at scale. They need to be able to turn through this data to drive analytics, and they serve up insights based on those analytics really at the desktop of insurance professionals. And by the way, that has to be in the natural transition of national transaction. Of that employees work day. So an underwriter at a desktop claim him on the desktop, the sales associate of desktop. Those insights need to be served up at that point in time when most relevant. And you know. So if we think about how insurance companies are leveraging data, we see this really on kind of three horizons and starting from the left hand side of the page here, this is really brilliant basics. So how my leveraging core core data and core applied intelligence to monetize your existing strategy? And I think this brilliant based, brilliant basics concept is where most of most of my clients, at least within insurance are are today. You know, how are we leveraging data in the most effective way and putting it in the hands of business decision makers to make decisions largely through reporting and some applied intelligence? Um, Horizon two. We see, you know, definitely other industries blazing a trail here, and this is really about How do we integrate ecosystems and partners Now? I think within insurance, you know, we've had data providers forever, right? Whether it's NPR data, credit data risk data, you know, data aggregators and data providers have been a critical part of the insurance sector for for decades. I think what's different about this this ecosystem and partnership model is that it's much more Oneto one and it's much more, you know, kind of. How do we integrate more tightly and how do we become more embedded in each other's transactions? I think that we see some emergence of this, um, in insurance with automotive manufacturers with building management systems. But I think in the grand scheme of things, this is really very, very nascent for us as a sector. And I think the third horizon is is, you know, how do we fundamentally think about data differently to drive new business models? And I, you know, I don't know that we haven't ensure here in North America that's really doing this at any sort of scale. We certainly see pilots and proofs of concepts. We see some carriers in Europe farther down this path, but it's really it's really very new for us. A Z Think about these three horizons for insurance. So you know what's what's behind all this and what's behind. You know, the next powering of digital transformation and and we think at the end of the exercise, its data data will be the next engine that powers digital transformation. So in this exhibit, you know we see the three horizons across the top. You know, data is activated and activating digital transformation. And this, you know, this purple 3rd, 3rd road here is we think some of the foundational building blocks required to kind of get this right. But I think what's most important about about this this purple third bar here is the far right box, which is business adoption. Because you can build this infrastructure, you can have. You know, this great scalable cloud capability. Um, you can create a bunch of applications and intelligence, but unless it's adopted by the business, unless it's democratized, unless those insights and decisions air served up in the natural course of business, you're gonna have trouble really driving value. So that way, I think this is a really interesting time for data. We think this is kind of the next horizon to power the next age of digital transformation for insurance companies. With that brief prelude, I am, I'm honored. Thio, turn it over to Michael Stone Is the Cielo at CNN Insurance? >>Thanks, Jim, for that intro and very exciting Thio be here is part of part of beyond when I think a digital transformation within the context of insurance, actually look at it through the lens of competing in an era of near perfect information. So in order to be able to deliver all of the potential value that we talked about with regard to data and changing ecosystem and changing demands, the question becomes, How do you actually harness the information that's available to everybody to fundamentally change the business? So if you'll indulge me a bit here, let me tell you just a little bit more for those that don't know about insurance, what it really is. And I use a very long run on sentence to do that. It's a business model where capital is placed against risk in the form of products and associated services sold the customers through channels two companies to generate a return. Now, this sounds like a lot of other businesses in across multiple industries that were there watching today. But the difference within insurance is that every major word in that long run on sentence is changing sources of capital that we could draw on to be able to underwrite risk of going away. The nature of risk itself is changing from the perspective of policies that live six months to a year, the policies that could last six minutes. The products that we're creating are changing every day for our ability to actually put a satellite up in the air or ensure against the next pandemic. Our customers are not just companies or individuals, but they could be governments completely different entities than we would have been in sharing in the past and channels were changing. We sell direct, we sell through brokers and products are actually being embedded in other products. So you may buy something and not even know that insurance is a part of it. And what's most interesting here is the last word which is around return In the old world. Insurance was a cash flow business in which we could bring the premium in and get a level of interest income and being able to use that money to be able thio buffer the underwriting results that we would have. But those returns or dramatically reduced because of the interest income scenario, So we have to generate a higher rate of return. So what do we need to do? Is an insurance company in through this digital transformation to be able to get there? Well, fundamentally, we need to rethink how we're using information, and this is where thought spot and the cloud coming for us. We have two basic problems that we're looking to solve with information. The first one is information veracity. Do we believe it? When we get it? Can we actually trust it? Do we know what it means when we say that this is a policy in force or this is a new customer where this is the amount of attention or rate that we're going to get? Do we actually believe in that piece of data? The second is information velocity. Can we get it fast enough to be able to capitalize upon it? So in other words, we're We're working in a situation where the feedback loop is closing quickly and it's operating at a speed that we've never worked in before. So if we can't solve veracity and velocity, then we're never going to be able to get to where we need to go. So when we think of something like hot spot, what do we use it for? We use it to be able to put it in the hands of our business years so that they could ask the key questions about how the business is running. How much profit of my generating this month? What brokers do I need to talk? Thio. What is my rate retention? Look like what? The trends that I'm seeing. And we're using that mechanism not just to present nice visualizations, but to enable that really quick, dynamic question and answer and social, socially enabled search, which completely puts us in a different position of being able to respond to the market conditions. In addition, we're using it for pattern recognition. Were using it for artificial intelligence. We're gonna be capitalizing on the social aspect of of search that's that's enabled through thought spot and also connecting it into our advanced machine learning models and other capabilities that we currently have. But without it solving the two fundamental problems of veracity and velocity, we would be handicapped. So let me give you some advice about if I were in your position and you don't need to be in sleepy old industry like insurance to be able to do this, I'll leave you with three things. The first one is picking water holes so What are the things that you really want to be good at? What are the pieces of information that you really need to know more about? I mean, in insurance, its customers, it's businesses, locations, it's behavior. There are only a few water also really understand and pick those water holes that you're going to be really good at. The second is stand on the shoulders of giants. You know, in the world of technology, there's often a philosophy that says, Well, I can build it something better than somebody else create if I have it in house. But I'm happy to stand on the shoulders of giants like Thought Spot and Google and others to be able to create this capability because guess what? They're gonna out innovate any of the internal shops all day and every day. So don't be afraid. Thio. Stand side by side on the shoulders of giants as part of your journey. Unless you've got to build these organizations not just the technology for rapid experimentation and learning, because guess what? The moment you deliver insight, it begs another question, which also could change the business process, which could change the business model and If your organization the broader organization of business technology, analytics, customer service operations, etcetera is not built in a way that could be dynamic and flexible based on where the market is or is going, then you're gonna miss out on the opportunity. So again, I'm proud to be part of the fast black community. Really love the technology. And if if you look too, have the same kind of issues with your given industry about how you can actually speed up decision making, deliver insights and deliver this kind of search and recommended to use it. And with that, let's go to some questions. >>Awesome. Thank you so much, Michael and Jim for that in depth perspective and those tangible takeaways for our audience. We have a few minutes left and would love to ask a few questions. So here's the first one for Michael Michael. What are some of the most important things that you know now that you didn't know before you started this process? I think one of >>the things that's a great question. I think one of the things that really struck me is that, you know, traditional thinking would be very use case centric or pain point centric Show me, uh, this particular model or a particular question you want me to answer that can build your own analytics to do that or show me a deficiency in the system and I can go and develop a quick head that will do well, then you know, wallpaper over that particular issue. But what we've really learned is the foundation matters. So when we think about building things is building the things that are below the waterline, the pipes and plumbing about how you move data around how the engines work and how it all connects together gives you the above the waterline features that you could deliver to. You know, your employees into your customers much faster chasing use cases across the top above the waterline and ignoring what's below the water line to me. Is it really, uh, easy recipe too quick? Get your way to nothing. So again, focus on the foundation bill below the water line and then iterated above the water line that z what the lessons we've learned. It has been very effective for us. >>I think that's a very great advice for all those watching today on. But Here's one for Jim. Jim. What skills would you say are required for teams to truly adopt this digital transformation process? >>Yeah, well, I think that's a really good question, and I think I'd start with it's It's never one. Well, our experience has shown us number a one person show, right? So So we think to kind of drive some of the value that that that Michael spoke about. We really looked across disciplinary teams, which is a an amalgamation of skills and and team members, right? So if you think about the data science skills required, just kinda under under understand how toe toe work with data and drive insights, Sometimes that's high end analytic skills. Um, where you gonna find value? So some value architectural skills Thio really articulate, you know, Is this gonna move the needle for my business? I think there's a couple of critical critical components of this team. One is, you know, the operation. Whatever. That operation maybe has to be embedded, right, because they designed this is gonna look at a piece of data that seems interesting in the business Leader is going to say that that actually means nothing to me in my operation. So and then I think the last the last type of skill would be would be a data translator. Um, sitting between sometimes the technology in the business so that this amalgamation of skills is important. You know, something that Michael talked about briefly that I think is critical is You know, once you deliver insight, it leads to 10 more questions. So just in a intellectual curiosity and an understanding of, you know, if I find something here, here, the implications downstream from my business are really important. So in an environment of experimenting and learning thes thes cross discipline teams, we have found to be most effective. And I think we thought spot, you know, the platform is wired to support that type of analysis and wired to support that type of teaming. >>Definitely. I think that's though there's some really great skills. That's for people to keep in mind while they are going through this process. Okay, Michael, we have another question for you. What are some of the key changes you've had to make in your environment to make this digital transformation happen? >>That's a great question. I think if you look at our environment. We've got a mixture of, you know, space agent Stone age. We've got old legacy systems. We have all sorts of different storage. We have, you know, smatterings of things that were in cloud. The first thing that we needed to do was make a strong commitment to the cloud. So Google is our partner for for the cloud platform on unabashedly. The second thing that we needed to dio was really rethink the interplay between analytics systems in operational systems. So traditionally, you've got a large data warehouses that sit out over here that, you know, we've got some kind of extract and low that occurs, and we've got transactional operational systems that run the business, and we're thinking about them very differently from the perspective of bringing them together. How Doe I actually take advantage of data emotion that's in the cloud. So then I can actually serve up analytics, and I can also change business process as it's happening for the people that are transacting business. And in the meantime, I can also serve the multiple masters of total cost and consumption. So again, I didn't applications are two ships that pass in the night and never be in the world of Sienna. When you look at them is very much interrelated, especially as we want to get our analytics right. We want to get our A i m all right, and we want to get operational systems right By capturing that dated motion force across that architecture er that was an important point. Commit to the cloud, rethink the way we think analytics systems, work and operational systems work and then move them in tandem, as opposed to doing one without the other one in the vacuum. >>That's that's great advice, Michael. I think it's very important those key elements you just hit one question that we have final question we have for Jim. Jim, how do you see your client sustain the benefits that they've gained through this process? >>Yeah, it's a really good question. Um, you know, I think about some of the major themes around around beyond right, data fluency is one of them, right? And as I think about fluency, you only attain fluency through using the language every single day. They were day, week, over week, month over month. So you know, I think that applies to this. This problem too. You know, we see a lot of clients have to change probably two things at the same time. Number one is mindset, and number two is is structure. So if you want to turn these data projects from projects into processes, right, so so move away from spinning up teams, getting getting results and winding down. You wanna move away from that Teoh process, which is this is just the way working for these teams. Um, you have to change the mindset and often times you have to marry that with orb structure change. So So I'm gonna spin up these teams, but this team is going to deliver a set of insights on day. Then we're gonna be continuous improvement teams that that persist over time. So I think this shifting from project teams to persistent teams coupled with mindset coupled with with or structure changed, you know, a lot of times has to be in place for a period of time to get to get the fluency and achieve the fluency that that most organizations need. >>Thanks, Jim, for that well thought out answer. It really goes to show that the transformation process really varies when it comes to organizations, but I think this is a great way to close out today's track. I like to think Jim, Michael, as well as all the experts that you heard earlier today for sharing. There's best practice as to how you all can start transforming your organization's by building a data fluent culture, Um, and really empowering your employees to understand what data means and how to take actions with it. As we wrap up and get ready for the next session, I'd like to leave you all with just a couple of things. Number one if you miss anything or would like to watch any of the other tracks. Don't worry. We have everything available after this event on demand number two. If you want to ask more questions from the experts that you heard earlier today, you have a chance to do so. At the Meet The Experts Roundtable, make sure to attend the one for track four in cultivating a data fluent culture. Now, as we get ready for the product roadmap, go take a sip of water. This is something you do not want to miss. If you love what you heard yesterday, you're gonna like what you hear today. I hear there's some type of Indiana Jones theme to it all, so I won't say anything else, but I'll see you there.

>>Yeah, yeah. >>Welcome back. I'm so excited to introduce our next session empowerment through inclusion, reimagining society and technology. This is a topic that's personally very near and dear to my heart. Did you know that there's only 2% of Latinas in technology as a Latina? I know that there's so much more we could do collectively to improve these gaps and diversity. I thought spot diversity is considered a critical element across all levels of the organization. The data shows countless times. A diverse and inclusive workforce ultimately drives innovation better performance and keeps your employees happier. That's why we're passionate about contributing to this conversation and also partnering with organizations that share our mission of improving diversity across our communities. Last beyond, we hosted the session during a breakfast and we packed the whole room. This year, we're bringing the conversation to the forefront to emphasize the importance of diversity and data and share the positive ramifications that it has for your organization. Joining us for this session are thought spots Chief Data Strategy Officer Cindy Housing and Ruhollah Benjamin, associate professor of African American Studies at Princeton University. Thank you, Paola. So many >>of you have journeyed with me for years now on our efforts to improve diversity and inclusion in the data and analytic space. And >>I would say >>over time we cautiously started commiserating, eventually sharing best practices to make ourselves and our companies better. And I do consider it a milestone. Last year, as Paola mentioned that half the room was filled with our male allies. But I remember one of our Panelists, Natalie Longhurst from Vodafone, suggesting that we move it from a side hallway conversation, early morning breakfast to the main stage. And I >>think it was >>Bill Zang from a I G in Japan. Who said Yes, please. Everyone else agreed, but more than a main stage topic, I want to ask you to think about inclusion beyond your role beyond your company toe. How Data and analytics can be used to impact inclusion and equity for the society as a whole. Are we using data to reveal patterns or to perpetuate problems leading Tobias at scale? You are the experts, the change agents, the leaders that can prevent this. I am thrilled to introduce you to the leading authority on this topic, Rou Ha Benjamin, associate professor of African studies at Princeton University and author of Multiple Books. The Latest Race After Technology. Rou ha Welcome. >>Thank you. Thank you so much for having me. I'm thrilled to be in conversation with you today, and I thought I would just kick things off with some opening reflections on this really important session theme. And then we could jump into discussion. So I'd like us to as a starting point, um, wrestle with these buzzwords, empowerment and inclusion so that we can have them be more than kind of big platitudes and really have them reflected in our workplace cultures and the things that we design in the technologies that we put out into the world. And so to do that, I think we have to move beyond techno determinism, and I'll explain what that means in just a minute. Techno determinism comes in two forms. The first, on your left is the idea that technology automation, um, all of these emerging trends are going to harm us, are going to necessarily harm humanity. They're going to take all the jobs they're going to remove human agency. This is what we might call the techno dystopian version of the story and this is what Hollywood loves to sell us in the form of movies like The Matrix or Terminator. The other version on your right is the techno utopian story that technologies automation. The robots as a shorthand, are going to save humanity. They're gonna make everything more efficient, more equitable. And in this case, on the surface, he seemed like opposing narratives right there, telling us different stories. At least they have different endpoints. But when you pull back the screen and look a little bit more closely, you see that they share an underlying logic that technology is in the driver's seat and that human beings that social society can just respond to what's happening. But we don't really have a say in what technologies air designed and so to move beyond techno determinism the notion that technology is in the driver's seat. We have to put the human agents and agencies back into the story, the protagonists, and think carefully about what the human desires worldviews, values, assumptions are that animate the production of technology. And so we have to put the humans behind the screen back into view. And so that's a very first step and when we do that, we see, as was already mentioned, that it's a very homogeneous group right now in terms of who gets the power and the resource is to produce the digital and physical infrastructure that everyone else has to live with. And so, as a first step, we need to think about how to create more participation of those who are working behind the scenes to design technology now to dig a little more a deeper into this, I want to offer a kind of low tech example before we get to the more hi tech ones. So what you see in front of you here is a simple park bench public bench. It's located in Berkeley, California, which is where I went to graduate school and on this particular visit I was living in Boston, and so I was back in California. It was February. It was freezing where I was coming from, and so I wanted to take a few minutes in between meetings to just lay out in the sun and soak in some vitamin D, and I quickly realized, actually, I couldn't lay down on this bench because of the way it had been designed with these arm rests at intermittent intervals. And so here I thought. Okay, the the armrest have, ah functional reason why they're there. I mean, you could literally rest your elbows there or, um, you know, it can create a little bit of privacy of someone sitting there that you don't know. When I was nine months pregnant, it could help me get up and down or for the elderly, the same thing. So it has a lot of functional reasons, but I also thought about the fact that it prevents people who are homeless from sleeping on the bench. And this is the Bay area that we were talking about where, in fact, the tech boom has gone hand in hand with a housing crisis. Those things have grown in tandem. So innovation has grown within equity because we haven't thought carefully about how to address the social context in which technology grows and blossoms. And so I thought, Okay, this crisis is growing in this area, and so perhaps this is a deliberate attempt to make sure that people don't sleep on the benches by the way that they're designed and where the where they're implemented and So this is what we might call structural inequity. By the way something is designed. It has certain effects that exclude or harm different people. And so it may not necessarily be the intense, but that's the effect. And I did a little digging, and I found, in fact, it's a global phenomenon, this thing that architects called hostile architecture. Er, I found single occupancy benches in Helsinki, so only one booty at a time no laying down there. I found caged benches in France. And in this particular town. What's interesting here is that the mayor put these benches out in this little shopping plaza, and within 24 hours the people in the town rallied together and had them removed. So we see here that just because we have, uh, discriminatory design in our public space doesn't mean we have to live with it. We can actually work together to ensure that our public space reflects our better values. But I think my favorite example of all is the meter bench. In this case, this bench is designed with spikes in them, and to get the spikes to retreat into the bench, you have to feed the meter you have to put some coins in, and I think it buys you about 15 or 20 minutes. Then the spikes come back up. And so you'll be happy to know that in this case, this was designed by a German artists to get people to think critically about issues of design, not just the design of physical space but the design of all kinds of things, public policies. And so we can think about how our public life in general is metered, that it serves those that can pay the price and others are excluded or harm, whether we're talking about education or health care. And the meter bench also presents something interesting. For those of us who care about technology, it creates a technical fix for a social problem. In fact, it started out his art. But some municipalities in different parts of the world have actually adopted this in their public spaces in their parks in order to deter so called lawyers from using that space. And so, by a technical fix, we mean something that creates a short term effect, right. It gets people who may want to sleep on it out of sight. They're unable to use it, but it doesn't address the underlying problems that create that need to sleep outside in the first place. And so, in addition to techno determinism, we have to think critically about technical fixes that don't address the underlying issues that technology is meant to solve. And so this is part of a broader issue of discriminatory design, and we can apply the bench metaphor to all kinds of things that we work with or that we create. And the question we really have to continuously ask ourselves is, What values are we building in to the physical and digital infrastructures around us? What are the spikes that we may unwittingly put into place? Or perhaps we didn't create the spikes. Perhaps we started a new job or a new position, and someone hands us something. This is the way things have always been done. So we inherit the spike bench. What is our responsibility when we noticed that it's creating these kinds of harms or exclusions or technical fixes that are bypassing the underlying problem? What is our responsibility? All of this came to a head in the context of financial technologies. I don't know how many of you remember these high profile cases of tech insiders and CEOs who applied for Apple, the Apple card and, in one case, a husband and wife applied and the husband, the husband received a much higher limit almost 20 times the limit as his wife, even though they shared bank accounts, they lived in Common Law State. And so the question. There was not only the fact that the husband was receiving a much better interest rate and the limit, but also that there was no mechanism for the individuals involved to dispute what was happening. They didn't even know what the factors were that they were being judged that was creating this form of discrimination. So in terms of financial technologies, it's not simply the outcome that's the issue. Or that could be discriminatory, but the process that black boxes, all of the decision making that makes it so that consumers and the general public have no way to question it. No way to understand how they're being judged adversely, and so it's the process not only the product that we have to care a lot about. And so the case of the apple cart is part of a much broader phenomenon of, um, racist and sexist robots. This is how the headlines framed it a few years ago, and I was so interested in this framing because there was a first wave of stories that seemed to be shocked at the prospect that technology is not neutral. Then there was a second wave of stories that seemed less surprised. Well, of course, technology inherits its creator's biases. And now I think we've entered a phase of attempts to override and address the default settings of so called racist and sexist robots, for better or worse. And here robots is just a kind of shorthand, that the way people are talking about automation and emerging technologies more broadly. And so as I was encountering these headlines, I was thinking about how these air, not problems simply brought on by machine learning or AI. They're not all brand new, and so I wanted to contribute to the conversation, a kind of larger context and a longer history for us to think carefully about the social dimensions of technology. And so I developed a concept called the New Jim Code, which plays on the phrase Jim Crow, which is the way that the regime of white supremacy and inequality in this country was defined in a previous era, and I wanted us to think about how that legacy continues to haunt the present, how we might be coding bias into emerging technologies and the danger being that we imagine those technologies to be objective. And so this gives us a language to be able to name this phenomenon so that we can address it and change it under this larger umbrella of the new Jim Code are four distinct ways that this phenomenon takes shape from the more obvious engineered inequity. Those were the kinds of inequalities tech mediated inequalities that we can generally see coming. They're kind of obvious. But then we go down the line and we see it becomes harder to detect. It's happening in our own backyards. It's happening around us, and we don't really have a view into the black box, and so it becomes more insidious. And so in the remaining couple minutes, I'm just just going to give you a taste of the last three of these, and then a move towards conclusion that we can start chatting. So when it comes to default discrimination. This is the way that social inequalities become embedded in emerging technologies because designers of these technologies aren't thinking carefully about history and sociology. Ah, great example of this came Thio headlines last fall when it was found that widely used healthcare algorithm affecting millions of patients, um, was discriminating against black patients. And so what's especially important to note here is that this algorithm healthcare algorithm does not explicitly take note of race. That is to say, it is race neutral by using cost to predict healthcare needs. This digital triaging system unwittingly reproduces health disparities because, on average, black people have incurred fewer costs for a variety of reasons, including structural inequality. So in my review of this study by Obermeyer and colleagues, I want to draw attention to how indifference to social reality can be even more harmful than malicious intent. It doesn't have to be the intent of the designers to create this effect, and so we have to look carefully at how indifference is operating and how race neutrality can be a deadly force. When we move on to the next iteration of the new Jim code coded exposure, there's attention because on the one hand, you see this image where the darker skin individual is not being detected by the facial recognition system, right on the camera or on the computer. And so coated exposure names this tension between wanting to be seen and included and recognized, whether it's in facial recognition or in recommendation systems or in tailored advertising. But the opposite of that, the tension is with when you're over included. When you're surveiled when you're to centered. And so we should note that it's not simply in being left out, that's the problem. But it's in being included in harmful ways. And so I want us to think carefully about the rhetoric of inclusion and understand that inclusion is not simply an end point. It's a process, and it is possible to include people in harmful processes. And so we want to ensure that the process is not harmful for it to really be effective. The last iteration of the new Jim Code. That means the the most insidious, let's say, is technologies that are touted as helping US address bias, so they're not simply including people, but they're actively working to address bias. And so in this case, There are a lot of different companies that are using AI to hire, create hiring software and hiring algorithms, including this one higher view. And the idea is that there there's a lot that AI can keep track of that human beings might miss. And so so the software can make data driven talent decisions. After all, the problem of employment discrimination is widespread and well documented. So the logic goes, Wouldn't this be even more reason to outsource decisions to AI? Well, let's think about this carefully. And this is the look of the idea of techno benevolence trying to do good without fully reckoning with what? How technology can reproduce inequalities. So some colleagues of mine at Princeton, um, tested a natural learning processing algorithm and was looking to see whether it exhibited the same, um, tendencies that psychologists have documented among humans. E. And what they found was that in fact, the algorithm associating black names with negative words and white names with pleasant sounding words. And so this particular audit builds on a classic study done around 2003, before all of the emerging technologies were on the scene where two University of Chicago economists sent out thousands of resumes to employers in Boston and Chicago, and all they did was change the names on those resumes. All of the other work history education were the same, and then they waited to see who would get called back. And the applicants, the fictional applicants with white sounding names received 50% more callbacks than the black applicants. So if you're presented with that study, you might be tempted to say, Well, let's let technology handle it since humans are so biased. But my colleagues here in computer science found that this natural language processing algorithm actually reproduced those same associations with black and white names. So, too, with gender coded words and names Amazon learned a couple years ago when its own hiring algorithm was found discriminating against women. Nevertheless, it should be clear by now why technical fixes that claim to bypass human biases are so desirable. If Onley there was a way to slay centuries of racist and sexist demons with a social justice box beyond desirable, more like magical, magical for employers, perhaps looking to streamline the grueling work of recruitment but a curse from any jobseekers, as this headline puts it, your next interview could be with a racist spot, bringing us back to that problem space we started with just a few minutes ago. So it's worth noting that job seekers are already developing ways to subvert the system by trading answers to employers test and creating fake applications as informal audits of their own. In terms of a more collective response, there's a federation of European Trade unions call you and I Global that's developed a charter of digital rights for work, others that touches on automated and a I based decisions to be included in bargaining agreements. And so this is one of many efforts to change their ecosystem to change the context in which technology is being deployed to ensure more protections and more rights for everyday people in the US There's the algorithmic accountability bill that's been presented, and it's one effort to create some more protections around this ubiquity of automated decisions, and I think we should all be calling from more public accountability when it comes to the widespread use of automated decisions. Another development that keeps me somewhat hopeful is that tech workers themselves are increasingly speaking out against the most egregious forms of corporate collusion with state sanctioned racism. And to get a taste of that, I encourage you to check out the hashtag Tech won't build it. Among other statements that they have made and walking out and petitioning their companies. Who one group said, as the people who build the technologies that Microsoft profits from, we refuse to be complicit in terms of education, which is my own ground zero. Um, it's a place where we can we can grow a more historically and socially literate approach to tech design. And this is just one, um, resource that you all can download, Um, by developed by some wonderful colleagues at the Data and Society Research Institute in New York and the goal of this interventionist threefold to develop an intellectual understanding of how structural racism operates and algorithms, social media platforms and technologies, not yet developed and emotional intelligence concerning how to resolve racially stressful situations within organizations, and a commitment to take action to reduce harms to communities of color. And so as a final way to think about why these things are so important, I want to offer a couple last provocations. The first is for us to think a new about what actually is deep learning when it comes to computation. I want to suggest that computational depth when it comes to a I systems without historical or social depth, is actually superficial learning. And so we need to have a much more interdisciplinary, integrated approach to knowledge production and to observing and understanding patterns that don't simply rely on one discipline in order to map reality. The last provocation is this. If, as I suggested at the start, inequity is woven into the very fabric of our society, it's built into the design of our. Our policies are physical infrastructures and now even our digital infrastructures. That means that each twist, coil and code is a chance for us toe. We've new patterns, practices and politics. The vastness of the problems that we're up against will be their undoing. Once we accept that we're pattern makers. So what does that look like? It looks like refusing color blindness as an anecdote to tech media discrimination rather than refusing to see difference. Let's take stock of how the training data and the models that we're creating have these built in decisions from the past that have often been discriminatory. It means actually thinking about the underside of inclusion, which can be targeting. And how do we create a more participatory rather than predatory form of inclusion? And ultimately, it also means owning our own power in these systems so that we can change the patterns of the past. If we're if we inherit a spiked bench, that doesn't mean that we need to continue using it. We can work together to design more just and equitable technologies. So with that, I look forward to our conversation. >>Thank you, Ruth. Ha. That was I expected it to be amazing, as I have been devouring your book in the last few weeks. So I knew that would be impactful. I know we will never think about park benches again. How it's art. And you laid down the gauntlet. Oh, my goodness. That tech won't build it. Well, I would say if the thoughts about team has any saying that we absolutely will build it and will continue toe educate ourselves. So you made a few points that it doesn't matter if it was intentional or not. So unintentional has as big an impact. Um, how do we address that does it just start with awareness building or how do we address that? >>Yeah, so it's important. I mean, it's important. I have good intentions. And so, by saying that intentions are not the end, all be all. It doesn't mean that we're throwing intentions out. But it is saying that there's so many things that happened in the world, happened unwittingly without someone sitting down to to make it good or bad. And so this goes on both ends. The analogy that I often use is if I'm parked outside and I see someone, you know breaking into my car, I don't run out there and say Now, do you feel Do you feel in your heart that you're a thief? Do you intend to be a thief? I don't go and grill their identity or their intention. Thio harm me, but I look at the effect of their actions, and so in terms of art, the teams that we work on, I think one of the things that we can do again is to have a range of perspectives around the table that can think ahead like chess, about how things might play out, but also once we've sort of created something and it's, you know, it's entered into, you know, the world. We need to have, ah, regular audits and check ins to see when it's going off track just because we intended to do good and set it out when it goes sideways, we need mechanisms, formal mechanisms that actually are built into the process that can get it back on track or even remove it entirely if we find And we see that with different products, right that get re called. And so we need that to be formalized rather than putting the burden on the people that are using these things toe have to raise the awareness or have to come to us like with the apple card, Right? To say this thing is not fair. Why don't we have that built into the process to begin with? >>Yeah, so a couple things. So my dad used to say the road to hell is paved with good intentions, so that's >>yes on. In fact, in the book, I say the road to hell is paved with technical fixes. So they're me and your dad are on the same page, >>and I I love your point about bringing different perspectives. And I often say this is why diversity is not just about business benefits. It's your best recipe for for identifying the early biases in the data sets in the way we build things. And yet it's such a thorny problem to address bringing new people in from tech. So in the absence of that, what do we do? Is it the outside review boards? Or do you think regulation is the best bet as you mentioned a >>few? Yeah, yeah, we need really need a combination of things. I mean, we need So on the one hand, we need something like a do no harm, um, ethos. So with that we see in medicine so that it becomes part of the fabric and the culture of organizations that that those values, the social values, have equal or more weight than the other kinds of economic imperatives. Right. So we have toe have a reckoning in house, but we can't leave it to people who are designing and have a vested interest in getting things to market to regulate themselves. We also need independent accountability. So we need a combination of this and going back just to your point about just thinking about like, the diversity on teams. One really cautionary example comes to mind from last fall, when Google's New Pixel four phone was about to come out and it had a kind of facial recognition component to it that you could open the phone and they had been following this research that shows that facial recognition systems don't work as well on darker skin individuals, right? And so they wanted Thio get a head start. They wanted to prevent that, right? So they had good intentions. They didn't want their phone toe block out darker skin, you know, users from from using it. And so what they did was they were trying to diversify their training data so that the system would work better and they hired contract workers, and they told these contract workers to engage black people, tell them to use the phone play with, you know, some kind of app, take a selfie so that their faces would populate that the training set, But they didn't. They did not tell the people what their faces were gonna be used for, so they withheld some information. They didn't tell them. It was being used for the spatial recognition system, and the contract workers went to the media and said Something's not right. Why are we being told? Withhold information? And in fact, they told them, going back to the park bench example. To give people who are homeless $5 gift cards to play with the phone and get their images in this. And so this all came to light and Google withdrew this research and this process because it was so in line with a long history of using marginalized, most vulnerable people and populations to make technologies better when those technologies are likely going toe, harm them in terms of surveillance and other things. And so I think I bring this up here to go back to our question of how the composition of teams might help address this. I think often about who is in that room making that decision about sending, creating this process of the contract workers and who the selfies and so on. Perhaps it was a racially homogeneous group where people didn't want really sensitive to how this could be experienced or seen, but maybe it was a diverse, racially diverse group and perhaps the history of harm when it comes to science and technology. Maybe they didn't have that disciplinary knowledge. And so it could also be a function of what people knew in the room, how they could do that chest in their head and think how this is gonna play out. It's not gonna play out very well. And the last thing is that maybe there was disciplinary diversity. Maybe there was racial ethnic diversity, but maybe the workplace culture made it to those people. Didn't feel like they could speak up right so you could have all the diversity in the world. But if you don't create a context in which people who have those insights feel like they can speak up and be respected and heard, then you're basically sitting on a reservoir of resource is and you're not tapping into it to ensure T to do right by your company. And so it's one of those cautionary tales I think that we can all learn from to try to create an environment where we can elicit those insights from our team and our and our coworkers, >>your point about the culture. This is really inclusion very different from just diversity and thought. Eso I like to end on a hopeful note. A prescriptive note. You have some of the most influential data and analytics leaders and experts attending virtually here. So if you imagine the way we use data and housing is a great example, mortgage lending has not been equitable for African Americans in particular. But if you imagine the right way to use data, what is the future hold when we've gotten better at this? More aware >>of this? Thank you for that question on DSO. You know, there's a few things that come to mind for me one. And I think mortgage environment is really the perfect sort of context in which to think through the the both. The problem where the solutions may lie. One of the most powerful ways I see data being used by different organizations and groups is to shine a light on the past and ongoing inequities. And so oftentimes, when people see the bias, let's say when it came to like the the hiring algorithm or the language out, they see the names associated with negative or positive words that tends toe have, ah, bigger impact because they think well, Wow, The technology is reflecting these biases. It really must be true. Never mind that people might have been raising the issues in other ways before. But I think one of the most powerful ways we can use data and technology is as a mirror onto existing forms of inequality That then can motivate us to try to address those things. The caution is that we cannot just address those once we come to grips with the problem, the solution is not simply going to be a technical solution. And so we have to understand both the promise of data and the limits of data. So when it comes to, let's say, a software program, let's say Ah, hiring algorithm that now is trained toe look for diversity as opposed to homogeneity and say I get hired through one of those algorithms in a new workplace. I can get through the door and be hired. But if nothing else about that workplace has changed and on a day to day basis I'm still experiencing microaggressions. I'm still experiencing all kinds of issues. Then that technology just gave me access to ah harmful environment, you see, and so this is the idea that we can't simply expect the technology to solve all of our problems. We have to do the hard work. And so I would encourage everyone listening to both except the promise of these tools, but really crucially, um, Thio, understand that the rial kinds of changes that we need to make are gonna be messy. They're not gonna be quick fixes. If you think about how long it took our society to create the kinds of inequities that that we now it lived with, we should expect to do our part, do the work and pass the baton. We're not going to magically like Fairy does create a wonderful algorithm that's gonna help us bypass these issues. It can expose them. But then it's up to us to actually do the hard work of changing our social relations are changing the culture of not just our workplaces but our schools. Our healthcare systems are neighborhoods so that they reflect our better values. >>Yeah. Ha. So beautifully said I think all of us are willing to do the hard work. And I like your point about using it is a mirror and thought spot. We like to say a fact driven world is a better world. It can give us that transparency. So on behalf of everyone, thank you so much for your passion for your hard work and for talking to us. >>Thank you, Cindy. Thank you so much for inviting me. Hey, I live back to you. >>Thank you, Cindy and rou ha. For this fascinating exploration of our society and technology, we're just about ready to move on to our final session of the day. So make sure to tune in for this customer case study session with executives from Sienna and Accenture on driving digital transformation with certain AI.

>>Yeah, yeah. >>Hello and welcome back. I hope you're ready for our next session. Become the analyst of the future. We'll hear the customer's perspective about their increasingly strategic role and the potential career growth that comes with it. Joining us today are Nate Weaver, director of product marketing at Thought Spot. Yasmin Natasa, senior director of national sales strategy and insights over at Comcast and Steve Would Ledge VP of customer and partner initiatives. Oughta Terex. We're so happy to have you all here today. I'll hand things over to meet to kick things off. >>Yeah, thanks, Paula. I'd like to start with a personal story that might resonate with our audience, says an analyst. Early in my career, I was the intermediary between the business and what we called I t right. Basically database administrators. I was responsible for understanding business logic gathering requirements, Ringling data building dashboards for executives and, in my case, 100 plus sales reps. Every request that came through the business intelligence team. We owned everything, right? Indexing databases for speed, S s. I s packages for data transfer maintaining Department of Data Lakes all out cubes, etcetera. We were busy. Now we were constantly building or updating something. The worst part is an analyst, If you ask the business, every request took too long. It was slow. Well, from an analyst perspective, it was slow because it's a complex process with many moving parts. So as an analyst fresh out of grad school often felt overeducated, sometimes underappreciated, like a report writer, we were constantly overwhelmed by never ending ad hoc request, even though we had hundreds of reports and robust dashboards that would answer 90% of the questions. If the end user had an analytical foundation like I did right, if they knew where to look and how to navigate dimensions and hierarchies, etcetera. So anyway, point is, we had to build everything through this complex and slow, um, process. So for the first decade of my career, I had this gut feeling there had to be a better way, and today we're going to talk about how thought SWAT and all tricks are empowering the analysts of the future by reimagining the entire data pipeline. This paradigm shift allows businesses and data teams thio, connect, transform, model and, most importantly, automate what used to be this terribly complex data analysis process. With that, I'd like to hand it over to Steve to describe the all tricks analytic process automation platform and how they help analysts create more robust data sets that enable non technical end users toe ask and answer their own questions, but also more sophisticated business questions. Using Search and AI Analytics in Thoughts Fire Steve over to you. >>Thanks for that really relevant example. Nate and Hi, everyone. I'm Steve. Will it have been in the market for about 20 years, and then Data Analytics and I can completely I can completely appreciate what they was talking about. And what I think is unique about all tricks is how we not only bring people to the data for a self service environment, but I think what's often missed in analytics is the automation and figure out. What is the business process that needs to be repeated and connecting the dots between the date of the process and the people To speed up those insights, uh, to not only give people to self service, access to information, to do data prep and blending, but more advanced analytics, and then driving that into the business in terms of outcomes. And I'll show you what that looks like when you talk about the analytic process automation platform on the next slide. What we've done is we've created this end to end workflow where data is on the left, outcomes around the right and within the ultras environment, we unify data prep and blend analytics, data science and process automation. In this continuous process, so is analysis or an end user. I can go ahead and grab whatever data is made available to me by i t. You have got 80 plus different inputs and a p i s that we connect to. You have this drag and drop environment where you conjoined the data together, apply filters, do some descriptive analytics, even do things like grab text documents and do sentiments analysis through that with text, mining and natural language processing. As people get more used to the platform and want to do more advanced analytics and process automation, we also have things like assisted machine learning and predictive analytics out of the box directly within it as well and typically within organizations. These would be different departments and different tools doing this and we try to bring all this together in one system. So there's 260 different automation building blocks again and drag a drop environment. And then those outcomes could be published into a place where thoughts about visualizes that makes it accessible to the business users to do additional search based B I and analytics directly from their browser. And it's not just the insights that you would get from thought spot, but a lot of automation is also driving unattended, unattended or automated actions within operational systems. If you take an example of one of our customers that's in the telecommunications world, they drive customer insights around likeliness to turn or next best offers, and they deliver that within a salesforce applications. So when you walk into a retail store for your cell phone provider, they will know more about you in terms of what services you might be interested in. And if you're not happy at the time and things like that. So it's about how do we connect all those components within the business process? And what this looks like is on this screen and I won't go through in detail, but it's ah, dragon drop environment, where everything from the input data, whether it's cloud on Prem or even a local file that you might have for a spreadsheet. Uh, I t wants to have this environment where it's governed, and there's sort of components that you're allowed to have access to so that you could do that data crept and blending and not just data within your organization, but also then being able to blend in third party demographic data or firm a graphic information from different third party data providers that we have joined that data together and then do more advanced analytics on it. So you could have a predictive score or something like that being applied and blending that with other information about your customer and then sharing those insights through thought spots and more and more users throughout the organization. And bring that to life. In addition to you, as we know, is gonna talk about her experience of Comcast. Given the world that we're in right now, uh, hospital care and the ability to have enough staff and and take care of all of our people is a really important thing. So one of our customers, a large healthcare network in the South was using all tricks to give not only analyst with the organization, but even nurses were being trained on how to use all tricks and do things like improve observation. Wait time eso that when you come in, the nurse was actually using all tricks to look at the different time stamps out of ethic and create a process for the understands. What are all the causes for weight in three observation room and identify outliers of people that are trying to come in for a certain type of care that may wait much longer than on average. And they're actually able to reduce their wait time by 22%. And the outliers were reduced by about 50% because they did a better job of staffing. And overall staffing is a big issue if you can imagine trying to have a predictive idea of how many staff you need in the different medical facilities around the network, they were bringing in data around the attrition of healthcare workers, the volume of patient load, the scheduled holidays that people have and being able to predict 4 to 6 months out. What are the staff that they need to prepare toe have on on site and ready so they could take care of the patients as they're coming in. In this case, they used in our module within all tricks to do that, planning to give HR and finance a view of what's required, and they could do a drop, a drop down by department and understand between physicians, nurses and different facilities. What is the predicted need in terms of staffing within that organization? So you go to the next slide done, you know, aside from technology, the number one thing for the analysts of the future is being able to focus on higher value business initiatives. So it's not just giving those analysts the ability to do this self service dragon drop data prep and blend and analytics, but also what are the the common problems that we've solved as a community? We have 150,000 people in the alter its community. We've been in business for over 23 years, so you could go toe this gallery and not only get things like the thought spot tools that we have to connect so you can do direct query through T Q l and pushed it into thought spot in Falcon memory and other things. But look at things like the example here is the healthcare District, where we have some of our third party partners that have built out templates and solutions around predictive staffing and tracking the complicating conditions around Cove. It as an example on different KPs that you might have in healthcare, environment and retail, you know, over 150 different solution templates, tens of thousands of different posts across different industries, custom return and other problems that we can solve, and bringing that to the community that help up level, that collective knowledge, that we have this business analyst to solve business problems and not just move data, and then finally, you know, as part of that community, part of my role in all tricks is not only working with partners like thought spot, but I also share our C suite advisory board, which we just happen to have this morning, as a matter of fact, and the number one thing we heard and discussed at that customer advisory board is a round up Skilling, particularly in this virtual world where you can't do in classroom learning how do we game if I and give additional skills to our staff so that they can digitize and automate more and more analytic processes in their organization? I won't go through all this, but we do have learning paths for both beginners. A swell as advanced people that want to get more into the data science world. And we've also given back to our community. There's an initiative called Adapt where we've essentially donated 125 hours of free training free access to our products. Within the first two weeks, we've had over 9000 people participate in that get certified across 100 different companies and then get jobs in this new world where they've got additional skills now around analytics. So I encourage you to check that out, learn what all tricks could do for you in up Skilling your journey becoming that analysts of the future And thanks for having me today thoughts fun looking forward to the rest of conversation with the Azmin. >>Yeah, thanks. I'm gonna jump in real quick here because you just mentioned something that again as an analyst, is incredibly important. That's, you know, empowering Mia's an analyst to answer those more sophisticated business questions. There's a few things that you touched on that would be my personal top three. Right? Is an analyst. You talked about data cleansing because everyone has data quality problems enhancing the data sets. I came from a supply chain analytics background. So things like using Dun and Bradstreet in your examples at risk profiles to my supplier data and, of course, predictive analytics, like creating a forecast to estimate future demand. These are things that I think is an analyst. I could truly provide additional value. I'd like to show you a quick example, if I may, of the type of ad hoc request that I would often get from the business. And it's fairly complex, but with a combination of all tricks and thought spots very easy to answer. Crest. The request would look something like this. I'd like to see my spend this year versus last year to date. Uh, maybe look at that monthly for Onley, my area of responsibility. But I only want to focus on my top five suppliers from this year, right? And that's like an end statement. I saw that in one of your slides and so in thoughts about that's answering or asking a simple question, you're getting the answer in maybe 30 seconds. And that's because behind the scenes, the last part is answering those complexities for you. And if I were to have to write this out in sequel is an analyst, it could take me upwards, maybe oven our because I've got to get into the right environment in the database and think about the filters and the time stamps, and there's a lot going on. So again, thoughts about removes that curiosity tax, which when becoming the analysts of the future again, if I don't have to focus on the small details that allows me to focus on higher value business initiatives, right. And I want to empower the business users to ask and answer their own questions. That does come with up Skilling, the business users as well, by improving data fluency through education and to expand on this idea. I wanna invite Yasmin from Comcast to kind of tell her personal story. A zit relates to analysts of the future inside Comcast. >>Well, thank you for having me. It's such a pleasure. And Steve, thank you so much for starting and setting the groundwork for this amazing conversation. You hit the nail on the head. I mean, data is a Trojan horse off analytics, and our ability to generate that inside is eyes busy is anchored on how well we can understand the data on get the data clean It and tools, like all tricks, are definitely at the forefront off ability to accelerate the I'll speak to incite, which is what hot spot brings to the table. Eso My story with Thought spot started about a year and a half ago as I'm part of the Sales Analytics team that Comcast all group is officially named, uh, compensation strategy and insight. We are part of the Consumer Service, uh, Consumer Service expected Consumer Service group in the cell of Residential Sales Organization, and we were created to provide insight to the Comcast sells channel leaders Thio make sure that they have database insight to drive sales performance, increased revenue. We When we started the function, we were really doing a lot of data wrangling, right? It wasn't just a self performance. It waas understanding who are customers were pulling a data on productivity. Uh, so we were going into HR systems are really going doing the E T l process, but manually sometimes. And we took a pause at one point because we realized that we're spending a good 70% of our time just doing that and maybe 5% of our time storytelling. Now our strength was the storytelling. And so you see how that balance wasn't really there. And eso Jim, my leader pause. It pulls the challenge of Is there a better way of doing this on DSO? We scan the industry, and that's how we came across that spot. And the first time I saw the tool, I fell in love. There's not a way for me to describe it. I fell in love because I love the I love the the innovation that it brought in terms of removing the middleman off, having to create all these layers between the data and me. I want to touch the data. I want to feel it, and I want to ask questions directly to it, and that's what that's what does for us. So when we launched when we launch thoughts about for our team, we immediately saw the difference in our ability to provide our stakeholders with better answers faster. And the combination of the two makes us actually quite dangerous right on. But it has been It has been a great great journey altogether are inter plantation was done on the cloud because at the time, uh, the the we had access to AWS account and I love to be at the edge of technology, So I figured it would be a good excuse for me to learn more about cloud technology on its been things. Video has been a great journey. Um, my, my background, uh, into analytics comes from science. And so, for me, uh, you know, we are really just stretching the surface off. What is possible in terms off the how well remind data to answer business questions on Do you know, tools like thought spot in combination with technologies. Like all trades, eyes really are really the way to go about it. And the up skilling, um the up skilling off the analysts that comes with it is really, really, really exciting because people who love data want to be able to, um want to be efficient about how they spend time with data. Andi and that's what? That's what I spend a lot of my Korea I'd Comcast and before Comcast doing so It gives me a lot of ah, a lot of pleasure to, um to bring that to my organization and to walk with colleagues outside off. We didn't Comcast to do so The way we the way we use stops, that's what we did not seem is varies. One of the things that I'm really excited about is integrating it with all the tools that we have in our analytics portfolio, and and I think about it as the over the top strategy. Right. Uh, group, like many other groups, wouldn't Comcast and with our organizations also used to be I tools. And it is not, um, you choose on a mutually exclusive strategies, right? Eso In our world, we build decision making, uh, decision making tools from the analysis that we generate. When we have the read out with the cells channel leaders, we we talk about the insight, and invariably there's some components off those insight that they want to see on a regular basis. That becomes a reporting activity. We're not in a reporting team. We partner with reporting team for them to think that input and and and put it on and create a regular cadence for it. Uh, the over the top strategy for me is, um, are working with the reporting team to then embed the link to talk spot within the report so that the questions that can be answered by the reports left dashboard are answered within the dashboard. But we make sure that we replicate the data source that feeds that report into thought spot so that the additional questions can then be insert in that spot. It and it works really well because it creates a great collaboration with our partners on the on the reporting side of the house on it also helps of our end the end users do the cell service in along the analytic spectrum, right? You go to the report when you can, when all you need is dropped down the filters and when the questions become more sophisticated, you still have a platform in the place to go to ask the questions directly and do things that are a bit funk here, like, you know, use for like you because you don't know what you're looking for. But you know that there's there's something there to find. >>Yeah, so yeah, I mean, a quick question. Our think would be on this year's analytics meet Cloud open for everyone and your experience. What does that mean to you? Including in the context of the thought spot community inside Comcast? >>Oh yes, it's the Comcast community. The passport commedia Comcast is very vibrant. My peers are actually our colleagues, who I have in my analytics village prior to us getting on board with hot spot and has been a great experience for us. So have thoughts, but as an additional kind of topic Thio to connect on. So my team was the second at Comcast to implement that spot. The first waas, the product team led by Skylar, and he did his instance on Prem. Um, he the way that he brings his data is, is through a sequel server. When I came what, as I mentioned earlier, I went on the cloud because, as I mentioned earlier, I like to be on the edge of technology and at the time thought spot was moving towards towards the cloud. So I wanted to be part of that wave. There's Ah, mobile team has a new instance that is on the cloud thing. The of the compliance team uses all tricks, right? And the S O that that community to me is really how the intellectual capital that we're building, uh, using thought spot is really, really growing on by what happens to me. And the power of being on the cloud is that if we are all using the same tool, right and we are all kind of bringing our data together, um, we are collaborating in ways that make the answer to the business questions that the C suite is asking much better, much richer. They don't always come to us at the same time, right? Each function has his own analytics group, Andi. Sometimes if we are not careful, we're working silo. But the community allows us to know about what each other are working on. And the fact that we're using the same tool creates a common language that translates into opportunities for collaboration, which will translate into, as I mentioned earlier, richer better on what comprehensive answers to the business. So analyst Nick the cloud means better, better business and better business answers and and better experiences for customers at the end of the day, so I'm all for it. >>That's great. Yeah. Comcast is obviously a very large enterprise. Lots of data sources, lots of data movement. It's cool to hear that you have a bit of a hybrid architecture, er thought spot both on premise. Stand in the cloud and you did bring up one other thing that I think is an important question for Steve. Most people may just think of all tricks as an E T l tool, but I know customers like Comcast use it for way more than just that. Can you expand upon the differences between what people think of a detail tool and what all tricks is today? >>Yeah, I think of E. T L tools as sort of production class source to target mapping with transformations and data pipelines that air typically built by I t. To service, you know, major areas within the business, and that's super valuable. One doesn't go away, and in all tricks can provide some of that. But really, it's about the end user empowerment. So going back to some of guys means examples where you know there may be some new information that you receive from a third party or even a spreadsheet that you develop something on. You wanna start to play around that information so you can think of all the tricks as a data lab or data science workbench, in fact, that you know, we're in the Gartner Magic Quadrant for data science and machine learning platforms. Because a lot of that innovation is gonna happen at the individual level we're trying to solve. And over time, you might want to take that learning and then have I t production eyes it within another system. But you know, there's this trade off between the agility that end users need and sort of the governance that I t needs to bring. So we work best in a environment where you have that in user autonomy. You could do E tail workloads, data prep and Glenn bringing your own information on then work with i t. To get that into the right server based environment to scale out in the thought spot and other applications that you develop new insights for the business. So I see it is ah, two sides of the same coin. In many ways, a home. And >>with that we're gonna hand it back over to a Paula. >>Thank you, Nate, Yasmin and Steve for the insights into the journey of the analyst of the future. Next up in a couple minutes, is our third session of today with Ruhollah Benjamin, professor of African American Studies at Princeton University, and our chief data strategy officer, Cindy House, in do a couple of jumping jacks or grab a glass of water and don't miss out on the next important discussion about diversity and data.

>> Narrator: From around the globe, it's theCUBE with coverage of the Global .NEXT Digital Experience brought to you by Nutanix. >> Welcome back, I'm Stu Miniman and this is theCUBE's coverage of the Nutanix .NEXT Digital Experience. We've got two of the c-suite here to really dig into some of the strategy and partnerships talked at their annual user conference. Happy to welcome back to the program two of our CUBE alumni first of all, we have Tarkan Maner. He is the Chief Customer Officer at Nutanix and joining us also Rajiv Mirani, he is the Chief Technology Officer, CTO. Rajiv, Tarkan, great to see you both. Thanks so much for joining us on theCUBE. >> Great to be back. >> Good to see you. >> All right. So Tarkan talk about a number of announcements. You had some big partner executives up on stage. As I just talked with Monica about, Scott Guthrie wearing the signature red polo, you had Kirk Skaugen from Lenovo of course, a real growing partnership with Nutanix, a bunch of others and even my understanding the partner program for how you go to market has gone through a lot. So a whole lot of stuff to go into, partnerships, don't need to tackle it all here upfront, but give us some of the highlights from your standpoint. >> I'll tell this to my dear friend Rajiv and I've been really busy, last few months and last 12 months have been super, super busy for us. And as you know, the latest announcements we made the new $750 million investment from Bain capital, amazing if by 20 results, Q4, big results. And obviously in the last few months big announcements with AWS as part of our hybrid multicloud vision and obviously Rajiv and I, we're making sale announcements, product announcements, partner announcements at .NEXT. So at a high level, I know Rajiv is going to cover this a little bit more in detail, but we covered everything under these three premises. Run better, run faster and run anywhere. Without stealing the thunder from Rajiv, but I just want to give you at a high level a little bit. What excites us a lot is obviously the customer partner intimacy and all this new IP innovation and announcement also very strong, very tight operational results and operational execution makes the company really special as a independent software vendor in this multicloud era. Obviously, we are the only true independent software vendor to do not run a business in a sense with fast growth. Timed to that announcement chain we make this big announcement with Azure partnership, our Nutanix portfolio under the Nutanix cluster ran now available as Bare-Metal Service on Azure after AWS. The partnership is new with Azure. We just announced the first angle of it. Limited access customers are taking it to look at the service. We're going to have a public preview in a few months, and more to come. And obviously we're not going to stop there. We have tons of work going on with other cloud providers, as well. Tying that, obviously, big focus with our Citrix partnership globally around our end user computing business as Rajiv will outline further, our portfolio on top of our digital infrastructure, tying the data center services, DevOps services, and you user computing services, Citrix partnership becomes a big one, and obviously you're tying the Lenovo and HP partnership to these things as the core platforms to run that business. It's creating tons of opportunity and I'll cover a little bit more further in a bit more detail, but one other partnership we are also focusing on, our Google partnership and on desktop as a service. So these are all coming to get around data center, DevOps, and user competent services on top of that amazing infrastructure Rajiv and team built over the past 10 years. I see Rajiv as one of our co-founders and one side with the right another. So the business is obviously booming in multiple fronts. This, if by 2020 was a great starting point with all this investment, that bank capital $750 million, big execution, ACD transition, software transition. And obviously these cloud partnerships are going to make big differences moving forward. >> Yeah, so Rajiv, want to build off what Tarkan was just saying there, that really coming together, when I heard the strategy run better, run faster, run anywhere, it really pulled together some of the threads I've been watching at Nutanix the last couple of years. There's been some SaaS solutions where it was like, wait, I don't understand how that ties back to really the core of what Nutanix does. And of course, Nutanix is more than just an HCI company, it's software and that simplicity and the experience as your team has always said, trying to make things invisible, but help if you would kind of lay out, there's a lot of announcements, but architecturally, there were some significant changes from the core, as well as, if I'm reading it right, it feels like the portfolio has a little bit more cohesion than I was seeing a year or so ago. >> Yeah, actually the theme around all these announcements is the same really, it's this ability to run any application, whether it's the most demanding traditional applications, the SAP HANA, the Epics and so on, but also the more modern cloud native application, any kind of application, we want the best platform. We want a platform that's simple, seamless, and secure, but we want to be able to run every application, we want to run it with great performance. So if you look at the announcements that are being made around strengthening the core with the Block Store, adding things like virtual networking, as well as announcements we made around building Karbon platform services, essentially making it easier for developers to build applications in a new cloud native way, but still have the choice of running them on premises or in the cloud. We believe we have the best platform for all of that. And then of course you want to give customers the optionality to run these applications anywhere they want, whether that's a private cloud, their own private data centers and service providers, or in the public cloud and the hyperscalers. So we give them that whole range of choices, and you can see that all the announcements fit into that one theme: any application, anywhere, that's basically it. >> Well, I'd like you to build just a little bit more on the application piece. The developer conversation is something we've been hearing from Nutanix the last couple of years. We've seen you in the cloud native space. Of course, Karbon is your Kubernetes offering. So the line I used a couple of years ago at .NEXT was modernize the platform, then you can modernize all of your applications on top of it, so where does Nutanix touch the developer? You know, how does that, building new apps, modernizing my apps tie into the Nutanix discussion? >> Yeah great question, Stu. So last year we introduced Karbon for the first time. And if you look at Karbon, the initial offering was really targeted at an IT audience, right? So it's basically the goal was to make Kubernetes management itself very easy for the IT professional. So essentially, whether you were creating a Nutanix, sorry, a Karbon cluster, or scaling it out or upgrading Kubernetes itself. We wanted to make that part of the life cycle very, very simple for IT. For the developer we offered the Vanilla Kubernetes system. And this was something that developers asked us for again and again, don't go around mucking around with Kubernetes itself, we want Vanilla Kubernetes, we want to use our Kube Cuddle or the tools that we're used to. So don't go fork off and build the economic Kubernetes distribution. That's the last thing we want. So we had a good platform already, but then we wanted to take the next step because very few applications today are self contained in the sense that they run entirely within themselves without dependence on external services, especially when you're building in the cloud, you have access, suppose you're building an Amazon, you have access to RDS to manage your databases. Don't have to manage it yourself. Your object stores, data pipelines, all kinds of platform services available, which really can accelerate development of your own applications, right? So we took the stand said, look, this is good. This is important. We want to give developers the same kind of services, but we want to make it much more democratic in the sense that we want them to be able to run these applications anywhere, not just on AWS or not just on GCP. And that's really the genesis of Kubernetes platform services. We've taken the most common services people use in the cloud and made them available to run anywhere. Public cloud, private cloud, anywhere. So we think it's very exciting. >> Tarkan, we had, you and I had a discussion with one of your partners on how this hybrid cloud scenario is playing out at HP discover, of course, with the GreenLake solution. I'm curious from your standpoint, all the things that Rajiv was just talking about, that's a real change, if you think about kind of the traditional infrastructure people they're needing to move up the stack. You've got partnerships with the hyperscalers. So help explain a little bit the ripple effect as Nutanix helps customers simplify and modernize, how your partners and your channel can still participate. >> So perfect, look, as you heard from Rajiv, this is like all coming super nicely together. As Rajiv outlined, with the data center, operations and services, DevOps services, to enable that faster time to market capable, that Kubernetes offering and user services, our desktop services on top of that classical industry-leading, record-breaking digital infrastructure. That hybrid cloud infrastructure we call today. You play this game with devoting a little bit, as you remember, we used to call hyper-converged infrastructure. Now we call it of the hybrid cloud infrastructure, in a sense. All those pieces coming together nicely end-to-end, unlike any other vendor, and from a software only perspective, we're not owned by a hardware company which is making a huge difference. Gives us tremendous level of flexibility, democratization, and freedom of choice. Cloud to us is basically is not a destination. It's an operating model. You heard me say this before, as Rajiv also said. So in our strategy, when you look at it, Stu, we have a three pronged approach on top of our on-prem, marketplace on-prem capable. There's been 17,000+ customers, 7,000+ channel and strategic partners. Also as part of this big announcement, this new partner program we called Elevate, on the Elevate brand, bringing all the channel partners, ISEs, platform partners, hyperscalers, Telco XPSs, and our global market partners all in one bucket where we manage them, simply the incentives. It's a very simple way to execute that opposite Chris Kaddaras, our Chief Revenue Officer, as well as Christian Alvarez, our Chief Partner Officer sort of speaking on global goal, the channels, working together tightly with our organization on the product front to deliver this. So one key point I want to share with you, tying to what Rajiv said earlier on the multicloud area, obviously we realize customers are looking for freedom of choice. So we have our own cloud, Nutanix cloud, under the XI brand. X-I, XI brand, which is basically our own logistics, our own basically, serviceability, payment capability and our software, running off our portal partnerships like Equinix delivering that software as a service. We started with disaster recovery as a service, very fast growing business. Now we announced our GreenLake partnership with HPE in the backend that data center as a service might be actually HP GreenLake if the customer wants it. So that partnership creates huge opportunities for us. Obviously, on top of that, we have these Telco XSP partnerships. As we're announcing partnerships with some amazing source providers like OBH. You heard today from college Sudani in society general, they are not only using AWS and Azure and Nutanix on-prem and Nutanix clusters on Azure and AWS for their internal departments, but they also use a local service provider in France for data gravity and data security reasons. A French company dealing with French business and data centers, with that kind of data governance requirements within the country, within the borders of France. So in that context we are also the service provider partnerships coming in. We're going to announce a partnership with OVHS vault, which is a big deal for us. And tying to this, as Rajiv talked about, our clusters portfolio, our portfolio basically running on-prem on AWS and Azure. And we're not going to stop there obviously. So give choice to the customers. So as Rajiv said, basically, Nutanix can run anywhere. On top of that we announced just today with Capgemini, a new dev test environment is a service. Where Rajiv's portfolio, end-to-end, data center, DevOps, and some of the UC capabilities for dev test reasons can run as a service on Capgemini cloud. We have similar partnerships with HCL, similar partnerships with (indistinct) and we're super excited for this .NEXT in FI21 because of those reasons. >> Rajiv, one of the real challenges we've had for a long time is, I want to be able to have that optionality. I want to be able to live in any environment. I don't want to be stuck in an environment, but I want to be able to take advantage of the innovation and the functionality that's there. Can you give us a little bit of insight? How do you make sure that Nutanix can live these environments like the new Azure partnership and it has the Nutanix experience, yet I can take advantage of, whether it be AI or some other capabilities that a Google, an Amazon or a Microsoft has. How do you balance that? You have to integrate with all of these partners yet, not lock out the features that they keep adding. >> Right, absolutely, that's a great point, Stu. And that's something we pride ourselves on, that we're not taking shortcuts. We're not trying to create our own bubble in these hyperscalers, where we run in an isolated environment and can't interact with the rest of the services they offer. And that's primarily why we have spent the time and the effort to integrate closely with their virtual networking, with the services that they provide and essentially offer the best of both worlds. We take the Nutanix stack, the entire software stack, everything we build from top to bottom, make it available. So the same experience is there with upgrades and prism, the same experience is available on-prem and in the cloud. But at the same time, as you said, we want people to have full speed access to cloud services. There's things the cloud is doing that will be very difficult for anybody to do. I mean, the kind of thing that, say Google does with AI, or Azure does with databases. It's remarkable what these guys are doing, and you want to take advantage of those services. So for us, it's very, very important, that access is not constrained in any way, but also that customers have the time to make this journey, right? If they want to move to cloud today, they can do that. And then they can refactor and redevelop their applications over time and start consuming these sales. So it's not an all or nothing proposition. It's not that you have to refactor it, rewrite before you can move forward. That's been extremely important for us and it's really topical right now, especially with this pandemic. I think one thing all of IT has realized is that you have to be agile. You have to be able to react to things and timeframes you never thought you needed to, right. So it's not just disaster recovery, but the amount of effort that's gone in the last few months in enabling a distributed workforce, who thought it would happen so quickly? But it's a kind of agility that, an optionality that we are giving to customers that really makes it possible. >> Yeah, absolutely. Right now, things are moving pretty fast. So let me let both of you have the final word. Give us a little bit viewpoint, as things are moving fast, what's on the plate? What should we be expecting to see from Nutanix and your ecosystem through the rest of 2020, Tarkan? >> So look, heard from us, Stu, I know you're talking to multiple folks and you had this discussions with us, end-to-end, and look for the company to be successful, customer partner intimacy, IP innovation, and execution, and operational excellence. Obviously, all three things need to come together. So in a sense, Stu, we just need to keep moving. I give this analogy a lot, as Benjamin Franklin says, the human beings are divided in three categories, you know? The first one is those who are immovable. They never move. Second category, those who, you know, are movable, you can move them if you try hard. And obviously third category, those who just move. Not only themselves, but they move others, like in a sense, in a nice way to refer to Benjamin Franklin, with one of our key founders in the US, in a sense as the founders of this company, with folks like Rajiv and other executives, and some of the newcomers, we a culture, which just keeps moving and the last 12 months, you've seen some of these. And obviously going back to the announcement day, AWS, now Azure, the Capgemini announcement then test as a service around some of the portfolio that Rajiv talked about or a Google partnership on desktop as a service, deep focus on Citrix globally with Azure, Google, and ourselves on-prem, off-prem. And obviously some of the big moves were making with some of the customers, it's going to continue. This is just the beginning. I mean, literally Rajiv and I are doing these .NEXT conferences, announcements, and so on. We're actually doing calls right now to basically execute for the next 12 months. We're planning the next 12 months' execution. So we're super excited now with this new Bain Capital investment, and also the partnership, the product, we're ready to rock and roll. So look forward to seeing you soon, Stu, and we're going to have more news to cover with you. >> Yeah, exactly right, Tarkan. I think as Tarkan said we are at the beginning of a journey right now. I think the way hybrid cloud is now becoming seamless opens up so many possibilities for customers, things that were never possible before. Most people when they talk hybrid cloud, they're talking about fairly separate environments, some applications running in the public cloud, some running on premises. Applications that are themselves hybrid that run across, or that can burst from one to the other, or can move around with both app and data mobility. I think the possibilities are huge. And it's going to be many years before we see the full potential of this platform. >> Well Rajiv and Tarkan, thank you so much for sharing all of the updates, congratulations on the progress, and absolutely look forward to catching up in the near future and watching the journey. >> Thanks, Stu. >> Thank you, Stu. >> And stay with us for more coverage here from the Nutanix .NEXT digital experience. I'm Stu Miniman, and as always, thank you for watching theCUBE. (bright music)

>> From the Silicon Angle Media Office in Boston, Massachusetts, it's the Cube. Now here's your host Stu Miniman. >> Hi, I'm Stu Miniman and welcome to the Cube's Boston area studio. This is a Cube conversation. Happy to welcome to the program first time guest Benjamin Nye, CEO of Turbonomic, a Boston-based company. Ben, thanks so much for joining us. >> Stu, thanks for having me. >> Alright Ben, so as we say, we are fortunate to live in interesting times in our industry. Distributed architectures are what we're all working on, but at the same day, there's a lot of consolidation going on. You know, just put this in context. Just in recent past, IBM spent 34 billion dollars to buy Red Hat. And the reason I bring that up is a lot of people talk about you know, it's a hybrid multi-cloud world. What's going on? The thing I've been saying for a couple of years is as users, two things you need to watch. Care about their data an awful lot. That's what drives businesses. And what drives the data really? It's their applications. >> Perfect. >> And that's where Turbonomic sits. Workload automation is where you are. And that's really the important piece of multi-cloud. Maybe give our audience a little bit of context as to why this really, IBM buying Red Hat fits into the general premise of why Turbonomic exists. >> Super. So the IBM Red Hat combination I think is really all about managing workloads. Turbonomic has always been about managing workloads and actually Red Hat was an investor, is an investor in Turbonomic, particularly for open stack, but more importantly open shift now. When you think about the plethora of workloads, we're gonna have 10 to one number of workloads relative to VMs and so worth when you look at microservices and containers. So when you think about that combination, it's really, it's an important move for IBM and their opportunity to plan hybrid and multi-cloud. They just announced the IBM multi-cloud manager, and then they said wait a minute, we gotta get this thing to scale. Obviously open shift and Red Hat is scale. 8.9 million developers in their community and the opportunity to manage those workloads across on-prim and off in a cloud-native format is critical. So relate that to Turbo. Turbo is really about managing any workload in any environment anywhere at all times. And so we make workloads smart, which is self-managing anywhere real time, which allows the workloads themselves to care for their own performance assurance, policy adherence, and cost effectiveness. And when you can do that, then they can run anywhere. That's what we do. >> Yeah, Ben, bring us inside of customers. When people hear applications and multi-cloud, there was the original thing. Oh well, I'm gonna be able to burst to the cloud. I'm gonna be moving things all the time. Applications usually have data behind them. There's gravity, it's not easy to move them. But I wanna be able to have that flexibility of if I choose a platform, if I move things around, I think back to the storage world. Migration was one of the toughest things out there and something that I spent the most time and energy to constantly deal with. What do you see today when it comes to those applications? How do they think about them? Do they build them one place and they're static? Is it a little bit more modular now when you go to microservices? What do you see and hear? >> Great, so we have over 2,100 accounts today including 20% of the Fortune 500, so a pretty good sample set to be able to describe this. What I find is that CIOs today and meet with many of them, I want either born in the cloud, migrate to the cloud, or run my infrastructure as cloud. And what they mean is they want, they're seeking greater agility and elasticity than they've ever had. And workloads thrive in that environment. So as we decompose the applications and decompose the infrastructure and open it up, there's now more places to run those different workloads and they seek the flexibility to be able to create applications much more quickly, set up environments a lot faster, and then they're more than happy to pay for what they use. But they get tired of the waste candidly of the traditional legacy environments. And so there's a constant evolution for how do I take those workloads and distribute them to the proper location for them to run most performantly, most cost effectively, and obviously with all the compliance requirements of security and data today. >> Yeah, I'm wondering if you could help connect the dots for us. In the industry, we talk a lot about digital transformation. >> Yeah. >> If we said two or three years ago was a lot of buzz around this, when I talk to N users today, it's reality. Absolutely, it's not just, oh I need to be mobile and online and everything. What do you hear and how do my workloads fit into that discussion? >> So it's an awesome subject. When you think about what's going on in the industry today, it's the largest and fastest re-platforming of IT ever. Okay, so when you think about for example at the end of 2017, take away dollars and focus on workloads. There were 220 million workloads. 80% were still on prim. For all the growth in the cloud, it was still principally an on prim market. When you look now forward, the differential growth rates, 63% average growth across the cloud vendors, alright, in the IAS market. And I'm principally focused on AWS and Ajur. And only 3% growth rate in the on premise market. Down from five years ago and continuing a decline because of the expense, fergility, and poor performance that customers are receiving. So the re-platforming is going on and customers' number one question is, can you help me run my workloads in each of these three environments? So to your point, we're not yet where people are bursting these workloads in between one environment and another. My belief is that will come. But in today's world, you basically re-platform those workloads. You put them in a certain environment, but now you gotta make sure that you run them well performantly and cost effectively in those environments. And that's the digital transformation. >> Okay. So Ben, I think back to my career. If I turn back the clock even two decades, intelligence, automation, things we were talking about, it's different today. When I talk to the people building software, re-platforming, doing these things today, machine learning and AI, whatever favorite buzzword you have in that space is really driving significant changes into this automation space. I think back to early days of Turbonomic. I think about kinda the virtualization environments and the like. How does automation intelligence, how is it different today than it was say, when the company was founded? >> Wow. Well so for one, we've had to expand to this hybrid and multi-cloud world, right? So we've taken our data model which is AI ops, and driven it out to include Ajur and AWS. But the reason would say why. Why is that important? And ultimately, when people talk about AI ops, what they really mean whether it's on prim or off, is resource-aware applications. I can no longer affect performance by manually running around and doing the care and feeding and taking these actions. It's just wasteful. And in the days where people got around that by over-provisioning on prim sometimes as much as 70 or 80% if you look at the resource actually used, it was far too expensive. Now take that to the cloud, to the public cloud, which is a variable cost environment and I pay for that over-provisioning every second of the rest of my life and it's just prohibitive. So if I want to leverage the elasticity and agility of the cloud, I have to do it in a smarter measure and that requires analytics. And that's what Turbonomic provides. >> Yeah and actually I really like the term AI ops. I wonder if you can put a little bit of a point on that because there are many admins and architects out there that they hear automation and AI and say, oh my gosh, am I gonna be put out of a job? I'm doing a lot of these things. Most people we know in IT, they're probably doing way more than they'd like to and not necessarily being as smart with it. So how does the technology plus the people, how does that dynamic change? >> So what's fascinating is if you think about the role of tech, it was to remove some of the labor intensity in business. But when you then looked inside of IT, it's the most labor intensive business you can find, right? So the whole idea was let's not have people doing low value things. Let's do them high value. So today when we virtualize an unpremised estate, we know that we can share it. Run two workloads side by side, but when a workload spikes or a noisy neighbor, we congest the physical infrastructure. What happens then is that it gets so bad that the application SLA breaks. Alerts go off and we take super expensive engineers to go find hopefully troubleshoot and find root cause. And then do a non-disruptive action to move a workload from one host to another. Imagine if you could do that through pure analytics and software. And that's what our AI ops does. What we're allowing is the workloads themselves will pick the resources that are least congested on which to run. And when they do that rather than waiting for it to break and then try and fix it people, we just let it take that action on its own and trigger a V motion and put it into a much happier state. That's how we can assure performance. We'll also check all the compliance and policies that govern those workloads before we make a move so you can always know that you're in keeping with your affinity-in affinity rules, your HADR policies, your data sovereignty, all these different myriad of regulations. Oh and by the way, it'll be a lot more cost effective. >> Alright, Ben, you mentioned V motion. So people that know virtualization, this was kind of magic when we first saw it to be able to give me mobility with my workloads. Help modernize us with cubernetties. Where does that fit in your environment? How does multi-cloud world, as far as I see, cubernetties does not break the laws of physics and allow me to do V motion across multi-clouds. So where does cubernetties fit in your environment? And maybe you can give us a little bit of compare contrast of kinda the virtualization world and cubernetties, where that fits. >> Sure, so we look at containers or the pods, a grouping of containers, as just another form of liquidity that allows workloads to move, alright? And so again we're decomposing applications down to the level of microservices. And now the question you have to ask yourself is when demand increases on an application or on indeed a container, am I to scale up that container or should I clone it and effectively scale it out? And that seems like a simple question, but when you're looking at it at huge amounts of scale, hundreds of containers or pods per workload or per VM, now the question is, okay, whichever way I choose, it can't be right unless I've also factored the imposition I'm putting on the VM in which that container and or pod sits. Because if I'm adding memory in one, I have to add it to the other 'cause I'm stressing the VM differentially, right? Or should I actually clone the VM as well and run that separately? And then there's another layer, the IAS layer. Where should that VM run? In the same host and cluster and data center if it's on prim or in the same availability zone and region if it's off prim? Those questions all the way down the stack are what need to be answered. And no one else has an answer for that. So what we do is we instrument a cubernetties or an open shift or even on the other side a cloud foundry and we actually make the scheduler live and what we call autonomic. Able to interrelate the demand all the way down through the various levels of the stack to assure performance, check the policy, and make sure it's cost effective. And that's what we're doing. So we actually allow the interrelationship between the containers and their schedulers all the way down through the virtual layer and into the physical layer. >> Yeah, that's impressive. You really just did a good job of explaining all of those pieces. One of the challenges when I talk to users, they're having a real hard time keeping up. (laughing) We said I've started to figure out my cloud environment. Oh wait, I need to do things with containers. Oh wait, I hear about the server-less thing. What are some of the big challenges you're hearing from customers? Who do they turn to to help them stay on top of the things that are important for their business? >> So I think finding the sources of information now in the information age when everything has gone to software or virtual or cloud has become harder. You don't get it all from the same one or two monolithic vendors, strategic vendors. I think they have to come to the Cube as an example of where to find this information. That's why we're here. But I think in thinking about this, there's some interesting data points. First on the skills gap, okay, Accentra did a poll of their customer base and found that only 14% of their customers thought they had the requisite skills on staff to warrant their moves to the cloud. Think about that number, so 86% don't. And here's another one. When you get this wrong, there's some fascinating data that says 80% of customers receive a cloud bill north of three times what they expected to spend. Now just think about. Now I don't know which number's bigger frankly, Stu. Is it the 80% or the three times? But there's the conversation. Hey, boss, I just spent the entire annual budget in a little over a quarter. You still wanna get that cup of coffee? (laughing) So the costs of being wrong are enormously expensive. And then imagine if I'm not governing the policies and my workloads wind up in a country that they're not meant to per data sovereignty. And then we get breached. We have a significant problem there from a compliance standpoint. And the beauty is software can manage all this and automation can help alleviate the constrain of the skills gap that's going on. >> Yeah, you're totally right. I think back to five years ago, I was at Amazon Reinvent. And they had a tool that started to monitor a little bit of are you actually using the stuff that you're paying for? And there were customers walking out and saying, I can save 60 to 70% over what I was doing. Thank you Amazon for helping to point that out. When I lived on the data center side and vendors that sold stuff, I couldn't imagine if your sales rep came and said, hey, we deployed this stuff and we know you spent millions of dollars. It seems like we over-provisioned you by two to three x what you expected. You'd be fired. So it was like in Wall Street. Treats Amazon a little bit differently than they do everybody else. So on the one hand, we're making progress. There's lots of software companies like yourself. There's lots of companies helping people to optimize their cost on there. But still, this seems like there's a long way to go to get multi-cloud and the cost of what's going on there under control. Remember the early days? They said cloud was supposed to be simple and cheap and turned out to be neither of those. So Ben, I want to give you the opportunity. What do you see both as an industry and for Turbonomic, what's the next kinda six to 12 months bring? >> Good, can I hit your cloud point first? It's just when you think of Amazon, just to see how the changes. If I go and provision a workload in Amazon EC2 alone, there's 1.7 million different combinations from which I can choose across all the availability zones, all the regions, and all the services. There's 17 families who compute service alone as just one example. So what Amazon looks at Turbonomic and says, you're almost a customer control plane for us. You're gonna understand the demand on the workload, and then you can help the customer, advise the customer which service, which instance types, all the way down through not just compute and memory, but down into network and storage are the ones that we should do. And the reason we can do this so cost effectively is we're doing it on a basis of a consumption plan, not an allocation plan. And Amazon as a retailer in their origin, has cut prices 62 times, so they're very interested in using us as a means of making their customers more cost effective so that they're indeed paying for what they use, but not paying for what they don't use. They've recognized us as giving us the migration tools competency, as well as the third party cloud management competencies that frankly are very rare in the marketplace. And recognize that those are because production apps are now running at Amazon like never before. Ajur, Microsoft Ajur is not to be missed on this one, right? So they've said we too wanna make sure that we have cost effective operations. And what they've described is when a customer moves to Ajur, that's a Ajur customer at ACA. But then they need to make sure that they're growing inside of Ajur and there's a magic number of 5,000 dollars a month. If they exceed that, then they're Ajur for life, okay? The problem becomes if they pause and they say, wow this is expensive or this isn't quite right. Now they just lost a year of growth. And so the whole opportunity with Ajur and they actually resell our assessment products for migration planning as well as the optimization thereafter. And the whole idea is to make sure again customers are only paying for what they use. So both of these platforms in the cloud are super aggressive with one another, but also relative to the un-prim legacy environments to make sure that the workloads are coming into their arena. And if you look at the value of that, they round numbers about three to 6,000 dollars a year per workload. We have three million smart workloads that we manage today at Turbonomic. Think what that's worth in the realm of the prize at the public cloud vendors and it's a really interesting thing. And we'll help the customers get there most cost effectively as they can. >> Alright, so back to looking forward. Would love to hear your thoughts on just what customers need broadly and then some of the areas that we should look for Turbonomic in the future. >> Okay, so I think you're gonna continue to see customers look for outlets for this decomposed application as we've described it. So microservices, containers, and VMs running in multiple different environments. We believe that the next one, so today in market we have STDC, the software defined data center and virtualization. We have IAS and PASS in the public and hybrid cloud worlds. The next one we believe will be as applications at the edge become less pedestrian, more strategic and more operationally intensive, then you're talking about Amazon Prime delivery or your driverless cars or things along those lines. You're going to see that the edge really is gonna require the cell tower to become the next generation data center. You're gonna see compute memory and storage and networking on the cell tower because I need to process and I can't take the latency of going back to the core, be it cloud core or on premise core. And so you'll do both, but you'll need that edge processing. Okay, what we look at is if that's the modern data center, and you have processing needs there that are critical for those applications that are yet to be born, then our belief is you're gonna need workload automation software because you can't put people on every single cell tower in America or the rest of the world. So, this is sort of a confirming trend to us that we know we're in the right direction. Always focus on the workloads, not the infrastructure. If you make the application workloads perform, then the business will run well regardless of where they perform. And in some environments like a modern day cell tower, they're just not gonna be the opportunity to put people in manual response to a break fix problem set at the edge. So that's kinda where we see these things headed. >> Alright, well Ben Nye, pleasure to catch up with you. Thanks so much for giving us the update on where the industry is and Turbonomic specifically. And thank you so much for watching. Be sure to check out theCube.net for all of our coverage. Of course we're at all the big cloud shows including AWS Reinvent and CubeCon in Seattle later this year. So thank you so much for watching the Cube. (gentle music)

(uptempo techno music) >> Announcer: Live from Washington, D.C, it's CUBE Conversations with John Furrier. >> Hello there and welcome to this special CUBE Conversations here in Washington, D.C. We're getting all the stories, we're at the Halcyon House here with Kate Goodall who is the Co-Founder and CEO of Halcyon for a CUBE Conversation. Thanks for joining me today. >> My pleasure. >> So talk about Halcyon and your mission. You're doing something really important here in societal entrepreneurship. It's a non-profit, it's a really interesting mission. You're having an impact. Talk about what you guys are doing. >> Yeah, we believe in the power of human creativity and the power of compassion to change the world for the better. And by that I mean that we take some incredible change makers with really bold ideas about how they can affect societal change through business and art, and we give them a number of supports including a free place to live in this very expensive city, a fantastic mentor, an office, a community around them, money, and we don't take equity in their ventures. >> And this house that we're here is a mansion in Washington, D.C. Talk about the story about this house and this residence. >> Yeah, it's got very revolutionary roots. It was built by Benjamin Stoddert who was the first Secretary of the Navy during the Revolutionary War. And from then it exchanged hands several times. One of them was a relative of Mark Twain. And he is responsible for most of its 30,000 square feet. And then lastly, it was in the hands of the Dreyfus family before it was bought by Dr. Kuno who is my co-founder and the chair of Halcyon. >> And the Halcyon mission, you guys have a unique formula. Talk about how the fellowships, how do you guys select the ventures, what's the program? They live here. >> Yeah. >> It's a residence. >> Yeah. >> So it's interesting. >> Yeah, we give them three things, everything thing breaks down into three things. Space, community, and access. We believe that if you give people not only physical space, which is important because we have to remember that not everyone has a parents' basement they can live in and friends and family they can go get money from. So it democratizes the playing field to just be able to select people with the best ideas and the most talent and not the best drive. But also head space. What does it mean when you give someone with a brilliant idea five months to just work on their idea? Then community is very, very important. There's a lot of atrocious analogies for entrepreneurship. People compare it to staring into the abyss or chewing glass or... It creates a lot of emotions, lots of ups and downs. So having a built in community, which we have here is very important. Then lastly access, and by that I mean there are not only investors, but these days governments, philanthropists, others that are seeking solutions to some of these very hairy 21st century problems. They want access to these ideas. And if we do our job correctly, we're creating a bridge for these entrepreneurs to those people as well. >> Yeah entrepreneurship certainly is hard. And it's even harder when you're trying to crack the code on societal problems. >> Kate: Yes. >> And so this kind of brings up an interesting trend that we've been seeing emerging really rapidly in the past few years with cloud computing and other... Big data, internet of things technologies on a global scale, is the societal entrepreneurship model where you're accelerating opening up new ways to democratize, crowd source, fund, and change the game and reimagine philanthropy, policy, education, diversity, all in one. >> Yeah. >> You guys are kind of doing that here. It really is a ground zero here in Washington, D.C because of the access and the ecosystem of governments and everything's here. So you're seeing this building up in Washington, D.C. Talk about this new force, this new driving force of change called societal entrepreneurship. >> Yeah so it's, we believe it's definitely one way to really change the game. It's a way to use business principles to attack some of these enormous social problems. Many would argue that philanthropy and perhaps government have failed at some of this recently. Philanthropy was originally designed to solve problems, not to become a charity machine. And certainly, the government finds it hard to do some of those things today as well. And so figuring out how to really attack some of these enormous, hairy 21st century problems using these business principles so that their solutions can also be scaled effectively is absolutely what we're trying to approach. >> It's interesting, you see the old guard, the old ways of doing things, policy, people just checking boxes, philanthropy a big donor kind of model. And then now with cloud computing, new things are emerging. In your mind, what's changed the most now from just even 5, 10 years ago? What's the big difference in today's culture and today's environment in the world and Washington, D.C? >> Oh my gosh, so many things I could talk about. One of the reasons I think that social enterprise really came into being, partially is because there was recession and millennials didn't have jobs. So they had to create them and they created them in a new model. They created them in a way that gave them satisfaction beyond just getting a paycheck. The Jobs Act gave foundations the ability to invest in for profits and gave us crowd sourcing and crowd funding. And these things have really made some of this cross sectoral pollenization possible for the first time. I think people genuinely are frustrated that this amazing pace of change and Internet of Things and all of this stuff still hasn't solved some of these big problems. So there's so many forces at play. And I think one thing that I'll also point to because as I explained to you, I'm an archeologist and historian by training, and if you look over the course of human history, any time when you've had rapid change in technologies or you've had vast inequalities in terms of wealth, you end up with a depression or a war, or both. And I really believe that the power of social entrepreneurship can, for once, maybe let the gas out of the balloon a little bit more gently, and I think that's something really great to be optimistic about. >> How do you see that happening? I mean, we're a connected society now. >> Yeah. >> We have our mobile devices. >> Yeah, yeah. >> We have our things on our body, Internet of Things. It's all there, is that how you see it? How do you see the relief coming so we don't have a war or a depression? >> Yeah, I think that's the point, we have tremendous power now, right? To just in our hands, to be able solve some of these problems. Human ingenuity is a great thing. I think creativity and compassion are going to be the things that machines replicate last. And so we support that wholeheartedly. And I think maybe we can talk about some examples of some of our ventures, right, and what they're doing because I think that's the best way to paint. What does this mean, what is it? One of our current fellows, Ryan Soscia has created JDoe which is a way to anonymously unite victims of sexual assaults so that they can take legal action. It has a business model, but it's been proven that victims of assault are much more effective when they go as a group instead of alone. So it's a really brilliant way to use technology. Another one from our past cohort, Brandon Anderson is using a chat bot, Raheem AI to collect better data on policing. And then is working with police departments to use that data so that they can have better community relations. So these are both very relevant and timely issues that we're approaching in a non-partisan way using technology to solve. One more I'll give in our current cohort. Pilleve, which is a company that's thinking about the Internet of Things and how it can solve for the opiate crisis. They've created a pill bottle that connects to your phone or your family's phone and can give data and control over medication so that you can really start to attack addiction. >> Kate, talk about the power of we capital, what you've been doing with women's networking in Washington DC. >> Yeah. >> Because it's not just the women in tech inclusion issue, there's a lot of disparity we've been covering certainly at Silicon Angle, but there's really a lot of powerful women and talented folks, whether it's creative or on the business side or technical side, where the societal problems, these are products that are used by the entire population and so there's an effort to have more women involved in not just designing products, but actually being part of these new re-imagined solutions and technologies. >> Yeah. >> How important do you see that here, and what are some of the hurdles and successes that you've had here? >> I agree with that analysis completely. And I'm biased, but I think that Washington is an amazing city for some incredibly smart women. And when we created Halcyon, we created a committee that was diverse and reflective of the diversity we wanted to see how cohorts. So diverse by any factor. Age, gender, race, sexual orientation and what's that resulted in happily is a housing community that has 52% of our ventures founded or co-founded by women, and 58% of our ventures founded by a person of color. But then when we looked around, the investor base didn't exactly reflect our fellows. So we started to think about how we could engender and cultivate investors that were also diverse. And one of the ways to do that was to create a group of women in D.C. that wanted to fund social impact, leaning women led ventures, and it's called the WE Capital. It's led by Dr. Kuno, who is my co-founder and chair at Halcyon, and Sheila Johnson who was one of the founders of BET and has now founded Salamander Resorts. And there's 13 other remarkable women in that contingent and they're all paying it back. But and a very smart way that gets them market rate returns. >> This is interesting, the community paying forward has been the ethos of very robust and successful communities Silicon Valley here in Washington, D.C. How do you scale that? How do you go global with this? Because now you have a global model. Silicon Valley D.C. and all around world where you now have different communities coming together, all the same mission potentially. How do you blend it all in? How do you take that to the next level? >> That's a good question. We're gradually building what I call a kind Army. Just this amazing community that has ripple effects. We don't feel that we have to own or control this in anyway. Just over 3 1/2 years, we've had 55 ventures come through here. They've raised nearly $40 million dollars. Impacted half a million people around the world in a positive way. They've created nearly 500 jobs. You start to see the exponential growth even just as we sit here in this building. But I do think that's a long way to go in terms of people understanding this social societal entrepreneurship. People have different definitions for it and it's a long way to go in term terms of government and philanthropy really being able to understand it. Because in some ways as I mentioned, they lost touch with who their customers are. >> Okay and I've always been saying in Silicon Valley and on my Facebook page and also on theCube that SiliconValley doesn't get D.C. They try to come in waves around. You don't get it and they're impatient, I would say if I categorize. They get D.C. but I don't think they have the patience for it. It's a new culture here. Also the pace of change is accelerating in D.C. but it's a formula for D.C. What is the secret to be successful in Washington, D.C if you're a tech entrepreneur or investor or someone from Silicon Valley or not from here? >> We do get the advantage of being able to see who does that well and who doesn't. And tech is obviously leading ahead of policy. Policy is trailing tech and I think that can understandably make policymakers nervous. They've got a lot of understanding to do to be able to make some policy decisions. And these tech solutions are very complicated so the people in tech that I see being successful around policy of those that will take the time to really sit down and pick through a problem with policy maker and help them to understand it. Policy makers are actually very smart but they're dealing with a lot. >> John: So education. >> Education, education absolutely. You can't come in here >> Patience. >> And be impatient that they're not getting it. But I think that's going to essential. We've got to figure out how to talk each other and how to talk across different languages, different domain, different sectors and creates some better intersectionality. >> So what's next for Halcyon? What's the vision? What's your vision of how this will go forward? Obviously you've got a great model, batches coming through cohorts, and you have demo days here. I noticed your set up downstairs for a demo day so it's very robust, classic incubator, accelerator model with the residences leading it there. What's next? Where do you go from here? >> We don't take equity in any of our ventures but we are thinking about creating a fund, because so many of our ventures are performing exceptionally well. And we're actually going to be launching a festival that really takes the power of creativity and compassion, and art and technology here in D.C. and that will be in June. And we're hoping it that way, we can reach a wide audience, and that's going to be very exciting. The long term vision really is how can we harness the power of compassionate and creativity to solve 21st century problems, and how can we do that at scale? >> The classic disruption model is gate keepers start being disrupted by the new guard as Andy Jassy would say in Amazon. These a new creative as well. I did a panel at Sundance a few weeks ago where we talked about this creative where democratization is happening at artist level, and the government maker level. And that seems to be happening across all industries. A new creative is developing. What's your view of the digital impact? Because artistry can be sculptures and painting and whatnot to classic artistry or film making but now tech's involved, digital. >> Yeah. >> It's coming together. Is the vision how you see art and science coming together? >> Yeah, artists are fantastic disrupters. Sometimes they don't even need to paint a picture. They just use their ability as an artist to do things other people can't. And that's why they're awfully fun to be round. I think that you're absolutely right. I point to Dee Rees as an great example, who didn't get her funding for her film Mudbound through the the Hollywood machine, instead she went straight to Netflix and now she's getting an Oscar. That's a new way of doing things. We have one of our fellows, DeShuna who created kweliTV which is Netflix for the African diaspora because Netflix just doesn't have the kind of black filmmaking that she wants to see. So yeah I absolutely see people using digital to do different kinds of disrupting including on the outside of things. We have another program, the Arts Lab. Very similar to this but working with excellent artists who are thinking about social justice. One of the artist, Georgia Os-acs is doing a project called Two Future Women. And she's collecting letters that women are writing to other women 19 years from now. They're being archived by the museums in D.C. and will be displayed on the eve of the Women's March. Wouldn't it be great to know what the suffragette were thinking? And that all requires technology to be able to successfully collect those, disseminate them, archive them et cetera. >> So New channels to the market place breaking down the barriers for the gate keeper seems to be the trend. How is that happening in your world, in D.C and in philanthropy? You're now creating a new model of entrepreneurship. >> Yes, yes. >> Not just philanthropy, hey nice job or policy check box, it's real change. >> And arguably a new model for philanthropy because very rarely is philanthropy so immersive where we're literally taking these people and we're in the living with them for five months, and giving them all of these supports. And I think it's also a new model and that it's risk taking. It's not a safe and secured, metric based, proven solutions. It's some of these centers are going to fail and I think that that's okay. That's just testing and trying and finding the best and moving forward. I was going to make another point. >> You guys are changing the world obviously, I made a comment on Facebook, we're saving the world at the same time because you mentioned you can actually get ahead of some of these trends with this gap. Whether it's inequity, inequality or however these gaps are causing even war or depression as history points out. Now you have an opportunity to use, not just diagnostic capability but predictive and prescriptive mechanisms. What are some of those things that someone could see and connect the dots around an example of something that's prescriptive. Say wait, wow, time out. We've got something going on over there as a problem space we can solve with a solution. What are some examples that you see playing out where this model could work? >> I'm not sure I quite understand the question. >> If you had the ability to use technology to solve some societal problems, what are some examples that you're seeing here in your incubator that are pointing to this new trend? >> Yeah, I think that our fellows are fantastic examples of that. Many of them are tech enabled whether or not they're using apps or the cloud or just a new actual technology product. One of our fellows is using, he's created a new product that disrupts the vestibular system so that you don't feel motion sickness. Now this is actually a product that is obviously very valuable for just everyday people, who are going to be in driver-less cars trying to do their work. But it turns out very useful for the military and very useful for people who are trying to create virtual reality. 40% of people can not put a virtual reality headset on and not feel nauseous. So I do think that it is tech's job to solve some of the problems that we haven't been able to solve yet. In many ways, the internet and the Internet of Things is our biggest leap forward since fire. Now how are we going to use it to create the disruption that fire did? Fire allowed us to eat more things, grow bigger then start to farm and and I think that we haven't even hit the cusp of what the internet can do yet. It can do way more things and deliver products to our doorsteps. >> Next up at the wheel, you get fired-- >> Right, what's is the tech wheel? I think it's going to be really-- >> Personal question for you, what is the big learnings that you've had over the past few years? (mumbles) say well I didn't expect that to happen or wow, that was super awesome or a failure or a success? What was your big learnings that you've come out-- >> Oh my gosh, do you have an hour? We've learnt how not to do and how to do mentorship very well. You can't take mentorship lightly. This is human chemistry we're talking about and even if you think you've got the perfect match on paper, it may not work. We have certainly learned a lot about how it is really important to have investors that reflect entrepreneurs because to your very point, that work is going to take everyone to create technologies that work for everyone. It also creates and builds even investors who look like everyone because otherwise there is an inherent bias. Really good people have inherent bias and that needs to be solved for. Because I straddle both art and entrepreneurship in my role. These some really interesting things that I've noticed in terms of how entrepreneurs see the world as infinite resource and artist see it as very finite. And how some of our systemic problems are reflected almost identically in both fields. This is an interesting statistic. 5% of venture capital goes to women, we know that and 1% to African Americans, 0.01% to Black women. In the museum world, in museums in the western hemisphere, 5% of their art collection is women artists, 1% is African American artists. That's not a coincidence, that's a clear picture of how power structures have evolved to make certain types of decisions about who should get capital, who is worth collecting, and we're definitely solving for that. >> And certainly having a lens on that and exposing that-- >> Kate: Absolutely. >> Is the way to-- >> It's very important. >> Talk about artistry, one of the things we've been talking about in the software and in the tech business is the role of artistry and craft. And that we see that swinging back with cloud computing. I would say to the craft out a software development but you're seeing these integrated solutions where craftsmanship and art are coming together. We're seeing examples, certainly in Asia, in China we're seeing examples where the development world, the technical world has come together with artistry world to create these new solutions. So you've got creative and you've got technical coming together. That's what you're doing. >> Yeah, no absolutely. >> What's the success formula? Is there one? Is it right brain, left brain, what's the-- >> I don't know. We've just got this bubbly caldron of creativity and we're pulling stuff out of it as we go, but I think it's important for us not to forget about art. Art has been at the forefront of every social change, every movement. If it does its job, it's of the moment and it tells us a lot about ourselves. But there's also that important thing about art with technology, and with consumer products. The reason that the iPhone was so successful is because it's a thing of beauty, and everyone is in awe of it. So design is critical, it's absolutely critical when you're thinking about scale or consumer products or tech that works. >> And having a good taste for a good art is also a skill. >> Yeah. >> Knowing what's beautiful. >> Of course. >> Tech guys love to have that skill. >> You could argue that that's getting democratized and disrupted as well. >> Kate, thanks so much for spending some time here. >> My pleasure, this is fun. >> Cube Conversation, Kate Goodall, co-founder and CEO of Halcyon here in Washington, D.C. Changing the world, societal entrepreneurship. A lot of great actions. This is theCube coverage. Thanks for watching. (uptempo techno music)

(upbeat music) >> Welcome to this special CUBEConversation here in the Palo Alto CUBE studio. I'm John Furrier, the co-host, theCUBE co-founder of SiliconANGLE Media. In theCUBE we're here with Alan Cohen, CUBE alumni, joining us today for a special segment on the future of technology and the impact to society. Always good to get Alan's commentary, he's the Chief Commercial Officer for Illumio, industry veteran, has been through many waves of innovation and now more than ever, this next wave of technology and the democratization of the global world is upon us. We're seeing signals out there like cryptocurrency and blockchain and bitcoin to the disruption of industries from media and entertainment, biotech among others. Technology is not just a corner industry, it's now pervasive and it's having some significant impacts and you're seeing that in the news whether it's Facebook trying to figure out who they are from a data standpoint to across the board every company. Alan, great to see you. >> Always great to be here, I always feel like, I can't tell whether I'm at the big desk at ESPN or I've got the desk chair at CNBC, but that's what it's like being on theCUBE. >> Great to have you on extracting the signal noises, a ton of noise out there, but one of things of the most important stories that we're tracking is, that's becoming very obvious, and you're seeing it everywhere from Meed to all aspects of technology. Is the impact of technology to people in society, okay you're seeing the election, we all know what that is, that's now a front and center in the big global conversation, the Russian's role of hacking, the weaponizing of data, Facebook's taking huge brand hits on that, to emerging startups, and the startup game that we're used to in Silicon Valley is changing. Just the dynamics, I mean cryptocurrency raises billions of dollars but yet (laughs) something like 10, 20% of it's been hacked and stolen. It's a really wild west kind of environment. >> Well it's a very different environment. John, you and I have been in the technology industry certainly for a whole bunch of lines under our eyes over the years have gone there. My friend Tom Friedman has this phrase that he says, "Everybody's connected and nobody's in control," so the difference is that, as you just said, the tech industry is not a separate industry. The tech industry is in every product and service. Cryptocurrency is like, the concept of that money is just code. You know, our products and services are just code, it raises a couple of really core issues. Like for us on the security point of view, if I don't trust people with the products they're selling me, that I feel like they're going to be hacked, including my personal data, so your product now includes my personal information, that's a real problem because that could actually melt down commerce in a real way. Obviously the election is if I don't trust the social systems around it, so I think we're all at an, and I'd like to say world is still kind of like iRobot moment, and if you remember iRobot, it's like, people build all these robots to serve humankind and then one day the robots wake up and they go, "We have our own point of view on how things are going to work" and they take over, and I think whether it's the debate about AI, whether cryptocurrency's good or bad, or more importantly, the products and services I use, which are now all digitally connected to me, whether I trust them or not is an issue that I think everyone in our industry has to take a step back because without that trust, a lot of these systems are going to stop growing. >> Chaos is an opportunity, I think that's been quoted many times, a variety-- >> You sound like Jeff Goldblum in like Jurassic Park, yeah. (laughing) >> So chaos is upon us, but this is an opportunity. The winds are shifting, and that's an opportunity for entrepreneurs. The technology industry has to start working for us but we've got to be mindful of these blind spots and the blind spots are technology for good not necessarily just for profits, so that also is a big story right now. We see things like AI for good, Intel has been doing a lot of work on that area, and you see stars dedicated to societal impact, then young millennials, you see the demographic shift where they want to work on stuff that empowers people and changes society so a whole kind of new generation revolution and kind of hippie moment, if you look at the 60s, what the 60s were, right? >> Well there's people out in the street protesting, right? There were a couple of million women out in the street this weekend, so we are in that kind of moment again, people are not happy with things. >> And I believe this is a signal of a renaissance, a change, a sea change at enormous levels, so I want to get your thoughts on this. As technology goes out in mainstream, certainly from a security standpoint, your business Illumio is in that now where there's not a lot of control, just like you were mentioning before we came on that all the spends happening but no one has more than 4% market share. These are dynamics and this is not just within one vertical. What's your take on this, how do you view this sea change that's upon us, this tech revolution? >> Well, you know, think about it. You and I grew up in the era where clients server took over from main frame, right? So remember there was this big company called IBM and they owned a lot of the industry, and then it blew up for client server and then there were thousands of companies and it consolidated its way down, but when those thousands of new companies, like you didn't know what was going to be Apollo and what was going to be Oracle right? Like you didn't know how that was going to work out, there was a lot of change and a lot of uncertainty. I think now we're seeing this on a scale like that's 10x of this that there's so much innovation and there's so much connectedness going on very rapidly, but no one is in control. In the security market, you know, what's happening in our world is like, people said, okay I have to reestablish control over my data, I've lost that control, and I've lost it for good reasons, meaning I've evolved to the cloud, I've evolved to the app economy, I've done all of these things, and I've lost it for bad reasons because like am I, like I'm not really running my data center the way I should. We're in the beginning of a move in of people kind of reasserting that control, but it's very hard to put the genie back in the bottle because the world itself is so much more dynamic and more distributed. >> It's interesting, I've been studying communities and online communities for over a decade in terms of dynamics. You know, from the infrastructural level, how packets move to a human interaction. It's interesting, you mentioned that we're all connected and no one's in control, but you now see a ground swell of organic self-forming networks where communities are starting to work together. You kind of think about the analog world when we grew up without computers and networks, you kind of knew everyone, you knew your neighbor, you knew who the town loony was, you kind of knew things and people watch each other's kids and parents sat from the porch, let the kid play, that's the way that I grew up, but it was still chaotic but yet somewhat controlled by the group. So I got to ask you, when you see things like cryptocurrency, things like KYC, know your customer, anti money laundering, which is, you know these are policy based things, but we're in a world now where, you know, people don't know who their neighbors are. You're starting to see a dynamic where people are-- >> Put the phone down. >> Asserting themselves to know their neighbor, to know their customer, to have a connected tissue with context and so your trust and reputation become super important. >> Well I think people are really, so like every time there is a shift in technology, there's scary stuff. There's the fuddy-duddy moment where people are saying, "Oh we can't use that," or "I don't know that," and you know, clearly we're in this kind of new kam-ree and explosion of this cloud mobile blah blah blah type of computing thing and ... Blah blah blah is always a good intersection when you don't have a term. Then things form around it, and just as you said, so if you think about 25 years ago, right, people created The WELL and there was community writing first bulletin boards and like now we have Facebook and you go through a couple of generations and for a while, things feel out of control and then it reforms. I personally am an optimist. Ultimately I believe in the inherent goodness of people, but inherent goodness leaves you open and then, you know, could be manipulated, and people figure these things out. Whether it's cryptocurrency or AI, they are really exciting technologies that don't have any ground rules, right? What's going to happen I believe is that people are going to reestablish ground rules, they're going to figure out some of the core issues, and some of these things may make it, and some of these things may not make it. Like cryptocurrency, like I don't know whether it makes it or not, but certainly the blockchain as a technology we're going to be incorporating in what we do, and maybe the blockchain replaces VPNs and last generation's way of protecting zeros and ones. If AI is figuring out how to read an MRI in five minutes, it's a good thing, and if the AI is teaching you how to exclude old folks for me finding jobs, it's a bad thing. I think as technology forms, there's always Spectre and 007, right? There's always good and bad sides and you know, I think if you believe-- >> I'm with you on that. I think value shifts and I think ultimately it's like however you want to look at it will shift to something, value activity will be somewhere else. Behind me in the bookshelf is a book called The World is Flat and you're quoted in it a lot as a futurist because you have inherently that kind of view, well that's not what you do for a living, but you're kind of in an opt-- >> Alan: Marketing, futurist, kind of same thing. >> Thomas Friedman, the book, that was a great book and at that time, it was game changing. If you take that premise into today where we are living in a flat world and look at cryptocurrency, and then over with the geo political landscape, I mean I just can't see why the Federal Reserve wouldn't reign in this cryptocurrency because if Japan's going to control a bunch of, or China, it's going to be some interesting conversations. I mean I would be like all over that if I was in the Federal Reserve. >> I think people-- Look, cryptocurrency's really interesting and I think people a little over-rotated. If you look at the amount of GDP that's invested in cryptocurrency, it's like, I don't know, there might've been, you know 20 years ago the same amount involved invested in Beanie Babies, right? I mean things show up for a while and the question is is it sustainable over time? Now I'm trained as an economist, you and I have had this conversation, so I don't know how you have a series of monetary without kind of governmental backing, I just don't understand. But I do understand that people find all kinds of interesting ways to trade, and if it's an exchange, like I mean what's the difference between gold and cryptocurrency? Somebody has ascribed a value to something that really has no efficacy outside of its usage. Yeah I mean you can make a filling or bracelets out of gold but it doesn't really mean anything except people agree to a unit of value. If people do that with cryptocurrency, it does have the ability to become a real currency. >> I want to pick your perspective on this being an economist, this is is the hottest area of cryptocurrency, it's also known as token economics, is a concept. >> Alan: Token economics. >> You know that's an area that theCUBE, with CUBE coins, experimenting with tokens. Tokens technically are used for things in mobile and whatnot but having a token as a utility in a network is kind of the whole concept, so the big trend that we're seeing and no one's really talking about this yet is instead of having a CTO, Chief Technology Officer, they're looking for a CEO, a Chief Economist Officer, because what you're seeing with the MVP economy we're living in and this gamification which became growth hack which didn't really help users, the notion of decentralized applications and token economics can open the door for some innovation around value and it's an economic problem, how you have a fiscal policy of your token, there's a monetary policy, what's it tied to? A product and a technology, so you now have a now a new, twisted, intertwined mechanism. >> Well you have it as part of this explosion, right? We're at a period of time, it feels like there's a great amount of uncertainly because everything's, you know, there's a lot of different forces and not everybody's in control of them, and you know, it's interesting. Google has this architecture, they call it BeyondCorp, where the concept is like networks are not trusted so I will just put my trust in this device, Duo Security's a great example of a company that's built a technology, a security technology around it which is completely antithetical to everything we know about networks and security. They're saying everything's the internet, I'll just protect the device that it's on. It's a kind of perfect architecture for a world like where nobody is in charge, so just isolate those, buy this, what is a device? It's a token too, it's a person, your iPhone's your personal token. Then over time, systems will form around it. I think we just have to, we always have to learn how to function in a different type of economy. I mean democracy was a new economy 250 years ago that kind of screwed around with most of the world, and a lot of people didn't think it would make it, in fact we went through two World War wars that it was a little on the edge whether democracy was going to make it and it seems to have done okay, like it was pretty good IPO to buy into. You know, in 1776. But it's always got risks and struggles with it. I think if, ultimately it comes together, it's whether a large group of people can find a way to function socially, economically, and with their personal safety in these systems. >> You bring up a great point, so I want to go to the next level in this conversation which is around-- >> Alan: You've got the wrong guy if you're going to the next level because I just tapped out. >> No, no, no we'll get you there. It's my job to get you there. The question is that everyone always wants to look at, whether it's someone looking at the industry or actors inside the industries across the board, mainly the tech and we'll talk about tech, is the question of are we innovating? You brought up some interesting nuances that we talk about with token economics. I mean Steve Jobs had the classic presentation where he had street signs, technology meets liberal arts. That's a mental image that people who know Steve Jobs, know Apple, was a key positioning point for Apple at that time which was let's make computers and technology connect with society, liberal arts. But we were just talking about is the business impact of technology, the economics, and that's just not like just some hand waving, making technology integrate with business. You're in the security business, There are some gamification technology, gamification that's business built into the products. So the question is, if we have the integration of business, technology, economics, policy, society rolling into the product definitions of innovation, does that change the lens and the aperture of what innovation is? >> I think it does, right? The IT industry's somewhere between three and four trillion dollars depends on how it counts in. It grows pretty slowly, it grows by a low single digit. That tells me as composite, like is that, that slow growth is a structural signal about how consumers of technology think in a macro sense. On a micro sense, things shift very rapidly, right? New platforms show up, new applications show up, all kinds of things show up. What I don't think we have done yet, to your point, is in this new integrated world, the role of technology is not just technology anymore. I don't think, you know you said you need Chief Economical Officer, what about Chief Political Officer? What about a Chief Social Officer? How many heads of HR make decisions about the insertion of systems into their business? And that's what this kind of iRobot concept is in my mind which is that you know, we are exceeding control of things that used to be done by human beings to systems and when you see control, the social mores, the political mores, the cultural mores, and the human emotional mores have to move with it. We don't tend to think about things like that. We're like, "I win and my competitors lose." Like technology used to be much more of a zero sum, my tech's better than yours. But the question is not just is my tech better than yours, is my customer better off in their industry for the consumption of my technology of inserting it into their offering or their service? You know what, that is probably going to be the next area of study. The other thing that's very important in whether, any of you have read Peter Thiel's book Zero to One, the nature of competition technology used to feel like a flat playing field and now the other thing that's rising is do you have super winners? And then what is the power of the super winners? So you mentioned whether it's Facebook or Google or Amazon or you know, or Microsoft, the FANG companies right? Their roles are so much more significant now than the Four Horsemen of the Nasdaq were in 2000 when you had Intel and Cisco and Oracle and Saht-in it's a different game. >> You're seeing that now. That's a good point, so you're reinforcing kind of this notion that the super players if you will are having an impact, you're mentioning the confluence of these new sectors, you know, government, policy, social are new areas. The question is, this sounds like a strategic imperative for the industry, and we're early so it's not like there's a silver bullet or is there, it doesn't sound like there, so to me that's not really in place yet, I mean. >> Oh no. We're not even in alpha. We have demo code for the new economy and we're trying to get the new model funded. >> John: That's the demo version, not the real version. It's the classic joke. >> Yeah this not the alpha or the beta version that like you're going to go launch it. If people think they're launching it, I think it's a little preliminary and you know, it's not just financial investment, it's like do I buy in? I'll tell you something that's really interesting. I've been visiting a bunch of our customers lately and the biggest change I'd say in the last two years is they now have to prove to their customers they're going to be good custodians of their data. Think about that, like you could go to any digital commerce you do, any website you use and you give them basically the ticket to the Furrier family privacy, you do, but you don't spend a lot of time questioning whether they're really going to protect your data. That has changed. And it's really changing in B2B and in government organizations. >> The role of data to us is regulation, GDPR in Europe, but this is a whole new dynamic. >> It's not just my data because I'm worried about my credit card getting hacked, I'm worried about my identity. Like am I going to show up as a meme in some social media feed that's substituted for the news? I don't want to use the FN word, but you know what I mean? It is a really brave new world. It's like a hyper-democracy and a hyper-risky state at the same time. >> We're living in an area of massive pioneering, new grounds, this is new territory so there's a lot of strategic imperatives that are yet not defined. So now let's take it to how people compete. We were talking before we came on camera, you mentioned the word we're in an MVP economy, minimum viable product concept, and you're seeing that being a standard operating procedure for essentially de-risking this challenge. The old way of you know, build it, ship it, will it work? We're seeing the impact from Hollywood to big tech companies to every industry. >> Well you've got a coffee mug for a company that does both. Amazon does MVP in entertainment, like we'll create one pilot and see if it goes as opposed to ordering a season for 17 million dollars to hey, let's try this feature and put it out on AWS. What's interesting is I don't think we've completely tilted but the question is will buyers of technology, of entertainment products, of any product start to say, "I'll try it." You know like, look, I've done four startups and I always know there's somebody I can go to get and try my early product. There are people that just have an appetite, right? The Jeffrey Moores, early adapter, all the way to the left of the-- >> They'll buy anything new. >> They'll try it, they're interested, they have the time and the resources, or they're just intellectually curious. But it was always a very small group of people in the IT industry. What I think that the MVP economy is starting to do is look, I Kickstarted my wallet. I don't know if I'm the only person who bought that skinny little wallet on Kickstarter, it doesn't matter to me, it had appeal. >> What's the impact of the MVP economy? Is it going to change to the competitive landscape like Peter Thiel was suggesting? Does it change the economics? Does it change the makeup of the team? All of the above? What's your thoughts on how this is going to impact? Certainly the encumbrance will seem to be impacted or not. >> I think two things happen. One, it attacks the structural way markets work. If you go back to classical economics, land, labor, and capital, and people who own those assets, now you add information as a fourth. If those guys were around now they would say that would be the fourth core asset, production, I'm sorry, means of production is the term. The people who can dominate that would dominate a market. Now that that's flattened out, you know, I think it pushes against the traditional structures and it allows new giants to kind of show up overnight. I mean the e-commerce market is rife with companies that have, like look at Stich Fix. A company driven by AI, fashions, tries to figure out what you like, sends it to you every month, just had a monster IPO. We invented, by the way the Spiegal Catalog, except like with a personal assistant and you know, it's changed that in just a short number of years. I think two things happen. One is you'll get new potential giants but certainly new players in the market quickly. Two, it'll force a change in the business model of every company. If you're in a cab in any city in the world, I'm not saying whether the app works there or not, Uber and Lyft has forced every cab company to show you here's the app to call the cab. They haven't quite caught up to the rest of the experience. What I think happens is ultimately, the larger players in an industry have to accommodate that model. For people like me, people who build companies or large technology companies, we may have to start thinking about MVPing of features early on, working with a small group, which is a little what the beta process is but now think about it as a commercial process. Nobody does it, but I bet sure a lot of people will be doing it in five years. >> I want to get your take on that approach because you're talking about really disrupting, re-imagining industry, the Spiegal catalog now becomes digital with technology, so the role of technology in business, we kind of talked about the intertwine of that and its nuance, it's going to get better in my opinion. But specifically the IT, the information technology industry is being disrupted. Used to be like a department, and the IT department will give you your phone on your desk, your PC on your desk or whatever, now that's being shattered and everyone that's participating in that IT industry is evolving. What's your take on the IT industry's disruption? >> Well look, it started 20 years ago when Marc Benioff and Salesforce decided to sell the sales forces instead of IT people, right? They went around to the end buyer. I don't think it's a new trend, I think a lot of technology leaders now figure out how to go to the business buyer directly and make their pitch and interestingly enough, the business buyer, if the IT team doesn't get on board, will do that. >> John: Because of cloud computing and ... >> Because of everything. The modern analog I think in our world is that the developers are increasingly in control. Like my friend Martin Casado up in Andreessen talks about this a lot. The traditional model on our industry is you build a product, you launch it, you launch your company, you work with the traditional analyst firms, you try to get a little bit of halo, you get customer references, those are the things you do and there was a very wall structured, for example, enterprise buying cycle. >> And playbook. >> Playbook, and there's the challenger sale and there's Jeffrey Moore and there's like seeing God. You've got your textbooks on how it's been done. As everything turns into code, the people who work with code for a living increasingly become the front end of your cycle and if you can get to them, that changes. Like I mean think about like, you know, Tom wrote about this actually in The World is Flat, like Linux started as a patchy. It didn't start with the IT department, it started with developers and there was the Linux foundation and now Linux is everything. >> There's a big enemy called the big mini computer, and not operating systems and work stations. >> Wiped out whole parts of Boston and other parts of the world, right? >> Exactly, that's why I moved out here. >> You filed client's server out here. >> I filed a smell of innovation. No but this is interesting because this location of industries is happening, so with that, so they also on the analog, so Martin's at Andreessen, so we'll do a little VC poke there at the VCs because we love them of course, they're being dislocated-- >> I don't (mumbles) my investors. >> Well no, their playbook is being challenged. Here's an example, go big or go home investment thesis seems not to be working. Where if you get too much cash on the front end, with the MVP economy we were just riffing on and with the big super powers, the Amazons and the Googles, you can't just go big or go home, you're going to be going home more than going big. >> I think they know that. I mean Dee-nuh Suss-man who's I think Chief Investment Officer at Nasdaq has a very well known talking line that there are half as many public companies as there were 10 years ago, so the exit scenario for our industry is a little bit different. We now have things like acqui-hires, right we have other models for monetization, but I think what the flip side of it is, we're in the-- >> Adapt or die because the value will shift. Liquidity's changing, which acqui-hires-- >> I think the investment community gets it completely and they spend a lot more time with the developer mindset. In fact I think there's been a doubling down focus on technical founders versus business founders for companies for just that reason because as everything turns to code, you got to hang out with the code community. I think there are actually-- >> You think there'll be more doubling down on technical founders? You do, okay. >> Yeah I think because that is ultimately the shift. There are business model shifts, but it's, you know, I mean like Uber was a business model shift, I mean the technology was the iPhone and GPS and they wrote an app for it, but it was a business model shift, so it can be a business model shift. >> And then scale. >> And then scale and then all of those other things. But I think if you don't think about developers when you're in our, and it's like we built Illumio because a developer could take the product and get started. I mean you can, developers actually can write security policy with our product because there's a class of customers, where as not everyone where that matters. There's other people where the security team is in charge or the infrastructure team is in charge but I think everything is based on zeros and ones and everything is based on code and if you're not sensitive to how code gets bought, consumed, I mean there's a GitHub economy which is I don't even have to write the code, I'll go look at your code and maybe use pieces of it, which has always been around. >> Software disruption is clear. Cloud computing is scale. Agile is fast, and with de-risking capabilities, but the craft is coming back and some will argue, we've talked about on theCUBE before is that, you know, the craftsmanship of software is moving to up the stack in every industry, so-- >> I think it's more like a sports league. I love the NBA, right? In the old days, your professional team, you'd scout people in college. Now they used to scout them in high school, now they're scouting kids in middle school. >> (laughs) That's sad. >> Well what it says is that you have to-- >> How can you tell? >> You know but they can, right? I think you know, your point about it craft, you're going to start tracking developers as they go through their career and invest and bet on them. >> Don't reveal our secrets to theCUBE. We have scouts everywhere, be careful out there. (laughs) >> But think about that, imagine it's like there's such a core focus on hiring from college, but we had an intern from high school two years ago. We hire freshman. >> Okay so let's go, I want to do a whole segment on this but I want to just get this point because we're both sports fans and we can riff on sports all day long. >> I'm just not getting the chance >> And the greatness of Tom Brady >> to talk about the Patriots. >> And Tom Brady's gotten his sixth finger attached to his hands for his sixth ring coming up. No but this is interesting. Sports is highly data driven. >> Alan: Yep. >> Okay and so what you're getting at here, with an MVP economy, token economics is more of a signal, not yet mainstream, but you can almost go there and think okay data driven gives you more accuracy so if you can bring data driven to the tech world, that's kind of an interesting point. What's your thoughts on that? >> Yeah I mean look, I think you have to track everything. You have to follow things, and by the way, we have great tools now, you can track people through LinkedIn. There's all kinds of vehicles to tracking individuals, you track products, you track everything, and you know look, we were talking about this before we went on the show right, people make decisions based on analytics increasingly. Now the craft part is what's interesting and I'm not the complete expert, I'm on the business side, I'm not an engineer by training, but look a lot of people understand a great developer is better than five bad developers. >> Well Mark Andris' 10x is a classic example of that. >> There's clearly a star system involved, so if I think in middle school or in high school, you're going to be a good developer, and I'm going to track your career through college and I'm going to try to figure out how to attach. That's why we started hiring freshmen. >> Well my good friend Dave Girouard started a company that does that, will fund the college education for people that they want to bet on. >> Sure, they're just taking an option in them. >> Yeah, option on their earnings. Exactly. >> They are. >> It sounds like token economics to me. (laughs) >> You know you can sell anything. We are in that economy, you can sell those pieces. The good news is I think it can be a great flattener, meaning that it can move things back more to a meritocracy because if I'm tracking people in high school, I'm not worrying whether they're going to go to Stanford or Harvard or Northwestern, right? I'm going to track their abilities in an era and it's interesting, speaking about craft, you know, what are internships? They're apprenticeships. I mean it is a little bit like a craft, right? Because you're basically apprenticing somebody for a future payout for them coming to work for you and being skilled because they don't know anything when they come and work, I shouldn't say that, they actually know a lot of things. >> Alan, great to have you on theCUBE as always, great to come in and get the update. We'll certainly do more but I'd like to do a segment on you on the startup scene and sort of the venture capital dynamics, we were tracking that as well, we've been putting a lot of content out there. We believe Silicon Valley's a great place. This mission's out there, we've been addressing them, but we really want to point the camera this year at some of the great stuff, so we're looking forward to having you come back in. My final question for you is a personal one. I love having these conversations because we can look back and also look forward. You do a lot of mentoring and you're also helping a lot of folks in the industry within just your realm but also startups and peers. What's your advice these days? Because there's a lot of things, we just kind of talked a lot of it. When people come to you for advice and say, "Alan, I got a career change," or "I'm looking at this new opportunity," or "Hey, I want to start a company," or "I started a company," how is your mentoring and your advisory roles going on these days? Can you share things that you're advising? Key points that people should be aware of. >> Well look, ultimately ... I never really thought about it, you just asked the question so, ultimately, I think to me it comes down to own your own fate. What it means is like do something that you're really passionate about, do something that's going to be unique. Don't be the 15th in any category. Jack Welch taught us a long time ago that the number one player in a market gets 70% of the economic value, so you don't want to play for sixth place. It's like Ricky Bobby said, if you're not first, you're last. (John chuckles) I mean you can't always be first, but you should play for that. I think for a lot of companies now, I think they have to make sure that, and people participating, make sure that you're not playing the old playbook, you're not fighting yesterday's battle. Rhett Butler in Gone With the Wind said, "There's a lot of money in building up an empire, "and there's even more money in tearing it down." There are people who enter markets to basically punish encumbrance, take share because of innovation, but I think the really inspirational is you know, look forward five years and find a practical but aggressive path to being part of that side of history. >> So are we building up or are we taking down? I mean it seems to me, if I'm not-- >> You're always doing both. The ocean is always fighting the mountains, right? That is the course of, right? And then new mountains come up and the water goes someplace else. We are taking down parts of the client server industry, the stack that you and I built a lot of our personal career of it, but we're building this new cloud and mobile stack at the same time. And you're point is we're building a new currency stack and we're going to have to build a new privacy stack. It's never, the greatest thing about our industry is there's always something to do. >> How has the environment of social media, things out there, we're theCUBE, we do our thing with events, and just in general, change the growth plans for individuals if you were, could speak to your 23 year old self right now, knowing what you know-- >> Oh I have one piece of advice I give everybody. Take as much risk as humanly possible in your career earlier on. There's a lot of people that have worked with me or worked for me over the years, you know people when they get into their 40s and they go, "I'm thinking about doing a startup," I go, "You know when you got two kids in college "and you're trying to fund your 401K, "working for less cash and more equity may not be "the most comfortable conversation in your household." It didn't work well in my household. I mean I'm like Benjamin Button. I started in big companies, I'm going to smaller companies. Some day it's just going to be me and a dog and one other guy. >> You went the wrong way. >> Yeah I went the wrong way and I took all the risk later. Now I was lucky in part that the transition worked. When I see younger folks, it's always like, do the riskiest thing humanly possible because the penalty is really small. You have to find a job in a year, right? But you know, you don't have the mortgage, and you don't have the kids to support. I think people have to build an arc around their careers that's suitable with their risk profile. Like maybe you don't buy into bitcoin at 19,000. Could be wrong, could be 50,000 sometime, but you know it's kind of 11 now and it's like-- >> Yeah don't go all in on 19, maybe take a little bit in. It's the play and run-- >> Dollar cost averaging over the years, that's my best fidelity advice. I think that's what's really important for people. >> What about the 45 year old executive out there, male or female obviously, the challenges of ageism? We're in economy, a gig economy, whatever you want to call, MVP economics, token economics, this is a new thing. Your advice to someone who's 45 who just says "Hey you're too old for our little hot startup." What should they do? >> Well being on the other side of that history I understand it firsthand. I think that you have an incumbent role in your career to constantly re-educate yourself. If you show up, whether you're a 25, 35, 45, 55, or 65, I hope I'm not working when I'm 75, but you never know right? (mumbles) >> You'll never stop working, that's my prediction. >> But you know have you mastered the new skills? Have you reinvented yourself along the way? I feel like I have a responsibility to feed the common household. My favorite part of my LinkedIn profile, it says, "Obedient worker bee at the Cohen household," because when I go home, I'm not in charge. I've always felt that it's up to me to make sure I'm not going to be irrelevant. That to me is, you know, that to me, I don't worry about ageism, I worry about did I-- >> John: Relevance. >> Yeah did I make myself self-obsolescent? I think if you're going to look at your career and you haven't looked at your career in 15 years and you're trying to do something, you may be starting from a deficit. So the question, what can I do? Before I make that jump, can I get involved, can I advise some small companies? Could I work part time and on the weekends and do some things so that when you finally make that transition, you have something to offer and you're relevant in the dialogue. I think that's, you know, nobody trains you, right? We're not good as an industry-- >> Having a good community, self-learning, growth mindset, always be relevant is not a bad strategy. >> Yeah, I mean because I find increasingly, I see people of all ages in companies. There is ageism, there is no doubt. There's financial ageism and then there's kind of psychological bias ageism, but if you keep yourself relevant and you are the up to speed in your thing, people will beat a path to want to work for you because there's still a skill gap in our industry-- >> And that's the key. >> Yeah, make sure that you're on the right side of that skill gap, and you will always have something to offer to people. >> Alan, great to have you come in the studio, great to see you, thanks for the commentary. It's a special CUBEConversation, we're talking about the future of technology impact the society and a range of topics that are emerging, we're on a pioneering, new generational shift and theCUBE is obviously covering the most important stories in Silicon Valley from figuring out what fake news is to impact to the humans around the world and again, we're doing our part to cover it. Alan Cohen, CUBEConversation, I'm John Furrier, thanks for watching. (upbeat music)

>> Announcer: Live from New York City it's The Cube, covering IBM data science for all. Brought to you by IBM. (light digital music) >> Welcome back to data science for all. It's a whole new game. And it is a whole new game. >> Dave Vellante, John Walls here. We've got quite a distinguished panel. So it is a new game-- >> Well we're in the game, I'm just happy to be-- (both laugh) Have a swing at the pitch. >> Well let's what we have here. Five distinguished members of our panel. It'll take me a minute to get through the introductions, but believe me they're worth it. Jennifer Shin joins us. Jennifer's the founder of 8 Path Solutions, the director of the data science of Comcast and part of the faculty at UC Berkeley and NYU. Jennifer, nice to have you with us, we appreciate the time. Joe McKendrick an analyst and contributor of Forbes and ZDNet, Joe, thank you for being here at well. Another ZDNetter next to him, Dion Hinchcliffe, who is a vice president and principal analyst of Constellation Research and also contributes to ZDNet. Good to see you, sir. To the back row, but that doesn't mean anything about the quality of the participation here. Bob Hayes with a killer Batman shirt on by the way, which we'll get to explain in just a little bit. He runs the Business over Broadway. And Joe Caserta, who the founder of Caserta Concepts. Welcome to all of you. Thanks for taking the time to be with us. Jennifer, let me just begin with you. Obviously as a practitioner you're very involved in the industry, you're on the academic side as well. We mentioned Berkeley, NYU, steep experience. So I want you to kind of take your foot in both worlds and tell me about data science. I mean where do we stand now from those two perspectives? How have we evolved to where we are? And how would you describe, I guess the state of data science? >> Yeah so I think that's a really interesting question. There's a lot of changes happening. In part because data science has now become much more established, both in the academic side as well as in industry. So now you see some of the bigger problems coming out. People have managed to have data pipelines set up. But now there are these questions about models and accuracy and data integration. So the really cool stuff from the data science standpoint. We get to get really into the details of the data. And I think on the academic side you now see undergraduate programs, not just graduate programs, but undergraduate programs being involved. UC Berkeley just did a big initiative that they're going to offer data science to undergrads. So that's a huge news for the university. So I think there's a lot of interest from the academic side to continue data science as a major, as a field. But I think in industry one of the difficulties you're now having is businesses are now asking that question of ROI, right? What do I actually get in return in the initial years? So I think there's a lot of work to be done and just a lot of opportunity. It's great because people now understand better with data sciences, but I think data sciences have to really think about that seriously and take it seriously and really think about how am I actually getting a return, or adding a value to the business? >> And there's lot to be said is there not, just in terms of increasing the workforce, the acumen, the training that's required now. It's a still relatively new discipline. So is there a shortage issue? Or is there just a great need? Is the opportunity there? I mean how would you look at that? >> Well I always think there's opportunity to be smart. If you can be smarter, you know it's always better. It gives you advantages in the workplace, it gets you an advantage in academia. The question is, can you actually do the work? The work's really hard, right? You have to learn all these different disciplines, you have to be able to technically understand data. Then you have to understand it conceptually. You have to be able to model with it, you have to be able to explain it. There's a lot of aspects that you're not going to pick up overnight. So I think part of it is endurance. Like are people going to feel motivated enough and dedicate enough time to it to get very good at that skill set. And also of course, you know in terms of industry, will there be enough interest in the long term that there will be a financial motivation. For people to keep staying in the field, right? So I think it's definitely a lot of opportunity. But that's always been there. Like I tell people I think of myself as a scientist and data science happens to be my day job. That's just the job title. But if you are a scientist and you work with data you'll always want to work with data. I think that's just an inherent need. It's kind of a compulsion, you just kind of can't help yourself, but dig a little bit deeper, ask the questions, you can't not think about it. So I think that will always exist. Whether or not it's an industry job in the way that we see it today, and like five years from now, or 10 years from now. I think that's something that's up for debate. >> So all of you have watched the evolution of data and how it effects organizations for a number of years now. If you go back to the days when data warehouse was king, we had a lot of promises about 360 degree views of the customer and how we were going to be more anticipatory in terms and more responsive. In many ways the decision support systems and the data warehousing world didn't live up to those promises. They solved other problems for sure. And so everybody was looking for big data to solve those problems. And they've begun to attack many of them. We talked earlier in The Cube today about fraud detection, it's gotten much, much better. Certainly retargeting of advertising has gotten better. But I wonder if you could comment, you know maybe start with Joe. As to the effect that data and data sciences had on organizations in terms of fulfilling that vision of a 360 degree view of customers and anticipating customer needs. >> So. Data warehousing, I wouldn't say failed. But I think it was unfinished in order to achieve what we need done today. At the time I think it did a pretty good job. I think it was the only place where we were able to collect data from all these different systems, have it in a single place for analytics. The big difference between what I think, between data warehousing and data science is data warehouses were primarily made for the consumer to human beings. To be able to have people look through some tool and be able to analyze data manually. That really doesn't work anymore, there's just too much data to do that. So that's why we need to build a science around it so that we can actually have machines actually doing the analytics for us. And I think that's the biggest stride in the evolution over the past couple of years, that now we're actually able to do that, right? It used to be very, you know you go back to when data warehouses started, you had to be a deep technologist in order to be able to collect the data, write the programs to clean the data. But now you're average causal IT person can do that. Right now I think we're back in data science where you have to be a fairly sophisticated programmer, analyst, scientist, statistician, engineer, in order to do what we need to do, in order to make machines actually understand the data. But I think part of the evolution, we're just in the forefront. We're going to see over the next, not even years, within the next year I think a lot of new innovation where the average person within business and definitely the average person within IT will be able to do as easily say, "What are my sales going to be next year?" As easy as it is to say, "What were my sales last year." Where now it's a big deal. Right now in order to do that you have to build some algorithms, you have to be a specialist on predictive analytics. And I think, you know as the tools mature, as people using data matures, and as the technology ecosystem for data matures, it's going to be easier and more accessible. >> So it's still too hard. (laughs) That's something-- >> Joe C.: Today it is yes. >> You've written about and talked about. >> Yeah no question about it. We see this citizen data scientist. You know we talked about the democratization of data science but the way we talk about analytics and warehousing and all the tools we had before, they generated a lot of insights and views on the information, but they didn't really give us the science part. And that's, I think that what's missing is the forming of the hypothesis, the closing of the loop of. We now have use of this data, but are are changing, are we thinking about it strategically? Are we learning from it and then feeding that back into the process. I think that's the big difference between data science and the analytics side. But, you know just like Google made search available to everyone, not just people who had highly specialized indexers or crawlers. Now we can have tools that make these capabilities available to anyone. You know going back to what Joe said I think the key thing is we now have tools that can look at all the data and ask all the questions. 'Cause we can't possibly do it all ourselves. Our organizations are increasingly awash in data. Which is the life blood of our organizations, but we're not using it, you know this a whole concept of dark data. And so I think the concept, or the promise of opening these tools up for everyone to be able to access those insights and activate them, I think that, you know, that's where it's headed. >> This is kind of where the T shirt comes in right? So Bob if you would, so you've got this Batman shirt on. We talked a little bit about it earlier, but it plays right into what Dion's talking about. About tools and, I don't want to spoil it, but you go ahead (laughs) and tell me about it. >> Right, so. Batman is a super hero, but he doesn't have any supernatural powers, right? He can't fly on his own, he can't become invisible on his own. But the thing is he has the utility belt and he has these tools he can use to help him solve problems. For example he as the bat ring when he's confronted with a building that he wants to get over, right? So he pulls it out and uses that. So as data professionals we have all these tools now that these vendors are making. We have IBM SPSS, we have data science experience. IMB Watson that these data pros can now use it as part of their utility belt and solve problems that they're confronted with. So if you''re ever confronted with like a Churn problem and you have somebody who has access to that data they can put that into IBM Watson, ask a question and it'll tell you what's the key driver of Churn. So it's not that you have to be a superhuman to be a data scientist, but these tools will help you solve certain problems and help your business go forward. >> Joe McKendrick, do you have a comment? >> Does that make the Batmobile the Watson? (everyone laughs) Analogy? >> I was just going to add that, you know all of the billionaires in the world today and none of them decided to become Batman yet. It's very disappointing. >> Yeah. (Joe laughs) >> Go ahead Joe. >> And I just want to add some thoughts to our discussion about what happened with data warehousing. I think it's important to point out as well that data warehousing, as it existed, was fairly successful but for larger companies. Data warehousing is a very expensive proposition it remains a expensive proposition. Something that's in the domain of the Fortune 500. But today's economy is based on a very entrepreneurial model. The Fortune 500s are out there of course it's ever shifting. But you have a lot of smaller companies a lot of people with start ups. You have people within divisions of larger companies that want to innovate and not be tied to the corporate balance sheet. They want to be able to go through, they want to innovate and experiment without having to go through finance and the finance department. So there's all these open source tools available. There's cloud resources as well as open source tools. Hadoop of course being a prime example where you can work with the data and experiment with the data and practice data science at a very low cost. >> Dion mentioned the C word, citizen data scientist last year at the panel. We had a conversation about that. And the data scientists on the panel generally were like, "Stop." Okay, we're not all of a sudden going to turn everybody into data scientists however, what we want to do is get people thinking about data, more focused on data, becoming a data driven organization. I mean as a data scientist I wonder if you could comment on that. >> Well I think so the other side of that is, you know there are also many people who maybe didn't, you know follow through with science, 'cause it's also expensive. A PhD takes a lot of time. And you know if you don't get funding it's a lot of money. And for very little security if you think about how hard it is to get a teaching job that's going to give you enough of a pay off to pay that back. Right, the time that you took off, the investment that you made. So I think the other side of that is by making data more accessible, you allow people who could have been great in science, have an opportunity to be great data scientists. And so I think for me the idea of citizen data scientist, that's where the opportunity is. I think in terms of democratizing data and making it available for everyone, I feel as though it's something similar to the way we didn't really know what KPIs were, maybe 20 years ago. People didn't use it as readily, didn't teach it in schools. I think maybe 10, 20 years from now, some of the things that we're building today from data science, hopefully more people will understand how to use these tools. They'll have a better understanding of working with data and what that means, and just data literacy right? Just being able to use these tools and be able to understand what data's saying and actually what it's not saying. Which is the thing that most people don't think about. But you can also say that data doesn't say anything. There's a lot of noise in it. There's too much noise to be able to say that there is a result. So I think that's the other side of it. So yeah I guess in terms for me, in terms of data a serious data scientist, I think it's a great idea to have that, right? But at the same time of course everyone kind of emphasized you don't want everyone out there going, "I can be a data scientist without education, "without statistics, without math," without understanding of how to implement the process. I've seen a lot of companies implement the same sort of process from 10, 20 years ago just on Hadoop instead of SQL. Right and it's very inefficient. And the only difference is that you can build more tables wrong than they could before. (everyone laughs) Which is I guess >> For less. it's an accomplishment and for less, it's cheaper, yeah. >> It is cheaper. >> Otherwise we're like I'm not a data scientist but I did stay at a Holiday Inn Express last night, right? >> Yeah. (panelists laugh) And there's like a little bit of pride that like they used 2,000, you know they used 2,000 computers to do it. Like a little bit of pride about that, but you know of course maybe not a great way to go. I think 20 years we couldn't do that, right? One computer was already an accomplishment to have that resource. So I think you have to think about the fact that if you're doing it wrong, you're going to just make that mistake bigger, which his also the other side of working with data. >> Sure, Bob. >> Yeah I have a comment about that. I've never liked the term citizen data scientist or citizen scientist. I get the point of it and I think employees within companies can help in the data analytics problem by maybe being a data collector or something. I mean I would never have just somebody become a scientist based on a few classes here she takes. It's like saying like, "Oh I'm going to be a citizen lawyer." And so you come to me with your legal problems, or a citizen surgeon. Like you need training to be good at something. You can't just be good at something just 'cause you want to be. >> John: Joe you wanted to say something too on that. >> Since we're in New York City I'd like to use the analogy of a real scientist versus a data scientist. So real scientist requires tools, right? And the tools are not new, like microscopes and a laboratory and a clean room. And these tools have evolved over years and years, and since we're in New York we could walk within a 10 block radius and buy any of those tools. It doesn't make us a scientist because we use those tools. I think with data, you know making, making the tools evolve and become easier to use, you know like Bob was saying, it doesn't make you a better data scientist, it just makes the data more accessible. You know we can go buy a microscope, we can go buy Hadoop, we can buy any kind of tool in a data ecosystem, but it doesn't really make you a scientist. I'm very involved in the NYU data science program and the Columbia data science program, like these kids are brilliant. You know these kids are not someone who is, you know just trying to run a day to day job, you know in corporate America. I think the people who are running the day to day job in corporate America are going to be the recipients of data science. Just like people who take drugs, right? As a result of a smart data scientist coming up with a formula that can help people, I think we're going to make it easier to distribute the data that can help people with all the new tools. But it doesn't really make it, you know the access to the data and tools available doesn't really make you a better data scientist. Without, like Bob was saying, without better training and education. >> So how-- I'm sorry, how do you then, if it's not for everybody, but yet I'm the user at the end of the day at my company and I've got these reams of data before me, how do you make it make better sense to me then? So that's where machine learning comes in or artificial intelligence and all this stuff. So how at the end of the day, Dion? How do you make it relevant and usable, actionable to somebody who might not be as practiced as you would like? >> I agree with Joe that many of us will be the recipients of data science. Just like you had to be a computer science at one point to develop programs for a computer, now we can get the programs. You don't need to be a computer scientist to get a lot of value out of our IT systems. The same thing's going to happen with data science. There's far more demand for data science than there ever could be produced by, you know having an ivory tower filled with data scientists. Which we need those guys, too, don't get me wrong. But we need to have, productize it and make it available in packages such that it can be consumed. The outputs and even some of the inputs can be provided by mere mortals, whether that's machine learning or artificial intelligence or bots that go off and run the hypotheses and select the algorithms maybe with some human help. We have to productize it. This is a constant of data scientist of service, which is becoming a thing now. It's, "I need this, I need this capability at scale. "I need it fast and I need it cheap." The commoditization of data science is going to happen. >> That goes back to what I was saying about, the recipient also of data science is also machines, right? Because I think the other thing that's happening now in the evolution of data is that, you know the data is, it's so tightly coupled. Back when you were talking about data warehousing you have all the business transactions then you take the data out of those systems, you put them in a warehouse for analysis, right? Maybe they'll make a decision to change that system at some point. Now the analytics platform and the business application is very tightly coupled. They become dependent upon one another. So you know people who are using the applications are now be able to take advantage of the insights of data analytics and data science, just through the app. Which never really existed before. >> I have one comment on that. You were talking about how do you get the end user more involved, well like we said earlier data science is not easy, right? As an end user, I encourage you to take a stats course, just a basic stats course, understanding what a mean is, variability, regression analysis, just basic stuff. So you as an end user can get more, or glean more insight from the reports that you're given, right? If you go to France and don't know French, then people can speak really slowly to you in French, you're not going to get it. You need to understand the language of data to get value from the technology we have available to us. >> Incidentally French is one of the languages that you have the option of learning if you're a mathematicians. So math PhDs are required to learn a second language. France being the country of algebra, that's one of the languages you could actually learn. Anyway tangent. But going back to the point. So statistics courses, definitely encourage it. I teach statistics. And one of the things that I'm finding as I go through the process of teaching it I'm actually bringing in my experience. And by bringing in my experience I'm actually kind of making the students think about the data differently. So the other thing people don't think about is the fact that like statisticians typically were expected to do, you know, just basic sort of tasks. In a sense that they're knowledge is specialized, right? But the day to day operations was they ran some data, you know they ran a test on some data, looked at the results, interpret the results based on what they were taught in school. They didn't develop that model a lot of times they just understand what the tests were saying, especially in the medical field. So when you when think about things like, we have words like population, census. Which is when you take data from every single, you have every single data point versus a sample, which is a subset. It's a very different story now that we're collecting faster than it used to be. It used to be the idea that you could collect information from everyone. Like it happens once every 10 years, we built that in. But nowadays you know, you know here about Facebook, for instance, I think they claimed earlier this year that their data was more accurate than the census data. So now there are these claims being made about which data source is more accurate. And I think the other side of this is now statisticians are expected to know data in a different way than they were before. So it's not just changing as a field in data science, but I think the sciences that are using data are also changing their fields as well. >> Dave: So is sampling dead? >> Well no, because-- >> Should it be? (laughs) >> Well if you're sampling wrong, yes. That's really the question. >> Okay. You know it's been said that the data doesn't lie, people do. Organizations are very political. Oftentimes you know, lies, damned lies and statistics, Benjamin Israeli. Are you seeing a change in the way in which organizations are using data in the context of the politics. So, some strong P&L manager say gets data and crafts it in a way that he or she can advance their agenda. Or they'll maybe attack a data set that is, probably should drive them in a different direction, but might be antithetical to their agenda. Are you seeing data, you know we talked about democratizing data, are you seeing that reduce the politics inside of organizations? >> So you know we've always used data to tell stories at the top level of an organization that's what it's all about. And I still see very much that no matter how much data science or, the access to the truth through looking at the numbers that story telling is still the political filter through which all that data still passes, right? But it's the advent of things like Block Chain, more and more corporate records and corporate information is going to end up in these open and shared repositories where there is not alternate truth. It'll come back to whoever tells the best stories at the end of the day. So I still see the organizations are very political. We are seeing now more open data though. Open data initiatives are a big thing, both in government and in the private sector. It is having an effect, but it's slow and steady. So that's what I see. >> Um, um, go ahead. >> I was just going to say as well. Ultimately I think data driven decision making is a great thing. And it's especially useful at the lower tiers of the organization where you have the routine day to day's decisions that could be automated through machine learning and deep learning. The algorithms can be improved on a constant basis. On the upper levels, you know that's why you pay executives the big bucks in the upper levels to make the strategic decisions. And data can help them, but ultimately, data, IT, technology alone will not create new markets, it will not drive new businesses, it's up to human beings to do that. The technology is the tool to help them make those decisions. But creating businesses, growing businesses, is very much a human activity. And that's something I don't see ever getting replaced. Technology might replace many other parts of the organization, but not that part. >> I tend to be a foolish optimist when it comes to this stuff. >> You do. (laughs) >> I do believe that data will make the world better. I do believe that data doesn't lie people lie. You know I think as we start, I'm already seeing trends in industries, all different industries where, you know conventional wisdom is starting to get trumped by analytics. You know I think it's still up to the human being today to ignore the facts and go with what they think in their gut and sometimes they win, sometimes they lose. But generally if they lose the data will tell them that they should have gone the other way. I think as we start relying more on data and trusting data through artificial intelligence, as we start making our lives a little bit easier, as we start using smart cars for safety, before replacement of humans. AS we start, you know, using data really and analytics and data science really as the bumpers, instead of the vehicle, eventually we're going to start to trust it as the vehicle itself. And then it's going to make lying a little bit harder. >> Okay, so great, excellent. Optimism, I love it. (John laughs) So I'm going to play devil's advocate here a little bit. There's a couple elephant in the room topics that I want to, to explore a little bit. >> Here it comes. >> There was an article today in Wired. And it was called, Why AI is Still Waiting for It's Ethics Transplant. And, I will just read a little segment from there. It says, new ethical frameworks for AI need to move beyond individual responsibility to hold powerful industrial, government and military interests accountable as they design and employ AI. When tech giants build AI products, too often user consent, privacy and transparency are overlooked in favor of frictionless functionality that supports profit driven business models based on aggregate data profiles. This is from Kate Crawford and Meredith Whittaker who founded AI Now. And they're calling for sort of, almost clinical trials on AI, if I could use that analogy. Before you go to market you've got to test the human impact, the social impact. Thoughts. >> And also have the ability for a human to intervene at some point in the process. This goes way back. Is everybody familiar with the name Stanislav Petrov? He's the Soviet officer who back in 1983, it was in the control room, I guess somewhere outside of Moscow in the control room, which detected a nuclear missile attack against the Soviet Union coming out of the United States. Ordinarily I think if this was an entirely AI driven process we wouldn't be sitting here right now talking about it. But this gentlemen looked at what was going on on the screen and, I'm sure he's accountable to his authorities in the Soviet Union. He probably got in a lot of trouble for this, but he decided to ignore the signals, ignore the data coming out of, from the Soviet satellites. And as it turned out, of course he was right. The Soviet satellites were seeing glints of the sun and they were interpreting those glints as missile launches. And I think that's a great example why, you know every situation of course doesn't mean the end of the world, (laughs) it was in this case. But it's a great example why there needs to be a human component, a human ability for human intervention at some point in the process. >> So other thoughts. I mean organizations are driving AI hard for profit. Best minds of our generation are trying to figure out how to get people to click on ads. Jeff Hammerbacher is famous for saying it. >> You can use data for a lot of things, data analytics, you can solve, you can cure cancer. You can make customers click on more ads. It depends on what you're goal is. But, there are ethical considerations we need to think about. When we have data that will have a racial bias against blacks and have them have higher prison sentences or so forth or worse credit scores, so forth. That has an impact on a broad group of people. And as a society we need to address that. And as scientists we need to consider how are we going to fix that problem? Cathy O'Neil in her book, Weapons of Math Destruction, excellent book, I highly recommend that your listeners read that book. And she talks about these issues about if AI, if algorithms have a widespread impact, if they adversely impact protected group. And I forget the last criteria, but like we need to really think about these things as a people, as a country. >> So always think the idea of ethics is interesting. So I had this conversation come up a lot of times when I talk to data scientists. I think as a concept, right as an idea, yes you want things to be ethical. The question I always pose to them is, "Well in the business setting "how are you actually going to do this?" 'Cause I find the most difficult thing working as a data scientist, is to be able to make the day to day decision of when someone says, "I don't like that number," how do you actually get around that. If that's the right data to be showing someone or if that's accurate. And say the business decides, "Well we don't like that number." Many people feel pressured to then change the data, change, or change what the data shows. So I think being able to educate people to be able to find ways to say what the data is saying, but not going past some line where it's a lie, where it's unethical. 'Cause you can also say what data doesn't say. You don't always have to say what the data does say. You can leave it as, "Here's what we do know, "but here's what we don't know." There's a don't know part that many people will omit when they talk about data. So I think, you know especially when it comes to things like AI it's tricky, right? Because I always tell people I don't know everyone thinks AI's going to be so amazing. I started an industry by fixing problems with computers that people didn't realize computers had. For instance when you have a system, a lot of bugs, we all have bug reports that we've probably submitted. I mean really it's no where near the point where it's going to start dominating our lives and taking over all the jobs. Because frankly it's not that advanced. It's still run by people, still fixed by people, still managed by people. I think with ethics, you know a lot of it has to do with the regulations, what the laws say. That's really going to be what's involved in terms of what people are willing to do. A lot of businesses, they want to make money. If there's no rules that says they can't do certain things to make money, then there's no restriction. I think the other thing to think about is we as consumers, like everyday in our lives, we shouldn't separate the idea of data as a business. We think of it as a business person, from our day to day consumer lives. Meaning, yes I work with data. Incidentally I also always opt out of my credit card, you know when they send you that information, they make you actually mail them, like old school mail, snail mail like a document that says, okay I don't want to be part of this data collection process. Which I always do. It's a little bit more work, but I go through that step of doing that. Now if more people did that, perhaps companies would feel more incentivized to pay you for your data, or give you more control of your data. Or at least you know, if a company's going to collect information, I'd want you to be certain processes in place to ensure that it doesn't just get sold, right? For instance if a start up gets acquired what happens with that data they have on you? You agree to give it to start up. But I mean what are the rules on that? So I think we have to really think about the ethics from not just, you know, someone who's going to implement something but as consumers what control we have for our own data. 'Cause that's going to directly impact what businesses can do with our data. >> You know you mentioned data collection. So slightly on that subject. All these great new capabilities we have coming. We talked about what's going to happen with media in the future and what 5G technology's going to do to mobile and these great bandwidth opportunities. The internet of things and the internet of everywhere. And all these great inputs, right? Do we have an arms race like are we keeping up with the capabilities to make sense of all the new data that's going to be coming in? And how do those things square up in this? Because the potential is fantastic, right? But are we keeping up with the ability to make it make sense and to put it to use, Joe? >> So I think data ingestion and data integration is probably one of the biggest challenges. I think, especially as the world is starting to become more dependent on data. I think you know, just because we're dependent on numbers we've come up with GAAP, which is generally accepted accounting principles that can be audited and proven whether it's true or false. I think in our lifetime we will see something similar to that we will we have formal checks and balances of data that we use that can be audited. Getting back to you know what Dave was saying earlier about, I personally would trust a machine that was programmed to do the right thing, than to trust a politician or some leader that may have their own agenda. And I think the other thing about machines is that they are auditable. You know you can look at the code and see exactly what it's doing and how it's doing it. Human beings not so much. So I think getting to the truth, even if the truth isn't the answer that we want, I think is a positive thing. It's something that we can't do today that once we start relying on machines to do we'll be able to get there. >> Yeah I was just going to add that we live in exponential times. And the challenge is that the way that we're structured traditionally as organizations is not allowing us to absorb advances exponentially, it's linear at best. Everyone talks about change management and how are we going to do digital transformation. Evidence shows that technology's forcing the leaders and the laggards apart. There's a few leading organizations that are eating the world and they seem to be somehow rolling out new things. I don't know how Amazon rolls out all this stuff. There's all this artificial intelligence and the IOT devices, Alexa, natural language processing and that's just a fraction, it's just a tip of what they're releasing. So it just shows that there are some organizations that have path found the way. Most of the Fortune 500 from the year 2000 are gone already, right? The disruption is happening. And so we are trying, have to find someway to adopt these new capabilities and deploy them effectively or the writing is on the wall. I spent a lot of time exploring this topic, how are we going to get there and all of us have a lot of hard work is the short answer. >> I read that there's going to be more data, or it was predicted, more data created in this year than in the past, I think it was five, 5,000 years. >> Forever. (laughs) >> And that to mix the statistics that we're analyzing currently less than 1% of the data. To taking those numbers and hear what you're all saying it's like, we're not keeping up, it seems like we're, it's not even linear. I mean that gap is just going to grow and grow and grow. How do we close that? >> There's a guy out there named Chris Dancy, he's known as the human cyborg. He has 700 hundred sensors all over his body. And his theory is that data's not new, having access to the data is new. You know we've always had a blood pressure, we've always had a sugar level. But we were never able to actually capture it in real time before. So now that we can capture and harness it, now we can be smarter about it. So I think that being able to use this information is really incredible like, this is something that over our lifetime we've never had and now we can do it. Which hence the big explosion in data. But I think how we use it and have it governed I think is the challenge right now. It's kind of cowboys and indians out there right now. And without proper governance and without rigorous regulation I think we are going to have some bumps in the road along the way. >> The data's in the oil is the question how are we actually going to operationalize around it? >> Or find it. Go ahead. >> I will say the other side of it is, so if you think about information, we always have the same amount of information right? What we choose to record however, is a different story. Now if you want wanted to know things about the Olympics, but you decide to collect information every day for years instead of just the Olympic year, yes you have a lot of data, but did you need all of that data? For that question about the Olympics, you don't need to collect data during years there are no Olympics, right? Unless of course you're comparing it relative. But I think that's another thing to think about. Just 'cause you collect more data does not mean that data will produce more statistically significant results, it does not mean it'll improve your model. You can be collecting data about your shoe size trying to get information about your hair. I mean it really does depend on what you're trying to measure, what your goals are, and what the data's going to be used for. If you don't factor the real world context into it, then yeah you can collect data, you know an infinite amount of data, but you'll never process it. Because you have no question to ask you're not looking to model anything. There is no universal truth about everything, that just doesn't exist out there. >> I think she's spot on. It comes down to what kind of questions are you trying to ask of your data? You can have one given database that has 100 variables in it, right? And you can ask it five different questions, all valid questions and that data may have those variables that'll tell you what's the best predictor of Churn, what's the best predictor of cancer treatment outcome. And if you can ask the right question of the data you have then that'll give you some insight. Just data for data's sake, that's just hype. We have a lot of data but it may not lead to anything if we don't ask it the right questions. >> Joe. >> I agree but I just want to add one thing. This is where the science in data science comes in. Scientists often will look at data that's already been in existence for years, weather forecasts, weather data, climate change data for example that go back to data charts and so forth going back centuries if that data is available. And they reformat, they reconfigure it, they get new uses out of it. And the potential I see with the data we're collecting is it may not be of use to us today, because we haven't thought of ways to use it, but maybe 10, 20, even 100 years from now someone's going to think of a way to leverage the data, to look at it in new ways and to come up with new ideas. That's just my thought on the science aspect. >> Knowing what you know about data science, why did Facebook miss Russia and the fake news trend? They came out and admitted it. You know, we miss it, why? Could they have, is it because they were focused elsewhere? Could they have solved that problem? (crosstalk) >> It's what you said which is are you asking the right questions and if you're not looking for that problem in exactly the way that it occurred you might not be able to find it. >> I thought the ads were paid in rubles. Shouldn't that be your first clue (panelists laugh) that something's amiss? >> You know red flag, so to speak. >> Yes. >> I mean Bitcoin maybe it could have hidden it. >> Bob: Right, exactly. >> I would think too that what happened last year is actually was the end of an age of optimism. I'll bring up the Soviet Union again, (chuckles). It collapsed back in 1991, 1990, 1991, Russia was reborn in. And think there was a general feeling of optimism in the '90s through the 2000s that Russia is now being well integrated into the world economy as other nations all over the globe, all continents are being integrated into the global economy thanks to technology. And technology is lifting entire continents out of poverty and ensuring more connectedness for people. Across Africa, India, Asia, we're seeing those economies that very different countries than 20 years ago and that extended into Russia as well. Russia is part of the global economy. We're able to communicate as a global, a global network. I think as a result we kind of overlook the dark side that occurred. >> John: Joe? >> Again, the foolish optimist here. But I think that... It shouldn't be the question like how did we miss it? It's do we have the ability now to catch it? And I think without data science without machine learning, without being able to train machines to look for patterns that involve corruption or result in corruption, I think we'd be out of luck. But now we have those tools. And now hopefully, optimistically, by the next election we'll be able to detect these things before they become public. >> It's a loaded question because my premise was Facebook had the ability and the tools and the knowledge and the data science expertise if in fact they wanted to solve that problem, but they were focused on other problems, which is how do I get people to click on ads? >> Right they had the ability to train the machines, but they were giving the machines the wrong training. >> Looking under the wrong rock. >> (laughs) That's right. >> It is easy to play armchair quarterback. Another topic I wanted to ask the panel about is, IBM Watson. You guys spend time in the Valley, I spend time in the Valley. People in the Valley poo-poo Watson. Ah, Google, Facebook, Amazon they've got the best AI. Watson, and some of that's fair criticism. Watson's a heavy lift, very services oriented, you just got to apply it in a very focused. At the same time Google's trying to get you to click on Ads, as is Facebook, Amazon's trying to get you to buy stuff. IBM's trying to solve cancer. Your thoughts on that sort of juxtaposition of the different AI suppliers and there may be others. Oh, nobody wants to touch this one, come on. I told you elephant in the room questions. >> Well I mean you're looking at two different, very different types of organizations. One which is really spent decades in applying technology to business and these other companies are ones that are primarily into the consumer, right? When we talk about things like IBM Watson you're looking at a very different type of solution. You used to be able to buy IT and once you installed it you pretty much could get it to work and store your records or you know, do whatever it is you needed it to do. But these types of tools, like Watson actually tries to learn your business. And it needs to spend time doing that watching the data and having its models tuned. And so you don't get the results right away. And I think that's been kind of the challenge that organizations like IBM has had. Like this is a different type of technology solution, one that has to actually learn first before it can provide value. And so I think you know you have organizations like IBM that are much better at applying technology to business, and then they have the further hurdle of having to try to apply these tools that work in very different ways. There's education too on the side of the buyer. >> I'd have to say that you know I think there's plenty of businesses out there also trying to solve very significant, meaningful problems. You know with Microsoft AI and Google AI and IBM Watson, I think it's not really the tool that matters, like we were saying earlier. A fool with a tool is still a fool. And regardless of who the manufacturer of that tool is. And I think you know having, a thoughtful, intelligent, trained, educated data scientist using any of these tools can be equally effective. >> So do you not see core AI competence and I left out Microsoft, as a strategic advantage for these companies? Is it going to be so ubiquitous and available that virtually anybody can apply it? Or is all the investment in R&D and AI going to pay off for these guys? >> Yeah, so I think there's different levels of AI, right? So there's AI where you can actually improve the model. I remember when I was invited when Watson was kind of first out by IBM to a private, sort of presentation. And my question was, "Okay, so when do I get "to access the corpus?" The corpus being sort of the foundation of NLP, which is natural language processing. So it's what you use as almost like a dictionary. Like how you're actually going to measure things, or things up. And they said, "Oh you can't." "What do you mean I can't?" It's like, "We do that." "So you're telling me as a data scientist "you're expecting me to rely on the fact "that you did it better than me and I should rely on that." I think over the years after that IBM started opening it up and offering different ways of being able to access the corpus and work with that data. But I remember at the first Watson hackathon there was only two corpus available. It was either the travel or medicine. There was no other foundational data available. So I think one of the difficulties was, you know IBM being a little bit more on the forefront of it they kind of had that burden of having to develop these systems and learning kind of the hard way that if you don't have the right models and you don't have the right data and you don't have the right access, that's going to be a huge limiter. I think with things like medical, medical information that's an extremely difficult data to start with. Partly because you know anything that you do find or don't find, the impact is significant. If I'm looking at things like what people clicked on the impact of using that data wrong, it's minimal. You might lose some money. If you do that with healthcare data, if you do that with medical data, people may die, like this is a much more difficult data set to start with. So I think from a scientific standpoint it's great to have any information about a new technology, new process. That's the nice that is that IBM's obviously invested in it and collected information. I think the difficulty there though is just 'cause you have it you can't solve everything. And if feel like from someone who works in technology, I think in general when you appeal to developers you try not to market. And with Watson it's very heavily marketed, which tends to turn off people who are more from the technical side. Because I think they don't like it when it's gimmicky in part because they do the opposite of that. They're always trying to build up the technical components of it. They don't like it when you're trying to convince them that you're selling them something when you could just give them the specs and look at it. So it could be something as simple as communication. But I do think it is valuable to have had a company who leads on the forefront of that and try to do so we can actually learn from what IBM has learned from this process. >> But you're an optimist. (John laughs) All right, good. >> Just one more thought. >> Joe go ahead first. >> Joe: I want to see how Alexa or Siri do on Jeopardy. (panelists laugh) >> All right. Going to go around a final thought, give you a second. Let's just think about like your 12 month crystal ball. In terms of either challenges that need to be met in the near term or opportunities you think will be realized. 12, 18 month horizon. Bob you've got the microphone headed up, so I'll let you lead off and let's just go around. >> I think a big challenge for business, for society is getting people educated on data and analytics. There's a study that was just released I think last month by Service Now, I think, or some vendor, or Click. They found that only 17% of the employees in Europe have the ability to use data in their job. Think about that. >> 17. >> 17. Less than 20%. So these people don't have the ability to understand or use data intelligently to improve their work performance. That says a lot about the state we're in today. And that's Europe. It's probably a lot worse in the United States. So that's a big challenge I think. To educate the masses. >> John: Joe. >> I think we probably have a better chance of improving technology over training people. I think using data needs to be iPhone easy. And I think, you know which means that a lot of innovation is in the years to come. I do think that a keyboard is going to be a thing of the past for the average user. We are going to start using voice a lot more. I think augmented reality is going to be things that becomes a real reality. Where we can hold our phone in front of an object and it will have an overlay of prices where it's available, if it's a person. I think that we will see within an organization holding a camera up to someone and being able to see what is their salary, what sales did they do last year, some key performance indicators. I hope that we are beyond the days of everyone around the world walking around like this and we start actually becoming more social as human beings through augmented reality. I think, it has to happen. I think we're going through kind of foolish times at the moment in order to get to the greater good. And I think the greater good is using technology in a very, very smart way. Which means that you shouldn't have to be, sorry to contradict, but maybe it's good to counterpoint. I don't think you need to have a PhD in SQL to use data. Like I think that's 1990. I think as we evolve it's going to become easier for the average person. Which means people like the brain trust here needs to get smarter and start innovating. I think the innovation around data is really at the tip of the iceberg, we're going to see a lot more of it in the years to come. >> Dion why don't you go ahead, then we'll come down the line here. >> Yeah so I think over that time frame two things are likely to happen. One is somebody's going to crack the consumerization of machine learning and AI, such that it really is available to the masses and we can do much more advanced things than we could. We see the industries tend to reach an inflection point and then there's an explosion. No one's quite cracked the code on how to really bring this to everyone, but somebody will. And that could happen in that time frame. And then the other thing that I think that almost has to happen is that the forces for openness, open data, data sharing, open data initiatives things like Block Chain are going to run headlong into data protection, data privacy, customer privacy laws and regulations that have to come down and protect us. Because the industry's not doing it, the government is stepping in and it's going to re-silo a lot of our data. It's going to make it recede and make it less accessible, making data science harder for a lot of the most meaningful types of activities. Patient data for example is already all locked down. We could do so much more with it, but health start ups are really constrained about what they can do. 'Cause they can't access the data. We can't even access our own health care records, right? So I think that's the challenge is we have to have that battle next to be able to go and take the next step. >> Well I see, with the growth of data a lot of it's coming through IOT, internet of things. I think that's a big source. And we're going to see a lot of innovation. A new types of Ubers or Air BnBs. Uber's so 2013 though, right? We're going to see new companies with new ideas, new innovations, they're going to be looking at the ways this data can be leveraged all this big data. Or data coming in from the IOT can be leveraged. You know there's some examples out there. There's a company for example that is outfitting tools, putting sensors in the tools. Industrial sites can therefore track where the tools are at any given time. This is an expensive, time consuming process, constantly loosing tools, trying to locate tools. Assessing whether the tool's being applied to the production line or the right tool is at the right torque and so forth. With the sensors implanted in these tools, it's now possible to be more efficient. And there's going to be innovations like that. Maybe small start up type things or smaller innovations. We're going to see a lot of new ideas and new types of approaches to handling all this data. There's going to be new business ideas. The next Uber, we may be hearing about it a year from now whatever that may be. And that Uber is going to be applying data, probably IOT type data in some, new innovative way. >> Jennifer, final word. >> Yeah so I think with data, you know it's interesting, right, for one thing I think on of the things that's made data more available and just people we open to the idea, has been start ups. But what's interesting about this is a lot of start ups have been acquired. And a lot of people at start ups that got acquired now these people work at bigger corporations. Which was the way it was maybe 10 years ago, data wasn't available and open, companies kept it very proprietary, you had to sign NDAs. It was like within the last 10 years that open source all of that initiatives became much more popular, much more open, a acceptable sort of way to look at data. I think that what I'm kind of interested in seeing is what people do within the corporate environment. Right, 'cause they have resources. They have funding that start ups don't have. And they have backing, right? Presumably if you're acquired you went in at a higher title in the corporate structure whereas if you had started there you probably wouldn't be at that title at that point. So I think you have an opportunity where people who have done innovative things and have proven that they can build really cool stuff, can now be in that corporate environment. I think part of it's going to be whether or not they can really adjust to sort of the corporate, you know the corporate landscape, the politics of it or the bureaucracy. I think every organization has that. Being able to navigate that is a difficult thing in part 'cause it's a human skill set, it's a people skill, it's a soft skill. It's not the same thing as just being able to code something and sell it. So you know it's going to really come down to people. I think if people can figure out for instance, what people want to buy, what people think, in general that's where the money comes from. You know you make money 'cause someone gave you money. So if you can find a way to look at a data or even look at technology and understand what people are doing, aren't doing, what they're happy about, unhappy about, there's always opportunity in collecting the data in that way and being able to leverage that. So you build cooler things, and offer things that haven't been thought of yet. So it's a very interesting time I think with the corporate resources available if you can do that. You know who knows what we'll have in like a year. >> I'll add one. >> Please. >> The majority of companies in the S&P 500 have a market cap that's greater than their revenue. The reason is 'cause they have IP related to data that's of value. But most of those companies, most companies, the vast majority of companies don't have any way to measure the value of that data. There's no GAAP accounting standard. So they don't understand the value contribution of their data in terms of how it helps them monetize. Not the data itself necessarily, but how it contributes to the monetization of the company. And I think that's a big gap. If you don't understand the value of the data that means you don't understand how to refine it, if data is the new oil and how to protect it and so forth and secure it. So that to me is a big gap that needs to get closed before we can actually say we live in a data driven world. >> So you're saying I've got an asset, I don't know if it's worth this or this. And they're missing that great opportunity. >> So devolve to what I know best. >> Great discussion. Really, really enjoyed the, the time as flown by. Joe if you get that augmented reality thing to work on the salary, point it toward that guy not this guy, okay? (everyone laughs) It's much more impressive if you point it over there. But Joe thank you, Dion, Joe and Jennifer and Batman. We appreciate and Bob Hayes, thanks for being with us. >> Thanks you guys. >> Really enjoyed >> Great stuff. >> the conversation. >> And a reminder coming up a the top of the hour, six o'clock Eastern time, IBMgo.com featuring the live keynote which is being set up just about 50 feet from us right now. Nick Silver is one of the headliners there, John Thomas is well, or rather Rob Thomas. John Thomas we had on earlier on The Cube. But a panel discussion as well coming up at six o'clock on IBMgo.com, six to 7:15. Be sure to join that live stream. That's it from The Cube. We certainly appreciate the time. Glad to have you along here in New York. And until the next time, take care. (bright digital music)