>>Really excited about this year's data, citizens with so many of you together. Uh, I'm going to talk today about accessible data, because what good is the data. If you can get it into your hands and shop for it, but you can't understand it. Uh, and I'm here today with, uh, bald, really thrilled to be here with Paul. Paul is an award-winning author on all topics data. I think 20 books with 21st on the way over 300 articles, he's been a frequent speaker. He's an expert in future trends. Uh, he's a VP at cognitive systems, uh, over at IBM teachers' data also, um, at the business school and as a champion of diversity initiatives. Paul, thank you for being here, really the conformance, uh, to the session with you. >>Oh, thanks for having me. It's a privilege. >>So let's get started with, uh, our origins and data poll. Um, and I'll start with a little story of my own. So, uh, I trained as an engineer way back when, uh, and, um, in one of the courses we got as an engineer, it was about databases. So we got the stick thick book of CQL and me being in it for the programming. I was like, well, who needs this stuff? And, uh, I wanted to do my part in terms of making data accessible. So essentially I, I was the only book that I sold on. Uh, obviously I learned some hard lessons, uh, later on, as I did a master's in AI after that, and then joined the database research lab at the university that Libra spun off from. Uh, but Hey, we all learned along the way. And, uh, Paula, I'm really curious. Um, when did you awaken first to data? If you will? >>You know, it's really interesting Stan, because I come from the opposite side, an undergrad in economics, uh, with some, uh, information systems research at the higher level. And so I think I was always attuned to what data could do, but I didn't understand how to get at it and the kinds of nuances around it. So then I started this job, a database company, like 27 years ago, and it started there, but I would say the awakening has never stopped because the data game is always changing. Like I look at these epochs that I've been through data. I was a real relational databases thinking third normal form, and then no SQL databases. And then I watch no SQL be about no don't use SQL, then wait a minute. Not only sequel. And today it's really for the data citizens about wait, no, I need SQL. So, um, I think I'm always waking up in data, so I'll call it a continuum if you will. But that was it. It was trying to figure out the technology behind driving analytics in which I took in school. >>Excellent. And I fully agree with you there. Uh, every couple of years they seem to reinvent new stuff and they want to be able to know SQL models. Let me see. I saw those come and go. Uh, obviously, and I think that's, that's a challenge for most people because in a way, data is a very abstract concepts, um, until you get down in the weeds and then it starts to become really, really messy, uh, until you, you know, from that end button extract a certain insights. Um, and as the next thing I want to talk about with you is that challenging organizations, we're hearing a lot about data, being valuable data, being the new oil data, being the new soil, the new gold, uh, data as an asset is being used as a slogan all over. Uh, people are investing a lot in data over multiple decades. Now there's a lot of new data technologies, always, but still, it seems that organizations fundamentally struggle with getting people access to data. What do you think are some of the key challenges that are underlying the struggles that mud, that organizations seem to face when it comes to data? >>Yeah. Listen, Stan, I'll tell you a lot of people I think are stuck on what I call their data, acumen curves, and you know, data is like a gym membership. If you don't use it, you're not going to get any value on it. And that's what I mean by accurate. And so I like to think that you use the analogy of some mud. There's like three layers that are holding a lot of organizations back at first is just the amount of data. Now, I'm not going to give you some stat about how many times I can go to the moon and back with the data regenerate, but I will give you one. I found interesting stat. The average human being in their lifetime will generate a petabyte of data. How much data is that? If that was my apple music playlist, it would be about 2000 years of nonstop music. >>So that's some kind of playlist. And I think what's happening for the first layer of mud is when I first started writing about data warehousing and analytics, I would be like, go find a needle in the haystack. But now it's really finding a needle in a stack of needles. So much data. So little time that's level one of mine. I think the second thing is people are looking for some kind of magic solution, like Cinderella's glass slipper, and you put it on her. She turns into a princess that's for Disney movies, right? And there's nothing magical about it. It is about skill and acumen and up-skilling. And I think if you're familiar with the duper, you recall the Hadoop craze, that's exactly what happened, right? Like people brought all their data together and everyone was going to be able to access it and give insights. >>And it teams said it was pretty successful, but every line of business I ever talked to said it was a complete failure. And the third layer is governance. That's actually where you're going to find some magic. And the problem in governance is every client I talked to is all about least effort to comply. They don't want to violate GDPR or California consumer protection act or whatever governance overlooks, where they do business and governance. When you don't lead me separate to comply and try not to get fine, but as an accelerant to your analytics, and that gets you out of that third layer of mud. So you start to invoke what I call the wisdom of the crowd. Now imagine taking all these different people with intelligence about the business and giving them access and acumen to hypothesize on thousands of ideas that turn into hundreds, we test and maybe dozens that go to production. So those are three layers that I think every organization is facing. >>Well. Um, I definitely follow on all the days, especially the one where people see governance as a, oh, I have to comply to this, which always hurts me a little bit, honestly, because all good governance is about making things easier while also making sure that they're less riskier. Um, but I do want to touch on that Hadoop thing a little bit, uh, because for me in my a decade or more over at Libra, we saw it come as well as go, let's say around 2015 to 2020 issue. So, and it's still around. Obviously once you put your data in something, it's very hard to make it go away, but I've always felt that had do, you know, it seemed like, oh, now we have a bunch of clusters and a bunch of network engineers. So what, >>Yeah. You know, Stan, I fell for, I wrote the book to do for dummies and it had such great promise. I think the problem is there wasn't enough education on how to extract value out of it. And that's why I say it thinks it's great. They liked clusters and engineers that you just said, but it didn't drive lineup >>Business. Got it. So do you think that the whole paradigm with the clouds that we're now on is going to fundamentally change that or is just an architectural change? >>Yeah. You know, it's, it's a great comment. What you're seeing today now is the movement for the data lake. Maybe a way from repositories, like Hadoop into cloud object stores, right? And then you look at CQL or other interfaces over that not allows me to really scale compute and storage separately, but that's all the technical stuff at the end of the day, whether you're on premise hybrid cloud, into cloud software, as a service, if you don't have the acumen for your entire organization to know how to work with data, get value from data, this whole data citizen thing. Um, you're not going to get the kind of value that goes into your investment, right? And I think that's the key thing that business leaders need to understand is it's not about analytics for kind of science project sakes. It's about analytics to drive. >>Absolutely. We fully agree with that. And I want to touch on that point. You mentioned about the wisdom of the crowds, the concept that I love about, right, and your organization is a big grout full of what we call data citizens. Now, if I remember correctly from the book of the wisdom of the crowds, there's, there's two points that really, you have to take Canada. What is, uh, for the wisdom of the grounds to work, you have to have all the individuals enabled, uh, for them to have access to the right information and to be able to share that information safely kept from the bias from others. Otherwise you're just biasing the outcome. And second, you need to be able to somehow aggregate that wisdom up to a certain decision. Uh, so as Felix mentioned earlier, we all are United by data and it's a data citizen topic. >>I want to touch on with you a little bit, because at Collibra we look at it as anyone who uses data to do their job, right. And 2020 has sort of accelerated digitization. Uh, but apart from that, I've always believed that, uh, you don't have to have data in your title, like a data analyst or a data scientist to be a data citizen. If I take a look at the example inside of Libra, we have product managers and they're trying to figure out which features are most important and how are they used and what patterns of behavior is there. You have a gal managers, and they're always trying to know the most they can about their specific accounts, uh, to be able to serve as them best. So for me, the data citizen is really in its broadest sense. Uh, anyone who uses data to do their job, does that, does that resonate with you? >>Yeah, absolutely. It reminds me of myself. And to be honest in my eyes where I got started from, and I agree, you don't need the word data in your title. What you need to have is curiosity, and that is in your culture and in your being. And, and I think as we look at organizations to transform and take full advantage of their, their data investments, they're going to need great governance. I guarantee you that, but then you're going to have to invest in this data citizen concept. And the first thing I'll tell you is, you know, that kind of acumen, if you will, as a team sport, it's not a departmental sport. So you need to think about what are the upskilling programs of where we can reach across to the technical and the non-technical, you know, lots and lots of businesses rely on Microsoft Excel. >>You have data citizens right there, but then there's other folks who are just flat out curious about stuff. And so now you have to open this up and invest in those people. Like, why are you paying people to think about your business without giving the data? It would be like hiring Tom Brady as a quarterback and telling him not to throw a pass. Right. And I see it all the time. So we kind of limit what we define as data citizen. And that's why I love what you said. You don't need the word data in your title and more so if you don't build the acumen, you don't know how to bring the data together, maybe how to wrangle it, but where did it come from? And where can you fixings? One company I worked with had 17 definitions for a sales individual, 17 definitions, and the talent team and HR couldn't drive to a single definition because they didn't have the data accurate. So when you start thinking of the data citizen, concept it about enabling everybody to shop for data much. Like I would look for a USB cable on Amazon, but also to attach to a business glossary for definition. So we have a common version of what a word means, the lineage of the data who owns it, who did it come from? What did it do? So bring that all together. And, uh, I will tell you companies that invest in the data, citizen concept, outperform companies that don't >>For all of that, I definitely fully agree that there's enough research out there that shows that the ones who are data-driven are capturing the most markets, but also capturing the most growth. So they're capturing the market even faster. And I love what you said, Paul, about, um, uh, the brains, right? You've already paid for the brains you've already invested in. So you may as well leverage them. Um, you may as well recognize and, and enable the data citizens, uh, to get access to the assets that they need to really do their job properly. That's what I want to touch on just a little bit, if, if you're capable, because for me, okay. Getting access to data is one thing, right? And I think you already touched on a few items there, but I'm shopping for data. Now I have it. I have a cul results set in my hands. Let's say, but I'm unable to read and write data. Right? I don't know how to analyze it. I don't know maybe about bias. Uh, maybe I, I, I don't know how to best visualize it. And maybe if I do, maybe I don't know how to craft a compelling persuasion narrative around it to change my bosses decisions. So from your viewpoint, do you think that it's wise for companies to continuously invest in data literacy to continuously upgrade that data citizens? If you will. >>Yeah, absolutely. Forest. I'm going to tell you right now, data literacy years are like dog years stage. So fast, new data types, new sources of data, new ways to get data like API APIs and microservices. But let me take it away from the technical concept for a bit. I want to talk to you about the movie. A star is born. I'm sure most of you have seen it or heard it Bradley Cooper, lady Gaga. So everyone knows the movie. What most people probably don't know is when lady Gaga teamed up with Bradley Cooper to do this movie, she demanded that he sing everything like nothing could be auto-tuned everything line. This is one of the leading actors of Hollywood. They filmed this remake in 42 days and Bradley Cooper spent 18 months on singing lessons. 18 months on a guitar lessons had a voice coach and it's so much and so forth. >>And so I think here's the point. If one of the best actors in the world has to invest three and a half years for 42 days to hit a movie out of the park. Why do we think we don't need a continuous investment in data literacy? Even once you've done your initial training, if you will, over the data, citizen, things are going to change. I don't, you don't. If I, you Stan, if you go to the gym and workout every day for three months, you'll never have to work out for the rest of your life. You would tell me I was ridiculous. So your data literacy is no different. And I will tell you, I have managed thousands of individuals, some of the most technical people around distinguished engineers, fellows, and data literacy comes from curiosity and a culture of never ending learning. That is the number one thing to success. >>And that curiosity, I hire people who are curious, I'll give you one more story. It's about Mozart. And this 21 year old comes to Mozart and he says, Mozart, can you teach me how to compose a symphony? And Mozart looks at this person that says, no, no, you're too young, too young. You compose your fourth symphony when you were 12 and Mozart looks at him and says, yeah, but I didn't go around asking people how to compose a symphony. Right? And so the notion of that story is curiosity. And those people who show up in always want to learn, they're your home run individuals. And they will bring data literacy across the organization. >>I love it. And I'm not going to try and be Mozart, but you know, three and a half years, I think you said two times, 18 months, uh, maybe there's hope for me yet in a singing, you'll be a good singer. Um, Duchy on the, on the, some of the sports references you've made, uh, Paul McGuire, we first connected, uh, I'm not gonna like disclose where you're from, but, uh, I saw he did come up and I know it all sorts of sports that drive to measure everything they can right on the field of the field. So let's imagine that you've done the best analysis, right? You're the most advanced data scientists schooled in the classics, as well as the modernist methods, the best tools you've made a beautiful analysis, beautiful dashboards. And now your coach just wants to put their favorite player on the game, despite what you're building to them. How do you deal with that kind of coaches? >>Yeah. Listen, this is a great question. I think for your data analytics strategy, but also for anyone listening and watching, who wants to just figure out how to drive a career forward? I would give the same advice. So the story you're talking about, indeed hockey, you can figure out where I'm from, but it's around the Ottawa senators, general manager. And he made a quote in an interview and he said, sometimes I want to punch my analytics, people in the head. Now I'm going to tell you, that's not a good culture for analytics. And he goes on to say, they tell me not to play this one player. This one player is very tough. You know, throws four or five hits a game. And he goes, I'd love my analytics people to get hit by bore a wacky and tell me how it feels. That's the player. >>Sure. I'm sure he hits hard, but here's the deal. When he's on the ice, the opposing team gets more shots on goal than the senators do on the opposing team. They score more goals, they lose. And so I think whenever you're trying to convince a movement forward, be it management, be it a project you're trying to fund. I always try to teach something that someone didn't previously know before and make them think, well, I never thought of it that way before. And I think the great opportunity right now, if you're trying to get moving in a data analytics strategy is around this post COVID era. You know, we've seen post COVID now really accelerate, or at least post COVID in certain parts of the world, but accelerate the appetite for digital transformation by about half a decade. Okay. And getting the data within your systems, as you digitize will give you all kinds of types of projects to make people think differently than the way they thought before. >>About data. I call this data exhaust. I'll give you a great example, Uber. I think we're all familiar with Uber. If we all remember back in the days when Uber would offer you search pricing. Okay? So basically you put Uber on your phone, they know everything about you, right? Who are your friends, where you going, uh, even how much batteries on your phone? Well, in a data science paper, I read a long time ago. They recognize that there was a 70% chance that you would accept a surge price. If you had less than 10% of your battery. So 10% of battery on your phone is an example of data exhaust all the lawns that you generate on your digital front end properties. Those are logs. You can take those together and maybe show executive management with data. We can understand why people abandoned their cart at the shipping phase, or what is the amount of shipping, which they abandoned it. When is the signal when our systems are about to go to go down. So, uh, I think that's a tremendous way. And if you look back to the sports, I mean the Atlanta Falcons NFL team, and they monitor their athletes, sleep performance, the Toronto Raptors basketball, they're running AI analytics on people's personalities and everything they tweet and every interview to see if the personality fits. So in sports, I think athletes are the most important commodity, if you will, or asset a yet all these teams are investing in analytics. So I think that's pretty telling, >>Okay, Paul, it looks like we're almost out of time. So in 30 seconds or less, what would you recommend to the data citizens out there? >>Okay. I'm going to give you a four tips in 30 seconds. Number one, remember learning never ends be curious forever. You'll drive your career. Number two, remember companies that invest in analytics and data, citizens outperform those that don't McKinsey says it's about 1.4 times across many KPIs. Number three, stop just collecting the dots and start connecting them with that. You need a strong governance strategy and that's going to help you for the future because the biggest thing in the future is not going to be about analytics, accuracy. It's going to be about analytics, explainability. So accuracy is no longer going to be enough. You're going to have to explain your decisions and finally stay positive and forever test negative. >>Love it. Thank you very much fall. Um, and for all the data seasons is out there. Um, when it comes down to access to data, it's more than just getting your hands on the data. It's also knowing what you can do with it, how you can do that and what you definitely shouldn't be doing with it. Uh, thank you everyone out there and enjoy your learning and interaction with the community. Stay healthy. Bye-bye.

>> Live from Washington DC. It's theCUBE, covering Inforum DC2018, brought to you by Infor. >> Well good afternoon and welcome back to Inform18, we are live in Washington DC, the nation's capital for this year's show. Joining Dave Vellante and me is Corey Tollefson, who is the Senior Vice President and General Manager for retail at Infor. Corey good to see you today sir. >> Good to see you, good to be seen. >> Yeah, right (laughs) it is, under any circumstance right. >> Absolutely. >> So retail, you talk about a world that's kind of upside down now. The brick and mortar guys are, they aren't brick and mortar anymore. So talk about the state of the industry if you would a little bit since it's moved to the digital platform and how that's changing your work with it. >> It certainly was simple 20 years ago. Manufacturers manufactured things, wholesale distributors distributed things, and then retailers sold things. Right, and so the whole business model has been disrupted. Mainly because of the advent of the mobile phone, a mobile device. I said it last year it feels like everyday you wake up and it's very chaotic and there is a lot of disorder. And I think it's an amazing opportunity for retailers to reinvent themselves into a modern 21st century retailer. Everyday is a challenge but we're working on it. >> So what's it like, I mean, every retailer I talk to has this sort of Amazon war room. They're trying to use their physical presence to drive online. They're really getting creative. Amazon continues to do super well. There are those who are predicting the end of of retail stores because of AI etcetera. What's your take? You're knee deep in this business. >> Well I feel, I mean Amazon certainly is bringing a lot of downward pressure. It's the first digital, retail is the first industry to be digitally disrupted. It is happening in healthcare, its happening in manufacturing, but retail brought on the initial wave so to speak. And what I'm seeing is a lot of the middle of the road retailers that don't have too much of an online presence, their legacy brands that maybe had their following 20 years ago. They're going to get squeezed out because the middle in this group is going to get squeezed out. The high end brands that control their own brand image, they brand manufacture their own products, they also have their own retail stores. Those are the companies that are uniquely qualified to compete and thrive against Amazon because the last I looked having stores and having an outlet for immediate gratification of getting products and services is a good thing. The retailers that we are working with are combating that against pure plays like Amazon. >> But there's some consumer friction there right, and it's generational, so how we shop is different then how our kids shop. They look at retail in a very different, through a very different prism then we do. So how do you address that in terms of, how do you help your clients address that through different segmentation of their audiences and addressing those unique problems? >> Well even as a kid I remember that the retail shopping was a destination shopping experience, so we'd load up the family truck, and we'd go to a mall, and spend the whole day. There would be entertainment there, there would be restaurants to eat at. We'd shop and then we'd come home, it was a destination. Try doing that when it is 24 hours, seven days a week, 365 days a year on your phone, suddenly the social engagement, with social media, and Snapchat, and Twitter, and Facebook. Facebook is a little old for a lot of the younglings now, but the moral of the story is social media takes on everything and that's where the influence is. And that whole shopping experience it used to be, well I'm just going to get some product information and then I'm going to go into the store. That's been completely disrupted as well. One other aspect of this is the whole concept of consumerism is disrupted. There is a lot of, you know you look at a lot of the cool brands that are in other adjacent industries whether its Uber or Airbnb, they don't own any of their assets. Same thing is happening in retail, a lot of the new emerging brands are going to have disruptive business models. Like you go into a store and they don't even have any inventory. It's all made to order right. So there's a lot of disruption that's happening and we're working with a lot of brands to help. >> So talk about the next big thing NBT, next big thing in retail is that one of them? I go into a store and say that's what I want send it to my house, what else? >> Well I think one of the next big things that we're working on is the whole concept of machine learning. I think you guys have heard about this before, but the whole technology singularity where its the point in which there is no differentiation between engaging with a customer. Oh sorry engaging with a human versus engaging with a computer. We're not that far away and its a little bit scary. I think we talked about it a couple years ago but the whole concept is why do I need to interact with a human being for my shopping experience? I can just interact with a chat bot, for example. As long as I the customer gets the information I need to make an informed decision, I don't really feel weird talking to a computer anymore. >> Yeah so that's the idea of systems of agency, right, where the machine is taking action on behalf of the brand, and the consumer either doesn't know or doesn't care. >> Right that's right. >> So do you have customers that are on the precipice of doing that? >> Yeah we do. In one of the areas I have talked about this before, machine learning-based demand forecasting. So getting better at forecasting the right product, the right skew on a store-by-location basis. And what we do is we leverage a lot of the inherent capabilities of the internet. A lot of companies talk about cloud as simply a cost reduction. We view cloud as taking advantage of the world's greatest super computer which is the internet. And so, that's one of the areas in which we've been using machine learning. >> So what's the, you say the company, that mid-lane, or middle range, what are they to do now? Because they are kind of stuck, they have their challenges, they have this legacy approach that they are kind of in a tough spot. >> The die has been cast, if I was in their shoes, a lot of these middle of the road retailers. I would look at finding ways to optimize what I have. So whether that's optimizing your inventory, optimizing your labor. That's another thing we talked about, Charles this morning mentioned the whole concept of unleashing maximizing human behavior and unleashing human capital. For years we've been on shows like this talking about products, instead it's about engaging your customer. Everybody's a customer, if you're in healthcare you're a customer. In manufacturing distribution, you have customers. To look at it more from a human element around store associates, I think there's are a lot of middle of the road retailers that have an old iconic brand that could reinvent themselves with time and enough patience. >> How do you deal with the inevitable, well first of all how do your customers deploy your software? It's in the cloud. >> Yeah. >> It's in the Amazon cloud right? >> Well three years ago we made a fundamental decision that we were not going to be an on premise company. So we are a cloud-only applications provider. The second decision point we made was, do we want to be suite or best-to-breed. And when we say suite that was our decision. The third point was, how do you want it to be able to be deployed? So when I started off in this industry which felt like yesterday. I feel like I'm super old now, I started off as a software developer for a company called Retech out of Minneapolis. You know I was doing batch forms, and Oracle PL/SQL and everything was tied to the database, and the user experience was basically a graphical depiction of a database. (Dave laughs) But back in those days-- >> And it still is in a lot of apps. >> Yeah. In those days it was pretty much all about developing that individual code. I kind of lost my train of thought on that. The way you can deploy our assets is on an individualized basis. You can deploy our demand forecasting engine for example. You can deploy our allocation and replenishment engine. And when you tie it all together, you can have a suite that doesn't need to be deployed like it used to be in the old days is where I was going. Which is you have to deploy the whole data model to get all the information that you're looking for. >> Okay so in retail you've got the inevitable, oh well, I'm going to run this in Amazon, they're my big competitor, they're disrupting me. What's the conversation like with customers? How do you guarantee we're protecting their data, you point to Netflix and say hey it's working for them? What do you say? >> Well I think, I mean we're Infor, we're a big company. It's on a case-by-case basis. Yes we have a relationship with AWS and yes they are a strategic partner for us. That doesn't preclude the fact that we work with Google we work with Azure. We are cloud agnostic in retail so, it hasn't been as big of an issue as a lot of industry critics and analysts have made it out to be. >> So if there were an issue, you'd could run it anywhere you want. >> Yeah you just swap it out yeah. >> Alright I want to change gears here. Announcement on the stage today, keynote Van Jones from CNN was talking about #YesWeCode, an organization he has an affiliation with. You've created this, well launched an initiative NextGen. First off explain what that is but fill us back up to the genesis of that because as we found out just a few moments before it's a pretty interesting journey. >> Yeah. >> That you personally were involved in. >> Yeah, I know I am sure a lot of friends and family that know me well are going to be tired of hearing this story. I will give you the condensed version, which is-- >> Take your time. >> Growing up in Minneapolis, I was a huge Prince fan like most Minneapolis people are. And through serendipity I met Prince's brother, and Prince's brother pre-social, pre-internet, pre-mobile, put me on Prince's private guest list for parties at Paisley Park. And so here I am I had a loving family, and I can't believe my mom and dad would let me do this, but I am 16, 17 years old going to parties with Prince. And when I say parties I mean these were intimate parties, maybe the most was 50 people in his house. Sometimes there's like five of us, and what happened at these parties were he would play new music. If we danced and got up there and jammed with him, then he'd put it on an album. If it wasn't very good, or he felt like there wasn't a good strong reaction he put it in his vault. So we were a test case, a Petri dish so to speak, for his music. And I got to build a relationship with him as much as anyone that could. He was a very stand-offish person, but a brilliant artist, and a brilliant human being for that matter. I got to build that relationship and through that relationship I met Van Jones. We hooked up again at one of Prince's memorials a couple of years ago after his death, and we looked at each other and we connected and I said I'm in the technology industry. And he goes we got to talk because there's some things related to Prince's legacy we should really talk about. Which ties us back to #YesWeCode and the announcement we made today about GenOne. >> For GenOne excuse me I said NextGen. >> Yeah GenOne. >> My fault. >> Yeah no, no worries. And the genesis of this was Prince, Rogers Nelson, and Van Jones had a conversation right after Trayvon Martin was shot and killed. And a lot of people suspect the main reason was he looked suspect because he had a hoodie on. And here is an African American kid wearing a hoodie, they follow him and bad things happen right. Van Jones asked Prince directly he goes, you know clearly that guy was racist. And Prince said, think again, maybe if that was a white kid in Silicon Valley wearing a hoodie he'd be a dot.com billionaire, but because we haven't produced enough people of color in CEO level positions in our tech industry, that's on us. Meaning we need to develop more of our own. And so this project means a lot to us, because of the fact that we don't think diversity is just a check box that you have on your corporate mission statement. We think diversity can change the DNA of your company and it can influence better products, solutions, and services to our customers. So it's really important for us and this is just the first step of a multi-echelon, multi-year, multi-faceted program. That we want to take this and roll it out to the entire industry. I'd love for Salesforce and Oracle and SAP and Workday. I'd love for all of them to adapt a program similar to this. This isn't pride of ownership, it's the right thing to do and putting brilliant kids and brilliant minds that maybe came from a bad circumstance, they all deserve a chance too. And it only makes all of us better, and I feel like a lot of great things have happened to me in my career and I feel like I have to give back. And if I can be a small part of this with Van, so be it. >> So that's a very thoughtful response by Prince, and you were saying earlier Corey it was sort of hard to get to know him. Was that typical of Prince, was he sort of introspective and maybe pensive and prescient in that way? >> Well the piece the people that don't understand about Prince is that the whole story of his life is written in his music. And he's released over two thousand songs, you know I'm sure the family and the estate might see this but I've heard another couple thousand songs that have been unreleased and it's beautiful brilliant music and his whole life story is there. You just need to listen to the lyrics, or read the lyrics and listen to the music. >> So was... You mentioned this story, and I just thought 17-year-old kid, I mean with all do respect you don't look like one of Prince's friends right. You're a Minnesota guy, he was too, but just different and I think, did you ever just think that what in the world am I doing here? >> I had that moment, I will never forget that one moment. So it was probably the summer of 1995, Prince was standing five feet from me. He had his right hand strumming his electric guitar, his left hand was playing lead keyboard lines on the keyboard, his right foot was controlling the pitch of the guitar, the left foot was controlling the pitch on the keys, and he was singing vocals and dancing. And I said to myself, I pinched myself, and I said this moment in time, if Amadeus Mozart was standing here he would be blown away. Because there is nobody in the history of music that can write, produce all this great music, but also maintain that look, that image. And then the musicianship, he's a musician's musician. You know we talk about Lenny Kravitz, I ran into Lenny Kravitz about 20 years ago sitting on Prince's couch. He probably doesn't remember me, I am pretty sure he doesn't. >> We'll find out tomorrow night. >> We'll find out tomorrow, but I mean the moral of the story is he was a musician's musician. I'll never forget sitting on the couch and this really soft spoken gal said to me she was really nervous to perform tonight. And I am like don't worry you go this, and it was an 18 year old Alicia Keys. And Prince behind the scenes had been cultivating and developing talent whether its Beyonce, Alicia Keys, Nora Jones, you know. These people he helped develop behind the scenes, and no one really knew it. >> Well his band members were always incredibly talented. I don't know if you ever saw Prince live. >> Nope, did not. >> You've saw him many times. Man as he would say, that band was tight. (laughing) >> That's right. >> Well the program's a great legacy. >> It is. >> And one that is certainly not apparent, but it is great to know that back story to know the generation of that. What got going and certainly I think there's a lot seems like of emotional equity that you and the company have invested, to make sure it's successful as well. >> We think that it was Prince's legacy, but we feel like he has passed the torch between Van, myself and Charles. This really means a lot to us. So we want to take it to the next level so, we are pretty excited. >> Fantastic. >> Congratulations. >> Thanks for having me here. >> Thanks for sharing the story too. I'm glad and it's just wonderful and look forward to talking to Charles about it, when we have him on tomorrow. Alright back with more we are live here, theCUBE is covering Inforum18 in Washington D.C. (upbeat music)