>>Welcome everyone to our continuous coverage on the cube of AWS reinvent 2021. I'm your host, Dave Nicholson. And I am absolutely delighted to be joined by two folks from Unisys. I have a company that has been in the business of helping people with everything related to it for a very, very long time. We heard a talk about data monetization at modernization with ANU Priya, rom Raj vice president of cloud solution management at Unisys, along with ANU palms, the high VP and CTO of cloud solution engineering at UNISIS. And, uh, just so that we keep everything clear, I'm just going to call you on new and ANU Palm, and we'll all know who we're talking to. Sure. The funny thing is I'm David Nicholson or Dave Nicholson. Dave Vellante is one of the founders of Silicon angle, the cube. So usually it's two Dave's battling in >>So I get to be David and he's Dave typically. So we're completely, we're completely used to this, right? So, so tell me about what Eunice is doing UNISIS is doing in the arena of app modernization and data modernization and migration into cloud. You Unisys has a long and storied history of managing it in people's environments, you know, in the sort of on-premise world, as well as, as well as cloud now. But, uh, I knew tell us, tell us a little about what you'd assist is doing in this space. And then we'll, we'll double click and dive in. >>Um, so you, you're probably very, very familiar with the six RS of modernization, right? All the way from migration modernization, all the way from replatform rehost to, to the other side of the spectrum, refactor and rearchitect, right? So what is DASA is that it takes clients on that journey, right? So we see clients in different stages of that journey. There are clients that come to us, uh, recently brought on board a pipeline they're very early in their journey. They just talking about their first set of migrations. There are clients that have taken the leap and done 75% of their workload is on cloud, even for Unisys 95% of more than 95% of our workload actually runs on cloud public cloud. So different stages of the journey, but no matter where they are in the journey, really moving the needle on modernization. Right. And what did he mean by modernization? It's it's taking advantage of the innovation in cloud, whether it's seven containers are AI and bringing that to the client so that they can drive those business outcomes. That's what we are passionate about doing. And we can talk to you about a couple of clients where we've done this on a, but I like to unopened to add on. >>Sure. Yeah. And, and just, and before you dive in on a Palm, I want to hear specifically about the inhibitors that you're seeing, the things that causing friction, right. Movement to cloud. >>Yeah. So cloud of the transformative technology is as disruptive and it brings about lots of benefits that are very well understood, but not realized, um, lower total cost of ownership, higher security, innovation, and agility. But the challenges that you see for customers really benefit from moving and migrating to the cloud are related to security and compliance. That comes up to be the top pain point, followed by cost of ownership that are optimizations that you need to do before you can benefit from really leveraging the benefits from the cloud and then innovation and agility, how to drive that. And there are certain things around app and data about innovation, data analytics, AIML that really helps realize those values, but it needs a concerted effort and a drive and a push to transform your infrastructure from where you are today to really get to derive the true benefits from the cloud. >>And we do a cloud barometer study of about thousands of organizations from a Unisys perspective, Dave, and as a Oklahoma saying, um, more than 60% of our clients say security is the biggest inhibitor they want help with security. You >>No, you're saying the inhibitor to going to cloud is security >>To accelerating the cloud journey. They always are perceptive. >>Is that, is that hesitancy, uh, just perception or is it reality? >>That's a great question, >>Dave, and you don't have to be gentle with me. Like you might with a client, you know, you can, you can reach over and smack me and say get over it. You're going to be fine, Dave, >>Actually, I'm a new from leaned into it already. In many cases, when you, when you actually get to your cloud configuration, right. You probably be more secure in the cloud, but it's getting clients confident with that setup. That's where the rubber meets the road. Right. And that's where we come in to say, um, do you understand the shared responsibility model with cloud? What is the cloud provider do? What does being here at AWS reinvent? What has AWS bring to the table for security? This is what the client is responsible for. For example, application security is completely their client's responsibility, right? In most cases. So, um, just working with the clients so that they understand the shared responsibility model and then making sure we protect all the different layers of the stack, but security, right? Even, even as apps are developed, you need to have DevSecOps pipeline, right? So I didn't say dev ops, I said, dev sec ops, because we want to make security a part of developing your applications and deploying them in cloud as well. So that's what we bring to the table and making sure clients feel confident in, in accelerating their cloud journey. So >>You can deal with customers like me, who, who truly believed that my money is safer in a coffee, can buried in my backyard than it is in a bank, right. With all those banking people wandering around. Um, so when you start looking at an environment and you, and you look at the totality of an it infrastructure landscape, how do you go about determining what is the low hanging fruit? What makes sense to move first from is that, is that always an ROI discussion that comes into play and are your customers, I like to give like five questions at the same time to confuse you and are your customers expecting to immediately save money? And how big is the ROI conversation in this? >>Uh, great question. So a couple of things need to be considered first, just to understand where does the customer in the digital transformation journey are there green fee where they only have on premise data center and they're trying to get to the cloud, or they already have dipped their toes and move to the cloud. And in the cloud, how far in advance are they in their transformation journey, have them not have the done apps and data modernization? Do they have, uh, uh, management operations capability for day one and day two cloud ops and fin ops and security ops, and other leveraging the power of the cloud, the copious amounts of data that cloud brings to the table. Uh, the, the important thing to understand is that 80% of the tools that work in the on-prem do not work in the cloud. So you have to understand the very nature of the cloud and to deal with it differently. >>The same old tools and creeks will not work in the cloud. And I call it the three V's in the cloud, velocity volume, and variety of data is different in the cloud. So when you're talking about security, you need to look at the cloud infrastructure, posture management. You need to look at the cloud workload, pasture management. You need to look at the data that's available and analyze and harness the data using AIML and data analytics. So you need a new set of clicks as it were to really harness the power of the cloud to derive the benefits from increased security, lower cost of ownership and innovation and agility. >>And it makes sense. Yeah. >>I mean, I think you touched on touched on it, but fin ops, right. And you asked the question David on, is that the biggest driver in terms of savings to get to the, to the cloud. And I think it's definitely one of the bigger factors, um, because, and be believe to, to realize that we offer a fin op service. And if you know, Upserve is not just for the cloud, but choosing models at different, right. It's not like your data center planning. We talked about the tools being different. It's more than the tools, right? So you could do reserved instances or you could do spot instances, completely different ballgame with AWS, right. Or you could do AWS savings plans. Are you maximizing all of that? And even beyond that, are you thinking beyond that into like AWS container suppose, um, EKS, are you talking about seven less and that could completely change your bill and your total kind of cost of ownership. You talk Dave about past databases, right? So platform as a service, and that could completely change your total cost of ownership there as well. So are you really maximizing that? And do you have a service around that? Do you have a trusted partner who can help you with fin ops is I think an important consideration there? >>Well, I don't know. Pretty, I know you're dying to talk about a customer example, make it real for us. Give us an example of, uh, of this process inaction where UNISIS has helped a customer on the journey. >>Absolutely. Dave. So, um, uh, one example that comes to mind is a large public university and they've got about a half a million students and they've got 20 plus campuses around the U S in California, Sarah, I might've given myself away there. And, and, uh, in, into what they've done is, um, initially they are big into AWS and they are into their cloud, uh, higher into the IBM cloud journey, uh, big time. And they are a hybrid deployment at this point. And initially, uh, they, uh, when they subscribed to our fin ops service, uh, we, we brought in all the different, uh, thinking around working with different organizations, they need to like business planning, right? You need to know which is your most significant apps and what do you want to invest in them in terms of modernization and in tuning your AWS spend. And so we did that. And so we got them about a 33% cost saving and what they did was then they took, looked at all of their AWS accounts across the campuses and said, we want fin ops across all of them. Let's consolidate all of them. So that's, that's the power of a synopsis is about 33% saving right there. Well, that is >>Particularly exciting for me because I assume that they're going to be lowering my kid's tuition next year. So I'll be, I'll be looking forward to that. And now I know Palm, we know why she was kicked out of the, uh, you know, the, the intelligence agency can't keep a secret. Let's, let's, let's talk about an amusement park, uh, famous for its rodent, but I'm not going to say the name. So, so out upon talk about, uh, the technology space that we're in the midst of here at AWS reinvent, right? Um, each time we have a keynote, we're hit with an, almost a mind boggling number of announcements, right? Customers can't keep, keep this stuff straight. They're 575 different kinds of instances. It used to be, we have S3 and we have VC too. Right. Would you like, would you like one, or would you like both, right? How do you help customers make sense of this? >>Yeah, no, that's, that's a great question because, um, the cloud is, uh, I, as I said, cloud has three V's velocity, variety and volume of data and, and the new kinds of services that are available. Day-by-day, it's growing the keys to really figure out, again, map the business objectives that you as a customer or a company are trying to achieve, understand where you are in your digital transformation journey. And then based on the two, uh, and assess where you at and, and companies like Unisys can work with the customer to assess their, what I call the digital transformation posture, which will then give, uh, give us clear indications or recommendations on what are the next stages in the transformation of journey. So whether it's whether you want to improve your security posture, whether you want to improve your cost of ownership, posture, whether you want to go to go to the cloud and leverage DevSecOps to benefit from the innovation and agility, we can help you. >>Unisys has DevSecOps as a service, uh, containers as a service where we can help our customers and partners migrate to the cloud, modernize the apps. And again, based on research, that's out there, you can speed up app deployment and development by 60% by leveraging the power of the cloud. So the benefits out there for customers to get access to, it's a question of finding the right combination of people, process and technology to get you there. And Unisys being a very trusted advisor is certainly able to help you accelerate that journey and get you to meet your business outcomes. So me, >>Um, let me ask the two of you, what might be an uncomfortable question, and that is obviously Unisys is in the business of managing things that aren't in cloud. Also, you have very, very large existing customers that are spending money with you, right? And if they'll just stay still and not do anything and not change, you'll keep making money into the future. Aren't some of these things that you're doing as a trusted advisor, almost counterintuitive from a, from a finance perspective at Unisys, at least in the short term, how do you, how do you balance that? >>It's a, it's a great question, Dave, and for us, we are customer obsessed. So that's, I know one of the AWS principles and we, we live by that as well. Right? So customer comes first and doing the right thing by them, whether it is the total cost of ownership when it's getting the security posture, right. That comes first for us. And if, if moving them to a public cloud will help them achieve that. We will do that. Right. So even if it means that our bill is going to be lower, right. So we'll give you a great example there. Um, Eunice's, as you know, Dave has been in the mainstream business and we've got customers that are still on clear path, right? So even with those customers, we help them with both transitions. We can run clear path to the, on public cloud and we also help with modernization, right? So we always do the right thing by the customer. It's really the customer's tries in terms of what does the business warrant, how much business disruption are they willing to take as we do this modernization journey. And that's what determines us. And that's what makes us trusted advisers. Um, you're not looking out for the bottom line there in terms of how much our bill would be. Yup. >>Well, that's a, that's actually a great place to wrap up. Uh, I think it's hilarious that you mentioned mainframe since you were five years old, you gave me, you gave me a blank stare. When I mentioned stuff, Unisys was doing 20 years ago on a free auto Palm from Unisys. Thank you so much. It's a great point to close on. You're a trusted advisor when you're doing things that are truly in the customer's best interest and not just in your own company's best interests. I'm Dave Nicholson for the cube. We'd like to thank you for joining our continuous coverage at AWS reinvent 2021 stay tuned because we are your leader in hybrid tech event coverage.

(upbeat music) >> Hello, and welcome to today's session of the 2021 AWS Global Public Sector Partner Awards. I'm delighted to present our special guests for today's program and they are Kyle Hines, VP Strategic Accounts at Presidio as well as chief Chuck Hoskin, Jr., chief of the Cherokee Nation. Welcome to the program, gentlemen >> Thank you. >> Terrific, well, delighted to have you here, we're going to discuss the key award of best partner transformation, most impactful nonprofit partner, of course now highlighting some of the technologies now being technology now being leveraged to help preserve the Cherokee language as well as its culture. Now, Chuck, I'd like to start with you and if you could describe some of the challenges that the Cherokee nation is now faced with in terms of preserving the language and its culture and how you see technology being able to really help preserve it. >> Well, thank you, Natalie. It was really good to be with you all today. The Cherokee language and culture is what makes us unique as a people. It's the link that links us back to time and immemorial through generations. And over those generations, there've been many threats to our language and culture. There's been disease after European contact, there's been dispossession, there's been our forced removal on the trail of tears. Other pressures in more modern times have continued to erode our language and culture, including, boarding schools, the public school system through most of the 20th century as Cherokee Nation has gotten back on its feet, that is to say when the govern the United States has allowed Cherokee Nation to do what we've always done well which is to govern ourselves, chart our own destiny, and preserve our life ways, we've been able to make preservation efforts but those generations of eroding our language and culture had coming to steep costs. We're the largest tribe in the country, 392,000 citizens and by the way we're mostly in Northeast, Oklahoma but we have Cherokees living all over the country even all over the world. And we only have 2000 fluent speakers left. So it's a great challenge to save a language that's truly endangered. And if we don't save it generations from now we may do a number of things exceedingly well as we do today, business, providing education and housing, creating a great healthcare system, but we will have lost that thing that makes us a unique people, that thing that links us back to our past. And so what we're doing today, working with great partners like Presidio is just indispensable to what's really our most important mission. >> Yeah, terrific. Well, thank you so much for those insights. I'd like to switch it over to Kyle and hear about the technologies now being utilized to preserve the Cherokee language and culture. >> Sure, happy to Natalie and thanks for having us this morning. So yeah, when we started to work with the Cherokee Nation, it was very clear to us that, there's obviously a higher power or a higher mission here. And so it's really been an honor to work with the chief and the nation and what we've been able to do is is take what the Cherokee Nation is trying to do in terms of language and cultural preservation and build solutions in really a very modern way. So between Inage’i, the 3D mobile open-world game and the virtual classroom platform, it's entirely a cloud native serverless solution in AWS, using a lot of the most modern tools and technologies in the marketplace. For example, in the mobile game, it's built around unity and the virtual classroom platform is built around the Amazon chime SDK, which allows us to really build something that is very clean and light and focused on what the nation is trying to achieve and really cut out a lot of the baggage and the other sort of plumbing and various other technologies that this would have, this type of solution would have taken just a few short years ago. >> Yeah, terrific. Well, Kyle, staying with you, what do you think were some of the factors behind the development of this solution? >> Yeah, so I think flexibility was key. Was maybe the biggest design goal in building these solutions because you learn a lot when you originally set out to build something and it starts to impact real users, and in this case, speakers of the Cherokee Nation, you learn a tremendous amount about the language and how it's used and how people communicate with each other. And so the main design goal of the solutions was to allow a sort of flexibility that lets us adapt. And every time we learn something and every time we find something that works or perhaps doesn't work quite as well as was imagined, we have the flexibility to change that and kind of stay nimble and on our toes. >> Terrific, well, Chuck, now switching over to you, why do you think that some of these, platforms like the virtual classroom are so effective with Cherokee speakers? >> Well, a couple of reasons, one pandemic related, during COVID the worst public health crisis the world seen in living memory, we have had to adapt quickly to continue on our mission to save this language. We couldn't afford a year off in terms of pairing speakers, by the way, most of our fluent speakers are over the age of 70, with young people who need to learn the language and be the new generation of speakers. So it's been really important that during those difficult times we could connect virtually and the technology we've been using has worked so effectively, but the other is really irrespective of what's going on in terms of having to isolate, and social distance and things of that nature during COVID, and that is just making sure we can make this language accessible, particularly to young people in a manner in which they are becoming accustomed to learning things throughout the rest of the world. And so using platforms that they're familiar with is very important but it also has to be something that an older generation of these fluent speakers, as I say most of them are over 70, can use. And that's what really has been so effective about this platform. It's so usable. Once you introduce it to people whether it's a young person who can adapt pretty quickly 'cause they're growing up immersed in it, or it's someone who has not been familiar with that technology, with just a little bit of showing them how to use it, suddenly this classroom becomes just like you're in person. And that makes all the difference in the world in terms of connecting these young people with their elders. As the other thing is Cherokees are by nature very much part of a big extended family. And so that personal connection that you can maintain through this platform is really important. I think it's going to be the key to how we save this language, because as I say we have Cherokees all over the country, even all over the world and we're going to harness our numbers, the large population we have and find those with the interest and aptitude to learn the language, we must use this technology and so far it's worked well. >> Yeah, terrific, and now switching over to Kyle, we'd love to hear from you how your team developed this technology. How they really thought out, what kinds of methods are really going to drive the interaction and the immersion and engagement among these disparate demographics of, elderly Cherokees and also the young generation. So, how did your team go about developing that? >> Yeah, it's a very good question because in a situation like this, there is no shortage of different ways that you could have built a solution like this. There are a lot of different ways that it could have been done. So the tax that we took was a rigorous focus on the user experience and on the experience of the speaker. And that allowed us to detach ourselves to a large degree from what were the exact technology choices that were implemented in terms of AWS services, other open source packages that run on AWS, it's being able to focus completely on what the nation was trying to achieve with their speakers, both through the game and the virtual classroom platform. It let us take a lot of other design decisions and technology choices sort of into the background and behind a level of abstraction. And so there's always quite a bit of rigorous testing and really making sure you understand how something's going to perform in the wild, but the reality of the situation was, the whole reason for doing it was the experience of the speakers, both in the game and in the classroom platform. So we stayed very focused on that and made technology decisions sort of second fiddle or lower priority. >> Terrific, well, Chuck, how do you think that these kinds of innovations could be applied to other areas of the Cherokee school system? >> Well, our greatest challenge is preserving language and culture, but we also have as part of our mission to educate this new generation of Cherokees coming up. For years and years, really generations, Cherokees who were able to get a good education many of them left our tribal lands for new opportunities. And so we lost a great deal because of the economic pressures here in Northeast, Oklahoma, particularly on our Cherokee lands. So the task now is to generate opportunity for a new generation coming up. Education is key to that and so if we want to create a pipeline of young Cherokees who want to get into the healthcare fields, want to get into aerospace, want to get into other professions, we've got to create an education system that is steadier and modern. We have a school that is K through 12th grade, K through the senior year, and so we have an opportunity really to do that. And I think for the first time in our history, in this era, I'm talking elect the last few decades, we are able to really craft education in a way that works for us and using technology and making choices about what that technology is, is important to us. It's a bygone era in which the federal government or the state is sort of imposing on us what choices we make. Now we can reach out with great partners all over the world like Presidio and say what solution can work for our classroom? When we can identify what the great demands are on the reservation in terms of jobs. And one of the great demands we have is healthcare. So how can we use technology to inspire little Cherokee boys and girls to grow up and be doctors and nurses here in just a few decades when we're building this great health system? Well, we're going to use technology to do it. So the possibilities are really unlimited and they need to be because we think our potential here in Cherokee Nation is unlimited. >> Yeah, I mean that's terrific to hear how technology is really encouraging younger generations to study, learn and really push themselves further. Kyle, I'd like to switch over to you and hear a little bit about the benefits of launching this kind of platform on AWS. >> Yeah, there are a lot of benefits to building this on AWS. And I think that it spans a couple of categories, even. I mean, from a technological perspective there was every tool and every service that we needed to build both of the solutions that we built right there in AWS. And when there was a, when there was a time where we needed to jump out and use a project outside of AWS, running on AWS such as the unity engine, AWS makes that very easy. So I would say that the choice was easy because there are technological realities and the breadth and the depth of the technological portfolio in AWS combined with the partnership that we get from them, It's really, you know, there's a lot of support when it comes to, Hey we're working with the Cherokee nation on something that's extremely important. We need your help. We need you to help us figure this out. It's never been hard to get that partnership. >> Terrific, and also following up on that, love to hear how AWS really helped with flexibility and also the cost effective effectiveness of this kind of platform. >> Yeah I would take those questions backwards or in reverse order because the cost-effectiveness of the solution is really, it's really something to make note of because when we build something in the way that we built these platforms they're serverless and event driven. Meaning that the Cherokee Nation is not paying for a solution constantly as we would in lives past running things in data centers and such. It really, the services in AWS allow us to say, Hey, let's spin up certain pieces of functionality when they're needed as they're being used. And the meter is running during that time, and the cost is occurred during the time it's being used and not all of the time. So that really has a dramatic impact on cost effectiveness. And then from a flexibility standpoint, as we learn new things, as we evolve the platform as we grow this out to more and more speakers and to more and more impact to the Cherokee Nation, we have all kinds of different technology choices that we can make and it's all contained within AWS. >> Yeah, and I'd like to open this now to both of you, starting with Chuck, how do you think this kind of technology could be applied to other cultures or languages that re seeking to preserve themselves? There's so many languages in the world that are now dying out because most of us are only speaking, just a few like English, Spanish, just a few others, what steps can be taken so that humanity can preserve these important languages? >> Well, you're right. There are so many endangered languages around the world and indigenous languages are unfortunately dying all over the world all the time, even as we speak, they're slipping away. The United nations is dedicated the next decade to the preservation of indigenous languages. That's gotten many leaders around the world thinking about how we can save languages here in this era. And I would encourage any tribal leader in particular in the United States, but I think it certainly applies around the world to seek out this technology. I mean, Cherokee Nation's in a position now where we can seek out the best in the world in terms of partnerships. And we've found that in Presidio. And of course they're using AWS which means they're using the best in the world and so the technology exists, and the willingness to work together exist. And I think generations ago that would have been not something we could have connected well on in terms of partnering with companies that were doing cutting edge things. So if you're looking to connect generations in terms of learning and sharing the language, which is just I cannot stress enough how indispensable that is to language preservation, this type of technology will do it. There are some, I think that may think, and I don't have a technology background, that if you're using this cutting edge technology, I mean this is the best in the world that you're going to speak only to this young generation coming up, and maybe it's inaccessible to an older generation. It's just not the case. This is so user-friendly that we we've been able to connect elders with young people. And if anyone in the world interested in preserving languages could see this in action, could see a young person sitting next to an elder talking about the technology or connecting virtually, it would change their whole perspective on what technology means for language reservations because I promise you all over the world the great challenges you have this group of older generations of people who know the language. They have it in their hearts, they have it in their minds and they're slipping away just from the passage of time. Connecting them with the generation coming up is just what we need to do. This technology allows us to do it. >> Yeah, Chuck following up on that when I hear about elderly people being able to connect with the younger generations in this way and share their history and their culture I'm sure that also, It must have a positive mental effect for them. Right, so elderly are often isolated. Do you have any insight on that? Any quality of insight what you've heard from people using this? >> Yeah, absolutely. And I think the last year has proven how valuable it is. I mean, we lost over 50 fluent Cherokee speakers and I mentioned earlier in the program, that we only have 2000 left. 50 to COVID and more to just the passage of time and old age. But we have many that are active and engaged in language preservation and they have said to me how valuable it's been to be able to be at home and yet still feel like they're part of this great mission that we have at the Cherokee Nation. Understand that this mission that we have is on par with what any nation in history has set as a goal to shoot for whether it's the United States wanting to land a man on the moon, we're trying to save the language. This is that level of importance. And so for an elder to feel like they're connected and still contributing during this past year difficult times, that makes all the difference in the world. And even as I say, as the pandemic recedes and we hope it continues to recede, there is still a need for elders to stay connected. And in many cases they cannot due to poor health, due to the lack of transportation, this knocks down those barriers and so there's a great deal of joy that has been gained from using this technology. And honestly, just talking to elders about young people getting the opportunity to play this video game even some elders that were voice actors in this game, that Presidio helped us develop. I mean, I can't tell you how important that is for somebody to use their language, to make a living. And that's part of how you preserve a language. Presidio has showed us a way that we can do just that. So we're not only training new speakers, we're giving this opportunity many cases to elders to do something that is very productive with the wonderful gift they have, which is the Cherokee language. >> Terrific, well that is really inspiring because potentially this technology could be utilized by generations to come. The current young people that are using this will one day be the elderly. So, Kyle, how do you see this technology potentially on this platform being evolved? What's the next step to keep it really up to date for future generations as it's evolving. >> Yeah, there's a lot of plans on where to take this I can tell you, honestly. From the perspective of the mobile game, you're building on a platform of an open world game means that the imagination is the limit quite honestly. So there are a lot of new characters and new levels and new adventures that are plans to further immerse the speakers in the platform. And I think that will, that will help with reach and it will help with the amount of connection that's built to the chief's point about bridging the older generations into the younger generations over that common bond of the language and the culture that keeps those connections alive. And so we want to expand the mobile game Engage, the navigate to be as accessible and as wide reaching and immersive as it possibly can, and there are a lot of plans in the works for that. And then with the virtual classroom platform, we started with a various focused constituency within the nation of the language immersion school. And there are many other educational services and even healthcare to the chief's earlier point again where I think there's a lot of potential for that one as well. >> All right, well, terrific gentlemen. Thank you so much for your insights, really fantastic hearing how this platform is really a difference in the lives of people in the Cherokee Nation. Of course, that were our guests, Kyle Hines, VP Strategic Accounts at Presidio as well as chief Chuck Hoskin Jr., the chief of the Cherokee Nation. And that's all for today's session at the 2021 AWS Global Public Sector Partner Awards, I'm your host for "theCUBE", Natalie Erlich. Thanks so much for watching. (upbeat music)

>> Narrator: From around the globe, it's theCUBE, with digital coverage of Dell Technologies World. Digital Experience brought to you by Dell Technologies. >> Welcome to theCUBE's coverage of Dell Technologies World 2020, the Digital Experience. I am Lisa Martin and I've got a couple of guests joining me. Please welcome Puneet Dhawan, the Director of Product Management, Hyper-converged infrastructure for Dell Technologies. Puneet great to see you today. >> Thank you, for having me over. >> And we've got a customer that's going to be articulating all the value that Puneet's going to talk about. Please welcome Greg Altman, the IT infrastructure manager from Swiff-Train. Hey, Greg, how are you today? >> I'm doing well. Thank you. >> Excellent. All right guys. So Puneet, let's start with you, give us a little bit of an overview of your role. You lead product management, for Dell Technologies partner aligned HCI systems. Talk to us about that? >> Sure, absolutely. Um so, you know, it's largely about providing customers the choice. My team specifically focuses on developing Hyper-converged infrastructure products for our customers that are aligned to key technologies from our partners, such as Microsoft, Nutanix, et cetera. And that, you know, falls very nicely with meeting our customers on what technology they want to pick on, what technology they want to go with, whether it's VMware, Microsoft, Nutanix, we have to source from the customers. >> Let's dig into Microsoft. Talk to us about Azure Stack HCI. How is Dell Tech working with them to position this in the market? >> Sure, um, this is largely about following the customer journey towards digital transformation. So both in terms of where they are in digital transformation and how they want to approach it. So for example, we have a large customer base who's looking to modernize their legacy Hyper-V architectures, and that's where Azure Stack HCI fits in very nicely, and not only our customers are able to modernize the legacy architectures using the architectural benefits of simplicity, high performance, simple management, scalability. (Greg breathes heavily) For HCI for Hyper-V, at the same time, they can connect to Azure to get the benefits of the bullet's force. Now on the other end, we have a large customer base who started off in Azure, you know, they have cloud native applications, you know, kind of born in the cloud. But they're also looking to bring some of the applications down to on-prem, or things like disconnected scenarios, regulatory concerns, data locality reasons. And for those customers, Microsoft and Dell have a department around Dell EMC Integrated solutions for Azure Stack Hub. And that's what essentially brings Azure ecosystem, on-prem so it's like running cloud in your own premises. >> So you mentioned a second ago giving customers choice, and we always talk about that at pretty much every event that we do. So tell me a little bit about how the long standing partnership that Dell Technologies has with Microsoft decades. How is that helping you to really differentiate the technology and then show the customers the different options, together these two companies can deliver? >> Sure, so we've had a very long standing partnerships, actually over three decades now. Across the spectrum whether we talk about our partnership more on the Windows 10 side, and the modernization of the workforce, to the level of hybrid cloud and cloud solutions, and helping even customers, you know, run their applications on Azure to our large services offerings. Over the past several years, we have realized how important is hybrid cloud and multicloud for customers. And that's where we have taken our partnership to the next level, to co-develop, co-engineer and bring to the market together our full portfolio of Azure Stack Hybrid Solutions. And that's where I've said, meeting customers on where they are either bringing Azure on-prem, or helping customers on-prem, modernize on-prem architectures using Azure Stack HCI. So, you know, there's a whole lot of core development we have done together to simplify how customers manage on-prem infrastructures on a day-to-day basis, how do they install it, even how they support it, you know, we have joined support agreements with Microsoft that encompassed and bearing the entirety of the portfolio so that customers have one place to go, which is Dell Technologies to get not only the product, either in US or worldwide, to a very secure supply chain to Dell EMC, at the same time for all their support consulting services, whether they're on-prem or in the cloud. We offer all those services in very close partnership with Microsoft. >> Terrific. Great. Let's switch over to you now, probably we talk about what Swiff-Train is doing with its Azure Stack HCI, tell our audience a little bit about Swiff-Train what you guys are what you do. >> Well, Swiff-Train is a full covering flooring wholesaler, we sell flooring across Texas, Oklahoma, Louisiana, Arkansas, even into Florida. And we're an 80 year old company, 80 plus. And we've been moving forward with kind of hybridizing our infrastructure, making use of cloud where it makes sense. And when it came to our on-prem infrastructure, it was old, well five, six years old, running Windows 2012 2016, it was time to upgrade. And when we look at doing a large scale upgrade, like that, we called Dell and say, you know, this is what we're trying to do, and what's the new technologies that we can do that makes the migration work easier. And that's where we wound up with Azure Stack. >> So from a modernization perspective, you mentioned 80 plus year old company, I was looking on the website 1937. I always like to talk to companies like that, because modernizing when you've been around for that long it's challenging, it's challenging culturally , it's challenging historically, But talk to us a little bit about some of the specifics, that you guys were looking to Dell and Microsoft to help modernize. And was this really to drive things like, you know, operational simplicity, allow the business to have more agility so that it can expand in some of those other cities, like we talked about? >> Absolutely. We were dealing with a long maintenance window five or six hours every week patching, updating. Since we moved to Azure Stack HCI, we have virtually zero downtime. That allows our night shifts or weekend crews to be able to keep working. And the system is just bulletproof. It just does not go down. And with the lifecycle management tools that we get with Windows Admin Center, and Dell's OpenManage Plug-in, I log into one pane of glass in the morning, and I look and I say, "Hey, all my servers are going great. Everything's in the green." I know that that day, I'm not going to have any infrastructure issues, I can deal with other issues that make the business money. >> And I'm sure they appreciate that. Tell us a little bit about the the actual implementation and the support as, as Puneet talked about all of the core development, the joint support that these two powerhouses deliver. Tell us about that implementation. And then for your day to day, what's your interaction with Dell and or Microsoft like? >> Well, for the implementation, we worked with our Dell representative. And we came up with a sizing plan. This is what we needed to do, we had eight or nine physical servers that we wanted to get rid of. And we wanted to compress down. Now we're definitely went from eight or nine to you servers down to three rack units of space with an edge, including the extra switches and stuff that we had to do. So I mean we were able to get rid of a lot of storage space or rack space. And as far as the implementation was really easy. Dell literally has a book, you follow the book and it's that simple. (Puneet chuckles) >> I like that I think more of us these days, can you somewhat write a book that we can just follow? That would be fantastic. One more question, Greg for you, before we go back to Puneet. As Puneet talked about in the beginning from describing his role, that you know, Dell Technologies works with a lot of other vendors. Why Azure Stack HCI for Swiff-Train? >> Well, it made sense for us. We were already moving, several of our websites were already moved to Azure, we've been a Hyper-V user for many years. So it was just kind of a natural evolution to migrate in that direction, because it kind of pulls all of our management tools into one, well you know, a one pane of glass type of scenario. >> Excellent. All right Puneet back to you. With some of the things that you talked about before and that Greg sort of articulated about simplifying day-to-day. Greg, I saw in my notes that you had this old aging infrastructure, you were spending five hours a week patching maintain, that you say is now virtually eliminated, Puneet, Dell Technologies and Microsoft had done quite a bit of work to simplify the operational experience. Talk to us about that, and what are some of the measurable improvements that you guys have made? >> Sure. It all starts with neither on how we approach the problem, and we have always taken a very product-centric approach at Azure Stack HCI. You know, unlike, some of our competition, which had followed. There is a reference architecture, you can put Windows Server 2019 on it and go run your own servers, and the Hyper-converged Stack on it, but we have followed a very different approach where we have learned quite a lot, you know, we are the number one vendor in HCI space, and we know a thing or two about HCI and what customers really need there. So that's why from the very beginning, we have taken a product-centric approach, and doing that allows us to have product type offers in terms of our Kx notes that are specifically designed and built for Azure Stack HCI. And on top of that, we have done very specific integration to the management Stack, we've been doing Admin Center, that is the new management tool for Microsoft to manage, both on-prem, Hyper-converged infrastructure, your Windows servers, as well as any VM's that you're running on Azure, to provide customers a very seamless, you know, a single pane of glass for both the on-prem as well as infrastructure on public cloud services. And in doing that, our customers have really appreciated how simple it is to keep their clusters running, to reduce the maintenance windows, based on some of our internal testing that we have done. IT administrators can reduce the time they spend on maintaining the clusters by over 90%. Over 40% reduction in the maintenance window itself. And all that leads to your clusters running in a healthy state. So you don't have to worry about pulling the right drivers, right founder from 10 different places, making sure whether they are qualified or not when running together, we provide one single pane of glass that customers can click on, and you know, see whether their questions are compliant or not, and if yes go update. And all this has been possible by a joint engineering with Microsoft. >> Can you just describe the difference between an all in one validated HCI solution, which is what you're delivering, versus competitors that are only delivering a reference architecture? >> Absolutely. So if you're running just a reference architecture, you are running an operating system, systems Stack on a server, we know that when it comes to running HCI, that means running also business critical applications on a clustered environment. You need to make sure that all the hardware, the drivers, the founder, the hard drives, the memory configuration, the network configurations, all that can be very complex very easily. And if you have reference architectures, there is no way to know, but then running certified components in my note are not. How do you tell then? If a part fails? How do which part to sell or send, you know, for a replacement? If you're just running a reference architecture, you have no way to say the part the hard drive that failed, the one that was sent to the customer to replace whether that is certified for Azure Stack HCI or not? You know, what, how do you really make a determination, what is the right firmware that needs to be applied to a cluster of what other drivers that apply to be cluster, that are compliant and tested for Azure Stack HCI. None of these things are possible, if you just have a reference architecture approach. That's why we have been very clear that our approach is a product-based approach. And, you know, very frankly this is how we have... that's the feedback we've provided the Microsoft to, and we've been working very, you know, closely together. And you see that, now in terms of the new Azure Stack HCI, that Microsoft announced at Inspirely this year, that brings Microsoft into the mainstream HCI space as a product offering, and not just as a feature or a few features within the Windows Server program. >> Greg, I saw in the notes with respect to Swiff-Train that you guys have with Azure Stack HCI, you have reduced Rackspace by 50%, you talked about some of the Rackspace benefits. But you've also reduced energy by 70%. Those are big, impactful numbers, impacting not just your day-to-day but the overall business. >> That's true, >> Last question for you, Greg. If you think about how can you just describe the difference between an all in one validated HCI solution versus a reference architecture. For your peers watching in any industry. what's your... what are your top recommendations for going with a validated all in one solution? >> Well, we looked at doing the reference architecture's path, if you will, because we're hands on we like to build things and I looked at it and like Puneet said, "Drivers and memory and making sure that everything is going to work well together." And not only that everything is going to work well together. But when something fails, then you get into the finger pointing between vendors, your storage vendor, your process vendor, that's not something that we need to deal with. We need to keep a business running. So we went with Dell, it's one box, you know, but one box per unit and then you Stack two of them together you have a cluster. >> You make it sound so easy. >> Let us question-- >> I put together children's toys that were harder than building the Stack I promise you, I did it in an afternoon. >> Music to my ears Greg, thank you. (Greg giggles) >> It was that easy >> That is gold >> Easier to put together Azure Stack HCI than some, probably even opening the box of some children's toys I can imagine. (all chuckling) >> We should use that as a tagline. >> Exactly. You should, I think you have a new tagline there. Greg, thank you. Puneet, well last question for you, Would Dell Technologies World sessions on hybrid cloud benefits with Dell and Microsoft? Give us a flavor of what some of the things are that the audience will have a chance to learn. >> Yeah, this is a great session with Microsoft that essentially provides our customers an overview of our joint hybrid cloud solutions, both for Microsoft Azure Stack Hub, Azure stack HCI as well as our joint solutions on VMware in Azure. But much more importantly, we also talk about what's coming next. Now, especially with Microsoft as your Stack at CIO's a full blown product. Hyper hybrid, you know, HCI offering that will be available as, Azure service. So customers could run on-prem infrastructure that is Hyper-converged but managed pay bill for as an Azure service, so that they have always the latest and greatest from Microsoft. And all the product differentiation we have created in terms of a product-centric approach, simpler lifecycle management will all be applicable, in this new hybrid, hybrid cloud solution as well. And that led essentially a great foundation for our customers who have standardized on Hyper-V, who are much more aligned to Azure, to not worry about the infrastructure on-prem. But start taking advantages of both the modernization benefits of HCI. But much more importantly, start coupling back with the hybrid ecosystem that we are building with Microsoft, whether it's running an Azure Kubernetes service on top to modernize the new applications, and bringing the Azure data services such as Azure SQL Server on top, so that you have a consistent, vertically aligned hybrid cloud infrastructure Stack that is not only easy to manage, but it is modern, it is available as a pay as you go option. And it's tightly integrated into Azure, so that you can manage all your on-prem as well as public cloud resources on one single pane of glass, thereby providing customers whole lot more simplicity, and operational efficiency. >> And as you said, the new tagline said from, beautifully from Greg's mouth, "The customer easier to put together than many children's toys." Puneet, thank you so much for sharing with us what's going on with Azure Stack HCI, what folks can expect to learn and see at Dell Tech World of virtual experience. >> Thank you. >> And Greg, thank you for sharing the story, what you're doing. Helping your peers learn from you. And I'm going to say on behalf of Dell Technologies, that awesome new tagline. That was cool. (Greg chuckles) (Lisa chuckles) >> Thank you. 'Preciate your time. >> We're going to use it for sure. (Greg chuckles) >> All right, for Puneet Dhawan and Greg Altman. I'm Lisa Martin. You're watching theCUBE's coverage of Dell Technologies World, the Digital Experience. (soft music)

>>from around the globe. It's the Cube with digital coverage of you. I path live the release show brought to you by you. >>I path Hi. Welcome back to this special R p A drill down with support from you. I path You're watching The Cube. My name is Dave Volante and Bobby CMO. You know I passed Bobby. Good to see you again. Hope you're doing well. Thanks for coming on. >>Hi, Dave. It's great to see you as well. It's always a pleasure to be on the Cube and even in the virtual format, this is really exciting. >>So, you know, last year at forward, we talked about the possibility of a downturn. Now nobody expected this kind of downturn. But we talked about that. Automation was likely something that was going to stay strong even in the downturn. We were thinking about potential recession or an economic downturn. Stock market dropped, but nothing like this. How are you guys holding up in this posted 19 pandemic? What are you seeing in the marketplace? >>Yeah, we certainly we're not thinking of a black swan or rhino or whatever we call this, but, you know, it's been a pretty crazy couple of months for everybody. You know, when When this first started, we were like everybody else. Not sure how it impact our business. The interesting thing has been that you're in code. It actually brought a reality check through. A lot of companies and organizations realize that it's very few tools to respond quickly, right? Bond with, you know, cost pressures that we're urgent or preserving revenue, perhaps, or responding to Ah, strange resource is, you know, in all centers, or or built to support. You know, the surge in in, um, in the healthcare community. And so r p a became one of those tools that quickly waas knowledge and adopted. And so we went out two months ago to go find those 1st 1st use cases. Talk about him, then. You know, 1st 30 days we had 50 in production, right? Companies, you know, great organizations like Cleveland Clinic, right? You know where they use their parking lot? Give the first tests the swab tests, right of, uh, well, who have proven right? You know, they had a line of 88 hours by, you know, putting a robot in place in two days. They got that line down by 80 or 90% right? It is a huge hit as we see that kind of a kind of benefit all across right now in the world. Right now we have. We were featured in The Wall Street Journal recently with nurses and a large hospital system in Ireland called Matter. The nurses said in the interview that, you know they have. They were able to free up time to be a patient's right, which is what they're there for, anyway, thanks to robots during this during this emergency. So I think you know, it's it's definitely raise The awareness that that this technology is provides an amazing time to value, and that's it's pretty unprecedented in the world of B two B software. >>I want to share some data with you in our community is the first time we've we've shown this. Guys would bring up the data slide, and so this is ah, chart that e. T are produced. There's enterprise technology research. They go out of reporter. They survey CIOs and I T practitioners and a survey in different segments and the use of methodology Net score. And this is sort of how method how Net scores derived. And so what this chart shows is the percent of customers that responded there were about 125 You I path customers that responded. Are you adopting new U I path? Are you increasing spending in 2020? Are you planning on flat spending or decreasing spending? Are you replacing the platform of beacons? And so basically, we take the green, uh, subtract the read from the green, and that gives us net score. But the point is that Bobby abouts about 80% of your customers are planning to spend Maurin 2020 than they spent in 2019 and only about 6% of planning on spending less, which is fairly astounding. I mean, we've been reporting on this for a while in the heat nous in the in the automation market generally and specifically. But are you seeing this in the marketplace? And maybe you could talk about why? >>Well, we just finished our first fiscal quarter into the end of April, and we're still privately held, so we can be, uh, find some insights of our company, but yeah, the the pace of our business picked up actually in in the mark. April timeframe. Um, customer adoption, large customer adoption. Um, the number of new new companies and new logos were at a record high. And, you know, we're entering into this quarter now, and we have some 20 plus $1,000,000 deals that are like that. It closed, right? I mean, that's probably a 30% increase Versus what? How many we have today alone. Right? So our business, you know, is is now well over 400 million and air are we ended last year, 3 60 and the growth rate continues fast. I think you know what's interesting is that the pace of the recode world was already fast, right? The the luxury of time has kind of disappeared. And so people are thinking about, you know, they don't have they can't wait now, months and years for digital transformation. They have to do things in days and days and days and weeks. And and that's where our technology really comes into play. Right? And and and it actually is also coming to play well in the world of the remote workforce. Reality two of the ability for remote workers to get trained while they're home on automation to build automation pipelines to to build automation. Now, with our latest release, you can download our podcast, capture and report what you're doing, and it basically generates the process definition document and the sample files, which allow for faster implementation by our center of excellence. So what's really happening here? We see it is a sense of urgency coming out of this. Prices are coming down the curve. Hopefully, now this is of urgency that our customers are facing in terms of how they respond, you know, and respond digitally to helping their business out. And it varies a lot by industry, our state and local business was really thinking was not going to be the biggest laggard of any industry picked up in a significant way in the last couple of months, New York State, with Governor Cuomo, became a big customer of ours. There's a quote from L. A County, see Iot that I've got here. They just employed us. It's public, this quote, he said. Deputy CIO said Price is always the mother of invention. We can always carry forward the good things they're coming out of this crisis situation. He's referring to our P A is being a lesson. They learned hearing this, that they're going to carry forward. And so we see this state of Oklahoma became a customer and others. So I think that's that's what we're seeing kind of a broad based. It's worldwide. >>You're really organizations can't put it off anymore. I think you're right. It sort of brought forward the future into the present. Now you mentioned 360 million last year. We had forecast 350 million was pretty good for you guys released, so it's happy about that. But so obviously still a strong trajectory. You know, it might have been higher without without covert. We'll never know, but sort of underscores the strength of the space. Um, and February you guys, there was an article that so you're essentially Theo Dan, Daniel Hernandez was quoted. Is that on hold now? Are you guys still sort of thinking about pressing forward or too early to say right? >>Yeah. I mean, I think I think the reality is we have a very, very strong business. We've raised, you know, significant money from great investors, some of which are the leading VCs in the world. and also that the public company investors and, you know, we have, ah, aggressive plan. We have an aggressive plan to build out our platform for hyper automation to continue. The growth path is now becoming the center of companies of I, T and Digital Strategies, not on the side. Right. And so to do that, you know, we're gonna want capital to help fuel our our our ambitions and fuel Our ability to serve our customers and public markets is probably a very, very logical one. As Daniel mentioned in a in a A recent, uh, he's on Bloomberg that he definitely sees. That is ah, maybe accelerating that, You know, we're late Last year, we started focusing on sustainable growth as a company and operational regular. These are important things in addition to having strong growth that, you know, a long term company has to have in place. And I can tell you, um, I'm really excited about the fact that we, you know, we operate very much like a public company. Now, internally, we you know, we do draft earnings releases that aren't public yet, and we do mock earnings, earnings calls, and we have hired Thomas Hansen is runs our chief revenue officer with storage backgrounds. And so you're gonna interview as well. These are these are these are the best of the best, right? That joint, they're joined this company, they're joining alongside the arm Kalonzo the world that are part of this company. And so I think, Yeah, I think it's an AR It's likely. And and it's gonna We're here to be a long term leader in this decade of automation. >>Well, and one of the other things that we forecast on our breaking analysis we took a look at the total available market kind of like into it. Early days of service Now is you know, people were really not fully understanding the market and chillin C it is is quite large, so video. So when we look at the competition, you know, you guys, if I showed you the same wheel with automation anywhere, it would also look strong. You know, some of the others, maybe not a strong but still stronger than many of the segments. I mean, for instance, you know, on Prem hardware. You know, compared with that and you know the automation space in general across the board is very, very strong. So I wonder if maybe you could talk a little bit about how you guys differentiate from the competition. How you see that? >>Yeah, I think you know, we've We've come a long way in the last three years, right? In terms of becoming the market leader, having the highest market share, we're very open and transparent about our numbers with We've long had the vision of a robot. Every person, uh, and and we've been delivering on that on on that vision and ah, building out a platform that helps companies, you know, transform digitally enterprise wide. Right. So, you know, I don't see any of our competitors with a platform for hyper automation like this. We have an incredible focus on the ability to help people actually find the ideas, build the pipeline, score the pipelines and integrate those with the automation center of excellence. Right? We have the ability now with our latest release to help test automation testers now not only in the world of art A but actually take robotic robots and and architecture into doing test automation. The traditional test automation market in a much better and faster way So you know, we're innovating at a pace that that it is, I think, much faster than I don't. I don't know automation anywhere. I won't share any their numbers. You know, who knows what the numbers are. We have guesses, but I'm fairly certain that we continue to gain share on them. But you know, what's most important is customer adoption, and we've also seen a number of customers switch from some of our competitors to us. Our competitors are undercapitalized and middle. Invest in R and D. This is an investment area, really build a platform out from our competitors have architectures that are hard to upgrade, right? This has been a big source of pain for companies that have been on our competitors. Where upgrades are difficult requires them to retest every time where our upgrades are very rolling, you know, are very smooth. We have an insider program which you know, I don't think any of our competitors have. If you go inside that you had pat that your customer every single bit every single review betting, private preview, public preview and general availability, you can provide feedback on and the customers can score up new ideas. They drive our our roadmap. Right. And this is I think we operate differently. I think our growth is a is a good indication of that. And, you know, and there are new competitors like Microsoft. But I think you know, you know, medium or long term, you know, they're gonna make effort around our, um and you know, they're behind the, um, automation is really hard. The buried entry here is not it's not. Not easy. And we're going to keep me on that platform, play out, and I think that's ah, that's what makes us so different. Um and ah, you know, we have the renewal numbers, retention numbers, expansion numbers and and the revenue numbers to improve that, uh, you know, we're number one. >>Well, so I mean, there's a lot of ways to skin the cat, and you're right. You guys are really focused, you know, you automation anywhere really focused on this space, and you shared with us how you differentiate there. But as you point out Microsoft, they sort of added on I had talked to Allan, preferably the day from paga. You know, those guys don't position themselves as our PC, but they have r p A. I talked to, you know, our mutual friend Robert Young John the other day, right? They're piling onto this this trend, right? So why not? Right, It's it's ah, it's hot. But so, you know, clearly you guys are innovating there. I want to talk about your vision before we get into the latest product release two things that I would call out the term hyper automation with, I think is the Gartner term. And then it will probably stick. And then this this idea of a robot for every person How would you describe your vision? >>Yeah, I mean, we think that robots can and improve, you know, the the lives of of or pers everywhere, right? We think in every every function, every role. And we see that already, the job satisfaction and the people don't want to do the mundane, repetitive work, right? The new hires coming out of college, you know, they're gonna be excel and sequel server. We're no longer the tools of productivity. For them, it's it's your path. We have business. Schools that have committed top tier business schools have committed to deploying your path or to putting you're passing every force in the school these students are graduating with the right path is their most important skill going into companies. And they're gonna expect to be able to use robots within their companies in their daily lives. A swell. So, you know, we have customers today that are rolling out a robot for every person you know. We had Ah, Conoco Phillips on just earlier in our launch, talking about citizen developers, enabling says, developer armies of developers and growing enterprise wide. See, Intel was on as well from Singapore, the large telco. They're doing the exact same thing. So I think you know, I think this is this is this is this is about broad based digital transformation. Everybody participating And what happens is the leading companies to do this, you know, they're going to get the benefit of benefits out of it. It can reinvest that productivity, benefits and data science and analytics and serving customers and in, you know, and and, ah, new product ideas. And so, you know, this is this. You know, automation is going to fuel now the ability for companies to really differentiate and serve their customers better. And it's only needed enterprise wide view on it that you really maximizing. Take Amazon, for example, a great customer during during this prices. You know, they're trying to hire hundreds of thousands of people, right? Help in the fact that in their in their distribution centers elsewhere, this all served demand to help people who like you and I home or ordering things that we need, right? Well, they're use your path robots all throughout their HR hr on boarding HR recruiting HR administration And so helping them has been a big during this prices surge of robots is helping them actually hire workers. You know another example of Schneider Electric and amazing customer of ours. They're bringing their plants, their manufacturing facilities, implants back online faster by using robots to help manage the PPE personal protective equipment in the plant allow people workers to get back to work faster. Right? So what's happening is is, you know in that in those cases is your different examples of robots and different functions, right? In all cases, it's about helping grow a company faster. It's about helping protect workers. It's about helping getting revenue machines back up and running after Kobe is going to be critical to get back to work faster. So I'm I'm really excited about the fact that as people think about automation across the organization, the number of ideas and Aaron opportunities for improvement are are we're just starting to tap that potential. >>Well, this is why I think the vision is so important because you're talking about things that are transformative. Now, as you well know, one of the criticisms of RPS. So you have people, the suppliers and just yeah, we, you know, looking at mundane tasks, just automating mundane tasks like sometimes paving the cow path and say, you're very much aware of that criticism. But if I look at the recent announcements, you're really starting to build out that vision that you just talked about. They're really four takeaways. You sort of extending the core PAP platform, injecting AI end some or and more automation end to end automation really taken that full lifestyles lifecycle systems view and the last one is sort of putting it talks to the robot. For every person that sort of citizen automation, if you will, that sort of encompasses your product announcements. So it wasn't just sort of a point Announcement really is a underscores the platform. I wonder if you could just What do we need to know about you guys? Just that out. >>So we think about how we think about the rolls back to a division of robots person how automation can help different roles. And so this product launch $20 for this large scale launch that you just articulated, um, impacts in a fax and helps many different kinds of new roles Certainly process analysts now who examined processes, passes performance improvements. You know, they're a user of our process mining solution in our past. Find a solution that helps speed on our way. Arpaio engine, no testers and quality engineers. Now they can actually use studio pro and actually used test robots are brand new, and our new test manager is sort of the orchestration and management of test executions. Now they can participate in in leveraged power of robots and what they do as well. And we kind of think about that, you know, kind of across the board in our organization across the platform. They can use tools like you have path insights in Europe. If you're an analyst or your, uh ah. B I, this intelligence person really know what's going on with robots in terms of our wife for my organization and provide that up to the, you know, sea levels in the board of directors in real time. So I think that's that's the big part. Here is we're bringing, and we're helping bring in many, many different kinds of roles different kinds of people. Data scientist. You mentioned AI. Now data scientists can build a model. The models applied to ai fabric an orchestrator. It's drag and drop by our developer in studio, and now you can turn, you know, a a mundane, rules based task right into an experience based ones where a robot can help make a decision right. Based on experience and data, they can tweak and tune that model and data scientists can interact, you know, with the automation is flowing through your path. So I think that's how we think about it, right? You know, one of the great new capabilities, as well as the ability to engage line workers, dispatch out workers If you're a telco or or retail story retail store workers you know the robots can work with humans out in the field. We've got one real large manufacturer with 18,000 drivers in a DST direct store delivery scenario. And you know the ability for them to interact with robots and help them do their job in the field. Our customers better after the list data entry and data manipulation, multiple systems. So I this is this makes us very unique in our vision and in our execution. And again, I don't I have not heard of a single ah example by competitors that has any kind of a vision or articulation to be able to help a company enterprise wide and, you know, with the speed and the and the full, full vision that we have. >>Okay, so you're not worried about downturns. You can't control black swans Anyway, you're not worried about the competition. It feels like you know, you're worried about what you're worried about. You want about growing too fast. Additionally, deploying the the capital that you've raised. What worries you? >>Yeah. You know, we're paranoid or paranoid company, right? And when it comes to the market and and trying to drive, I think we've done a lot to help actually push the rock up the hill in terms of really, really driving our market, building the market, and we want to continue that right and not let up. So there's this kind of desire to never let up, right? Well, we always remind ourselves we must work harder, must work harder. We must work harder. And that's that's That's sort of this this mentality around ourselves, by the smartest people. Hire the smartest people you work with our customers, our customers are priority. Do that with really high excellence and really high sincerity that it comes through and everything that we do, you know, to build a world class operation to be, you know, Daniel DNS. When I first met him, he said, You know, I really want to be the enemy of the great news ecology company that serve customers really well. And it was amazing things for society, and and, you know, we're on that track, but we've got, you know, we're in the in the in the early innings. So, you know, making sure that we also run our business in a way that, um, you know, uh, is ready to be Ah, you know, publicly successful company on being able to raise new sources of capital to fund our ambitions and our ideas. I mean, you saw the number of announcements from our 24 release. It reminded me of an AWS re invent conference, where it's just innovation, innovation, innovation, innovation. And these are very real. They're not made up mythical announcements that some of our competitors do about launching some kind of discovery box doesn't exist, right? These are very real with real customers behind them, and and so you know, just doing that with the same level of tenacity. But being, you know, old, fast, immersed and humble, which are four core culture values along the way and not losing that Azeri grow. That's that's something we talk about maintaining that culture that's super critical to us. >>Everybody's talking about Okay, What What's gonna be permanent? Postpone it. I was just listening to Julie Sweet, CEO of Accenture, and she was saying that, you know, prior to Covic, they had data that showed that the top 25% of companies that have leaned into digital transformation were outperforming. You know, the balance of their peers, and I know question now that the the rest of that base really is going to be focused on automation. Automation is is really going to be one of those things that is high, high priority now and really for the next decade and beyond. So, Bobby, thanks so much for coming on the Cube and supporting us in this in this r p. A drill down. Really appreciate it, >>Dave. It's always a pleasure as always. Great to see you. Thank you. >>Alright. And thank you for watching everybody. Dave Volante. We'll be right back right after this short break. You're watching the cube. >>Yeah, yeah, yeah, yeah.

>>LA from Las Vegas. It's the cube covering AWS reinvent 2019 brought to you by Amazon web services and they don't play along with its ecosystem partners. >>Well, welcome back live in Las Vegas. We're here on the cube. Continue our coverage here of day two of AWS. Raven 2019 in fact, it took me to the last interview on the second day to be paired up with my guy. Still many minutes to what happened is this is the first interview we've done this way. >>John, you know, I've not been out playing golf >>well and I wouldn't mind if I was, it'd be all right Brandon. You know Brandon, you play golf. Brandon Young? I do. I play college golf so, and I have a, you can't see them, but I have some trousers that might match there and prove that I have done a few times. Paint shirt would be, he would very proud granted to VP of alliances to get lab. And where'd you play college golf by the way. I split some time in Oklahoma and down at rice down in Houston. Oh you, yes. Wow. Be a sooner. How back that has some pretty good golfers there. They do. Um, let's first off, let's talk about, um, VP of alliances sure. And get like what do you do? So what does that encompass? What's that all about? Covers a bunch of pieces. Uh, covers all of the big key partnerships with us. >>So that's going to be obviously Amazon, other big cloud providers, a lot of strategic technology partnerships and then all your system integrators, man service providers, resellers, um, and then functionally anything else that comes in. So also we're bringing the open source space. So lead a lot of our open source engagement, uh, uh, in as well. What kind of customer base we're talking about here? I mean for, for you guys, sorry, cause it's pretty significant. It's, um, so in the space we've got roughly to two to 3 million users that use get lab and count on it for building, deploying and securing their code. Uh, and somewhere between a hundred thousand and 200,000 companies, uh, that get loud is, uh, is being used. Now. >>Brennan, you're not dealing with get lab. You're also on the board for the Linux foundation. And you know, we're, we're getting close to 2020. So I even, I saw some people looking back at where open source has come in the last decade. And you know, get, of course is one of the predominant drivers the proliferation of opensource. So maybe tell us a little bit about, you know, what your customers come to. Uh, w you know, why, why get lab is so critical to what, >>sure. Yeah. Because if we look at history, it kind of makes naturally in get lab we're getting, so that was where our, our base was, uh, when we started in 2012, 2013. Um, as it's evolved, so in get continues to be that core piece you need. So whether you're doing get ops infrastructure is code application development, you've got to have state, you've got to store your issues, you've got to take care of that. That's just one Oh one in software development or infrastructure management. Um, so that's got to where we started. And then, you know, a couple of years later, we picked up and did a bunch of stuff in the CIC space. Initially we had them separate, uh, and customers kept saying, God, these might work well together and to the Linux world has always been single tool, very sharp, very narrow. Uh, so we held off on that for a long time. >>Um, finally said, Oh, we're going to give it a go, shift them together. And that's kind of led to where we are now, which is we think of, you know, get lab as a single tool for the entire dev ops life cycle. And that makes it easy for someone to get started to build it, secure it, ship it, all of that from idea to production in the shortest possible time. And so that's kind of how it evolved. And yeah, we've grown up with the open source world ever since. And um, it's an awesome place. All right, so you've got the alliances and we're here at the biggest cloud show there. So help us connect the dots. Get lab AWS. Yeah. Perfect. So if we kind of look back and we go, ah, look at the keynote, right? So Andy talked a whole bunch, front keynote, Goldman Sachs, big talk with Verizon, a lot around the services, new stuff with arm new chips, new, um, a lot of new databases. >>Um, all of that rolled out. Those are services as Amazon looked at it. Our goal, our job is to get those customers onto the Amazon services. We're the tool that helps them develop and deploy those applications. Goldman, huge customer, Verizon, huge customer. So the majority of the keynotes you'd get lab to get to Amazon. So we're that tool that does the application security deployment and um, you know, lets those devs really take advantage of the great services that Amazon delivers. You know, you talk about security is it, is it, um, and obviously it's increased in terms of its importance. We recognize we've, we've seen how vulnerable apps can be and, and these invasion points, is that being reflected in budgets? Are we seeing that? Are people making these kinds of investments or is there still some lip service being paid to it and maybe they need a little more money where their mouth is. >>There's not a shortage of dollars, so I'll be be real straight forward. That is for us, the big growth area is uh, application security in a pipeline. The notion of shift left, um, and it's been, it's actually one of the easier conversations because the CSOs really want to make sure that every piece of code is tested, be it static code, dynamic code, license scanning, all the above. Um, the way they've had to do that and traditionally done it is at the end of a pipeline and they make every dev on happy because they throw it all the way back to the front with the dev. And then I was like, Oh, thank you so much. I did that two weeks ago and now I have to go, why didn't we do it on the front side instead of the back side? You kill the most important thing, which is cycle time, right? >>Cycle time is time from idea to Chimp. So by shifting it left, there's plenty of money and the CSOs love it because just want you to spend it. It's where they spend it. Right. And so now they get all the code tested. The devs love it because they get feedback instead of the CSO saying this is broken. The two old, the second they hit command a couple minutes later, Oh it's broken. They go fix it, make another commit. They're going to move way faster much. Um, so that's really what we get at and yeah, but no short in dollars, the security still the windows, the spend happens, you're saying right on the front side instead of the back shop and try and get full coverage. So a lot of times otherwise if you're trying to do security after someone's developed it, you're not sure. Like are you getting every code, all a piece of code that was developed? Are you getting just a lot of it as you talked about web apps, a lot of it is the focus. Oh the web apps. Cause that's the front end. But intrusion, once it passed the front end, it's a soft interior. You've got to do every single piece of code has to be tested. >>Yeah. It's Brandon. So you know what I've heard, especially from, I mean, you know, my peers in the security industry, you know, security needs to be considered the entire way. Security is everyone's job chair's responsibility. I need to think about it. But the other thing that really has changed for people is you talk about CIC. D I need to move fast. Well hold on. The security team's got to review everything. One of the core principles of dev ops is you want to bake it in the process, you need to get them involved. And then there's DevSecOps which pulls all of these pieces together. So tell, tell us how those trends are going and that, you know, speed and security actually go together not opposed. >>Oh yeah. And because, and it's how you measure the, the speed. Cause I think sometimes the question is all back to what is it from it. It's, it's a life cycle. And if that's what you're measuring, being able to do the security earlier is so much faster because you're not having to iterate, um, later. But, um, it's continues to increase. Devs are getting more and more say that's not gonna change anytime soon. Um, empowering those devs to own the security, uh, empowering those devs through the pipeline to be able to deploy into Lambda, into far gate. They love that. And if you could give that and give the security, the visibility, the dashboarding, the understanding of what just went in, um, what code they're using, what the licenses are, that visibility is huge and that allows you to move fast cause it's trust. >>I mean actually, uh, I love the researchers at Dora, you know, do the annual survey, uh, on dev ops and they said, actually if you are a company that tends to deploy less often, it tends to take you much longer to recover and you're not geared to be able to do it. Uh, you know, my background networking and you think about, you know, security is one of those things like, well wait, I want to keep my things stable and not changing for a while, but that means you're less and less secure cause I need to be on the latest patch. I need to be able to update things there. So, uh, you know, CIC D I think leads to should lead to greater security. Do you have some stats around that for your customer as to, you know, how they measure that? >>We have some pretty good velocity. Um, so Goldman went with us and this is real public is they, they started with us and went from about a two week release cycle down to tens, 20 a hundred times a day. Um, and that, I mean that's a company that does a great job in dev, um, but can also be like smaller companies like wag labs that we talked with earlier and they same kind of thing. They went often from a week down to they were doing, they typically do 20 to 30 deployments a day. And again, it just makes you break the pieces smaller, less likely that you're going to introduce dependencies that break something and all that process builds on each other as the door is stuff. If you haven't read, you've read it obviously, but if the users haven't great place to get started and understand how this works. >>Has testing changed or is testing changing in terms of when you establish the criteria, what you're looking for in terms of I guess you have a lot of new capabilities so you've got to change, I assumed your criteria up front do have a little proper, a little more accurate evaluation is that environment it's changed somewhat. I mean testing in application testing it is pretty specific to every comfy. So tools continue to get better. Um, ways of review have gotten a lot better. So, uh, there's now a lot of capabilities that at the point that you're going to go into deployment, one of the harder pieces is doing, um, your user acceptance testing is like, God, am I going to see the same thing that a user will? Right. And a lot of these have gotten to a point like we have a one click at the end of the deploy, a review app. >>Anyone in the company can look at exactly rebuild everything you're going to bought to deploy. So there's some tools that make it faster. Um, but in terms of what your load balancing in terms of your user acceptance testing, a lot of those principles continue to be pretty girl. Uh, one of the big things we heard from Andy Jassy is talking about transformation and he said you can't just do it incrementally and you need, you know, clear leadership and commitment. We want to hear how, you know, you're hearing about this from your customers. How is get live helping customers along those transformation journeys. Sure. Um, so totally agree that, I mean, it's a cultural piece, uh, without question. I think there's a couple of places, there's the obviously the tool piece and just getting everyone on the same page. And we, we all know this intuitively is we've seen what w when you go from a word doc to a Google doc and everyone can edit the same time, that's transformation goes, you know what everyone's working on, uh, and you're not duplicating effort. >>And that, that's really in many ways that's what get lab is doing is just helping the front end. I, you know, product manager know exactly what's going on in the infrastructure side and you communicate in a similar language. Um, the other piece of that we are working a lot in is because, um, get lamb operates an extremely open culture. So we publish how we run the company in a handbook that's 2,500 pages. We're always updating it. So, uh, we do reviews every time we release, we release every single month for the last 120 months in a row. We go through, here's what the release is going to be. It's on YouTube. Everyone can see it when things go wrong, we publish it. So we have an outage, we will, we have live broadcast, how we get back out from an outage and we publish all of it for someone to understand. >>And so one of the other things, there's a lot of our customers are getting started on that journey. There's one thing for a deck that says, here's what you do for your transformation for your company. That's another thing when you can literally jump in on Monday morning under the get lab call and watch, get lab go through a post-mortem of when we had a small outage. Oh that's what a no blame looks like. Okay, now I understand that, Hey, what, what didn't we release that we could have done better? And those are processes that you can have it on a piece of paper, but it's a different thing when you can walk through that with the company. And it's even better when you're watching the company that's doing the same product, the same tool that you're using. So I mean that's a, that's a cultural decision. >>Yes. I mean it's gotta be right. Yeah. I love the no blame. Right. Cause you're saying instead of finger pointing, great or castigating, you know, we're, we're going to learn from this. And how do you think, what impact does that have on a customer when they see you in real time solving your problems? They know that. They know that if they have a question for us, that we both take it seriously and that we're going to do it in a way that they know when it's going to be resolved. And that doesn't mean that we always deliver at the same time that a customer asks. But that level of transparency breeds both trust. And it also helps a customer quantify what do they want, helps us huge amount of communication because they know what we're prioritizing and they understand why. And that isn't something that is typical to come, but it's always typically very hard unless you're broadcast everything like we do to know, well, why are they making that decision? >>Um, and so that's one of the real big reasons that our customers work with us. That's where we get 10,000 plus additional contributors to get lab as an open source project. And that helps massively of course. So the velocity is because there's no difference between a get labber or the thousand get lappers in 64 countries or any one of the 10,000 contributors or our biggest competitors that regularly make contributions to, uh, our, um, our landscape. So we have a landscape that's, how does dev ops work? Who does stuff well? Hey, have no shame if they delivered something better. I want to know that I make that commit. We will share it with the world that we are not good at that and you are better at it and you know what? We'll get better. Right. It's a winning formula. It's good. It's been working really well. I appreciate the time brand. A good saying. You can love the slacks. Wish we could show them of course. But next time, thanks for having us. All right. You're watching Carvery Cherif AWS reinvent 2019 on the queue.

>> Voiceover: Live from Las Vegas. It's theCUBE covering UiPath Forward Americas 2019. Brought to you by UiPath. >> Welcome back to the Bellagio, everybody. You are watching theCUBE, the leader in live tech coverage, this is Day 2 of UiPath's Forward III Conference and Kourtney Bradbeary is here R&D specialist at American Fidelity. She's joined by Michael Setticasi, who's the senior director of business development at Boston-based DataRobot, but Michael's from Seattle. Guys, welcome to theCUBE. >> Kourtney B.: Thank you. >> Kourtney, let's start with you. I know you guys, you kind of do benefit solutions, but maybe talk a little a bit about the company and some of the big trends that are driving what you guys are doing. >> Kourtney B: Absolutely. So I work with American Fidelity, it's an insurance company based out of Oklahoma, but our main focus is providing solutions to our customer pain points. So we're a niche-based organization that focuses mainly on education, so the public sector, so education in municipalities in providing solutions and benefits to our employers and our employees that we work with. >> Cool, and Michael, you guys, obviously data science is your thing, but describe a little bit more about what you guys do. >> Yeah, we're an AI enterprise company. What we're really trying to do is democratize the use of AI machine learning within organizations, and we really appeal to both data scientists and business users that understand their business and data and want to do more. >> So Kourtney, you're title is really interesting. R&D special projects, so you got this little sandbox that you get to play with, RPA is on the hype cycle and now it's in the trough of disillusionment, but it's kind of an early play around with things. How did you get in to RPA? Where you guys at? What's this R&D thing going on? Right, so with research and development, I guess there's a lot of space to work with emerging technologies, and AI, and RPA, and how those two things come together and anything new that we see and exciting we're able to apply that technology. It's one thing to think, "Oh, AI, that's cool. Let's do that." But if it doesn't benefit your customer at the end of the day, if it's not driving decisions in your organization, then we don't want to do AI just 'cause it's cool. We really want to do AI because it's what benefits our customer. So we got into RPA because when we saw a demo, and it was like, whoa. If that's real, if that's what we think it's going to be, that's a game changer. So you have RPA, and you have AI kind of coming up at the same time and whenever it was, first coming out a few years ago, they're silo, they're separate. What we've started to do recently is to bring the two industries together and really bring together the RPA component and the AI component to really become IPA, or Intelligent Process Automation, so that way we can really start to transform businesses. >> So this is interesting to me, Michael, because as Kourtney was saying, most people think of these things as separate and more aspirational down the road. You guys are AI experts, what are you seeing in terms of these two domains coming together? >> You hear about intelligent automation everywhere, right? We are pushing it hard, and we're seeing a lot of customers and potential prospects look at it, but I have to give credit to American Fidelity. They are ahead of the curve. They're combining this ability to use an RPA process and a machine learning model to really automate things and provide better customer service and get to the endpoint faster and more efficiently. So I think they're ahead of the curve, but you're going to see more and more of this in the marketplace. >> So Kourtney, a lot of the customers that we talk to, this is kind of my observation, is they're automating obviously mundane processes but frankly really crappy processes. They're really screwed up in a lot of ways. And they're throwing RPA at the problem, it sounds like you have a little different philosophy around how to apply automation. Can you explain that? >> Right, so you don't want to automate something that's bad because then it's going to break a lot, and it's just not a good idea. So what we've tried to do is whenever we get request in the door, there's always a stopping, if somebody has to make a decision, in the past, it's been "Okay, well we can automate the first part and the last part", but it's kind of have to stop in the middle for you to make a decision. And what DataRobot has allowed us to do, in the past, it was really hard to actually apply machine learning, 'cause you had to have these data scientists and they'd have to spend months trying to figure out what model for the data, and is it, you know, retraining a model is really difficult. DataRobot makes a data scientist's job so much easier and actually applicable to the workplace where you could scale, enable scaling, because without DataRobot or without a service like that, it's impossible to scale. So it allows us to implement AI with our RPA to then not just automate the mundane processes, but the small decisions that we make everyday, just 'cause we do our jobs everyday and we know how to do our jobs, AI enables us to automate those processes, as well. >> And you're doing that in an unattended way, or is it an attended automation? >> Both, both. So there's some processes that we have to have a human select things and make certain decisions along the way, or there's some processes that are completely unattended. With any automation, your goal is always to automate 100%, but in reality, you're usually going to get about 80% of a process automated. So what we try to do, we go for the hundred percent, rarely get that, but then you can take out the 20% for human review. And so maybe of the 20% that's not fully automated, maybe we can make stop points for human interaction there, but there have been some processes that we have been able to fully automate. >> So Michael, the data scientists complain that 80% of their time is spent in wrangling data and getting the data ready to actually build a model. I presume that's what you guys do, you solve that problem, right? >> We definitely solve some of that, right? If you get the data all in one place, DataRobot takes care of a lot of the data preparation that's involved in data science. We've also have ways to kind of manage the best places you store your data, so that if other people use the platform, they can see where to get it to. But overall, I would just say, when you look at UiPath and the way it's growing, it's such an exciting growing company like we heard Daniel yesterday mention their growth from customer from year to year, how they're the fastest enterprise software growing company out there. So you combine that RPA market with this growing machine learning market, and there's a ton of excitement. I mean, that's what you're seeing at the conference today. >> So you guys have data scientists on staff, is that right, or-- >> Correct! >> Okay, and so what does this mean for them? Does it mean you just need less of them, or they spend more of their time doing productive work? >> It means they spend more of their time doing productive work, instead of trying to figure out what model to fit, 'cause if you're a data scientist, or an actuary, or any, data analyst, or any of those things, you might know five models that you try to fit everything to. What DataRobot enables us to do is not be stuck to those five models that we know. It enables us to combine models, and choose models based on that data, so it really helps us with the modeling. >> Are you, I should've asked this before, are you still in R&D? Or are you in production? Or where are you at in terms of majority? >> Oh no, we're in production. We have two IPA processes in production today, and we're working on increasing that as we go. We have over a hundred an fifty RPA processes in production, as well as, many many just machine learning, so we're working on combining those now. So we have many machine learning, we have many RPA, and we're working on increasing our IPA. >> What have you seen as the business impact? Do we have enough data yet to sort of-- >> Absolutely. We don't try to focus on ROI. What we try to focus on is how is this impacting our customer, and how is this impacting employees' lives. There's obviously a lot of fear around automation but at American Fidelity, what we try to do is show how this is going to improve our employees' lives and we're by no means trying to cut jobs. We're actually going to have a net increase of jobs over the next five years. We're re skilling our workforce. We're really focusing on how it improves our employees, rather than focusing on ROI. >> So you're not on the ROI treadmill? So how did you get your CFO to sort of agree to all of this? >> So we do track ROI. It's not something we share publicly. But we focus more on our humans and our employees than our ROI. >> Is that because, I mean you're not, virtually every customer I've talked to says, "Well, we're not firing people. We're just getting more productive, or shifting them to more interesting tasks, et cetera, et cetera," and if you do the ROI calculations, you say "Oh, I don't need as many humans to do this anymore", and so you'd say, "Okay, FTE cost" and then you apply that, it's kind of a BS number, 'cause it's not like you're cutting people, so it's not a hard ROI. Is that why you don't focus on ROI? Or you just think it's worthless metric? >> No... >> Actually, I'm sorry. You said you do have it, you just don't share it publicly. >> Right, we just don't share our ROI publicly. And I don't think it's made up, or it's fake. I've never met an organization that says they have more people than they have work for people. There's always work. I really enjoy the first video opening of UiPath, it's, "since the beginning of time, humans have worked", and everyone thinks that automation is going to get rid of jobs, there's a lot of controversy over that, but realistically, if you think about the first industrial revolution, that was, after the first industrial revolution hit, that was the biggest economic upturn that had seen since that time. We're in that same space now. It's just hard to see it with where we're at. It's only going to increase, work is only going to increase. It's definitely going to change. I think it's naive to think that jobs won't change. And there will be jobs that will be eliminated, job functions, but I don't think there's elimination of humans needed, if that makes sense. >> Well yeah, it does. You guys sound like you're pretty visionary about how to apply technology to your business. And Michael, I mean, Kourtney's right, machines have always replaced humans, this is nothing new, first time ever that it's in cognitive function, so that scares people a little bit, but what else are you seeing in the marketplace that you can share with us? >> We're just seeing increased use of automation. So like, you might think when you talk DataRobot, you're using us for the top 1% things that a company might do, right? If you're a bank, you might use us to help out, figure out, how you can more efficiently lend customer's money, and make sure that you're making good investments, but what we're finding is, automation and machine learning models are being used everywhere. They're being used in marketing now, right? An example could be this show. We'll get leads from this show. Let's run some machine learning to understand what leads to follow up on first, because we'll get the best result. We're seeing machine learning in HR, right? Making sure their employees are happy, tracking employee churn through machine learning, so I think what we're seeing is it's being adopted more broadly, which means you need more people. We're not replacing people. >> So, why UiPath? >> Whenever we started the vendor process and started looking at several vendors, the UiPath product just was unmatched, frankly. There was a lot of vendors that had more code base, and there was then UiPath that anyone can learn. And that's what we really liked 'cause in American Fidelity, we've chosen to go with, we have a COE but we've also chosen to go with a democratized model where everyone in the organization will be able to build robots. We're training people to build robots. We have, each department has people that are dedicated. A certain portion of their time is building robots and UiPath really made that available with their products for anybody to be able to learn. >> So you have a COE. >> Kourtney B.: Yes. It was interesting, Craig LeClaire this morning, I don't know if you saw his keynote, but he kind of made this statement, it was sort of a off-handed statement, he said, "COE, maybe that's asking too much". He didn't use term tiger team, but I inferred, it's like, rather just kind of get a tiger team of some experts, but talk a little bit more about your COE. >> So, we kind of go with a hybrid model. If you think about, typical, it's weird because RPA is only a few years old, and we're thinking typical RPA, but people usually either go with a COE or completely democratized. We've really gone with a hybrid model, so we have a COE with governance where we've set a loose framework of what to follow, and we have code standards, when you say, follow these things. We have a knowledge library that we share. But we only have a handful of full-time RPA developers, and everyone help, those developers help, teach and help grow that knowledge throughout the organization, so that way we have people in every area that can also develop. So our developers are not our own key developers. Our developers are focused on the IPA, on the AI, whereas our other people throughout the organization are focused more on RPA so we can really make a big difference more quickly. >> Do you have a software robot that automates auditing and checks for compliance? >> Yes, so we have, one of our robots, the function that it does is audit one of our inputs, so we do have robots in almost every area that, yeah, we do have audit robots. >> Has it cut the auditing bill? Is that part of the ROI? You don't have to answer that. (giggles) >> Michael, our last question for you is where do you see this all going? This is very interesting to me because I've inferred from a lot of the conversations that, like that PepsiCo guy was up yesterday, talking about an AI fabric throughout the organization, not just tactical projects, and that kind of interested me, but I expected it's much further off. I'm hearing from Kourtney that it's actually real today. What's your sort of prediction or forecast for the adoption of this more advanced intelligent process automation? Is it kind of just starting now and it's going to explode? Or am I just missing the mark here? >> No, I think you're a hundred percent on. I mean, first off, I think, like I mentioned earlier, RPA and machine learning separately, are in these incredible growth stages. Right, and we think our message to customers now is if you're not thinking about how you're doing AI and machine learning, you're already behind 'cause your competition is. And so you better get thinking about it. I think we're going to get to that level with intelligent automation, with RPA plus machine learning very soon. I do think right now we're in that infancy stage where people are looking for used cases, and they want to hear great stories, and so I do think American Fidelity is ahead of the curve, but they're not going to be ahead of the curve for long. It's catching up. If you're not doing it, we're going to eventually get to that point where you'll have someone like Elon Musk or Masayoshi Son, say, if you're not thinking of intelligent automation, you're already going to be left behind. >> All right, congratulations on the work that you've done. >> Kourtney B.: Thank you. >> It's a really awesome story. Thanks so much for coming on theCUBE. >> Yeah, yeah, thanks for having us. >> Thanks for having us. >> All right, keep it right there, everybody. We'll be back from UiPath Forward day number 2. You're watching theCUBE. Be right back. (upbeat music)

>> from Austin, Texas. It's Theo Cube, covering pure storage. Accelerate 2019. Brought to you by pure storage. >> Welcome back to the Cube. The leader in live tech coverage. Lisa Martin and David Lantz wrapping up day one of our coverage of pure accelerate. 2019. Howdy. How do y'all Hey, I >> think I started a trend. >> I think you did. So, Dave, this has been a dice shot out of a cannon. I think, as only you know, pure does. Well, we had lots of conversations. Lots of news this morning, Which was nice to hear. As pure welcomes their 10th anniversary in a couple of weeks. We talked with customers. We talked in many different industries partners, Puritans. Lots of innovation has occurred in their 1st 10 years. Charlie got up on stage this morning. Then he came to the Cube and talked about this modern data experience and the 10 X improvements and many things that they're gonna deliver. Not in the next 10 years. In the next few years. >> Yes. So we're seeing a story of growth here. It's a theme. If you look read yours press releases, they start The first line is the only storage company that's growing, which is true, at least the storage company of size of a billion dollar plus storage company and talking a lot about modern storage. To me, it's a story of entering new markets their second decade tam expansion into new ai ai workloads. Certainly the cloud trying to make the cloud of a tailwind. We have just heard from Carrie Stanton of'em Data protection is an area. You know, years ago, Uh, I remember talking to executive at Netapp Tom George and saying, Hey, we're gonna buy ah, storage backup cos you know, we're gonna preserve our partnerships with whomever con vault and Veritas in vino, whoever they're working with time and you see pure taking a similar strategy E M. C at the time did something different. They vertically integrated. They they bought a company called Llegado. They integrated into compete. And of course, now they're that sort of their stack. And so, if you were small enough now still close to $2 billion at the at the end of this fiscal year that they don't have to necessarily vertically integrate, we'll see 10 Next 10. That's the third decade, what happens there and in the customer input you're seeing. Customers are continuing to invest in pure. They're very happy. What you've seen, Lisa is customers look at pure is shifting. And I said this on the Cube earlier shifting labor in tow. Pure czar and D. Now the hyper scale is like Amazon. They'll spend time of engineering time to save money. I t practitioners of the enterprise. They'll spend money to save time and so they will happily spend money on on products if they can lower the IittIe labor costs. So totally different mindsets and you're you're seeing that's taking hold and pure really has done a great job of that. Now, as I said in my my breaking analysis, you know, a couple weeks ago, analyzing the vendors pure, clearly growing. But these things go in cycles, right? There's hard compares. You're going to see. I guarantee you're going to see these other companies, you know, chewing their models. They're big, pure talks about 10 X. The reality is, you know, Delhi emcees 10 x the size of pure right, so they throw a farm or cash on. So if you're a big whale with a big install base, that's what you do, You mind it If you're pure and you're smaller, you're 1.51 point seven billion. You go hunting. And that's the dynamic worse we're seeing. I don't see that changing dramatically for quite some time until the economy shifts and in the mindset shifts and when. Then we'll see how pure adjusts its business model from, perhaps growth to more profitability. >> And speaking of growth, they're just coming off a very successful second quarter where they announced last month in August, 28% year on year, both adding about seven that new customers a day. A lot of that attributed to innovation and the channel. They did a good job in the last 18 months or so of pivoting. They're smaller medium customer business to the channel, allowing peer to focus on much more enterprise focus. And they actually I think, even in queue to close 50% more multi $1,000,000 deals this last quarter >> and well, and while those seem like great numbers, they actually the stock got hit after the quarter. Why? Because they lowered guidance. Why, Because of this NAND pricing confusion, Nan pricing drops so fast in the quarter faster. They expected it sort of hurt revenues a little bit. They expect that that softness that continue. So they've been conservative going for it. You know, who knows of this smart to be conservative cause I wouldn't say that they're sandbagging. I say they're being conservative, you know, makes a bigger question. You know, it's storage kind of a crappy business, and we'll see. I say, that is, if you're gonna win in storage right these days, you have to gain share. Pure is gaining share della. 0% growth appears to be gaining share 0% growth. It's not a great market. So what's happening, we don't really know is cloud siphoning off demand for the traditional on Prem surgeon Could be. Can these companies make cloud a tailwind or is cloud a zero sum game? I tend to think long term, the Maur cloud, the worse it is for on Prem. So that's why everybody's scrambling for this multi cloud strategy, which is very, very early days. Multi cloud today is largely a a symptom of multi vendor versus you know, a coherent user strategy with right we're management's. Now the Big Five are trying to change that pure is playing its role. Companies like Veum and others are playing their role, so we'll see how that plays out. I do think there's a clear opportunity and multi cloud, but, um, it you know, it's unclear how large that is or whether it's just going to be a series of horses for courses. In other words, the right strategic fit for the right workload. >> So your thoughts on the evolution of their AWS partnership really looking at what they're now doing with eight of us as this bridge toe hybrid cloud customers of choice on from hosted, you know, as a service public cloud your take on this forcing function of bringing pure and AWS together of the customer base. >> Yeah, I think it's actually pretty clever. Move by pure take their engineering. It's okay. We're gonna settle, do all the heavy lifting set up AWS with e c two priority E. C. Two instances networking we're gonna mirror. We're gonna the architect of the basically block storage inside of eight of its front ending s three, which is the cheap object store? Pretty innovative. What it does is it gives customers an option for hire availability block storage that looks like pure but runs on AWS in the cloud. Very clever. And so all the advantages of OPEC's versus cap ex. You know the cloud experience, but it's the pure management experience. Eso very clever. Give pure customers who were happy. An option is there. I'm sure they're hearing from the customers. Hey, we want to go to the cloud where we heard it from the the eight of us Speaker today. Gardner Data. 88% of customers have a cloud first strategy, but 86 continue to spend on print. Right? Okay. So smart by pure to do that, I don't know how big a business that's gonna be, but it's a nice hedge. In case that really, that trend takes off >> and your thoughts on one of the other announcements today. Another first rip your We've talked about that the number of times they have there been first in a lot of things in the last 10 years transitioning offering most of their portfolio as a service and your perspective against the other competitors that you mentioned. How do you see that? >> Yeah, you know, the first your lips, they're bigger than the small companies that people have never heard of, like Zadar, a storage who actually were probably one of the first. But but they're the first again $1,000,000,000 plus company to do this. That's what customers want Customers want. The cloud experience in a big part of that cloud experience is a pricing model in the utility model. That's cloud like when AWS announced outposts, it was a clear sign that the industry had had to respond. I'm not saying this is a response to Outpost, but it's clearly a response to the cloud model so paid by the drink. You know, Op X versus cap packs of being able to have that cloud pricing model and experience across the portfolio is goodness. >> So Charlie, their CEO, talked about this morning, this modern data experience going into the next decade, it's gonna be three. Us is simple, seamless, sustainable. We all want that. I think for anything in life, your take on that from marketing to reality >> I see is anything but simple. Let's be honest. It's seamless is probably the most overused word in a >> knot. I think in future proof >> it's the chance to say that and sustainable >> eh? Well >> sustained from the standpoint, what I love about the model is way. Heard this in the customer today. Well, you know, the five year TCO was kind of a wash, but then beyond five years, it was a no brainer because we're now in that subscription model. So I guess that's that's the sort of sustainability you think its sustainability in different ways. You know, green, I t >> right >> again. I t is not really green. So, you know, good marketing. >> Well, we heard from I think we had three or four customers on today with four to legal firms, one in New Zealand, one in the States we heard from a utility company out of Tulsa, Oklahoma, and then Mercedes AMG, Petunias Motor Sport. Formula One free, very different industries, similar stories in terms of the management simplicity of pure the evergreen model of being able to swap out and take advantage of those innovations and the things that Piers is doing the r and d on from a cost perspective. But I think those were three kind of common business and I t benefits that I heard articulated by three very different industries of very different sizes. >> I mean, I think it's important. Remember, you get a really effusive commentary from the pure customers, and I'm not trying to B B negative on that. They're very, very clear that companies like pure Nutanix cohesive the rubric wien. They have great customer experiences, and they're different than what companies air used to buying very often. Having said that, when we get these, when we get into these, you know, benefit, cost benefit discussions Typically you're you're you're comparing a modern, you know, circa 2019 platform with something that's, you know, five years old, so you better have a significantly better metrics again. Having said that, you're seeing a different experience, and that's clearly coming through in the customers that you talk to with pure. They started with a clean sheet of paper, didn't have a lot of technical debt, not a lot of baggage, that alone some really smart people that, you know, in Silicon Valley, you know, inundated with all this cloud stuff, and then they brought it forth very hard to build a billion dollar storage company. Pure was the 1st 1 since Netapp. So >> that was a couple of guys going >> to do it compelling couldn't do it. Equal logic couldn't do it after you've never heard of half of these companies, right? It's been it's been many, many years, decades since you saw a billion dollar storage company. That's how hard it is and to achieve escape velocity and fewer did it, which is quite a feat. And now that now the challenge is their market cap. It's so large that four and 1/2 1,000,000,000 and growing right ostensibly that they may be become acquisition proof. Okay, that's a good thing on the one hand, cause we love independent companies. On the other hand, at some point, the Tam Tam expansion within that little niche gets very difficult. That's why, for example, e M. C. Had to go out and buy a company like Llegado, and it made some actually, you know, some other crappy Apple acquisitions that didn't work out. And then they stumbled into VM, where it was gonna part of a TAM expansion strategy, and they lucked out because they the greatest acquisition in the history of I T. But I guess my point is at some point, a billion dollar company becomes a $2 billion company. Maybe give becomes a $5 billion company, and then it's like, OK, what do we do next? How do and you're seeing that app is in there now. Netapp is a growth challenge, Um, and a Tam expansion challenge. But it's too big to get acquired. There were years for their. For years. There were rumors about Cisco required, kept the stock up. It never happened. So stock buybacks tuck in acquisitions, you know, refresh of the portfolio, squeezing out a little bit of growth, some bad quarters. You know, that's That's the nature of the big company so pure at some point we'll hit that, but I think we're a couple of 1,000,000,000 away. >> They have also done a robust job of building a robust partner ecosystem. We talked to a number of them today, Cisco in video we had on the team. Tomorrow's Blanc is on in terms of this growth that you talked about, How well positioned are they with with the strategic and technology partnerships that they are not only building but evolving quite quickly? Where does that factor into your thoughts about their future in the next decade? >> I think, um, I think the key to that is their architecture. In terms of their AP, I, uh, framework. It makes it easy to integrate. Wait, Um and to the extent that they continue to grow, the customers buy their products, loved their products. The high end p s scores all that stuff, it's easier to have a NPS score when you're a billion dollar company is when you're, you know, $50 billion company. But are you with a big portfolio? But customers, clearly you're has momentum. People want to be with a winner. If yours a winner there. Architectures easy to integrate. Relatively speaking. Thio, You know the legacy vendors and it's clean across the portfolio. And so that's that's why I think the ecosystem continues to grow. I'd like to see more growth, you know, I remember service now when they were a billion dollar company and thinking, Wow, it was about this size, you know? Now you go to service now. I mean, you see the big, uh s eyes. You see a lot of niche players bumping into him or jumping up. I'd like to see that here, and I think it will continue. >> Well, this is certainly ah good chunk larger than last year's accelerate, which was about a year and 1/2 ago. And look where we are, Dave, We're in Austin. This is Dell's backyard. This is a bold company. I was telling you earlier today when I was doing some research for our guests, something that catches my attention as a marketer that many companies cannot d'oh and that is very bold and very direct against their competitors and tell customers this is why you should be buying us. I applaud that as a marketer, and as somebody who gets to interview folks on the Q, because it's hard to do. They have this bullish culture that they've always had, and they have grown in the last 10 years. We're seeing expansion, and we're seeing them not afraid to tackle anybody that their customers are looking at. >> So I want to talk about some of the industry dynamics as well. The I T industry loves a vacuum, and I think in some respects the acquisition of the EMS see by Del created a vacuum and pure is taking advantage of that now. For a while, Gel took its eye off the ball and was storage business was affected, and then they got their act together. And now it's 0% growth. It's it's Yeah, okay, I'd like to see better growth there, but they've been doing a lot of work, and pure is referenced this and some of the pressure. This is Dallas consolidating its portfolio, which is exactly the right thing to do. Deli emcees Portfolio is way too complicated, but you have to be careful. You can't just consolidate overnight because you're alienating your customers. So there's still some of that going on. The linchpin of Del strategy is VM wear. That is the key. That's where the future is for those guys. So when AMC was an independent storage company, it would fight tooth and nail. You know, Jeremy Burton was gonna take out net app, and he didn't do it. You have all these crazy videos and they, you know, they were focused, competitive oriented company that loved its customers and was very customer focused in many respects. I mean, they're still competitive, very competitive, but they're not that independent, pure play anymore. It's now it's netapp and pure, and I feel like net episode distracted, you know, with some of the struggles that pure is really, you know, has an opportunity. You know, I I remember Scott decent years and years and years ago told me when they were nobody said We think we could be the next TMC in storage. And I was like, Really? That's a amazingly bold statement when it appeared that the storage industry was kind of disappearing and everybody was getting acquired and it was becoming this vertically integrated converged infrastructure player with storage and networking and service. And that still may happen. A cloud, everything else, Um, but, you know, if you're has an opportunity to really become the leader in in this business in, you know, has an opportunity become the number one storage company takes some time, Uh, for a while. I question is, it doesn't really make sense to have independent stores, But you still see a lot of innovation. Certainly the backup vendors startups, you know, you see smaller companies, VC money still coming in back to something you said earlier. I t generally, and storage specifically really isn't simple. It's very complicated, and it's very hard. >> Well, Dave, we have had a great first day. I'm excited to work with you tomorrow. We've got cause coming on. Kicks coming on some more customers. Lots of good stuff in store for day two. >> All right, Cool. >> Likewise for David. Dante. I'm Lisa Martin. You're watching the Cube, the leader in live coverage.

>> From Austin, Texas, it's theCUBE, covering Pure Storage Accelerate 2019, brought to you by Pure Storage. >> Welcome back to theCUBE, the leader in live tech coverage. Lisa Martin with Dave Vellante. We are in Austin, Texas for Pure Accelerate '19. And we're excited to be talking with another one of Pure's happy successful customers. We've got Scott Pedram, the storage architect from One Gas. Scott, welcome to theCUBE. >> Thank you for having me. >> So One Gas. Give our audience a little bit of an overview of what One Gas is, what regions you serve, and then dig into your role as a storage architect. >> Of course. So One Gas, we're a natural gas utility company. So we're the downstream, the inline. So we actually deliver the natural gas to our customers, residential and commercial. We operate across Texas, Oklahoma, and Kansas, and various regions including Austin. In my role as storage architect, I help, I mean, basically a one-man show. So design the storage, implement the storage, run the storage. And I also help out in other areas such as the servers, the DBAs, networking, kind of a little bit of everything. >> So you've been a Pure customer for about three years. We were talking before we went live. Give us an overview of your storage infrastructure, your IT environment three years ago, and what the impetus was to evaluate Pure. >> Sure. So we were previously an IBM storage shop. I had IBM SAN volume controller backed by DS 8000, FlashSystem 820s, Storwize V7000s, so different tiers of storage all being managed by VSPC. As is common, the warranty runs out on the DS 8000. So it's time to look at a forklift upgrade or whatever the case may be. I had a plan all in place to replace it with IBM, but we are a fully regulated utility company. So I did my due diligence and brought in some competitors. EMT and Pure Storage. Heard Pure's story, especially the Evergreen storage model, and the five and six year total cost of ownership was actually pretty close, but once you went beyond that, there was no contest. Pure won hands down. And again, as a utility company, we like predictable, flat costs. So the fact that we could do that and not have to have this multi-million dollar expense again in just another three or four years. >> So I got to ask you, so TCO, done a lot of TCO studies, and the biggest component of total cost of ownership is labor, humans. So presumably, you did a full TCO, you looked at it. I'm surprised to hear you say that the five-year TCO was about comparable because Pure is, the Kool-Aid injection says it's simpler. It's more modern. Wouldn't that save head count or at least FTE? >> It could if we were a more complex environment, but as it stood, there's me and one other guy kind of as my backup. So, you still have to have somebody to run it, right? >> So that's what I asked so sometimes CFO's will go, Wait a minute. If we're not going to reduce head count, I'm not going to accept that as part of the cost reduction. Is that what's going on here? Because we're going to shift labor to more high value activity so, oftentimes the CFO doesn't count that in his or her business case. Was that the case or did you find that because you're so small it really didn't matter in terms of the management complexity? I'm interested in your thoughts on that. >> We didn't background management complexity when we were calculating TCO. It was purely the cost to acquire the storage and then the maintenance. >> Oh, so there was no management cost? No human capital, okay. >> No. >> And so it's you and somebody else. >> Scott: Correct. >> Have you now spent less time managing the Pure than you did previously with the IBM? >> Oh, for sure. >> Okay. >> And when I first got it I was afraid, am I going to work myself out of a job? >> The Pure? >> 'Cause it was so easy. >> Okay, so, you had two FTE's managing storage. >> Scott: Yeah. >> What percent of your time, prior to Pure, did you spend managing storage versus doing other stuff? (Scott sighs) I mean a rough ballpark. >> Yeah, rough ballpark. >> Dave: Was it 50/50? >> I would say, I was maybe doing 60 to 70% doing just Pure storage before. And now it's 20? >> So you've gone from 60 to 70, let's call it 65% of your time was spent managing storage tuning, troubleshooting, provisioning LANs, provisioning more capacity, planning, all those things that, we love it. Down to 20%. >> Probably. >> Roughly. I'm not going to hold you to it, but. Well I guess we're live TV, so I will hold you to it. (Scott laughing) But that's a significant savings. You can calculate that over five years, right? Take your fully loaded costs and boom, that adds up. What have you done with that time? What are you now doing? I presume you're not just hanging out. >> No, my boss is watching. >> Publicly traded, regulated utility, somebody's watching right? >> No, of course not. No I've been able to be a lot more proactive. So helping out, like I said, with the server teams, the inward teams. Consulting them on looking further. What is our longterm goal or strategy? What's the five year plan, type of thing. Instead of just fighting fires all day. Or, you know, next week we have to deal with this performance issue that's going to be coming up. >> Dave: So you've been able to be more strategic. >> For sure. >> And one more question on this whole, there's intangibles there that everybody always overlooks, but actually when you live them they make a big difference. Has there been a quality effect? In other words, instead of putting out fires you're doing thing that are more strategic. Do you feel like you have better quality infrastructure? And does that affect your business? >> I would say better quality in the fact that it's more consistent. So we ended up sweeping the entire floor with all Pure Storage. So all of production and non-production, in our case, is all on Pure. So the consistency of the latency and the response times and the performance that you get out of the storage. There is no more performance problems. It doesn't exist. >> And in terms of workloads, I know you're running Splunk on FlashArray. Give us some picture of that infrastructure, the workloads that you're running on it. And the stakeholders I can imagine them in different departments and different functions within One Gas that are using this system and not even realizing it because it's just available, it's there. >> Before Splunk, real quick, we had one application, we went to Flash. They thought their processing was broken because it completed so quickly. (Lisa laughing) >> That's a good thought to have. >> Yeah. So they finished so fast they came back to us, it's broken, I'm like, no it's not. (he laughs) >> What's your use case with Splunk? >> With Splunk it started out as cybersecurity and that's kind of what brought it in, but it has since expanded to monitoring, analytics. We actually use it when we roll out our trucks to the field to ensure that we're meeting the SLAs. There's so many different areas where we use Splunk, I'd have to refer to my notes. >> So infrastructure ops has become this big thing, right? And automation and things of that nature? Or not quite there? >> Not so much automation yet. But we do have a plan, a project to start doing more automation. >> And other analytics, I presume? I mean, they're all about analytics, right? >> A lot of our application teams, like our web development team, they use Splunk a lot for their application monitoring and trying to be proactive on that. >> Thinking about the security use case. Security practitioners often tell us, well, we get inundated with incidents. We don't have the time to sort through them all. Does having Splunk on an all FlashArray, high performance all FlashArray, does it affect the response of the security team? Or how does it affect the business, the security side of the business? >> I'm not able to answer that directly, but I can say that I have seen them do a lot of select all type queries, where they're just searching for a needle in a haystack, type of thing. And previously when we had multi-tiered storage those queries took forever, but now that it's all Flash, it's really quick. >> So they spent more time waiting than they do now. I mean that could be a two edge sword. Maybe they more stuff to sift through now. (he laughs) That's somebody else's problem. >> Well the data security is critical because your dealing with customers' data, right? And almost every month we hear about data breaches in the public. Whether it's a bank, or it's a social media platform. Unfortunately they're becoming quite common. But when you're dealing with personal customer data that's a big concern. Some of the things we're hearing Pure talk about is what they're doing with data protection and data security. And also kind of this sift from not looking at data protection as an insurance policy as much as it's an asset because you have so much information, you're storing it for longer, more and more customers, more data. How is that that being reflected up the chain, even up your chain of command and to the executive folks in terms of being confident that what they have your customers data running on in those three states that you talked about, is on a very solid secure platform? >> Well, security, it requires multiple layers. So Pure having always-on encryption is a big help. So if we do have, you know, a failed module that has to be replaced. I don't have to worry about making sure that it's securely erased, destroyed, and all that. 'Cause without the encryption key it's virtually crypto erased. And then of course we have all the security agents on the servers and the applications and our security cyber team managers, all of that. >> And what about cloud? What do you do in cloud? What's the strategy? >> We do cloud where it makes sense. For instance ServiceNow and O365 we're customers to both of those. >> Dave: So SaaS stuff. >> And mostly SaaS. In my opinion doing cloud is doing a lift and shift. And using cloud as infrastructure as a service doesn't make a whole lot of sense. For us anyway. As a utility company we're very pro-capital. So if we just shift that to another provider that's all operational. >> Whereas, take ServiceNow for example and change the operational model. Right? And you had a clear business impact where it wasn't a lift an shift. It was a transformation really. >> Exactly. >> Where do you want to go with Pure and storage infrastructure? It's just like, I just want it to work. I want it to be rock solid, dirt cheap, highly available, you know, high performance, or are there things that you would like to see Pure do that can help drive your business? >> Well I think the announcement today of the FlashArray//C is what I'm probably most exited about, in that I've already asked my business partners to get me some pricing, some quotes on, can I use that for my backups as a back up target? Instead of, you know, the underlying SaaS datadisks. So that's exciting for me. The fact that it's going to be the same software that I'm used to, that's all a plus. >> How are you protecting your Flash arrays today? >> We're implementing Commvault right now So we do leverage Commvault. It's called IntelliSnap. So basically it does a Pure level snapshot and then we can mount that on our media agents. >> Okay, so, using FlashArray//C, that's the right model number, I think. So obviously you want to use Flash, if it's cost effective, for everything. If it's cheaper than spinning Disk why not use it? Do you see any advantage, in theory, for recovery speed? For sure, yeah, absolutely. I mean, if you need to do a fast recovery, I mean, it's on Flash. But with what I'm looking most forward to though is even the ingest of the data, the initial backups. If there's a lot of, you know querying and trying to figure out what's changed and what's not, that can be a lot of disk thrashing on traditional spindle drives. >> So let's look into the future a little bit before we wrap here. You've been a Pure customer for three years now. Presuming you've done some upgrades and swap outs of controllers in that time? >> Not quite yet. In the coming months we will have our first ever green controller swap. I've actually had a failed controller. So effectively the same process. Where one controller's down and didn't have any issues with performance or, >> No downtime, no disruption. >> No downtime. Absolutely not. Even upgrades where they, you know, take one controller down and upgrade it. I'll do those during business hours. >> Are you comfortable with the, go ahead, sorry. >> Just because there's no performance degradation whatsoever. >> So you're obviously comfortable with the architecture. You seem like a pretty happy customer. Some of the critics will say, it's a duel controller architecture, that doesn't bother you? >> No, not at all. (he laughs) >> I had to ask with a straight face. What would you like to see Pure do? If Charlie G. and Carl are sitting right here, what's the one thing that I could do to make your life easier, what would it be? Besides cutting price, you can't say cut price. >> Yeah. You know what, that's a great question. I think what I would have been asking for, top of mind, would have been the lower tier, what they came out with today, the C. >> You know, another criticism from some of the competitors is they don't have tiering. And when you talk to Pure about it they go, oh, we don't need tiering, we don't believe in tiering. What are your thoughts as a practitioner? Would you want to have a tiered array, like high performance Flash, lower in the same array? Or is this not something that is necessary? >> I don't think so. I go back to the consistency. You know we have all of production on Flash now and it's, I don't have to worry about performance. Whereas before I was constantly having to monitor and manage you know, is all the right stuff on the right tier, and it was a headache. >> So automated tiering wasn't so automated? Is that a fair statement? >> It worked fairly well, but there were some cases where it didn't. >> Yeah. So you're better just throwing it at Flash and it'll take care of itself. >> Yeah. >> Dave: Cool. >> So you've got a foundation now that's going to allow One Gas to evolve continually and we look forward to hearing in the next year or so when you go through that first big evergreen upgrade, how that goes. But it sounds like you've made the right choice and the foundation that you've got is pretty strong. And so many other layers of the business are benefiting and they don't even know it. Because as you said before, on of the constituents thought something was broken, it was that fast. >> Correct. >> So well done on your decision. >> Thank you. >> Thank you so much, Scott, for stopping by theCUBE and talking with Dave and me about what One Gas has been doing how you're succeeding and we look forward to hearing more of your success. >> Thank you. >> Dave: Great to have you, thanks. >> Scott: Appreciate it. >> For Dave Vellante. I'm Lisa Martin. You're watching theCUBE, from Pure Accelerate '19. (upbeat electronic music)

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

- [Announcer] Live, from New York, it's theCUBE. Covering theCUBE New York City 2018. Brought to you by SiliconANGLE Media, and its ecosystem partners. - Hello everyone, welcome back to CUBE NYC. This is a CUBE special presentation of something that we've done now for the past couple of years. IBM has sponsored an influencer panel on some of the hottest topics in the industry, and of course, there's no hotter topic right now than AI. So, we've got nine of the top influencers in the AI space, and we're in Hell's Kitchen, and it's going to get hot in here. (laughing) And these guys, we're going to cover the gamut. So, first of all, folks, thanks so much for joining us today, really, as John said earlier, we love the collaboration with you all, and we'll definitely see you on social after the fact. I'm Dave Vellante, with my cohost for this session, Peter Burris, and again, thank you to IBM for sponsoring this and organizing this. IBM has a big event down here, in conjunction with Strata, called Change the Game, Winning with AI. We run theCUBE NYC, we've been here all week. So, here's the format. I'm going to kick it off, and then we'll see where it goes. So, I'm going to introduce each of the panelists, and then ask you guys to answer a question, I'm sorry, first, tell us a little bit about yourself, briefly, and then answer one of the following questions. Two big themes that have come up this week. One has been, because this is our ninth year covering what used to be Hadoop World, which kind of morphed into big data. Question is, AI, big data, same wine, new bottle? Or is it really substantive, and driving business value? So, that's one question to ponder. The other one is, you've heard the term, the phrase, data is the new oil. Is data really the new oil? Wonder what you think about that? Okay, so, Chris Penn, let's start with you. Chris is cofounder of Trust Insight, long time CUBE alum, and friend. Thanks for coming on. Tell us a little bit about yourself, and then pick one of those questions. - Sure, we're a data science consulting firm. We're an IBM business partner. When it comes to "data is the new oil," I love that expression because it's completely accurate. Crude oil is useless, you have to extract it out of the ground, refine it, and then bring it to distribution. Data is the same way, where you have to have developers and data architects get the data out. You need data scientists and tools, like Watson Studio, to refine it, and then you need to put it into production, and that's where marketing technologists, technologists, business analytics folks, and tools like Watson Machine Learning help bring the data and make it useful. - Okay, great, thank you. Tony Flath is a tech and media consultant, focus on cloud and cyber security, welcome. - Thank you. - Tell us a little bit about yourself and your thoughts on one of those questions. - Sure thing, well, thanks so much for having us on this show, really appreciate it. My background is in cloud, cyber security, and certainly in emerging tech with artificial intelligence. Certainly touched it from a cyber security play, how you can use machine learning, machine control, for better controlling security across the gamut. But I'll touch on your question about wine, is it a new bottle, new wine? Where does this come from, from artificial intelligence? And I really see it as a whole new wine that is coming along. When you look at emerging technology, and you look at all the deep learning that's happening, it's going just beyond being able to machine learn and know what's happening, it's making some meaning to that data. And things are being done with that data, from robotics, from automation, from all kinds of different things, where we're at a point in society where data, our technology is getting beyond us. Prior to this, it's always been command and control. You control data from a keyboard. Well, this is passing us. So, my passion and perspective on this is, the humanization of it, of IT. How do you ensure that people are in that process, right? - Excellent, and we're going to come back and talk about that. - Thanks so much. - Carla Gentry, @DataNerd? Great to see you live, as opposed to just in the ether on Twitter. Data scientist, and owner of Analytical Solution. Welcome, your thoughts? - Thank you for having us. Mine is, is data the new oil? And I'd like to rephrase that is, data equals human lives. So, with all the other artificial intelligence and everything that's going on, and all the algorithms and models that's being created, we have to think about things being biased, being fair, and understand that this data has impacts on people's lives. - Great. Steve Ardire, my paisan. - Paisan. - AI startup adviser, welcome, thanks for coming to theCUBE. - Thanks Dave. So, uh, my first career was geology, and I view AI as the new oil, but data is the new oil, but AI is the refinery. I've used that many times before. In fact, really, I've moved from just AI to augmented intelligence. So, augmented intelligence is really the way forward. This was a presentation I gave at IBM Think last spring, has almost 100,000 impressions right now, and the fundamental reason why is machines can attend to vastly more information than humans, but you still need humans in the loop, and we can talk about what they're bringing in terms of common sense reasoning, because big data does the who, what, when, and where, but not the why, and why is really the Holy Grail for causal analysis and reasoning. - Excellent, Bob Hayes, Business Over Broadway, welcome, great to see you again. - Thanks for having me. So, my background is in psychology, industrial psychology, and I'm interested in things like customer experience, data science, machine learning, so forth. And I'll answer the question around big data versus AI. And I think there's other terms we could talk about, big data, data science, machine learning, AI. And to me, it's kind of all the same. It's always been about analytics, and getting value from your data, big, small, what have you. And there's subtle differences among those terms. Machine learning is just about making a prediction, and knowing if things are classified correctly. Data science is more about understanding why things work, and understanding maybe the ethics behind it, what variables are predicting that outcome. But still, it's all the same thing, it's all about using data in a way that we can get value from that, as a society, in residences. - Excellent, thank you. Theo Lau, founder of Unconventional Ventures. What's your story? - Yeah, so, my background is driving technology innovation. So, together with my partner, what our work does is we work with organizations to try to help them leverage technology to drive systematic financial wellness. We connect founders, startup founders, with funders, we help them get money in the ecosystem. We also work with them to look at, how do we leverage emerging technology to do something good for the society. So, very much on point to what Bob was saying about. So when I look at AI, it is not new, right, it's been around for quite a while. But what's different is the amount of technological power that we have allow us to do so much more than what we were able to do before. And so, what my mantra is, great ideas can come from anywhere in the society, but it's our job to be able to leverage technology to shine a spotlight on people who can use this to do something different, to help seniors in our country to do better in their financial planning. - Okay, so, in your mind, it's not just a same wine, new bottle, it's more substantive than that. - [Theo] It's more substantive, it's a much better bottle. - Karen Lopez, senior project manager for Architect InfoAdvisors, welcome. - Thank you. So, I'm DataChick on twitter, and so that kind of tells my focus is that I'm here, I also call myself a data evangelist, and that means I'm there at organizations helping stand up for the data, because to me, that's the proxy for standing up for the people, and the places and the events that that data describes. That means I have a focus on security, data privacy and protection as well. And I'm going to kind of combine your two questions about whether data is the new wine bottle, I think is the combination. Oh, see, now I'm talking about alcohol. (laughing) But anyway, you know, all analogies are imperfect, so whether we say it's the new wine, or, you know, same wine, or whether it's oil, is that the analogy's good for both of them, but unlike oil, the amount of data's just growing like crazy, and the oil, we know at some point, I kind of doubt that we're going to hit peak data where we have not enough data, like we're going to do with oil. But that says to me that, how did we get here with big data, with machine learning and AI? And from my point of view, as someone who's been focused on data for 35 years, we have hit this perfect storm of open source technologies, cloud architectures and cloud services, data innovation, that if we didn't have those, we wouldn't be talking about large machine learning and deep learning-type things. So, because we have all these things coming together at the same time, we're now at explosions of data, which means we also have to protect them, and protect the people from doing harm with data, we need to do data for good things, and all of that. - Great, definite differences, we're not running out of data, data's like the terrible tribbles. (laughing) - Yes, but it's very cuddly, data is. - Yeah, cuddly data. Mark Lynd, founder of Relevant Track? - That's right. - I like the name. What's your story? - Well, thank you, and it actually plays into what my interest is. It's mainly around AI in enterprise operations and cyber security. You know, these teams that are in enterprise operations both, it can be sales, marketing, all the way through the organization, as well as cyber security, they're often under-sourced. And they need, what Steve pointed out, they need augmented intelligence, they need to take AI, the big data, all the information they have, and make use of that in a way where they're able to, even though they're under-sourced, make some use and some value for the organization, you know, make better use of the resources they have to grow and support the strategic goals of the organization. And oftentimes, when you get to budgeting, it doesn't really align, you know, you're short people, you're short time, but the data continues to grow, as Karen pointed out. So, when you take those together, using AI to augment, provided augmented intelligence, to help them get through that data, make real tangible decisions based on information versus just raw data, especially around cyber security, which is a big hit right now, is really a great place to be, and there's a lot of stuff going on, and a lot of exciting stuff in that area. - Great, thank you. Kevin L. Jackson, author and founder of GovCloud. GovCloud, that's big. - Yeah, GovCloud Network. Thank you very much for having me on the show. Up and working on cloud computing, initially in the federal government, with the intelligence community, as they adopted cloud computing for a lot of the nation's major missions. And what has happened is now I'm working a lot with commercial organizations and with the security of that data. And I'm going to sort of, on your questions, piggyback on Karen. There was a time when you would get a couple of bottles of wine, and they would come in, and you would savor that wine, and sip it, and it would take a few days to get through it, and you would enjoy it. The problem now is that you don't get a couple of bottles of wine into your house, you get two or three tankers of data. So, it's not that it's a new wine, you're just getting a lot of it. And the infrastructures that you need, before you could have a couple of computers, and a couple of people, now you need cloud, you need automated infrastructures, you need huge capabilities, and artificial intelligence and AI, it's what we can use as the tool on top of these huge infrastructures to drink that, you know. - Fire hose of wine. - Fire hose of wine. (laughs) - Everybody's having a good time. - Everybody's having a great time. (laughs) - Yeah, things are booming right now. Excellent, well, thank you all for those intros. Peter, I want to ask you a question. So, I heard there's some similarities and some definite differences with regard to data being the new oil. You have a perspective on this, and I wonder if you could inject it into the conversation. - Sure, so, the perspective that we take in a lot of conversations, a lot of folks here in theCUBE, what we've learned, and I'll kind of answer both questions a little bit. First off, on the question of data as the new oil, we definitely think that data is the new asset that business is going to be built on, in fact, our perspective is that there really is a difference between business and digital business, and that difference is data as an asset. And if you want to understand data transformation, you understand the degree to which businesses reinstitutionalizing work, reorganizing its people, reestablishing its mission around what you can do with data as an asset. The difference between data and oil is that oil still follows the economics of scarcity. Data is one of those things, you can copy it, you can share it, you can easily corrupt it, you can mess it up, you can do all kinds of awful things with it if you're not careful. And it's that core fundamental proposition that as an asset, when we think about cyber security, we think, in many respects, that is the approach to how we can go about privatizing data so that we can predict who's actually going to be able to appropriate returns on it. So, it's a good analogy, but as you said, it's not entirely perfect, but it's not perfect in a really fundamental way. It's not following the laws of scarcity, and that has an enormous effect. - In other words, I could put oil in my car, or I could put oil in my house, but I can't put the same oil in both. - Can't put it in both places. And now, the issue of the wine, I think it's, we think that it is, in fact, it is a new wine, and very simple abstraction, or generalization we come up with is the issue of agency. That analytics has historically not taken on agency, it hasn't acted on behalf of the brand. AI is going to act on behalf of the brand. Now, you're going to need both of them, you can't separate them. - A lot of implications there in terms of bias. - Absolutely. - In terms of privacy. You have a thought, here, Chris? - Well, the scarcity is our compute power, and our ability for us to process it. I mean, it's the same as oil, there's a ton of oil under the ground, right, we can't get to it as efficiently, or without severe environmental consequences to use it. Yeah, when you use it, it's transformed, but our scarcity is compute power, and our ability to use it intelligently. - Or even when you find it. I have data, I can apply it to six different applications, I have oil, I can apply it to one, and that's going to matter in how we think about work. - But one thing I'd like to add, sort of, you're talking about data as an asset. The issue we're having right now is we're trying to learn how to manage that asset. Artificial intelligence is a way of managing that asset, and that's important if you're going to use and leverage big data. - Yeah, but see, everybody's talking about the quantity, the quantity, it's not always the quantity. You know, we can have just oodles and oodles of data, but if it's not clean data, if it's not alphanumeric data, which is what's needed for machine learning. So, having lots of data is great, but you have to think about the signal versus the noise. So, sometimes you get so much data, you're looking at over-fitting, sometimes you get so much data, you're looking at biases within the data. So, it's not the amount of data, it's the, now that we have all of this data, making sure that we look at relevant data, to make sure we look at clean data. - One more thought, and we have a lot to cover, I want to get inside your big brain. - I was just thinking about it from a cyber security perspective, one of my customers, they were looking at the data that just comes from the perimeter, your firewalls, routers, all of that, and then not even looking internally, just the perimeter alone, and the amount of data being pulled off of those. And then trying to correlate that data so it makes some type of business sense, or they can determine if there's incidents that may happen, and take a predictive action, or threats that might be there because they haven't taken a certain action prior, it's overwhelming to them. So, having AI now, to be able to go through the logs to look at, and there's so many different types of data that come to those logs, but being able to pull that information, as well as looking at end points, and all that, and people's houses, which are an extension of the network oftentimes, it's an amazing amount of data, and they're only looking at a small portion today because they know, there's not enough resources, there's not enough trained people to do all that work. So, AI is doing a wonderful way of doing that. And some of the tools now are starting to mature and be sophisticated enough where they provide that augmented intelligence that Steve talked about earlier. - So, it's complicated. There's infrastructure, there's security, there's a lot of software, there's skills, and on and on. At IBM Think this year, Ginni Rometty talked about, there were a couple of themes, one was augmented intelligence, that was something that was clear. She also talked a lot about privacy, and you own your data, etc. One of the things that struck me was her discussion about incumbent disruptors. So, if you look at the top five companies, roughly, Facebook with fake news has dropped down a little bit, but top five companies in terms of market cap in the US. They're data companies, all right. Apple just hit a trillion, Amazon, Google, etc. How do those incumbents close the gap? Is that concept of incumbent disruptors actually something that is being put into practice? I mean, you guys work with a lot of practitioners. How are they going to close that gap with the data haves, meaning data at their core of their business, versus the data have-nots, it's not that they don't have a lot of data, but it's in silos, it's hard to get to? - Yeah, I got one more thing, so, you know, these companies, and whoever's going to be big next is, you have a digital persona, whether you want it or not. So, if you live in a farm out in the middle of Oklahoma, you still have a digital persona, people are collecting data on you, they're putting profiles of you, and the big companies know about you, and people that first interact with you, they're going to know that you have this digital persona. Personal AI, when AI from these companies could be used simply and easily, from a personal deal, to fill in those gaps, and to have a digital persona that supports your family, your growth, both personal and professional growth, and those type of things, there's a lot of applications for AI on a personal, enterprise, even small business, that have not been done yet, but the data is being collected now. So, you talk about the oil, the oil is being built right now, lots, and lots, and lots of it. It's the applications to use that, and turn that into something personally, professionally, educationally, powerful, that's what's missing. But it's coming. - Thank you, so, I'll add to that, and in answer to your question you raised. So, one example we always used in banking is, if you look at the big banks, right, and then you look at from a consumer perspective, and there's a lot of talk about Amazon being a bank. But the thing is, Amazon doesn't need to be a bank, they provide banking services, from a consumer perspective they don't really care if you're a bank or you're not a bank, but what's different between Amazon and some of the banks is that Amazon, like you say, has a lot of data, and they know how to make use of the data to offer something as relevant that consumers want. Whereas banks, they have a lot of data, but they're all silos, right. So, it's not just a matter of whether or not you have the data, it's also, can you actually access it and make something useful out of it so that you can create something that consumers want? Because otherwise, you're just a pipe. - Totally agree, like, when you look at it from a perspective of, there's a lot of terms out there, digital transformation is thrown out so much, right, and go to cloud, and you migrate to cloud, and you're going to take everything over, but really, when you look at it, and you both touched on it, it's the economics. You have to look at the data from an economics perspective, and how do you make some kind of way to take this data meaningful to your customers, that's going to work effectively for them, that they're going to drive? So, when you look at the big, big cloud providers, I think the push in things that's going to happen in the next few years is there's just going to be a bigger migration to public cloud. So then, between those, they have to differentiate themselves. Obvious is artificial intelligence, in a way that makes it easy to aggregate data from across platforms, to aggregate data from multi-cloud, effectively. To use that data in a meaningful way that's going to drive, not only better decisions for your business, and better outcomes, but drives our opportunities for customers, drives opportunities for employees and how they work. We're at a really interesting point in technology where we get to tell technology what to do. It's going beyond us, it's no longer what we're telling it to do, it's going to go beyond us. So, how we effectively manage that is going to be where we see that data flow, and those big five or big four, really take that to the next level. - Now, one of the things that Ginni Rometty said was, I forget the exact step, but it was like, 80% of the data, is not searchable. Kind of implying that it's sitting somewhere behind a firewall, presumably on somebody's premises. So, it was kind of interesting. You're talking about, certainly, a lot of momentum for public cloud, but at the same time, a lot of data is going to stay where it is. - Yeah, we're assuming that a lot of this data is just sitting there, available and ready, and we look at the desperate, or disparate kind of database situation, where you have 29 databases, and two of them have unique quantifiers that tie together, and the rest of them don't. So, there's nothing that you can do with that data. So, artificial intelligence is just that, it's artificial intelligence, so, they know, that's machine learning, that's natural language, that's classification, there's a lot of different parts of that that are moving, but we also have to have IT, good data infrastructure, master data management, compliance, there's so many moving parts to this, that it's not just about the data anymore. - I want to ask Steve to chime in here, go ahead. - Yeah, so, we also have to change the mentality that it's not just enterprise data. There's data on the web, the biggest thing is Internet of Things, the amount of sensor data will make the current data look like chump change. So, data is moving faster, okay. And this is where the sophistication of machine learning needs to kick in, going from just mostly supervised-learning today, to unsupervised learning. And in order to really get into, as I said, big data, and credible AI does the who, what, where, when, and how, but not the why. And this is really the Holy Grail to crack, and it's actually under a new moniker, it's called explainable AI, because it moves beyond just correlation into root cause analysis. Once we have that, then you have the means to be able to tap into augmented intelligence, where humans are working with the machines. - Karen, please. - Yeah, so, one of the things, like what Carla was saying, and what a lot of us had said, I like to think of the advent of ML technologies and AI are going to help me as a data architect to love my data better, right? So, that includes protecting it, but also, when you say that 80% of the data is unsearchable, it's not just an access problem, it's that no one knows what it was, what the sovereignty was, what the metadata was, what the quality was, or why there's huge anomalies in it. So, my favorite story about this is, in the 1980s, about, I forget the exact number, but like, 8 million children disappeared out of the US in April, at April 15th. And that was when the IRS enacted a rule that, in order to have a dependent, a deduction for a dependent on your tax returns, they had to have a valid social security number, and people who had accidentally miscounted their children and over-claimed them, (laughter) over the years them, stopped doing that. Well, some days it does feel like you have eight children running around. (laughter) - Agreed. - When, when that rule came about, literally, and they're not all children, because they're dependents, but literally millions of children disappeared off the face of the earth in April, but if you were doing analytics, or AI and ML, and you don't know that this anomaly happened, I can imagine in a hundred years, someone is saying some catastrophic event happened in April, 1983. (laughter) And what caused that, was it healthcare? Was it a meteor? Was it the clown attacking them? - That's where I was going. - Right. So, those are really important things that I want to use AI and ML to help me, not only document and capture that stuff, but to provide that information to the people, the data scientists and the analysts that are using the data. - Great story, thank you. Bob, you got a thought? You got the mic, go, jump in here. - Well, yeah, I do have a thought, actually. I was talking about, what Karen was talking about. I think it's really important that, not only that we understand AI, and machine learning, and data science, but that the regular folks and companies understand that, at the basic level. Because those are the people who will ask the questions, or who know what questions to ask of the data. And if they don't have the tools, and the knowledge of how to get access to that data, or even how to pose a question, then that data is going to be less valuable, I think, to companies. And the more that everybody knows about data, even people in congress. Remember when Zuckerberg talked about? (laughter) - That was scary. - How do you make money? It's like, we all know this. But, we need to educate the masses on just basic data analytics. - We could have an hour-long panel on that. - Yeah, absolutely. - Peter, you and I were talking about, we had a couple of questions, sort of, how far can we take artificial intelligence? How far should we? You know, so that brings in to the conversation of ethics, and bias, why don't you pick it up? - Yeah, so, one of the crucial things that we all are implying is that, at some point in time, AI is going to become a feature of the operations of our homes, our businesses. And as these technologies get more powerful, and they diffuse, and know about how to use them, diffuses more broadly, and you put more options into the hands of more people, the question slowly starts to turn from can we do it, to should we do it? And, one of the issues that I introduce is that I think the difference between big data and AI, specifically, is this notion of agency. The AI will act on behalf of, perhaps you, or it will act on behalf of your business. And that conversation is not being had, today. It's being had in arguments between Elon Musk and Mark Zuckerberg, which pretty quickly get pretty boring. (laughing) At the end of the day, the real question is, should this machine, whether in concert with others, or not, be acting on behalf of me, on behalf of my business, or, and when I say on behalf of me, I'm also talking about privacy. Because Facebook is acting on behalf of me, it's not just what's going on in my home. So, the question of, can it be done? A lot of things can be done, and an increasing number of things will be able to be done. We got to start having a conversation about should it be done? - So, humans exhibit tribal behavior, they exhibit bias. Their machine's going to pick that up, go ahead, please. - Yeah, one thing that sort of tag onto agency of artificial intelligence. Every industry, every business is now about identifying information and data sources, and their appropriate sinks, and learning how to draw value out of connecting the sources with the sinks. Artificial intelligence enables you to identify those sources and sinks, and when it gets agency, it will be able to make decisions on your behalf about what data is good, what data means, and who it should be. - What actions are good. - Well, what actions are good. - And what data was used to make those actions. - Absolutely. - And was that the right data, and is there bias of data? And all the way down, all the turtles down. - So, all this, the data pedigree will be driven by the agency of artificial intelligence, and this is a big issue. - It's really fundamental to understand and educate people on, there are four fundamental types of bias, so there's, in machine learning, there's intentional bias, "Hey, we're going to make "the algorithm generate a certain outcome "regardless of what the data says." There's the source of the data itself, historical data that's trained on the models built on flawed data, the model will behave in a flawed way. There's target source, which is, for example, we know that if you pull data from a certain social network, that network itself has an inherent bias. No matter how representative you try to make the data, it's still going to have flaws in it. Or, if you pull healthcare data about, for example, African-Americans from the US healthcare system, because of societal biases, that data will always be flawed. And then there's tool bias, there's limitations to what the tools can do, and so we will intentionally exclude some kinds of data, or not use it because we don't know how to, our tools are not able to, and if we don't teach people what those biases are, they won't know to look for them, and I know. - Yeah, it's like, one of the things that we were talking about before, I mean, artificial intelligence is not going to just create itself, it's lines of code, it's input, and it spits out output. So, if it learns from these learning sets, we don't want AI to become another buzzword. We don't want everybody to be an "AR guru" that has no idea what AI is. It takes months, and months, and months for these machines to learn. These learning sets are so very important, because that input is how this machine, think of it as your child, and that's basically the way artificial intelligence is learning, like your child. You're feeding it these learning sets, and then eventually it will make its own decisions. So, we know from some of us having children that you teach them the best that you can, but then later on, when they're doing their own thing, they're really, it's like a little myna bird, they've heard everything that you've said. (laughing) Not only the things that you said to them directly, but the things that you said indirectly. - Well, there are some very good AI researchers that might disagree with that metaphor, exactly. (laughing) But, having said that, what I think is very interesting about this conversation is that this notion of bias, one of the things that fascinates me about where AI goes, are we going to find a situation where tribalism more deeply infects business? Because we know that human beings do not seek out the best information, they seek out information that reinforces their beliefs. And that happens in business today. My line of business versus your line of business, engineering versus sales, that happens today, but it happens at a planning level, and when we start talking about AI, we have to put the appropriate dampers, understand the biases, so that we don't end up with deep tribalism inside of business. Because AI could have the deleterious effect that it actually starts ripping apart organizations. - Well, input is data, and then the output is, could be a lot of things. - Could be a lot of things. - And that's where I said data equals human lives. So that we look at the case in New York where the penal system was using this artificial intelligence to make choices on people that were released from prison, and they saw that that was a miserable failure, because that people that release actually re-offended, some committed murder and other things. So, I mean, it's, it's more than what anybody really thinks. It's not just, oh, well, we'll just train the machines, and a couple of weeks later they're good, we never have to touch them again. These things have to be continuously tweaked. So, just because you built an algorithm or a model doesn't mean you're done. You got to go back later, and continue to tweak these models. - Mark, you got the mic. - Yeah, no, I think one thing we've talked a lot about the data that's collected, but what about the data that's not collected? Incomplete profiles, incomplete datasets, that's a form of bias, and sometimes that's the worst. Because they'll fill that in, right, and then you can get some bias, but there's also a real issue for that around cyber security. Logs are not always complete, things are not always done, and when things are doing that, people make assumptions based on what they've collected, not what they didn't collect. So, when they're looking at this, and they're using the AI on it, that's only on the data collected, not on that that wasn't collected. So, if something is down for a little while, and no data's collected off that, the assumption is, well, it was down, or it was impacted, or there was a breach, or whatever, it could be any of those. So, you got to, there's still this human need, there's still the need for humans to look at the data and realize that there is the bias in there, there is, we're just looking at what data was collected, and you're going to have to make your own thoughts around that, and assumptions on how to actually use that data before you go make those decisions that can impact lots of people, at a human level, enterprise's profitability, things like that. And too often, people think of AI, when it comes out of there, that's the word. Well, it's not the word. - Can I ask a question about this? - Please. - Does that mean that we shouldn't act? - It does not. - Okay. - So, where's the fine line? - Yeah, I think. - Going back to this notion of can we do it, or should we do it? Should we act? - Yeah, I think you should do it, but you should use it for what it is. It's augmenting, it's helping you, assisting you to make a valued or good decision. And hopefully it's a better decision than you would've made without it. - I think it's great, I think also, your answer's right too, that you have to iterate faster, and faster, and faster, and discover sources of information, or sources of data that you're not currently using, and, that's why this thing starts getting really important. - I think you touch on a really good point about, should you or shouldn't you? You look at Google, and you look at the data that they've been using, and some of that out there, from a digital twin perspective, is not being approved, or not authorized, and even once they've made changes, it's still floating around out there. Where do you know where it is? So, there's this dilemma of, how do you have a digital twin that you want to have, and is going to work for you, and is going to do things for you to make your life easier, to do these things, mundane tasks, whatever? But how do you also control it to do things you don't want it to do? - Ad-based business models are inherently evil. (laughing) - Well, there's incentives to appropriate our data, and so, are things like blockchain potentially going to give users the ability to control their data? We'll see. - No, I, I'm sorry, but that's actually a really important point. The idea of consensus algorithms, whether it's blockchain or not, blockchain includes games, and something along those lines, whether it's Byzantine fault tolerance, or whether it's Paxos, consensus-based algorithms are going to be really, really important. Parts of this conversation, because the data's going to be more distributed, and you're going to have more elements participating in it. And so, something that allows, especially in the machine-to-machine world, which is a lot of what we're talking about right here, you may not have blockchain, because there's no need for a sense of incentive, which is what blockchain can help provide. - And there's no middleman. - And, well, all right, but there's really, the thing that makes blockchain so powerful is it liberates new classes of applications. But for a lot of the stuff that we're talking about, you can use a very powerful consensus algorithm without having a game side, and do some really amazing things at scale. - So, looking at blockchain, that's a great thing to bring up, right. I think what's inherently wrong with the way we do things today, and the whole overall design of technology, whether it be on-prem, or off-prem, is both the lock and key is behind the same wall. Whether that wall is in a cloud, or behind a firewall. So, really, when there is an audit, or when there is a forensics, it always comes down to a sysadmin, or something else, and the system administrator will have the finger pointed at them, because it all resides, you can edit it, you can augment it, or you can do things with it that you can't really determine. Now, take, as an example, blockchain, where you've got really the source of truth. Now you can take and have the lock in one place, and the key in another place. So that's certainly going to be interesting to see how that unfolds. - So, one of the things, it's good that, we've hit a lot of buzzwords, right now, right? (laughing) AI, and ML, block. - Bingo. - We got the blockchain bingo, yeah, yeah. So, one of the things is, you also brought up, I mean, ethics and everything, and one of the things that I've noticed over the last year or so is that, as I attend briefings or demos, everyone is now claiming that their product is AI or ML-enabled, or blockchain-enabled. And when you try to get answers to the questions, what you really find out is that some things are being pushed as, because they have if-then statements somewhere in their code, and therefore that's artificial intelligence or machine learning. - [Peter] At least it's not "go-to." (laughing) - Yeah, you're that experienced as well. (laughing) So, I mean, this is part of the thing you try to do as a practitioner, as an analyst, as an influencer, is trying to, you know, the hype of it all. And recently, I attended one where they said they use blockchain, and I couldn't figure it out, and it turns out they use GUIDs to identify things, and that's not blockchain, it's an identifier. (laughing) So, one of the ethics things that I think we, as an enterprise community, have to deal with, is the over-promising of AI, and ML, and deep learning, and recognition. It's not, I don't really consider it visual recognition services if they just look for red pixels. I mean, that's not quite the same thing. Yet, this is also making things much harder for your average CIO, or worse, CFO, to understand whether they're getting any value from these technologies. - Old bottle. - Old bottle, right. - And I wonder if the data companies, like that you talked about, or the top five, I'm more concerned about their nearly, or actual $1 trillion valuations having an impact on their ability of other companies to disrupt or enter into the field more so than their data technologies. Again, we're coming to another perfect storm of the companies that have data as their asset, even though it's still not on their financial statements, which is another indicator whether it's really an asset, is that, do we need to think about the terms of AI, about whose hands it's in, and who's, like, once one large trillion-dollar company decides that you are not a profitable company, how many other companies are going to buy that data and make that decision about you? - Well, and for the first time in business history, I think, this is true, we're seeing, because of digital, because it's data, you're seeing tech companies traverse industries, get into, whether it's content, or music, or publishing, or groceries, and that's powerful, and that's awful scary. - If you're a manger, one of the things your ownership is asking you to do is to reduce asset specificities, so that their capital could be applied to more productive uses. Data reduces asset specificities. It brings into question the whole notion of vertical industry. You're absolutely right. But you know, one quick question I got for you, playing off of this is, again, it goes back to this notion of can we do it, and should we do it? I find it interesting, if you look at those top five, all data companies, but all of them are very different business models, or they can classify the two different business models. Apple is transactional, Microsoft is transactional, Google is ad-based, Facebook is ad-based, before the fake news stuff. Amazon's kind of playing it both sides. - Yeah, they're kind of all on a collision course though, aren't they? - But, well, that's what's going to be interesting. I think, at some point in time, the "can we do it, should we do it" question is, brands are going to be identified by whether or not they have gone through that process of thinking about, should we do it, and say no. Apple is clearly, for example, incorporating that into their brand. - Well, Silicon Valley, broadly defined, if I include Seattle, and maybe Armlock, not so much IBM. But they've got a dual disruption agenda, they've always disrupted horizontal tech. Now they're disrupting vertical industries. - I was actually just going to pick up on what she was talking about, we were talking about buzzword, right. So, one we haven't heard yet is voice. Voice is another big buzzword right now, when you couple that with IoT and AI, here you go, bingo, do I got three points? (laughing) Voice recognition, voice technology, so all of the smart speakers, if you think about that in the world, there are 7,000 languages being spoken, but yet if you look at Google Home, you look at Siri, you look at any of the devices, I would challenge you, it would have a lot of problem understanding my accent, and even when my British accent creeps out, or it would have trouble understanding seniors, because the way they talk, it's very different than a typical 25-year-old person living in Silicon Valley, right. So, how do we solve that, especially going forward? We're seeing voice technology is going to be so more prominent in our homes, we're going to have it in the cars, we have it in the kitchen, it does everything, it listens to everything that we are talking about, not talking about, and records it. And to your point, is it going to start making decisions on our behalf, but then my question is, how much does it actually understand us? - So, I just want one short story. Siri can't translate a word that I ask it to translate into French, because my phone's set to Canadian English, and that's not supported. So I live in a bilingual French English country, and it can't translate. - But what this is really bringing up is if you look at society, and culture, what's legal, what's ethical, changes across the years. What was right 200 years ago is not right now, and what was right 50 years ago is not right now. - It changes across countries. - It changes across countries, it changes across regions. So, what does this mean when our AI has agency? How do we make ethical AI if we don't even know how to manage the change of what's right and what's wrong in human society? - One of the most important questions we have to worry about, right? - Absolutely. - But it also says one more thing, just before we go on. It also says that the issue of economies of scale, in the cloud. - Yes. - Are going to be strongly impacted, not just by how big you can build your data centers, but some of those regulatory issues that are going to influence strongly what constitutes good experience, good law, good acting on my behalf, agency. - And one thing that's underappreciated in the marketplace right now is the impact of data sovereignty, if you get back to data, countries are now recognizing the importance of managing that data, and they're implementing data sovereignty rules. Everyone talks about California issuing a new law that's aligned with GDPR, and you know what that meant. There are 30 other states in the United States alone that are modifying their laws to address this issue. - Steve. - So, um, so, we got a number of years, no matter what Ray Kurzweil says, until we get to artificial general intelligence. - The singularity's not so near? (laughing) - You know that he's changed the date over the last 10 years. - I did know it. - Quite a bit. And I don't even prognosticate where it's going to be. But really, where we're at right now, I keep coming back to, is that's why augmented intelligence is really going to be the new rage, humans working with machines. One of the hot topics, and the reason I chose to speak about it is, is the future of work. I don't care if you're a millennial, mid-career, or a baby boomer, people are paranoid. As machines get smarter, if your job is routine cognitive, yes, you have a higher propensity to be automated. So, this really shifts a number of things. A, you have to be a lifelong learner, you've got to learn new skillsets. And the dynamics are changing fast. Now, this is also a great equalizer for emerging startups, and even in SMBs. As the AI improves, they can become more nimble. So back to your point regarding colossal trillion dollar, wait a second, there's going to be quite a sea change going on right now, and regarding demographics, in 2020, millennials take over as the majority of the workforce, by 2025 it's 75%. - Great news. (laughing) - As a baby boomer, I try my damnedest to stay relevant. - Yeah, surround yourself with millennials is the takeaway there. - Or retire. (laughs) - Not yet. - One thing I think, this goes back to what Karen was saying, if you want a basic standard to put around the stuff, look at the old ISO 38500 framework. Business strategy, technology strategy. You have risk, compliance, change management, operations, and most importantly, the balance sheet in the financials. AI and what Tony was saying, digital transformation, if it's of meaning, it belongs on a balance sheet, and should factor into how you value your company. All the cyber security, and all of the compliance, and all of the regulation, is all stuff, this framework exists, so look it up, and every time you start some kind of new machine learning project, or data sense project, say, have we checked the box on each of these standards that's within this machine? And if you haven't, maybe slow down and do your homework. - To see a day when data is going to be valued on the balance sheet. - It is. - It's already valued as part of the current, but it's good will. - Certainly market value, as we were just talking about. - Well, we're talking about all of the companies that have opted in, right. There's tens of thousands of small businesses just in this region alone that are opt-out. They're small family businesses, or businesses that really aren't even technology-aware. But data's being collected about them, it's being on Yelp, they're being rated, they're being reviewed, the success to their business is out of their hands. And I think what's really going to be interesting is, you look at the big data, you look at AI, you look at things like that, blockchain may even be a potential for some of that, because of mutability, but it's when all of those businesses, when the technology becomes a cost, it's cost-prohibitive now, for a lot of them, or they just don't want to do it, and they're proudly opt-out. In fact, we talked about that last night at dinner. But when they opt-in, the company that can do that, and can reach out to them in a way that is economically feasible, and bring them back in, where they control their data, where they control their information, and they do it in such a way where it helps them build their business, and it may be a generational business that's been passed on. Those kind of things are going to make a big impact, not only on the cloud, but the data being stored in the cloud, the AI, the applications that you talked about earlier, we talked about that. And that's where this bias, and some of these other things are going to have a tremendous impact if they're not dealt with now, at least ethically. - Well, I feel like we just got started, we're out of time. Time for a couple more comments, and then officially we have to wrap up. - Yeah, I had one thing to say, I mean, really, Henry Ford, and the creation of the automobile, back in the early 1900s, changed everything, because now we're no longer stuck in the country, we can get away from our parents, we can date without grandma and grandpa setting on the porch with us. (laughing) We can take long trips, so now we're looked at, we've sprawled out, we're not all living in the country anymore, and it changed America. So, AI has that same capabilities, it will automate mundane routine tasks that nobody wanted to do anyway. So, a lot of that will change things, but it's not going to be any different than the way things changed in the early 1900s. - It's like you were saying, constant reinvention. - I think that's a great point, let me make one observation on that. Every period of significant industrial change was preceded by the formation, a period of formation of new assets that nobody knew what to do with. Whether it was, what do we do, you know, industrial manufacturing, it was row houses with long shafts tied to an engine that was coal-fired, and drove a bunch of looms. Same thing, railroads, large factories for Henry Ford, before he figured out how to do an information-based notion of mass production. This is the period of asset formation for the next generation of social structures. - Those ship-makers are going to be all over these cars, I mean, you're going to have augmented reality right there, on your windshield. - Karen, bring it home. Give us the drop-the-mic moment. (laughing) - No pressure. - Your AV guys are not happy with that. So, I think the, it all comes down to, it's a people problem, a challenge, let's say that. The whole AI ML thing, people, it's a legal compliance thing. Enterprises are going to struggle with trying to meet five billion different types of compliance rules around data and its uses, about enforcement, because ROI is going to make risk of incarceration as well as return on investment, and we'll have to manage both of those. I think businesses are struggling with a lot of this complexity, and you just opened a whole bunch of questions that we didn't really have solid, "Oh, you can fix it by doing this." So, it's important that we think of this new world of data focus, data-driven, everything like that, is that the entire IT and business community needs to realize that focusing on data means we have to change how we do things and how we think about it, but we also have some of the same old challenges there. - Well, I have a feeling we're going to be talking about this for quite some time. What a great way to wrap up CUBE NYC here, our third day of activities down here at 37 Pillars, or Mercantile 37. Thank you all so much for joining us today. - Thank you. - Really, wonderful insights, really appreciate it, now, all this content is going to be available on theCUBE.net. We are exposing our video cloud, and our video search engine, so you'll be able to search our entire corpus of data. I can't wait to start searching and clipping up this session. Again, thank you so much, and thank you for watching. We'll see you next time.

New Orleans Louisiana it that you covering dot next conference 2018 brought to you by Nutanix welcome back to the cubes coverage here of Nutanix next 2018 here in New Orleans Louisiana the brass bands are going talking to lots of customers been a great event so far and for Keith Townsend and I'm Stu minimun we always love to be able to talk to customers each one of them has a different story different analysis different challenges they're facing happened to welcome Alex Walker who's the senior vice president of IT at IBC Bank out of Texas thanks so much for joining us thank you alright so you've actually been going to all the shows just like I have at this Keys first one who's been getting getting the inaugural visit here but first of all tell us about yourself a little bit of background what you run at the bank and just give us quick sketch of the bank oh let's start with the bank you know we're in our 51st year we are based in Laredo Texas and it's a community bank mostly and commercial right you know where we are 19th according to Forbes magazine best banks in the country so we went up from 46 to 19 this year Congrats and so great accomplishments for the bank itself it's a great operation we're in 88 cities in the in Texas and Oklahoma and about 13 billion in assets great and what's under your purview as the SPID okay so you an all IT for the bank I'm not this not the development side of it you know without the operations infrastructure yes okay 51 year old company finance going through a lot of changes before we get in to the tech just give us one or two some of those the stresses and strains that you're feeling is business well regulation is one right over the last several years the increasing regulation has caused a tremendous growth in our auditing Keith Kountz rates at Department and a lot of cost to the bank I started about three and a half years ago and the bank was looking at how do we prepare for a change right potentially hoping for some change in them in the regulatory climate and so forth but we needed to prepare for that and prepare for growth so we we need to take a look at our infrastructure of everything across the board yeah maybe could organizationally where does that pension for change come from what kind of air cover do you get from from News exercise what's of the staff underneath you know how do they take change well initially there was a lot of reluctance right people were in the status quo they're comfortable with what they had not necessarily happy with it but taking on change is it's difficult right so we looked at operational costs some of the basic things we had two data centers at the time literally a hundred and fifty yards apart from each other so we said we can do we can do more right the bank's motto is we do more and so we said how do we do more for the bank for their customers improve the quality of the services the uptime and so and and reduce its cost so it's your bank so change in a bank a lot of times means going from one store to reef vendor to another storage or a vendor and that's a big deal big set of conversations you know your your your you know it we are sitting at the 19th best bank and then the fourteenth you don't get there by turning over the table part called the table you your get you get there by being steady what made you guys actually consider something as revolutionary as HCI when it came to change well when we looked at the infrastructure that we had and you know it goes back to simon Sinek start with quiet right why are we doing this I asked I asked the my department when I first started who are our competitors and they gave us the names of all the local banks and so forth and the usual suspects the large banks and I said no they're not that's the bank's customers our competitors are AWS Rackspace Microsoft is your Google Cloud it's the these are the hosting companies we host applications for our customers we're shared services for our bank once we understand who we are then we have to take a different approach because now if we're competing with them it's no wonder that the bank is starting to branch out and do their own thing right some unit I'm getting contracts with the cloud providers or with other service providers because we're too far behind we're not cost-effective we're not competitive so it doesn't mean that we want to build massive data centers everywhere but we need to have the same level of services that they provide so from a validation perspective it you start to look at the cost of hyper-converged in general I'm sorry how long you guys have been a new tennis customer three years okay so from a cost perspective as you start to look at hyper-converged how did you even begin to compare it to your existing environment well I looked I looked at the the studies that are out there particular there was an IDC study done member on 2015 that said that customers of like size all different types of customers we're getting these these benefits I said wow if I could get those that'd be really cool right so I went to the board I went to my boss the CIO and I said I think we could get this this would be a really good but then again people said we never heard of mechanics what is this our applications aren't certified with Nutanix you know so let's talk about procurements and I said well let's just do a PLC and that's bringing this in and and we'll run VMware on it which is what we were certified at the time our applications and I said let's let's look at this infrastructure this we brought in the PLC but what we did is we took Nutanix and had them talk directly to my accounting the bank's accounting department right we all know we all work for accountants eventually and so we said if we can get them to agree that if we can get these then they're gonna be behind us from the are white and TCO models right so we went through and said what are we paying for this what are we paying for that what's the hyung going rates for this let's get some samples of if we ordered this and replace it we had eleven storage frames from seven different vendors or we couldn't move data around from one storage frame to another because we had over time acquired a lot of different frames and like most places never retired them right and so all that layer of complexity what we did is we said this on this PLC let's test this out okay cut to the chase we we got the we got the numbers we were then three or two 5% of everything that came out in that study and so we bought that that that equipment immediately placed our first order which was 12 notes still want to keep it constrained so one of food in the water but I said this is a technology I'm betting on five years we'll write it off in five years we can get rid of it and move on to the next thing what happened was we were getting so such good wins we actually completed in our five-year model we completed that in roughly around two years because the acceleration based upon the benefits that we got some of the requirements that we had for change within the organization replace all equipment and so forth we were able to to accelerate that not only that we just finished upgrading our D our site which was not part of that five-year plan and just completed that and so within three years we've now are our 97% on Nutanix and we just took delivery of 24 of the Robo nodes which we're going to put out in our branch operations that'll leave us with five servers that are not Nutanix other than our for AIX system yeah Alex can you tell us what what were the key metrics that you were looking at to measure success and you did some TCO studies you actually presented here at the conference what do you recommend to your peers as to how they should be able to evaluate rolling out something like this well for one and a big one was licensing right it's far more efficient what we got for example we got we were able to take our Fibre Channel switches running about quarter of a million plus each and and get rid of those would we when we look at it the bandwidth that that's taken on the servers it's writing data to storage going through this storage controller going into this the sand and coming back that delay was substantial so much so that when we moved all of our databases into Nutanix and eliminated that infrastructure we're running 66% faster than we did on current technology on a conventional architecture did what was the business response on this did it change anything in the business what did the users say well when they'd users Jobs ran far faster than they did before when we went back and said I don't need as many Microsoft sequel licenses as they did before for consolidation fewer cores the tremendous benefits our sequel developed our sequel management team for example it takes far less time to stand up servers do migrations things like that so what's the Delta between the prediction debrief their predicted ROI and the realized our ROI you guys realize your savings much quicker wolves worldwide little surprises well the surprises were we were conservative we didn't include any soft costs those are difficult to we missed it me Steve Kaplan are all are all I got a TCO guy for Nutanix go back and forth on the soft cost don't show weak soft cost show me where I can give the money back to my accountants who we all have to report to correct right yeah so what we found is the fact that we were conservative we were getting much better benefits so again when we look at the servers we bought too many cores right so now I this good problem now I can migrate more systems I did anticipate based upon that spin so the time the technology to the financial benefits the reduction and latency allows you to stop spending money on more cores that you didn't need less latency equals better performance better performance tools more dense newness Lourdes units means less money spent so we we actually shut down one of the data centers and migrated into a single data center and it's we're running somewhere around up third a little bit more than a third of that data center so the electrical expend is down in aggregate roughly around 40% so that's real money okay you mentioned that you're also using Nutanix for disaster recovery tell us what led to that that's a newer solution from Nutanix how that experience go we're using the note annex replication for that and when we our legacy was that some of them were taped and some of it was you know migrating data you know a typical older dr type of situation we're in our testing now and that's a little bit complex because we have to protect that dr site from production but we're mirroring the the systems exactly as they are in production so when you spin it up its life right so we have to build a barrier between those systems so if we take that even then taking that into account we can get it up in hours rather than and when we say hours like a couple of hours rather than the 22 12 to 24 hours that we were before and it's 10 systems not 4 systems so roughly about a hundred servers or so minimally all right Alex look forward a little bit tell us what's on your roadmap what kind of things you're doing and if there's intersections with titanic's there we're looking at VDI for example something that we now that we've reengineering our network as well that we're looking at doing that for branch operations and security right but looking forward into AI and and blockchain and which is going to be very disruptive for financial institutions okay you mentioned blockchain so definitely need to get get your take as to what can you share either personally or from the Bakke standpoint cryptocurrency of course will I and I do pay taxes on it but realistically I'm mining with you know for video carts it's it's not it's really understand from as a chief technologist I'm I really need to understand these things you don't make appendix fluster off on the side I did ask her I could have the old data center and the when we're doing I'm doing that really effectively to better understand that but I think what we're looking at it blockchain is tremendous opportunities for many improvements in security and loss prevention and other types of things within the financial side I'm seeing a lot of big financial institutions that are getting filing for patents on block chains and they're they're bringing it up in their ten cases potentially very disruptive and very expensive and some of them are saying specifically cryptocurrency and blockchain and some of them are saying new you know new competition in the market right so we take that to kind of mean that they're they're thinking about the same things we are so keep a eye on to the future especially when it comes to something like blockchain this relatively inefficient at processing transactions how does that impact your data center strategy you guys just went down from you know huge space reduced electrical power by 40% any considerations around kind of the blood blockchain at a commercial level of use within the bank and how it might impact your strategy we're a conservative bank so would we we're having discussions about what what does that mean right what it were do we think that's might come in and it's very early for us right we've been busy you know the datacenter moves and other types of things too so we're starting to look at that and have some a few conversations about what do we think it it is we're talking to some of our our business partners and say how might we cooperate with you guys to do excuse me to use some of this blockchain technology it's a it's a different way of doing it you know when in the past we might use relational databases like sequel server or something to do something some of this work where distributed ledger might be a far easier better way to do that so it's another tool I like to say that you know video didn't kill the radiostar right yeah there's more type of radio out there than there ever was so this is another tool that we have to look and say well how does this how do we utilize this what with the right technology for the right job and we're being very cautious about that all right well Alex Walker really appreciate you sharing all the updates on IBC Bank pleasure to catch up with you and look forward to seeing you more than ten echoes in the future for Keith Townsend Thomas do minimun more coverage here at Nutanix duck necks New Orleans thanks for watching the queue [Music]

(upbeat music) >> Announcer: Live from Las Vegas it's theCube covering AWS re:Invent 2017 presented by AWS, Intel and our ecosystem of partners. >> Well welcome back here on theCube we are live at re:Invent, AWS's big show, and I mean big show here in Las Vegas spanning some four hotels hundreds of thousands of exhibit space and nearly 50,000 attendees gonna be a great 3 days and we're glad you're with us here on theCube. I'm John Walls, along with Lisa Martin again, glad to have you here and we're now joined by Paul Beavers who is VP of products he specializes on the RND and the product management side of the house of BMC and Paul, glad to have you with us. Say, A Cube first-timer, right? >> Yes I am, nice to meet you, glad to be here. >> John: Well go easy on ya. >> Okay, good. >> John: And a Bronco >> Yeah >> John: UCO, Central Oklahoma >> Yes, absolutely >> I'm an old Tulsa guy >> Oh, are you? >> So I know a lot about UCO My wife's a UT grad >> Alright good, we'll keep it all in the house here First, tell us about BMC first, company's been around for nearly, what, almost some 40 years, so you've gone through multiple iterations, so how'd you get to the point to where you are now and what are you doing now? >> You know, the way that I like to think about BMC is while the technology, the underlying technology has changed a lot over the years we started off with our roots in mainframe. We supported many different Unix platforms, Linux platforms different types of databases, but the one thing that has always been the same is, BMC had one overarching goal which is to help our customers succeed with IT, regardless of what the platform is. So as the industry is transitioned, I've been in the industry about 30 years and over the last 30 years as the industry's transitioned it, there has always been a need for our large enterprises, insurance companies, finance companies to be successful with their IT. And there's always a gap to be filed around making IT better and making IT functional making it perform and most importantly making sure that it's supporting the business and the business is continuing. >> And that kind of previews a question that I wanted to ask you, is as you've seen massive technology shifts since 1981, what are some of the trends that you are seeing that the business is really leading with? The business outcomes that IT has to facilitate. >> I think the, obviously there's been lots of different transitions in the business and the technology over the years since 81. I think the last five years have been the most pivotal. And the reason is because, not because there is a change in deity or the technology but because of all of the different technology and opportunities that are out there, businesses are now leveraging IT to be the business as opposed to support the business. Right, so if you take things like Uber, Netflix, Airbnb even banks today, the IT is the business, right. So if you think back about five or ten years ago, IT, a mobile app for the bank was a convenience now if you're a member of a bank and the mobile app doesn't work, you're gonna find a new bank. That's all there is to it, it is now critical. It's what digital transformation really means, it's not a buzzword, it's real and all the businesses that surround us we're at Amazon's event, right, Amazon, one of the most, the biggest digital businesses there is. All of those businesses have a new dependency on, on IT. So that change has created opportunities for companies like BMC to ensure that IT works because then we ensure that the digital businesses are working. >> And you say, you know, not a buzz word, a reality but yet there's still a lot of people on the other side of that fence, right, and they haven't made that transformation yet or they're in the process, that's what you're all about right, facilitating that, so what do you, talking to those who may be a little bit of a foot dragger, you might say, and they've got to make some different decisions now, so how do you, how are you coaxing those folks along and what's your primary messaging on that? >> There's kind of two different aspects on that. So one is from a business perspective we really want to see, if they don't digitally transform, they won't exist in five years. And I think they know that, so, I think the situation's becoming more and more dire or urgent for them. One of the things that has helped them is things like AWS, Amazon web services, in the cloud, makes it much easier to digitally transform, right. Because it's so readily available and actually there's whole businesses that are growing up on AWS. So what we do at BMC is help those customers that are the edge, they're about to make a decision around cloud. We help them ensure that they're going to be okay when they go to the cloud, right. An example would be, we've been with them now, some of these companies, large insurance company in the Midwest, we've been with them for 30 years as customer and we're still going to be there and we're still going to help them on their cloud journey. And that story gets repeated time and time again across our customer base. >> Lisa: One of the interesting things that was in the news, John Furrier wrote a great article that was published on Forbes the other day. He did an exclusive interview with Andy Jassy, the CEO of AWS, who talked about the, AWS 18 billion dollar run rate 42% growth a year, he said, you know, we haven't here by working with startups alone. We're at the precipices of this mass enterprise migration. You guys have been a partner with AWS for a while you're an ISV, what are some of the new things that you really hear at AWS re:Invent to reinforce with respect to your strategic partnership with AWS? >> You know, when, I can break that down into kinda three simple, three simple ways, right. So when you think about a cloud migration customers are typically looking, looking to do three different things, right, they're either looking to save money by lifting and shifting existing workloads and putting them into the cloud. And Amazon, that's a sweet spot for them they've been doing that for a while. But, that's kind of the entry level what we're seeing is leveraging the native services that AWS provides, not only make it cheaper for the customer but it makes it, it makes it much faster to develop apps and to succeed with digital transformation. Matter of fact, the application development within enterprises are now becoming more integrators of different cloud services and technologies as opposed to building applications from scratch. So it becomes an arms race, if you will, for the different vendors, right, the first bank to get to a mobile app, the first insurance company to do everything online. All of these different needs and capibilites around digital transformation AWS facilitates that. And they do it, they do it, they have some competition, but they're really leading, they're really leading the path. >> And in speaking of that leadership that we, I was talking about their growth rate earlier and they are in the clear lead. And they have a very consistent message coming from Andy Jassy, we're not lookin in the rear view mirror. I'm curious, you've mentioned application development a minute ago, how are, how's your conversation with in organizations, whether it's a bank or an insurance company, AWS has done a great job of attracting developers. Are you seeing the shift, in terms of your conversations, up the chain of command to the CEO, the corporate board? >> I'll answer that in two different ways. So, first of all, if you think about IT operations, right, so IT operations are the guys within these enterprises that typically make sure that IT runs. It's all about monitoring and provisioning, the work that to make IT run. That is BMC's sweet spot. And what you find in these companies is they get, they start small with a cloud strategy and then at some point they reach critical mass and the CEOs and the CIOs get nervous about okay, what if the cloud breaks, right? And so they want to manage that with the rigor and disipline that they manage typical IT operations. That's a real sweet spot for BMC. Because we can manage AWS and monitor all the applications running AWS and give those CEOs and CIOs and CFOs the comfort that their applications are going to be there when they need to, and as we already said earlier, those applications now are their businesses so the cost of an outage is way more significant that it was even five years ago. >> John: You mentioned, you know, four, five year trend this has been going on for little bit now. So just as capabilities have changed, I'm sure the questions coming in are changing too, right? So what's kind of leap frog to the head of the pack in terms of when people come to you and say, hey, I need help, but this is what's worrying me today as opposed to what was answered yesterday. >> You know, the way that I would answer that is scalability, right, so when applications go outside the enterprise, out into the consumer world, right, everybody's got the app on their mobile phone, you go from tens of thousands of users to millions of users. And so the performance metrics and the data that you generate goes into very, very large amounts of data. In order to understand performance, you have to have a new technique. And so understanding performance in modern times is really the problem at hand and that's where you start to hear about things like, big data and the ability to store petabytes of data and the ability to search and analyze that data very quickly. Leveraging machine learning and analytics that's where the big need is today. And that's where companies like BMC are rotating to be able to support that massive scale, that volume of information. Because it's no longer about a thousand users of an internal app it's about, I've got a loyal, we were talking to a grocery store the other day, they have a loyalty app with two and a half million users and by the way, if the loyalty app doesn't work they go to a different grocery store. So it's a completely different model but it's really, I would say the number one concern right now is the scale and second to that is, in order to achieve scale enterprises are leveraging much more modern technology both in the cloud and on the premises but that modern technology, you have to be able to monitor and understand the performance of that modern technology. >> One more question for you Paul. What are you most excited to hear from AWS this week? We've seen a couple of announcements that hit the wire Monday morning at midnight about AI for example. What are some of the things that you and BMC are excited to hear from your partner AWS? >> You know, I actually today, I was in the partner, key note summit. I'm excited about the way that AWS is rotating from a DevOps motion to enterprise. So they announced this week that there's actually going to be the ability for ISV's like BMC to sell product in the AWS marketplace but do it in a way that you can price it and consume it as an enterprise. So they're literally, that's actually news to me at this event, is that they're really uplifting this approach around sort of smaller groups and targeting big enterprises and for us at BMC selfishly, giving us the ability to deliver on AWS to very, very large enterprises which is our customer base, we support the global 2000. >> John: That's why you're licking your chops this week >> Exactly, absolutely Absolutely (John laughs) >> Paul, thanks for the time >> No problem, thank you >> Glad to have you on theCube and look forward to the next time down the road too. >> Paul: Absolutely, anytime. >> John: Alright, Paul Beavers, joining us from BMC >> Very nice to meet both of you >> Back with more, we're here at re:Invent we're live in Las Vegas and you are watching our coverage here on theCube. (upbeat music)

>> Announcer: Live, from Orlando, Florida, it's the Cube covering Grace Hopper's celebration of women in computing brought to you by Silicon Angle Media >> Welcome back to the Cube's coverage of the Grace Hopper conference here in Orlando, Florida I'm your host Rebecca Knight, along with my co host Jeff Frick. We're joined by Megan Smith. We're very excited to have you on the show. >> It's good to be here >> She is the third US CTO and also the CEO of a new company, Shift7.co, so thanks so much for joining us. >> Thanks for having me, it's great to be here. It's so fun to be at Hopper, >> Rebecca: It is, it is! >> It's cool, it's the Grace Hopper celebration, because we're trying to celebrate women in computing, and we're what, at 18 thousand people now, >> The biggest ever, >> Plus I think, 6 thousand people joining on the livestream, which is great. >> Before the cameras were rolling, we were talking about your role as the 3rd US CTO, and just talking about getting more technology into government to help leaders work together, and move faster. Tell us a little about this initiative. >> What's so great, is it's not partisan, fixing the government and making it work better, so all the work that we were doing continues. What we were able to put in place, during the Obama administration, and continues to Trump, were things like, the CT office. Having technical people, so I worked at Google, people work at Amazon, Facebook, Twitter, these companies who have that background, to join in on policy conversations, one, to join in on capacity building the government, so data sciences and tech and, let's have our services be as great as Amazon, or as Twitter, or Oracle, and not be sort of retro, really serve the American people. And then also, helping the American people in general, with capacity building, things like computer science for all. So that was an initiative that continues to get all of our children to have coding at school. That all children, you couldn't graduate from high school without having had some experience on learning of coding Coding is a 21st century fluency, it's a skill we all need, Like freshman biology. You want to know some biology, you want to know some coding, you want to know how to write, so making sure they have is tech-up, which was a program we started to help train Americans, there's six hundred thousand jobs open, in the United States, and they pay 50% more than the average American salary. The companies are starving. How do we rapidly get more Americans into these jobs? It turns out that people have, of course, created these fabulous code boot camps, you can train in three months for these jobs, some of them are paid, some times they pay you, all different kinds, some are online, some are offline, they're all over the country. So we're able to get more people to consider, a job like that, culturally they think, Well I don't, why would I, I don't know how to do that. Well you can, this is a fun and interesting and exciting career, you can do digital marketing, you can do user interface design. You can get involved in front end or back end coding, product management, all those things, sales. And so, how do you pull lots more Americans in, get our companies fueled so we have really the economic opportunity, and they're all over the country. Location wise, and topic wise. So we did tech hour now, and a tech jobs tour, which is not what we did in government, but we continue some of that work. >> This weird dichotomy, because on one end, people are worried about tech taking jobs, on the other hand, there's a ton of open tech jobs. And there's this transition period, that's difficult, obviously for people that didn't grow up, but one of the keynote speakers today, told a really heartening story, that she didn't get into it until the day she had to leave her abusive husband, and now she is a coder >> That's Doctor Sue Black, who was just given the Order of the British Empire, I mean, she is an incredible computer scientist. Yes, she escaped an abusive marriage with three small children, in her early 20s, I think. Ended up moving into public housing, and dealing with three children only being the school from 9 until 3, and eventually getting her PhD in computer science, and really, she started Techmoms now, she continues to do research in other things, but she's really trying to use her story, and her organizing capacity, to have more people realize this isn't hard like figuring out gravity waves that won the Nobel prize. This is hard like writing a hard essay, so we all can learn to write an essay. It takes some mastery work, you don't learn it in kindergarten but by the time you're in 7th, 8th, 9th, 10th, 12th grade, you can do it. >> It's not rocket science. >> Right, so coding is like that. >> The other piece you said that's very interesting, is the consumerization of IT. We've seen it at enterprise, a huge trend. But, now I expect everything that's on my phone, when I interact with Facebook or Amazon, or whatever, to be in all the applications, so, as you said, that's influencing government, and the way they have to deliver services, and I would imagine, too, with kind of the next wave of kids coming in, graduating, going into public service, they certainly have that expectation, right? They've been working on their phone forever of course it should be on the phone. >> And so we want everybody in our country fluent in computer science and coding at a basic level, like again, like freshman biology or takin' chemistry in high school, or taking writing. So that everyone could realize this is not rocket science we could have these kinds of capabilities as part of our services, from Housing and Urban Development, from the Department of Education. You know, a lot of us use our phones to get places, you know, on our maps, and so that's actually data coming from the US Geological survey, if you're looking at the weather, you're looking at NOAA's satellites, this is open government data. We were able to open over two hundred thousand data sets, from all over government, not private data, but public data, that you could make an entire app store, or Google play set of products on top of that. Government wouldn't have to pay for that, it just packages up the API as well. A really good example of that, is the US census team. There's nothing more big data than census, they have all of our information from a data perspective, and so they did opportunity.census.gov, and they said to various agencies, let us help you bridge these data sets into something that someone could build on top of, like we're seeing from the courses sector, we saw wonderful things like, Housing and Urban Development said, okay, our challenges are housing affordability, mobility, these are the challenges instead of having HUD make an app for Americans to come to, they just can explain what their problem is, what data sets, and then engage extraordinary companies, like airbnb, Redfins, Zillow, these fabulous tech companies, who can make instead a product for 100% of the Americans, rather than only wealthy or middle class Americans, and so they did things like, opportunity score, and airbnb helping you figuring out, if I rent a room in my house I can make my rent more affordable, very creative apps, that we can see, same thing for the Department of Ed or Department of Labor, and as the data gets out there, and as apps come, also the opportunity for data science and machine learning. What if, as much as we serve ads to ourselves, in these algorithms, what if we use the algorithms to help Americans find a job that they would love? You know, job matching, and these kinds of opportunities. of the problems in the world, and helping government get more fluent at that. And the way to do that is not so much, jam the government You have to do this, but find terrific talent like we see at Hopper, and have them cycle into the government, to be co-leaders just like a surgeon general would come. >> Are you facing recruitment challenges in that same way though? In the sense that technology is having a hard enough time recruiting and retaining women, but the government, too, is that seen as enough of an employer of choice for young talented, bright ambitious, young women? >> I'm not in government now, but when we were in there, we found a very interesting thing. Alex Mcgovern, who had been the general counsel of Twitter who was Stephanie's CTO with me and led a lot of our tech quals we called TQ like tech IQ in policy, together with economists and lawyers and others have if we're going to decide net neutrality, let's include everyone, including computer scientists, and we're going to sue bridge and open source, So we talked about that, and on the way going in Mcgovern, he said, wouldn't it be cool if, just like when you look at a lawyer's resume, you might see that they clerk and they served their county through clerking and through the judicial system, as well as being a private lawyer, they were a public defender, that's a pretty normal thing to see on a legal resume. If you looked at medical, you might see them going into NIH or doing some research, if you looked at a scientist, they might have gone to, done some NSF work or others. But for the tech crew, there is of course amazing technical people in NASA, NAH and the Department of Energy, and there's great IT teams, but there's not this thing that the Silicon Valley crew resume would say, oh, yeah, I served my country. So that's why, under President Obama, we were able to create these incredible programs. The Presidential Innovation Fellows, which was a one year term of service, The United States Digital Service, which is a three months to a two year term of service in the VA. What's more amazing if you build Amazon, than to go as a second act and help our veterans? It's an incredible honor, to the point of, will they come? Yes, that's what we were hoping, could we have that be a normal thing, and yes it's become a normal thing. And the Trump administration continues it. The 18F team is in the general services administration, they're on 18th and F so they have a code name. But that particular team is located around the country, not only in DC but in San Francisco, in Chicago, and others. So you see this tech sector flowing now into the government on a regular basis, and we welcome more peoples. The government is who shows up to help, so we need the tech sector to show up cause we've got a lot of money as a country, but if we're not effectively using it we're not serving the American people and foster children, veterans, elders, others need the services that they deserve and we have the money, so let's make it happen the way the tech sector is delivering Amazon packages or searches. >> What is your feeling, this is not your first Grace Hopper obviously, but what is your feeling about this conference, and advice that you would give to young women who are here, maybe for their first or second time, in terms of getting the most their time here? >> You know, I think the main thing is, it's a celebration, that's fun and you can walk up to anyone, so just talk to everyone. I've been talking to a million people on the floor, fabulous. Students are here, more senior technical leaders are here. We've been running speed mentoring, we're running a program called the Tech Jobs Tour, it's at Techjobstour.com, it's a #Americanshiring, and we've been going to 50 different cities and so we're running a version of that, and we do speed mentoring, so come to the speed mentoring sessions, it's a five minute pop, talk to someone about what you're tryin' to do. Lot's of programs like that, get into the sessions, come to the keynotes which are so inspiring, and Melinda Gates was amazing today, Dr. Fefe Lee was incredible, just across aboard, Dr Sue Black was here, I thought it was great today, actually, just to reflect on Melinda's keynote, I think this might have been the first time, I was talking to her, that she's really talked about her own technical experience >> That struck me, too! As a coder, starting in computer science. I didn't really understand that she had really started very early, with Apple 3 and the story of her dad >> And her love of her Apple 3, right! and really high school coding, which is so important for young people in high school and middle school, even younger. The Muscogee Creek Tribe, in Oklahoma, is teaching robotics in head start, so we can start in preschool. Just make it fun, and interesting. They're funny, they don't do battle bots, because you don't really want to teach 3 and 4 year olds to fight, so instead they have collaborative robots. >> Robots who work together Age appropriate. >> Well Megan Smith, this has been so fun talking to you, thanks so much for coming on our show. >> Thanks for having me. >> We will have more from the Grace Hopper Conference just after this, I'm Rebecca Knight for Jeff Frick (music)

>> Announcer: Live from Las Vegas it's theCUBE, covering NetApp Insight 2017. Brought to you by NetApp. (upbeat techno music) >> Hello, everyone. Welcome to this special CUBE presentation. We are here at the Mandalay Bay in Las Vegas, Nevada for NetApp Insight 2017. I'm John Furrier, your co-host and co-founder of SiliconANGLE Media. Here at theCUBE, here with Keith Townsend for all day today. Keith Townsend at CTO Advisor covering NetApp 2017 here at the Mandalay Bay in Las Vegas. And before we kickoff a long day of great conversations with thought leaders, experts, executives, and also customers of NetApp who are transitioning to a whole digital world, a digital transformation. We can't not address the massacre that happened only a few days ago here in Las Vegas, here at the Mandalay Bay, our second home of theCUBE. If you know theCUBE, you know that we're here all the time. Hits home for us, but that pales in comparison to the families and victims of the 58 dead, 59 total but 58 that have died plus the shooter. Over 500 injured in the heinous cowardly act from the shooter who killed those people. Really I'm trying to kind of hold it together because it really hits home for me because, like 9/11, it's one of those moments that this is planned. This was a coordinated attack, kind of like the Oklahoma bombing, and it reflects on our society. I want to make a comment. And Keith, I'd like to get your thoughts in a minute. But first I would like to say our hearts and prayers are with the victims and families. And want to put a shout out to the first responders because if you look at the Mandalay Bay and what happened here, there could have been a lot more that have died. And that is really a testament to the people who responded, to this unpredictable act. And our prayers go out to the families and victims. And again, a shout out to the law enforcement people. Keith, this is a tragedy that people are trying to make sense out of it. And you know, we have to move on. Obviously, we're here at the NetApp event. A lot of great things to talk about with data and the future and how society will change with technology. But this is a time in history where we're seeing a societal shift. But we got to make sense of it. >> Yeah, you know, John, I'm going to try and keep it together as well. I think this is my seventh time in Vegas this year. And I'm sure every time I've spent at least some time in Mandalay Bay. This event, you know, I had a personal tragedy in my own life of losing my nephew to gun violence. We're all scratching for answers and trying to find a solution to this. And I'm a little bit ... It's a tough moment I think, personally, for us and our friends in the community. But the folks here at NetApp have done a really great job. Not just NetApp but the community in general, here in Las Vegas there's been folks in the community that have organized blood drives. The Red Cross has actually asked us to stop donating blood because of the outpouring of support. And I think that focus of hope in changing the world is what I would like to focus on. >> Well, I mean, take a company like NetApp having their annual customer event, partner event here at Mandalay Bay. It's their big event. And on their doorstep this happens. How they've handled themselves, I think, shows the culture of NetApp. They respect, they took pause. They canceled the first day. They handled it with extreme class. George Kurian put out there a personal story. But this is what it's about. We've got to move on. But I think to me, it's not about politics. It's not about any of that. It's about how do we move forward? And I hate to use a cliché, it's a wake up call. The world has changed in an instant through a prism of a known life. We heard that at 9/11. It's been 16 years. Enough's enough. And here's the deal, we have to be awake. We are realizing that, not the digital transformation for the enterprise, it is a transformation around the world. If you look at geopolitics, or you look at what's happened even today in the news. Even though the President of the United States is here to visit with the families, the Senate Intelligence Committee points out more fake news influenced via social media on Facebook with the Russians hacking the election. They didn't really hack the election, they just used advertising and albatross Facebook among other platforms to manipulate the election. Equifax hack, turns out as I reported originally on theCUBE, it was a state-sponsored activity, it was not a hack. These are new realities. And this is the theme that we see at theCUBE across our events that we go to, the new reality that we are living in a completely different society and it's on us to lean in and be part of the solution. And it's not about being a political solution or saying, "Hey, I'm praying." I mean, we're praying. But you can pray. Praying is what you do, action is another. But it's not about just the gun laws or this or that, it's about the society and the communities. The GoFundMe's are going crazy for the victims, but you can't replace the mother. We had a loss in our community, former Cisco employee lost her life, three kids. The communities have to lean in, individuals have to lean in if they have expertise. I think this is going to be a call to arms that's going to have a revolutionary effect on people. And I think it's an opportunity for the technology industry to lean in, use what we know. We have AI. We got blockchain. We got machine-learning. And this data, the slogan of NetApp couldn't be more perfect. Changing the world with data this is the mandate. >> So, George Kurian gave an ardent, and just compassionate... I had a tough time keeping myself together at the end of yesterday's keynote. George shared how data helped save his son's life. His 13-year-old son comes home every day thankful for technology. And we need to find ways to use AI, use machine learning to impact our communities. While we're talking about the larger, global community, even in my hometown of Chicago that's ravished by violence. You know, there's ways to use social media, data, AI-driven changes to help create policies and to help enable community organizers to understand the source of this nonsense basically. We say this is the new normal, but we should never grow numb to it. >> And I'm grateful -- >> John: No, it's not normal. It's not normal. And this is why I tell my daughter who's the class president of junior high school, Paolo Alto High School, this is not normal. This is not normal. This is not what we want. >> Keith: No! >> You know, you're personal tragedy, hit home with you personally. You had to rationalize it. And you're also a very active participant in the community. This is a new opportunity. The new normal is to behave differently, not the outcome. How do you look at that? Given what you've been through personally and now this, it brings together emotions but then the logic has to kick in. >> Keith: Right. >> You have to execute, actually take action. >> So, it started again Monday when a bunch of us had to make the decision on whether or not we're going to make the trip to Vegas to participate in a enterprise IT show. Your initial gut reaction is, "You know what, so many dead. What does it really matter to go to a conference at this point in time?" And then, you start to rationalize. "You know what? My way of life, our way of life cannot change. We can't allow this tragic event to change how we approach it." And again, NetApp and George did a great job of kicking off the conversation saying that we need to use this as a pivot point to drive the conversation to how us technologists can leverage this. >> Let's take this to where NetApp's living right now. NetApp Insight 2017 is the even we're kicking off here, all day coverage, here on theCUBE with Keith Townsend, expert in the field. Cloud, data, storage, it's all converging. But the reality is is that NetApp has SolidFire. They've bought great company. You're seeing a DNA transfer off of the original DNA of NetApp which has been very innovative culture. They have a very big success story as a start up, went public, and now are continuing to transform. Their customers are transforming but you bring up this new normal that the behavior we want to change and the outcomes that will become of it, speaks to the culture of what we're seeing in the enterprise transformation. A new class of developers are coming in. And the class of developers are about DevOps, their about infrastructure as code. And these new developers, have a new mindset. >> Yeah, so NetApp, a storage company, right? They store bits, retrieve bits. Not so much. They spent a hour on stage yesterday, even before they talked about any products, any architectures, talking about the value of data. Data is the ... And John, you've talked about data for as long as I've known you. Data is the number one asset of any company and NetApp focused not on storage, not on arrays, not on how fast the speeds and feeds go, but the value of data and extracting that value from your subsystems and then going into the conversation around how NetApp can assist in that journey in leveraging data. >> Okay, we're going to kickoff Day One coverage with NetApp Insight 2017 here on theCUBE. Changing the world with data. That is the focus, that is the conversation. And that is an aperture, that's the entire world from how you store the data, how to use the data. How do you to put it to work? How do you create value and transformation? This is theCUBE bringing the action here from the Mandalay Bay in Las Vegas for NetApp Insight 2017. Stay with us. We'll be right back with our next guest after this short break. (upbeat techno music)