(bright upbeat music) >> Hey, good morning from Las Vegas. It's Lisa Martin and Paul Gillin here. We are on day three of AWS re:Invent. We started Monday night, we went all day yesterday, we are going all day today and all day tomorrow. The amount of content coming at you from theCUBE, great, interesting, fascinating conversations with AWS, its customers, its ecosystem partners is incredible. Paul, what's your take so far on re:Invent? We've been here two and a half days. >> Well, it's just a fire hose. Like I've said before, this morning's keynote was about was about ML, machine learning and AI, and I stopped counting at 15 new announcements during about a 90 minute keynote, it's just one thing after another. And that's the nature of re:Invent, you know? It's always a showcase for new stuff. And they talk about customers, you talk about customers, I love it when we have a chance to talk to customers on theCUBE as we are about to do. >> We are about to talk to one of the nation's leading digital banks, you know them well, Capital One. Please welcome, Lo Li, Managing Vice President of Customer Digital Experience and Payments. Thank you so much, Lo, for joining us. >> Why, thank you, I'm glad to be here. >> Talk a little bit about your role where it fits within the organization, what it encompasses? >> Sure, yeah. So, I lead the retail bank technology organization which is a form of, you know, we have teams that lead digital experiences for our consumers. We look after agent in-person experiences with their cafes in branches, our call centers and as well as of our MarTech and payments ecosystem. >> So you're new to Capital One, in the last less than a year, you know, we all know it, we love it, we know the tagline, what's in your wallet? I think we can all recite that. It's as I said in the opening, it's one of the nation's leading digital banks and technology is really core to its business strategy and delivering value to customers. What attracted you to Capital One and talk about it really as a digital bank that delivers all that value. >> Of course. Yeah, so, you know, I spent 20 years of my career in a digital space in retail, and fashion and hospitality. And that is what I love about IT and the industry that I'm in and what I do, which is bringing really great solutions and products to consumers and getting them excited about an experience and a brand. So I knew early on in my career I was attracted to really great brands and brands that wanted to innovate and disrupt the consumer space. So when Capital One gave me an opportunity, I couldn't be happier, right? This is an incredible bank, we have an incredible story, we're a young bank and yet we are very much on the leading edge of a digital bank experience. >> And you were in an interesting place because as we know retail banking is declining or at least bank branches are in decline. More and more people want to do their banking on their mobile apps or through their computers, particularly younger customers. And so you're having to manage all this, what are you doing? How are you tracking to these demographic changes accelerated by the pandemic and recreating the customer experience through multiple channels? >> Yeah, great question. We want to give our consumers an omnichannel experience irrespective of, you know, the few that still want to go into branches or perhaps they want to experience a cafe, and while there meet with one of our branch ambassadors to talk about their banking, we have consumers that want to go digital. So what we do is that we make sure that we're looking after the consumer holistically, irrespective of the channel. So whether they call into the call center because they need servicing or if they're physically present or they want to carry that on digitally, we make sure that we create super personalized custom experiences. We also work with a bunch of designers that are thinking through, you know, the life of a consumer now and their relationship to a bank. It is, to your point, it is no longer a branch, you know? That is a ubiquitous experience that we're by large knowing that we have to figure out and rethink. So, we're very lucky to have great designers that work with us and work on what is that experience that we want our consumers to have, from the pastries and the coffee, and the experience of being with an ambassador and how we can lead them through our iPads and digital experiences to continue to stay with us and for us to service them. >> You know, if we think about how much banking has changed especially in the last couple of years, when suddenly you couldn't get into a branch, even if you wanted to, it's amazing how we have this expectation that on my phone I can do any transaction I want in real time, I'm going to be able to see my balance, I can transfer money, I can make a payment. And we don't think about the technology on the back end but it's absolutely critical to powering that experience. >> Yeah. >> Talk about how you're doing that and is there customer feedback in that process? >> There is, but that's music to my ears by the way. The fact that you don't think about it tells me we're doing something really right, right? So first and foremost, we are super hypervigilant about security, that is top of mind, we are well managed. The cloud has enabled us to create these infrastructures that are highly secure, that are scalable and that allows us to really focus on innovation. So we use our mobile platform and our apps in that way, right? We know that this is a scalable, secure platform. We create really great products, we create very custom experiences for you that are relevant to you and your family and we create these digital products that are supposed to meet you where you are. >> But we certainly have, you know, this expectation that I'm going to get what I want, it's going to be relevant, it's going to be timely. If not, I'm going to pick up, not the phone, I'm going to go on social media and make a complaint. So from a brand reputation perspective, you guys, what you're doing is clearly going in the right direction. >> Yeah, yeah. Look, we take our bank voice and the voice of the customer extremely seriously. So, we have a really large infrastructure from a bank operations perspective. We have our bank voice agents that work with us that give us kind of really real-time feedback from our customers. You know, by the time you pick up the phone and call usually something has gone really wrong, right? So, we make sure that we stay lockstep with what our first level agents are hearing. Then we also look into our feedbacks, we have obviously ways to look into our mobile app. We look at all the reviews that we have and incorporate that into how we think about our product and how we invest and innovate on them. >> Before we turned on the cameras, you said an amazing thing. Capital One doesn't have any data centers anymore, doesn't have any mainframes anymore, it is fully in the cloud. Understanding that you weren't there in those old days but how does that change the way you think about new features, about technology, new technology developments for the customer when you don't have that legacy to drag along with you? >> It's incredible, right? Our cost efficiency, our production efficiency, how we think about going to the market now is really getting us to focus on the right parts of that product. We don't have to carry a lot of the technical debt, we don't carry that old infrastructure. So the way we develop, the way we design, the way we go to market is a lot faster than it ever was. >> Well, and the culture is there, the cultural mindset is there to be able to do that. I mean, if you think about who you compete with some of these institutions that have been around for a hundred years that also have to transform and digitize 'cause the customers expect it. That has to be a seamless process but their culture also has to be there because changing from being On-prem data centers to being completely in the cloud, it's a big change. >> Yeah, actually, you hit it, right? The cloud transformation is big, and hard and sticky. You got to move these workloads, you got to make 'em native, you got to deploy. But to your point, the harder part really is the culture, right? Because the cloud will then unleash productivity, it will unleash continuous improvement. It will bring product partners along the ride because they have to think differently about what they want to go to the market with, how they think about the cost of those units, how they think about cloud. So, you know, in my opinion, Capital One has done an incredible job bringing that entire, the entire organization along this cloud transformation including our culture, our processes, and our people. >> I know Capital One is proud of the work it's been doing in AI and machine learning. Can you talk about from the retail banking perspective, how is machine learning being applied to improve the customer experience? >> Yeah, well, you know, as you know, AI and machine learning is the heart of the bank, is the heart of Capital One. When we started in the early 90s, we were the only bank that was really trying to challenge how we use data to provide better products for our consumers, and that is ingrained in our DNA and everything that we do. So if you were to look at bank, we would start with, you know, from the time you are authenticating yourself, how we think about fraud and how do we capture bad actors, all the way to if you were to call into a call center, we use a lot of natural language processing models to make sure that we assess your sentiment, we give you the support that you need, and then of course, use that to learn more about how we service you. >> Interesting, I'm just wondering, do you think about Capital One as a technology company that does banking or a bank that is powered by technology? >> We are a technology company, and we happen to also have a bank. >> Lisa: I love that. What are some of the things that you've heard and seen at the show? Obviously, we're hearing numbers between 55 and 70,000 people here. It's crazy. And we're only getting a snapshot of that because here we are at Venetian Expo and the conference is going on all over the strip. But what are some of the things that you've heard from AWS that excite you about the partnership going forward? >> You know, I'll be honest, one of my happiest, proud moments, when we're talking about Lambda SnapStart yesterday, we actually, our team that is here today was part of the first beta of bringing in Lambda SnapStart. And we're super excited because it helps propel our serverless agenda. You know, we're continued to transform into the cloud. So, we have a lot of these partnership opportunities that, you know, make me super proud. >> Well follow up on serverless because to a lot of people, it's a concept that they don't really understand how to put it to practice. How is serverless a step forward? What has it enabled you to do that you couldn't otherwise do? >> Wow, a bunch. I think first and foremost, it helps us stay, you know, very well managed, security wise, right? It allows us to create automation and it takes away a lot of the heavy lifting that our engineers would have to do otherwise. And the byproduct of that is that we get to go focus on really fun, innovative ideas, and we get to go work on product development. We're taking a lot of the grit work of the management of the servers out of the engineer's hand and automating them. >> Banking, of course, one of the most regulated industries on the planet, has Cloud been able to help you in that respect? >> Yes. Yes it has. Look, we are in a regulated space which means everything we do has a ton of scrutiny, for the right reasons. So we actually built it into our design, so our design, our products, we design our platforms with security in mind, with the regulations in mind and make it where it's less of a thought, right? So, we obviously spend a lot of time from a risk posture helping our associates understand, really respecting the responsibility that we have to look after everybody's assets, right? Like it's, what a more incredible job than that? So, we spend a lot of time thinking about what is our risk posture, where is it, you know, from what you would imagine the regular scan vulnerabilities all the way to data protection. And now that we protect that data in Fly, like they're all things that is our number one job and we spend a ton of time focused on it. >> That's good, it's very complex but security is a topic we discuss regularly. We've seen the threat landscape change so dramatically in the last couple of years. Bad actors are getting far more sophisticated. They're leveraging the technology but when it comes to banking as Paul was talking about, from a regulations perspective, from an end customer perspective, we have this expectation that you're going to keep my data secure because nobody wants to be the next headline. >> Lo: Yes, that's right. That's right, and look, we are getting, we're getting smarter as well, right? So we are able to detect and monitor and go after the bad actors faster. We're doing it in a way that allows us configurability, it gives us time, it gives us speed, but at the same time we also work as a network, right? So a lot of our banks, we, you know, in some ways share a lot of this information to make sure that we're all going after a common enemy. >> Capital One recently launched a software company, Capital One Software, which is a relatively unusual move by a financial services organization. How has that affected the thinking at the company about what the company is and what other opportunities there might be outside of pure banking? >> Yeah, absolutely. So, Capital One Software is a very exciting new line of business. I think the team that is there is doing some really incredible, innovative work. But you know what's really interesting is they were talking about our new product SlingShot, it was born out of our needs, right? We knew that we needed to have better governance around our data. We created really great tools and it was very obvious that there was a commercial applicability there. And that is how we will continue to operate, right? As a bank, we're all in the cloud, we're all in in the cloud. It will give us the ability to start sharing some of these best practices. And I think the best is yet to come, I think we got some really good stuff in the pipeline. >> Lisa: Anything you can share in the-- >> No. >> Lisa: No? Tight lips. >> Tight lips. >> Excellent, well, last couple of questions. What's the main theme here? When people walk into the Venetian Expo and they see Capital One next to all these tech companies, what's the main theme that Capital One wants to get across to the greater community? >> Yeah, look, our mission is to change banking for good, it always has been our mission. We're very fortunate to be in a position to be tech innovators, and we're fortunate to disrupt, and that's what I want people to get out of it. >> Excellent, my last question for you, kind of continuing on this theme. If you had, you were going to have the opportunity to create new branding and it's going to go in the cafes and it's going to be like a little billboard inside about Capital One being a technology company that does banking. What do you think that that billboard, that sign would say? >> I think I'm going to stick with the change banking for good. I mean, that really is at the heart of our mission. >> Paul: It's a nice double message too, yeah. >> Yeah, with technology, with disruption, ultimately that's where our hearts and minds are at. >> Awesome. Lo, it's been great to have you on the program. Thank you for sharing what you're doing at Capital One, how you're working with AWS and also emerging technologies like AI and ML to really create a seamless digital customer experience. We really appreciate your time and your insights. >> Thank you. >> All right, for our guest and for Paul Gillin I'm Lisa Martin. You're watching theCUBE, the leader in live emerging and enterprise tech coverage. (upbeat music)

>>The cube presents HPE discover 2022 brought to you by HPE. >>Hey everyone. Welcome back to the Cube's day one coverage of HPE discover 22 live from the Venetian in Las Vegas. I got a power panel here, Lisa Martin, with Dave Valante, John furrier, Holger Mueller also joins us. We are gonna wrap this, like you've never seen a rap before guys. Lot of momentum today, lot, lot of excitement, about 8,000 or so customers, partners, HPE leaders here. Holger. Let's go ahead and start with you. What are some of the things that you heard felt saw observed today on day one? >>Yeah, it's great to be back in person. Right? 8,000 people events are rare. Uh, I'm not sure. Have you been to more than 8,000? <laugh> yeah, yeah. Okay. This year, this year. I mean, historically, yes, but, um, >>Snowflake was 10. Yeah. >>So, oh, wow. Okay. So 8,000 was my, >>Cisco was, they said 15, >>But is my, my 8,000, my record, I let us down with 7,000 kind of like, but it's in the Florida swarm. It's not nicely. Like, and there's >>Usually what SFI, there's usually >>20, 20, 30, 40, 50. I remember 50 in the nineties. Right. That was a different time. But yeah. Interesting. Yeah. Interesting what people do and it depends how much time there is to come. Right. And know that it happens. Right. But yeah, no, I think it's interesting. We, we had a good two analyst track today. Um, interesting. Like HPE is kind of like back not being your grandfather's HPE to a certain point. One of the key stats. I know Dave always for the stats, right. Is what I found really interesting that over two third of GreenLake revenue is software and services. Now a love to know how much of that services, how much of that software. But I mean, I, I, I, provocate some, one to ones, the HP executives saying, Hey, you're a hardware company. Right. And they didn't even come back. Right. But Antonio said, no, two thirds is, uh, software and services. Right. That's interesting. They passed the one exabyte, uh, being managed, uh, as a, as a hallmark. Right. I was surprised only 120,000 users if I had to remember the number. Right, right. So that doesn't seem a terrible high amount of number of users. Right. So, but that's, that's, that's promising. >>So what software is in there, cuz it's gotta be mostly services. >>Right? Well it's the 70 plus cloud services, right. That everybody's talking about where the added eight of them shockingly back up and recovery, I thought that was done at launch. Right. >>Still who >>Keep recycling storage and you back. But now it's real. Yeah. >>But the company who knows the enterprise, right. HPE, what I've been doing before with no backup and recovery GreenLake. So that was kind of like, okay, we really want to do this now and nearly, and then say like, oh, by the way, we've been doing this all the time. Yeah. >>Oh, what's your take on the installed base of HP. We had that conversation, the, uh, kickoff or on who's their target, what's the target audience environment look like. It certainly is changing. Right? If it's software and services, GreenLake is resonating. Yeah. Um, ecosystems responding. What's their customers cuz managed services are up too Kubernetes, all the managed services what's what's it like what's their it transformation base look like >>Much of it is of course install base, right? The trusted 20, 30 plus year old HP customer. Who's keeping doing stuff of HP. Right. And call it GreenLake. They've been for so many name changes. It doesn't really matter. And it's kind of like nice that you get the consume pain only what you consume. Right. I get the cloud broad to me then the general markets, of course, people who still need to run stuff on premises. Right. And there's three reasons of doing this performance, right. Because we know the speed of light is relative. If you're in the Southern hemisphere and even your email servers in Northern hemisphere, it takes a moment for your email to arrive. It's a very different user experience. Um, local legislation for data, residency privacy. And then, I mean Charles Phillips who we all know, right. Former president of uh, info nicely always said, Hey, if the CIOs over 50, I don't have to sell qu. Right. So there is not invented. I'm not gonna do cloud here. And now I've kind of like clouded with something like HP GreenLake. That's the customers. And then of course procurement is a big friend, right? Yeah. Because when you do hardware refresh, right. You have to have two or three competitors who are the two or three competitors left. Right. There's Dell. Yeah. And then maybe Lenovo. Right? So, so like a >>Little bit channels, the strength, the procurement physicians of strength, of course install base question. Do you think they have a Microsoft opportunity where, what 365 was Microsoft had office before 365, but they brought in the cloud and then everything changed. Does HP have that same opportunity with kind of the GreenLake, you know, model with their existing stuff. >>It has a GreenLake opportunity, but there's not much software left. It's a very different situation like Microsoft. Right? So, uh, which green, which HP could bring along to say, now run it with us better in the cloud because they've been selling much of it. Most of it, of their software portfolio, which they bought as an HP in the past. Right. So I don't see that happening so much, but GreenLake as a platform itself course interesting because enterprise need a modern container based platform. >>I want, I want to double click on this a little bit because the way I see it is HP is going to its installed base. I think you guys are right on say, this is how we're doing business now. Yeah. You know, come on along. But my sense is, some customers don't want to do the consumption model. There are actually some customers that say, Hey, of course I got, I don't have a cash port problem. I wanna pay for it up front and leave me alone. >>I've been doing this since 50 years. Nice. As I changed it, now <laugh> two know >>Money's wants to do it. And I don't wanna rent because rental's more expensive and blah, blah, blah. So do you see that in the customer base that, that some are pushing back? >>Of course, look, I have a German accent, right? So I go there regularly and uh, the Germans are like worried about doing anything in the cloud. And if you go to a board in Germany and say, Hey, we can pay our usual hardware, refresh, CapEx as usual, or should we bug consumption? And they might know what we are running. <laugh> so not whole, no offense against the Germans out. The German parts are there, but many of them will say, Hey, so this is change with COVID. Right. Which is super interesting. Right? So the, the traditional boards non-technical have been hearing about this cloud variable cost OPEX to CapEx and all of a sudden there's so much CapEx, right. Office buildings, which are not being used truck fleets. So there's a whole new sensitivity by traditional non-technical boards towards CapEx, which now the light bulb went on and say, oh, that's the cloud thing about also. So we have to find a way to get our cost structure, to ramp up and ramp down as our business might be ramping up through COVID through now inflation fears, recession, fears, and so on. >>So, okay. HP's, HP's made the statement that anything you can do in the cloud you can do in GreenLake. Yes. And I've said you can't run on snowflake. You can't run Mongo Atlas, you can't run data bricks, but that's okay. That's fine. Let's be, I think they're talking about, there's >>A short list of things. I think they're talking about the, their >>Stuff, their, >>The operating experience. So we've got single sign on through a URL, right. Uh, you've got, you know, some level of consistency in terms of policy. It's unclear exactly what that is. You've got storage backup. Dr. What, some other services, seven other services. If you had to sort of take your best guess as to where HP is now and peg it toward where Amazon was in which year? >>20 14, 20 14. >>Yeah. Where they had their first conference or the second we invent here with 3000 people and they were thinking, Hey, we're big. Yeah. >>Yeah. And I think GreenLake is the building blocks. So they quite that's the >>Building. Right? I mean similar. >>Okay. Well, I mean they had E C, Q and S3 and SQS, right. That was the core. And then the rest of those services were, I mean, base stock was one of that first came in behind and >>In fairness, the industry has advanced since then, Kubernetes is further along. And so HPE can take advantage of that. But in terms of just the basic platform, I, I would agree. I think it's >>Well, I mean, I think, I mean the software, question's a big one. I wanna bring up because the question is, is that software is getting the world. Hardware is really software scales, everything, data, the edge story. I love their story. I think HP story is wonderful Aruba, you know, hybrid cloud, good story, edge edge. But if you look under the covers, it's weak, right? It's like, it's not software. They don't have enough software juice, but the ecosystem opportunity to me is where you plug and play. So HP knows that game. But if you look historically over the past 25 years, HP now HPE, they understand plug and play interoperability. So the question is, can they thread the needle >>Right. >>Between filling the gaps on the software? Yeah. With partners, >>Can they get the partners? Right. And which have been long, long time. Right. For a long time, HP has been the number one platform under ICP, right? Same thing. You get certified for running this. Right. I know from my own history, uh, I joined Oracle last century and the big thing was, let's get your eBusiness suite certified on HP. Right? Like as if somebody would buy H Oracle work for them, right. This 20 years ago, server >>The original exit data was HP. Oracle. >>Exactly. Exactly. So there's this thinking that's there. But I think the key thing is we know that all modern forget about the hardware form in the platforms, right? All modern software has to move to containers and snowflake runs in containers. You mentioned that, right? Yeah. If customers force snowflake and HPE to the table, right, there will be a way to make it work. Right. And which will help HPE to be the partner open part will bring the software. >>I, I think it's, I think that's an opportunity because that changes the game and agility and speed. If HP plays their differentiation, right. Which we asked on their opening segment, what's their differentiation. They got size scale channel, >>What to the enterprise. And then the big benefit is this workload portability thing. Right? You understand what is run in the public cloud? I need to run it local. For whatever reason, performance, local residency of data. I can move that. There that's the big benefit to the ISVs, the sales vendors as well. >>But they have to have a stronger data platform story in my that's right. Opinion. I mean, you can run Oracle and HPE, but there's no reason they shouldn't be able to do a deal with, with snowflake. I mean, we saw it with Dell. Yep. We saw it with, with, with pure and I, if our HPE I'd be saying, Hey, because the way the snowflake deal worked, you probably know this is your reading data into the cloud. The compute actually occurs in the cloud viral HB going snowflake saying we can separate compute and storage. Right. And we have GreenLake. We have on demand. Why don't we run the compute on-prem and make it a full class, first class citizen, right. For all of our customers data. And that would be really innovative. And I think Mongo would be another, they've got OnPrem. >>And the question is, how many, how many snowflake customers are telling snowflake? Can I run you on premise? And how much defo open years will they hear from that? Right? This is >>Why would they deal Dell? That >>Deal though, with that, they did a deal. >>I think they did that deal because the customer came to them and said, you don't exactly that deal. We're gonna spend the >>Snowflake >>Customers think crazy things happen, right? Even, even put an Oracle database in a Microsoft Azure data center, right. Would off who, what as >>Possible snowflake, >>Oracle. So on, Aw, the >>Snow, the snowflakes in the world have to make a decision. Dave on, is it all snowflake all the time? Because what the reality is, and I think, again, this comes back down to the, the track that HP could go up or down is gonna be about software. Open source is now the software industry. There's no such thing as proprietary software, in my opinion, relatively speaking, cloud scale and integrated, integrated integration software is proprietary. The workflows are proprietary. So if they can get that right with the partners, I would focus on that. I think they can tap open source, look at Amazon with open source. They sucked it up and they integrated it in. No, no. So integration is the deal, not >>Software first, but Snowflake's made the call. You were there, Lisa. They basically saying it's we have, you have to be in snowflake in order to get the governance and the scalability, all that other wonderful stuff. Oh, but we we'll do Apache iceberg. We'll we'll open it up. We'll do Python. Yeah. >>But you can't do it data clean room unless you are in snowflake. Exactly. Snowflake on snowflake. >>Exactly. >>But got it. Isn't that? What you heard from AWS all the time till they came out outposts, right? I mean, snowflake is a market leader for what they're doing. Right. So that they want to change their platform. I mean, kudos to them. They don't need to change the platform. They will be the last to change their platform to a ne to anything on premises. Right. But I think the trend already shows that it's going that way. >>Well, if you look at outpost is an signal, Dave, the success of outpost launched what four years ago, they announced it. >>What >>EKS is beating, what outpost is doing. Outpost is there. There's not a lot of buzz and talk to the insiders and the open source community, uh, EKS and containers. To your point mm-hmm <affirmative> is moving faster on, I won't say commodity hardware, but like could be white box or HP, Dell, whatever it's gonna be that scale differentiation and the edge story is, is a good one. And I think with what we're seeing in the market now it's the industrial edge. The back office was gen one cloud back office data center. Now it's hybrid. The focus will be industrial edge machine learning and AI, and they have it here. And there's some, some early conversations with, uh, I heard it from, uh, this morning, you guys interviewed, uh, uh, John Schultz, right? With the world economic 4k birth Butterfield. She was amazing. And then you had Justin bring up a Hoar, bring up quantum. Yes. That is a differentiator. >>HP. >>Yes. Yeah. You, they have the computing shops. They had the R and D can they bring it to the table >>As, as HPC, right. To what they Schultz for of uh, the frontier system. Right. So very impressed. >>So the ecosystem is the key for them is because that's how they're gonna fill the gaps. They can't, they can't only, >>They could, they could high HPC edge piece. I wouldn't count 'em out of that game yet. If you co-locate a box, I'll use the word box, particularly at a telco tower. That's a data center. Yep. Right. If done properly. Yep. So, you know, what outpost was supposed to do actually is a hybrid opportunity. Aruba >>Gives them a unique, >>But the key thing is right. It's a yin and yang, right? It's the ecosystem it's partners to bring those software workload. Absolutely. Right. But HPE has to keep the platform attractive enough. Right. And the key thing there is that you have this workload capability thing that you can bring things, which you've built yourself. I mean, look at the telcos right. Network function, visualization, thousands of man, years into these projects. Right. So if I can't bring it to your edge box, no, I'm not trying to get to your Xbox. Right. >>Hold I gotta ask you since in the Dave too, since you guys both here and Lisa, you know, I said on the opening, they have serious customers and those customers have serious problems, cyber security, ransomware. So yeah. I teach transformation now. Industrial transformation machine learning, check, check, check. Oh, sounds good. But at the end of the day, their customers have some serious problems. Right? Cyber, this is, this is high stakes poker. Yeah. What do you think HP's position for in the security? You mentioned containers, you got all this stuff, you got open source, supply chain, you have to left supply chain issues. What is their position with security? Cuz that's the big one. >>I, I think they have to have a mature attitude that customers expect from HPE. Right? I don't have to educate HP on security. So they have to have the partner offerings again. We're back at the ecosystem to have what probably you have. So bring your own security apart from what they have to have out of the box to do business with them. This is why the shocker this morning was back up in recovery coming. <laugh> it's kind like important for that. Right? Well >>That's, that's, that's more ransomware and the >>More skeleton skeletons in the closet there, which customers should check of course. But I think the expectations HP understands that and brings it along either from partner or natively. >>I, I think it's, I think it's services. I think point next is the point of integration for their security. That's why two thirds is software and services. A lot of that is services, right? You know, you need security, we'll help you get there. We people trust HP >>Here, but we have nothing against point next or any professional service. They're all hardworking. But if I will have to rely on humans for my cyber security strategy on a daily level, I'm getting gray hair and I little gray hair >>Red. Okay. I that's, >>But >>I think, but I do think that's the camera strategy. I mean, I'm sure there's a lot of that stuff that's beginning to be designed in, but I, my guess is a lot of it is services. >>Well, you got the Aruba. Part of the booth was packed. Aruba's there. You mentioned that earlier. Is that good enough? Because the word zero trust is kicked around a lot. On one hand, on the other hand, other conversations, it's all about trust. So supply chain and software is trusting trust, trust and verified. So you got this whole mentality of perimeter gone mentality. It's zero trust. And if you've got software trust, interesting thoughts there, how do you reconcile zero trust? And then I need trust. What's what's you? What are you seeing older on that? Because I ask people all the time, they're like, uh, I'm zero trust or is it trust? >>Yeah. The middle ground. Right? Trusted. The meantime people are man manipulating what's happening in your runtime containers. Right? So, uh, drift control is a new password there that you check what's in your runtime containers, which supposedly impenetrable, but people finding ways to hack them. So we'll see this cat and mouse game going on all the time. Yeah. Yeah. There's always gonna be the need for being in a secure, good environment from that perspective. Absolutely. But the key is edge has to be more than Aruba, right? If yeah. HV goes away and says, oh yeah, we can manage your edge with our Aruba devices. That's not enough. It's the virtual probability. And you said the important thing before it's about the data, right? Because the dirty secret of containers is yeah, I move the code, but what enterprise code works without data, right? You can't say as enterprise, okay, we're done for the day check tomorrow. We didn't persist your data, auditor customer. We don't have your data anymore. So filling a way to transport the data. And there just one last thought, right? They have a super interesting asset. They want break lands for the venerable map R right. Which wrote their own storage drivers and gives you the chance to potentially do something in that area, which I'm personally excited about. But we'll see what happens. >>I mean, I think the holy grail is can I, can I put my data into a cloud who's ever, you know, call it a super cloud and can I, is it secure? Is it governed? Can I share it and be confident that it's discoverable and that the, the person I give it to has the right to use it. Yeah. And, and it's the correct data. There's not like a zillion copies running. That's the holy grail. And I, I think the answer today is no, you can, you can do that maybe inside of AWS or maybe inside of Azure, look maybe certainly inside of snowflake, can you do that inside a GreenLake? Well, you probably can inside a GreenLake, but then when you put it into the cloud, is it cross cloud? Is it really out to the edge? And that's where it starts to break down, but that's where the work is to be done. That's >>The one Exide is in there already. Right. So men being men. Yeah. >>But okay. But it it's in there. Yeah. Okay. What do you do with it? Can you share that data? What can you actually automate governance? Right? Uh, is that data discoverable? Are there multiple copies of that data? What's the, you know, master copy. Here's >>A question. You guys, here's a question for you guys analyst, what do you think the psychology is of the CIO or CSO when HP comes into town with GreenLake, uh, and they say, what's your relationship with the hyperscalers? Cause I'm a CIO. I got my environment. I might be CapEx centric or Hey, I'm open model. Open-minded to an operating model. Every one of these enterprises has a cloud relationship. Yeah. Yeah. What's the dynamic. What do you think the psychology is of the CIO when they're rationalizing their, their trajectory, their architecture, cloud, native scale integration with HPE GreenLake or >>HP service. I think she or he hears defensiveness from HPE. I think she hears HPE or he hears HPE coming in and saying, you don't need to go to the cloud. You know, you could keep it right here. I, I don't think that's the right posture. I think it should be. We are your cloud. And we can manage whether it's OnPrem hybrid in AWS, Azure, Google, across those clouds. And we have an edge story that should be the vision that they put forth. That's the super cloud vision, but I don't hear it >>From these guys. What do you think psycho, do you agree with that? >>I'm totally to make, sorry to be boring, but I totally agree with, uh, Dave on that. Right? So the, the, the multi-cloud capability from a trusted large company has worked for anybody up and down the stack. Right? You can look historically for, uh, past layers with cloud Foundry, right? It's history vulnerable. You can look for DevOps of Hashi coop. You can look for database with MongoDB right now. So if HPE provides that data access, right, with all the problems of data gravity and egres cost and the workability, they will be doing really, really well, but we need to hear it more, right. We didn't hear much software today in the keynote. Right. >>Do they have a competitive offering vis-a-vis or Azure? >>The question is, will it be an HPE offering or will, or the software platform, one of the offerings and you as customer can plug and play, right. Will software be a differentiator for HP, right. And will be close, proprietary to the point to again, be open enough for it, or will they get that R and D format that, or will they just say, okay, ES MES here on the side, your choice, and you can use OpenShift or whatever, we don't matter. That's >>The, that's the key question. That's the key question. Is it because it is a competitive strategy? Is it highly differentiated? Oracle is a highly differentiated strategy, right? Is Dell highly differentiated? Eh, Dell differentiates based on its breadth. What? >>Right. Well, let's try for the control plane too. Dell wants to be an, >>Their, their vision is differentiated. Okay. But their execution today is not >>High. All right. Let me throw, let me throw this out at you then. I'm I'm, I'm sorry. I'm I'm HPE. I wanna be the glue layer. Is that, does that fly? >>What >>Do you mean? The group glue layer? I'll I wanna be, you can do Amazon, but I wanna be the glue layer between the clouds and our GreenLake will. >>What's the, what's the incremental value that, that glue provides, >>Provides comfort and reliability and control for the single pane of glass for AWS >>And comes back to the data. In my opinion. Yeah. >>There, there there's glue levels on the data level. Yeah. And there's glue levels on API level. Right. And there's different vendors in the different spaces. Right. Um, I think HPE will want to play on the data side. We heard lots of data stuff. We >>Hear that, >>But we have to see it. Exactly. >>Yeah. But it's, it's lacking today. And so, Hey, you know, you guys know better than I APIs can be fragile and they can be, there's a lot of diversity in terms of the quality of APIs and the documentation, how they work, how mature they are, what, how, what kind of performance they can provide and recoverability. And so just saying, oh wow. We are living the API economy. You know, the it's gonna take time to brew, chime in here. Hi. >><laugh> oh, so guys, you've all been covering HPE for a long time. You know, when Antonio stood up on stage three years ago and said by 2022, and here we are, we're gonna be delivering everything as a service. He's saying we've, we've done it, but, and we're a new company. Do you guys agree with that? >>Definitely. >>I, yes. Yes. With the caveat, I think, yes. The COVID pandemic slowed them down a lot because, um, that gave a tailwind to the hyperscalers, um, because of the, the force of massive O under forecasting working at home. I mean, everyone I talked to was like, no one forecasted a hundred percent work at home, the, um, the CapEx investments. So I think that was an opportunity that they'd be much farther along if there's no COVID people >>Thought it wasn't impossible. Yeah. But so we had the old work from home thing right. Where people trying to get people fired at IBM and Yahoo. Right. So I would've this question covering the HR side and my other hat on. Right. And I would ask CHS let's assume, because I didn't know about COVID shame on me. Right. I said, big California, earthquake breaks. Right. Nobody gets hurt, but all the buildings have to be retrofitted and checked for seism logic down. So everybody's working from home, ask CHS, what kind of productivity gap hit would you get by forcing everybody working from home with the office unsafe? So one, one gentleman, I won't know him, his name, he said 20% and the other one's going ha you're smoking. It's 40 50%. We need to be in the office. We need to meet it first night. And now we went for this exercise. Luckily not with the California. Right. Well, through the price of COVID and we've seen what it can do to, to productivity well, >>The productivity, but also the impact. So like with all the, um, stories we've done over two years, the people that want came out ahead were the ones that had good cloud action. They were already in the cloud. So I, I think they're definitely in different company in the sense of they, I give 'em a pass. I think they're definitely a new company and I'm not gonna judge 'em on. I think they're doing great. But I think pandemic definitely slowed 'em down that about >>It. So I have a different take on this. I think. So we've go back a little history. I mean, you' said this, I steal your line. Meg Whitman took one for the Silicon valley team. Right. She came in. I don't think she ever was excited that I, that you said, you said that, and I think you wrote >>Up, get tape on that one. She >>Had to figure out how do I deal with this mess? I have EDS. I got PC. >>She never should have spun off the PC, but >>Okay. But >>Me, >>Yeah, you can, you certainly could listen. Maybe, maybe Gerstner never should have gone all in on services and IBM would dominate something other than mainframes. They had think pads even for a while, but, but, but so she had that mess to deal with. She dealt with it and however, they dealt with it, Antonio came in, he, he, and he said, all right, we're gonna focus the company. And we're gonna focus the mission on not the machine. Remember those yeah. Presentations, but you just make your eyes glaze over. We're going all in on Azure service >>And edge. He was all on. >>We're gonna build our own cloud. We acquired Aruba. He made some acquisitions in HPC to help differentiate. Yep. And they are definitely a much more focused company now. And unfortunately I wish Antonio would CEO in 2015, cuz that's really when this should have started. >>Yeah. And then, and if you remember back then, Dave, we were interviewing Docker with DevOps teams. They had composability, they were on hybrid really early. I think they might have even coined the term hybrid before VMware tri-state credit for it. But they were first on hybrid. They had DevOps, they had infrastructure risk code. >>HPE had an HP had an awesome cloud team. Yeah. But, and then, and then they tried to go public cloud. Yeah. You know, and then, you know, just made them, I mean, it was just a mess. The focus >>Is there. I give them huge props. And I think, I think the GreenLake to me is exciting here because it's much better than it was two years ago. When, when we talked to, when we started, it's >>Starting to get real. >>It's, it's a real thing. And I think the, the tell will be partners. If they make that right, can pull their different >>Ecosystem, >>Their scale and their customers and fill the software gas with partners mm-hmm <affirmative> and then create that integration opportunity. It's gonna be a home run if they don't do that, they're gonna miss the operating, >>But they have to have their own to your point. They have to have their own software innovation. >>They have to good infrastructure ways to build applications. I don't wanna build with somebody else. I don't wanna take a Microsoft stack on open source stack. I'm not sure if it's gonna work with HP. So they have to have an app dev answer. I absolutely agree with that. And the, the big thing for the partners is, which is a good thing, right? Yep. HPE will not move into applications. Right? You don't have to have the fear of where Microsoft is with their vocal large. Right. If AWS kind of like comes up with APIs and manufacturing, right. Google the same thing with their vertical push. Right. So HPE will not have the CapEx, but >>Application, >>As I SV making them, the partner, the bonus of being able to on premise is an attractive >>Part. That's a great point. >>Hold. So that's an inflection point for next 12 months to watch what we see absolutely running on GreenLake. >>Yeah. And I think one of the things that came out of the, the last couple events this past year, and I'll bring this up, we'll table it and we'll watch it. And it's early in this, I think this is like even, not even the first inning, the machine learning AI impact to the industrial piece. I think we're gonna see a, a brand new era of accelerated digital transformation on the industrial physical world, back office, cloud data center, accounting, all the stuff. That's applications, the app, the real world from space to like robotics. I think that HP edge opportunity is gonna be visible and different. >>So guys, Antonio Neri is on tomorrow. This is only day one. If you can imagine this power panel on day one, can you imagine tomorrow? What is your last question for each of you? What is your, what, what question would you want to ask him tomorrow? Hold start with you. >>How is HPE winning in the long run? Because we know their on premise market will shrink, right? And they can out execute Dell. They can out execute Lenovo. They can out Cisco and get a bigger share of the shrinking market. But that's the long term strategy, right? So why should I buy HPE stock now and have a good return put in the, in the safe and forget about it and have a great return 20 years from now? What's the really long term strategy might be unfair because they, they ran in survival mode to a certain point out of the mass post equipment situation. But what is really the long term strategy? Is it more on the hardware side? Is it gonna go on the HPE, the frontier side? It's gonna be a DNA question, which I would ask Antonio. >>John, >>I would ask him what relative to the macro conditions relative to their customer base, I'd say, cuz the customers are the scoreboard. Can they create a value proposition with their, I use the Microsoft 365 example how they kind of went to the cloud. So my question would be Antonio, what is your core value proposition to CIOs out there who want to transform and take a step function, increase for value with HPE? Tell me that story. I wanna hear. And I don't want to hear, oh, we got a portfolio and no, what value are you enabling your customers to do? >>What and what should that value be? >>I think it's gonna be what we were kind of riffing on, which is you have to provide either what their product market fit needs are, which is, are you solving a problem? Is it a pain point is a growth driver. Uh, and what's the, what's that tailwind. And it's obviously we know at cloud we know edge. The story is great, but what's the value proposition. But by going with HPE, you get X, Y, and Z. If they can explain that clearly with real, so qualitative and quantitative data it's home >>Run. He had a great line of the analyst summit today where somebody asking questions, I'm just listening to the customer. So be ready for this Steve jobs photo, listening to the customer. You can't build something great listening to the customer. You'll be good for the next quarter. The next exponential >>Say, what are the customers saying? <laugh> >>So I would make an observation. And my question would, so my observation would be cloud is growing collectively at 35%. It's, you know, it's approaching 200 billion with a big, big four. If you include Alibaba, IBM has actually said, Hey, we're gonna gr they've promised 6% growth. Uh, Cisco I think is at eight or 9% growth. Dow's growing in double digits. Antonio and HPE have promised three to 4% growth. So what do you have to do to actually accelerate growth? Because three to 4%, my view, not enough to answer Holger's question is why should I buy HPE stock? Well, >>If they have product, if they have customer and there's demand and traction to me, that's going to drive the growth numbers. And I think the weak side of the forecast means that they don't have that fit yet. >>Yeah. So what has to happen for them to get above five, 6% growth? >>That's what we're gonna analyze. I mean, I, I mean, I don't have an answer for that. I wish I had a better answer. I'd tell them <laugh> but I feel, it feels, it feels like, you know, HP has an opportunity to say here's the new HPE. Yeah. Okay. And this is what we stand for. And here's the one thing that we're going to do that consistently drives value for you, the customer. And that's gonna have to come into some, either architectural cloud shift or a data thing, or we are your store for blank. >>All of the above. >>I guess the other question is, would, would you know, he won't answer a rude question, would suspending things like dividends and stock buybacks and putting it into R and D. I would definitely, if you have confidence in the market and you know what to do, why wouldn't you just accelerate R and D and put the money there? IBM, since 2007, IBM spent is the last stat. And I'm looking go in 2007, IBM way, outspent, Google, and Amazon and R and D and, and CapEx two, by the way. Yep. Subsequent to that, they've spent, I believe it's the numbers close to 200 billion on stock buyback and dividends. They could have owned cloud. And so look at this business, the technology business by and large is driven by innovation. Yeah. And so how do you innovate if >>You have I'm buying, I'm buying HP because they're reliable high quality and they have the outcomes that I want. Oh, >>Buy their products and services. I'm not sure I'd buy the stock. Yeah. >>Yeah. But she has to answer ultimately, because a public company. Right. So >>Right. It's this job. Yeah. >>Never a dull moment with the three of you around <laugh> guys. Thank you so much for sharing your insights, your, an analysis from day one. I can't imagine what day two is gonna bring tomorrow. Debut and I are gonna be anchoring here. We've got a jam packed day, lots going on, hearing from the ecosystem from leadership. As we mentioned, Antonio is gonna be Tony >>Alma Russo. I'm dying. Dr. >>EDMA as well as on the CTO gonna be another action pack day. I'm excited for it, guys. Thanks so much for sharing your insights and for letting me join this power panel. >>Great. Great to be here. >>Power panel plus me. All right. For Holger, John and Dave, I'm Lisa, you're watching the cube our day one coverage of HPE discover wraps right now. Don't go anywhere, cuz we'll see you tomorrow for day two, live from Vegas, have a good night.

>>The cube presents HPE discover 2022 brought to you by HPE. >>Hey everyone. Welcome to Las Vegas. It's the cube live on the show floor at HPE discover 2022, the first in person discover in three years, there are about 8,000 people here. The keynote was standing room only Lisa Martin here. I got a powerhouse group joining me for this keynote analysis. Dave ante joins us, Keith Townsend, John farrier, guys. Lot of news. It's all about HPE GreenLake. What were some of the things Dave, that stuck out to you? >>Well, I'll tell you right now, I gotta just quote, Antonio OIR said, Neri said four years ago, I declared that the enterprise of the future would be edge centric, cloud enabled and data driven. As a result, we launched HPE GreenLake. It kind of declared victory. Now I would say that what they're talking about and what they announced, I would consider table stakes. You know, I wish it started in 2014. I wish Antonio took over in 2015 instead of 2018, but I have to give credit, he's brought a focus and uh, and a, he think he's amped it up, John. I mean, if he's really prioritizing, uh, the, as a service they're going on in all in they're burning the boats, uh, and it's good. They got a lot of work to do. They >>Got a lot of work to do three years ago, John Antonio stood on this very stage saying we, and by 2022, we're gonna be delivering our entire portfolio as a service here we are with GreenLake. What I wanna get your thoughts on Keith's as well. >>Yeah. Well, first of all, I think that the crowded house was, uh, and a sign of people wanna come back together. So it's, to me, that was the first good news I saw, which was the HP community, their customer base. They're all here. They're glad to be back and forth. So it shows that they, their customer base it's resonating their value proposition of annual recurring revenue as a service plus the contract values with GreenLake are up. So this resonance with the customers, Dave, on the new operating model, that's a great check the box there. Um, I would say that I don't think HP's, as far along as Antonio had hopes, he'd be the pandemic was a setback. Um, but GreenLake is a real shining star. It's, uh, it's producing some green if you will money for them in terms of contracts, but they still got a lot more work to do because they're in a really interesting zone, Dave, because edge the cloud, although relevant and accurate where the, the shift is going, are they really there with, with the goods? And to me, I'm looking forward to seeing this discover if they have it or not. Certainly the messaging's good, but we're gonna UN UN unpeel that onion back and look at it. But >>Keith they're on the curve, right? At least they're on the cloud curve. >>They're absolutely on the curve. They have APIs, they have consistent developer experience. They announced the developer portal. They're developer centric. You can now consume your three par storage array services via a Terraform, uh, provider. They speak the language of cloud practitioners. You might struggle a little bit if I'm a small startup, you know, why would I look towards HPE? They kind of answered that a little bit. They had evil genius as a customer on stage, not a huge organization. A lot of the pushback they've been given is that if I may startup, I can simply go to a AWS portal, launch, a free trial service and run it. HPE kind of buried the lead. They now have, at least they announced preannounced the capability to, to trial GreenLake. So they're moving in the right direction. But you know, it's, it's it's table states. Well, >>Here's the thing. Here's the dynamic day that's going on. This is something that we've got got we're first of we've been covering HPE HP for now 11 years with the cube and look at Amazon's success and look at where Amazon's struggling. If you can say that they're having crossed overs to the enterprise, uh, cuz the enterprises are now just getting up to speed. You're seeing the rise of lack of talent. It certainly changing, uh, cyber security. You can't find talent. Kubernetes, good luck with that. Try to find someone. So you're seeing the enterprise aren't really geared up or staffed up for doing what I call, you know, high end cloud. So the rise of managed services is, is what we're seeing out there right now. You want Kubernetes clusters is a great set of managed services. You want other services? So that's the tell sign that the enterprises H HP's customers are now walking before they can run. They're crawling, they're now they're walking. So it's they have time to get in the Amazon lane in my opinion. Well, you >>Think about the hallmarks of cloud, obviously there's as a service, there's consumption based pricing. There's a developer, you know, friendliness, uh, there's ecosystem, which is really, really important. I think today, a lot of the ecosystem is partners, resellers and managed service providers. And to your point, Keith table stakes are things like single sign on being able to have, you know, a console being able to do it from a, from a URL to your point about startups is really interesting because that's one of the other hallmarks of cloud is you attract startups. And Lisa, we were at the snowflake summit and I asked the same question, can snowflake attract startups with their own super cloud. And what you saw was ecosystem partners developing in the snowflake cloud and monetizing. And that's something that we're waiting to see here. And I, I think they know >>You're suggesting way you suggesting that HP's gonna attract startups. >>Well, >>I, I think that's a sign if they can do that. That's a sign. And, and right now, I mean, you heard the example that Keith Keith gave. Uh, but, but not, not many. >>Yeah. I'm hoping that H I don't think HP is gonna ever attract startups, but I think the opportunity GreenLake affords the ecosystem is build clouds or purpose driven clouds around GreenLake. Mm-hmm <affirmative> whether it's the agreement with Equinix or all the cos and semi clouds, I think GreenLake gets most small CSPs, a leg up or 80% of the way there, where they can add that 20% of the IP and build services around GreenLake. And then that can attract the, the startup >>Or entrepreneurs. So the, the big question is, okay, where are these developers gonna come from? They could come from incumbents inside of companies. You know, the, the, the DevOps crowd from the enterprise, the really ops dev crowd. Right? I mean, yeah, don't you see that as a sort of a form of innovation startup, even though it's not a true startup. >>Yeah. Even though it's not, >>So Todd's making faces over there, we <laugh> >>Look, it, look it, they have >>Listen, if they don't, if they can't >>Do that, no, this is their focus is not startups. I agree with Keith on this one, they have to take care of business, home Depot. They have big customers and they have a lot of SMBs as well. They've got a great channel. H HP's got amazing infrastructure and, and client action going on. They gotta get the operating model, right job one as a service ARR, and then contract value and, and nail that with GreenLake. >>Who's their ideal customer profile. >>Their ideal is their install base. Look what Microsoft did with 365, they were going down. Their stock price was 26. At one point go to the, they went to the cloud 365, moved everything to the cloud and look at the success they're having. HP has the same kind of installed base. They gotta bring them along. They gotta get the operating model, right. And the developers that they're targeting are the ones inside the company and, or manage services that they're gonna go to the ecosystem for. That's where the cloud native comes in. That's where thing kind of comes together. So to me, I'm bullish on the operating model, but I'm skeptical that HP can get that cloud native developer. I haven't seen it yet. I'm looking for it. We're gonna look for it here. >>A key to that is going to be consistently. I, the, one of the things I'm looking for on the tech side, I, I hate to compare what HPE is doing to what VMware did with vCloud error years ago, but vCloud error on the outside looked >>Wonderful. Yes, >>It did. Once you tried to use it, it was just flaky underneath. And that's the part I'm looking to see customers pounding on it and saying, you know what API call after API I call, can I, uh, provision 10,000 pods a day? Does it scale down? Does it scale? And is it consistent? Is it >>Fragile Al roo she's co seasoned veteran? Uh, she was at V VMware cloud. She saw that movie. She gets a Mulligan, Dave. So I think her leadership is impressive. And I think she could bring a lot to the table to your point about don't make that same mistake and they gotta get this architecture, right. If they get the operating model right with GreenLake, they can double down on that and enable the developers that are driving the digital transformation. That to me is the, the key positions that they have to nail. And they do that. The rest is just fringe work. In my opinion, >>The reason why Alma was brought in, sorry, Lisa, it was, and then you gotta chime in here was to really build out that platform so that internal people at HPE can actually build value on top of it and the ecosystem that's her priority. >>We're gonna hear a lot from the ecosystem in the next couple of days, but I wanna get your perspective on, you've been following HPE a long time, all three of you. What are some of the things that you're hearing right now that are differentiators? We were just at Dell technologies. We talking about apex. We saw the big announcement they had with snowflake. We were at snowflake two weeks ago. I wanna get all three of your opinions on what are you seeing? Where is HP leading? >>I mean, HPE and Dell will, both with Dell, with apex are go, they're both gonna differentiate with their strengths. And, you know, for Dell, that's their breadth and their, their portfolio. And for, for HPE, that's their sort of open posture. I mean, John, you, you know this well, uh, that's their, their ecosystem, which I know has to evolve. And to me, their focus, you know, Antonio laid out some of the key differentiators. I, I, I think some of them were kind of, you know, pushing the envelope a little bit. Uh, but, but I think they're focus on as a service burning the, the, the boats telling wall street, this is our business. I think that's their differentiator. Is that they're, they're all in. >>Yeah. I, I think they, they try to highlight it by re announcing their private cloud service. I don't even know why they needed to announce that they have a private cloud. GreenLake is a cloud it's is a private cloud >>With block storage, hit disaster recovery. It's like good >>With like everything you get. But I think the, the key is, is that all of that is available today and you can get it in all kinds of frame of, of formats and, and frames specifically, if I'm a customer and I wanna get outta the data center and you, you know, Dave, we go back and forth about this all the time, and I wanna repatriate some workloads to Kubernetes on prem. I don't need to spend up another data center. I can go to Equinix, get GreenLake min IO, object storage on the back end, HPE lighthouse, all those services that I need for Kubernetes and repatriate my workloads without buying a new data center. And I get it as a service. I can get that Dave from HPE GreenLake, Dell apex is on the way. The >>Other thing they're differentiating with Aruba, that's something that Dell doesn't have. Yeah. And, and that is their edge play, I think is stronger than >>Of the others. Mean the, to me, the differentiator for HP is their, their history. Their channel's amazing. They got great Salesforce and they have serious customers and they have serious customers that have serious problems, uh, cyber security, uh, infrastructure, the security paradigm's changed. Uh, the deployment is changed how they deploy applications in their customer base. So they gotta step up to that challenge. And I think their differentiator is gonna be their size, their field and their ability to bring that operating model. And the hybrid model is a steady state. That's clear multi-cloud is just hybrids stitched together, but hybrid cloud, which is basically on premises and cloud to edge operating model is the number one thing that they need to nail. And if they nail that right, they will have a poll position that they could accelerate on. And again, I'm really gonna be watching how well they could enable cloud native developers, okay. To build modern agile applications while solving those serious problems with those serious customers. So again, I think hybrids spun in their direction. I'm not gonna say they got lucky, cuz they've always been on the hybrid bandwagon since we've been covering them. But I thought they'd be for a long day, but they're lucky to have hybrid. That's good for them. And I think do what Microsoft did convert their customers over and they do that, right? >>I think the key to that is gonna be ecosystem. Again, the developers need to see, especially the data piece, they talk about the cloud operating model. I think they're really moving that direction. The data piece to me is the weakest. Like they'll, they'll make claims that we can do anything that the cloud can do. You can't run snowflake, can't run data bricks, can't run Mongo Atlas. So they gotta figure out that data layer and that's optionality of, of data stores. And they don't have that today. >>Yeah. They, they, they have an announcement coming and I can't pre-announce it, but they're, they've, I've deemed them against it. They have the vision, Emeral data services, their data fabric multi-protocol access is a great start. They need the data network behind it. They need the ability to build a super cloud, a across multiple cloud providers, bringing some Google infos love inside of, uh, right next to your data. They have the hardware, they have the infrastructure, but they don't have the services. >>That's a key thing. I think one, you just brought up great point, Keith, and that is, is that at the end of the day, Dave, we're in a market now where agility and speed can be accomplished by startups or any company and HP's customers. Okay. Can move fast too. Okay. And so whoever can extend that value. If HPE can enable value creation for their customers, that's gonna be truly their, their task at hand, they got the channel, they got some leverage, but at the end of the day, the customers have alternatives now and they can move faster to get the value that they need to solve their serious problems. Uh, like cyber, like scalable infrastructure, like infrastructures code, like data ops, like AI ops, it's all here. And it's all coming really fast. Can GreenLake carry the day. And >>By the way, everything we just said about GreenLake in terms of table stakes and everything else, it applies for Dell. >>Yeah, absolutely. >>No question. It does guys. We have, and jam packed three days. We're gonna be talking with the ecosystem. We're gonna be talking with HPE leaders with customers. You're gonna hear all of these, uh, all this information unpacked over the next three days. We will be right back with our first guest for Dave ante, Keith Townson and John furrier. I'm Lisa Martin. Our first guest joins us momentarily.

>>Good morning, everyone. Welcome back to the Cube's coverage of snowflake summit live from Caesar's forum in Las Vegas, Lisa Martin, with Dave Valante. Dave, we have had an action packed two days here, talking with loads of folks. There's been about 10,000 attendees here, the momentum, the excitement for snowflake, what they're building, what they're, what they've announced is huge. >>I'll tell you like this is a getaway day and there's still decent amount of buzz going on in the ecosystem here and the exhibit hall. And I was just saying, when you walk around Las Vegas, you'd never know the economy's about the tank with, you know, inflation is on the rise. I mean, Vegas is packed. >>It is packed it a lot of shows going on here. We are excited to welcome Patrick Barch, the senior director of product management at capital one software to the program. Patrick, it's great to have you. >>Thank you. It's great to be here. >>So we all know capital one. I love the commercials. I'm sure you have a, a large say in how fun and creative they are. Talk to us about capital one software. This is a new business software business. It >>Is. And so, you know, from our founding days in 1994, capital one has always recognized the power of data and technology to create differentiated experiences for our customers. But about 10 years ago, we declared that we were gonna reinvent the way that we build and use technology. One of the key steps in that journey was migrating from our owned and operated data centers to the public cloud. But in order to do that, we needed to build a number of products and platforms to help us operate at scale because the market just wasn't quite there yet. And so capital one software, which we announced last week, Woohoo is our first foray into bringing some of those cloud and data management products to market. >>Talk to us about you. Capital one is one of Snowflake's longest running and largest customers. How does snowflake help facilitate that >>A couple different ways? So first snowflake is a, it's a super powerful platform. They've changed the game when it comes to leveraging data. At scale in the cloud, we were an early investor. We were, we were one of their biggest customers. They've been a great partner along the way, helping us adopt the platform. But for us, when we adopted back in 2018 ish, we realized that with all of this power comes a lot of responsibility. And so we needed to make sure that we were putting good governance and good controls around our usage of snowflake from the start. And so, you know, we, we, we needed to build some, some tools to help us optimize our, our usage of snowflake. >>Okay. So you basically said we're going all in the cloud. You guys have made huge investments in, in AWS and obviously snowflake. And then now you're, you're sort of taking what you did internally and exposing it almost like, like Amazon did Amazon retail and then that's how AWS was born. Okay, awesome. What kind of results did you see internally in terms of the primary benefit? If I understand it is cost savings, but also better data management, right? Is that fair? >>So the, the totality of what we've built internally covers both cost savings, data management, data security, adherence to data privacy legislation. The product that we announced here at summit is really focused on cost optimization for snowflake, right? And so with these tools, we've been able to save about 27% on our projected snowflake costs. We've been able to save our teams about 50,000 hours of manual effort by reducing the number of change orders that they have to execute manually through automated infrastructure management. We've reduced our cost per query by about 43%. And so really what these enabled us to do is just get really efficient with how we use the system. You know, one, one of the challenges you might run into with snowflake is, is unexpected costs. And so by leveraging these tools, we've been able to make sure that our costs are predictable and consistent from month to month, which enables us to budget appropriately. >>And, and that's 50,000 hours person hours over what period of time >>Have to get back to you on the exact amounts? I mean, >>Years, months, several years. Weeks. Yeah. Yeah. Okay. So, but we're talking about tens and tens of millions of dollars, right? If you, I mean, just assume a hundred bucks an hour for, for a person just fully loaded. I mean, I'll just do that math. Okay. And 20% percent on snowflake cost. So here's, here's the question? Well, well, first of all, what's the vision, what's the like gimme a five year vision for, for the software group at capital one, >>We wanna bring capital one's data and cloud management expertise to the masses. Okay. We've spoken to a number of companies that are trying to follow in our footsteps. We've, we've heard again and again, that our challenges are their challenges. Our, the path that we walked is the path that they're trying to walk in. So we are super excited about bringing all of our expertise to the market. >>So start with cost savings, but the vision transcends cost savings, absolutely going into security, privacy, data management, >>Absolutely absolutely workflow. And the, the, you know, the industry's in a super interesting place now where it's very fragmented. There is a galaxy of tools out there. You, you look around here, there's hundreds and hundreds of different solutions, but they're point solutions. They're all going after an individual piece of the management puzzle. And what we found was that we needed to create these integrated experiences that were aligned to our team's jobs to be done, not necessarily in terms of, you know, a capability like cataloging or quality or entitlements, you know, in order to efficiently operate at scale, you need to string those things together in a way that lets your team get their job done. >>So my last question on this flow is, I dunno if you're familiar with you guys, maybe familiar with Sarah Wong and Martin CASAA published a piece that got, you know, pretty wide viewing and discussion. They are out out of Andreesen, a 16 Z that the cost of good sold for SaaS companies who are born in the cloud are gonna become so overwhelming that they're gonna repatriate and start managing themselves. And they use Dropbox as an example. Now Dropbox is storage. So it's very specific niche, you know, and I've talked to many, many companies like snowflake about this, and they're like, eh, that ain't happening anytime soon. How do you feel about that? Because if you look at SAS companies that are born in the cloud, their gross margins are, you know, they don't get to 90%, but they're healthy, you know, 75, you know, sometimes 78% even snowflakes, you know, end of decade forecast Scarelli has it. I think it's 78%. And the reason it's not higher is because of the cloud cost. You gotta pay the cloud bills, my belief and I've argued, this is that's okay. I can negotiate cloud bills. I can work with tools like yours over time to keep those down. And the cloud guys are gonna be competing with each other, but, but what do you make of that Patrick >>Cloud costs? Aren't gonna go down. Data is expanding at an exponential rate. The scale of data today is orders of magnitude versus what it was in on-prem systems. And so, you know, I don't think the cloud providers are too worried because data is exploding at such a, a crazy pace. And so it really becomes about using all of those resources as efficiently as possible. And, and in the cloud where compute is fully elastic, it scales infinitely instantly on demand. You know, it's all about getting it's, it's, it's all about making sure that if you're spending more, you're getting more business value. There's not wastage in the system. >>Same question, but different. Do you feel like strategically organizations generally in capital one specifically will, will, will optimize their time on optimizing or spend their, their effort optimizing the cloud costs? Or do you feel like long term you can actually be cheaper to manage yourself? In other words, our, our cloud benefits of not doing all that heavy lifting offset that potential, you know, cost equation. >>I mean, you saved just so much time and effort and headache, not having to manage physical infrastructure. And so like, you know, snowflake, you can write a sequel command to create a database. You can write a sequel command to create a data warehouse. Like the market will not give up that level of simplicity for managing infrastructure. And so I think at the end of the day, you're gonna, you're gonna see a focus on efficiency because what you really want your teams to be focused on your old, your old DBA and data engineering teams is focused on driving customer value, not in the weeds of infrastructure management. >>And that's why I think you guys, this is a great business that you're starting. And I think you, I, frankly, I think you're gonna get a lot of competition, which is a good thing that says you're in a great business and you guys are first >>Talk about the customer experience. You know, we are also as consumers demanding, we wanna be able to transact ASAP. We wanna make sure that, you know, on the swipe fraud detection happens, how does the Slingshot help facilitate and improve the customer experience if I'm transacting or I'm gonna sign up or I'm getting a mortgage. >>So with Slingshot, we enable your company, regardless of what you do at, at capital one, we're, we're a bank to build more personalized experiences for customers in a more cost effective way. And so Enno is our, our intelligent, personal banking assistant with snowflake. We're enable Enno to do way more than we were previously for less than we would've without some of these tools. >>And that's a huge competitive differentiator because we expect as consumers and of whatever it is. We want a personalized experience, right? That's relevant. That's gonna offer us products and services that might build upon what we've already done. >>It's it's kind of table stakes these days. Yes. And so with these tools and with snowflake, we were able to onboard our business teams were able to onboard over 400 new use cases over, over that same time period. And so really what it's enabled us to do is unlock the innovative power of our company and create more of these customer experiences. >>How does the customer visualize those, those cost savings? And, and, and do, do, do you have some tooling, maybe it's in the works to help them predict what kind of cost savings they have based on some modeling that >>You do. And absolutely. So we enable teams to enforce good governance around infrastructure management, up front by building rules and enabling their teams to create warehouses, create databases. And then once that infrastructure is up and running, we give them a whole bunch of dashboards that show transparency and to spend, we enable chargebacks to lines of business in today's consumption, driven business models. It's hard to reconcile at the end of the month, if you spent what you thought you spent and, and data costs have gone from CapEx to OPEX and, but not everybody is an expert. And so we look at usage data, we look at usage history and we come up with recommendations for how you can save money by, you know, tweaking this or tweaking that or better optimizing your, your compute. >>Should we expect you as you expand your opportunity to take your expertise and aim it at AWS more broadly, maybe Redshift more specifically, Google GCP, big query Azure, what, what should we expect there? >>You know, there's, there's a lot of opportunity to help companies optimize costs across other cloud providers as well. This, this concept of elastic compute, isn't just specific to snowflake. That's certainly one path that we could go down. You know, we have a lot of expertise in, in data management as well, and data privacy, data security. And so that's that, that's another path as well that, that we have expertise in. And so, you know, I think it's, it's an exciting time we're in, we're in an exciting place, but it's early days, >>Did you do a working backwards document? Can you share that with us? >>Fortunately >>Not five, five or 10 years down the road, you may decide to do that, right? >>Yeah. Let me, let me check with my PR person to see if I'm allowed to share here. That's >>I mean, I think this is gonna be a huge success and, and I think it it's, it's, it follows a lot of the things that we've learned from AWS. Yeah. And you guys have been all in there and, and, you know, it's funny, right? We laugh about working backwards, customer obsession, two pizza teams. I mean, it really has changed the sort of way that we think about developing software and, and managing infrastructures. I, I think you're gonna have a, a huge business and I, I wish you the best. >>I, I appreciate that. And the, the thing, a lot of that statement is, you know, internal teams are now starting to demand consumer great experiences for the tools that they use. Yeah, for sure. And so one of the things that we did was treat our internal associates. Like they were external customers, we applied design thinking, we applied product management, we built our experience in terms of what are you trying to accomplish? And what's getting in your way, because that's what people have come to expect with all of these consumer experiences, >>Collaboration. That's right. What last question for you? What would you say to peers in your, whatever, same industry, other industries that are really trying to figure out how to get their hands on data to become a data company, what would you advise them? Why should they choose >>Snowflake gives you so many building blocks out of the box to help you create a, a well-managed data ecosystem? You know, the simplicity with which you can create new infrastructure, define policies for that infrastructure onboard new users. I mean, it, it's one of the platforms in internally capital one that has the highest NPS score. And so, you know, if you're looking to adopt a, a data cloud platform, I mean, snowflake is certainly high up on the list of what you should be looking at. >>That's >>Awesome. How do you, do you consider this a SA, is it a consumption or how do you price for this? >>So we, we don't have published pricing at the moment, but it is, it is a SAS product. You know, what we can share is it'll, it'll be a, you know, small fraction of, of your, of your total credit spend with snowflake and, and >>You're thinking a subscription or, or haven't figured that out yet, >>It it'll likely be a, a consumption model based on, you know. Okay. >>So the, so, so say, you know, it's funny SAS, I get it. Software's a service, but it, but because it's consumption, I think it's like modern SAS. If I can say that, you know, it's cloud >>SAS and it, it, you know, it's more important to make sure right now, because we're so early that we're actually providing the right value to customers. We have a pretty generous trial program going on right now where you can try the, the, the software out for free to make sure it, it fits your needs. So, >>Okay. So you're in trial, right. I should have clarified that you're in trial now. And, and so, yeah, of course you haven't figured out exactly how you're gonna price it yet. But >>The, the, the official posture that we're taking is public preview. We've, we've been in private preview for the last six months. We've onboarded a, a couple of customers who are starting to use the product. And so the, the big announcement this week is we're officially in public preview, come on in. >>So you gotta get product market fit. That's right. Before you figure out your pricing and before you, then you, then you're gonna scale. Great. >>What's been the feedback so far >>Overwhelmingly positive. Somebody stopped by the booth and said, oh my God, that's so cool. We've heard a lot of, wow, we need this right now. You know, it's, I had pretty, pretty high expectations coming in, just based on the value that this is created for capital one, but I've, I've been blown away by, by what I've heard from the people who've stopped by our booth. >>Awesome. Patrick, thank you for joining Dave and me on the program, talking about what you're doing with capital one software seems like you're just in early innings, but so much potential to come. We wish you the best of luck with that. And you have to come back and tell us how it's going. Thanks so much. Thanks for having me, our pleasure for Dave ante. I'm Lisa Martin. You're watching the cube our day three coverage of snowflake summit 22 live from Las Vegas continues after a short break.

>>from around the globe. It's the >>cube with digital >>coverage of IBM >>Think 2021 brought to you >>by IBM. Welcome back everyone to the cube coverage of IBM Think 2021 virtual um john for your host of the cube. Our next guest taylor Holloway. Chief technology officer at advent one. Tyler welcome to the cube from down under in Australia and we're in Palo alto California. How are you? >>Well thanks john thanks very much. Glad to be glad to be on here. >>Love love the virtual cube of the virtual events. We can get to talk to people really quickly with click um great conversation here around hybrid cloud, multi cloud and all things software enterprise before we get started. I wanna take a minute to explain what you guys do at advent one. What's the main focus? >>Yeah. So look we have a lot of customers in different verticals. Um so you know generally what we provide depends on the particular industry the customers in. But generally speaking we see a lot of demand for operational efficiency, helping our clients tackle cyber security risks, adopt cloud and set them up to modernize the applications. >>And this is this has been a big wave coming in for sure with you know, cloud and scale. So I gotta ask you, what are the main challenges that you guys are solvent for your customers um and how are you helping them overcome come that way and transformative innovative way? >>Yeah, look, I think helping our clients um improve their security posture is a big one. We're finding as well that our customers are gaining a lot of operational efficiency by adopting sort of open source technology red huts an important partner of ours as his IBM um and we're seeing them sort of move away from some more proprietary solutions. Automation is a big focus for us as well. We've had some great outcomes with our clients or helping them automate um and you know, to live up um you know the stand up and data operations of environments a lot quickly a lot more easily and uh and to be able to sort of apply some standards across multiple sort of areas of their I. T. Estate. >>What are some of the solutions that you guys are doing with IBM's portfolio on the infrastructure side, you got red hat, you've got a lot of open source stuff to meet the needs of clients. What do you mean? What's the mean? >>Uh Yeah I think on the storage side will probably help our clients sort of tackle the expanding data in structured and particularly unstructured data they're trying to take control of so you know, looking at spectrum scale and those type of products from an audio perspective for unstructured data is a good example. And so they're flush systems for more block storage and more run of the mill sort of sort of environments. We have helped our clients consolidate and modernize on IBM power systems. Having Red Hat is both a Lynx operating system and having open shift as a container platform. Um really helps there. And Red Hat also provides management overlay, which has been great on what we do with IBM power systems. We've been working on a few different sort of use cases on power in particular. More recently, SAP Hana is a big one where we've had some success with our clients migrating Muhanna on to onto IBM power systems. And we've also helped our customers, you know, improve some um some environments on the other end of the side, such as IBM I, we still have a large number of customers with, with IBM I and and you know how do we help them? You know some of them are moving to cloud in one way or another others are consuming some kind of IRS and we can sort of wrap around a managed service to to help them through. >>So I gotta ask you the question, you know U C T. Oh you played a lot of technologies kubernetes just become this lingua franca for this kind of like I'll call a middleware kind of orchestration layer uh containers. Also you're awesome but I gotta ask you when you walk into a client's environment you have to name names but you know usually you see kind of two pictures man, they need some serious help or they got their act together. So either way they're both opportunities for Hybrid cloud. How do you how do you how do you evaluate the environment when you go in, when you walk into those two scenarios? What goes through your mind? What some of the conversations that you guys have with those clients. Can you take me through a kind of day in the life of both scenarios? The ones that are like I can't get the job done, I'm so close in on the right team and the other ones, like we're grooving, we're kicking butt. >>Yeah. So look, let's start well, I supposed to start off with you try and take somewhat of a technology agnostic view and just sort of sit down and listen to what they're trying to achieve, how they're going for customers who have got it. You know, as you say, all nailed down things are going really well. Um it's just really understanding what what can we do to help. Is there an opportunity for us to help at all like there? Um, you know, generally speaking, there's always going to be something and it may be, you know, we don't try and if someone is going really well, they might just want someone to help with a bespoke use case or something very specific where they need help. On the other end of the scale where a customer is sort of pretty early on and starting to struggle. We generally try and help them not boil the ocean at once. Just try and get some winds, pick some key use cases, you know, deliver some value back and then sort of growing from there rather than trying to go into a customer and trying to do everything at once tends to be a challenge. Just understand what the priorities are and help them get going. >>What's the impact been for red hat? Um, in your customer base, a lot of overlap. Some overlap, no overlap coming together. What's the general trend that you're seeing? What's the reaction been? >>Yeah I think it's been really good. Obviously IBM have a lot of focus on cloud packs where they're bringing their software on red hat open shift that will run on multiple clouds. So I think that's one that we'll see a lot more of overtime. Um Also helping customers automate their I. T. Operations with answerable is one we do quite a lot of um and there's some really bespoke use cases we've done with that as well as some standardized one. So helping with day two operations and all that sort of thing. But there's also some really sort of out there things customers have needed to automate that's been a challenge for them and being able to use open source tools to do it has worked really well. We've had some good wins there, >>you know, I want to ask you about the architecture and I'm just some simplify it real. Just for the sake of devops, um you know, segmentation, you got hybrid clouds, take a programmable infrastructure and then you've got modern applications that need to have a I some have said I've even sit on the cube and other broadcast that if you don't have a I you're gonna be at a handicap some machine learning, some data has to be in there. You can probably see ai and mostly everything as you go in and try to architect that out for customers um and help them get to a hybrid cloud infrastructure with real modern application front end with using data. What's what's the playbook? Do you have any best practices or examples you can share or scenarios or visions that you see uh playing >>out? I think you're the first one is obviously making sure customers data is in the right place. So if they might be wanting to use um some machine learning in one particular cloud provider and they've got a lot of their applications and data in another, you know, how do we help them make it mobile and able to move data from one cloud to another or back into court data center? So there's a lot of that. I think that we spend a lot of time with customers to try and get a right architecture and also how do we make sure it's secure from end to end. So if they're moving things from into multiple one or more public clouds as well as maybe in their own data center, making sure connectivity is all set up properly. All the security requirements are met. So I think we sort of look at it from a from a high level design point of view, we look at obviously what the target state is going to be versus the current state that really take into account security, performance, connectivity or those sort of things to make sure that they're going to have a good result. >>You know, one of the things you mentioned and this comes up a lot of my interviews with partners of IBM is they always comment about their credibility and all the other than the normal stuff. But one of the things that comes out a lot pretty much consistently is their experience in verticals. Uh they have such a track record in verticals and this is where AI and machine learning data has to be very much scoped in on the vertical. You can't generalize and have a general purpose data plane inside of vertically specialized kind of focus. How how do you see that evolving, how does IBM play there with this kind of the horizontally scalable mindset of a hybrid model, both on premise in the cloud, but that's still saying provide that intimacy with the data to fuel the machine learning or NLP or power that ai which seems to be critical. >>Yeah, I think there's a lot of services where you know, public cloud providers are bringing out new services all the time and some of it is pre can and easy to consume. I think what IBM from what I've observed, being really good at is handling some of those really bespoke use cases. So if you have a particular vertical with a challenge, um you know, there's going to be sort of things that are pre can that you can go and consume. But if you need to do something custom that could be quite challenging. How do they sort of build something that could be quite specific for a particular industry and then obviously being able to repeat that afterwards for us, that's obviously something we're very interested in. >>Yeah, tell I love chatting whether you love getting the low down also, people might not know your co author of a book performance guy with IBM Power Systems, So I gotta ask you, since I got you here and I don't mean to put you on the spot, but if you can just share your vision or any kind of anecdotal observation as people start to put together their architecture and again, you know, Beauty's in the eye of the beholder, every environment is different. But still, hybrid, distributed concept is distributed computing. Is there a KPI is there a best practice on as a manager or systems architect to kind of keep an eye on what what good is and how how good becomes better because the day to operations becomes a super important concept. We're seeing some called Ai ops where okay, I'm provisioning stuff out on a hybrid Cloud operational environment. But now day two hits are things happen as more stuff entered into the equation. What's your vision on KPs and management? What to keep tracking? >>Yeah, I think obviously attention to detail is really important to be able to build things properly. A good KPI particularly managed service area that I'm curious that understanding is how often do you actually have to log into the systems that you're managing? So if you're logging in and recitation into servers and all this sort of stuff all the time, all of your automation and configuration management is not set up properly. So, really a good KPI an interesting one is how often do you log into things all the time? If something went wrong, would you sooner go and build another one and shoot the one that failed or go and restore from backup? So thinking about how well things are automated. If things are immutable using infrastructure as code, those are things that I think are really important when you look at, how is something going to be scalable and easy to manage going forward. What I hate to see is where, you know, someone build something and automates it all in the first place and they're too scared to run it again afterwards in case it breaks something. >>It's funny the next generation of leaders probably won't even know like, hey, yeah, taylor and john they had to log into systems back in the day. You know, I mean, I could be like a story they tell their kids. Uh but no, that's a good Metro. This is this automation. So it's on the next level. Let's go the next level automation. Um what's the low hanging fruit for automation? Because you're getting at really the kind of the killer app there, which is, you know, self healing systems, good networks that are programmable but automation will define more value. What's your take? >>I think the main thing is where you start to move from a model of being able to start small and automate individual things which could be patching or system provisioning or anything like that. But what you really want to get to is to be able to drive everything through, get So instead of having a written up paper, change request, I'm going to change your system and all the rest of it. It really should be driven through a pull request and have things through it and and build pipelines to go and go and make a change running in development, make sure it's successful and then it goes and gets pushed into production. That's really where I think you want to get to and you can start to have a lot of people collaborating really well on this particular project or a customer that also have some sort of guard rails around what happens in some level of governance rather than being a free for all. >>Okay, final question. Where do you see event one headed? What's your future plans to continue to be a leader? I. T. Service leader for this guy? BMS Infrastructure portfolio? >>I think it comes down to people in the end, so really making sure that we partner with our clients and to be well positioned to understand what they want to achieve and and have the expertise in our team to bring to the table to help them do it. I think open source is a key enabler to help our clients adopt a hybrid cloud model to sort of touched on earlier uh as well as be able to make use of multiple clouds where it makes sense from a managed service perspective. I think everyone is really considering themselves and next year managed service provider. But what that means for us is to provide a different, differentiated managed service and also have the strong technical expertise to back it up. >>Taylor Holloway, chief technology officer advent one remote videoing in from down under in Australia. I'm john ferrier and Palo alto with cube coverage of IBM thing. Taylor, thanks for joining me today from the cube. >>Thank you very much. >>Okay, cube coverage. Thanks for watching ever. Mhm mm

>>Yeah, >>yeah. Hello and welcome to this track to creating engaging analytics experiences for all. I'm Hannah Sinden Thought spots Omiya director of marketing on. I'm delighted to have you here today. A boy Have we got to show for you now? I might be a little bit biased as the host of this track, but in my humble opinion, you've come to a great place to start because this track is all about everything. Thought spot. We'll be talking about embedded search in a I thought spot one spot I. Q. We've got great speakers from both thoughts about andare customers as well as some cool product demos. But it's not all product talk. We'll be looking at how to leverage the tech to give your users a great experience. So first up is our thoughts about one deep dive. This session will be showing you how we've built on our already superb search experience to make it even easier for users across your company to get insight. We've got some great speakers who are going to be telling you about the cool stuff they've been working on to make it really fantastic and easy for non technical people to get the answers they need. So I'm really delighted to introduce Bob Baxley s VP of design and experience That thought spot on Vishal Kyocera Thought spots director of product management. So without further ado, I'll hand it over to Bob. Thanks, >>Hannah. It's great to be here with everybody today and really excited to be able to present to you thought spot one. We've been working on this for months and months and are super excited to share it before we get to the demo with Shawl, though, I just want to set things up a little bit to help people understand how we think about design here. A thought spot. The first thing is that we really try to think in terms of thought. Spot is a consumer grade product, terms what we wanted. Consumer grade you x for an analytics. And that means that for reference points rather than looking at other enterprise software companies, we tend to look at well known consumer brands like Google, YouTube and WhatsApp. We firmly believe that people are people, and it doesn't matter if they're using software for their own usage or thought are they're using software at work We wanted to have a great experience. The second piece that we were considering with thoughts about one is really what we call the desegregation of bundles. So instead of having all of your insights wraps strictly into dashboards, we want to allow users to get directly to individual answers. This is similar to what we saw in music. Were instead of you having to buy the entire album, of course, you could just buy individual songs. You see this in iTunes, Spotify and others course. Another key idea was really getting rid of gate keepers and curators and kind of changing people from owning the information, helping enable users to gather together the most important and interesting insights So you can follow curator rather than feeling like you're limited in the types of information you can get. And finally, we wanted to make search the primary way, for people are thinking about thought spot. As you'll see, we've extended search from beyond simply searching for your data toe, also searching to be able to find pin boards and answers that have been created by other people. So with that, I'll turn it over to my good friend Rachel Thio introduce more of thought, spot one and to show you a demo of the product. >>Thank you, Bob. It's a pleasure to be here to Hello, everyone. My name is Michelle and Andy, product management for Search. And I'm really, really excited to be here talking about thoughts about one our Consumer analytics experience in the Cloud. Now, for my part of the talk, we're gonna first to a high level overview of thoughts about one. Then we're going to dive into a demo, and then we're gonna close with just a few thoughts about what's coming next. So, without any today, let's get started now at thought spot. Our mission is to empower every user regardless of their expertise, to easily engage with data on make better data driven decisions. We want every user, the nurse, the neighborhood barista, the teacher, the sales person, everyone to be able to do their jobs better by using data now with thoughts about one. We've made it even more intuitive for all these business users to easily connect with the insights that are most relevant for them, and we've made it even easier for analysts to do their jobs more effectively and more efficiently. So what does thoughts about one have? There's a lot off cool new features, but they all fall into three main categories. The first main category is enhanced search capabilities. The second is a brand new homepage that's built entirely for you, and the third is powerful tools for the analysts that make them completely self service and boost their productivity. So let's see how these work Thought Spot is the pioneer for search driven analytics. We invented search so that business users can ask questions of data and create new insights. But over the years we realized that there was one key piece off functionality that was missing from our search, and that was the ability to discover insights and content that had already been created. So to clarify, our search did allow users to create new content, but we until now did not have the ability to search existing content. Now, why does that matter? Let's take an example. I am a product manager and I am always in thought spot, asking questions to better understand how are users are using the product so we can improve it now. Like me, A lot of my colleagues are doing the same thing. Ah, lot of questions that I asked have already been answered either completely are almost completely by many of my colleagues, but until now there's been no easy way for me to benefit from their work. And so I end up recreating insights that already exists, leading to redundant work that is not good for the productivity off the organization. In addition, even though our search technology is really intuitive, it does require a little bit of familiarity with the underlying data. You do need to know what metric you care about and what grouping you care about so that you can articulate your questions and create new insights. Now, if I consider in New employees product manager who joins Hotspot today and wants to ask questions, then the first time they use thought spot, they may not have that data familiarity. So we went back to the drawing board and asked ourselves, Well, how can we augment our search so that we get rid off or reduced the redundant work that I described? And in addition, empower users, even new users with very little expertise, maybe with no data familiarity, to succeed in getting answers to their questions the first time they used Hot Spot, and we're really proud and excited to announce search answers. Search answers allows users to search across existing content to get answers to their questions, and its a great compliment to search data, which allows them to search the underlying data directly to create new content. Now, with search answers were shipping in number of cool features like Answer Explainer, Personalized search Results, Answer Explorer, etcetera that make it really intuitive and powerful. And we'll see how all of these work in action in the demo. Our brand new homepage makes it easier than ever for all these business users to connect with the insights that are most relevant to them. These insights could be insights that these users already know about and want to track regularly. For example, as you can see, the monitor section at the top center of the screen thes air, the KP eyes that I may care most about, and I may want to look at them every day, and I can see them every day right here on my home page. By the way, there's a monitoring these metrics in the bankrupt these insights that I want to connect with could also be insights that I want to know more about the search experience that I just spoke about ISS seamlessly integrated into the home page. So right here from the home page, I can fire my searchers and ask whatever questions I want. Finally, and most interestingly, the homepage also allows me to connect with insights that I should know about, even if I didn't explicitly ask for them. So what's an example? If you look at the panel on the right, I can discover insights that are trending in my organization. If I look at the panel on the left, I can discover insights based on my social graph based on the people that I'm following. Now you might wonder, How do we create this personalized home page? Well, our brand new, personalized on boarding experience makes it a piece of cake as a new business user. The very first time I log into thought spot, I pay three people I want to follow and three metrics that I want to follow, and I picked these from a pool of suggestions that Ai has generated. And just like that, the new home page gets created. And let's not forget about analysts. We have a personalized on boarding experience specifically for analysts that's optimized for their needs. Now, speaking of analysts, I do want to talk about the tools that I spoke off earlier that made the analysts completely self service and greatly boost their productivity's. We want analysts to go from zero to search in less than 30 minutes, and with our with our new augmented data modeling features and thoughts about one, they can do just that. They get a guided experience where they can connect, model and visualize their data. With just a few clicks, our AI engine takes care off a number of tasks, including figuring out joints and, you know, cleaning up column names. In fact, our AI engine also helps them create a number of answers to get started quickly so that these analysts can spend their time and energy on what matters most answering the most complicated and challenging and impactful questions for the business. So I spoke about a number of different capabilities off thoughts about one, but let's not forget that they are all packaged in a delightful user experience designed by Bob and his team, and it powers really, really intuitive and powerful user flows, from personalized on boarding to searching to discover insights that already exist on that are ranked based on personalized algorithms to making refinements to these insights with a assistance to searching, to create brand new insights from scratch. And finally sharing all the insights that you find interesting with your colleagues so that it drives conversations, decisions and, most importantly, actions so that your business can improve. With that said, let's drive right into the demo for this demo. We're going to use sales data set for a company that runs a chain off retail stores selling apparel. Our user is a business user. Her name is Charlotte. She's a merchandiser, She's new to this company, and she is going to be leading the genes broader category. She's really excited about job. She wants to use data to make better decisions, so she comes to thought spot, and this is what she sees. There are three main sections on the home page that she comes to. The central section allows you to browse through items that she has access to and filter them in various ways. Based for example, on author or on tags or based on what she has favorited. The second section is this panel on the right hand side, which allows her to discover insights that are trending within her company. This is based on what other people within her company are viewing and also personalized to her. Finally, there's this search box that seamlessly integrated into the home page. Now Charlotte is really curious to learn how the business is doing. She wants to learn more about sales for the business, so she goes to the search box and searches for sales, and you can see that she's taken to a page with search results. Charlotte start scanning the search results, and she sees the first result is very relevant. It shows her what the quarterly results were for the last year, but the result that really catches her attention is regional sales. She'd love to better understand how sales are broken down by regions. Now she's interested in the search result, but she doesn't yet want to commit to clicking on it and going to that result. She wants to learn more about this result before she does that, and she could do that very easily simply by clicking anywhere on the search result card. Doing that reveals our answer. Explain our technology and you can see this information panel on the right side. It shows more details about the search results that she selected, and it also gives her an easy to understand explanation off the data that it contains. You can see that it tells her that the metrics sales it's grouped by region and splitter on last year. She can also click on this preview button to see a preview off the chart that she would see if she went to that result. It shows her that region is going to be on the X axis and sales on the Y axis. All of this seems interesting to her, and she wants to learn more. So she clicks on this result, and she's brought to this chart now. This contains the most up to date data, and she can interact with this data. Now, as she's looking at this data, she learns that Midwest is the region with the highest sales, and it has a little over $23 million in sales, and South is the region with the lowest sales, and it has about $4.24 million in sales. Now, as Charlotte is looking at this chart, she's reminded off a conversation she had with Suresh, another new hire at the company who she met at orientation just that morning. Suresh is responsible for leading a few different product categories for the Western region off the business, and she thinks that he would find this chart really useful Now she can share this chart with Suresh really easily from right here by clicking the share button. As Charlotte continues to look at this chart and understand the data, she thinks, uh, that would be great for her to understand. How do these sales numbers across regions look for just the genes product category, since that's the product category that she is going to be leading? And she can easily narrow this data to just the genes category by using her answer Explorer technology. This panel on the right hand side allows her to make the necessary refinements. Now she can do that simply by typing in the search box, or she can pick from one off the AI generated suggestions that are personalized for her now. In this case, the AI has already suggested genes as a prototype for her. So with just a single click, she can narrow the data to show sales data for just jeans broken down by region. And she can see that Midwest is still the region with the highest sales for jeans, with $1.35 million in sales. Now let's spend a minute thinking about what we just saw. This is the first time that Charlotte is using Thought spot. She does not know anything about the data sources. She doesn't know anything about measures or attributes. She doesn't know the names of the columns. And yet she could get to insights that are relevant for her really easily using a search interface that's very much like Google. And as she started interacting with search results, she started building a slightly better understanding off the underlying data. When she found an insight that she thought would be useful to a colleague offers, it was really seamless for her to share it with that colleague from where she Waas. Also, even though she's searching over content that has already been created by her colleagues in search answers. She was in no way restricted to exactly that data as we just saw. She could refine the data in an insight that she found by narrowing it. And there's other things you can do so she could interact with the data for the inside that she finds using search answers. Let's take a slightly more complex question that Charlotte may have. Let's assume she wanted to learn about sales broken down by, um, by category so that she can compare her vertical, which is jeans toe other verticals within the company. Again, she can see that the very first result that she gets is very relevant. It shows her search Sorry, sales by category for last year. But what really catches her attention about this result is the name of the author. She's thrilled to note that John, who is the author of this result, was also an instructor for one off for orientation sessions and clearly someone who has a lot of insight into the sales data at this company. Now she would love to see mawr results by John, and to do that, all she has to do is to click on his name now all of the search results are only those that have been authored by John. In fact, this whole panel at the top of the results allow her to filter her search results or sort them in different ways. By clicking on these authors filter, she can discover other authors who are reputed for the topic that she's searching for. She can also filter by tags, and she can sort these results in different ways. This whole experience off doing a search and then filtering search results easily is similar to how we use e commerce search engines in the consumer world. For example, Amazon, where you may search for a product and then filter by price range or filter by brand. For example, Let's also spend a minute talking about how do we determine relevance for these results and how they're ranked. Um, when considering relevance for these results, we consider three main categories of things. We want to first make sure that the result is in fact relevant to the question that the user is asking, and for that we look at various fields within the result. We look at the title, the author, the description, but also the technical query underpinning that result. We also want to make sure that the results are trustworthy, because we want users to be able to make business decisions based on the results that they find. And for that we look at a number of signals as well. For example, how popular that result is is one of those signals. And finally, we want to make sure the results are relevant to the users themselves. So we look at signals to personalize the result for that user. So those are all the different categories of signals that we used to determine overall ranking for a search result. You may be wondering what happens if if Charlotte asks a question for which nobody has created any answer, so no answers exist. Let's say she wants to know what the total sales of genes for last year and no one's created that well. It's really easy for her to switch from searching for answers, which is searching for content that has already been created to searching the data directly so she can create a new insight from scratch. Let's see how that works. She could just click here, and now she's in the search data in her face and for the question that I just talked about. She can just type genes sales last year. And just like that, she could get an answer to her question. The total sales for jeans last year were almost $4.6 million. As you can see, the two modes off search searching for answers and searching, the data are complementary, and it's really easy to switch from one to the other. Now we understand that some business users may not be motivated to create their own insights from scratch. Or sometimes some of these business users may have questions that are too complicated, and so they may struggle to create their own inside from scratch. Now what happens usually in these circumstances is that these users will open a ticket, which would go to the analyst team. The analyst team is usually overrun with these tickets and have trouble prioritizing them. And so we started thinking, How can we make that entire feedback loop really efficient so that analysts can have a massive impact with as little work as possible? Let me show you what we came up with. Search answers comes with this system generated dashboard that analysts can see to see analytics on the queries that business users are asking in search answers so it contains high level K P. I is like, You know how many searches there are and how many users there are. It also contains one of the most popular queries that users are asking. But most importantly, it contains information about what are popular queries where users are failing. So the number on the top right tells you that about 10% off queries in this case ended with no results. So the user clearly failed because there were no results on the table. Right below it shows you here are the top search queries for original results exist. So, for example, the highlighted row there says jean sales with the number three, which tells the analysts that last week there were three searches for the query jean sales and the resulted in no results on search answers. Now, when an analyst sees a report like this, they can use it to prioritize what kind of content they could be creating or optimizing. Now, in addition to giving them inside into queries which led to no results or zero results. This dashboard also contains reports on creatives that lead to poor results because the user did get some results but didn't click on anything, meaning that they didn't get the answer that they were looking for. Taking all these insights, analysts can better prioritize and either create or optimize their content to have maximum impact for their business users with the least amount of for. So that was the demo. As you can see with search answers, we've created a very consumer search interface that any business user can use to get the answers to their questions by leveraging data or answers that have already been created in the system by other users in their organization. In addition, we're creating tools that allow analysts toe create or optimized content that can have the highest impact for these business users. All right, so that was the demo or thoughts about one and hope you guys liked it. We're really excited about it. Now Let me just spend a minute talking about what's coming next. As I've mentioned before, we want to connect every business user with the insights that are most relevant for them, and for that we will continue to invest in Advanced AI and personalization, and some of the ways you will see it is improved relevance in ranking in recommendations in how we understand your questions across the product within search within the home page everywhere. The second team that will continue to invest in is powerful analyst tools. We talked about tools and, I assure you, tools that make the analysts more self service. We are committed to improving the analyst experience so that they can make the most off their time. An example of a tool that we're really excited about is one that allows them to bridge the vocabulary difference that this even business user asks questions. A user asked a question like revenue, but the column name for the metric in the data set its sales. Now analysts can get insights into what are the words that users air using in their questions that aren't matching anything in the data set and easily create synonyms so that that vocabulary difference gets breached. But that's just one example of how we're thinking about empowering the analysts so that with minimal work, they can amplify their impact and help their business users succeed. So there's a lot coming, and we're really excited about how we're planning to evolve thoughts about one. With all that said, Um, there's just, well, one more thing that my friend Bob wants to talk to you guys about. So back to you, Bob. >>Thanks, Michelle. It's such a great demo and so fun to see all the new work that's going on with thought. Spot one. All the happenings for the new features coming out that will be under the hood. But of course, on the design side, we're going to continue to evolve the front end as well, and this is what we're hoping to move towards. So here you'll see a new log in screen and then the new homepage. So compared to the material that you saw just a few minutes ago, you'll notice this look is much lighter. A little bit nicer use of color up in the top bar with search the features over here to allow you to switch between searching against answers at versus creating new answers, the settings and user profile controls down here and then on the search results page itself also lighter look and feel again. Mork color up in the search bar up the top. A little bit nicer treatments here. We'll continue to evolve the look and feel the product in coming months and quarters and look forward to continue to constantly improving thoughts about one Hannah back to you. >>Thanks, Bob, and thank you both for showing us the next generation of thought spot. I'd love to go a bit deeper on some of the points you touched on there. I've got a couple of questions here. Bob, how do you think about designing for consumer experience versus designing for enterprise solutions? >>Yes, I mentioned Hannah. We don't >>really try to distinguish so much between enterprise users and consumer users. It's really kind of two different context of use. But we still always think that users want some product and feature and experience that's easy to use and makes sense to them. So instead of trying to think about those is two completely different design processes I think about it may be the way Frank Lloyd Wright would approached architecture. >>Er I >>mean, in his career, he fluidly moved between residential architecture like falling water and the Robie House. But he also designed marquis buildings like the Johnson wax building. In each case, he simply looked at the requirements, thought about what was necessary for those users and designed accordingly. And that's really what we do. A thought spot. We spend time talking to customers. We spend time talking to users, and we spent a lot of time thinking through the problem and trying to solve it holistically. And it's simply a possible >>thanks, Bob. That's a beautiful analogy on one last question for you. Bischel. How frequently will you be adding features to this new experience, >>But I'm glad you asked that, Hannah, because this is something that we are really really excited about with thoughts about one being in the cloud. We want to go really, really fast. So we expect to eventually get to releasing new innovations every day. We expect that in the near future, we'll get to, you know, every month and every week, and we hope to get to everyday eventually fingers crossed on housing. That can happen. Great. Thanks, >>Michelle. And thank you, Bob. I'm so glad you could all join us this morning to hear more about thoughts about one. Stay close and get ready for the next session. which will be beginning in a few minutes. In it will be introduced to thoughts for >>everywhere are >>embedded analytics product on. We'll be hearing directly from our customers at Hayes about how they're using embedded analytics to help healthcare providers across billing compliance on revenue integrity functions. To make more informed decisions on make effective actions to avoid risk and maximize revenue. See you there.

>> Announcer: From around the globe. It's theCUBE. With digital coverage of AWS re-invent 2020 sponsored by Intel, AWS, and our community partners. >> Hi, welcome to theCUBE virtual and our coverage of AWS reinvent 2020. We are theCUBE virtual and I'm your host Keith Townsend. Today I'm joined with Melanie Frank who is managing VP of technology at Capital One. Welcome to theCUBE Melanie >> Thanks for having me glad to be here. >> So first time on theCUBE, but you guys have done something big at Capital One. So we're not going to take it easy on you. This is, this has been hitting the news cycles. You guys have closed down your last data center. What spurred the, the initiative for Capital One to exit to private data center. >> Oh, there's so many cool technology, you think that we'll talk about, but you know, if you want to talk about why that is not tech for the sake of tech in this case, this is about working back from, from what our customer needs are. So I think of how the digital world has transformed our expectations as consumers, right. I, I actually was, I use a digital assistant a lot in the kitchen. And so the other day I was cooking and, you know, I update a shopping list to set a timer. I'm just used to doing those things. And the other day I actually asked my digital assistant to set my stove to 350 degrees, which I do not have a smart stove. It's not integrated with my digital assistant, nothing in my home has that capability right now, but it really kind of struck me as a wow, this whole, like this, this interaction has changed my expectations now for my entire kitchen. And I think that those types of experiences now are what we've come to expect as consumers. And that really was the center of it for us, our shift to cloud and exit of the data centers was all about our ability to provide our customers with experiences that are real-time and intelligent that you just can't do, if you're running on outdated technology in a data center. >> So I absolutely understand the benefits of when you're there. The other day, I was bringing up another circuit in our data center and I'm thinking our virtual data center and I'm thinking, wow, man, this is so easy. I can just issue a command software defined. And now the data centers has redundant connectivity, but getting there is a process can you talk to us about the process and how long it took for Capital One to actually reach that goal. >> Yeah, you know, you're so right. Like it is so nice once you're there, but it is not to be underestimated the, the transformational aspect of this, so this was a part of a massive eight year technology transformation, really. That was about modernizing the way in which we worked as well as the tech infrastructure itself. So our goal was to get to this destination where we were faster and more nimble, like you described with those new capabilities for those customers. But we're talking about this eight year transformation where we transformed our talent. We had to hire product managers, data scientists, designers. We shifted our developer skill sets. We're now sitting at an 11,000 person tech organization with 85% of that being, you know, engineers, we shifted the way we work to agile, is it is just much more conducive to that rapid delivery of value. And then of course, on the tech side, really since about 2014, we've closed eight data centers and rebuilt thousands of applications to take full advantage of the cloud technology and capabilities. >> Cool. So it goes without saying, you guys won the world's biggest financial organizations and you've highlighted the non-technical part of the journey. Can you provide a little bit of insight for us on the, kind of the, your partners within the bank, not just technologists in the technology organization, how was this not necessarily disruptive, but changing, you know, groups like audit your financial services. You're constantly worried about audit. How did audit embraced this change? >> Well, I think there was a huge learning for the entire organization to think about what, what parts of what we do need to be done differently. In some ways there were a lot of benefits if I think about our business partners in the finance team where, you know, you had a data center running with massive amounts of technology infrastructure, perhaps you had to size that technology infrastructure for your peak loads, for us during, you know, holiday shopping periods and things like that. And now we're at a position where we can much more nimbly control the tech. We can audit scale up, we can audit scale down that is much more cost-effective for us, for our business. And then from a financial perspective, you just take that use case for the finance department it's, you know, adjusting so that we can directly show that cost to the line of business and allow them to make the changes that they need, which makes sense for their business and their customers. >> So let's talk about more of that process and the journey from a technology perspective, as we look at something as mature as a bank's infrastructure, not all of those applications can be migrated easily and re-platformed easily. How did you guys deal with those tough last to move application, you know, that last 20%? >> Yeah. I think, you know, it early with that, for us with a declaration that, you know, kind of I'll say the easier part, anything new gets built into the cloud. And as you point out that is way easier than tackling some of those things that you you've probably been dealing with and tackling for a very, very long time, from an application standpoint. We knew early on that it would be better if we could modernize the applications themselves as we moved them to the cloud to really kind of unlock the advantages because there's one part of the advantages of the cloud infrastructure. There is a second part of what it forced was a application modernization and a tech modernization for us. And so those two things together were super powerful. We had a few stubborn ones that we said, okay, can we containerize this? Can we lift and shift this over it's, to me, it was likening to, you know, moving from one house to another and you've, you're kind of cleaning out your attic and you're trying to figure out, ideally, you don't take anything to the new house that you don't need and you do all this cleanup. And at some point you say, well, this I'm going to put in this box and I will deal with it kind of at the new house. And ideally you do that before you put it right back in the attic. So we had a few of those, but in large part, you know, 85%, I think that's, that's part of why it took us so long was let's, let's do this right. And let's get, get this so that these applications can run effectively and take full advantage of the cloud. >> So let's talk about some of the potential benefits and the past eight to nine months. My relationship with my commercial banker, with my private banker have really changed due to the pandemic. Talk to me about some of the advantages or capabilities the bank has gained as a result of moving all almost all. Well now totally to the public cloud. >> Yeah. Yeah. It's a good question. I think I'll start with one that is a little bit more technically oriented then talk about the capabilities. So, you mentioned the pandemic and we had, you know massive amounts of planning as we were kind of taking in the full impact of what was about to happen for our associates and our customers, you know and trying to think through how will customer behavior change during a pandemic? We didn't have a whole lot of indicators as to what that might look like. You know, how is their activity going to change from a transactions, for example, or, you know, are they going to change the frequency with which they're logging in online or paying the cloud gave us the flexibility. As you mentioned earlier to scale rapidly in case the projections that we were making were wrong about consumer behavior. And so we could keep the platforms up and running and recover them much quicker, more resilient infrastructure to make sure that it's up because we really we're in unprecedented times, trying to think through how, how behaviors and needs of customers would change. Secondly, you know, from a capability standpoint, we talked about the need for those real time intelligent experiences that only cloud can give you only modern applications can give you things like, you know Eno, our digital assistant, which is built on a streaming architecture, it can identify unusual charges, 40% tip and alert me in real time. You know, these days 40% tip, I'm trying to help local businesses, that's, that's exactly true. But the fact that Eno is out there kind of looking out and watching my back and saying, this is unusual is, is this you you're transacting a lot online who knows what the fraudsters are looking for. It's those types of experiences that, that you can't build. If you are posting transactions to a mainframe that, you know, runs a batch process overnight, it doesn't help me if you tell me the next day. >> So let's talk about this talent transformation a little bit too, because one of the most difficult things I've witnessed with any type of, of massive transformation like this is recruitment and retention of talent, not the industry hasn't quite built up the talent pool to support such massive transformations. How is this impacting your talent and recruitment processes? >> Yeah. So, massively. And the good news is, you know, given the amount of time we've been on this transformation, we had some time to allow that to adjust, you know, when we started and knowing that, that we were focused largely on AWS, we said, we'd be great if we could go find it, you know thousands of engineers who are, you know, deep experts in AWS, and they didn't necessarily exist at the time given that there, there aren't a whole lot of companies doing what we were doing at the time besides perhaps, you know, AWS themselves and Netflix and they're good partners to us. So we don't need to, to steal everybody's talent. And so we started early on with training and re-skilling our engineers, generally speaking, I find that engineers love using new things. And they in particular love learning newer technologies. I haven't found one yet who's kind of resistant and, you know, wanting to go back and learn COBOL or Fortran like I had to. And I was in college. So, you know, the fact that, that they could, could learn some of these modern tech help evolve and develop them, you know, really kind of push on, on some of the capabilities and, and partner with partners like AWS to enhance the capabilities that are out there. And that's, that's an engineer's dream. The fact that they had, we had plenty of time. We made the declaration that we were going to go all in on cloud. Well, before we targeted getting it done probably before we even knew how in the world we were going to get there, it gave folks plenty of time to think through the training. We provided massive amounts of, of access to learning and training certifications of, for, for everyone to develop the skills that they needed. And I think it's just been great and super fun from a talent perspective. >> I love that you mentioned Netflix, they've been another company that's been extremely public with their journey to the cloud. We kind of think of Netflix is just born in the cloud company and they weren't, and they had a journey to the cloud you share your journey to the cloud. What are some of the pieces of advice, the best practices you can give other companies looking to take that similar journey? >> I will say to, you know, not underestimate the transformative part, for us I think I've said it before. I'll I will say it again. This was not just a tech transformation, you know, this started with our customer needs. It started with a business strategy. It was transformative to our culture for how we, how we think about building and delivering capabilities, as well as the software, then that underlies and supports them. And so I think, you know, starting from a place of where are you trying to go and why? And giving yourself really the fortitude and commitment to achieve it, because you mentioned it, it is not necessarily easy. If you run on a yearly budget cycle, you if, unless you are, you know, running on very few applications at this point, you know, you will not get this done in kind of one year budget cycle, this is a multi-year journey. And ideally you're changing the technology itself, but also how software gets delivered. And therefore then as we just talked about the talent required to do so. >> So Melanie, we've been watching your journey for the past couple of years and we so appreciate you sharing your journey with theCUBE. More importantly, you're now a CUBE alum, and you get all the benefits of the CUBE alum, which has a great headshot that the team has shared, but we really appreciate you sharing a builder's journey at this builder's show. Stay tuned for more coverage of AWS re-invent 2020 via that you.. virtual. Thanks for joining us. (gentle upbeat music)

>> Hi, I'm Jay Limburn, Director of Offering Management from IBM DataOps. As an organization, we've been focusing on simplifying the data and AI life cycle, allowing you to discover and prepare data, and then use that data to build, deploy, govern, and manage your models for the range of capabilities that take advantage of machine and human intelligence. DataOps is a critical and complementary discipline to AI. The methodology enables agile data collaboration, driving speed and scale of operation, (audio distorts) throughout the data and AI life cycle. Learn more on May 27th when IBM and client leaders come together during the DataOps CrowdChat event online. I hope to see you then.

>>Hi. I'm Jalen Burn, director of offering management, IBM Data Ops. As an organization, we've been focusing on simplifying the data, and they are lifecycle allowing you to discover and prepare data and then use that data the build, deploy, govern and manage your models with a range of capabilities that take advantage of machine and human intelligence. Data Ops is a critical and complementary Dissident II. The methodology enables agile data collaboration, driving speed and scale of operations and throughout the data lifecycle learn more on May 27 when IBM and client leaders come together during the data Ops Crowdchat event online. I hope to see you then.

>> 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)

>> Announcer: Live from Washington D.C. It's theCUBE! Covering AWS Public Sector Summit. Brought to you by Amazon Web Services. >> Welcome back everyone to theCUBE's live coverage of AWS Public Sector here in beautiful Washington D.C. Springtime in D.C., there's no better time to be here. I'm your host, Rebecca Knight, co-hosting along with John Furrier, always so much fun to work with you. >> Great to see you. >> And this is a very exciting event for you in particular 'cause you've been doing a lot of great reporting around the modernization of IT in government. I'd love to have you just start riffing, John. What's on your mind right now coming into this show? What are some of the questions that're burning? >> I mean clearly the most important story that needs to be told and is being talked about here in D.C. in the tech world is, for this show specifically, is the JEDI contract, the Joint Enterprise Defense Initiative. It's a word that's not being kicked around at this show because-- >> Rebecca: Nothing to do with Star Wars. >> It's literally the elephant in the room because the contract's been waiting, Oracle's been dragging it on and Oracle's been part of apparently, my opinion from my reporting, is involved in some dirty under-handed tactics against Amazon. But it's being delayed because they're suing it. And Oracle's out. They have no chance of winning the deal, it's really Microsoft and Amazon are going to get a lion's share of the business. So you have, that's the biggest story in tech in D.C. in a long time, is the role of cloud computing is playing in reshaping how government, public sector operates. Combine that with the fact that a new generation of workers are coming in who have no dogma around IT technology, how it's bought or consumed and purchased, and the overcharging that's been going on for many many years, it's been called the Beltway Bandits for a reason because of the waste and sometimes corruption. So a new generation's upon us and Amazon is the leader in making the change happen. The deal they did with the CIA a few years ago really was the catalyst. And since then, public sector and the government has realized that there's advantages to cloud, not only for operating and serving society and its citizens but also competitiveness on a global scale. So a huge transformation, that's the story we're following. That's the story that we got into from the cloud side of the business here in D.C. and that is just raging and expanding and compounded by other factors like Facebook. Irresponsibility in how they managed the data there. Elections were tied in the balance. You're seeing Brexit in the UK. You're seeing counter-terrorism organizations using the dark web and other cyber security challenges at the United States. Literally digital war is happening so a lot of people, smart people, have recognized this and it's now for the first time coming out. >> Right, and I think the other thing that we're also starting to talk much more about is the regulation. I know that you're friendly with Kara Swisher and she bangs on about this all the time. But then she said in a column the other day the problem is is that they're now guns ablazing but do they really understand it? And also, is it too feeble, too little too late? >> I mean, Kara Swisher nailed her story in the New York Times and opinion piece. And I've had similar opinions. Look it. She's been around for a long time, I've been around for a long time. I remember when Bill Clinton was president, that's when the internet was upon us, the Department of Commerce did a good job with the domain name system, they shepherded the technology and they brought it out in a way that was responsible and let government and industry have a nice balancing act with each other and the government really didn't meddle too much. But there was responsibility back then and it wasn't moving as fast. So now you look at what's happening now, the government can't just not ignore the fact that YouTube is, in essence, its own state. And it's acting irresponsibly with how they're handling their situation. You got Facebook run by a 30-something-year-old, which essentially could be as large as a government. So there's no ethics, there's no thinking behind some of the consequences that they've become. So this begs the question, as a technology hock myself, I love tech, never seen tech I didn't like. I mean I love tech. But there's a point where you got to get in there and start shaping impact on ethics and society and we're seeing real examples of how this can wildfire out of control, how tech has just become uncontrollable in a way. >> Yes, no absolutely. And so who is going to be the one to do that? I know that on the show later you're going to be talking to Jay Carney who was obviously in the Obama administration, now here at AWS. It's a well-worn path from the public sector to technology. Susan Molinari, a couple of other, David Plouffe. That is the thing though, that these people really need to get it. Before they can lay down regulations and laws. >> Again, back to why we're here and stories we're trying to tell and uncover and extract is I think the big story that's emerging from this whole world is not just the impact of cloud, we talked about that, we're going to continue to cover that. It's the societal impact and this real there there, there's the intersection of public policy and technology and science where you don't have to be a programmer, you can be an architect of change and know how it works. Then being a coder and trying to codify a government or society. I think you're going to see a new kind of skillset emerge where there's some real critical thinking into how technology can be used for good. You're seeing the trends, Hackathon For Good here, you're seeing a lot of different events where you have inclusion and diversity, bringing more perspectives in. So you got the perfect storm right now for a sea change where it won't be led by the nerds, so to speak, but geeky digital generations will change it. I think that's going to be a big story. Not just workforce changeover but real disciplines around using machine-learning for ethics, societal impact. These are the storylines. I think this is going to be a big long 10-year, 20-year changeover. >> But what will it take though? For the best and the brightest of the nerds to want to go into public service rather than go work for the tech behemoths that are making these changes? I mean that's the thing, it's a war for talent and as we know and we've discussed a lot on theCUBE, there's a big skills gap. >> I think it's been talked about a lot on the web, the millennials want to work for a company that's mission-based. What more mission-based can you look for than so unto our public service right now? John F. Kennedy's famous line, "Ask not what your country can do for you, "what you can do for you country." That might have that appeal for the younger generation because we need it! So the evidence is there and you look at what's going on with our government. There's so many inefficiencies from healthcare to tax reform to policies. There's a huge opportunity to take that waste, and this is what cloud computing and AI and machine-learning can do, is create new capabilities and address those critical waste areas and again, healthcare is just one of many many many others in government where you can really reduce that slack with tech. So it's a great opportunity. >> And where would you say, and I know you've been reporting on this for a long time, where is the government in terms of all of this? I remember not very long ago when healthcare.gov was rolled out and it was revealed that many agencies were still using floppy disks. The government is, first of all is not this monolithic thing, it's many different agencies all with their own tech agendas and with their own processes and policies. So where do you place the government in terms of its modernization right now? >> On the elected officials side, it's weak. They're really not that smart when it comes to tech. Most of the people that are involved in the elected side of the Hill are either lawyers or some sort of major that's not technical. So you can see that with Sundar Pichai from Google and Mark Zuckerberg's testimony when the basic kind of questions they're asking, it's almost a joke. So I think one, the elected officials have to become more tech-savvy. You can't regulate and govern what you don't understand. I think that something that's pretty obvious to most digital natives. And then on the kind of working class, the Defense Department and these other agencies, there's real people in there that have a passion for change and I think there's change agents, Amazon's done really well there. I think that is a piece where you're going to see a movement, where you're going to see this digital native movement where people going to be like, "There's no excuse not to do this right." And I think there's new ways to do it, I think that's going to change. So that's that. On the business side, to how the government procures technology is literally like the '80s, it's like that movie "Hot Tub Time Machine" where you get thrown back. Everything is based on 1980s procurement, 1990s procurement. I mean, shipping manuals. So all these things have to change. How do you procure cloud? If you got to go through a six-month procurement process just to spit up some servers, that's not agility. So procurement's got to change. Competitiveness, what does that mean? This Oracle deal with JEDI highlights a lot of flaws in the government. Which is Oracle's using these rules around procurement to try to stall Amazon, it's kind of like a technicality but it's so irrelevant to the reality of the situation. So procurement has to change. >> Well one of the things you said about how there's a lot of pressure to get it right. And that is absolutely true because we are dealing with national security issues, people's lives, health, these really important topics. And yet the private sector doesn't always get it right the first time either. So how would you describe the government, the federal approach to how they start to implement these new technologies and experiment with other kinds of tools and techniques? >> Well I think there's obviously some agencies that have sensitive things. CIA's a poster child in my opinion of how to do it right. The JEDI, Department of Defense is emulating that and that's a good thing. The Department of Defense is also going multicloud as they put out in their statement. Amazon for the JEDI piece which is for troops in the field. I think that every agency's going to have its own workload and those workloads should decide which cloud to use based upon the architecture of the workload. 'Cause the data needs to be in the cloud, it needs to be real time. And to take the military example, you can't have lag in military, it's not a video game, it's real life, people die. Lag can literally kill people in the field. So technology can be a betterment there but technology to avoid fighting is another one. So you have all these things going on, I think the government's got to really design everything around the workload, their mission, their applications, rather than designing around here's your infrastructure, then decide. >> One of the things we talk about all the time, almost ad nauseam, on theCUBE is digital transformation. And so how do you think about those two, private sector versus public sector? What are the big differences in terms of these institutions on their own journeys of digital transformation? >> I think the government's slower. That's an easy one to talk about. I think there's a lot of moving parts involved, you mentioned some of the procurement things, so a lot of processes. It's the same kind of equation. People process technology, except the people that process is much more complicated on the public sector side than private sector, unless it's a big company. So imagine the biggest company in the private sector side, multiply that times a hundred, that's the government. So in each agency there's a lot of things going on there. But it's getting better. I think cloud has shown that you can actually do that, the people side of things going to be addressed by this new migration of new generation of people coming in saying, "I don't really care how you did it before, "this is how we're going to do it today." The processes are going to be optimized so there's some innovation around process improvement that's going to end on the wayside and the technology everyday is coming faster and faster. Recognition, facial recognition software. Look at that. AI. These are things that are just undeniable now, they have to be dealt with. What do you do to privacy? So again, back to process. So people process technology. >> AWS is a behemoth in cloud computing. What do you want to be hearing here at this conference? They're so far ahead of Google and Microsoft but we cannot count those two companies out, of course not. But what are you looking for for key messaging at this show? >> Well I'm looking forward to seeing Andy Jassy's Fireside Chat with Teresa Carlson tomorrow. I'm interested in some of the use cases coming out of Teresa Carlson's top customers in public sector, again it's global public sector so it's not just in North America here in the United States. I'm interested in also understanding what's real and what's not real around the fear, uncertainty and doubt that a lot of people have been putting on Amazon. Because I see Amazon posturing in a way that's saying go faster, make change and it's not so much that they want to monopolize the entire thing, they're just moving faster. And I think Andy Jassy yesterday saying that they welcome regulation is something that they're trying to push the regulators on. So I think they welcome change. So I want to understand if Amazon really wants to go faster or is there an agenda there. (laughs) What's going on? >> I know, methinks these tech titans are asking for a little too much regulation right now. I mean obviously Mark Zuckerberg has also said, "Please regulate us, I can't do this alone." And here we have Andy Jassy yesterday saying those same things. >> Andy Jassy said on stage yesterday with Kara Swisher, "We can't arrest people." So if their tech goes bad, they're only beholden to the consequences as a private entity. They're not the law so this is where again, back to top story here is that, what is the role of government? This change is here. It's not going away, it's only going to get faster. So the sooner the elected officials and all the agencies get out in front of the digital transformation, the sooner the better. Otherwise it's going to be a wrecking ball. >> Well I cannot wait to dig into more of this over the next two days with you, here at AWS Public Sector. >> All right. >> I'm Rebecca Knight for John Furrier, you are watching theCUBE. (upbeat music)

>> Live, from Barcelona Spain, it's theCube! Covering, KubeCon CloudNativeCon Europe 2019: Brought to you by RedHat, the Cloud Native Computing Foundation and the Ecosystem Partners. >> Hi, and welcome back. this is theCube's coverage of KubeCon CloudNativeCon 2019 here in Barcelona, Spain. We're at the end of day one of two days of live, wall-to-wall coverage. I'm Stu Miniman, and at the end of the day, what we try to do always is do our independent analysis and say what we really think. And joining me is someone that usually has no problem telling you exactly what he thinks online. So, I've challenged Mr. Corey Quinn. Cloud economist, of the Duckbill Group. and the curator, author, Last Week in AWS. To tell us what he actually thinks. >> Well, Stu, you know what your problem is. All the best feedback starts off that way. Now, this has been a fascinating experience for me. This is the first time I've ever been to KubeCon. I didn't quite know what to expect- >> It's KubeCon, not Koob-Con. Come on. It is in GitHub, how you have to make the pronunciation correct. >> We are on theCube. We would think that we would be subject matter experts on this. >> CNCF will be cracking down on you if I don't correct you on this. >> I still maintain we're in Barcelona, Italy. But that's a whole separate argument to have with other people. >> Yes, well, most Americans are geographically challenged. And we understand you have some challenges too. >> Exactly, most Americans need to learn geography, we go to war. (chuckling) >> All right, so, Corey, I guess the first question for you is, you usually go to mostly AWS shows. Most of the customers we've talked to have been AWS customers. So is this feeling much different from the usual show you go to? >> The focus of the conversations is different, and to be clear, I'm not much of a cloud partisan myself. I deal with AWS primarily because, not for nothing, that's where my customers are. That tends to be exactly where the expensive problems tend to live. For better or worse. If that changes, so will I. >> So, you're saying yet that the other cloud providers don't have their customers big enough bills, or they just haven't figured out how you might be able to help them in the future? >> To be very honest with you. Yes, is the short answer. Right now on aggregate, my customers spend about a billion dollars a year on AWS. I don't see the same order of magnitude on other providers, but it's coming. It is very clearly coming. None of these providers are shrinking as far as size goes. It's largely a matter of time. >> Alright. But Corey, I hope at least you've understood that Kubernetes at the center for all things. And that multi-cloud is the way that we are today and will always be in the future. And we should all hold hands and sing along, that we all get along. Is that what you've learned so far? >> I think that's absolutely what I've learned so far. It comes down to religion and it's perfectly name for it. I mean, Kubernetes was the Greek God of spending money on cloud services. >> All right. But seriously. Corey, I think one of the things that I really liked is. We talk to customers and there were some interesting things at least I heard when you talked about they see huge value in what they're doing with Kubernetes. Many of them only have one cloud provider today. Yet they are choosing to lay on Kubernetes either with AWS or with another solution there. What's been your take of what you've heard about. Kind of the why and what they're doing? >> There've been a few different reasons on it. One that resonated with me did validate what I talked about at the beginning of the day. Which was, that by trying to position yourself to be strategically amenable to any potential provider you might want to use in the future. You are sacrificing velocity. And you're gaining agility, losing velocity to do that. Is that trade off worth it? I don't think I'm qualified to judge. I think that's a decision every business has to make on its own. My argument has always been that if that's the decision you make, do it knowingly. And I don't think we've talked to anyone who's made that unknowingly today. >> Yeah. I think that's a really good point. What is it, you know, surprised you or interest you that we've heard so far? >> I have to be honest. I have a long and storied history in open source. I was staff at the Freenode IRC network for about a decade. Which was an interesting time. And I've seen a lot of stuff, but I don't think I've ever seen two open source projects merge before. The fact that we saw that today is still swirling around in my head for better or worse. >> Yeah. And it was OpenCensus and OpenTracing coming together. Open Telemetry. So, definitely check out Ben Siegelman. and it was Morgan McLean from a Google cloud. You know, really interested in discussion. I don't think we're sharing too much when we say off camera. There were like, look, it's like, yes, they got us in a room and we worked, but we'll try not to throw punches here on the set and everything like that. We understand that look, there are people that put these things together and you have smart people that build things the way that it should be done. And these were not like two very similar projects going in the same direction, they were built with different design principles and therefore there'll be somethings that they all need to reconcile to be able to go forward. But yeah, very interesting. >> And everyone we spoke to today was very focused on what the needs of their customers, whoever they happen to be and how to meet those customers and their business requirements. There's no one that we spoke to that was sitting here saying, oh, this is the right answer because it is technically correct. The answer is we're always of the form. This is what we need to do in order to serve customers. And it's very hard to argue against that strategy. >> All right, but none of this really matters because Serverless, right Corey? >> Oh, absolutely. Serverless is the way and the light of the future and to some extent I believe that. >> But they're not doing Serverless. I'm pretty sure they're half a step behind you. Yes, it tends to be, it's easy to make go ahead and die and say, Oh, if you're not running the absolute latest bleeding edge thing, you're behind, you're backwards, etc. And I don't get that all the sense that that is reality. I think that there's, if you're building something greenfield today, you are fundamentally going to make different choices, than if you have something you're trying to carry forward. And I don't just mean carrying forward a technical sense. I mean carrying it forward in terms of process, in terms of culture, in terms of existing business units that need to modernize. People are moving in the same general direction. The question that I think is still on answered is, today, there's a perception rightly or wrongly, that Containers are slightly behind Serverless. I don't know that that necessarily holds true. I think that they are aligned towards the same business value. I think, judge either one of them by today's constraints in the context of longer term strategy is a mistake. I'm curious to see what happens. >> Corey, I love. So we had Jeff Brewer from Intuit and they were like look, we're doing Serverless, we're doing a lot of Containerless stuffs and I'd love it for my developer not to have to worry about. And they've had been moved down that path. So, we know one of the truisms out there is everything in IT is always additive. When you talk to them and say, oh, well I'm going into cloud wait, I still have some stuff that, running on my main frame or my eyes series. And that we'll probably be running there when I've retired. We were talking offline. It's like, well, there's been a little resurgence in COBOL. Just because it did not die after Y2K and so did these things always come back and it's always additive and the longer you've been in business as a company, the more legacy you need to be able to maintain and extend and connect to where you want to go with the future. >> It's almost a sawtooth curve. As complexity continues to rise it becomes to a point where it's untenable. There's something that comes out that abstracts that away and you're back down to a level a human being might actually be able to understand. And you take it a step further and you start to see it again and again and again, and then it collapses down. Docker and a lot of the handbuilt orchestration systems were like that. And then Kubernetes came out. Initially it was fairly simple and then things have been added to it now. And I think we're climbing that sawtooth curve again. Whether or not that maintains? Whether or not that simplifies again? I find that history rhymes particularly in tech. >> Well yeah and I always worry sometimes when you talk about the abstraction layer you got to be really careful what you're abstracting. What we see here a lot, is a lot of times it's people, how can I just consume that? I want to buy it as a service and somebody take care of that not, it hides the complexity for me but some of the complexity is still there. >> Right. So our site is now intermittently slow what do you plan to do? Its update my resume immediately cause we're never untangling that Gordian knot of an infrastructure. That's not a great answer but it is an honest one in some shops. >> I've talked to, we know that there was, for a long time people outsourced what they were doing. And we need to make sure that when you're buying something as a service that you haven't outsourced, That you understand what's important to your business, what happens when things go wrong. We had some discussion today about, networking and observability that we need to be able to go down that rabbit hole, at least turn to somebody who can. Because just because I can't touch that gear doesn't mean my next not on the line, If something goes wrong. >> You can outsource a lot of work. You can't outsource responsibility. I put slightly more succinctly, the line I've always liked was you own your own availability. If you have a provider that you've thrown a lot of these things over to and they go down, well sure you're going to have loud angry phone calls and maybe a few bucks back from an SLA credit. We your customers we're down and we're suffering. So the choices you made impact your businesses perception in the market and your customer's happiness. So as much as fun as it is to be able to throw things over the wall for someone else to deal with, you're still responsible. And I think that people forget that at their own peril. >> One of the things I like. I've got a long history in open source to. If there are things that aren't perfect or things that are maturing. A lot of times we're talking about them in public. Because there is a roadmap and people are working on it and we can all go to the repositories and see where people are complaining. So at a show like this, I feel like we do have some level of transparency and we can actually have realism here. What's been your experience so far? >> I think that people have been remarkably transparent about the challenges that they're facing in a way that you don't often get at a vendor show. Where you have a single vendor, you're at their show, regardless of who that might be. You're not going to be invited back if you wind up with a litany of people coming on a video show or a podcast or screaming and sobbing in the bathroom, however you want to, whatever your media is. Just have a litany of complaints the entire time or make that provider look bad. I don't sense that there's any of that pressure. And for some reason, and this is my first coop gone, so maybe this is just the way this culture it works. Everyone, regardless of who they worked for or what they're working on or what their experience has been, seems happy. I can only assume there's something in the water. >> All right. Well, I've just been informed that the CNCF had asked me to remove Corey because he refuses to say KubeCon. But, Corey. Since this might be your last time on the program, any other final words that you have for it or I will let you do something very rare and if you have any questions for me. Love on my way. >> Absolutely. What did you find today that you didn't expect to find? >> The one that jumps out for me really is two things. One, we discussed it already is the, the observability piece coming together. The other one is. You talk about that maturation of where Amazon fits in this ecosystem. And we had lovely conversation, with Abby fuller. But not just that one. We talked to the users and how they think about it. Which is what really matters is, there's so much talk about, who contributes more code and who does the most here. But look, we're talking cloud. Most of these customers are using AWS as if not the cloud, one of the clouds. I've set it on theCube many times. When you live in a hybrid and multi-cloud world and the public cloud, AWS is the far leader. There's no debating that. So they are participating here. They are doing plenty for what their customers want and they give choice and they listen to the feedback. So that was interesting to me that maturation of where that sits because when I come into the show and many times it is, it is the open source in this whole ecosystem, trying to prevent Amazon from taking over the world. And look, we want a good robust ecosystem out there. >> We absolutely do. >> While I have many friends that work for Amazon. We probably don't want to all be working for a single company down the road. >> I certainly don't. >> We like a nice robust ecosystem where there is choice out there and that keeps its (mumbles). So that maturation of where they are on has been interesting to me so far, especially from the user stand point. >> Very much so. I don't think that anyone wants to look back and say, wow, I'm sure glad we have only one option in this entire space that does anything useful. And then a whole bunch of could have the didn't. And for better or worse, I don't think that the future is nearly as clear cut as the past of cloud. Historically, AWS has been the 800 pound gorilla. I think that we hearing fascinating things from GCP and from Azure. I don't necessarily think that the future is preordained. I do think right now it is AWS game to lose, but I'm starting to see a lot of other players in his face start to make a lot of very interesting and arguably very correct moves. >> All right. Well, we know you as our audience have lots of places where you can turn to find your information and we are always pleased that when you turn to us to watch theCube. if you have any feedback for ourselves, Corey Quinn and myself, Stu Miniman. Reach out on Twitter. We are easy to reach on that. And we have lots of posts. So if you're like, Hey, tired of looking at this mug here. Let us know. But hopefully we're asking the questions and digging into the areas that you want and we'll help your businesses going forward. So we are at the end of day one, Two days live coverage here at KubeCon CloudNativeCon. This is the cube. You're a leader in live tech coverage. Thanks for watching. (music)

>> Live from Miami Beach, Florida. It's theCUBE, covering VeeamON 2019. Brought to you by Veeam. >> Welcome to sunny Miami, everybody. This is theCube, the leader in live tech coverage. My name is Dave Vellante I'm here with Peter Burse. This is day one of VeeamON, theCUBE's third year covering VeeamON. First year was Enola, last year was in Chicago, they chose Miami at the Fontainebleau Hotel. >> Bummer. >> Yeah, which is a real bummer here. A lot of swankiness, a lot of fun people, A lot of big boats Peter, and this morning we're here at the Keynotes, theCUBE is going to be covering wall to wall coverage. We like to go out to the events extract the signal from the noise. Peter and I have done a number of shows together. Peter, I love working with you cause you bring great insights and I want to start off with Veeam. The company, the host company here. We saw when we started Wikibon, we saw the ascendancy of Veaeam kind of coincide with virtualization, and it was all about making backup simpler and easier to use for small to medium size businesses. That's what Ratmir Timashev , the co-founder called Act One. Now, they try to really ride the wave of cloud to create Act Two, of course they're not alone. You've got companies like Rubrik and Cohesity, and then established players, like Dell EMC and Veritas and IBM. All trying to hang on and get a piece of the 15 billion dollar business. But we're seeing the notion of backup and recovery move beyond just a insurance policy into this idea of data protection, what some people call, data management, which, you and I have talked about, means a lot of different things to a lot of different people And a concept that you've sort of coined called data assurance. I don't know if you've coined it, but you've certainly talked about it articulary. I want to unpack some of those trends with you. You've been studying this market. You've written about this notion of data protection. Your take on the event here, 2000 people, but most importantly, what's going on in the marketplace. >> Let's make one single point about Veeam. Ten years ago, you remember, the whole notion of backing up and restoring virtual machines was really hard. It's still something that we take for granted today, but it's pretty amazing technology that we can actually do this. Take these software images of physical devices and actually generate backup that can be very very quickly restored at very very high fidelity. It still is something magical. The reason why I say that is because the degree of complexity and the direction we're going. As state gets associated with different parts of the computing system or not associated with different parts of the computing system, it's going to become that much more challenging. We talked about Kubernetes clusters, for example. They're supposed to be stateless. They're supposed to be, you know, spin 'em up, spin 'em down. Spin 'em up, spin 'em down. Minimize the amount of state. Places that much more pressure on how you handle your data and do data management. Where I like to start, Dave, is we talk about what's going to happen next. Number one, folks have gotten the cloud wrong. Cloud was not strategy for centralizing computing. It really is a strategy for distributing computing with control, with services, with protection, with a common management type of mind. >> What do you mean by that? People think of cloud as putting everything into the public cloud in some kind of central location. Explain the distributed notion. >> The thing that's really interesting about the cloud is that these standards evolve, and as the experience evolves, and as the technology gets built and invented, that we now can see that we can bring cloud services to where the data resides. That's probably, well that's not probably. That's what's going to happen. The cloud is increasingly going to recognize the data, the cost of data state and the cost of data movement, are two of the biggest costs in any computing system. We want to keep data proximate to the activity it's going to support. Not just where it's created, but the activities it's going to support. That's how you associate data and business value. >> You're specifically talking about the services following the data in a consistent manner. Whether it's on-prem, in the cloud, or-- >> That's what it has to be able to do. We have to not just put the data where it's located, but that data as an asset has certain services associated, certain metadata associated with it, and often certain code associated with it. The whole notion is to be able to assure that when I spin up one of these new modern applications that don't know a lot about state, that the data is there. The services that make that data integress, secure, viable, backup and restorable, et cetera, are resonant. Very importantly, that that metadata that describes policy and other types of things also is easily invoked and easily applied without an enormous amount of administrative headache. So ultimately we can get to greater distribution of data with greater automation, lower administration, and greater security. >> We talked at the top about Veeam is really trying to ride the wave of cloud, just the same way it rode the wave of virtualization. There were three announcements today. The first was that Veeam hit a billion dollars in a trailing 12 month basis. That's big for pureplace software company traditionally in backup. Billion dollars is quite a milestone. >> Big range back up. >> Yeah really, it really SMB backup. >> 350 thousand customers. >> 350 thousand customers. Like 4000 a month. They also announced Veeam Availability Orchestrator v2, which is all about fast recovery. We asked Danny Allen in the briefing this morning, how they do that. It's complicated. It's a function of architecture, metadata management, but essentially doing fast recovery without necessarily having to rely on replication. There are some other components of that. Automated testing, dynamic documentation. We're going to dig into that a little bit more. Then there's this notion of with Veeam, a set of open APIs, which is cloud-like. When you think of riding the cloud wave, what do you think of Peter? You think of open, you think of, you mentioned Kubernetes and microservices. You think of an ecosystem. You think of simple. You think of cloud-like pricing. Can, in your opinion, Veeam take that success it's had in virtualization and kind of replicate that in the cloud? >> You and I have been on the phone with customers where we've argued to the customer that there's going to be greater specialization of data services based on greater specialization of a customer's data needs. Some people argue with us a lot. Just as some people used to argue with us about the whole notion of hybrid cloud. For a long time, You guys are crazy when you say that. When I saw that with Veeam, which I think is an especially important feature of today's announcement, it opens up the possibility that I can have a common platform for data assurance, data protection, but allow an ecosystem to create value in response to different classes of needs because data protection is going to be a strategic capability with any digital business. If I'm a business that's not treating data as an asset, as a basis for differentiating from my competitors, I have to protect that data and everything that it means and assure that it's available. That has now become a strategic business capability. Like every single strategic business capability, and I'm talking about it from an architectural sense here, there's going to be specialization and specificity to that business. With Veeam, creates an opportunity for an ecosystem to create additional layers of value and function on top of that core set of services to better map Veeam to specific customer needs. That's a good thing. >> When you talk about the ecosystem, I'm glad you brought that up. You got partners like HPE, Cisco, NetApp, Lenovo, Nutanix. Those are sort of the top tier partners that these guys have mentioned and a number of other partners as well. Veeam has become that billion dollar company, and is now attracting and building out this ecosystem in a pretty big way. Ratmir put up a chart that the market's 15 billion. They're not alone, as they say, you've got established players like Dell EMC, certainly Veritas, IBM with the old Tivoli products and then some other new stuff. Then you've got Cohesity and Rubrik just announced, maybe earlier this year, 250 million dollar investments, actually late last year and early this year. Veeam countered that with a 500 million dollar investment. It's a little unclear exactly where all that money is going. Private company, three private companies. But the big point is. >> Close to Miami. (mumbles) >> The point is, a lot of money coming into this space. In the enterprise, data protection is very very hot. Why is that, you mentioned it, is because of digital business and the need to protect data, assure data, be able to recover transparently and very quickly. >> And using some of these new modern application development styles that are intended to create as many options to the developer as possible. That's where you get the agility. >> Your point about Kubernetes and being stateless and some of the security challenges that we were talking about last night. This notion of data assurance, being able to spin up and automatically spin down containers so that they're not a threat. Raising the bar, raising the cost for the bad guys to get in and hack your systems, making it more complex, making it less attractive because Kubernetes, microservices, containers. Sometimes microservices, as one pundit once said, it's so micro. It's some important stuff in there. >> Oh look, you can build really crappy applications with virtually any technology, right. But microservices, when you sit down with a senior guy in a development organization and you ask him about microservices, or her about microservices, it all starts with the observation that microservices is an approach to doing application development. Just as client services started off as an approach to doing application development, where you think about, well I'm going to put all the application function here and all the database function here and we'll make database calls between the two. That's basically what microservices is. If you think about it any other way, you're missing the starting point. It's a way of thinking about how you break down a problem. Increasingly business wants to break down problems into smaller parts that are more segmented, more compartmentalized. But also that don't necessarily persist for any number of different reasons. Resource consumption, change and the need to change, security, et cetera. The whole concept that overtime we're going to see applications being comprised of containers that thought through the microservices approach built with languages that are supportive of containers and utilizing containers as the infrastructure. The other thing is, going back to the first point, virtual machines virtualized hardware. Containers virtualized operating systems. It's a really interesting technology when you come right down to it. Backing up and restoring all that is going to be challenging. Real beauty of this is that ultimately containers are going to reduce threat surface. Not just by the dimensions of location, identity, but also time, because I can vary containers out. It's going to be a multi-dimensional approach to improving security, enhancing function, and getting greater productivity out of IT investments. >> You got to protect that stuff. So we're here, VeeamON, day one. We got two days of wall to wall coverage with theCUBE. Veeam, a billion dollar company, going after a 15 billion dollar pie. We're going to hear from Ratmir Timashev, who's the co-founder of Veeam, and a number of customers and partners. Keep it right there, you're watching theCUBE. Dave Vellante with Peter Burse. We'll be right back after this short break. (techno music)

produced from the cube studios this is strong by science in-depth conversations about science based training sports performance and all things health and wellness here's your host max smart [Music] [Applause] [Music] all right thank you guys tune in today I have the one and only Dean of big data the man the myth the legend bill Schwarz oh also my dad is the CTO of Hitachi van Tara and IOC in analytics he has a very interesting background because he is the well he's known as the Dean of big data but also the king of the court and all things basketball related when it comes to our household and unlike most people in the data world and I want to say most as an umbrella term but a some big bill has an illustrious sports career playing at Coe College the Harvard of the Midwest my alma mater as well but I think having that background of not just being computer science but where you have multiple disciplines involved when it comes to your jazz career you had basketball career you have obviously the career Iran now all that plays a huge role in being able to interpret and take multiple domains and put it into one so thank you for being here dad yeah thanks max that's a great introduction I rep reciate that no it's it's wonderful to have you and for our listeners who are not aware bill is referring him is Bill like my dad but I call my dad the whole time is gonna drive me crazy bill has a mind that thinks not like most so he he sees things he thinks about it not just in terms of the single I guess trajectory that could be taken but the multiple domains that can go so both vertically and horizontally and when we talk about data data is something so commonly brought up in sports so commonly drop in performance and athletic development big data is probably one of the biggest guess catchphrases or hot words or sayings that people have nowadays but doesn't always have a lot of meaning to it because a lot of times we get the word big data and then we don't have action out of big data and bill specialty is not just big data but it's giving action out of big data with that going forward I think a lot of this talk to be talking about how to utilize Big Data how do you guys data in general how to organize it how to put yourself in a situation to get actionable insights and so just to start it off Becky talked a little bit on your background some of the things you've done and how you develop the insights that you have thanks max I have kind of a very nos a deep background but I've been doing data analytics a long time and I was very fortunate one of those you know Forrest Gump moments in life where in the late 1980s I was involved in a project at Procter & Gamble I ran the project where we brought in Walmart's point of sales data for the first time into a what we would now call a data warehouse and for many of this became the launching point of the data warehouse bi marketplace and we can trace the effect the origins of many of the BI players to that project at Procter & Gamble in 87 and 88 and I spent a big chunk of my life just a big believer in business intelligence and data warehousing and trying to amass data together and trying to use that data to report on what's going on and writing insights and I did that for 20 25 years of my life until as you probably remember max I was recruited out Business Objects where I was the vice president of analytic applications I was recruited out of there by Yahoo and Yahoo had a very interesting problem which is they needed to build analytics for their advertisers to help those advertisers to optimize or spend across the Yahoo ad network and what I learned there in fact what I unlearned there was that everything that I had learned about bi and data warehouse and how you constructed data warehouses how you were so schema centric how everything was evolved around tabular data at Yahoo there was an entirely different approach the of my first introduction to Hadoop and the concept of a data Lake that was my first real introduction into data science and how to do predictive analytics and prescriptive analytics and in fact it was it was such a huge change for me that I was I was asked to come back to the TD WI data world Institute right was teaching for many years and I was asked to do a keynote after being at Yahoo for a year or so to share sort of what were the observations what did I learn and I remember I stood up there in front of about 600 people and I started my presentation by saying everything I've taught you the past 20 years is wrong and it was well I didn't get invited back for 10 years so that probably tells you something but it was really about unlearning a lot about what I had learned before and probably max one of the things that was most one of the aha moments for me was bi was very focused on understanding the questions that people were trying to ask an answer davus science is about us to understand the decisions they're trying to take action on questions by their very nature our informative but decisions are actionable and so what we did at Yahoo in order to really drive the help our advertisers optimize your spend across the Yahoo ad network is we focus on identifying the decisions the media planners and buyers and the campaign managers had to make around running a campaign know what what how much money to allocate to what sides how much how many conversions do I want how many impressions do I want so all the decisions we built predictive analytics around so that we can deliver prescriptive actions to these two classes of stakeholders the media planners and buyers and the campaign managers who had no aspirations about being analysts they're trying to be the best digital marketing executives or you know or people they could possibly be they didn't want to be analysts so and that sort of leads me to where I am today and my my teaching my books my blogs everything I do is very much around how do we take data and analytics and help organizations become more effective so everything I've done since then the books I've written the teaching I do with University of San Francisco and next week at the National University of Ireland and Galway and all the clients I work with is really how do we take data and analytics and help organizations become more effective at driving the decisions that optimize their business and their operational models it's really about decisions and how do we leverage data and analytics to drive those decisions so what would how would you define the difference between a question that someone's trying to answer versus a decision but they're trying to be better informed on so here's what I'd put it I call it the Sam test I am and that is it strategic is it actionable is it material and so you can ask questions that are provocative but you might not fast questions that are strategic to the problems you're trying to solve you may not be able to ask questions that are actionable in a sense you know what to do and you don't necessarily ask questions that are material in the sense that the value of that question is greater than the cost of answering that question right and so if I think about the Sam test when I apply it to data science and decisions when I start mining the data so I know what decisions are most important I'm going through a process to identify to validate the value and prioritize those decisions right I understand what decisions are most important now when I start to dig through the data all this structured unstructured data across a number different data sources I'm looking for I'm trying to codify patterns and relationships buried in that data and I'm applying the Sam test is that against those insights is it strategic to the problem I'm trying to solve can I actually act on it and is it material in the sense that it's it's it's more valuable to act than it is to create the action around it so that's the to me that big difference is by their very nature decisions are actually trying to make a decision I'm going to take an action questions by their nature are informative interesting they could be very provocative you know questions have an important role but ultimately questions do not necessarily lead to actions so if I'm a a sport coach I'm writing a professional basketball team some of the decisions I'm trying to make are I'm deciding on what program best develops my players what metrics will help me decide who the best prospect is is that the right way of looking at it yeah so we did an exercise at at USF too to have the students go through an exercise - what question what decisions does Steve Kerr need to make over the next two games he's playing right and we go through an exercise of the identifying especially in game decisions exercise routes oh no how often are you gonna play somebody no how long are they gonna play what are the right combinations what are the kind of offensive plays that you're gonna try to run so there's a know a bunch of decisions that Steve Kerr is coach of the Warriors for example needs to make in the game to not only try to win the game but to also minimize wear and tear on his players and by the way that's a really good point to think about the decisions good decisions are always a conflict of other ideas right win the game while minimizing wear and tear on my players right there's there are there are all the important decisions in life have two three or four different variables that may not be exactly the same which is by this is where data science comes in the data science is going to look across those three or four very other metrics against what you're going to measure success and try to figure out what's the right balance of those given the situation I'm in so if going back to the decision about about playing time well think about all the data you might want to look at in order to optimize that so when's the next game how far are they in this in this in the season where do they currently sit ranking wise how many minutes per game has player X been playing looking over the past few years what's there you know what's their maximum point so there's there's a there's not a lot of decisions that people are trying to make and by the way the beauty of the decisions is the decisions really haven't changed in years right what's changed is not the decisions it's the answers and the answers have changed because we have this great bound of data available to us in game performance health data you know all DNA data all kinds of other data and then we have all these great advanced analytic techniques now neural networks and unstructured supervised machine learning on right all this great technology now that can help us to uncover those relationships and patterns that are buried in the data that we can use to help individualize those decisions one last point there the point there to me at the end when when people talk about Big Data they get fixated on the big part the volume part it's not the volume of big data that I'm going to monetize it's the granularity and what I mean by that is I now have the ability to build very detailed profiles going back to our basketball example I can build a very detailed performance profile on every one of my players so for every one of the players on the Warriors team I can build a very detailed profile it the details out you know what's their optimal playing time you know how much time should they spend before a break on the feet on the on the on the court right what are the right combinations of players in order to generate the most offense or the best defense I can build these very detailed individual profiles and then I can start mission together to find the right combination so when we talk about big it's not the volume it's interesting it's the granularity gotcha and what's interesting from my world is so when you're dealing with marketing and business a lot of that when you're developing whether it be a company that you're trying to find more out about your customers or your startup trying to learn about what product you should develop there's tons of unknowns and a lot of big data from my understanding it can help you better understand some patterns within customers how to market you know in your book you talk about oh we need to increase sales at Chipotle because we understand X Y & Z our current around us now in the sports science world we have our friend called science and science has helped us early identify certain metrics that are very important and correlated to different physiological outcomes so it almost gives us a shortcut because in the big data world especially when you're dealing with the data that you guys are dealing with and trying to understand customer decisions each customer is individual and you're trying to compile all together to find patterns no one's doing science on that right it's not like a lab work where someone is understanding muscle protein synthesis and the amount of nutrients you need to recover from it so in my position I have all these pillars that maybe exist already where I can begin my search there's still a bunch of unknowns with that kind of environment do you take a different approach or do you still go with the I guess large encompassing and collect everything you can and siphon after maybe I'm totally wrong I'll let you take it away no that's it's a it's a good question and what's interesting about that max is that the human body is governed by a series of laws we'll say in each me see ology and the things you've talked about physics they have laws humans as buyers you know shoppers travelers we have propensity x' we don't have laws right I have a propensity that I'm gonna try to fly United because I get easier upgrades but I might fly you know Southwest because of schedule or convenience right I have propensity x' I don't have laws so you have laws that work to your advantage what's interesting about laws that they start going into the world of IOT and this concept called digital twins they're governed by laws of physics I have a compressor or a chiller or an engine and it's got a bunch of components in it that have been engineered together and I can actually apply the laws I can actually run simulations against my digital twins to understand exactly when is something likely to break what's the remaining useful life in that product what's the severity of the the maintenance I need to do on that so the human body unlike the human psyche is governed by laws human behaviors are really hard right and we move the las vegas is built on the fact that human behaviors are so flawed but body mate but bat body physics like the physics that run these devices you can actually build models and one simulation to figure out exactly how you know what's the wear and tear and what's the extensibility of what you can operate in gotcha yeah so that's when from our world you start looking at subsystems and you say okay this is your muscular system this is your autonomic nervous system this is your central nervous system these are ways that we can begin to measure it and then we can wrote a blog on this that's a stress response model where you understand these systems and their inferences for the most part and then you apply a stress and you see how the body responds and even you determine okay well if I know the body I can only respond in a certain number of ways it's either compensatory it's gonna be you know returning to baseline and by the mal adaptation but there's only so many ways when you look at a cell at the individual level that that cell can actually respond and it's the aggregation of all these cellular responses that end up and manifest in a change in a subsystem and that subsystem can be measured inferential II through certain technology that we have but I also think at the same time we make a huge leap and that leap is the word inference right we're making an assumption and sometimes those assumptions are very dangerous and they lead to because that assumptions unknown and we're wrong on it then we kind of sway and missed a little bit on our whole projection so I like the idea of looking at patterns and look at the probabilistic nature of it and I'm actually kind of recently change my view a little bit from my room first I talked about this I was much more hardwired and laws but I think it's a law but maybe a law with some level of variation or standard deviation and it we have guardrails instead so that's kind of how I think about it personally is that something that you say that's on the right track for that or how would you approach it yeah actually there's a lot of similarities max so your description of the human body made up of subsystems when we talk to organizations about things like smart cities or smart malls or smart hospitals a smart city is comprised of a it's made up of a series of subsystems right I've got subsystems regarding water and wastewater traffic safety you know local development things like this look there's a bunch of subsystems that make a city work and each of those subsystems is comprised of a series of decisions or clusters of decisions with equal use cases around what you're trying to optimize so if I'm trying to improve traffic flow if one of my subsystems is practically flow there are a bunch of use cases there about where do I do maintenance where do I expand the roads you know where do I put HOV lanes right so and so you start taking apart the smart city into the subsystems and then know the subsystems are comprised of use cases that puts you into really good position now here's something we did recently with a client who is trying to think about building the theme park of the future and how do we make certain that we really have a holistic view of the use cases that I need to go after it's really easy to identify the use cases within your own four walls but digital transformation in particular happens outside the four walls of an organization and so what we what we're doing is a process where we're building journey maps for all their key stakeholders so you've got a journey map for a customer you have a journey map for operations you have a journey map for partners and such so you you build these journey maps and you start thinking about for example I'm a theme park and at some point in time my guest / customer is going to have a pity they want to go do something you want to go on vacation at that point in time that theme park is competing against not only all the other theme parks but it's competing against major league baseball who's got things it's competing against you know going to the beach in Sanibel Island just hanging around right there they're competing at that point and if they only start engaging the customer when the customers actually contacted them they must a huge part of the market they made you miss a huge chance to influence that person's agenda and so one of the things that think about I don't know how this applies to your space max but as we started thinking about smart entities we use design thinking and customer journey match there's a way to make certain that we're not fooling ourselves by only looking within the four walls of our organization that we're knocking those walls down making them very forest and we're looking at what happens before somebody engages it with us and even afterwards so again going back to the theme park example once they leave the theme park they're probably posting on social media what kind of fun they had or fun they didn't have they're probably making plans for next year they're talking to friends and other things so there's there's a bunch of stuff we're gonna call it afterglow that happens after event that you want to make certain that you're in part of influencing that so again I don't know how when you combined the data science of use cases and decisions with design thinking of journey Maps what that might mean to do that your business but for us in thinking about smart cities it's opened up all kinds of possibilities and most importantly for our customers it's opened up all kinds of new areas where they can create new sources of value so anyone listening to this need to understand that when the word client or customer is used it can be substituted for athlete and what I think is really important is that when we hear you talk about your the the amount of infrastructure you do for an idea when you approach a situation is something that sports science for in my opinion especially across multiple domains it's truly lacking what happens is we get a piece of technology and someone says go do science while you're taking the approach of let's actually think out what we're doing beforehand let's determine our key performance indicators let's understand maybe the journey that this piece of technology is going to take with the athlete or how the athletes going to interact with this piece of technology throughout their four years if you're in the private sector right that afterglow effect might be something that you refer to as a client retention and their ability to come back over and over and spread your own word for you if you're in the sector with student athletes maybe it's those athletes talking highly about your program to help with recruiting and understanding that developing athletes is going to help you know make that college more enticing to go to or that program or that organization but what really stood out was the fact that you have this infrastructure built beforehand and the example I give I spoke with a good number of organizations and teams about data utilization is that if if you're to all of a sudden be dropped in the middle of the woods and someone says go build a cabin now how was it a giant forest I could use as much wood as I want I could just keep chopping down trees until I had something that had with a shelter of some sort right even I could probably do that well if someone said you know what you have three trees to cut down to make a cabin you could become very efficient and you're going to think about each chop in each piece of wood and how it's going to be used and your interaction with that wood and conjunction with that woods interaction with yourself and so when we start looking at athlete development and we're looking at client retention or we're looking at general health and wellness it's not just oh this is a great idea right we want to make the world's greatest theme park and we want to make the world's greatest training facility but what infrastructure and steps you need to take and you said stakeholders so what individuals am i working with am I talking with the physical therapist am i talking with the athletic trainer am I talking with the skill coach how does the skill coach want the data presented to them maybe that's different than how the athletic trainer is going to have a day to present it to them maybe the sport coach doesn't want to see the data unless something a red flag comes up so now you have all these different entities just like how you're talking about developing this customer journey throughout the theme park and making sure that they have a you know an experience that's memorable and causes an afterglow and really gives that experience meaning how can we now take data and apply it in the same way so we get the most value like you said on the granular aspect of data and really turn that into something valuable max you said something really important and one of the things that let me share one of many horror stories that that that comes up in my daily life which is somebody walking up to me and saying hey I got a client here's their data you know go do some science on it like well well what the heck right so when we created this thing called the hypothesis development canvas our sales teams hate it or do the time our data science teams love it because we do all this pre work we just say we make sure we understand the problem we're going after the decision they're trying to make the KPI is it's what you're going to measure success in progress what are they the operational and financial business benefits what are the data sources we want to consider here's something by the way that's it's important that maybe I wish Boeing would have thought more about which is what are the costs of false positives and false negatives right do you really understand where your risks points are and the reason why false positive and false negatives are really important in data science because data size is making predictions and by virtue of making predictions we are never 100% certain that's right or not predictions hath me built on I'm good enough well when is good enough good enough and a lot of that determination as to when is good enough good enough is really around the cost of false positives and false negatives think about a professional athlete like the false the you know the ramifications of overtraining professional athlete like a Kevin Durant or Steph Curry and they're out for the playoffs as huge financial implications them personally and for the organization so you really need to make sure you understand exactly what's the cost of being wrong and so this hypothesis development canvas is we do a lot of this work before we ever put science to the data that yeah it's it's something that's lacking across not just sports science but many fields and what I mean by that is especially you referred to the hypothesis canvas it's a piece of paper that provides a common language right it's you can sit it out before and for listeners who aren't aware a hypothesis canvas is something bill has worked and developed with his team and it's about 13 different squares and boxes and you can manipulate it based on your own profession and what you're diving into but essentially it goes through the infrastructure that you need to have setup in order for this hypothesis or idea or decision to actually be worth a damn and what I mean by that is that so many times and I hate this but I'm gonna go in a little bit of a rant and I apologize that people think oh I get an idea and they think Thomas Edison all son just had an idea and he made a light bulb Thomas Edison's famous for saying you know I did you know make a light bulb I learned was a 9000 ways to not make a light bulb and what I mean by that is he set an environment that allowed for failure and allowed for learning but what happens often people think oh I have an idea they think the idea comes not just you know in a flash because it always doesn't it might come from some research but they also believe that it comes with legs and it comes with the infrastructure supported around it that's kind of the same way that I see a lot of the data aspect going in regards to our field is that we did an idea we immediately implement and we hope it works as opposed to set up a learning environment that allows you to go okay here's what I think might happen here's my hypothesis here's I'm going to apply it and now if I fail because I have the infrastructure pre mapped out I can look at my infrastructure and say you know what that support beam or that individual box itself was the weak link and we made a mistake here but we can go back and fix it

>> Produced from the Cube studios. This's strong by science, in depth conversations about science based training, sports performance and all things health and wellness. Here's your hose, Max Marzo. I'm with >> the one and only Cory Slush Inger Cory is the director of men's sorry, director of performance from men's basketball at Stanford University. Good friend of mine, extremely passionate human. And for those you don't know former college basketball Hooper Corey really happened. Happy on a day to thank you for being here. >> No, man, it's an absolute pleasure. Me, Max. It's It's kind of crazy how our relationship has evolved throughout the years. Ah, start with Diem. You know, that's how it usually goes, the way your T shirt and he's got hair. So I wish I was that God, like I got it down here, but I got it out talk. So don't worry, Max. I'm going to make you a T shirt and I'm sending Teo. You said >> make a T shirt. I >> will wear >> until you plant cast with you again. >> Be careful with the pick. Might be >> way careful with that. Wait. Speaking of that, Corey, I mean, before we went on air here, you have a little story about your beard. And not to say you're only known for the beard, but the beer definitely is a staple in the slashing. Your appearance give me back for that. I want to hear it, and they will dive into some of the science. >> Yeah, man. So as far as the beard, I mean, it started at you. Maybe we're on a Spanish tour went overseas, and I did. One of those crazy handlebar mustache is right. I mean, it was gnarly, but being overseas just didn't shave, right? I mean, we're there for almost a week and a half, and I just started growing out the stubble. And then people are like, keep it going. And so I kept going and we were winning a lot of games. And then we end up winning a championship. And so it became like the tournament beard or became like the season beard. And so I just kept rolling it from there, and yeah, that's that's kind of where the beard is stated for now. And then when I realized, like if I could, it almost looks like a cancer patient. So I needed a key because he's blond eyebrows, man from five feet away. It looks like I'm ball period like I can't grow here. So, yeah, that's where the beard states is at this point. >> Well, Iet's fifty. I'm getting mine going. I'm not going to your caliber. I keep it trimmed, but it makes me feel like I'm a scientist or something. If I have a beard, makes you more intelligent, but getting off the topic here. When it comes to developing anybody, people say, you know, athletes, athletes, athletes athletes are what zero point zero zero one percent of population when it comes to developing anybody at all. We got talking about the bass aspects of human movement human development. You have an interesting take on this, and I don't want to spoil it for the listeners. I'd rather have you say it first, cause I'll just bastardized and screw it up. You're going to take on developing anybody regardless if they're an athlete or just general population, >> right? I mean, if you look through human evolution one or two things that we used to do, I used to farm. We used to kill things with our hands. We used to climb, you know, we used to throw things, you know? I mean, look at the the early Olympics, right? I mean, that's basically what the events wass. He wrestled someone. You ran faster than someone. You ran further than someone, and you threw some things. I and basically that's what human capacity is. So my goal before we actually trained them to be better athletes, is to make them better humans first, because if I can express their ability to be a better human, then they will be able to express their ability to be a better athlete. >> Joshua and with those movements, selections. If you have unique choice food people who don't follow up Instagram better weigh on your instagram handle at the end. But the selections of exercises you pick, it's not traditional a sense. Let's load a bar up. Let's do a hand claim you really take ownership of different shaped objects for that way, whether it be a yoke, whether it be a kettle bell, how do you come up with the most movements? Elections? What goes into that decision making? And for any individual out there, whether they are fast ball player who's seven one or a guy who's five eight, how do you decide which of those implements are best fitted for you? >> Well, everything that shaped the way I believe is one hundred ten percent based off my environment. And look, I played college basketball. Don't look at my stats. I was not that good, but I trained in or I've played with, and now for ten years I've trained that basketball athletic population, so you can imagine with me. Okay, I'm five foot ten. Very average, at best, especially with my links, man. Now imagine six foot six, but a seven foot two weeks man and all those things that I was good at, clean snatched jerk. You know, I was a purist in the beginning. I mean, of course I was right. I was just learning what strength iss How to be strong. Now, I'm trying to imagine further. Like, how do I have impact? How do I have quote unquote transfer? What? I'm trying to load these freaks. I mean, these guys are not normal human beings, right? They got seven foot two wings fans and short torso, so their levers are crazy. So now I'm asking them to do the same things that got me strong. Being at five. Ten, it just doesn't make much sense to me now, Not saying they don't have the capacity to do it mean help. Be honest with you. Some of my best weightlifters actually been seven foot tall, But that being said, if there's a way I can load them, that makes a lot more sense. That's easy to teach. I could do it often, and it's right in their comfort zone now, not comfort as in like we're not training hard, but like in their center of mass, where they can actually manipulate loads heavy loads at that with decent speeds. Then, yeah, I'm going to do that. So, for instance, we look at a bar bell, clean snatches all good. Why can't we do the same intent with a trap door? I mean, we could still pull. We could still triple extend and then we can still catch in that power position. The only thing that changes is the complexity of the movement. Now I'm not manipulating myself around a straight bar bell. It's in my centre of mass. And now I, Khun Express quote unquote force. Ah, lot more efficient, Effective. So now I can load it more loaded faster and do less teaching. Yeah, I do that. That makes a lot of things So that's really what it came from. And then to be honest with you, But how do you experience that light? How do you know a seven foot feels like? How do you know? And so you know, I've dabbled town some ways too. Open up my consciousness, if you will, to allow me to feel that ord, allow the imagination, my creativity to tryto understand what that could feel like. And then, of course, obviously feedback from my athletes. But I mean, why you always see, like the old school dues were just like, Oh, this is weak. This is squad. We we box what we what do we do? Whatever to get strong. But it's like, you know, it makes sense. If you're five foot six, it doesn't make much sense if your seven foot tall so you've got a truly find ways to experience it yourself. And now by the means that you do that probably not going to talk about on this podcast. But the way I did it work. >> Yeah, well, we'll refrain from diving that specific. I'd appreciate it on because to each his own one of the things you mentioned like talking about Hooper's I played basketball. I played your Batch three point shooter. Anyone's listening, too, By the way, when my feet are set, I'm not. I'm not an athlete, but I could shoot the shit out of basketball. I'LL be very blunt with you. I've >> been on the receiving end of that on one of our own game. You don't have to talk when you busted my ask way >> down to like. A lot of basketball players are bad movers, and what I mean by that it's their very good when you put a ball in their hands. That is something you talked about, too. But when you get them in a dance room right there, a lot different than football players and I mean by that is you don't see a bad end zone celebration, right? Want touchdown dances look really good, Odell Beckham being very soon and a lot of it's because those patterns are done without a ball in their hand. This is my opinion and they're very primal and natural with a minute and basketball everything's doing the ball in their hand and then when they start to move, especially because they're developing this, you starts. We're like a third rate. Now they have to only play basketball. And typically you don't play football and basketball, especially football. The high level, because you know you prepping for the basketball season itself. >> You get that deal in Scotland. Shit, bro, >> You have to play basketball for every waking hour the next fifteen years to get there. I'm kidding, but I'm thinking about my head is we're not exposed to those different movement. Parents were stuck in this ninety foot unless you're how light is forty six feet, something like that with court that really constrains how we move. And then you put someone in a waiting room where all the son of dealing with external loads and very unique movement patterns you get guys who just looked walking and I think you talked about this on different podcast, but I want to get into a little bit. Here was, I think so. That stems from our coaching of a young athletes and our physical education that we no longer does. Have we used to have back in the day and how that's really affecting athletes as they get older. >> I couldn't agree more. I mean, I get these quote unquote specialized athletes. And to be honest with you, I don't have athletes like I have guys who have a basketball in their hand. They got really long levers and they have some skill, right? They have some skill to be able to go from point A to point B and put on orange round ball into a cellar. That's that's so happen to be ten foot off the ground. That's what I have. I don't have a true athlete who can pick things up off the floor who could sit down on the floor and stand up, who can throw things who can sprint, who could jump onto things. I mean, some of the best vertical jumps that you see in basketball are not even close to what you would see in football and track and field. When you think this is a sport with the high flyers counter movement, jump hands on hips averages that I've seen on teams eighteen inches and everybody is like Oh, that's terrible But that's a true counter movement jump with long levers. So now if we add some momentum to that and add a seven foot two wingspan and then all of a sudden their elbows above the ramp. Right? So that's the difference we get. We see this a NRI or this false thought, or this false vision of what athleticism is because they're so long. But in reality. And then you put a bunch of cornerbacks out there that would be really special to see, because these are guys that are like five foot ten and the most explosive fast dude you've ever seen. There's don't have the skill to play basketball. So you know, with the way we are, physical education is set up now, obviously has been chopped in half, half, half so no more education. Physical education is what we get to. They only play one sport. They sit in chairs that they're not really made to be. They live in this wart western society where every chair they sit in Is that it? His ninety, which for them is more like this, right? And then they get up and down on these beds that their feet are hanging off of. So I don't know what sleep looks like for that. And if you saw my guys get on an airplane, a commercial airplane, you would be cringing the entire time because they're literally bundled up like this. And so not on ly. Are we trying to correct childhood development? I'm trying to correct what they deal with on a daily basis. Just walking the class. We watching my guys duck through door frames constantly. It is like some some of them are guards and they're ducking through frames. And you're just like I don't know how you've made it this far without knocking yourself out. So there's so many that it's really all about the environment and her. When I've trained my athletes, it's all about giving them the environment they have never had. So that's why we utilize the resting room. The gymnastics room. It's soft had so they know, so they don't necessarily fear the ground. They don't fear their interactions gravity. So now I'm giving them the ability to learn how to change levels. You know, little guys. So I don't see six foot ten guys wrestling, right? So I have an opportunity. Now they learn how to interact and change levels, and then even more so you put somebody with them. So now we're like pushing and pulling, just like you see in football. So now they know where they put their feet. So now we're not stepping on feet constantly looking. I mean, God, Hey, these guys are like because sixteen seventeen shoes like, of course, I'm going to step on each other's speed. But if they have that awareness in that sense of where other people are, then maybe they don't make that misstep. Or maybe they get their self out of harm's way and then even more so just learning how to fall. They learn how to fall properly from standing toe floor transitions. Then, when they jumped through the air at forty two inch words, whatever you see, that's make believe for you. Switch vertical right word, but and then they get hit in the air, and now they've got to figure out the most effective way. Not the break there. Nash. Well, most of the guys are going to do everything they can to stay on their feet. Well, that's where you want to get blown out, right? So now if I can give them a tumbling strategy, so now that they can interact with the floor a lot more smoother, athletic, well, then maybe they have a chance to not get hurt and be be back in the action, right? So it's performance enhancing as well as injury mitigation. >> I >> know that. I mean, I don't know where to begin. I have about nine comments off that. First. I love the idea of talking about how these guys are living in a world built for some one, five, ten. I'm six two and Kelsey, my girlfriend. But, hey, can you reach above and grab the top? Can apostle whatever I'm like? Yeah, Okay. But you look at a guy until you actually play hoops. I think, and really appreciate how big these dudes are. You play. It's a guy who's seven one. You look at him and go, Oh, my gosh, like that's at a different human. And then you know his shoe size next to you and you shake his hand and you get to the other side of his hand. You start to understand, like, who we dealing with here, right? You look at these, you know the body needs to heal when it goes into a stress or whatever, and we're putting these guys in positions that the body would not otherwise deem for recovery right now, like this call. Time out. Is that the funniest thing? MBA timeouts. Aside from LeBron James, that's got the nine foot chair right? These guys come out and these will stools that are too small for meaning, and >> so they're not really >> rusting. And you got a dude who's trying to recover his heart rate, but really the whole time, he's in a hip flexion. He's never been in the past, you know, thirty years, right? And if you're thinking about really taking care of an athlete, we spend so much time in the weight room and all this great stuff we can do. So Muchmore. If we had a liberty, too, I use we usually more like you, um, to you, then develop an environment that conducive to them. I know University. Kentucky did that. If you look at their dorm rooms, they had ESPN going on two years ago when they built at the new facility. For the basketball players, the sinks were higher, the magical tired, they were longer. And if you ever wash a guy who's seven foot dragging on the water fountain, I mean the amount of spinal flexion he has to go under. It's ridiculous. The guy's curling up in a C. And I mean, that's crazy to think about because the whole time on the way we were talking about how do we get these guys in a position that they can function successfully? And right now it's like optimally because obviously would have been something we did fifteen years ago to get in a position, right? But how do we get them to be successful? So I pose the question to your court. I'm gonna give you the keys to the castle. The kingdom. Okay, Philip, um, maybe not the whole environment. But there's three things you like to change the outside of the weight room that you had the crystal ball and you could go either back in time more just socially. Okay. I want to change his guys. You know, the size of his car. You know that the chair he sits and we're three things that you pick and dio >> number one. I would get them involved and dance or martial arts as their first sport. That would be probably number one so or gymnastics something. I don't care how tall you are like Who cares if you're not trying Win a gold medal at three, Right? Is just learning how to do those things right? Understanding your body number two. I would change how physical education is and in western society, um, and then number three. Let's give you something actual physical number three. If I could make what? I >> got some for you. Well, you're thinking, OK, I got you want to think your third for me? Basketball players eat horribly. You're so single, teacher. Yeah, basketball players, at least by team. And I will make this universal blanket statement. They just don't like to eat for some reason. Right? Who for? Three hours and drinking game and call it good. And I don't get it like I have a fat ass. My play. I gained weight in season. Really? Team he'll know what a food I take over which you're pulling their postgame meals. And that's when they remove the snack girl. Remember the snack role when, uh, >> you know, you have todo I had Taco Bell, bro. Like we won. We got talking about, you know? So I asked the level Appalachia, which we suck. >> I think I'm going to go a little. Can't you apologize? We're going to go play and that's a D three hoops. That's finest. We're rolling to a game. It's up north took a four hour drive and we stopped at the rude crib an hour and a half before taking a corner booth buffet of ribs. They got a bunch of island boys here. The rib crib you bring up platters were basically, you know, and capacity. And when they get like five points because our center had to pull out the throat at halftime. >> Yeah, it is. Did you ever have to drive the team ban? Because I have ways in the backseat in the bag who thought that was, like level once again, level athlete, that unreal. But I would say that the third thing Don't be wrong. Yes, food. But if there's a way, I mean, if there's a truly economical way across the board to just look, it got health, we could do that, don't care. But I can change your environment that could change your internal environment and will, And the number one is if I can just poof your gut and I can look at everything, then that will be the number one, because just a little moving world. But I don't know how you're absorbing it. I don't know what's going on. And then you wantto talk about these kids that you know, a phD or these kids that are super restless. Well, I think it starts with the gut, because if you're got health sucks, so does this. So that would be the third thing. >> No, that's crazy That way. May I have a little bit of experience is our company. I don't deal with the actual read now that the things I've learned and seeing the idea of taking that integrated approach. So hey, let's actually look at your stomach. Yes, you have to collect your poop three times a day, and I'm sorry. If you're going to do that, you can start to look at what you produced and way of excreting and whether or not you're absorbing what you need to absorb. And we start looking at injuries and no tendon, health and muscle tissue, everything as a holistic approach. What? We gotta look at the internal environment if any of our environments messed up inside and we're trying to impose a stressor on the body. But we have no idea what the internal systems like, and you have certain deficiencies or certain aspects that your lack and these were certain areas where it again people go, Oh, that's not scientific. There's no study. Well, unfortunately, if you understand complex systems and their dynamic interactions and not to get too detail, I'Ll explain it as simple as I can. But what happens is we have an outcome like a strange angle, and we say, Oh, and go weak angle get hurt, right? Well, kind of grooming. Or maybe it's ankle week. That's a risk factor. Athlete didn't sleep enough the past three nights. Risk factor Athlete had some sort of physical contact during the game. That critter there system risk factor athlete. Nutritionally, it wasn't recovering from previous workouts and games. Risk factors so happens of all these risk factors, and that's just a very there's no all the risk factors. A lot involved, all but these risk factors come about and then we have the probabilistic nature of something toe happen. So oh, how likely is it that something bad will go wrong and we see the last straw on the camel's back sprain an ankle and we go a week. But maybe it's didn't sleep enough Ankle week. All this other stuff and that ankle sprain. For people interested in complex systems, it's called an emergent pattern. So there's a common pattern that occurs when you have things go wrong. So if the money C l it's like, Oh, gluten medias is weak knee Val Agus. All right, you're a muscular control all these things that go into and nothing can pinpoint it. So if we're including these bomber, you know about mechanical factors and Eve Alvis, why aren't we including some internal factors like gut health Or, you know, the blood wood for the micro nutrient efficient season? Yes, I know I'm not versed enough to speak on micronutrient deficiencies and our interactions off, you know, health and whatnot. But something as simple as college in environments haven't adequate vitamin C for, you know, ten and healing instead of, you know, repair is obviously a factor. And so when we start looking the bottom, we gotta look at the big picture. It's not just how your knee bends. It's not how you shoot a jump shot. It's not how you land every time. >> Where are you? Our body is so much more resilient and durable than you. Give it credit for me. We've survived as a species. We're a very long time. You're very harsh conditions and you're going to tell me it's that one jump that got you one job. One job is the one that Oh, that needs a little dalliance. That's the one that got you. I mean, if you super slow mo A lot of these great expressions of physical capacity in sport it was you would be like, Oh, my God, they're neither this there that But in reality, like that's I'm close to the reason why they like break or don't Break. And Jordan shallow, brilliant dude, He gave me this metaphor. He was saying to Philip, a pond, Well, it's like this fungus that will Philip a pond and it doubles its size every day. So if it starts off it like, you know, point two, then the next day be point for and he asked me, he's like, Okay, if it's going to Philip in thirty days, Philip, the whole pond, What's the day? It's half full. Then I thought for a second it took me a lot longer than I should have thought about it. But he's like, but he an injection goes day twenty nine. I >> don't want an answer, by the way. >> Yeah, was like Day twenty nine I. That's why I look at the human body like that is literally the last thing and then pull. And so it's all these. We could have had all these interventions from day to today twenty eight or day twenty nine. Even the notes that one just last. Ah, strong. The camel's back to just there goes, you know, And that's what's great about being in the collegiate setting. And being a Stanford is we have a lot of safety nets for our safety, and that's if you will. So we try to have as many quote unquote KP eyes and objective measurements to give us an idea of what could possibly happen. But in reality, it's still the dynamic environment, so I don't understand. Like I can't account for school. I can't account for their sleep. I mean, we could through, like, grouper or or whatever, but it's not realistic and thine and are setting and in their gut hell's like way picking up poop. Three times a day. They were not drawn blood once. We're not doing these things. So unless we're doing that, then you're just trying to create most resilient, durable human beings so they can withstand the stressors some more than others. But hopefully have a successful season. >> No, that's like I hate to break it to people. We don't know what we're doing. We're doing our best. I think chase Wells with him. A Stanford. Get a great line, he said. We can't guarantee success. We can almost guarantee you're not guaranteed to fail. And what I mean by that is that you can't always KP eyes and really, we're looking at. If you jump nine inches, we're probably not going to be very good basketball unless you're seven. No, right. And so we're looking at the human system as a means of understanding what is going on really lagged behind in regards to your performance assessment and what might be hindering you in regards to launch into no tracking? Can I get a little bit of data? A lot? The way explain it is kind of like I don't ask my girlfriend Kelsey, how she's doing. Once a week, you know. I asked her every day and why I asked that every day is to realize, you know, all my clothes that I left out pissing her off. You know, I did. I forget that we're supposed to go on a date last night. You know, I might not have forgot a wallet last night. We went to dinner from now on, Accent, all supposed to buy. But that's a true story. WeII >> brought up. I mean, that's the most important thing is you gotta have feedback daily, right? And wait here. It's really simple. We take a controlled environment, do some things in it before they go into a dynamic environment, which is basketball games of basketball practice. So what we do is we call that microdot. It's our way of training. Every day, in some form or fashion, these individuals come into their work, their human capacity, a Siri's, if you will. Then after that, they go into their B series, which is complex. This is really what I know what's going on. I don't get me wrong when they walk in to get their weight, are joking or making eye contact and get that handshake. How firm is that handshake thes air, All the quantitative things that I'm trying to pick up as they're coming through the door. Then you watch them say We're hitting clean, complex and they're going through the motions and their consulate changing grip or or the pool isn't looking too good, and any sharp today will boom. That's my control Now. It's not the most objective feedback, but at least it's a constant. And so that's my way of having once against safety nets from a safety nets and then weekly or depending on how many games we have that we do, our force plate jumps. So once again, another safety net, and then we have our connects on day. So our GPS data that they do on the practice gym once again any one of those in isolation doesn't tell me much. But if I have a bunch of them, then I can at least paint a better picture from quantitative qualitative, and then I can go and knit. Pick what I think they're intervention may need to be, and so it's not going to be perfect, not even close, but as long as you have a constant and yours is beautiful. Like you said, Just something simple. You get daily. Hey, how are you doing? And you know how they express that. I'm doing good. I'm doing good. I'm cool. I'm great. Like, you know, what there was in flux is are like, you know what? They're how they're truly feeling. Just based off that one question alone. But once again, if you can set up your system or your program or whatever toe have safety nets for your safety nets, then I think you can You can catch a >> lot of those along the way. >> Yeah. No, that makes sense. It's how you provide context to a situation. And the more information that we can apply that we didn't classifier more to a system like jumping is, you know, your lower body strength and your verbal expressions, your most emotional state on DH, maybe even sweep or other things that go into that, the more we could understand what's actually happening to the person. So I was kind of really bad for a second. You said some of micro dose in and term overdose. You refer into training a little bit often. Yep. And Corey is well known for this and for those at home listening, I'm going to my best to explain it. Short weeks. I got a question off of it. If you know, explains it will stay here for another hour and a half because great to listen to. But I want Teo a little bit of a different direction off of athletics about it. Firstly, micro doses the idea that we're applying a moderate level toe, low level stressor consistently, and that adaptation occurs from the aggravation off those dresses over a period of time. So we're never going to Hi, we're never going to low. And the idea is that training in the weight room is only one small piece of your life. They even programmed High Day, and you don't sleep that night or you have emotional stressor for your case, your practice. Then all of a sudden, that high, big, magnified and starts spilling over the bar and becomes too much the idea of micro dozing, especially a non controlled external environment where it's called life, and we're trying to apply enough that you can handle. If someone's feeling good, then they can push a little bit that they themselves. Now My question for you, Cory, is I love an athletic sense. I also see it being very applicable to anyone out there general population and especially in terms of I got two things. Us too. In terms of one, someone learned a movement. You get a chance to do it often and daily and someone who wants to learn how to be in the weight room. And secondly, because there are, let's say we do it eight out of ten days. If you only miss one day, you're only missing ten percent of your entire workout, right? So instead of doing looking at this whole one workout one day, you look at like a ten day period. If you got eight days of pick from and you just can't do one, you only missed ten percent versus if you only had five days of pick one and you miss one, you missed twenty percent, right? And so now we have the ability to be more flexible in our environment. So how does that fit in like a general population? If it was my dad or my girlfriend trying to learn howto use some of this micro dose in the weight room. How do you plan? >> So one hundred percent with micro dozing. The reason why it came about was it was a solution to a problem. My problem is I don't have enough exposure to my guys. So how do I create more training frequency? And now we got rid of warm up something that was just kind of getting them ready for practice. That kind of don't care about it. The coach hated seen me do it. I personally hated doing it. So now it was a solution. What it turned into was motor learning. Now you want to learn how to train, will do it all the time. So that's where complex comes in. It's the value of orcs work, right? So basically, you take a bar bill and you do every movement that you would do in a weight room, in some sense, in one set, so you'd hinge You do a hip flexion. You do a press, do a pool. If I break down each one of those into isolation, it would look like already else Squad, Polish, military, press or row, those air all movements that you would do and if you separated each exercise in an isolation you would go more resistance on, just like you would see in general fitness, right? Like we're going to do three sets of ten on bench press or three sets a tent on back squad. Well, that's great. How about we just put it all in one and now we have more exposure. So now I'm learning how to do the movements, and then you can't tell me that doing one thing once a week is actually going to make you learn the movement. So now you learn those little small video sequences that you see with thirty year experience power lifters who truly understand, like, move from body, this foot stance, or this is how I start to hinge here within my squat X degree. And that's how they perfected is because they have so much exposure to it. So we're doing the same thing. We're just trying to create exposure at lower thresholds and and in doing it often now as faras general population, what's the number one concern? But I don't have enough time. Oh, really? You don't have a thirty minute today, twenty to thirty minutes a day to not kind ofwork. Now. Every day I call B s. I say You just don't want to train. So that's where my producing to me is beautiful in the general population is because it's living the way you start your day. It's lunch, or it's when you get off work. Perfect. You can pick any of those three slots twenty, thirty minutes. You can eat and shower and get backto work or before work. So you can't tell me that everybody doesn't have that situation. So now, creating training frequency, you're getting enough volume throughout the week. Now we have on and then most importantly, like you brought up if I just had to miss that one day, it's ten percent of my training like it's not well, only train twice a week, So fifty percent of my training is gone. So that's where I think it's beautiful. And that's where he could work from general population to the most elite athletes in the world and the reason why I say the most elite athletes in the world because I just so happen to train to of So I do it with all these populations

>> Live from Orlando, Florida, it's theCUBE, covering Enterprise Connect 2019. Brought to you by, Five9. >> Welcome to theCUBE I'm Lisa Martin with Stu Mennamen. We are live on the show floor at Enterprise Connect 2019. Stu, welcome to Orlando! >> Thanks so much Lisa, great to be with you, (amplified voice echoing) and real excited to be here at Enterprise Connect. >> Likewise, and as you can hear, the show floor just opened, so we have a nice, conflicting overhead announcement. But Stu, this event is really interesting because it has evolved dramatically over the last 28, 29 years, where it was PBX, and then Voice Con. and for the last what, eight or so, it's been Enterprise Connect. As has, in terms of evolution, evolved enterprise communications, enterprise collaborations, cloud, AI, et cetera. Lot's of things and exciting news to talk about this week. >> Yeah Lisa, like any show, you say how are you relevant today? What is changing? What is staying the same? And as you said, 29 years of this show, first time we're going live here with theCUBE. But yeah, it is now, you know, unified communications. We're talking about cloud-based contact centers, like our friends here at Five9, who brought us here to the show, but 6,500 people is what I heard from the people that run the show. And it's been growing, it's been, you know, how do things like cloud and AI really transform some of these markets and at least in some ways, there are some things that remind me of what I worked on in this hotel communication space back in the late 90's, and some of those things are drastically different. So you know, we're not talking about call centers, we're talking about contact centers and that consumer experience. How data, and mobile, and the internet, and cloud, are changing, is definitely something that we're going to be digging into a lot this week. >> Yes, and another thing that we're going to dig into is this rising change in the empowerment of the consumer, right? We're consumers every day, we want to be able to transact, or get information on a mortgage or something from whatever channel we want, omnichannel is really going to be a key theme here. It's being able to talk to the customer where they want to be communicated with, and ensuring though, that it's not just, maybe you start out on web, and you go to chat, then maybe it's a call, maybe even as an escalation through Twitter. But that the organization that you're trying to engage with, has a contact center that can follow your trail, and follow your data, to be able to understand what the real issue is, and in a timely manner, empower that agent who's talking to you, whatever medium, to act correctly so you don't churn. >> Yeah, Lisa as you know, there's something that our audience, everyone has had to call support at one time or another. Myself, you know, I tend to troubleshoot a lot of stuff myself. When I actually want to call in, I want to get the answers, I don't want to have to spend a long time going through some robotic, you know, hi, give me an agent please, give me an agent, agent, agent. And then when I get to that person, I don't want to have to go through steps one through 17 because I've already done that myself so, how do I escalate fast? If I can do that all online or in chat, even better for me, because you know, I don't necessarily want to have to talk to a person, but when I do want to talk to a person, I want them to understand my environment, help me get there. And that's where a lot of these environments are helping today. How is it, you know, do I understand the client? Can I help them with where they need to be? And super hot-button is, you know, what about data? You know, how is the role of data in these environments changing? As a consumer, if there's certain things that I'm using, and I'm worried about them, talking about my privacy. But when it comes to the support experience, absolutely, I want you to understand who I am in the context and take care of things fast. >> You mentioned AI and one of the things that I'm curious to learn about this week is, is the maturation of that. But also something that you and I hear at pretty much every show theCUBE goes to, which is a lot, and that is, it's not about completely transforming to AI, there has to be a human AI combination to really, extract the most value from these experiences. >> Yeah, Lisa, you bring up a great point there. So right, automation and robots, absolutely are playing a bigger and bigger role, but the answer is not, you know, it's not binary, it's not one or the other, it's how can intelligence, and machines augment what they're doing? And when you talk to the contact center people, absolutely it's about, how do I get people information faster? How do I make those agents react faster and hopefully have a better job? You know when you talk about the people, and you know, Lisa my first job out of school, I worked in a call center and if you're answering calls all day, or answering emails, you know that's something that you have to do day-after-day and it can be tough. So if there's automation intelligence that can take care of it, prompt you with the information you need, help lead you along the way, help you get to mastery and resolution so much faster, that's all goodness. We want both the consumer and the employees to have a better experience and there's the promise that AI, and automation, and robots can all help with that experience. Not just a wholesale, let's rip out the people and put in technology. >> No, you're absolutely right, and it also is, I'm curious to learn too this week about, the employee training. One of the interviews you did recently in the Boston CUBE studio, the guest there mentioned, I recommend every C-level spend some amount of time in the call, contact center, to understand, are our processes efficient? If there's Sticky Notes and paper everywhere, we probably have some process challenges. But are those agents empowered to make the right decisions at the right time in order to, like I said before, prevent churn, and increase the customer lifetime value. So that customer experience is table stakes all the way up to the C-suite. >> Yeah I mean Lisa, as we know, if you talk to any marketer, and say, what do you want? I want to know what my customer wants. What do they need? What are the challenges? And when a customer's reaching out with a problem, that can be a great opportunity. Now hopefully there, you can solve their issue, because the concern is, maybe they won't even reach out. You know, if it's not on my website, if I tried to do it, or I had to wait too long, I might go turn to a competitor. It's easier sometimes just to leave. And we know every time, one person calls, there's usually many more that didn't call, that might've had that same issue. So, understanding where I can engage, more touchpoints with our customers is a good thing, and how can we leverage that into a good experience? And I know when I look into the contact center, it's not just the inbound requests, but how did that tie into outbound conversations? >> And enabling an organization to use that data, in a trusted manner as you mentioned, to switch from being reactive, to proactive, to eventually, predictive. But one of the points you mentioned is very valid and that is, for every customer that initiates a conversation through a contact center, there's probably exponential more customers with the same problem that aren't. So these companies need to be using AI in the cloud contact center as a service to really understand it's the customer that's telling you what the problem is, how do you get that information gleaned from it? You know, starting to use analytics and things that probably back in your early call center days, you didn't have access to, to really hone in on what that problem is, how prevalent is this problem? So do we need to throw a lot of resources at solving this, because this is going to ultimately help drive our business forward? >> Yeah, absolutely and Lisa, these are the kind of things that we talk about in the cloud world today, which has a huge impact on this show is, I have contacts with customers, we have engagement and data there, and what other services are there that will plug into this environment? So AI, you asked about the maturity, at least from what I've seen so far, we are early days in seeing that roll out. But, there's a lot of other technologies here. You talk about cloud, talk about text-to-speech, talk about devices that will help whether it's not just phones, and headsets and the like, but lots of other tools, that the enterprise uses to connect with their ultimate end users themselves, hence, Enterprise Connect. The communication at the center of it all. And it's interesting here in 2019, to see that relevance, and that intersection of the people and the technology to hopefully help people have better relationships longterm with their customers. >> Absolutely, so you mentioned, we're in the booth at Five9 here, there's about 140 exhibitors here, you mentioned 6,500 attendees here in Orlando. 60 plus sessions across nine tracks, unified communication, cloud communications, team collaborations, we've got Jace Moreno from Microsoft Teams on shortly with us today, so it's going to be a very interesting week. I'm very much looking forward to co-hosting with you and learning a lot about how the consumer is really driving, and has a table at the decision-making table within organizations. >> Yeah absolutely, and Lisa we've got a great line up. Really two and a half days, a half-day today from three to seven and then the full days from right after the keynote through the ending. The expo floor just opened up, a great buzz here already at the show, I'm looking forward to being able to walk around and see some of the technology, and some great guests on the program. Of course our friends here at Five9 who brought us here, we've got the CEO of Poly, rebranded Plantronics and PolyCom, the CIO of Zoom, and many other guests on the program, some of the industry analysts and the like. So, real excited to dig in and always a pleasure Lisa, to be digging in with you. >> Likewise, thanks Stu, I'm excited to learn more about this contact center as a service market. It seems early days as you mentioned. And I always appreciate it when businesses identify that. No we don't have all the answers for AI and the combination of humans and machines, it's early days, early innings as you said, but they're here to learn from each other, and understand how it is that they can really influence and drive these kinds of conversations forward. >> Yeah the fun fact on that, I was listening to a podcast on the way to the airport and it talked about actually, with all the data that we have today, often times the answer is easy, it's I need to be able to ask the right questions. And Lisa, you and I know a thing or two about trying to ask the right questions. >> We do. >> So we have lots of opportunities to do that this week. And hear how all the people in this ecosystem are thinking about asking better questions and getting to their customers. >> Yeah, so I predict it's going to be a thought-provoking week Stu, I'm looking forward to being here with you. We want to thank you for watching theCUBE's kickoff of our live coverage of Enterprise Connect 2019, day one of three, stick around, Stu and I will be right back with our first guest. (upbeat synth music)