(upbeat music) >> Hello, brilliant humans and welcome back to theCUBE. We're live from Detroit, Michigan. My name is Savannah Peterson. Joined here with John Furrier, John, so exciting, day three. >> Day three, cranking along, doing great, final day of KubeCon, it wraps up. This next segment's going to be great. It's about WebAssembly, the hottest trend here, at KubeCon that nobody knows about cause they just got some funding and it's got some great traction. Multiple players in here. People are really interested in this and they're really discovering it. They're digging into it. So, we're going to hear from one of the founders of the company that's involved. So, it'll be great. >> Yeah, I think we're right at the tip of the iceberg really. We started off the show with Scott from Docker talking about this, but we have a thought leader in this space. Please welcome Matt Butcher the CEO and co-founder of Fermyon Thank you for being here. Welcome. >> Yeah, thanks so much for having me. Favorite thing to talk about is WebAssembly after that is coffee but WebAssembly first. >> Hey, it's the morning. We can talk about both those on the show. (all chuckles) >> It might get confusing, but I'm willing to try. >> If you can use coffee as a metaphor to teach everyone about WebAssembly throughout the rest of the show. >> All right. That would be awesome. >> All right I'll keep that in mind. >> So when we were talking before we got on here I thought it was really fun because I think the hype is just starting in the WebAssembly space. Very excited about it. Where do you think we're at, set the stage? >> Honestly, we were really excited to come here and see that kind of first wave of hype. We came here expecting to have to answer the question you know, what is WebAssembly and why is anybody looking at it in the cloud space, and instead people have been coming up to us and saying, you know this WebAssembly thing, we're hearing about it. What are the problems it's solving? >> Savannah: Yeah. >> We're really excited to hear about it. So, people literally have been stopping us in restaurants and walking down the street, hey, "You're at KubeCon, you're the WebAssembly people. Tell us more about what's going on." >> You're like awesome celeb. I love this. >> Yeah, and I, >> This is great >> You know the, the description I used was I expected to come here shouting into the void. Hey, you know anybody, somebody, let me tell you about WebAssembly. Instead it's been people coming to us and saying "We've heard about it. Get us excited about it," and I think that's a great place to be. >> You know, one of the things that's exciting too is that this kind of big trend with this whole extraction layer conversation, multicloud, it reminds me of the old app server days where, you know there was a separation between the back end and front end, and then we're kind of seeing that now with this WebAssembly Wasm trend where the developers just want to have the apps run everywhere and the coding to kind of fall in, take a minute to explain what this is, why it's important, why are people jazzed about there's other companies like Cosmonic is in there. There's a lot of open source movement behind it. You guys are out there, >> Savannah: Docker. >> 20 million in fresh funding. Why is this important? What is it and why is it relevant right now? Why are people talking about it? >> I mean, we can't... There is no penasia in the tech world much for the good of all of us, right? To keep us employed. But WebAssembly seems to be that technology that just sort of arose at the right time to solve a number of problems that were really feeling intractable not very long ago. You know, at the core of what is WebAssembly? Well it's a binary format, right? But there's, you know, built on the same, strain of development that Java was built on in the 90's and then the .net run time. But with a couple of little fundamental changes that are what have made it compelling today. So when we think about the cloud world, we think about, okay well security's a big deal to us. Virtual machines are a way for us to run other people's untrusted operating systems on our hardware. Containers come along, they're a... The virtual machine is really the heavyweight class. This is the big thing. The workhorse of the cloud. Then along come Containers, they're a little slimmer. They're kind of the middleweight class. They provide us this great way to sort of package up just the application, not the entire operating system just the application and the bits we care about and then be able to execute those in a trusted environment. Well you know, serverless was the buzzword a few years ago. But one thing that serverless really identified for us is that we didn't actually have the kind of cloud side architecture that was the compute layer that was going to be able to fulfill the promise of serverless. >> Yeah. >> And you know, at that time I was at Microsoft we got to see behind the curtain and see how Azure operates and see the frustration with going, okay how do we get this faster? How do we get this startup time down from seconds to hundreds of milliseconds, WebAssembly comes along and we're able to execute these things in sub one millisecond, which means there is almost no cost to starting up one of these. >> Sub one millisecond. I just want to let everyone rest on that for a second. We've talked a lot about velocity and scale on the show. I mean everyone here is trying to do things faster >> Yep >> Obviously, but that is a real linchpin that makes a very big difference when we're talking about deploying things. Yeah. >> Yeah, and I mean when you think about the ecological and the cost impact of what we're building with the cloud. When we leave a bunch of things running in idle we're consuming electricity if nothing else. The electricity bill keeps going up and we're paying for it via cloud service charges. If you can start something in sub one millisecond then there's no reason you have to leave it running when nobody's using it. >> Savannah: Doesn't need to be in the background. >> That's right. >> So the lightweight is awesome. So, this new class comes up. So, like Java was a great metaphor there. This is kind of like that for the modern era of apps. >> Yeah. >> Where is this going to apply most, do you think? Where's it going to impact most? >> Well, you know, I think there are really four big categories. I think there's the kind of thing I was just talking about I think serverless and edge computing and kind of the server class of problem space. I think IOT is going to benefit, Amazon, Disney Plus, >> Savannah: Yes, edge. >> And PBS, sorry BBC, they all use WebAssembly for the players because they need to run the same player on thousands of different devices. >> I didn't even think about that use case. What a good example. >> It's a brilliant way to apply it. IOT is a hard space period and to be able to have that kind of layer of abstraction. So, that's another good use case >> Savannah: Yeah. >> And then I think this kind of plugin model is another one. You see it was Envoy proxy using this as a way to extend the core features. And I think that one's going to be very, very promising as well. I'm forgetting one, but you know. (all chuckles) I think you end up with these kind of discreet compartments where you can easily fit WebAssembly in here and it's solving a problem that we didn't have the technology that was really adequately solving it before. >> No, I love that. One of the things I thought was interesting we were all at dinner, we were together on Tuesday. I was chatting with Paris who runs Deliveroo at Apple and I can't say I've heard this about too many tools but when we were talking about WebAssembly she said "This is good for everybody" And, it's really nice when technologies come along that will raise the water level across the board. And I love that you're leading this. Speaking of you just announced a huge series aid, 20 million dollars just a few days ago. What does that mean for you and the team? >> I mean there's a little bit of economic uncertainty and it's always nice, >> Savannah: Just a little bit. >> Little bit. >> Savannah: It's come up on the show a little bit this week >> Just smidge. and it's nice to know that we're at a critical time developing this kind of infrastructure layer developing this kind of developer experience where they can go from, you know, blinking cursor to deployed application in two minutes or less. It would be a tragedy if that got forestalled merely because you can't achieve the velocity you need to carry it out. So, what's very exciting about being able to raise around like that at this critical time is that gives us the ability to grow strategically, be able to continue releasing products, building a community around WebAssembly as a whole and of course around our products at Fermyon is a little smaller circle in the bigger circle, and that's why we are so excited about having closed around, that's the perfect one to extend a runway like that. >> Well I'm super excited by this because one I love the concept. I think it's very relevant, like how you progress heavyweight, middleweight, maybe this is lightweight class. >> I know, I'm here for the analogy. No, it's great, its great. >> Maybe it's a lightweight class. >> And we're slimming, which not many of us can say in these times so that's awesome. >> Maybe it's more like the tractor trailer, the van, now you got the sports car. >> Matt: Yeah, I can go.. >> Now you're getting Detroit on us. >> I was trying for a coffee, when I just couldn't figure it out. (all chuckles) >> So, you got 20 million. I noticed the investors amplify very good technical VC and early stage firm. >> Amazing, yeah. >> Insight, they do early stage, big early stage like this. Also they're on the board of Docker. Docker was intent to put a tool out there. There's other competition out there. Cosmonic is out there. They're funded. So you got VC funded companies like yourselves and Cosmonic and others. What's that mean? Different tool chains, is it going to create fragmentation? Is there a common mission? How do you look at the competition as you get into the market >> When you see an ecosystem form. So, here we are at KubeCon, the cloud native ecosystem at this point I like to think of them as like concentric rings. You have the kind of core and then networking and storage and you build these rings out and the farther out you get then the easier it is to begin talking about competition and differentiation. But, when you're looking at that core piece everybody's got to be in there together working on the same stuff, because we want interoperability, we want standards based solutions. We want common ways of building things. More than anything, we want the developers and operators and users who come into the ecosystem to be able to like instantly feel like, okay I don't have to learn. Like you said, you know, 50 different tools for 50 different companies. "I see how this works", and they're doing this and they're doing this. >> Are you guys all contributing into the same open source? >> Yep, yeah, so... >> All the funding happens. >> Both CNCF and the ByteCode Alliance are organizations that are really kind of pushing forward that core technology. You know, you mentioned Cosmonic, Microsoft, SOSA, Red Hat, VMware, they're all in here too. All contributing and again, with all of us knowing this is that nascent stage where we got to execute it. >> How? >> Do it together. >> How are you guys differentiating? Because you know, open source is a great thing. Rising Tide floats all boats. This is a hot area. Is there a differentiation discussion or is it more let's see how it goes, kind of thing? >> Well for us, we came into it knowing very specifically what the problem was we wanted to solve. We wanted this serverless architecture that executed in sub one millisecond to solve, to really create a new wave of microservices. >> KubeCon loves performance. They want to run their stuff on the fastest platform possible. >> Yeah, and it shouldn't be a roadblock, you know, yeah. >> And you look at someone like SingleStore who's a database company and they're in it because they want to be able to run web assemblies close to the data. Instead of doing a sequel select and pulling it way out here and munging it and then pushing it back in. They move the code in there and it's executing in there. So everybody's kind of finding a neat little niche. You know, Cosmonic has really gone more for an enterprise play where they're able to provide a lot of high level security guarantees. Whereas we've been more interested in saying, "Hey, this your first foray into WebAssembly and you're interested in serverless we'll get you going in like a couple of minutes". >> I want to ask you because we had Scott Johnston on earlier opening keynote so we kind of chatted one-on-one and I went off form cause I really wanted to talk to him because Docker is one of the most important companies since their pivot, when they did their little reset after the first Docker kind of then they sold the enterprise off to Mirantis they've been doing really, really well. What's your relationship to Docker? He was very bullish with you guys. Insights, joint investor. Is there a relationship? You guys talk, what's going on there? >> I mean, I'm going to have to admit a little bit of hero worship on my part. I think Scott is brilliant. I just do, and having come from the Kubernetes world the Fermyon team, we've always kind of kept an eye on Docker communicated with a lot of them. We've known Justin Cormack for years. Chris Cornett. (indistinct) I mean yeah, and so it has been a very natural >> Probably have been accused of every Docker Con and we've did the last three years on the virtual side with them. So, we know them really well. >> You've always got your finger on the pulse for them. >> Do you have a relationship besides a formal relationship or is it more of pass shoot score together in the industry? >> Yeah. No, I think it is kind of the multi-level one. You come in knowing people. You've worked together before and you like working with each other and then it sort of naturally extends onto saying, "Hey, what can we do together?" And also how do we start building this ecosystem around us with Docker? They've done an excellent job of articulating why WebAssembly is a complimentary technology with Containers. Which is something I believe very wholeheartedly. You need all three of the heavyweight, middleweight, lightweight. You can't do all the with just one, and to have someone like that sort of with a voice profoundly be able to express, look we're going to start integrating it to show you how it works this way and prevent this sort of like needless drama where people are going, oh Dockers dead, now everything's WebAssembly, and that's been a great.. >> This fight that's been going on. I mean, Docker, Kubernetes, WebAssembly, Containers. >> Yeah. >> We've seen on the show and we both know this hybrid is the future. We're all going to be using a variety of different tools to achieve our goals and I think that you are obviously one of them. I'm curious because just as we were going on you mentioned that you have a PhD in philosophy. (Matt chuckles) >> Matt: Yeah. >> Which is a wild card. You're actually our second PhD in philosophy working in a very technical role on the show this week, which is kind of cool. So, how does that translate into the culture at Fermyon? What's it like on the team? >> Well, you know, a philosophy degree if nothing else teaches you to think in systems and both human systems and formal systems. So that helps and when you approach the process of building a company, you need to be thinking both in terms of how are we organizing this? How are we organizing the product? How do we organize the team? We have really learned that culture is a major deal and culture philosophy, >> Savannah: Why I'm bringing it up. >> We like that, you know, we've been very forward. We have our chip values, curiosity, humility inclusivity and passion, and those are kind of the four things that we feel like that each of us every day should strive to be exhibiting these kinds of things. Curiosity, because you can't push the envelope if you don't ask the hard questions. Humility, because you know, it's easy to get cocky and talk about things as if you knew all the answers. We know we don't and that means we can learn from Docker and Microsoft >> Savannah: That's why you're curious. >> And the person who stops by the booth that we've never met before and says, "hey" and inclusivity, of course, building a community if you don't execute on that well you can't build a good community. The diversity of the community is what makes it stronger than a singular.. >> You have to come in and be cohesive with the community. >> Matt: Yeah. >> The app focus is a really, I think, relevant right now. The timing of this is right online. I think Scott had a good answer I thought on the relationship and how he sees it. I think it's going to be a nice extension to not a extension that way, but like. >> It probably will be as well. >> Almost a pun there John, almost a pun. >> There actually might be an extension, but evolution what we're going to get to which I think is going to be pure application server, like. >> Yep, yep. Like performance for new class of developer. Then now the question comes up and we've been watching developer productivity. That is a big theme and our belief is that if you take digital transformation to its conclusion IT and developers aren't a department serving the business they are the business. That means the developer workflows will have to be radically rebuilt to handle the velocity and new tech for just coding. I call it architectural list. >> I like that. I might steal that. >> It's a pun, but it's also brings up the provocative question. You shouldn't have to need an architecture to code. I mean, Java was great for that reason in many ways. So, if that happens if the developers are running the business that means more apps. The apps is the business. You got to have tool chains and productivity. You can't have fragmentation. Some people are saying WebAssembly might, fork tool chains, might challenge the developer productivity. what's your answer to that? How would you address that objection? >> I mean the threat of forking is always lurking in the corner in open source. In a way it's probably a positive threat because it keeps us honest it keeps us wanting to be inclusive again and keep people involved. Honestly though, I'm not particularly worried about it. I know that the W-3 as a standards body, of course, one of the most respected standards bodies on the planet. They do html, they do cascading style sheets. WebAssembly is in that camp and those of us in the core are really very interested in saying, you know, come on in, let's build something that's going to be where the core is solid and you know what you got and then you can go into the resurgence of the application server. I mean, I wholeheartedly agree with you on that, and we can only get there if we say, all right, here are the common paradigms that we're all going to agree to use, now let's go build stuff. >> And as we've been saying, developers are setting, I think are going to set the standards and they're going to vote with their code and their feet, if you will. >> Savannah: A hundred percent. >> They will decide if you're not aligning with what they want to do. okay. On how they want to self-serve and or work, you'll figure that out. >> Yep, yep. >> You'll get instant feedback. >> Yeah. >> Well, you know, again, I tell you a huge fan of Docker. One of the things that Docker understood at the very outset, is that they had an infrastructure tool and developers were the way to get adoption, and if you look at how fast they got adoption versus many, many other technologies that are profoundly impacted. >> Savannah: Wild. >> Yeah. >> Savannah: It's a cool story. >> It's because they got the developers to go, "This is amazing, hey infrastructure folks, here's an infrastructure tool that we like" and the infrastructure folks are used to code being tossed over the wall are going, "Are you for real?" I mean, and that was a brilliant way to do it and I think that what.. >> John: Yeah, yeah. >> We want to replay in the WebAssembly world is making it developer friendly and you know the kind of infrastructure that we can actually operate. >> Well congratulations to the entire community. We're huge fans of the concept. I kind of see where it's going with connect the dots. You guys getting a lot of buzz. I have to ask you, my final question is the hype is beyond all recognition at this point. People are super pumped and enthusiastic about it and people are looking at it maybe some challenging it, but that's all good things. How do you get to the next level where people are confident that this is actually going to go the next step? Hype to confidence. We've seen great hype. Envoy was hyped up big time before it came in, then it became great. That was one of my favorite examples. Hype is okay, but now you got to put some meat on the bone. The sizzle on the stake so to speak. So what's going to be the stake for you guys as you see this going forward? What's the need? >> Yeah, you know, I talk about our first guiding story was, you know, blinking cursor to deployed application in two minutes. That's what you need to win developers initially. So, what's the next story after that? It's got to be, Fermyon can run real world applications that solve real world problems. That's where hype often fails. If you can build something that's neat but nobody's quite sure what to do with it, to use it, maybe somebody will discover a good use. But, if you take that gambling asset, >> Savannah: It's that ending answer that makes the difference. >> Yeah, yeah. So we say, all right, what are developers trying to build with our platform and then relentlessly focus on making that easier and solving the real world problem that way. That's the crucial thing that's going to drive us out of that sort of early hype stage into a well adopted technology and I talk from Fermyon point of view but really that's for all of us in the WebAssembly. >> John: Absolutely. >> Very well stated Matt, just to wrap us up when we're interviewing you here on theCUBE next year, what do you hope to be able to say then that you can't say today? >> All this stuff about coffee we didn't cover today, but also.. (all chuckles) >> Savannah: Here for the coffee show. Only analogies, that's a great analogy. >> I want to walk here and say, you know last time we talked about being able to achieve density in servers that was, you know, 10 times Kubernetes. Next year I want to say no, we're actually thousands of times beyond Kubernetes that we're lowering people's electricity bill by making these servers more efficient and the developers love it. >> That your commitment to the environment is something I want to do an entirely different show on. We learned that 7-8% of all the world's powers actually used on data centers through the show this week which is jarring quite frankly. >> Yeah, yeah. Tragic would be a better way of saying that. >> Yeah, I'm holding back so that we don't go over time here quite frankly. But anyways, Matt Butcher thank you so much for being here with us. >> Thank you so much for having me it was pleasure.. >> You are worth the hype you are getting. I am grateful to have you as our WebAssembly thought leader. In addition to Scott today from Docker earlier in the show. John Furrier, thanks for being my co-host and thank all of you for tuning into theCUBE here, live from Detroit. I'm Savannah Peterson and we'll be back with more soon. (ambient music)

>>Hey, everyone. Welcome back to accelerating analytics, maturity. I'm your host. Lisa Martin, Alan Jacobson joins me next. The chief data and analytics officer at Altrix Ellen. It's great to have you on the program. >>Thanks Lisa. >>So Ellen, as we know, everyone knows that being data driven is very important. It's a household term these days, but 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. What's your advice, your recommendations for organizations who are just starting out with analytics >>And you're spot on many organizations really aren't leveraging the, the full capability of their knowledge workers. And really the first step is probably assessing where you are on the journey, whether that's you personally, or your organization as a whole, we just launched an assessment tool on our website that we built with the international Institute of analytics, that in a very short period of time, in about 15 minutes, you can go on and answer some questions and understand where you sit versus your peer set versus competitors and kind of where you are on the journey. >>So when people talk about data analytics, they often think, ah, this is for data science experts like people like you. So why should people in the lines of business like the finance folks, the marketing folks, why should they learn analytics? >>So domain experts are really in the best position. They, they know where the gold is buried in their companies. They know where the inefficiencies are, and it is so much easier and faster to teach a domain expert a bit about how to automate a process or how to use analytics than it is to take a data scientist and try to teach them to have the knowledge of a 20 year accounting professional or a, or a logistics expert of your company. It much harder to do that. And really, if you think about it, the world has changed dramatically in a very short period of time. If, if you were a marketing professional 30 years ago, you likely didn't need to know anything about the internet, but today, do you know what you would call that marketing professional? If they didn't know anything about the internet, probably unemployed or retired. And so knowledge workers are having to learn more and more skills to really keep up with their professions. And analytics is really no exception. Pretty much in every profession, people are needing to learn analytics, to stay current and, and be capable for their companies. And companies need people who can do that. >>Absolutely. It seems like it's table stakes. These days, let's look at different industries. Now, are there differences in how you see analytics in automation being employed in different industries? I know Altrix is being used across a lot of different types of organizations from government to retail. I also see you're now with some of the leading sports teams, any differences in industries. >>Yeah. There's an incredible actually commonality between domains industry to industry. So if you look at what an HR professional is doing, maybe attrition analysis, it's probably quite similar, whether they're in oil and gas or in a high tech software company. And so really the similarities are, are much larger than you might think. And even on the, on, on the, on the sports front, we see many of the analytics that sports teams perform are very similar. So McLaren is one of the great partners that we work with and they use TRICS across many areas of their business from finance to production, extreme sports, logistics, wind tunnel engineering, the marketing team analyzes social media data, all using Altrics. And if I take as an example, the finance team, the finance team is trying to optimize the budget to make sure that they can hit the very stringent targets that F1 sports has. And I don't see a ton of difference between the optimization that they're doing to hit their budget numbers and what I see fortune 500 finance departments doing to optimize their budget. And so really the, the commonality is very high. Even across industries. >>I bet every F fortune 500 or even every company would love to be compared to the same department within McLaren F1, just to know that wow, what they're doing is so in incre incredibly important as is what we are doing. Absolutely. So talk about lessons learned, what lessons can business leaders take from those organizations like McLaren, who are the most analytically mature >>Probably first and foremost, is that the ROI with analytics and automation is incredibly high. Companies are having a ton of success. It's becoming an existential threat to some degree, if, if your company isn't going on this journey and your competition is it, it can be a, a huge problem. IDC just did a recent study about how companies are unlocking the ROI using analytics. And the data was really clear organizations that have a higher percentage of their workforce using analytics are enjoying a much higher return from their analytic investment. And so it's not about hiring two double PhD statisticians from Oxford. It really is how widely you can bring your workforce on this journey. Can they all get 10% more capable? And that's having incredible results at businesses all over the world. An another key finding that they had is that the majority of them said that when they had many folks using analytics, they were going on the journey faster than companies they didn't. And so picking technologies, that'll help everyone do this and, and do this fast and do it easily. Having an approachable piece of software that everyone can use is really a key, >>So faster able to move faster, higher ROI. I also imagine analytics across the organization is a big competitive advantage for organizations in any industry. >>Absolutely the IDC or not. The IDC, the international Institute of analytics showed huge correlation between companies that were more analytically mature versus ones that were not. They showed correlation to growth of the company. They showed correlation to revenue and they showed correlation to shareholder values. So across really all of the, the, the key measures of business, the more analytically mature companies simply outperformed their competition. >>And that's key these days is to be able to outperform your competition. You know, one of the things that we hear so often, Alan, is people talking about democratizing data and analytics. You talked about the line of business workers, but I gotta ask you, is it really that easy for the line of business workers who aren't trained in data science, to be able to jump in, look at data, uncover and extract business insights to make decisions. >>So in, in many ways, it really is that easy. I have a 14 and 16 year old kid. Both of them have learned Altrics they're, Altrics certified. And, and it was quite easy. It took 'em about 20 hours and they were, they, they were off to the races, but there can be some hard parts. The hard parts have more to do with change management. I mean, if you're an accountant, that's been doing the best accounting work in your company for the last 20 years. And all you happen to know is a spreadsheet for those 20 years. Are you ready to learn some new skills? And, and I would suggest you probably need to, if you want, keep up with your profession. The, the big four accounting firms have trained over a hundred thousand people in Altrix just one firm has trained over a hundred thousand. >>You, you can't be an accountant or an auditor at some of these places with, without knowing Altrix. And so the hard part, really in the end, isn't the technology and learning analytics and data science. The harder part is this change management change is hard. I should probably eat better and exercise more, but it's, it's hard to always do that. And so companies are finding that that's the hard part. They need to help people go on the journey, help people with the change management to, to help them become the digitally enabled accountant of the future. The, the logistics professional that is E enabled that that's the challenge. >>That's a huge challenge. Cultural, cultural shift is a challenge. As you said, change management. How, how do you advise customers? If you might be talking with someone who might be early in their analytics journey, but really need to get up to speed and mature to be competitive, how do you guide them or give them recommendations on being able to facilitate that change management? >>Yeah, that's a great question. So, so people entering into the workforce today, many of them are starting to have these skills Altrics is used in over 800 universities around the globe to teach finance and to teach marketing and to teach logistics. And so some of this is happening naturally as new workers are entering the workforce, but for all of those who are already in the workforce have already started their careers, learning in place becomes really important. And so we work with companies to put on programmatic approaches to help their workers do this. And so it's, again, not simply putting a box of tools in the corner and saying free, take one. We put on hackathons and analytic days, and it can, it can be great fun. We, we have a great time with, with many of the customers that we work with helping them, you know, do this, helping them go on the journey and the ROI, as I said, you know, is fantastic. And not only does it sometimes affect the bottom line, it can really make societal changes. We've seen companies have breakthroughs that really make great impact to society as a whole. >>Isn't that so fantastic to see the, the difference that that can make. It sounds like you're, you guys are doing a great job of democratizing access to alter X to everybody. We talked about the line of business folks and the incredible importance of enabling them and the, the ROI, the speed, the competitive advantage. Can you share some specific examples that you think of Alter's customers that really show data breakthroughs by the lines of business using the technology? >>Yeah, absolutely. So, so many to choose from I'll I'll, I'll give you two examples. Quickly. One is armor express. They manufacture life saving equipment, defensive equipments, like armor plated vests, and they were needing to optimize their supply chain, like many companies through the pandemic. We, we see how important the supply chain is. And so adjusting supply to, to match demand is, is really vital. And so they've used all tricks to model some of their supply and demand signals and built a predictive model to optimize the supply chain. And it certainly helped out from a, a dollar standpoint, they cut over a half a million dollars of inventory in the first year, but more importantly, by matching that demand and supply signal, you're able to better meet customer customer demand. And so when people have orders and are, are looking to pick up a vest, they don't wanna wait. >>And, and it becomes really important to, to get that right. Another great example is British telecom. They're, they're a company that services the public sector. They have very strict reporting regulations that they have to meet and they had, and, and this is crazy to think about over 140 legacy spreadsheet models that they had to run to comply with these regulatory processes and, and report, and obviously running 140 legacy models that had to be done in a certain order and linked incredibly challenging. It took them over four weeks, each time that they had to go through that process. And so to, to save time and have more efficiency in doing that, they trained 50 employees over just a two week period to start using Altrix and, and, and learn Altrix. And they implemented an all new reporting process that saw a 75% reduction in the number of man hours. >>It took to run in a 60% runtime performance. And so, again, a huge improvement. I can imagine it probably had better quality as well, because now that it was automated, you don't have people copying and past data into a spreadsheet. And that was just one project that this group of, of folks were able to accomplish that had huge ROI, but now those people are moving on and automating other processes and performing analytics in, in other areas, you can imagine the impact by the end of the year that they will have on their business, you know, potentially millions upon millions of dollars. This is what we see again. And again, company after company government agency, after government agency is how analytics are really transforming the way work is being done. >>That was the word that came to mind when you were describing the all three customer examples, the transformation, this is transformative. The ability to leverage alters to, to truly democratize data and analytics, give access to the lines of business is transformative for every organization. And, and also the business outcomes. You mentioned, those are substantial metrics based business outcomes. So the ROI and leveraging a technology like alri seems to be right there, sitting in front of you. >>That's right. And, and to be honest, it's not only important for these businesses. It's important for, for the knowledge workers themselves. I mean, we, we hear it from people that they discover Alrich, they automate a process. They finally get to get home for dinner with their families, which is fantastic, but, but it leads to new career paths. And so, you know, knowledge workers that have these added skills have so much larger opportunity. And I think it's great when the needs of businesses to become more analytics and analytic and automate processes actually matches the needs of the employees. And, you know, they too wanna learn these skills and become more advanced in their capabilities, >>Huge value there for the business, for the employees themselves to expand their skillset, to, to really open up so many opportunities for not only the business to meet the demands of the demanding customer, but the employees to be able to really have that breadth and depth in their field of service. Great opportunities there. Alan, is there anywhere that you wanna point the audience to go, to learn more about how they can get started? >>Yeah. So one of the things that we're really excited about is how fast and easy it is to learn these tools. So any of the listeners who wanna experience Altrix, they can go to the website, there's a free download on the website. You can take our analytic maturity assessment, as we talked about at the beginning and, and see where you are on the journey and just reach out. You know, we'd love to work with you and your organization to see how we can help you accelerate your journey on, on analytics and automation, >>Alan, it was a pleasure talking to you about democratizing data and analytics, the power in it for organizations across every industry. We appreciate your insights and your time. >>Thank you so much >>In a moment, Paula Hanson, who is the president and chief revenue officer of ultras and Jackie Vander lay graying. Who's the global head of tax technology at eBay will join me. You're watching the cube, the leader in high tech enterprise coverage.

>> It's no surprise that 73% of organizations indicate analytics spend will outpace other software investments in the next 12 to 18 months. After all as we know, data is changing the world and the world is changing with it. But is everyone's spending resulting in the same ROI? This is Lisa Martin. Welcome to "theCUBE"'s presentation of democratizing analytics across the enterprise, made possible by Alteryx. An Alteryx commissioned IDC info brief entitled, "Four Ways to Unlock Transformative Business Outcomes from Analytics Investments" found that 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. On this special "CUBE" presentation, Jason Klein, product marketing director of Alteryx, will join me to share key findings from the new Alteryx commissioned IDC brief and uncover how enterprises can derive more value from their data. In our second segment, we'll hear from Alan Jacobson, chief data and analytics officer at Alteryx. He's going to discuss how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. And then in our final segment, Paula Hansen, who is the president and chief revenue officer of Alteryx, and Jacqui Van der Leij Greyling, who is the global head of tax technology at eBay, they'll join me. They're going to share how Alteryx is helping the global eCommerce company innovate with analytics. Let's get the show started. (upbeat music) Jason Klein joins me next, product marketing director at Alteryx. Jason, welcome to the program. >> Hello, nice to be here. >> Excited to talk with you. What can you tell me about the new Alteryx IDC research, which spoke with about 1500 leaders, what nuggets were in there? >> Well, as the business landscape changes over the next 12 to 18 months, we're going to see that analytics is going to be a key component to navigating this change. 73% of the orgs indicated that analytics spend will outpace other software investments. But just putting more money towards technology, it isn't going to solve everything. And this is why everyone's spending is resulting in different ROIs. And one of the reasons for this gap is because 93% of organizations, they're still not fully using the analytics skills of their employees, and this widening analytics gap, it's threatening operational progress by wasting workers' time, harming business productivity and introducing costly errors. So in this research, we developed a framework of enterprise analytics proficiency that helps organizations reap greater benefits from their investments. And we based this framework on the behaviors of organizations that saw big improvements across financial, customer, and employee metrics, and we're able to focus on the behaviors driving higher ROI. >> So the info brief also revealed that nearly all organizations are planning to increase their analytics spend. And it looks like from the info brief that nearly three quarters plan on spending more on analytics than any other software. And can you unpack, what's driving this demand, this need for analytics across organizations? >> Sure, well first there's more data than ever before, the data's changing the world, and the world is changing data. Enterprises across the world, they're accelerating digital transformation to capitalize on new opportunities, to grow revenue, to increase margins and to improve customer experiences. And analytics along with automation and AI is what's making digital transformation possible. They're providing the fuel to new digitally enabled lines of business. >> One of the things that the study also showed was that not all analytics spending is resulting in the same ROI. What are some of the discrepancies that the info brief uncovered with respect to the changes in ROI that organizations are achieving? >> Our research with IDC revealed significant roadblocks across people, processes, and technologies. They're preventing companies from reaping greater benefits from their investments. So for example, on the people side, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy as compared to the technology itself. And next, while data is everywhere, most organizations, 63% from our survey, are still not using the full breadth of data types available. Yet data's never been this prolific, it's going to continue to grow, and orgs should be using it to their advantage. And lastly organizations, they need to provide the right analytics tools to help everyone unlock the power of data. >> So they- >> They instead rely on outdated spreadsheet technology. In our survey, nine out of 10 respondents said less than half of their knowledge workers are active users of analytics software beyond spreadsheets. But true analytic transformation can't happen for an organization in a few select pockets or silos. We believe everyone regardless of skill level should be able to participate in the data and analytics process and be driving value. >> Should we retake that, since I started talking over Jason accidentally? >> Yep, absolutely we can do so. We'll just go, yep, we'll go back to Lisa's question. Let's just, let's do the, retake the question and the answer, that'll be able to. >> It'll be not all analytics spending results in the same ROI, what are some of the discrepancies? >> Yes, Lisa, so we'll go from your ISO, just so we get that clean question and answer. >> Okay. >> Thank you for that. On your ISO, we're still speeding, Lisa, so give it a beat in your head and then on you. >> Yet not all analytics spending is resulting in the same ROI. So what are some of the discrepancies that the info brief uncovered with respect to ROI? >> Well, our research with IDC revealed significant roadblocks across people, processes, and technologies, all preventing companies from reaping greater benefits from their investments. So on the people side, for example, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy as compared to the technology itself. And next, while data is everywhere, most organizations, 63% in our survey, are still not using the full breadth of data types available. Data has never been this prolific. It's going to continue to grow and orgs should be using it to their advantage. And lastly, organizations, they need to provide the right analytic tools to help everyone unlock the power of data, yet instead they're relying on outdated spreadsheet technology. Nine of 10 survey respondents said that less than half of their knowledge workers are active users of analytics software. True analytics transformation can't happen for an organization in a few select pockets or silos. We believe everyone regardless of skill level should be able to participate in the data and analytics process and drive value. >> So if I look at this holistically, then what would you say organizations need to do to make sure that they're really deriving value from their investments in analytics? >> Yeah, sure. So overall, the enterprises that derive more value from their data and analytics and achieve more ROI, they invested more aggressively in the four dimensions of enterprise analytics proficiency. So they've invested in the comprehensiveness of analytics across all data sources and data types, meaning they're applying analytics to everything. They've invested in the flexibility of analytics across deployment scenarios and departments, meaning they're putting analytics everywhere. They've invested in the ubiquity of analytics and insights for every skill level, meaning they're making analytics for everyone. And they've invested in the usability of analytics software, meaning they're prioritizing easy technology to accelerate analytics democratization. >> So very strategic investments. Did the survey uncover any specific areas where most companies are falling short, like any black holes that organizations need to be aware of at the outset? >> It did, it did. So organizations, they need to build a data-centric culture. And this begins with people. But what the survey told us is that the people aspect of analytics is the most heavily skewed towards low proficiency. In order to maximize ROI, organizations need to make sure everyone in the organization has access to the data and analytics technology they need. And then the organizations also have to align their investments with upskilling in data literacy to enjoy that higher ROI. Companies who did so experience higher ROI than companies who underinvested in analytics literacy. So among the high ROI achievers, 78% have a good or great alignment between analytics investment and workforce upskilling compared to only 64% among those without positive ROI. And as more orgs adopt cloud data warehouses or cloud data lakes, in order to manage the massively increasing workloads- Can I start that one over. >> Sure. >> Can I redo this one? >> Yeah. >> Of course, stand by. >> Tongue tied. >> Yep, no worries. >> One second. >> If we could do the same, Lisa, just have a clean break, we'll go your question. >> Yep, yeah. >> On you Lisa. Just give that a count and whenever you're ready. Here, I'm going to give us a little break. On you Lisa. >> So are there any specific areas that the survey uncovered where most companies are falling short? Like any black holes organizations need to be aware of from the outset? >> It did. You need to build a data-centric culture and this begins with people, but we found that the people aspect of analytics is most heavily skewed towards low proficiency. In order to maximize ROI organizations need to make sure everyone has access to the data and analytics technology they need. Organizations that align their analytics investments with upskilling enjoy higher ROI than orgs that are less aligned. For example, among the high ROI achievers in our survey, 78% had good or great alignment between analytics investments and workforce upskilling, compared to only 64% among those without positive ROI. And as more enterprises adopt cloud data warehouses or cloud data lakes to manage increasingly massive data sets, analytics needs to exist everywhere, especially for those cloud environments. And what we found is organizations that use more data types and more data sources generate higher ROI from their analytics investments. Among those with improved customer metrics, 90% were good or great at utilizing all data sources, compared to only 67% among the ROI laggards. >> So interesting that you mentioned people, I'm glad that you mentioned people. Data scientists, everybody talks about data scientists. They're in high demand, we know that, but there aren't enough to meet the needs of all enterprises. So given that discrepancy, how can organizations fill the gap and really maximize the investments that they're making in analytics? >> Right, so analytics democratization, it's no longer optional, but it doesn't have to be complex. So we at Alteryx, we're democratizing analytics by empowering every organization to upskill every worker into a data worker. And the data from this survey shows this is the optimal approach. Organizations with a higher percentage of knowledge workers who are actively using analytics software enjoy higher returns from their analytics investment than orgs still stuck on spreadsheets. Among those with improved financial metrics, AKA the high ROI achievers, nearly 70% say that at least a quarter of their knowledge workers are using analytics software other than spreadsheets compared to only 56% in the low ROI group. Also among the high ROI performers, 63% said data and analytic workers collaborate well or extremely well compared to only 51% in the low ROI group. The data from the survey shows that supporting more business domains with analytics and providing cross-functional analytics correlates with higher ROI. So to maximize ROI, orgs should be transitioning workers from spreadsheets to analytics software. They should be letting them collaborate effectively and letting them do so cross-functionally. >> Yeah, that cross-functional collaboration is essential for anyone in any organization and in any discipline. Another key thing that jumped out from the survey was around shadow IT. The business side is using more data science tools than the IT side. And it's expected to spend more on analytics than other IT. What risks does this present to the overall organization, if IT and the lines of business guys and gals aren't really aligned? >> Well, there needs to be better collaboration and alignment between IT and the line of business. The data from the survey, however, shows that business managers, they're expected to spend more on analytics and use more analytics tools than IT is aware of. And this isn't because the lines of business have recognized the value of analytics and plan to invest accordingly, but a lack of alignment between IT and business. This will negatively impact governance, which ultimately impedes democratization and hence ROI. >> So Jason, where can organizations that are maybe at the outset of their analytics journey, or maybe they're in environments where there's multiple analytics tools across shadow IT, where can they go to Alteryx to learn more about how they can really simplify, streamline, and dial up the value on their investment? >> Well, they can learn more on our website. I also encourage them to explore the Alteryx community, which has lots of best practices, not just in terms of how you do the analytics, but how you stand up in Alteryx environment, but also to take a look at your analytics stack and prioritize technologies that can snap to and enhance your organization's governance posture. It doesn't have to change it, but it should be able to align to and enhance it. >> And of course, as you mentioned, it's about people, process, and technologies. Jason, thank you so much for joining me today, unpacking the IDC info brief and the great nuggets in there. Lots that organizations can learn and really become empowered to maximize their analytics investments. We appreciate your time. >> Thank you, it's been a pleasure. >> In a moment, Alan Jacobson, who's the chief data and analytics officer at Alteryx is going to join me. He's going to be here to talk about how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. You're watching "theCUBE", the leader in tech enterprise coverage. >> Somehow many have come to believe that data analytics is for the few, for the scientists, the PhDs, the MBAs. Well, it is for them, but that's not all. You don't have to have an advanced degree to do amazing things with data. You don't even have to be a numbers person. You can be just about anything. A titan of industry or a future titan of industry. You could be working to change the world, your neighborhood, or the course of your business. You can be saving lives or just looking to save a little time. The power of data analytics shouldn't be limited to certain job titles or industries or organizations because when more people are doing more things with data, more incredible things happen. Analytics makes us smarter and faster and better at what we do. It's practically a superpower. That's why we believe analytics is for everyone, and everything, and should be everywhere. That's why we believe in analytics for all. (upbeat music) >> Hey, everyone. Welcome back to "Accelerating Analytics Maturity". I'm your host, Lisa Martin. Alan Jacobson joins me next. The chief of data and analytics officer at Alteryx. Alan, it's great to have you on the program. >> Thanks, Lisa. >> So Alan, as we know, everyone knows that being data driven is very important. It's a household term these days, but 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. What's your advice, your recommendations for organizations who are just starting out with analytics? >> You're spot on, many organizations really aren't leveraging the full capability of their knowledge workers. And really the first step is probably assessing where you are on the journey, whether that's you personally, or your organization as a whole. We just launched an assessment tool on our website that we built with the International Institute of Analytics, that in a very short period of time, in about 15 minutes, you can go on and answer some questions and understand where you sit versus your peer set versus competitors and kind of where you are on the journey. >> So when people talk about data analytics, they often think, ah, this is for data science experts like people like you. So why should people in the lines of business like the finance folks, the marketing folks, why should they learn analytics? >> So domain experts are really in the best position. They know where the gold is buried in their companies. They know where the inefficiencies are. And it is so much easier and faster to teach a domain expert a bit about how to automate a process or how to use analytics than it is to take a data scientist and try to teach them to have the knowledge of a 20 year accounting professional or a logistics expert of your company. Much harder to do that. And really, if you think about it, the world has changed dramatically in a very short period of time. If you were a marketing professional 30 years ago, you likely didn't need to know anything about the internet, but today, do you know what you would call that marketing professional if they didn't know anything about the internet, probably unemployed or retired. And so knowledge workers are having to learn more and more skills to really keep up with their professions. And analytics is really no exception. Pretty much in every profession, people are needing to learn analytics to stay current and be capable for their companies. And companies need people who can do that. >> Absolutely, it seems like it's table stakes these days. Let's look at different industries now. Are there differences in how you see analytics in automation being employed in different industries? I know Alteryx is being used across a lot of different types of organizations from government to retail. I also see you're now with some of the leading sports teams. Any differences in industries? >> Yeah, there's an incredible actually commonality between the domains industry to industry. So if you look at what an HR professional is doing, maybe attrition analysis, it's probably quite similar, whether they're in oil and gas or in a high tech software company. And so really the similarities are much larger than you might think. And even on the sports front, we see many of the analytics that sports teams perform are very similar. So McLaren is one of the great partners that we work with and they use Alteryx across many areas of their business from finance to production, extreme sports, logistics, wind tunnel engineering, the marketing team analyzes social media data, all using Alteryx, and if I take as an example, the finance team, the finance team is trying to optimize the budget to make sure that they can hit the very stringent targets that F1 Sports has, and I don't see a ton of difference between the optimization that they're doing to hit their budget numbers and what I see Fortune 500 finance departments doing to optimize their budget, and so really the commonality is very high, even across industries. >> I bet every Fortune 500 or even every company would love to be compared to the same department within McLaren F1. Just to know that wow, what they're doing is so incredibly important as is what we're doing. >> So talk- >> Absolutely. >> About lessons learned, what lessons can business leaders take from those organizations like McLaren, who are the most analytically mature? >> Probably first and foremost, is that the ROI with analytics and automation is incredibly high. Companies are having a ton of success. It's becoming an existential threat to some degree, if your company isn't going on this journey and your competition is, it can be a huge problem. IDC just did a recent study about how companies are unlocking the ROI using analytics. And the data was really clear, organizations that have a higher percentage of their workforce using analytics are enjoying a much higher return from their analytic investment, and so it's not about hiring two double PhD statisticians from Oxford. It really is how widely you can bring your workforce on this journey, can they all get 10% more capable? And that's having incredible results at businesses all over the world. An another key finding that they had is that the majority of them said that when they had many folks using analytics, they were going on the journey faster than companies that didn't. And so picking technologies that'll help everyone do this and do this fast and do it easily. Having an approachable piece of software that everyone can use is really a key. >> So faster, able to move faster, higher ROI. I also imagine analytics across the organization is a big competitive advantage for organizations in any industry. >> Absolutely the IDC, or not the IDC, the International Institute of Analytics showed huge correlation between companies that were more analytically mature versus ones that were not. They showed correlation to growth of the company, they showed correlation to revenue and they showed correlation to shareholder values. So across really all of the key measures of business, the more analytically mature companies simply outperformed their competition. >> And that's key these days, is to be able to outperform your competition. You know, one of the things that we hear so often, Alan, is people talking about democratizing data and analytics. You talked about the line of business workers, but I got to ask you, is it really that easy for the line of business workers who aren't trained in data science to be able to jump in, look at data, uncover and extract business insights to make decisions? >> So in many ways, it really is that easy. I have a 14 and 16 year old kid. Both of them have learned Alteryx, they're Alteryx certified and it was quite easy. It took 'em about 20 hours and they were off to the races, but there can be some hard parts. The hard parts have more to do with change management. I mean, if you're an accountant that's been doing the best accounting work in your company for the last 20 years, and all you happen to know is a spreadsheet for those 20 years, are you ready to learn some new skills? And I would suggest you probably need to, if you want to keep up with your profession. The big four accounting firms have trained over a hundred thousand people in Alteryx. Just one firm has trained over a hundred thousand. You can't be an accountant or an auditor at some of these places without knowing Alteryx. And so the hard part, really in the end, isn't the technology and learning analytics and data science, the harder part is this change management, change is hard. I should probably eat better and exercise more, but it's hard to always do that. And so companies are finding that that's the hard part. They need to help people go on the journey, help people with the change management to help them become the digitally enabled accountant of the future, the logistics professional that is E enabled, that's the challenge. >> That's a huge challenge. Cultural shift is a challenge, as you said, change management. How do you advise customers if you might be talking with someone who might be early in their analytics journey, but really need to get up to speed and mature to be competitive, how do you guide them or give them recommendations on being able to facilitate that change management? >> Yeah, that's a great question. So people entering into the workforce today, many of them are starting to have these skills. Alteryx is used in over 800 universities around the globe to teach finance and to teach marketing and to teach logistics. And so some of this is happening naturally as new workers are entering the workforce, but for all of those who are already in the workforce, have already started their careers, learning in place becomes really important. And so we work with companies to put on programmatic approaches to help their workers do this. And so it's, again, not simply putting a box of tools in the corner and saying free, take one. We put on hackathons and analytic days, and it can be great fun. We have a great time with many of the customers that we work with, helping them do this, helping them go on the journey, and the ROI, as I said, is fantastic. And not only does it sometimes affect the bottom line, it can really make societal changes. We've seen companies have breakthroughs that have really made great impact to society as a whole. >> Isn't that so fantastic, to see the difference that that can make. It sounds like you guys are doing a great job of democratizing access to Alteryx to everybody. We talked about the line of business folks and the incredible importance of enabling them and the ROI, the speed, the competitive advantage. Can you share some specific examples that you think of Alteryx customers that really show data breakthroughs by the lines of business using the technology? >> Yeah, absolutely, so many to choose from. I'll give you two examples quickly. One is Armor Express. They manufacture life saving equipment, defensive equipments, like armor plated vests, and they were needing to optimize their supply chain, like many companies through the pandemic. We see how important the supply chain is. And so adjusting supply to match demand is really vital. And so they've used Alteryx to model some of their supply and demand signals and built a predictive model to optimize the supply chain. And it certainly helped out from a dollar standpoint. They cut over a half a million dollars of inventory in the first year, but more importantly, by matching that demand and supply signal, you're able to better meet customer demand. And so when people have orders and are looking to pick up a vest, they don't want to wait. And it becomes really important to get that right. Another great example is British Telecom. They're a company that services the public sector. They have very strict reporting regulations that they have to meet and they had, and this is crazy to think about, over 140 legacy spreadsheet models that they had to run to comply with these regulatory processes and report, and obviously running 140 legacy models that had to be done in a certain order and length, incredibly challenging. It took them over four weeks each time that they had to go through that process. And so to save time and have more efficiency in doing that, they trained 50 employees over just a two week period to start using Alteryx and learn Alteryx. And they implemented an all new reporting process that saw a 75% reduction in the number of man hours it took to run in a 60% run time performance. And so, again, a huge improvement. I can imagine it probably had better quality as well, because now that it was automated, you don't have people copying and pasting data into a spreadsheet. And that was just one project that this group of folks were able to accomplish that had huge ROI, but now those people are moving on and automating other processes and performing analytics in other areas. So you can imagine the impact by the end of the year that they will have on their business, potentially millions upon millions of dollars. And this is what we see again and again, company after company, government agency after government agency, is how analytics are really transforming the way work is being done. >> That was the word that came to mind when you were describing the all three customer examples, transformation, this is transformative. The ability to leverage Alteryx, to truly democratize data and analytics, give access to the lines of business is transformative for every organization. And also the business outcome you mentioned, those are substantial metrics based business outcomes. So the ROI in leveraging a technology like Alteryx seems to be right there, sitting in front of you. >> That's right, and to be honest, it's not only important for these businesses. It's important for the knowledge workers themselves. I mean, we hear it from people that they discover Alteryx, they automate a process, they finally get to get home for dinner with their families, which is fantastic, but it leads to new career paths. And so knowledge workers that have these added skills have so much larger opportunity. And I think it's great when the needs of businesses to become more analytic and automate processes actually matches the needs of the employees, and they too want to learn these skills and become more advanced in their capabilities. >> Huge value there for the business, for the employees themselves to expand their skillset, to really open up so many opportunities for not only the business to meet the demands of the demanding customer, but the employees to be able to really have that breadth and depth in their field of service. Great opportunities there, Alan. Is there anywhere that you want to point the audience to go to learn more about how they can get started? >> Yeah, so one of the things that we're really excited about is how fast and easy it is to learn these tools. So any of the listeners who want to experience Alteryx, they can go to the website, there's a free download on the website. You can take our analytic maturity assessment, as we talked about at the beginning, and see where you are on the journey and just reach out. We'd love to work with you and your organization to see how we can help you accelerate your journey on analytics and automation. >> Alan, it was a pleasure talking to you about democratizing data and analytics, the power in it for organizations across every industry. We appreciate your insights and your time. >> Thank you so much. >> In a moment, Paula Hansen, who is the president and chief revenue officer of Alteryx, and Jacqui Van der Leij Greyling, who's the global head of tax technology at eBay, will join me. You're watching "theCUBE", the leader in high tech enterprise coverage. >> 1200 hours of wind tunnel testing, 30 million race simulations, 2.4 second pit stops. >> Make that 2.3. >> Sector times out the wazoo. >> Way too much of this. >> Velocities, pressures, temperatures, 80,000 components generating 11.8 billion data points and one analytics platform to make sense of it all. When McLaren needs to turn complex data into winning insights, they turn to Alteryx. Alteryx, analytics automation. (upbeat music) >> Hey, everyone, welcome back to the program. Lisa Martin here, I've got two guests joining me. Please welcome back to "theCUBE" Paula Hansen, the chief revenue officer and president at Alteryx, and Jacqui Van der Leij Greyling joins us as well, the global head of tax technology at eBay. They're going to share with you how Alteryx is helping eBay innovate with analytics. Ladies, welcome, it's great to have you both on the program. >> Thank you, Lisa, it's great to be here. >> Yeah, Paula, we're going to start with you. In this program, we've heard from Jason Klein, we've heard from Alan Jacobson. They talked about the need to democratize analytics across any organization to really drive innovation. With analytics, as they talked about, at the forefront of software investments, how's Alteryx helping its customers to develop roadmaps for success with analytics? >> Well, thank you, Lisa. It absolutely is about our customers' success. And we partner really closely with our customers to develop a holistic approach to their analytics success. And it starts of course with our innovative technology and platform, but ultimately we help our customers to create a culture of data literacy and analytics from the top of the organization, starting with the C-suite. And we partner with our customers to build their roadmaps for scaling that culture of analytics, through things like enablement programs, skills assessments, hackathons, setting up centers of excellence to help their organization scale and drive governance of this analytics capability across the enterprise. So at the end of the day, it's really about helping our customers to move up their analytics maturity curve with proven technologies and best practices, so they can make better business decisions and compete in their respective industries. >> Excellent, sounds like a very strategic program, we're going to unpack that. Jacqui, let's bring you into the conversation. Speaking of analytics maturity, one of the things that we talked about in this event is the IDC report that showed that 93% of organizations are not utilizing the analytics skills of their employees, but then there's eBay. How Jacqui did eBay become one of the 7% of organizations who's really maturing and how are you using analytics across the organization at eBay? >> So I think the main thing for us is when we started out was is that, our, especially in finance, they became spreadsheet professionals instead of the things that we really want our employees to add value to. And we realized we had to address that. And we also knew we couldn't wait for all our data to be centralized until we actually start using the data or start automating and being more effective. So ultimately we really started very, very actively embedding analytics in our people and our data and our processes. >> Starting with people is really critical. Jacqui, continuing with you, what were some of the roadblocks to analytics adoption that you faced and how did you overcome them? >> So I think eBay is a very data driven company. We have a lot of data. I think we are 27 years around this year, so we have the data, but it is everywhere. And how do you use that data? How do you use it efficiently? How do you get to the data? And I believe that that is definitely one of our biggest roadblocks when we started out and just finding those data sources and finding ways to connect to them to move forward. The other thing is that people were experiencing a lot of frustration. I mentioned before about the spreadsheet professionals. And there was no, we were not independent. You couldn't move forward, you would've put it on somebody else's roadmap to get the data and to get the information if you want it. So really finding something that everybody could access analytics or access data. And finally we have to realize is that this is uncharted territory. This is not exactly something that everybody is used to working with every day. So how do you find something that is easy, and that is not so daunting on somebody who's brand new to the field? And I would call those out as your major roadblocks, because you always have, not always, but most of the times you have support from the top, and in our case we have, but at the end of the day, it's our people that need to actually really embrace it, and making that accessible for them, I would say is definitely not per se, a roadblock, but basically a block you want to be able to move. >> It's really all about putting people first. Question for both of you, and Paula we'll start with you, and then Jacqui we'll go to you. I think the message in this program that the audience is watching with us is very clear. Analytics is for everyone, should be for everyone. Let's talk now about how both of your organizations are empowering people, those in the organization that may not have technical expertise to be able to leverage data, so that they can actually be data driven. Paula. >> Yes, well, we leverage our platform across all of our business functions here at Alteryx. And just like Jacqui explained, at eBay finance is probably one of the best examples of how we leverage our own platform to improve our business performance. So just like Jacqui mentioned, we have this huge amount of data flowing through our enterprise and the opportunity to leverage that into insights and analytics is really endless. So our CFO Kevin Rubin has been a key sponsor for using our own technology. We use Alteryx for forecasting all of our key performance metrics, for business planning, across our audit function, to help with compliance and regulatory requirements, tax, and even to close our books at the end of each quarter. So it's really going to remain across our business. And at the end of the day, it comes to how do you train users? How do you engage users to lean into this analytic opportunity to discover use cases? And so one of the other things that we've seen many companies do is to gamify that process, to build a game that brings users into the experience for training and to work with each other, to problem solve and along the way, maybe earn badges depending on the capabilities and trainings that they take. And just have a little healthy competition as an employee base around who can become more sophisticated in their analytic capability. So I think there's a lot of different ways to do it. And as Jacqui mentioned, it's really about ensuring that people feel comfortable, that they feel supported, that they have access to the training that they need, and ultimately that they are given both the skills and the confidence to be able to be a part of this great opportunity of analytics. >> That confidence is key. Jacqui, talk about some of the ways that you're empowering folks without that technical expertise to really be data driven. >> Yeah, I think it means to what Paula has said in terms of getting people excited about it, but it's also understanding that this is a journey and everybody is at a different place in their journey. You have folks that's already really advanced who has done this every day. And then you have really some folks that this is brand new or maybe somewhere in between. And it's about how you get everybody in their different phases to get to the initial destination. I say initial, because I believe a journey is never really complete. What we have done is that we decided to invest, and built a proof of concept, and we got our CFO to sponsor a hackathon. We opened it up to everybody in finance in the middle of the pandemic. So everybody was on Zoom and we told people, listen, we're going to teach you this tool, it's super easy, and let's just see what you can do. We ended up having 70 entries. We had only three weeks. So and these are people that do not have a background. They are not engineers, they're not data scientists. And we ended up with a 25,000 hour savings at the end of that hackathon from the 70 entries with people that have never, ever done anything like this before. And there you have the result. And then it just went from there. People had a proof of concept. They knew that it worked and they overcame the initial barrier of change. And that's where we are seeing things really, really picking up now. >> That's fantastic. And the business outcome that you mentioned there, the business impact is massive, helping folks get that confidence to be able to overcome sometimes the cultural barriers is key here. I think another thing that this program has really highlighted is there is a clear demand for data literacy in the job market, regardless of organization. Can each of you share more about how you're empowering the next generation of data workers? Paula, we'll start with you. >> Absolutely, and Jacqui says it so well, which is that it really is a journey that organizations are on and we as people in society are on in terms of upskilling our capabilities. So one of the things that we're doing here at Alteryx to help address this skillset gap on a global level is through a program that we call SparkED, which is essentially a no-cost analytics education program that we take to universities and colleges globally to help build the next generation of data workers. When we talk to our customers like eBay and many others, they say that it's difficult to find the skills that they want when they're hiring people into the job market. And so this program's really developed just to do just that, to close that gap and to work hand in hand with students and educators to improve data literacy for the next generation. So we're just getting started with SparkED. We started last May, but we currently have over 850 educational institutions globally engaged across 47 countries, and we're going to continue to invest here because there's so much opportunity for people, for society and for enterprises, when we close the gap and empower more people with the necessary analytics skills to solve all the problems that data can help solve. >> So SparkED has made a really big impact in such a short time period. It's going to be fun to watch the progress of that. Jacqui, let's go over to you now. Talk about some of the things that eBay is doing to empower the next generation of data workers. >> So we basically wanted to make sure that we kept that momentum from the hackathon, that we don't lose that excitement. So we just launched the program called eBay Masterminds. And what it basically is, is it's an inclusive innovation in each other, where we firmly believe that innovation is for upskilling for all analytics roles. So it doesn't matter your background, doesn't matter which function you are in, come and participate in in this where we really focus on innovation, introducing new technologies and upskilling our people. We are, apart from that, we also said, well, we shouldn't just keep it to inside eBay. We have to share this innovation with the community. So we are actually working on developing an analytics high school program, which we hope to pilot by the end of this year, where we will actually have high schoolers come in and teach them data essentials, the soft skills around analytics, but also how to use Alteryx. And we're working with, actually, we're working with SparkED and they're helping us develop that program. And we really hope that at, say, by the end of the year, we have a pilot and then also next year, we want to roll it out in multiple locations in multiple countries and really, really focus on that whole concept of analytics for all. >> Analytics for all, sounds like Alteryx and eBay have a great synergistic relationship there that is jointly aimed at especially going down the stuff and getting people when they're younger interested, and understanding how they can be empowered with data across any industry. Paula, let's go back to you, you were recently on "theCUBE"'s Supercloud event just a couple of weeks ago. And you talked about the challenges the companies are facing as they're navigating what is by default a multi-cloud world. How does the Alteryx Analytics Cloud platform enable CIOs to democratize analytics across their organization? >> Yes, business leaders and CIOs across all industries are realizing that there just aren't enough data scientists in the world to be able to make sense of the massive amounts of data that are flowing through organizations. Last I checked, there was 2 million data scientists in the world, so that's woefully underrepresented in terms of the opportunity for people to be a part of the analytics solution. So what we're seeing now with CIOs, with business leaders is that they're integrating data analysis and the skillset of data analysis into virtually every job function, and that is what we think of when we think of analytics for all. And so our mission with Alteryx Analytics Cloud is to empower all of those people in every job function, regardless of their skillset, as Jacqui pointed out from people that are just getting started all the way to the most sophisticated of technical users. Every worker across that spectrum can have a meaningful role in the opportunity to unlock the potential of the data for their company and their organizations. So that's our goal with Alteryx Analytics Cloud, and it operates in a multi cloud world and really helps across all sizes of data sets to blend, cleanse, shape, analyze, and report out so that we can break down data silos across the enterprise and help drive real business outcomes as a result of unlocking the potential of data. >> As well as really lessening that skill gap. As you were saying, there's only 2 million data scientists. You don't need to be a data scientist, that's the beauty of what Alteryx is enabling and eBay is a great example of that. Jacqui, let's go ahead and wrap things with you. You talked a great deal about the analytics maturity that you have fostered at eBay. It obviously has the right culture to adapt to that. Can you talk a little bit and take us out here in terms of where Alteryx fits in as that analytics maturity journey continues and what are some of the things that you are most excited about as analytics truly gets democratized across eBay? >> When we're starting up and getting excited about things when it comes to analytics, I can go on all day, but I'll keep it short and sweet for you. I do think we are on the top of the pool of data scientists. And I really feel that that is your next step, for us anyways, is that how do we get folks to not see data scientists as this big thing, like a rocket scientist, it's something completely different. And it's something that is in everybody in a certain extent. So again, partnering with Alteryx who just released the AI ML solution, allowing folks to not have a data scientist program, but actually build models and be able to solve problems that way. So we have engaged with Alteryx and we purchased the licenses, quite a few. And right now through our Masterminds program, we're actually running a four month program for all skill levels, teaching them AI ML and machine learning and how they can build their own models. We are really excited about that. We have over 50 participants without a background from all over the organization. We have members from our customer services. We have even some of our engineers are actually participating in the program. We just kicked it off. And I really believe that that is our next step. I want to give you a quick example of the beauty of this is where we actually just allow people to go out and think about ideas and come up with things. And one of the people in our team who doesn't have a data scientist background at all, was able to develop a solution where there is a checkout feedback functionality on the eBay side where sellers or buyers can verbatim add information. And she built a model to be able to determine what relates to tax specific, what is the type of problem, and even predict how that problem can be solved before we as a human even step in, and now instead of us or somebody going to verbatim and try to figure out what's going on there, we can focus on fixing the error versus actually just reading through things and not adding any value, and it's a beautiful tool and I was very impressed when I saw the demo and definitely developing that sort of thing. >> That sounds fantastic. And I think just the one word that keeps coming to mind, and we've said this a number of times in the program today is empowerment. What you're actually really doing to truly empower people across the organization with varying degrees of skill level, going down to the high school level, really exciting. We'll have to stay tuned to see what some of the great things are that come from this continued partnership. Ladies, I want to thank you so much for joining me on the program today and talking about how Alteryx and eBay are really partnering together to democratize analytics and to facilitate its maturity. It's been great talking to you. >> Thank you, Lisa. >> Thank you so much. (cheerful electronic music) >> As you heard over the course of our program, organizations where more people are using analytics who have deeper capabilities in each of the four Es, that's everyone, everything, everywhere, and easy analytics, those organizations achieve more ROI from their respective investments in analytics and automation than those who don't. We also heard a great story from eBay, great example of an enterprise that is truly democratizing analytics across its organization. It's enabling and empowering line of business users to use analytics, not only focused on key aspects of their job, but develop new skills rather than doing the same repetitive tasks. We want to thank you so much for watching the program today. Remember you can find all of the content on thecube.net. You can find all of the news from today on siliconangle.com and of course alteryx.com. We also want to thank Alteryx for making this program possible and for sponsoring "theCUBE". For all of my guests, I'm Lisa Martin. We want to thank you for watching and bye for now. (upbeat music)

>> Announcer: Live, from Las Vegas, it's the Cube covering Veritas Vision 2017 brought to you by Veritas. >> Welcome back to Las Vegas, everybody. This is the Cube, the leader in live tech coverage, and this is our second day of Veritas Vision in 2017. I'm Dave Vellante with Stu Miniman. Jason Buffington is here, good friend of the Cube, Senior Analyst with the Enterprise Strategy Group, otherwise known as ESG. Jason, good to see you again. >> Thanks for having me back. >> We've been bumping into each other a lot lately, a lot of storage stuff going on and you you gave a panel discussion today. You had, you know, three of the four big Cloud guys up there, no Amazon, Stu. They weren't up on the panel, but that was good, you had an interview with those guys. >> Jason: Yeah. >> So, congratulations on that and welcome again. >> Yeah, everyone wants to talk about data protection, right? So, there's... >> Dave: Hottest topic, isn't it? >> It is, every time you go to a show, the last show that I was at, it seemed like over half the booths were talking about data protection. So, to come here, you know, Veritas kind of owns that as a name. And so it's been fun to just be part of the participants. >> Yeah, Jason, you know, you cover this base, and you know Veritas well. There are people I talked to getting ready for this, and they said, "We remember Veritas back in its hay day." You know, back pre-acquisition. During the virtualization era, it kind of got quiet. I mean, they got acquired by Semantic, things went down, but now they're an independent company, and one of the shows that, you know, we've been at VMWorld, absolutely. Data protection is super hot, you know, product of the year was one of those companies, whole lot of startups there, a lot of investment. What's your take on kind of the new Veritas, you know, where they fit in that ecosystem with all those startups and everybody else? >> No, that's a good read, so let's talk about the market first, and then I'll put Veritas in it, right? So, I think you're spot on that when the virtualization wave came through, most of the really big established data protection vendors were not first market, right? And in fact, every time that we see this, I've been doing this for 28 years, I've been backing stuff up, right? And for most of it, every time the platform shifts, the traditional dominant data protection vendors are not the first ones to jump on that new gear, right? Windows versus NetWare, now we're into virtualization. So, we saw Veeam, and PHD and vRanger, and a few others that barely get an honorable mention in that line, right? We're in a really interesting time, though, this time around because every time, in the past, when you moved off of the old platform, the presumption was, you turned it off, right? This time around, we're on the, here's a fancy word, we're on the precipice of a new shift again because we're looking at Cloud as the new platform to move to. But here's the fun part. We're not leaving the old stuff behind, right? We're not turning off all the virtual servers and the physical servers are on their way out the door as we go to Cloud. We're embracing Multicloud as the new destination, not this mid-step along the way. And I think that's really interesting because, just like in every time past, it means we're going to get a reset of the leader board when it comes to data protection. And, just like in times past, the secret sauce that made you dominant on the last platform, doesn't necessarily give you an edge technology-wise on the next platform. All it really does is give you momentum, right? So, yeah, there's a few other folks that we could list that they've got some momentum going for one reason or another along the way, but for the marketplace, if physical and virtual and Cloud are all going to be together, Veritas has been doing some of those for 20 some odd years. They've made some announcements around the rest of the suites. I think they're in a good place here. The thing I'm excited about from Veritas, and I do, I'm a fan, you want to root for them, right? I mean, 25 years on the bench, you want to see them keep going. I think the opportunity is that, since the divestiture from Semantic, they have a lot more focus, right? You know, it's really hard to tell a story that's everything from Malware and cyber security, all the way through to a breadth of data protection. But if you look at how they're talking about things now, and I really like the 360 narrative that kind of pulls it all together. Every part of their portfolio kind of pulls the other parts together, right? It doesn't matter, in data management, whether you want to start with backup, or you want to start with storage, or you want to start with availability, anywhere you look on that circle, it's going to pull the rest of the line in, and these are all the things that folks are asking for from a customer base. So, I like the tech that they've got. I like where the market is headed, and I think they've got a real shot to be one of those top three dominant names that we talk about moving forward. >> Yeah, so, I mean it's a 30 plus year history. >> Jason: Yeah. >> And pretty amazing, I mean this is an amazing story, this company. I mean, they came out, kind of a small company, and then there was that relationship which they bought Seagate. You know, Seagate's backup business. Seagate actually had a piece of the company for a while. >> Jason: Yeah. >> You know, Al Shugart, when he sold that stock, basically saved Seagate cause of the cash infusion. So, it was a long history, and then they kind of went dormant... >> Jason: Yeah. >> For a while under the Symantec Governance. And now, so the big question is, can Veritas get its mojo back in the space and become that super hot company again? >> So, by the way, sidebar, you talked about Seagate. I actually have a copy of Seagate Backup Exec sitting on a shelf in my office. (Dave laughing) And one of these days, I will open up the data protection museum, cause I think I've got most of the pieces and parts laying around. So, can Veritas get is mojo back? The thing that Veritas has to consistently remind people, one, we are not your daddy's or your granddaddy's backup company anymore, right? So, they're working on things like, they announced this week a new UI coming for NetBackup 8.1, and I thought they were going to crowd mob out of affirmation for that. People were so excited for, you know, finally we're going to get a contemporary UI that doesn't look like 1995 coming in, in that backup. So, certainly, some of the cosmetics, the sterilization of that UI going across as many of those products as possible in order to provide more of a contemporary feel. That's an easy place to dig on, right? But I think what Veritas really needs to think about is, they need to remind folks that, while they are not the stodgy presumption of what people might think, this is not their first rodeo in any of these areas, right? We had new announcements on software to find storage this week. Things like storage foundation and VCS, they've been doing that for 25 years, right? I mean, they've been doing to software to find storage before it was a thing, right? Availability, right? So, we talk about, I like the VRP product. I think it's a cool architecture, and something certainly that powers a lot of the Cloud mobility type capabilities that are there. And the idea of a heterogeneous platform to enable higher levels of availability, I think the market is just now growing into that, right? So, the trick is, we're not the old folks, but, oh by the way, we have reams of experience like you can't imagine. Let's put those things together and have an enterprise level conversation. >> So, let's lay the horses out on the track here. I mean, we were all at VMWorld, and we saw the, it was the hottest... That and security, backup and security are the two hottest spaces in the business right now. We saw the startups, the Cohesity's, the Rubrik's, the Zerto's, and sort of, the upshots. The Veeams, you know, a lot of action at their booths. Obviously, Veritas getting its mojo back. Where's Commvault in all this, so how do you lay out the horses on the track, what's the competitive landscape look like? Paint a picture for us. >> Yeah, so, first and foremost, I always go back to what ESG calls the data protection spectrum, right? So, the behaviors of archive, backup, snapshot, replication, availability. They are not interchangeable mechanisms. We call it a spectrum as a rainbow kind of feel. You know, when is the last time you went outside, saw a rainbow in the sky, and one of the colors was missing? You know, these colors do not replace each other. Snapshots and replications, etc. When you look at where the market's going, imagine a capital Y. In fact, if you go look up on your favorite blog site, I have a blog on, why does data protection have to evolve? This is the answer to your question. The base of that Y is just backup. Can you make copies of all of your stuff? And even that, I think a lot of folks have a challenge with. The next step up is that idea of data protection. So, backup plus snapshots plus replications, single set of policies. Where the market's going, and how it kind of lays out the horses, is now we're at that fork in the road in the capital Y, right? And some of the folks are moving down the availability path. And think about that word for a second, you can remember the vendors who like to go that direction. We're going from reactive recovery to proactive assured productivity, right? Because all the backup folks are just as down until somebody hits the restore button. That's the thing that no one really wants to talk about, as opposed to, if you have monitoring, if you have orchestration, if you have failover and rapid recovery mechanisms. Now, you really do have an availability story that comes out of that. And not all the vendors that you mentioned have that. >> Dave: Well, who are the leaders? >> Yeah, so, certainly, from a momentum and brand perspective, Veeam is definitely on the front line of that, you know, I think car racing is more easier... >> Dave: Cause they've got growth and... >> Yeah, they have momentum, they have, certainly virtualization is still a sweet spot for the data centers... >> Obviously, Veritas is... >> Veritas is absolutely... >> They said 15 years in a row in the Gartner Upper Right... >> Yeah. >> Okay, check. >> Dell EMC, broad portfolio there. Those are kind of the biggest three from, who has all the checked boxes they need to make sure they have a dialogue for the next conversation. >> And Commvault, you wouldn't put in that? >> So, well, I always think of three, you know, bronze, silver, gold, not in that order. >> Yeah, it's like baseball playoffs. Who's going to get in, who's the wild card, you know. >> So, Commvault checks all the right boxes, right? They have all the right narratives along the way. I think the challenge is, organizationally, they're a little siloed in how they tell the stories, and so sometimes it's hard to remember that they're actually the only ones who have a single code base. The ones that, you know, one set of tech that can check all the boxes. Everyone else actually has some myriad of pieces and parts that have to be assembled along the way. >> Dave: So, that's both a strength and a weakness... >> Yeah. >> Dave: For Commvault, right? >> Yeah, the opportunity is there to increase the marketing to tell one narrative. >> Kind of Tivoli, same thing, right? >> Yes, same kind of idea there. And by the way, I don't count, let's call them Spectrum Protect now, but I don't count them out. So, Spectrum Protect took a facelift a couple years ago and really got virtualization savvy. They took the, they had the same gap that everyone else that you mentioned had, and, what is it, six, four, a couple years back, they finally got around to that. And then they just announced Spectrum Protect Plus, which is really built for that V-Admin role. So, certainly we've got a good lens there. On the other side, just like in every other generation, you've got some upstarts that are looking pretty good. >> Well funded, some of them paid 100 million. >> Yeah, well funded, some of them I think have kind of a little bit of a puffer fish, right? They feel bigger than they are for the moment, and yet, the tech looks really good. They want to have a dialogue that says, don't start with backup and try to grow forward. Start over, right? Reimagine what storage might look like in the broader range of things. And by the way, data protection is one of the outcomes for that. And so, you put the Actifio, Cohesity, Rubrik, kind of mix, along the lines for that. You also get the... Catalogic stuff that goes into, that's OEM by IBM, kind of gets on the other side. I think that's going to be probably the coolest thing to watch in 2018. So, you hear the buzz words of copy data management. Everybody wants to talk about some version of those three words. We think that the market's going to go either evolution versus revolution. So, evolution is, start with the data protection folks that you know, and those technologies are going to grow into data management type folks. Here at the show, right, so we saw Veritas Velocity. It's their first foray into that. Cloud Point starts to come into that mix as well. So, the idea of keeping all you need, getting rid of it when you don't, and enabling, and here's the fun part, enabling those secondary use cases so that you can get more value out of that otherwise dormant data. Mike talked about that during the day one keynote. I thought he was spot on for that. So, that's the evolution approach. Revolution, start over, better storage, gets you the same results. Those other guys are old anyway... >> So, Bill Coleman's saying, "It's ours to lose." He said that to us on the Cube. They're obviously an evolution play. >> Jason: Yep. >> I've also heard, they've got, they've made the claim, "We've got the best engineering team in the business." Comments? >> So... >> Dave: It's a very competitive market. >> Yeah, it's hard to say best. I never like ultimate superlatives, but here's what I will say. I meet an amazing number of engineers at Veritas who have been doing this 15, 20, 25 years. There's a lot of wonderful institutional knowledge that comes out of that, that you don't get when you're three, five years, even if you come from multiple vendors, and you kind of pop along the way. There are folks that their initials are still in the source code of NetBackup, and I think that gives them an edge from that perspective if they have a vision from an architecture and from a message perspective on carrying it forward and growing beyond just backup. >> Yeah, Jason, want to get your commentary on the customers. So, one of the things we're trying to reconcile here is, they've got a lot of NetBackup customers. >> Jason: Yeah. >> And then they're pitching this new Cloud hyper-scale, distributed architecture world. Are the customers ready for that? Are they, you know, Bill Coleman told us, five years, ten years, maybe five years from now, every single product that's selling today will be obsolete. So, are the Veritas customers today ready to make that move? What are you hearing? Or are they just going to, you know, go to Microsoft and Amazon and, you know, come in that way? How does this, you know, it goes that kind of revolutionary, evolutionary, discussion you were having. >> Good read, so working backwards, I don't think the answer for better backup for the enterprise is clouding. Cloud managed, absolutely. Disaster recovery as a service, as a secondary tier for the people who don't want to have dormant data centers, yeah probably. But we're still going to have a significant majority of infrastructure on-prem that's going to demand for current SLAs to have recoverability on-prem as well. So, I don't think it starts from a Cloud angle. What I do think, from the Veritas customer perspective is, certainly, you know, Veritas is, their homies are the NetBack of admins. That role is evolving. Or maybe I should say it's devolving. You know, you're not going to have backup admins in the same way. Honestly, more and more, we see that data protection should be part of a broader system's management platform management conversation, right? Cause if I'm an IT generalist, that means I don't have a Ph.D. in backup, and I don't want one. I'm an IT generalist, and I'm the one who's responsible for provisioning servers, and patching servers, and providing access to servers. When those green lights turn red, I want to be able to be part of that process and not wait on somebody else. And if I want to be part of the recovery process, it means I better be part of the protection process as well. So, certainly, Veritas is going to have to grow into some new personas of who they're going to be adding value to. IT ops is the big one, right? So, the backup admin is starting to decline a little bit, the V-Admin for the virtualization role is starting to decline a little bit. That IT operations role is really taking a much more dominant share. That said, Veritas's best route to market is to go through the backup admin, and not in spite of because you can turn that backup admin into a hero by saying, "Look, you have a certain set of problems." "Your adjacent peers have a wider set of problems, "and aren't you going to be the smart one "to walk in somebody who can fix "the rest of the problems while we're at it." And that's that 360 story... >> Well, to your point, evolve or devolve, that role. So, we're out of time, but how about a plug for some recent research, what's hot, what's new, anything that you've worked on that you want to share with the audience. >> Yeah, so ESG, we just finished research on real world SLAs and availabilities. So, how are people doing that proactive lens, as opposed to just reactive? Today, earlier today, I kicked off research with the research team on copy data management, so all that evolution/revolution, we're in that right now. And then the next two projects we're working on, GDPR readiness and data protection drivers in Western Europe. Appliance form factors for data protection, so turnkey versus dedupe, is kind of the next one. And then we're going to refresh our Cloud Strategy Data Protection intersection, so BaaS, DRaaS, STaaS, IaaS, and SaaS, and how the protection traction moves. >> Awesome, sounds like a good lineup. I'd be interested to see that GDPR readiness. We'll have to forecast that and... >> That'll be fun. >> And then hit you up after that comes out cause there's going to be some big gaps going on there. >> Yeah. >> Hey, thanks very much for coming back in the Cube, good job. >> Thanks for having me. >> Alright, you're welcome. Okay, keep it right there everybody, Stu and I will be back. This is day two, Veritas Vision. You're watching the Cube.