(upbeat music) >> Hello, friends. Welcome back to The Cube's live coverage of AWS re:Invent 2022. We're in Vegas. Lovely Las Vegas. Beautiful outside, although I have only seen outside today once, but very excited to be at re:Invent. We're hearing between 50,000 and 70,000 attendees and it's insane, but people are ready to be back. This morning's keynote by CEO Adam Selipsky was full of great messages, big focus on data, customers, partners, the ecosystem. So excited. And I'm very pleased to welcome back one of our alumni to the program, David Shacochis, VP Enterprise Portfolio Strategy Product Management at Lumen. David, welcome back. >> Lisa, good to be here. The Five Timers Club. >> You are in the Five Timers Club. This is David's fifth appearance on the show. And we were talking before we went live- >> Do we do the jacket now and do we do the jacket later? >> Yeah, the jacket will come later. >> Okay. >> The Five Timers Club, like on SNL. We're going to have that for The Cube. We'll get you measured up and get that all fitted for you. >> That'd be better. >> So talk a little bit about Lumen. 'Cause last time you hear it wasn't Lumen. >> We weren't Lumen last time. So this is the first time... last time we were here on The Cube at re:Invent. This was probably 2019 or so. We were a different company. The company was called CenturyLink back then. We rebranded in 2020 to really represent our identity as a delivery of...as a solutions provider over our fiber network. So Lumen is the corporate brand, the company name. It represents basically a lot of the fiber that's been laid throughout the world and in North America and in enterprise metropolitan areas over the past 10 to 15 years. You know, companies like CenturyLink and Quest and Level 3, all those companies have really rolled up into building that core asset of the network. So Lumen is really the brand for the 21st century for the company, really focused on delivering services for the enterprise and then delivering a lot of value added services around that core network asset. >> So rebranding during the pandemic, what's been the customer feedback and sentiment? >> Yeah, I think customers have really actually appreciated it as certainly a more technology oriented brand, right? Sort of shifting away a little bit from some of the communications and telecom background of the company and the heritage. And while those assets that were built up during that period of time have been substantial, and we still build off of those assets going forward, really what a lot of the customer feedback has been is that it puts us in a posture to be a little bit more of a business solutions provider for customers, right? So there's a lot of things that we can do with that core network asset, the fiber networking a lot of the services that we launch on that in terms of public IP, you know, public internet capacity, private networking, private VPNs, VoIP and voice services. These are services that you'd expect from a company like that. But there's a lot of services inside the Lumen brand that you might surprise you, right? There's an edge computing capability that can deliver five milliseconds of latency within 95% of North American enterprise. >> Wow. >> There's a threat detection lab that goes and takes all of the traffic flowing over the public side of our network and analyzes it in a data lake and turns it into threat intelligence that we then offer off to our customers on a subscription basis. There's a production house that goes and, you know, does production networking for major sports arenas and sports events. There's a wide range of services inside of Lumen that really what the Lumen brand allows us to do is start talking about what those services can do and what networking can do for our customers in the enterprise in a more comprehensive way. >> So good changes, big brand changes for Lumen in the last couple of years. Also, I mean, during a time of such turmoil in the world, we've seen work change dramatically. You know, everybody...companies had to pivot massively quickly a couple years ago. >> Yep. >> Almost approaching three years ago, which is crazy amazing to be digital because they had to be able to survive. >> They did >> Now they're looking at being able to thrive, but now we're also in this hybrid work environment. The future of work has changed. >> Totally. >> Almost permanently. >> Yep. >> How is Lumen positioned to address some of the permanent changes to the work environments? Like the last time we were at re:Invented- >> Yeah. >> In person. This didn't exist. >> That's right. So really, it's one of the things we talk to our customers almost the most about is this idea of the future of work. And, you know, we really think about the future of work as about, you know, workers and workloads and the networks that connect them. You think about how much all of those demands are shifting and changing, right? What we were talking about, and it's very easy for all of us to conceptualize what the changing face of the worker looks like, whether those are knowledge workers or frontline workers the venues in which people are working the environments and that connectivity, predictability of those work desk environments changes so significantly. But workloads are changing and, you know we're sitting here at a trade show that does nothing but celebrate the transformation of workloads. Workloads running in ways in business logic and capturing of data and analysis of data. The changing methodologies and the changing formats of workloads, and then the changing venues for workloads. So workloads are running in places that never used to be data centers before. Workloads are running in interesting places and in different and challenging locations for what didn't used to be the data center. And so, you know, the workloads and the workloads are in a very dynamic situation. And the networks that connect them have to be dynamic, and they have to be flexible. And that's really why a lot of what Lumen invests in is working on the networks that connect workers and workloads both from a visibility and a managed services perspective to make sure that we're removing blind spots and then removing potential choke points and capacity issues, but then also being adaptable and dynamic enough to be able to go and reconfigure that network to reach all of the different places that, you know, workers and workloads are going to evolve into. What you'll find in a lot of cases, you know, the workers...a common scenario in the enterprise. A 500 person company with, you know, five offices and maybe one major facility. You know, that's now a 505 office company. >> Right. >> Right? The challenge of the network and the challenge of connecting workers and workloads is really one of the main conversations we have with our customers heading into this 21st century. >> What are some of the things that they're looking forward to in terms of embracing the future of work knowing this is probably how it's going to remain? >> Yeah, I think companies are really starting to experiment carefully and start to think about what they can do and certainly think about what they can do in the cloud with things like what the AWS platform allows them to do with some of the AWS abstractions and the AWS services allow them to start writing software for, and they're starting to really carefully, but very creatively and reach out into their you know, their base of enterprise data, their base of enterprise value to start running some experiments. We actually had a really interesting example of that in a session that Lumen shared here at re:Invent yesterday. You know, for the few hundred people that were there. You know, I think we got a lot of great feedback. It was really interesting session about the...really gets at this issue of the future of work and the changing ways that people are working. It actually was a really cool use case we worked on with Major League Baseball, Fox Sports, and AWS with the... using the Lumen network to essentially virtualize the production truck. Right? So you've all heard that, you know, the sports metaphor of, you know, the folks in the booth were sitting there started looking down and they're saying, oh great job by the guys or the gals in the truck. >> Yep. >> Right? That are, you know, that bring in that replay or great camera angle. They're always talking about the team and their production truck. Well, that production truck is literally a truck sitting outside the stadium. >> Yep. >> Full of electronics and software and gear. We were able to go and for a Major League Baseball game in...back in August, we were able to go and work with AWS, using the Lumen network, working with our partners and our customers at Fox Sports and virtualize all of that gear inside the truck. >> Wow. That's outstanding. >> Yep. So it was a live game. You know, they simulcast it, right? So, you know, we did our part of the broadcast and many hundreds of people, you know, saw that live broadcast was the first time they tried doing it. But, you know, to your point, what are enterprises doing? They're really starting to experiment, sort to push the envelope, right? They're kind of running things in new ways, you know, obviously hedging their bets, right? And sort of moving their way and sort of blue-green testing their way into the future by trying things out. But, you know, this is a massive revenue opportunity for a Major League Baseball game. You know, a premier, you know, Sunday night baseball contest between the Yankees and the Cardinals. We were able to go and take the entire truck, virtualize it down to a small rack of connectivity gear. Basically have that production network run over redundant fiber paths on the Lumen network up into AWS. And AWS is where all that software worked. The technical director of the show sitting in his office in North Carolina. >> Wow. >> The sound engineer is sitting in, you know, on his porch in Connecticut. Right? They were able to go and do the work of production anywhere while connected to AWS and then using the Lumen network, right? You know, the high powered capabilities of Lumens network underlay to be able to, you know, go and design a network topology and a worked topology that really wasn't possible before. >> Right. It's nice to hear, to your point, that customers are really embracing experimentation. >> Right. >> That's challenging to, obviously there was a big massive forcing function a couple of years ago where they didn't have a choice if they wanted to survive and eventually succeed and grow. >> Yeah. >> But the mindset of experimentation requires cultural change and that's a hard thing to do especially for I would think legacy organizations like Major League Baseball, but it sounds like they have the appetite. >> Yeah. They have the interest. >> They've been a fairly innovative organization for some time. But, you know, you're right. That idea of experimenting and that idea of trying out new things. Many people have observed, right? It's that forcing function of the pandemic that really drove a lot of organizations to go and make a lot of moves really quickly. And then they realized, oh, wait a minute. You know... I guess there's some sort of storytelling metaphor in there at some point of people realizing, oh wait, I can swim in these waters, right? I can do this. And so now they're starting to experiment and push the envelope even more using platforms like AWS, but then using a lot of the folks in the AWS partner network like Lumen, who are designing and sort of similarly inspired to deliver, you know, on demand and virtualized and dynamic capabilities within the core of our network and then within the services that our network can and the ways that our network connects to AWS. All of that experimentation now is possible because a lot of the things you need to do to try out the experiment are things you can get on demand and you can kind of pat, you can move back, you can learn. You can try new things and you can evolve. >> Right. >> Yep. >> Right. Absolutely. What are some of the things that you're excited about as, you know, here was this forcing function a couple years ago, we're coming out of that now, but the world has changed. The future of work as you are so brilliantly articulated has changed permanently. What are you excited about in terms of Lumen and AWS going forward? As we saw a lot of announcements this morning, big focus on data, vision of AWS is really that flywheel with Adams Selipsky is really, really going. What are you excited about going forward into 2023? >> Yeah, I mean we've been working with AWS for so long and have been critical partners for so long that, you know, I think a lot of it is continuation of a lot of the great work we've been doing. We've been investing in our own capabilities around the AWS partner network. You know, we're actually in a fairly unique position, you know, and we like to think that we're that unique position around the future of work where between workers, workloads and the networks that connect them. Our fingers are on a lot of those pulse points, right? Our fingers are on at really at the nexus of a lot of those dynamics. And our investment with AWS even puts us even more so in a position to go where a lot of the workloads are being transformed, right? So that's why, you know, we've invested in being one of the few network operators that is in the AWS partner network at the advanced tier that have the managed services competency, that have the migration competency and the network competency. You can count on one hand the number of network operators that have actually invested at that level with AWS. And there's an even smaller number that is, you know, based here in the United States. So, you know, I think that investment with AWS, investment in their partner programs and then investment co-innovation with AWS on things like that MLB use case really puts us in a position to keep on doing these kinds of things within the AWS partner network. And that's one of the biggest things we could possibly be excited about. >> So what does the go to market look like? Is it Lumen goes in, brings in AWS, vice versa? Both? >> Yeah, so a lot of being a member of the AWS partner network you have a lot of flexibility. You know, we have a lot of customers that are, you know, directly working with AWS. We have a lot of customers that would basically look to us to deliver the solution and, you know, and buy it all as a complete turnkey capability. So we have customers that do both. We have customers that, you know, just look to Lumen for the Lumen adjacent services and then pay, you know, pay a separate bill with AWS. So there's a lot of flexibility in the partner network in terms of what Lumen can deliver as a service, Lumen can deliver as a complete solution and then what parts of its with AWS and their platform factors into on an on-demand usage basis. >> And that would all be determined I imagine by what the customer really needs in their environment? >> Yeah, and sort of their own cloud strategy. There's a lot of customers who are all in on AWS and are really trying to driving and innovating and using some of the higher level services inside the AWS platform. And then there are customers who kind of looked at AWS as one of a few cloud platforms that they want to work with. The Lumen network is compatible and connected to all of them and our services teams are, you know, have the ability to go and let customers sort of take on whatever cloud posture they need. But if they are all in on AWS, there's, you know. Not many networks better to be on than Lumen in order to enable that. >> With that said, last question for you is if you had a bumper sticker or a billboard. Lumen's rebranded since we last saw you. What would that tagline or that phrase of impact be on that bumper sticker? >> Yeah, I'd get in a lot of trouble with our marketing team if I didn't give the actual bumper sticker for the company. But we really think of ourselves as the platform for amazing things. The fourth industrial revolution, everything going on in terms of the future of work, in terms of the future of industrial innovation, in terms of all the data that's being gathered. You know, Adam in the keynote this morning really went into a lot of detail on, you know, the depth of data and the mystery of data and how to harness it all and wrangle it all. It requires a lot of networking and a lot of connectivity. You know, for us to acquire, analyze and act on all that data and Lumen's platform for amazing things really helps forge that path forward to that fourth industrial revolution along with great partners like AWS. >> Outstanding. David, it's been such a pleasure having you back on The Cube. We'll get you fitted for that five timers club jacket. >> It sounds good. (Lisa laughs) >> I'll be back. >> Thanks so much for your insights and your time and well done with what you guys are doing at Lumen and AWS. >> Thanks Lisa. >> For David Shacochis, I'm Lisa Martin. You've been watching The Cube hopefully all day. This is our first full day of coverage at AWS re:Invent '22. Stick around. We'll be back tomorrow, and we know we're going to see you then. Have a great night. (upbeat music)

>> Announcer: From Miami Beach, Florida, it's The Cube, covering Acronis Global Cyber Summit 2019. Brought to you by Acronis. >> Welcome back everyone. We are here with The Cube coverage for two days. We're wrapping up, getting down on day one in the books for the Acronis Global Cyber Summit 2019. I'm John Furrier, your host of The Cube. We are in Miami Beach, the Fontainebleau Hotel. I'm personally excited for this next guest because I'm a huge Red Sox fan, even though I got moved out to California. Giants is in a different area. National League is different than American League, still my heart with the Red Sox. And we're here with an industry veteran, seasoned professional in IT and data, Brian Shield. Boston Red Sox Vice President of Technology and IT. Welcome to The Cube, thanks for joining us. >> Thank you. It's great to be here. >> John: So congratulations on the rings. Since I moved out of town, Red sox win their World Series, break the curse of the Bambino. >> Hey we appreciate that. Thank you. >> My family doesn't want me back. You got to show >> Yeah, maybe I'll put this one up for the, maybe someone can zoom in on this. Which camera is the good one? This one here? So, there ya go. So, World Series champs for at least for another week. (laughter) >> Bummer about this year. Pitching just couldn't get it done. But, good team. >> Happens. >> Again, things move on, but you know. New regime, new GM going to come on board. >> Yup. >> So, but in general, Red Sox, storied franchise. Love it there. Fenway Park, the cathedral of baseball parks. >> Brian: Defnitely. >> And you're seeing that just play out now, standard. So just a great place to go. We have tickets there. So, I got to ask you. Technology, sports, really is modernized faster than I think any category. And certainly cyber security forced to modernize because of the threats. But sports, you got a business to run, not just IT and making the planes run on time. >> Sure. >> Scouts, money, whatever. >> Fans. >> You got fan experience. >> Stadium opportunities. >> Club management, scouts are out there. So you got business, team, fans. And data's a big part of it. That's part of your career. Tell us what the cutting edge innovation is at the Red Sox these days. >> I think baseball in general, as you indicated, it's a very evolving kind of environment. I mean historically I think people really sort of relish the nostalgia of sports and Fenway Park being as historic as it is, was probably the pinnacle of that, in some respects. But Red Sox have always been leaders and baseball analytics, you know. And everyone's pretty familiar with "Moneyball" and Brad Pitt. >> John: Is that a true story, he turned down the GM job? >> I'm told it is. (laughter) I don't know if I fully vetted that question. But over the last six, seven years, you know we've really turned our attention to sort of leveraging sort of technology across the businesses, right? Not just baseball and analytics and how we do scouting, which continues to evolve at a very rapid pace. But also as you pointed out, running a better business, understanding our fans, understanding fan behavior, understanding stadiums. There's a lot of challenges around running an effective stadium. First and foremost to all of us is really ensuring it's a great fan experience. Whether it's artificial intelligence, or IoT technologies or 5G or the latest Wifi, all those things are coming up at Fenway Park. You and I talked earlier about we're about to break ground for a new theater, so a live theater on the outside, beyond the bleachers type of thing. So that'll be a 5,400-seat arena, 200 live performances a year, and with e-sports, you know, complementing it. It just gives you an example of just how fast baseball is sort of transitioning. >> And the theater, is that going to be blown out from where that parking garage is, structure and going towards >> So the corner of Landsdown and Ipswich, if you think of that sort of corner back there, for those that are familiar with the Fenway area. So it's going to be a very big change and you'll see the difference too from within the ballpark. I think we'll lose a couple of rows of the bleachers. That'll be replaced with another gathering area for fans and things like that, on the back end of that theater. So build a great experience and I think it really speaks to sort of our ability to think of Fenway as more of a destination, as a venue, as a complementary experience. We want people to come to the area to enjoy sports and to enjoy entertainment and things. >> You know Brian, the consumerization of IT has been kicked around. Last decade, that was a big buzzword. Now the blending of a physical event and digital has certainly consumed the world. >> Absolutely. >> And we're starting to see that dynamic. You speak to a theater. That's a physical space. But digital is also a big part of kind of that complementary. It's not mutually exclusive for each other. They're integrated business models. >> Absolutely. >> So therefore, the technology has to be seamless. The data has to be available. >> Yup. >> And it's got to be secure. >> Well the data's got to be ubiquitous, right? I mean you don't want to, if we're going to have fans attending theater and then you're going to go to Fenway Park or they leave a game and then go to some other event or they attend a tour of Fenway Park, and beyond maybe the traditional what people might think about, is certainly when you think about baseball and Fenway Park. You know we have ten to twelve concerts a year. We'll host Spartan games, you know. This Christmas, I'm sorry, Christmas 2020 we now have sort of the Fenway Bowl. So we'll be hosting the AAC ACC championship games there with ESPN. >> John: Hockey games? >> Hockey games. Obviously we have Liverpool soccer being held there so it's much more of a destination, a venue for us. How we leverage all the wonderful things about Fenway Park and how we modernize, how we get basically the best of what makes Fenway Park as great as it is, yet as modern as we can make it, where appropriate to create a great fan experience. >> It's a tough balance between balancing the brand and having things on brand as well. >> Sure. >> Does that come into your job a lot around IT? Saying being on brand, not kind of tearing down the old. >> Yeah absolutely. I think our CEOs and leadership team, I mean it's not success for us if you pan to the audience and everyone is looking at their phone, right? That's not what we aspire to. We aspire to leverage technology to simplify people's experience of how do you get to the ballpark, how do I park, how do I get if I want to buy concessions or merchandise, how do I do it easily and simply? How do we supplement that experience with maybe additional data that you may not have had before. Things like that, so we're doing a lot of different testing right now whether it's 4D technologies or how we can understand, watch a play from different dimensions or AI and be able to perhaps see sort of the skyline of Boston since 1912, when Fenway Park launched... And so we sort of see all these technologies as supplemental materials, really kind of making it a holistic experience for fans. >> In Las Vegas, they have a section of Las Vegas where they have all their test beds. 5G, they call it 5G, it's really, you know, evolution, fake 5G but it's a sandbox. One of the challenges that you guys have in Boston, I know from a constraint standpoint physically, you don't have a lot of space. How do you sandbox new technologies and what are some of the things that are cool that people might not know about that are being sandboxed? So, one, how do you do it? >> Yeah. >> Effectively. And then what are some of the cool things that you guys are looking at or things they might not know about that would be interesting. >> Sure. Yeah so Fenway Park, we struggle as you know, a little bit with our footprint. You know, honestly, I walk into some of these large stadiums and I get instant jealousy, relative to just the amount of space that people have to work with and things. But we have a great relationship with our partners so we really partner, I think, particularly well with key partners like Verizon and others. So we now have 5G partially implemented at Fenway Park. We expect to have it sort of fully live come opening day next year. So we're really excited about that. We hope to have a new version of Wifi, the latest version of Wifi available, for the second half of the year. After the All-Star Break, probably after the season's over. But before our bowl game hopefully. We're looking at some really interesting ways that we can tease that out. That bowl game, we're really trying to use that as an opportunity, the Fenway Bowl, as an opportunity to make it kind of a high-tech bowl. So we're looking at ways of maybe doing everything from hack-a-thons to a pre-egaming sort of event to some interesting fan experiential opportunities and things like that. >> Got a lot of nerds at MIT, Northeastern, BU, Bentley, Babson, all the schools in the area. >> Yeah, so we'll be reaching out to colleges and we'll be reaching out to our, the ACC and AACs as well, and see what we can do to kind of create sort of a really fun experience and capitalize on the evolving role of e-sports and the role that technology can play in the future. >> I want to get to the e-sports in a second but I want to just get the plug in for Acronis. We're here at their Global Cyber Summit. You flew down for it, giving some keynote speeches and talks around security. It's a security company, data protection, to cyber protection. It is a data problem, not a storage appliance problem. It's a data problem holistically. You get that. >> Sure. Sure. >> You've been in the business for a long time. What is the security kind of posture that you guys have? Obviously you want to protect the data, protect privacy. But you got to business. You have people that work with you, supply chain, complex but yet dynamic, always on environment. >> That's a great question. It's evolving as you indicated. Major League Baseball, first and foremost, does an outstanding job. So the last, probably last four plus years, Major League Baseball has had a cyber security program that all the clubs partake in. So all 30 clubs are active participants in the program. They basically help build out a suite of tools as well as the ability to kind of monitor, help participate in the monitoring, sort of a lot of our cyber security assets and logs And that's really elevated significantly our posture in terms of security. We supplement that quite a bit and a good example of that is like Acronis. Acronis, for us, represents the ability for us to be able to respond to certain potential threats like ransom-ware and other things. As well as frankly, what's wonderful about a tool like this is that it allows us to also solve other problems. Making our scouts more efficient. We've got these 125 scouts scattered around the globe. These guys are the lifeblood of our, you know, the success of our business. When they have a problem, if they're in Venezuela or the Dominican or someplace else, in southeast Asia, getting them up and running as quickly as we can, being able to consume their video assets and other things as they're scouting prospects. We use Acronis for those solutions. It's great to kind of have a partner who can both double down as a cyber partner as well as someone who helps drive a more efficient business. >> People bring their phone into the stadiums too so those are end points now connecting to your network. >> Definitely. And as you pointed out before, we've got great partnerships. We've got a great concession relationship with Aramark and they operate, in the future they'll be operating off our infrastructure. So we're in the point of rolling out all new point-of-sale terminals this off-season. We're excited about that 'cause we think for the first time it really allows us to build a very comprehensive, very secure environment for both ourselves and for all the touchpoints to fans. >> You have a very stellar career. I noticed you were at Scudder Investments back in the '80s, very cutting-edge firm. FTD that set the whole standard for connecting retailers. Again, huge scale play. Can see the data kind of coming out, they way you've been a CIO, CTO. The EVP CIO at The Weather Channel and the weather.com again, first mover, kind of pioneer. And then now the Red Sox, pioneering. So I got to ask you the modernization question. Red Sox certainly have been cutting-edge, certainly under the last few owners, and the previous Henry is a good one, doing more and more, Has the business model of baseball evolved, 'cause you guys a franchise. >> Sure. >> You operate under the franchisor, Major League Baseball, and you have jurisdictions. So has digital blurred the lines between what Advanced Media unit can do. You got communities developing outside. I watch the games in California. I'm not in there but I'm present digitally. >> Sure. Sure. >> So how has the business model flexed with the innovation of baseball? >> That's a great question. So I mean, first off, the relationship between clubs like ours and MLB continue to evolve. We have a new commissioner, relatively new commissioner, and I think the whole one-baseball model that he's been promoting I think has been great. The boundaries sometimes between digital assets and how we innovate and things like that continues to evolve. Major League Baseball and technology groups and product groups that support Major League Baseball have been a fantastic partner of ours. If you look at some of the innovations with Statcast and some of the other types of things that fans are now becoming more familiar with. And when they see how fast a runner goes or how far a home run goes and all those sort of things, these kinds of capabilities are on the surface, but even like mobile applications, to make it easy for fans to come into ballparks and things like that really. What we see is really are platforms for the future touchpoints to all of our customers. But you're right, it gets complicated. Streaming videos and people hadn't thought of before. >> Latin America, huge audience for the Red Sox. Got great players down there. That's outside the jurisdiction, I think, of the franchise agreement, isn't it? (laughs) >> Well, it's complicated. As this past summer, we played two games in England, right? So we enjoy two games in London, sadly we lost to the Yankees in both of those, but amazing experience and Major League Baseball really hats off to those guys, what they did to kind of pull that together. >> You mentioned Statcast. Every year when I meet with Andy Jassy at AWS, he's a sports fan. We love to talk sports. That's a huge, kind of shows the power of data and cloud computing. >> No doubt. >> How do you guys interface with Statcast? Is that an Amazon thing? Do they come to you? Are they leveraging dimensions, camera angles? How does that all work? Are you guys involved in that or? >> Brian: Oh yeah, yeah. >> Is that separate? >> So Statcast is just one of many data feeds as you can imagine. One of the things that Major League Baseball does is all that type of data is readily available to every club. So every club has access to the data. The real competitive differentiator, if you will, is how you use it internally. Like how your analysts can consume that data. We have a baseball system we call Beacon. We retired Carmine, if you're familiar with the old days of Carmine. So we retired Carmine a few years ago with Beacon. And Beacon for us represents sort of our opportunity to effectively collapse all this information into a decision-making environment that allows us to hopefully to kind of make the best decisions to win the most games. >> I love that you're answering all these questions. I really appreciate it. The one I really want to get into is obviously the fan experience. We talked about that. No talent on the field means no World Series so you got to always be constantly replenishing the talent pool, farm system, recruiting, scouting, all these things go on. They're instrumental. Data's a key driver. What new innovations that the casual fan or IT person might be interested in what's going on around scouting and understanding the asset of a human being? >> Right. Sure. I mean some of this gets highly confidential and things, but I think at a macro level, as you start to see both in the minor leagues and in some portions of the major leagues, wearable technologies. I think beyond just sort of player performance information that you would see traditionally with you might associate it with like Billy Beane, and things like that with "Moneyball" which is evolved obviously considerably since those days. I mean understanding sort of player wellness, understanding sort of how to get the most out of a player and understanding sort of, be able to kind of predict potential injuries and accelerate recoveries and being able to use all of this technology where appropriate to really kind of help sort of maximize the value of player performance. I mean, David Ortiz, you know, I don't know where we would have been in 2018 without, you know, David. >> John: Yeah. >> But like, you know >> Longevity of a player. >> Absolutely. >> To when they're in the zone. You wear a ring now to tell you if you're sleeping well. Will managers have a visual, in-the-zone, don't pull 'em out, he can go an extra inning? >> Well, I mean they have a lot of data. We currently don't provide all that data to the clubhouse. I mean, you know, and so If you're in the dugout, that information isn't always readily available type of thing. But players know all this information. We continue to evolve it. At the end of the day though, it's finding the balancing act between data and the aptitudes of our coaching staff and our managers to really make the wise decisions. >> Brian, final question for you. What's the coolest thing you're working on right now? Besides the fan having a great experience, 'cause that's you kind of touched on that. What's the coolest thing that you're excited about that you're working on from a tech perspective that you think is going to be game-changing or interesting? >> I think our cloud strategy coming up in the future. It's still a little bit early stage, but our hope would be to kind of have clarity about that in the next couple months. I think is going to be a game-changer for us. I think having, you know, we enjoy a great relationship with Dell EMC and yet we also do work in the cloud and so being able to leverage the best of both of those to be able to kind of create sort of a compelling experience for both fans, for both player, baseball operations as well as sort of running an efficient business, I think is really what we're all about. >> I mean you guys are the poster child for hybrid cloud because you got core, data center, IoT, and >> No doubt. So it's exciting times. And we're very fortunate that with our relationship organizations like Dell and EMC, we have leading-edge technologies. So we're excited about where that can go and kind of what that can mean. It'll be a big step. >> Okay two personal questions from me as a fan. One is there really a money-counting room like in the movie "The Town"? Where they count a big stack of dollar bills. >> Well, I'm sure there is. I personally haven't visited it. (laughs) I know it's not in the room that they would tell you it is on the movie. (laughter) >> And finally, can The Cube get press passes to cover the games, next to NESN? Talk tech. >> Yeah, we'll see what we can do. >> They can talk baseball. We can talk about bandwidth. Right now, it's the level five conductivity. We're looking good on the pipes. >> Yeah we'll give you a tech tour. And you guys can sort of help us articulate all that to the fans. >> Thank you so much. Brian Shield, Vice President of Technology of the Boston Red Sox. Here talking about security and also the complications and challenges but the mega-opportunities around what digital and fan experiences are with the physical product like baseball, encapsulates kind of the digital revolution that's happening. So keep covering it. Here in Miami, I'm John Furrier. We'll be right back after this short break. (techno music)

>> live from San Francisco, celebrating 10 years of high tech coverage. It's the Cube covering Veum World 2019. Brought to you by VM Wear and its ecosystem partners. >> Welcome back, everyone. Live Cube Live coverage here in San Francisco, California in the Mosconi North lobby for V Emerald 2019 tapes our 10th year covering with some great guest, three days of wall to wall coverage that an amazing signorina Rob Salmon is the president CEO of Cohee City. Dave Solo, presidency of the Special Olympics Northern California. Thanks for coming on. Thanks to spend the time. Thanks for doing. Set the table. Why we hear what we're talking about. What's the purpose here? I know I wouldn't want to set it up more >> absolutely. I've been involved with Special Olympics for several years now. When former company Netapp Matt Thompson over Adobe called me and said, We got this high tech challenge. Dr. We've never sold it out. We want it. We want to get more companies involved when you help out, and the answer was absolutely and that led to David asking me to be on the board. So I've been involved with David, the team for an awful long time. KOHI City When I joined the company, some of the folks there knew of my involvement is that we'd like to start participating as well, which has led to what we're doing here. Of'em World >> David Talk about Special Olympics Quick mission for sure about the folks that might not given update for sure. >> John Yes, so Special Olympics enriches the lives of children, adults with intellectual disabilities. And so, in our footprint in Northern California, with serve over 23,000 athletes ages eight above and it's it's it's interesting. There's a lot of misconceptions people will say to me That's a great event that you do every four years And they referring the World Games, especially its world games, where athletes from all over the world get a common compete. But locally, through the state programs, hundreds of competitions happen a each and every year. And in Northern California we have, or 400 competitions per year in 14 different sports provides a wonderful ray of opportunities for athletes to demonstrate what what they can do when given the opportunity >> to do so. Talk about the community of aspect of it because I think What's interesting is what's on TV and what's in the mainstream press. It's more reach people that can be known for that. But it's deeper than as you point out. But >> talk about the >> community aspect. Got volunteers, people, individuals involved. Yeah, but the makeup of the network? No, it's an incredible network. >> I think we've really brought in an expanded our reach over the last 10 years. It used to be well known primarily for sports programming. So now we have inclusive education and health programs. We're able to bring together people with and without intellectual disabilities through those mediums. So if I'd resource is to schools an education and they run special Olympics programming during the school day. So educators wanna have us because we're improving school clamp campuses, reducing bowling, enhancing social emotional learning. And so the work that we're doing is so so critical with that community, then the area health. We have inclusive health. So now we got health and medical crypt, uh, professionals that are now providing health screenings for athletes. So some of the younger volunteers that we get that they're wanting to make a career in the medical field they're exposed to our population, right? And so they learn more about their specific health needs. So it's really about changing people's attitudes. And so this community of supporters volunteers, health professionals, education, Really. Our goal is to change people's attitudes fundamentally worldwide about people with intellectual disabilities and really kind of produce inclusive mindsets. We call it really promote understanding. >> If I may. I I really think what David and his team does and folks of sports Special Olympics around the world, they're dying. Changing attitudes are changing lives, lives of the athletes, lives of the people that work with the athletes, lives of the families. If you go to these events and there's something special, there are a lot of fun. And when you get involved and you see it, it definitely touches your heart and you realize we could be doing so much more. We could be doing so much more. >> I'm struck by you. Clearly, there's a passion thread here, and your background is really interesting to me because you're an accomplished student athlete, played football on and then you started a career in nonprofit right away, and now Rob, he was somebody would have hired right. It was like the perfect student athlete. You know, magna cum laude. I want this guy on my team. My hard driving says that How did you get into this? And described the background of that >> know for sure, sewn with nonprofit work. I kind of kind of started out. I was working for Boys and Girls Clubs of America, raising money to go to grad school, to be a history professor of all things. And so I got involved with the Boys and Girls Club with special Olympics. When the opportunity came, what was what was unique about it? It's really about how sports changes people's lives. Growing up, my father left me when I was 10 years old, and so was my coaches. They were the ones that really wasn't for them. I don't know that I would be here today, so they really took an active role in my life. So I've been very passion. I believe sports is a catalyst for social change, changed my life and provide an opportunity for me to be successful. And so that's what I want to help get back to our after. And it's also so. It's interesting is it's also proves that takes a village, you know, in these experiences changes lives. I think this is the big story, and it points to that. The sports is one element of other things. Health care. So you start getting connected in this is where the magic happens. This is the key. Yeah, some of the stories that wherever just phenomenal. I think society focuses on what our athletes can't do and dwells on the disability. We don't do that. So what? We're passionate about showcasing what they can do and having our volunteer, you know, certified train coaches work with our athletes to really help them get to the next level so they could be successful not only on the field, but off the field. So I mean, I got to get involved. Talk about the virtual. You're in Northern California. That's your territory, your area. But people, how they get involved, they wanna be share some no points of touch. Yeah, for sure. So a couple key points to touch would be number one. We have over 20,000 volunteers in our footprints, so we have a tremendous need for volunteers both globally and here locally, with Special Olympics, Northern California number two is from a donor standpoint. So everything that we do for athletes is completely free. And we're able to do that because the support of our community partners, our corporate partners like, Oh, he city, you know, individual supporters foundations were able to do that because of themselves. You know, either someone could go to the global website Special Olympics dot order come to W w dot s, O N C dot or for Northern California. We're always looking for volunteers, donor's community supporters, and we're also looking for board members, particularly from the tech sector. Senior executives in the tech sector. Justin, you stay channel lies for the people involved that also includes the people who volunteered. I'm sure people that want to make a difference whether you're thinking of senior approach, rather urine or your employees who want to give back so tell about the lives changing impact there because this is a corporate angle here that's not doesn't it's not for profit thing. It's a four good thing. >> Oh, this is for a good thing, and the thing I did to that is, and we touched briefly on Boys and Girls Clubs of America. These are all great organizations. I know Patton is key note. This morning, touched on giving back. This is an opportunity. Well, we're all blessed. We should give back. But the whole notion of getting more involved in touching lives I'll start with my two boys. They went to summer games and U C Davis three or four years ago. Now both of her good runners and they had some other kids on the high school team go with them. They were incredibly impressed. They had a lot of fun. A little banter with the athletes. Newsome, Bath, please. Out there there, Let's talk your heart. The gun goes off for the start, and they're already you get the arms up, curing away, and there's others incredibly talented athletes as well. It's so it just opened your eyes of what is possible. You're the one thing I touch on Is self esteem matters for every one of us, whether you have a disability or not, whether you're young or my age, it matters for someone to tell you that you are good. You are really worthy. Your hard work is paying off. You see these athletes when they finish the race or accomplished something that couldn't be more proud going to these events it will want. You will want to get involved. That's what typically happens. >> It sounds like you do coverages gonna be making its way to these events. Actually, wait, are fully got this part in the NHL MLB, NFL Masters golf tournaments. We have to get a pro circuit going on here way. Wonderful. Yeah. Hey, this is a really great cause. Any final thoughts again, back for people who want to get involved in the North California group. What? What can you offer people? No, I think we offer people a tangible way, especially when we think of the tech sector. And we think of the, you know, the employees and the millennials and hands on way for people to come out to our regional competitions and actually engage with our athletes and volunteer and be hands on and actually see where your money goes. You know, see, see that it's something tangible and you're helping provide that venue for athletes to be successful. One of things I didn't mention that we're really proud of. So we have a way of athletes are college students. We have athletes that are full time employees. Married couples, >> Um, >> and then we have a published poet. But last couple months we have an athlete that passed the bar exam who is now going to be a practicing attorney on. So that's really shows that you know, one of the things that you guys are hitting on here, Rob, I know you guys do a lot with your company. You guys even donating one of your tech sessions for a survey that John Troyer's team did around. Check burnout. People get it and even my kids to go to the high school In a lot of high schools like this now, where people get stressed out of the weirdest things, >> This is the kind >> of thing that getting involved in these community events like this really could help everybody. She allowed a little bit, Really. Take a load off, work with people, see the connection, see the impact. It's a burnout tactic option. It's also a way to relieve some stress. Feel >> good about it. >> The employees of Cohee City, when they came to me and said they want to get more evolved, they didn't do it because of me, they did it because they're excited about working with Special Olympics and they're beaming. Means some of the athletes 11 9 with a bunch of athletes going the baseball game tonight, Hamilton tomorrow night, their families as well. We couldn't be more excited, But I agree with you. You look at all the stresses in our lives, and I think this notion of what you do, who you do with how you give back is really, really important. I think that gives back piece, I think more of us allowing employees to do that, helping our children and school understand truly important the value. Um, is this absolutely >> You guys are making a great point because we've both been involved in youth sports all our lives, and it's kind of become twisted where you've got kids needs and parents needs and the parents trying to meet him in the middle, and that's not the way it should be. Your initiatives, I mean, it underscores what it's really all about. Self esteem, having fun, supporting your teammates and the broader community. >> But they stay well and compete and win two that they're in there. See some of those players. I mean, they're >> hard. I've seen some hard core competition, no doubt. But how well do they start? So >> eight years always started eight. And we have an athlete that's 81 that participates in watching. >> So okay, so appropriate. But the reason I miss it because, you know, having studied this allowed it. It's like 12 years old is the crossover point where people start to get crazy. And if you start before then, in other words Oh, this kid is nine. But he's not that good. Who could tell what a nine year old Michael Jordan got cut from his freshman basketball team? So it just goes to show you. So I think that that again, the values that you guys air promoting our worthy thanks >> me feel better about what we're doing. A cohesive it really does. Thank you for doing this. Being able to put two things I'm really passionate about together. Ah, this is pretty special for me. And I think my it around our founder and the rest of the company. And in David and team, they just do a fantastic job. I just wanna make sure we keep building on it. >> Congratulations. Great to get the word out. Congratulations. All your hard work. Awesome Cube coverage live in San Francisco. We back with more after this short break.

>> Hey, welcome back, everybody. Jeffrey here with the Cube were Rhetorical Park in San Francisco on the shores of McCovey Cove. I just love saying that we >> haven't been here since >> 2014. We're excited to be back for a really interesting event is called Sports Tech Tokyo World Demo Day. This next guest has been at it for a number of years. A really cool technology. We're excited for the conversation and to welcome Mark Philip. He's the founder and CEO of Are >> You watching this Mark? >> Great to see you. Good to see you, too. Absolutely. So, first off, you've been Thio Park before. Here I have. It's been way too long. >> There are >> a few iconic stadiums in the world, and this has got to be one of the great. So let's get into it. So what is are you watching this all about? >> We are the best friend that is >> giving the digital tap on the shoulder when it's time to run to the couch. We monitor pitch by pitch, shot by shot data to figure out when the game gets exciting. I love my Yankees till death, but the >> Yankees Red Sox occasionally tend to >> take over my entire night when they play each other. So being able to get that tap on the shoulder saying, Hey, it's time to tune in or stop raking the leaves, there's a no hitter through eight. Okay, that's what we try to do. Okay, so let's break it down before we get some of the applications into which actor doing So You guys air, You're actively watching these games. You've got some type of an algorithm based on scoring plays. Pitch count. Are we? What are some of the things that drive? Whether this is an exciting game or not, it's a great question. The easiest way to think about it is if you imagine what a win probability graph looks like. So game probably starts off in the middle. Might go up or down based on who's winning, the more violently that graph goes up and down generally, the more exciting the game is, so when probability is a big factor. But also you think about rarity whether it's we had a no hitter last night, we had the Astros with a four picture no hitter a few weeks ago. You know, those sort of things that you don't see often, even if the game's nine nothing, even if the wind probabilities and changing. If that's a no hitter, that's something you want to turn into, right? And so are you tapping into just kind of some of the feeds that are out there in terms of what's happening in the game or you actually watching and using a I in terms of actually looking at a screen and making judgments? Sure, thankfully, I'm not watching or else I would never leave the house. But for us, it's about getting that real time live data. Okay, so I can see balls and strikes on my servers faster than I can see it on live TV, which is a little bit mind bending of time. So we work with the the official data sources. So whether it's a company like sport radar or stats or opt or Abels and pretty much anyone around the globe, we pull in that real time data so we can give people that tap on. The show says Hey, run to the couch. Run to the bar, tune in. Something interesting is about to happen, right? But what's entering your B to B play. So your customers are not me. Jeff, go to the couch. You're working through other people that might be motivated to have me run to the count. So how does your business model work? Who are some of your customers? What are some of the ways that they use your service? >> I'm I'm the guy behind the guy. I'm behind the >> Red Curtain, pulling the strings, you know, for us not to paint with an overly broad brush. But we're based in Austin, Texas, and one of the big things about a city like ours versus the city like this is that our companies tend to skew very B to B versus the Bay Area, which generally excuse a lot more B to C. So pitching to the cable companies, the sports providers, probably CBS Sports is our oldest customer right now. We work with small startups, more established folks, and everyone uses this differently. But the goal is the vision. Is that whether it's your DVR recording automatically when the game gets good or just making sure that, you know, maybe you want to place a bet on the Giants or if you are, ah, glutton for punishment my lowly Knicks if the if the spreads. Good enough, you know, getting that nudge when games get exciting is an accelerant. Not just for watching in, but I think, for fandom. Yeah, well, when Kevin Durant comes back, you'll get a bit more exciting >> Nets, not Nick's. I'm gonna give you one free one. So we had a conversation >> before we turn the cameras on about, you know, kind of this. This never ending attention span competition and the never ending shrinking of consumable media. And how you guys really play an interesting role in that evolution, where if you can give us a little bit deeper background, >> I think it's fascinating. You look at >> the N B A. That really any league. If you rewind five years ago, you have to pay to 5300 bucks to get access to anything digitally, and then you got access to everything, and then the NBA's said, Well, maybe just want to buy one team, so we'll let you pay things around 80 bucks and they just want to watch. One game will sell it to you for eight. I just want 1/4 with such for dollar 99 if you just want a few minutes with silty for 99 >> cents, and now they've done that really, really quietly. >> But I think it's seismic because I think all leagues we're gonna have to follow and do this. So if you look at these snack passes and especially as thes NFL rights are coming up, I could easily imagine someone like a YouTube or, I should say, a Google if they were to grab these rights, how easy would be to go to YouTube and get a game for a few bucks and how well their entire infrastructure would work. But rewind to today when you have 10 to 20 states that are online. As far as gambling goes, you take gambling. You take excitement analytics and you take the snack passes and you kind of mix him up in a pot and you get this vision of I can send you a Texas is Hey, LeBron has 60 points with 3/4. Do you want to pay 99 cents tow, Watch the finish, or do you want, let's say, place a wager on if he's gonna be Kobe's 81 point Lakers record and then we'll let you watch for free. And so getting both sides of that equation, whether your die hard or casual fan, it's hard to say no to both those options, right? And do you see within your customer base that drive to the smaller segmentation of snack packs? Is that driven by customer demand, or are they trying to get ahead of it a little bit and offer, you know, kind of different sizes of consumption, I guess, would be the right. >> Sure, I think the horse is out of the barn. I mean, imagine if >> we were still buying complete albums. Of course, we're buying tracks when we just wanna track the idea that we have to buy an entire season. No foul, 2430 games in an MLB season. Why won't you let me buy just one game? I say MLB leaves a million dollars on the table every single time is no hit bid because there's tons of people who have cut the cord, don't want to run to the bar, but would happily pay 99 cents to stream the last inning of a game on their phone on their commute. So I think it is a combination of digital. What shoring in that We're able to do these three single track sort of purchases, but also its people continue to cut the cord and rethink about how they spend their media dollars. It makes sense really interesting. So we're here. It's sports Tech, World Demo Day. What do you hope to get out of today? Why are you here? Gosh, at least to pay homage to the reason why I went to Tokyo for the first time and had life changing Rama and I feel like I need to sort of complete >> the cycle. Uh, sports like >> Tokyo is an amazing program. There's lots of different events that have shaped different ways. But there's something really unique about this. And when we all lands in Tokyo, I think it was something like 80 different entrepreneurs that came into met to meet with all of the Japanese sponsors. Everyone had the same vibe of just really happy >> to be there. >> They didn't take a percentage of these startups coming in, so you really saw different sizes, not just early stage, but late stages well and everyone was there, too. Connects and innovate and do interesting things together. So many of us were there for the first time that there's just a vibe to this event that I haven't seen in my 10 plus years in sports. Tak interesting. Well, Mark, great to sit down with you. Really cool story. And, um, I guess I'll be watching for your watching for your app. Is the man behind the man coming through my phone? Real sand Sounds great. >> All right. He's >> Mark. I'm Jeff. You're watching the Cube World. World Tech demo today here at Oracle Park. Thanks for watching. We'll see you next time.

>> from Boston, Massachusetts. It's the queue covering active eo 2019. Data driven you by activity. >> Welcome back to Boston, Everybody. Money >> belong here with my co host, a student of John >> Kerry's. Also here today You watching the Cuban leader and on the ground tech coverage. This is day one of active fio 19 data driven content Conference hashtag data driven 19 red cara minuses. Here is the senior vice president of fantasy Sports A draftkings Greg. Thanks for coming on. What a cool title. >> Yeah, it's It's, you know, I was joking with my wife. Anytime you could be working fantasy sports, it's a great place to be. Everybody's a little bit jealous. >> So the formula is easy, right? Offer big giant prizes and everybody comes And that's all there is suing. Anybody can come >> in. I just have the dream job right now. >> So hugely competitive market. You guys, you become the >> leader. We were in the radio. Check out your websites. I mean, take us through the draft kings and your ascendancy. How you got here? >> So, you know, company started in 2012 initially around sort of the major big American sports on DH. Then really a CZ. We started scale that we saw there was a huge consumer interest in the product players that would come on. We're very, very, very sticky. Um, and we've just been kind of, you know, pushing, pushing on growing that using these. So the initial founders are three former analyst. So come on. It's always been sort of a very analytically driven company. So they looked at what we were dealing with, and it was we had L TVs that were way higher than our cracks. So let's keep marketing and growing and growing and growing and finding out ways to offer a better product. So, over 2015 we did a major marketing blitz, blew up the company Absolutely huge. Um, and since then we've been just constantly innovating, adding new sports, adding new features on DH, adding ways toe on the product. And then even more recently, just about a year ago, we expanded also into online sports betting over New Jersey has that's become a legal product across the U. S. So it's been a great time to be at the company a lot of fun. >> What what was your first sport was like Amazon started in books and then, you know, scaled out what was your first sport. So it's actually the first sport was >> baseball because of the time that they actually launched. So is the middle of April. Sporting calendar is a little bit thin. Right then, so is it was baseball to start, and then once football season started, that's really when things take on >> 2015 is when you started the marketing blitz and I remember just here in the ads and it was just intense, like a while. This company's going for it. So you sort of took >> all the chips I went >> all in and it worked. Yeah, I mean, it's part of the, you know, the lifeblood of the company. It's We're a company that ends up being taking risks, but we take calculated risks. So at any given point, you sort of say, like, Hey, what is the what is the range of outcomes over here? We're not playing for second place. We want to be a market leader, so you have to take risks in order, be a market leader. So let's take calculated risks. Let's make sure we're not being insane, but you know we did the math. We figured out what? This is A This is a worthwhile shot. We pushed him for it. Andi really took off from their love to bet on >> sure things. Yeah, well, Greg, we know the people that play the fantasy for it feel that data is what differentiates whether they're going to live in, you know, winner lose. Talk to us a little bit about the data journey inside your business And how that helped differentiate draftkings in the market. Yes. So we think Death draftkings >> is one of the most analytically based companies in the, you know, definitely in the market, but also into sort of like General Cos right now we use our analytics platform to inform pretty much everything we dio on. Go to your point. You're joking. You know, it seems like fantasy sports is easy throughout some giant prizes there, and everything will take care of itself. You know, running a fantasy sports car company. If you throw out a contest that's too big, you lose a ton of money. There's a lot of asymmetric risk in the business where if we're right, we make a little bit more. But if we're wrong. We lose a ton very, very, very fast. So our ability to be very, very sound analytically is what allows us to sort of pushed the envelope and grow, grow, grow but not, you know, lose our heads along the way. You know, some of the fun of that is really, you know, when we first ran, I think one of the most game changing contest we ran was actually back in October of 2014. It was the very first millionaire maker contest I could still remember. It was Week five of the 2020 14 NFL season where we said, Hey, this it's crazy. We need crazy things that happen in order for it to work. But if we're on a $20 contest to enter with $1,000,000 top prize and 2,000,000 of total prizes, it could go viral, go absolutely crazy. And if it loses, here's how it'll losing. Here's how much will hurt us. It's a worthwhile risk. Let's go for it. So that sort of energy of, you know, doing discipline analysis and constantly sort of them. Taking the risk on the back of it is what allowed us to build >> up the brand value that you would have got out of that was sort of worth that risk in part anyway. And you wouldn't have to hurt presumably. >> Exactly. We knew our downside. As long as you know your downside, you're normally in a pretty good spot to take those risks. >> So where do you >> see this All going mean? So the company has grown. You're at this kind of critical mass now, Like we said, highly competitive, you know, knock down. You know, if you take your eye off the ball. So how do you guys keep this going? >> So we have a huge challenge ahead of us over the next couple of years, as sports betting becomes legal across the US, we need to make sure that we are one of the top competitors in that market. Sports betting in the US, we expect to be an absolutely enormous market. It will probably be significantly larger than the fantasy sports market in terms of absolute revenue and even, you know, on order of magnitude more competitive. So we need to be executing each step along the way a CZ markets open up. We need to be able to get into getting two market very, very fast. And that means our tech team needs to be working feverishly to make sure that we can hit the requirements that each legislator and each regulator puts on market entry in their state. We didn't mean making sure we're constantly figuring out what are the product elements that are absolutely critical for our for our users. Is it Maura around the live betting experiences that around the different markets that you offer? It's around pricing. And how do we find these things, these different lovers and told them to make sure that we're putting out a great product for users. And if we do that and throw a great product after users were pretty sure we can make you want >> to be one stop shopping presumably, right? I mean, all sports, right? But But then you've got these niche sports betting. I mean eggs, invest. Example. I could think of this horse racing. You know where it is alive. It's gonna video. It's got commentators on the ground that you know the business really well. Is >> that Is that the strategy to go sort of horizontal and so be a one stop shop or you >> gonna sort of pick your spots? What is the day to tell you? >> You know, I think we're constantly talking about it. One of the things that allowed our fantasy sports business to grow so fast was going a little bit more horizontal. So we offered Gulf in Mass at a time period when the primary competitors and the space vandal did not. On DH, we built that product into one of our largest sports. It's, you know, right up there with MLB in terms of the actual size that that comes in a Z have gone also horizontal, we pulled in other places, like NASCAR. Mm, a great sports that people are interested in. It gets more users into our platform. And honestly, if uses are interested in a product, we don't want them to have to go elsewhere. We want to be able to have the offerings that any sort of, you know, critical mass type environment is going toe is gonna have >> Well, it's that experience, right? Well, I like to shop in Amazon. You do, too, because I >> trusted. And it's the same user experience. So, Greg, one of things >> I'm hearing from you is something that everybody tries for, but it's really challenging that speed. How do you react that fast and move the company into new markets and new offerings and keep innovating? You know, culturally technology wise, you know, How does Draftkings do that? You know, I think a za company, you know, from really every single person that we recruit in higher We've been actually execution Aly disciplined throughout the company's history. It's It's something that our founders did a great job of instilling in the culture right at the gates. I mean, we've tried to foster all the way along the way, which is all the best strategies of the world. They're going to fail if you can't execute well and every single person down the company knows that. And we try to, you know, enable each person to be as autonomous as possible in their ability to execute their their portion of the business that allows us to move really, really, really fast. You know, we disseminate that responsibility quickly, and each leader and sort of each person knows what they have to do to execute. There's a high degree of accountability behind that, you know, I'd like to say there's some. There's some magic recipe that's, um, secret sauce, but it's a lot of just great people doing great work everyday. Well, Greg, you know it's any your competitors that they look at, You know, Boston's been been doing pretty well in Draftkings era, you know, for the last few years. ES o Boston's been a great market for us. We've expanded Conover here on DH. The sports teams have been fantastic, although the Bruins it was a little bit sad about Game seven over there, but it happens. >> So his m o be the flagship news that no, I wouldn't say >> that MLB was first, primarily just of the time of the year when we launched. NFL is always going to go, are not always going to be, but for the for the foreseeable future is the dominant US sport on will remain the dominant US for >> no reason. I mean, kids there watch MLB anymore. Maybe the maybe the playoffs and the games. It was a game. I think I'm some Father's day was like almost five hours long, you know, gets called. You can come in and out. But you know what some of the trends. You see soccer. Is that growing NFL? Obviously huge. Do you see so niche sports like lax coming on. >> So, uh, you know, starting point NFL has been huge. We actually launched a new product Ah, little over a year ago called Showdown, which allowed you start to do fantasy for a single game as opposed to the combination of games that's taken off fantastically because that's tapping into more of the I'm going to sit down and watch this game, and I would love to have a fantasy team on that on this game. That's really expanded the audience like that. That >> was genius because, look, if you're >> out of the running, it doesn't matter because I'm weak. On top of that N b A and NHL on fire. The embassy put out a great product is an actual sport league. You know, the Finals were great. You hate to see the injuries, but it was a great final. Siri's very competitive. The NHL Finals has been very, very competitive. Golf is growing phenomenally as a sport, way farm or interesting golf than I ever anticipated when I first started with the company and it's one of the most exciting things. When the Masters comes each year, every screen has turned to it and we see a huge player. Player number is kind of coming into that one. Beyond that, you know NASCAR. What's been interesting? NASCAR's been having a tough couple years, but the Truck series for us? We launched it this year and the trucks have been great. I don't know if you've watched NASCAR Trucks. They're wildly entertaining. Uh, you know, Emma, you got the big fighter. So every sport sort of has its moments. It's a matter of like picking those moments and figuring out how to make >> the most of them. Do you see boxing at all making a comeback? >> So we have thought about how to get boxing into a into a fantasy. We don't have it at the moment. We're putting a lot of thought into it, so we are actually seeing through. We've seen, you know, we've been in the M M A space and we've seen the growth out from there where that sports doing great and you look at places like Bela Tor. The Professional Fighters league is other leagues, and then boxing is the next step. There's a lot of interest there. I don't think they have the right products yet to be able to kind of engage with that extra way. So that's one of things we're working on. Also, you need a marquee fighter. You always need a marquee fighter. Kind of helped bring in the interest over on that side. So, um, be interesting to see with Taki on sort of the downside of his career. At this point on DH, Mayweather hasn't been fighting much. Will be interesting to see. Who's that next meeting with Adam. But >> I grew up in an era >> of Marquis fighters. What? They would fight, you know, they literally fight 6 70 times a year, you know, and you had used huge names on DSO, and then mm comes along and he's really hurt, >> but it feels like it's tryingto so to resuscitate. Yeah. I mean, I think these things could >> be a little bit cyclical. Like you get one Marquis fighter out there like so my wife, this Filipino. So I'm a huge backing out fan now way watch every fight. Even when we were living in remote locations that forces watching at weird hours. He's a type of athlete that could bring popularity of the sport. So if there was a major U. S. Fighter that gains that degree of sort of, you know that that degree of fame people will be into it, I think >> Do do do your analytics sort of have a probe into the activity at the at the fan level at the sports level, not just the fantasy level or the betting level? Is that a sort of ah ah predictor for you? Yet we >> see a lot of correlations between how many people play our sport are fantasy game, and how many people actually follow the underlying sport. Way can also see trends in terms of If I'm from Boston, I probably pick more patriots in my fantasy lineups than, uh, normal on DH. You can actually see that as people play different sports that you know, the number one Q. Be drafted in in Boston is almost always gonna be Tom Brady. And once you leave that you start seeing Aaron Rodgers pop up. Let's really, really fast. So you see these little micro trends where it's like you are still a sports fan of your local team in your local environment, but it manifest itself in the fantasy. >> So what you think that is? Do you think it's fan affinity >> or do you think it's just the sort of lack of knowledge out inside? You're sort of a circle of trust. >> I think it's probably a combination. I mean, I could say is, you know, following the Celtics in the mid to thousands, I knew the depth of the Celtics pension, how they would use their rotation better than anybody else, Probably better than anybody else in the coaches would probably disagree. But it's like I knew that James Posey was a huge value play on Saturday nights. I knew. I kind of with I feel the Eddie House nights. Uh, so, you know, on your local team, you probably know those players at the not the top top echelon All Stars, but the guy's right beneath. You know them a little bit better and probably more comfortable using >> what's your favorite sport. >> So my favorite sport, from a fantasy perspective, is I play all the basket. I play all football, played basketball just during play offs, and I played baseball. But baseball I'm strictly a fantasy player. I don't really follow the sport to play. I'm just playing fantasy. Okay, >> That's great. So, what do you think? The conference. Here. >> You have you Have you had any timeto interact? I know you were swamped after coming off the stage. >> You know, it looks like a great turnout over here. There's a lot of enthusiasm amongst them from people. I was a little bit late to the late to show up this morning, so I got a bit Swanson eager to go and be able to catch up a bit more. >> Okay, Well, Greg, thanks so much for coming on. The Cuba's great to have your every pleasure meeting you. >> All right, people. Right there. Still, when I >> was back with our next guest, John for it is also in the house. You wanted The Cube from active field data driven 19. Right back

>> Male Voiceover: Live from Atlanta, Georgia, it's theCUBE, covering Citrix Synergy Atlanta 2019. Brought to you by Citrix. >> Hi, welcome back to theCUBE. Lisa Martin with Keith Townsend and we're coming to you live from the show floor of Citrix Synergy 2019 in Atlanta, Georgia. And we're welcoming to theCUBE for the first time Adam Jones, the chief revenue officer of the Miami Marlins. Adam, it's great to have you on theCUBE. >> Pleasure to join you both today. >> So, baseball fans, White Sox, San Francisco Giants, Miami Marlins. Always cool to talk sports and technology when we can bring those two things together. I think the San Francisco Giants and the Miami Marlins might have something in common right now, but regardless of the standings, everybody wants to go to a game. You have to deliver, as chief revenue officer, a great a fan experience. You got to make sure all the vendors are there to deliver what those fans want, regardless of the standings. People still want to go to the games. Talk to us a little bit about your role as the CRO of the Miami Marlins, how long you've been doing it, and then we'll get into what you're doing with Citrix. >> Sure. So, joined the Marlins 18 months ago as part of new ownership and the new leadership team brought in to reset the standard for what the Miami Marlins organization could be. We want to be a world class sport entertainment enterprise. That means we're going to evolve beyond a traditional baseball team and ballpark. 26 years into the history of the franchise, eight years into the operating rights of a ballpark, and there's a lot of work to be done around those two assets but as we take the organization forward, we want to continue to broaden that enterprise to focus on more sport and entertainment offerings. >> So, chief revenue officer. We don't get many chief revenue officers at a technology conference. Help make the connection. You're a busy person. What made you take time out of your schedule to come to Citrix Synergy? >> Well, I think it's indicative of the culture we're building within our organization that we're putting data at the very center of our culture. We're going to make informed and timely decisions and we need our technology to enable that culture. And so, when it came to where we were going to align our IT group and it's a group that has built out a very robust, on-prem infrastructure over the past seven years following the opening of Marlins Park, the alignment under strategy, which was my initial title coming in, and now chief revenue officer as I took on more responsibility for the business side of the organization, was a strategic decision to make sure that the infrastructure was meeting the requirements of the organization as we rapidly evolve what our priorities are and what we need in order to deliver on their very aggressive and lofty expectations for their organization. >> So this morning during the keynote, we heard a lot about the digital workplace, the employee experience being really critical for any type of organization's digital transformation, and I just thought it was a really interesting viewpoint because we go to a lot of tech shows here at theCUBE, all over the world, and we don't often talk about employee experience or even culture, as a leading edge indicator of how successful a digital transformation is going to be, but employee experience is really critical to any business because whether those employees are interacting with seven to 10 apps a day based on their job, or they're interacting with your other users, in your case, Marlins fans, making sure those employees are productive, have what they need, in a personalized way, is critical. Talk to us about what the employee experience means for the Marlins, and also, as an indicator on the revenue side. >> Absolutely, so we have an evolving workforce. It's very young across a very diverse enterprise of activities. What we've been able to do in partnership with Citrix since day one of the ballpark, where we went from an organization of roughly 100-150 employees around the team to 300 plus across the team and the ballpark, is build out an infrastructure that was very light in terms of hardware, focused very much on the digital workspace keeps us very nimble, allows us to deploy capital in areas that we see tremendous value back in terms of application and utility. So, as we continue to make our workforce more mobile, I ask them to deliver and work at a higher rate of speed. We need to arm them with the tools that allow them to perform those roles in the office, out of the office, engage beyond more just than a 81 day transactional relationship across Marlins baseball, but how across 12 months out of the year, creating that 365 day touchpoint. They still have tools and access in order to create those memories, those engagements that we want with the market. >> So, talking about customer experience, Marlin baseball is more than just the 300 employees. It is your partners, it's all of your contractors. When I go to a ballpark, I don't see Mark the hot dog vendor I see Mark, the guy that works for the Marlins. My user experience, my customer experience needs to be excellent across that. As CRO, that's part of your responsibility, assuring that the whole Marlin family is presented as one unity. Talk to us about from not just a user experience perspective but also, security expectations of how you need to make that real for your customers. >> Sure, on the experience side, what we are doing is resetting the standard, not only for Marlins and for South Florida, but the industry as a whole. We've brought on a lot of great talent to the organization from across the industry that knows what's worked, what hasn't across our peers. We're applying that. We're challenging conventional practice trying to get out in front of the curve as to what is going to be the future of a game day experience, what is a sport entertainment enterprise more holistically. And so, as a result, we have to arm our employees with those tools that will allow them to engage consistently across all the touchpoints with our fans, with our partners. Try not to centralize data to the point where only a select few have and feel informed and empowered to make decisions and take action, but disseminate that information and empower everyone to deliver consistently across all of those touchpoints. On the security side, being a public interest entity, we're vulnerable. We're a target. There's plenty of precedent around the type of activity that these types of organizations can be prone to try to address, and so, security is a number one priority of ours to make sure that the IP we're creating maintains and stays ours, as well as the information we are collecting around our customers, around our players, stays within that secure environment as well. >> So if I think about going to a baseball game, which I love, there are so many sellable moments there. Whether I'm in the stands and I want to go buy food and beverage, or I want a new hat, or some sort of merchandise for my nephew or something. You have, as CRO, you've got all these different sellable moments, not just in the ballpark, in the physical experience, but even online. So having this kind of cohesive opportunity to sell not just tickets, but food and beverage, merchandise, in person, on mobile, on a tablet, on a desktop, it's got to be a critical part of your strategy Talk about the alignment with yourself and you said a lot of your IT guys have FOMO cause you're here, but I imagine that those experiences are essential that you have the right foundation and technological foundation to deliver sellable moments that deliver. >> That's right. So the ecosystem of a sport is a fairly diverse one from the ticketing transaction to all of the ballpark touchpoints. What we're trying to create is that 12 month relationship with a fan, so that goes into creating a lot of content and how we distribute that content, in order to continue to earn that engagement well beyond 81 plus dates of baseball. And the technology behind there, in terms of our storage and our accessibility, is what allows us to begin to personalize and tailor not only those core, traditional transactions and touchpoints of sport, but how we've begun to transition into more of that broader entertainment enterprise in making sure that we can deliver those as personalized and tailored as we can. >> So there was another Chicago team that showed the age of baseball. It was over 100 years before they won a-- >> Another Chicago team-- >> Yeah, another Chicago team that won a championship. So baseball has a lot of tradition. You're in a unique opportunity that you're coming into a new ownership, but still, baseball has traditions that are hard to compete against. So let's talk about what are some of the cultural changes and opportunities that you see that baseball needs to engage in where technology can help. >> Why I think an interesting thought around baseball and where it's been scrutinized as whether we pace a play or number of games, of not keeping up with the times, not being as snackable, short-form consumption as other sporting content. As everything tracks that way, baseball starts to differentiate itself in terms of the ability to create a very distinct and differentiated experience to a millennial, to a family, to an older consumer who has grown up with the traditions of baseball. And so while baseball needs to continue to innovate and modernize, there's actually this interesting equilibrium as to how much it continues to challenge those traditions that differentiate it from many of other points of contact and where it should continue to preserve those elements to hold what has been generational-type engagement. >> You know a great example of that is mlb.com and being able to watch a game anywhere. Baseball does an amazing job of embracing digital transformation, at least in baseball. One of the things that we talked about, or that David talked about onstage today, is the seven trillion dollar opportunity. That's big, even in baseball numbers. There's no bigger sporting numbers than baseball, but seven trillion dollars is opportunity. What are you excited about coming out of this show when you look at some of the potential game efficiencies from some of the automation announcements that were made today? >> For our organization, while there has been significant investment in infrastructure, great collaboration with Citrix up until this point. The exciting transformation for us is our migration into more of a hybrid cloud environment, which is going to allow us to onboard a number of new applications, tools, for our sales team, our service team, our game presentation groups, to continue to innovate and challenge how they've gone to market in the past. And having Citrix as a partner that has that environment for us to step into, one, gives us a ton of assurance in taking that next step and having someone that continues to bring us new tools within that environment, as well. So our ability to collaborate across the organization, I'd say we've only just skimmed the surface as to the true capability and power of a lot of the tools we've had in place, and very excited about unlocking the true power and potential of that environment moving forward. >> So this is your second season with the Marlins. You spent 15 years at PWC and before we went live, I thought, wow, that must have been a pretty big change going from PWC to major league baseball. But you actually have quite a history in sports. Tell us a little about that and maybe some of the similarities between major league baseball as an industry to other industries that kind of surprised you. >> Sure. Organizations couldn't be different, more different, in terms of profile and in set-up. What I did day-to-day, advising across sport and entertainment leading the sports practice at PWC positioned me for this incredible opportunity or challenge that is the Miami Marlins and what we're building in this aggressive vision that we've set as to how we're going to reset the standard and become world class as an enterprise. PWC and the history with the firm and professional services gave me a unique perspective as to how to take on many of the challenges that we have. Had the opportunity working across sport to really understand what works, what doesn't, so that we can avoid some of those missteps that others who have taken on this roadmap ahead of us have encountered. The breadth of infrastructure that a firm of PWC's size, also gives me a little more of a lens as to what the power and scale of a large organization can deliver in more of a small, mid-size business form, and not accept size or employee base as a constraint as to the types of tools and sophistication of our technology that we can deploy within a sports organization. >> Well, Adam, thank you so much for joining Keith and me on theCUBE this afternoon, talking about how you are helping to make big positive impacts for the Miami Marlins. We appreciate your time. >> I enjoyed it. Thank you. >> Go MLB. All right, for Keith Townsend, I'm Lisa Martin. You're watching theCUBE, live from our first day of coverage of Citrix Synergy 2019. Thanks for watching. (upbeat music)

>> From Sand Hill Road in the heart of Silicon Valley, it's theCUBE. Presenting, the People First Network, insights from entrepreneurs and tech leaders. >> Hello everyone I'm John Furrier with theCUBE, we are here in Sand Hill Road up at Mayfield Venture Capital Firm for their 50th anniversary, their People First Network series, produced with theCUBE and Mayfield, I'm John Furrier, with Bill Schlough, the Chief Information Officer of the San Francisco Giants, CUBE alumni, great to see you thanks for joining me today for this People First Series we're doing with Mayfield's 50th anniversary, thanks for coming in. >> Good to be here, John. >> So, been a while since we chatted, it's been a year, A lot's happening in tech, you can't go a year, that's like seven dog years in tech, lot happening, you're managing, as the CIO for the Giants, a lot of things going on in baseball, what's the priorities for you these days, obviously, you guys, great social, great fan experience, what's new for you, what's the priority? >> Man, there's always something new. It's what I love about it, this'll be my 20th season with the Giants comin' up. And, it never gets old, there's always new challenges. On the field, in the seats, off the field, you name it. As we look toward next year, really excited about bringin' in a new video board, which we haven't publicly announced, maybe I just did publicly announce, we're breaking news on theCUBE today. So we're puttin' in a new video board, it'll be over three times the size of the one we have today. That's big news, we're doing a lot of exciting things in the ticketing world. The ticketing world is really transforming right before our eyes in terms of the way fans buy tickets. It's changed a lot. Once up on a time you could call a game a sellout, and we sold out 530 straight games at AT&T Park, but really there's no such thing as a sellout anymore I mean, at any point you can get a great ticket, so we have to adapt to that and change the product that we're delivering to fans, so making some changes on the ticketing front, the fan experience, the ballpark with the video board, and another thing that's changing a lot is the way fans consume our game when they're not at the ballpark. It's rare that you're going to see somebody sit on a couch for three plus hours and watch a game continuously anymore. Fans are consuming through mobile devices, streaming, catching clips here and there, all different methods, and it's fun to be a part of that, because, fans still love the game, but they're just consuming it in different ways. >> Yeah, I love having chats with you on theCUBE because one of the things that have always been the same from nine years doing theCUBE is, the buzzword of consumerization of IT has been out there, overused, but you're living it, you have a consumer product, the ultimate consumer product, in Major League Baseball, and the Giants, great franchise, in a great city, in a great stadium, with a rabid fanbase, and they know tech, so you have all the elements of tech, but the expectation of consumers, and the experiences are changing all the time, you got to deliver on the expectations and introduce new experiences that become expectations, and this is the flywheel of innovation, and it's really hard, but I really respect what you guys are doing over there, and that's why I'm always curious, but, always, the question comes back to, is, can I get faster wifi in the stadium? (laughs) It's always the number one question >> It's funny that you ask that because it is AT&T Park, you know, so, honestly, we got to check that box, and we've had to for years, all the way back to when we first rolled it out, way back in 2004 when we first rolled out wifi in the park, people weren't asking for it then, people were coming to the ballpark with a laptop and plugging a card into it, and there were about a hundred of them that were accessing it, but today, what's interesting is, who knows what next, but we're not talkin' about wifi as much, wifi is just kind of, expected, you got to have it, like water. You're talkin' about 5G networks, and new ways to connect. Honestly, this past season, our wifi usage in terms of the number of fans that use wifi, what we call the take rate, the percentage of fans, was actually down 30% from the previous year. Not because we had less fans in the stadium, because this is the take rate, a percentage of fans in the stadium, went down, because AT&T made some massive investments in their cellular infrastructure at the ballpark, and if you're just connecting, and you got great bandwidth, you don't feel the need to switch over to wifi, so who knows what the future will hold? That's a great point, and you see the LTE networks have so much more power, it used to be you needed wifi to upload your photos, so you'd go in, log in, and if they auto login that's cool, but people don't need to. >> Not with photos, what they need it now for is when we see it really maxing out is events, like our Eagles concert, or Journey concert, or a really big game, like opening day, or honestly, Warriors playoffs game, 49ers football games, that's when folks are streamin' to video. For streamin' to video, they're still goin' to that wifi. Yeah, that's the proven method, plus they don't want to jack up their charges on the AT&T site, but I won't go there, Let's talk about innovat-- Most say unlimited, I will go there, most say unlimited these days. >> Really, I got to find that plan, my daughter's killin' me with her watchin' Netflix on LTE, I tell her. Innovation is changing, I want to get your thoughts on this, 'cause I know you're on the front end of a lot of innovations, you do a lot of advising here at Mayfield. The VC's always trying to read the tea leaves, you're living it, what's the innovation formula look like now for you 'cause as you're sittin' in your staff meetings, as you look at the team of people around you, you guys want to foster, you do foster, innovation culture. What's the formula, what do you guys do when you have those meetings, when everyone's sitting around the table sayin', what do we do next? "How do we create a better experience? "How can we get better fans, and better product "in their hands as fast as possible?" What's your strategy? >> You know, it's funny, people talk about the secret sauce for innovation, what's the formula? I would say, for us, it's really a symbiotic relationship with a lot of things, first of all, where we are, geographically, we've got folks like Mayfield, down the street, and many others, that we can talk to, that are, when innovation is happening, when the startups are incubating, they're being funded by these guys, a lot of times they are here, and our phones are ringing off the hook with a lot of folks so my formula for innovation is answer the phone and take the meetings, but, to be honest, that creates its own problems, because there's so many great ideas out there, if you try to do all of them, you're going to fail at all of them. You got to pick a very small few to try to experiment with, give it a shot, we just don't have the bandwidth, we only have 250 full-time staff on the business side. For us, geographically, you have to really be laser-focused and say okay, there are so many great ideas out here, which are the three or four that we're going to focus on this year, and really give it a try, that's really going to drive, propel our business forward, enhance our product on the field, whatever it might be, but I'll tell you where it really truly starts. It's from the top with our CEO. And, I've had a few different bosses over the years, but with the Giants, our CEO is singularly focused on all of us doing things folks have never done before regardless of what business unit you're in. Whether you're in ticketing, finance, marketing, sales, what drives him, and drives all of us, is innovation. And his eyes glaze over when I talk to him about cost-cutting, and his eyes can glaze over really fast. But when I talk to him about doing something no one's ever done before, that's when he sits forward in his chair, he gets engaged, and I just have a great boss, Larry Baer, he's been with us for 25 years wit the Giants, and he is the driver for it, he creates the culture from the top, where all of us, we want to impress him, and to impress him, you got to do sometin' nobody's ever done before, and what's even more interesting is there are some challenges and some changes talking place across our industry, as I said before, ticketing and other areas, and I've sat in meetings with him where somebody might raise their hand and say, "But this is happening across the industry, "so it's just a macro trend," and he'll get upset, be like, "I don't care about macro trends. "We are here in the Bay Area, "we're the San Francisco Giants, "we're going to do it our way." >> And so when you do it your way, he promotes risk-taking, so that's a great culture. What are some of the things you have tried that were risky, and/or risque, or maybe an experiment, that went well, and maybe ones that didn't go well, can you share some color commentary around that? >> Sure, over 20 years we've had some of all of those. I would say, I've had some real scary moments, our culture is collaborative, but I wouldn't call it combative, but we all have strong opinions, a lot of us have been there a long time, and we have strong opinions and so we'll battle, internally, a lot, but then once the battle is over, we'll all align behind the victory. Thinking back, one of the most stressful times for me at the ballpark was related to wifi, when we decided to take our antennas and put 'em under people's seats. No one had ever done that before, and there were two major concerns with that. One is, honestly are people going to get cancer from these antennas under their seats, it's never been done before, what's going to happen, and whether it's going to happen or not, what's the perception of our fans going to be, because, these are, the bread and butter is, the golden goose here, all the fans, so, yeah it's great that they're going to be, have faster connection here at AT&T Park, but if they think they're going to get cancer, they're going to cancel their season ticket plans, we got to problem. Number two is, we're taking away a little storage space also, under the seats, so it was very controversial internally, we did all of our research, we proved that having a wifi antennae under your seat is the equivalent to having a cell phone in your pocket, most people do that, so we're pretty safe there, and from the storage space perspective, honestly, it actually elevates your stuff, if somebody spills a Coke behind ya, it'll fall all around your purse, which is sitting on top of that wifi antenna so we came up with a good solution, but that was an example of something that was really controversial >> So beer goes on the antennae not your bag. (laughs) >> Exactly, your bag stays dry, we found a way to spin that but, there have been so many, I can go way back in time, back to the days when it was the PalmPilot that ruled the day instead of the apple >> Well you guys also did a good job on social media, I got to give you guys props, because, you're one of the first early adopters on making the fan experience very interactive. That was, at that time, not viewed as standard. Yeah, built the @Cafe at our ballpark, which is still there really to try to bring social media to the fans. >> I think you're the first ballpark to have a kale garden, too, I think. >> That's a little off topic, but yes, driven by one of our players, who's a big kale fan, yeah, the garden out in center field. >> So sustainibility's certainly important, okay, I got to ask the question around your role in the industry, because one of the things that's happening more and more in Major League Baseball and certainly as it crosses over to tech her at Mayfield Venture Capital, there's a lot of collaboration going on, and it's a very people-centric culture where, it used to be people would meet at conferences, or you'd do conference calls, now people are in touch in real time, so these networks are forming. It takes a village to create innovative products, whether you're inside the Giants, or outside in the ecosystem, how have you personally navigated that, and can you share some experiences to the folks watching, how you became successful working in an environment where it's collaborative inside the walls of the San Francisco Giants, but also outside? >> %100, the topic is near and dear to my heart, and from when I started with the Giants, that's what I love about our industry We compete on the field, and only on the field. When you look at who the Giants competitors are, from a business perspective, honestly the Dodgers are not a competitor from a business perspective. The A's are barely a competitor from a business perspective. We got a lot of competitors and very few of them are in our actual industry, so we collaborate all day, and it's been amazing, I can count on one hand, across all of sports, folks who have not been collaborative. There's a very small group of teams, your favorite team, the Boston Red Sox, are not on that list, they are very collaborative, but their arch rival, well there's a few others out there that may be less collaborative, but most of them are highly collaborative, from top down, and so, what I did from when I first started the first trip I made, was to Cleveland. And this was many years ago, Cleveland Indians had a reputation of being very progressive so I called up my counterpart there, I said, "I'm new to the industry, can I come out, "can I learn from you?" And that's where it started, and ever since, every year, we travel to two cities, I take at least four of my staff, to two cities each year and we meet with all the sports teams in those cities. This year, we went to Milwaukee and we met with the Brewers, and we did the Packers as well. Every year, over the 20 years we've visited pretty much every professional sports city, and we just go through it again, and always, red carpet, open door, and you build those face-to-face relationships, that you can pick up the phone and make the call, in a few weeks we're all going to get together in Denver at our MLB IT Summit, my job at the IT Summit every year is I host the golf classic, so I bring all the golfers, the hackers, the duffers out, and we have a great time on the golf course and build those relationships and again, the only thing that we don't really talk about that much is the technology we use to enhance the product on the field. Everything else is fair game. >> So share the business side, but the competitive advantage, where the battle's really having Dodger and Giants obviously on the field, highly competitive-- >> But what's cool about that is then I can meet with the other sports teams to talk about that, so I'll leave the teams nameless, but we've had some awesome collaborative discussions with NBA teams especially to talk about what they're doing to assess talent, and there's no competition there. >> So there's kind of rules of the road, kind of like baseball, unwritten rules. >> Right. >> So talk about the coolest thing that you guys have done this year, share something that you personally feel proud of, or fans love, what were some of the cool things this year that pops out for you? >> Sure, the technology that we invested in this year that I thought was a game-changer, we saw, we experimented with last season, but this year, we've been experimenting with VR and AR a little bit. But, a technology that we thought was really cool is called 4DReplay, it's a company out of Korea. And we saw them, we did an experiment with them, and then we implemented them for the full season this year and we've seen them at some other venues as well, the Warriors tried them at the Playoffs, but we had 'em full year and what we did was they put in about 120 cameras, spaced approximately five feet apart, between the bases. 120 of 'em, and they focus on the pitcher and the batter, so when you have a play, you can 3D, or 4D, 4D rotate around that play and watch the ball as it's moving off the bat, and get it from that full perspective, it's awesome for the fan experience, it gives them a perspective they never have, I love watching the picture, because you can see that hand, in full 4D glory pronating as it comes through on every pitch, if you can watch that hand carefully you can predict what kind of pitch it is, it's something that a fan has never had access to before, we did that for the first time this year. >> I had a new experience, obviously you see Statcast on TV now, a lot of this overlayed stuff happening, kind of creates like an esports vibe to the table. Esports is just coming. >> And it's just the beginning >> Your thoughts on esports, competitor, natural evolution, baseball's going to be involved in it, obviously, thing in the emerging technology's looking interesting, and the younger generation wants the hot, young... Sure, we feel like our game has been around a long time, and it still is, the rules haven't changed that much, but fans still enjoy it, but they just consume it differently and our game can be incredibly exciting in moments, but, there's also some gaps in there when you can build relationships. Some of the younger generation may fill those gaps with watching somethin' else, or two other things on their devices, but that's okay, we embrace that at the ballpark, but in terms of the emergence of esports, and the changing demographic of our fanbase, what we're trying to do is just package our game differently. One thing I'm really excited about, and startin' to see, we're in the early days, I consider with virtual reality, we experiment with it, maybe two or three years ago we've been doing some stuff with it, but I'd say it feels like we're in the second or third inning with virtual reality, where we're really going, and I've seen Intel doin' some of this stuff, I was out working with Intel in Pyeongchang, at the Olympics this past year, working with their PR team, and where it's going I can already visualize what this is going to be like, this concept of volumetric video. Where, it's not about having that courtside seat, in basketball, or that seat right behind home plate, it's about being wherever you want to be, anywhere in the action. And to me it's not about doin' it live, because in baseball, you don't know where the ball's going to go, it's about doin' it, replay, right after, okay, that ball was shot to Brandon Crawford, he made the most amazing diving play, picked it up, gunned it to first, where do you want to watch that from? Everybody's different, some people might want to watch it from right behind first base, some people might want to watch it right Brandon Crawford, behind the batter, with volumetric video and the future of VR, you'll be able to do that, and this esports generation, this fan's instant gratification want, unique experiences, that's what's going to deliver it. >> This is such an immersive environment, we're looking at this kind of volumetric things from Intel, and you got VR and AR, immersion, is a new definition, and it's not, I won't say putting pressure, it's evolving the business model, who would've thought that DraftKings and these companies would be around and be successful, that's gambling, okay, you now you got that, your VR so the business model's changing, I've been hearing even token and cryptocurrency, maybe baseball cards will be tokenized. So these are kind of new, crazy ideas that might be new fan experience and a business model for you guys. Your thoughts on those kind of wacky trends. >> That's why I love working with companies like Mayfield 'cause they're seeing the future before we see it, and I love being where we are, so we can talk to them, and learn about these companies. Another example, along those lines is, how are fans going to get to the ballpark five years from now, and how do we adapt to that because we're doing a major development right adjacent to the ballpark, we've got 4,000 parking spaces. Are we going to need those five years from now? Well we're going to build out that whole parking lot, we're going to put a structure in there. But five, ten years from now, we're building that structure so it can be adaptable, because, is anyone going to need to park? Is parking going to be like typing, you know on a typewriter, 10, 15 years now because everybody is in either self-driving cars, or ride shares, and the cars just, poof, go away, and they come back when you need 'em. >> Like I said, everything that's been invented's been on Star Trek except for the transporter room, but maybe they could transport to the game. >> We could use that in San Francisco. >> Bill, got to ask you about your role with Mayfield, because one of the things I've always been impressed with you is that you always have a taste for innovation, you're not afraid to put the toe in the water or jump in the deep end where the technology is, these guys are lookin' for some trends, too. How do you advise some of these guys, how do you work with Mayfield, what's the relationship, how are they to work with, what's the intersection between Mayfield and you? >> Well the one thing that Mayfield does is they put together a conference, each Summer, that I love comin' down to, and I get to meet a lot of my counterparts and we talked about meeting with my counterparts in sports, but I love meetin' with my counterparts across all industries, and Mayfield makes that possible, they bring us all together with some really interesting speakers on a variety of topics not all directly tech related, so it's a great opportunity for me to just get outside of the daily routine, get outside the box, open my mind, and I just have to drop down the road to do it. So that's an example, another thing is, Mayfield, and other firms will come to me, and just say, "Hey, here's a technology we're evaluating, "they think it would be a great fit in sports, "what do you think?" And so, I can give them some valuable feedback, on company's they're evaluating, companies will come to us, and I might throw them their way, so it's really a two way street >> Great relationship, so you're a sounding board for some ideas, you get to peek into the future, I mean, we've interviewed entrepreneurs, successful entrepreneurs here, it's a seven, eight year build out, so it's almost like an eight year peek into the future. >> Yeah, and it's super valuable, especially given where we are geographically and our inclination toward being on the leading edge. >> I want to just end the segment by sayin', thanks for comin' in, and I want you to show the ring there, 'cause I always, can't stop starin' at the hardware, you got the ring there, the world champion. >> It's a few years old at the moment, we're going to have to get a new one sometime soon. >> We got to work on that, so is there any cutting edge technology to help you evaluate the best player, who you lookin' at next year, what's goin' on? What's the trades goin' on, share us-- >> Are we off the record now, 'cause I have a feeling you're asking this for personal reasons, for your squad, so. >> I'm a Red Sox fan of the AL, obviously, moved here 20 years ago, big fan of the Giants, I love comin' to the games, you guys do a great job, fan experience is great, you guys do great job and I'm looking forward to seeing a great season. >> Thanks, yeah, hope springs eternal this time of year, we always block off October and expect to be busy, but when we have it back, it just gives us an opportunity to get a head start on everybody. >> Well Bill, thanks for coming in, Bill Schlough, CIO for the San Francisco Giants, here on Sand Hill Road talkin' about the 50th anniversary of Mayfield, and this is the People First Network, getting ideas from entrepreneurs, industry executives, and leaders. I'm John Furrier with theCUBE, thanks for watching. (electronic music)

>> (Narrator) From San Francisco, it's theCUBE. Covering Sumo Logic Illuminate 2018. Now, here's Jeff Frick. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're at Sumo Logic Illuminate at the Hyatt Regency at San Francisco airport in Burlingame, about 600 people. The second year this conference, about triple the amount of people that they had last year. A lot of buzz, a lot of activities, some really creative things that I've never seen in the conference world with the silent disco kind of treatment for the training is pretty cool. Everyone's in the same room listening to their own, in training, I've never seen that before. We're excited to have, fresh off the keynote, the leader of this party, President and CEO of Sumo Logic, Ramin Sayar. Ramin, great job on the keynote today. >> Great, thank you for having me today. >> Absolutely. >> Thanks for being here. >> So, a lot of passion really came through. It struck me and it was palatable in your keynote, really reaching out to the community and talking about being on this mission together. I wonder if you can speak a little bit to how important community is to you, to the company, and what you guys are trying to accomplish. >> Well the interesting thing about that, Jeff, is that that's really innate in our culture and that's part of, one of the reasons why I actually joined Sumo. Specifically, one of our core values is we're in it with our customers. And that permeates all the way through to every action that every employee takes every single day, and ultimately, is seen and felt here at an event like Illuminate. So when we talked about community, is we're living and breathing the same thing that a lot of our customers are every single day. All the challenges that they're dealing with, the cloud, the cost, the migrations, the training. And so the more we get intelligent in terms of using our own service, the better it is for the rest of the users in our community, so that was a big theme for not just what we wanted people to take away, but also naturally as part of the announcements we made around some of the new intelligence. >> Right, right. I think it's an under-reported kind of attribute of SaaS-based business models, in that you are in bed with your customer because you're taking money from them every month, or whatever the frequency is, so you've got to have this ongoing relationship and continue to deliver value. And we've heard that time and time again, we heard it from the MLB guy on stage, we had another partner on-- >> Samsung, the smart things. >> The smartphone, but we had another one here. But just talking about working together with your teams collaboratively to execute on the objectives at hand. Not just here's some stuff, I'll take the money, good luck, we'll see you next year. >> Yeah, interesting enough you point out something that's a precursor to being successful in the SaaS business, and that is, you're having to get reelected every single year. But we don't wait 'til every single year, we try to make sure from the moment we land a new customer that we help them understand what it's going to take for them to get, not just instant value, but ongoing value out of our service. And we often times make sure they also understand they we're actually living and breathing the same experience they are, so there's that trusted advisor relationship, not just a vendor relationship. >> Right. The other great thing I'd love to see, and I think we first interviewed Sumo at our first AWS San Francisco 2013, You guys definitely picked the right rocket ship to strap onto. But one of the things that we love to watch is kind of the change of a company from an application space to a platform space. 'Cause nobody has a line item for new platform, nobody wants to buy a new platform. I tried to launch a platform company as a platform, it doesn't work, you got to have an app. So that's what you guys did, but you've got the infrastructure and the architecture in place that's now allowing you to get into the platform play and the slide that really jumped out to me, and I took a picture of it on my camera, was the diversity of roles in organizations that have Sumo Logic. After, I think they've had 60 months, you start seeing customer success people, design people, quality assurance people, these are not engineers. This is not reliability, this is a whole separate set of people that are using this great tool that you guys have built to solve some different business objectives, and maybe the ones when they started the company. >> Well, that's predicated on how we started the company. We never started the company to be a silo tool use for one part of the organization. It was always meant for how do we take what was typically in the back room only to select few of folks in security or operations to other parts of the organization, thereby democratizing like we've been talking about. And so, over the last few years, since you mentioned AWS and the reinvent show, we spent an enormous amount of energy and investment in terms of making sure that we're constantly listening to our users, we're constantly redesigning and iterating on a user experience, so that we can actually extend from the power users that might be in development or operations or security, into these other teams that you've been mentioning. And now we're seeing evidence of that, which is phenomenal. >> So it's, you know, we go to so many shows, we talk to a lot of smart people, it's really fun. And one of the things that I've come to believe in terms of how do you drive innovation... Some really simple things, you give more people access to more data with the tools to manipulate it and then the ability to make decisions based on that data. And that was really a big part of your theme, in terms of, you know, some of the new product releases that you announced and also again what we just talked about in terms of the use cases, is giving more people the tools and the data so they can actually make innovative steps instead of just funneling it through you know, asking somebody to run a BI report for me or this or that. That's not the way anymore. >> You're spot on. And I think we're still earning that right, to be honest with you. And while we've seen massive adoption in terms of various profiles of users and the types of data, I think we're honestly just scratching the surface here. And specifically what I mean by that is, we've announced some interesting things around industry benchmarks and community insights and obviously the modern app report that you talked about and covered before, but there's also a different subset of users that are now embarking on and leveraging a platform like this, and those are the data engineers, and those are the data scientists, because they don't want to be left on the back room. They also want, just like security operations or analysts or development teams, to be able to collaborate, be able to iterate, be able to share their own experience with not just the service, but how they're to getting value out of this. And so what's most refreshing, and honestly something that we pay very close attention to, is the types of roles and users that are here. And you see people from interesting enough product or finance or success report to your comment, but that's innate in the value of something like this that we're referring to in terms of machine data analytics platform. >> Right. So you guys are in such a good spot with the machine data. The MLB guy was interesting. He just threw up a slide with a whole bunch of really big numbers. But even more than that, we were at an AT&T show on Monday that the conversation's all about 5G, and the big thing about 5G 100X, 100X more throughput than 4G, designed for machine-to-machine interaction. I mean, the tsunami of data that we've been living through up 'til now is going to be dwarfed by this continuing tsunami when we get 5G internet of things, industrial internet of things. You guys are pretty well positioned to take advantage of this big, giant trend. >> We are. But we're also being very conscious and prescriptive how we approach it. So we've been maniacally focused first on the new applications, and therefore the new architectures associated with these applications that are being built and born and bred in the cloud. Then we extended it to those that are being lifted and shifted, because we had to earn the trust and the right there, particularly those that were running traditionally on-prem, we want to rewrite the front end, and in doing so, we had to often times interface and interact and get sign-off by security. And so that naturally led us into the CISO, in the security operations analyst teams starting to understand, "What's going on over there? "Why are those guys using that service, and why aren't we?" So then we extended our opportunity to security analytics play, and you naturally pointed out there's other opportunities into connected devices, industrial IOT, and what we heard from some of our customers today, in consumer IOT. But we're going to go to it gradually. We're also going to go to it through partners, and really extend the platform as customers use it for those use cases, not necessarily how we see fit always. >> I wonder if you can dig a little deeper into how security has changed. You've been in the industry for a long time, go Gauchos, I saw you went to Santa Barbara, my daughter's at Santa Barbara now, so we're all about the Gauchos. But you've seen how security has changed from this walled garden or moat around the castle, however you wanted to describe it, into being baked everywhere, up and down the stack, throughout the applications, throughout the infrastructure, and how that's really changed everyone being involved in security, regardless of what your day job is or what your title is. >> See that's what's the interesting thing. You heard it from MLB and Neil. There's a shortage of security professionals that are out there, so it's no longer just a duty and a responsibility of security operations or analysts; it's everyone upstream. And that's the power of what Sumo provides. It can't be an afterthought. And so what we're helping understand for our customers to understand is, as you architect these new workloads, specifically looking at micro services or containers or cloud, put some forethought and insight into what does that mean from not just an operational perspective, how do you instrument, collect, and log and events and metrics, but also from a security perspective. And so when you're able to leverage one platform to do so, it actually is a connecting mechanism, meaning that it's bringing these teams together versus isolating and siloing them like in the past. >> Right, right. I'd love to jump... You did a little bit in your report and now you announced some of the benchmarks and stuff about how you're able to aggregate, anonymize and aggregate back end data from a lot of different customers to start to share that information. To use BI and machine intelligence to optimize. To use benchmarks and to help your customers do a better job. And you're sitting on a boatload of data. And it's really a great way to provide another layer of value, beyond just the core functions of the products. >> I totally agree. And we are still early in that journey, though. And as I mentioned earlier in the announcements today, one of the ways that we're fixated on making sure we continue to get more data is constantly look for ways that we can bend that cost curve down for our customers. So that they can start to ingest more their tier-two, tier-three data or their lower-performing data so we can get more intelligent, more smart, and also provide that value, add back into the community and the service. So we felt that we weren't ready before because we needed to see multiple sets of years across multiple different types of data sets to be able to launch and release something like global insights. We started actually three years ago with a modern app report, because that was usage-based, not survey-based. And it's really interesting-- >> Real data. >> Because it's real data, right? But we were contemplating, even three years ago when we did the report, do we start to put out some of these benchmarks? And we felt that we were too early, because we needed more data, we needed different types of data from across different geographies, different types of usage, different technologies, and so we held off. And so that was one of the things that we've been paying very close attention to, and what the announcement today was all centered on is, yes, we've been talking about some insights around the industry, but you as the community of users here are helping us get smart and helping each other get smarter, and we're going to start to allow you guys to compare yourselves, back to your question, around, "Am I best in class from an operational KPI perspective?" And what does that mean? From utilization versus cost. And, "Am I best in class from a key risk perspective?" From a security perspective, for example. And how does that compare to others? And when you're staring the reality of that type of data in your face, it forces you to do something, take action. And the whole premise here is insights and intelligence. And so the more forthcoming, transparent we are with our customers in terms of these types of insights and intelligence, the more they're going to be using and adopting the platform, and hopefully, together as a community, getting smarter, more efficient. >> The graphic you showed, you get a whole bunch of green lights and one yellow light, all the eyes go right to... "What the heck, what's my yellow light?" Alright, I give you the last word on a word that you used again a number of times in your keynote, and that's trust. >> Yes. >> At the end of the day, that is such an important word in all types of relationships, but certainly in business relationships. Why're you putting the focus on that? Clearly it's important, you're highlighting trust. In fact I think you said, "We are your trusted steward for your data." Really important attribute for this company. >> Well that's been something early on, Jeff, in our architecture and things we did in terms of guaranteeing data sovereignty, privacy, encryption. We took no short change or shortcuts in terms of how we architect the service, eight-plus years ago. And we don't take any of those now. And the trust comment is because we have to trust, we have to build the trust and relationship, not just in terms of the value they're getting out of using the service, but that we're going to make sure that we keep their data safe and secure. Because we are PCI certified. We are also HIPAA certified, SOC type one, type two, we're doing GPR, all these other attestations and stuff that our customers have to face, we're also facing. So together, we're actually creating a trusted network, and that's the strategy here, is to create that trusted network. To share the insights. >> Well the passion comes through. And again, congratulations on the show, and the success, and we continue to enjoy watching the ride. >> Thank you very much for being part of it. It's great to be here with you. >> He's Ramin, I'm Jeff, you're watching theCUBE. We're at Sumo Logic Illuminate 2018. Thanks for watching. (inquisitive electronic music)

>> Announcer: Live from Las Vegas. It's theCube! Covering Dell Technologies World 2018. Brought to you by Dell EMC and it's ecosystem partners. >> Welcome back to theCube's coverage of Day One of Dell Technologies World. I'm Lisa Martin with Dave Vellante in Las Vegas. Excited to welcome back to theCube one of our alumni Chhandomay Mandal, the Director of Marketing at Dell EMC. Chhandomay, nice to see you again. >> Happy to be here. >> We had a exciting keynote this morning, Michael Dell was talking about number one in market share for servers and storage, expecting when the 2018 calendar numbers, came out the first quarter to gain shares. What's going on with storage with All-Flash? >> We are excited about our storage All-Flash portfolio. We are going to have a couple of surprising announcements tomorrow, I cannot give away all of this. But all of our portfolio is going to continue to innovate based on all the things Michael touched upon, ranging from artificial intelligence, machine learning, all of those things. We have a complete portfolio of All-Flash products covering different market segments, customers. Ranging from the Max All-Flash, XtremIO, Unity accessories. So we are really excited about the face of innovations we are doing, the way we are capturing a market. So it's a great time to be in All-Flash storage. >> Chhandomay, I wonder if we can talk about how we got here. So the first modern instantiation of Flash, and there were a lot of SSD's and battery backed up memories in the past, but it was, I think it was EMC, dropped a flash drive into a Symmetrix way back when, and that began to change things. But people soon realized, the controller architecture's not going to support that, so we need All-Flash architectures. And then people quickly realized, oh wow, it's taken us decades to build this rich stack of services. Now fast forward basically a decade plus, where are we today in terms of All-Flash capabilities and adoption? >> In the enterprises today, you see All-Flash getting adopted at a very high rate. In fact, of the storage that we ship, almost 80% of it is All-Flash storage, and again, We have different products for different segments. And as you mentioned, we started from dropping SSD's into the enterprise arrays, a whole thing through the process. Now if you look at us, we have modern purpose-built All-Flash arrays like XtremIO and then All-Flash arrays like VMAX All-Flash and some announcements where you are going to see the maturity level over the last decade, all the data services that got brought in, and the very high-performance, low latency with mission critical availability that we are able to deliver, across the platform for all of our enterprise products. >> So Flash everywhere. And then we've made the observation a lot that, and it sounds trite, but I'll put it out there anyways, historically, when you think about storage it was all about persisting data. And you'd try to make it go as fast as you could, but it was mechanical. Now with Flash, it's all about doing stuff faster, real-time, low latency, massive IOPS, we're shifting the bottlenecks around. What's your take on that dynamic? >> Flash is a fast media, so having great performance is really, it will stay. That is not really the differentiator so to speak, but it needs to be coupled with advanced data services. You need to have very high resiliency. The customers can rely on you with five lines, six lines of availability day in and day out. As well as, you need to do the business solutions, transforming IT, helping businesses transform in their digital transformation process. Let me give you some quick examples. Lets take XtremIO for example. It started out as a purposeful, modern, leading All-Flash array. And it is built upon a unique architecture taking the advantage of Flash Media. It is content error, metadata-centric, active-active controller architecture that helps us deliver very high performance hundreds of thousands to millions of IOPS with very low, consistent latency. No matter how much you have written to that, what loads you are running, what are the system load, etc. But again, that's the first layer. The second layer of it is the advanced data services always on inline reducing the data space. So for example, the inline, the duplication, compression, and making sure we are not writing the duplicate data to the SSD's. Thereby increasing the longevity of the SSD media, as well as reducing the capacity footprint. And driving down costs. Speaking of that. You wrap it around into a very simple, modern UI that's very easy to manage. No tuning needed. That's where today's IT could go from the tactical day to day operations to strategic innovations. How they can do the IT transformation. Get into the digital transformation. Get ahead of their competition. Not only today but for tomorrow. >> And the content awareness and the metadata-centricity are what you just explained? Is that right? Can you connect those? >> Uh sure. Suppose when the data is being written, right? It might have duplicate data. Say for example you are running a video environment. Right? For your tens of thousands of users everybody has their Windows VM. Probably the same data across all the laptops. When you look at it in the XtremIO metadata-centric, always in memory architecture, the request comes in, you try to look it up. Now when you need to do that your metadata is always in memory and you are doing data reduction based on a unique fingerprinting algorithm, checking whether you have seen the data before. If you haven't seen the data before then only you only write it doing other data services on top of it. But if you have seen the data before then you you update the metadata in memory and acknowledge the right. You get a very fast, alright performance that is actually at memory speed, not even at the SSD speed. So this metadata-centric architecture that has all the metadata all the time in memory helps you accelerate the process especially in the case where a lot of duplicate data is present. >> It's a memory speed? Because you somehow eliminated an IO? Or is that NVMe? Or, or..? >> When you access data, right? An application says I want to access block XYZ. Any controller will need to have the metadata for it. And then based on the metadata it needs to do the access. It's like, when you go to a library, you want to find a book from a bookshelf. First you need to know the control number. And then based one the control number, which shelf, which rack, you go and fetch it. Storage controllers of every type works in the same way. If you cannot have your metadata in memory, then the first step the controller has to do is go down to the array, fetch the metadata, and then based on the metadata you fetch the data and solve the IO request. If you have the metadata always in memory, then that step is always eliminated. You can guarantee that your metadata is there and all you need to do is look up and solve the IO request. That's the key of delivering consistent performance. Okay? In other arrays if the metadata is not in memory you'll not get that consistency. But here we can deliver day in, and day out, 90% full or 10% full, whether it's OLTP or VDI, That high performance with very minimal latency. That's the key here. >> High performance, low latency. You've given us some really good overview into the potential that the technology can make to help IT-innovate. And as Michael Dell even said this morning that IT innovation is key. IT can be a profit center of an organization, really as a catalyst for digital transformation. Talk to us about some of the business benefits. That if a business is really wrapping their head around IT as a profit center, and as a driver of business strategy. What are some of the business benefits that All-Flash array can deliver to an organization? Any examples come to mind? >> Yes, I'll answer your question with one of the customer examples. Let's see how they have been doing it. It's my favorite example of Boston Red Socks. I'm from the Boston area. >> You're a fan, right? >> Absolutely. All the Boston sports teams. When Boston Red Socks was in the digital transformation journey, they had to transform a lot of things. First of all, the experiences of the spectators like us, who are in the field living to the moment, whether it's the jumbotrons, or getting the experience digitally on the smartphones. That's one aspect. The other aspect is there are a lot of analytics on all the players across MLB. To get the competitive advantage in terms of, which pitch or which batter? Who has what capabilities or deficiencies that they can go after the right player or when they are against them, how to take advantage of them. And then there are a lot of the business applications in a virtualized environment. As you look, ranging from better spectator experience, ranging to the coaches getting competitive advantage from the opposing players or the scouting department. And running the general back office applications, like Exchange and (mumbling), whatever need might be. Now they were able to consolidate all of these things into the XtremIO All-Flash array platform. And the ability to deliver this performance as well as getting a data reduction of almost seven is to one, was a key for Red Socks' digital transformation journey. >> So the business impact to Lisa's point is lower cost obviously, simpler management. But also faster time to result? How did they turn that into a competitive advantage? >> If they could run... Those analytics previously used to take ten hours. Now they can do it in two hours. That's an 80% faster turnaround time. Right? Previously if they could support 10,000 spectators on one particular wireless network. Now they have 80,000. It's the experience that's transformative for folks who are enjoying the game. It's the number of applications they are running. It's how they are running. They're viewing IT as a strategic investment. As opposed to something that's needed to run the operations. >> Well baseball games are like five hours now, cause you can even do an in game at that speed. How 'about the data services? When Flash first came out, All-Flash architectures they were not very rich in terms of data services. That's evolved. I mean the industry in general, and Dell EMC specifically, has put a lot of effort into that. Maybe you could describe some of the data. What do we mean by data services? Let's talk about copy services, migration services, snapshotting, etc. What are the important ones that we should know about? >> The important data services are thin provisioning, the data reduction technologies, the duplication, compression. Then you have your data protection in forms of various types of array technologies. The most important one I'll put out as how matter your snapshot surfaces, as well as what you can do for your data protection, business continuity, disaster recovery. Those are very critical for any businesses that needs to rely upon having their systems up and running 365 days 24 seven. Having those type of data surfaces is a key. And not only having, but also having a maturity. For example, taking VMAX All-Flash in this particular case, right? It's upon two (mumbling) of reliability, where SRDF is the gold standard in industry, in terms of resiliency, right? Six-ninths of ability. Those... Somebody coming up with brand new array on Day One cannot have it. We have seen that evolution with folks who originally had very fast storage. But then there was no data services. Right? It's the evolution of having the performance as well as the right data surfaces. That helps the customer transform their journey, both in terms of modernizing the IT infrastructure, as well as having the digital transformation to be competitive today and tomorrow. >> And the positioning of XtremIO, just to clarify for our audience, cause you got All-Flash VMAX, you got XtremIO. It's really... It's the high end of the midrange. Is that how we should think about that? >> We have a lot of... As you said the IMAX All-Flash, XtremIO, they're all important, and effectively we have the portfolio because with one product you cannot solve each and every customer needs. So picking on your very specific example, XtremIO is great for mixed workload consolidation, virtualized applications, VDI, as well as situations where you have lots of copies. So for example, you have a database, you need to create (mumbling) copies. You have copies for your backup, sandboxing. In these type of scenarios XtremIO is extremely good. And kind of like is the sweet spot. We are going to... We are having new XtremIO X-Bricks that are even lower priced point than the previous generation. Literally 55% better price entry point. Now this enterprise plus capabilities of XtremIO will be also available in the mid-market, at the mid-range price. >> Well Chhandomay, thanks so much for stopping by, and not only expanding on the customer awards that we saw this morning, by sharing with us the impact that the Boston Red Socks were making. But also sharing with us what's new with XtremIO and All-Flash. >> Thank you. >> And speaking between two Bostonians... >> Big night tonight. You got Bruins. We got Celtics. Red Socks take a back seat for awhile. But they'll be back. >> We want to thank you for watching theCUBE. We are live at Day One of Dell Technologies World. I'm Lisa Martin with Dave Vellante. Thanks for watching. Stick around, we'll be right back after a short break.

>> Voiceover: Live from Las Vegas, it's theCUBE, covering AWS re:Invent 2017. Presented by AWS, Intel, and our ecosystem of partners. >> Hey, hello everyone. Welcome back to day two of live coverage as theCUBE's exclusive analysis coverage of AWS re:Invent 2017. I'm John Furrier, co-host on set one with Stu Miniman here, analyst at Wikibon. And we got two sets here at Amazon re:Invent The first time we've done two sets, so much content. We have our directors' set with captains' chairs over there getting all the community content. And all the folks doing the innovation here at AWS. Stu, a lot to talk about. We've had companies come through, tell us about their innovation with AWS. But the bottom line is Andy Jassy's keynote just went off. I mean, he's like the energizer bunny. He keeps going and going and going. Announcement after announcement. I broke that Forbes story, laid out what ended up turning out to be the core messaging. Tons of stories on SiliconANGLE.com around Andy Jassy's exclusive interview that we had about a week and a half ago, prior to re:Invent. He's geared up. He's giddy up, as they say, his favorite word. He's taken on the competition. He took Oracle head on and called Oracle a company that abuses their customers. That was hard core, "abuse." He used the word, "abuse." In this culture, he could have just said, "predator." He's that kind of competitive vibe. Microsoft kind of called out Vinder 2 on the chart. Laying out the sets and services. Amazon putting the aggressive we're real stamp out there. What's your thoughts? You got the only analysis. >> So first of all John, this show is always impressive. One of the ones that I look forward to more than almost anything for the entire year. 43,000 people here. I spent the last day and a half in the analyst sessions. There wasn't a single analyst that was like, "Ho-hum." There are so many announcements. You go down the list and the number 73rd announcement on there, you're like, "I'm not sure." "There's this group of customers that's been waiting "for them and is going to transform their business. "It's potentially going to crush certain parts "of the industry." There's so much happening, there's lots of fanboys here. It's tough not to get exuberant about what's going on. Surprised to see Andy punching a little bit of competitors. Sure, he takes jabs at Larry Ellison every year. You know the red stack stuff, you know database. They're making huge piece on the migration. But talking a little bit more about Google and Microsoft, "Well they must be real competitors," a lot of people are saying, "if they're actually putting them up there, "going through the numbers," so many things we want to dig into here, and throughout the next two days. >> Yeah man, and the fact that he talks about the competitors means that it's still on his mind, although they're still full steam ahead. The thing about Jassy though, getting to know him, his style is not just talk, he walks it more than he talks. He'll only talk trash if he's got a solution in his back pocket. And what's different this year is, the bravado has gone up and the rhetoric around Oracle specifically has been really hard core. I mean he called them an abusive partner to their customers. That's a line in the sand. Those are fightin' words but then he goes on stage and essentially rolls out a series of database options. He spent a lot of time talking about databases, Stu, in his keynote. >> John, we got Aurora Serverless totally talking about, "How many companies, how many resources do you have focused "on managing the infrastructure under your database?" So, RDMS, paired with Serverless, absolutely game changer. People are super excited about it. There's so much going on. But I mean, John just take alone, the one thing they put up, it was one of the Gartner slides, and what's Amazon at now, 44% up from 39%? So there's talk about growth rates and everything like that. Amazon chugging along, dominant in their space, and so many pieces. >> That's the one critique I would give Jassy, the one thing I don't like about his keynote, and I don't like in general about Amazon is, they talk new guard, new guard, old guard is bad. They're using Gartner slides, too. I mean, you couldn't old guard then Gartner. Magic Quadrant has nothing to do with the presentation. It was infrastructures of service, didn't include platform as a service, didn't include SAS. I mean, they're using the wrong scoreboard. Now, I think he throws it up there because buyers kinda use Gartner as kind of a bellwether but they're not, they're old guard. He's got to get better stats and I'm pressuring them to get the stats. What is the scoreboard for cloud? >> Well, john, you know one of the things we always look at, there's two days of keynotes. Today is really the enterprise. Enterprise, Andy says, we're in kind of the early part of massive adoption from enterprise. He's talking enterprise-speak and yeah, they go to the Gartner Magic Quadrant, absolutely. John, what's happening in the software world? I mean, that's really where this is is the change of what's happening in the software. Amazon's at the vanguard. There was plenty of things that I'm sure developers will love here, but it wasn't the big focus of today's keynotes. >> To me, the canary in the coalmine is developers. The canary in the coalmine for the big mega trans are also venture capitalists. The canary in the coalmine of the startup entrepreneurs, those alpha entrepreneurs and last night we had a chance. I sat down multiple one on ones with some venture capitalists. We had some here on theCUBE, then we went to the Greylock, Amplify, and then IVP party and haD a chance to talk to some people. The general sentiment is this, we are in a sea change. It's like a tsunami. The whole beach is exposed before the big wave comes in, Stu. The top venture capitalists like Greylock and others, are looking at this going, "the models have changed." The funding model, the dynamics and everyone is going, "holy shit." That's where this renaissance in software development is happening and the top guys on the entrepreneurial side is saying, "the new way to do it is, "take less funding, I need to get in market fast "with a product, I need a partner that's gonna get me." The rest of the market is deer in the headlights, Stu. They're like, "wait a minute, do I compete with Amazon? "Do I partner with Amazon? "Which could do I use?" They get caught rearranging the deck chairs and they're taking their eye off the ball which is software. >> So john, the struggle I've been hearing, you know, you talked to a bunch of Amazon customers already this week. If you're in the enterprise and you're building your strategy, you got to write it on a whiteboard or an etch-a-sketch because things are changing so fast. The thing I was really looking forward to is what were they gonna be in cubernetties and you know, server list, huge promise, what are they delivering? What was the proof point? And I have to say, definitely impressed with what I saw so far. >> What's the top? I mean first of all, you're in the analyst meeting and I heard feedback from the analysts like, "we can't even comprehend all these things." I want you to boil it down for the folks not here and they're gonna be reading some blog posts and still getting a lot of coverage to go through certainly on theCube and SiliconANGLE will keep on. Bottom line, what's the executive summary in your mind, Stu? What should people pay attention to? What's the most important story? >> It is impossible to give one story to everyone but let me start with, Andy lays out, in your interview for Forbes and what he talked about in the keynote, kind of a compute continuum so if you're just using compute instances, there are some new big ones. If you want your AI stuff, your big data, they've got new compute instances. The bare middle offering is basically the fruits of what they have to do to be able to get vmware on AWS to work and they're now making that same instance available for those that want to be able to do other things with it, bring their own hypervisor, things like that. I could tell you, it's a massive... It's like 72 logical cores, huge amounts of memory and it is gonna be wicked expensive because it's not like most of the instances with Amazon, pick between these six versions, it's one. Here's a server and it's a big server, it's gonna be really expensive. We're gonna be digging in with a couple of vmware executives on that piece but the newer stuff, containers. The last year we've been hearing, Amazon's behind on cubernetties, Amazon's behind on cubernetties. They joined the CNCF for a couple months. Now they have EKS so full supporting cubernetties but here's the nuance, I talked to the people that run that group and ECS is not going away. They're there, we've seen all the time is they say, "oh here's the standard and we're gonna fully embrace it, "but our proprietary's version." Cubernetties doesn't scale the way you need, you gotta do our thing. Cubernetties, we can't integrate it with all our services, you know use our services. Andy was like, "hey, we're gonna give you a choice." Underneath that they had farpoint, I'm sorry fargate. Fargate is the underlying level that basically allows me to take rather than, you know, managing at the server level which really I was managing virtualization before. Now I'm managing at the compute level. When containers came out and Docker was buzzing, it was, "this is the new atomic instance "of how we manage things." Fargate really cooled down at that lower level so you have (mumbles) I keep saying fargate at the bottom level, now I've got ECS or cubernetties and I've got things like istio on top of that. You and I are gonna be at the CNCF show next week, CubeCon and everything like that. I'm sure Amazon is gonna suck a lot of the air out of that with what they're doing and gosh, I haven't even talked about serverless yet. >> First of all I mean, it's hard to boil it down like you said. You can't even breathe at this point, it's so exciting but the thing that is a success at Amazon also could be an Achilles heel because it has complexity so I noticed in messaging was everything to everyone or is everything to everything. It's got this vibe going on... >> Stu: Everything is everything. >> Everything is everything. A lot of people have been criticizing the software business on the community side, supplier side of trying to be everything to everyone. But that's what Amazon's doing, right? They're basically saying, "we're gonna give you everything "but it's not mandated that you choose one." So talk about that dynamic because the people critiquing them and saying, "well they're just throwing all this stuff out there, "it's just a feature." Is it viable? >> It's a great point and right, if you look at traditional enterprise vendors, it was, "oh my god look at that catalog "and all these thousands and thousands of skews "that are out there." I believe the number I heard is in the Amazon services, there's like 30,000 services out there and how do you, as a company, manage that? I talked to one global web company and I gave that. How do you keep up with this? How do you know what to do? And he's like, "well, we reach a certain price point. "I've got two TAMs, they help us work through this." There's no way any one person or even any company could be an expert on this. That's where Amazon needs to get consultative. That's where SIs need to come in. I'll tee up, that's where serverless really comes in because there's certain pieces that, as Andy talked about in the keynote, you know lambda is going everywhere. It's getting integrated into the environment. There's certain pieces of the stack that before I needed to choose my compute instance. I needed to figure out how much memory. I have to do all of these kind of things. If I choose a certain layer of integration, Amazon is gonna take care of those things underneath so absolutely they hear loud and clear that they want to simplify things. What was it, last year light sale was one of the big announcements. There's so many things. Spot instances had a huge growth to be able to drive down costs this year. I mean, dozens and dozens of features that Andy talked about this morning. Serverless, John, really massive wave. (mumbles) >> Let's connect the dots. There's a lot to talk about, we've got Werner Vogles keynote tomorrow. That should be really geeky and tech under the hood, but what Jassy is putting out there is a lot of the stuff you're mentioning but also he's got a wireless camera for facial recognition, they've got transcribe recognition, poly, lex, so the sets of services that are new and new guard like and the use cases from this are interesting. A lot of different connective devices so you see a little IOG. They're kind of laying out like this is a landscape. You know, we're gonna do statcast for MLB, NFL. We got edge devices, databases for S3. The programming model, the new assembly model. It's very modular. This is like the building blocks approach. It's not just the lambda and S3. You've got wireless cameras that do facial recognition. >> Right, because John, I talked to a couple customers that are doing serverless and they're working with Amazon and it's like, "oh well, where do you think of serverless functions as a service?" And they're like, "well really I have you know..." One customer was like, "I have a bunch of my own services "and I have APIs I write and now I can just call into "various Amazon services so it makes..." John, the whole API economy that we've been talking about for many years, you know, this is really Amazon having this come to fruition. I should be able to write my own APIs that can program to many of Amazon's APIs. If Dave Vellante was here, I'm sure he'd be talking about API creep because there's so many pieces but you know, Amazon, Andy is saying, "we have everything of the best." I think a lot of he's trying to attack there. Many customers we've talked to, they're going multi-cloud. What does that really mean? It's Amazon the primary. When are they using Google, Microsoft, Oracle, IBM? There's so many pieces. >> Stu, it's impressive to me. I get called a fanboy all the time, but I just call it as I see it and Amazon is crushing everyone else, in my opinion. There's no doubt about it. When we get more data from Microsoft or Google, then we'll compare, you know, and Oracle. They're not even talking so like they're hiding. They're building again. The tsunami is coming. The war is here. No doubt there's a cloud war and Microsoft is in it to win it. Google's hardcore so this is game on. What Amazon is doing is they're integrating new kinds of interactivity. You start to see Twitch more here. You see the NFL demo on stage that Andy did. The actual data that they're getting from the sensors. They're integrating the application so you know Goldman Sachs never goes on stage and does a testimonial. The guy's basically giving a lovefest for Amazon. That's Goldman Sachs. So you have new software models that are coming. This is something I think nobody's seeing. I think you talk to hardcore dudes. The infrastructures now with serverless is enabling creativity and I think this renaissance is for real. >> John, you nailed something. It's Sandy Carter who you know and have had on theCUBE many times, joined Amazon within the last year, talked about how Amazon, not just AWS but Amazon, is helping customers with buzzword digital transformation but how do you innovate? It's not just Amazon Web Services, there's so many things that the broader Amazon portfolio can tie into, you know. Absolutely, it's impressive. Customers always said it used to be like, "oh how can I have a network that's kinda like Google's?" Now it's "how can I innovate like Amazon?" >> Well Stu, we go to all the shows. We didn't go to Oracle Open World this year. Again, they're kind of silent right now because they don't want to talk to the press because they're gearing up. You've got Oracle, Microsoft, certainly very aggressive, more aggressive than Oracle, but Jassy is laying the line in the sand so we're gonna watch the new guard old guard thing play out. Microsoft is absolutely moving the needle. They are coming up to Amazon. There's no doubt that they're in the sights, in the rearview mirror. I think everyone else is really gearing up. You've got Alibaba cloud in China coming to the US. This is going to be exciting. The cloud game has got so much action in it. It's got the geeky under the hood and the sexiness of the application, Stu. I'm really super excited. >> Yeah, there's just so much information, you know. Choose your category. Choose where you're going. There is just no shortage. Everybody is geeking out. The big complaint is like how there's too many people. If you go standby, you go an hour ahead of time and you're still there and it's spread out, you know. The Aria and the MGM, there's all these things there. We're here at the heart of what used to be the one facility and now it's just spread out so much so you really need to kind of choose your focus, dig on in, and you know, we've got so many interviews. >> Stu, we're gonna want to wrap this up by saying the company that's behind us, you can't see or maybe you're able to see in the shot that's winning that no one's talking about much because they're just winning is Intel. They sell more chips. They sell more compute. The compute game is where it's at. You've just Intel kind of quietly under the surface and this growth is only gonna help Moore's law and everything else. >> John, it's just like the old Intel inside, you know. Amazon does more. They're buying more compute, whether that's standard compute, it's containers, or serverless at the end of the day, there's some Intel chips underneath almost all of it today. >> Intel's not putting their strategy up but it's clear to me through observation and talking to them, is that they're targeting the cloud as that new inside moment. They want to power the top clouds. They already are. They're kinda quietly keeping their nose clean and have their head down and power all those clouds. TheCUBE here powering all the data here at AWS re:Invent. I'm John Furrier, Stu Miniman. Day two kickoff, more great coverage. Stay with us, two sets here in Las Vegas. We'll be right back. (digital music)

>> There's a movement that's sweeping across businesses everywhere here in this country and around the world. And it's all about data. Today businesses are being inundated with data. To the tune of over two and a half million gigabytes that'll be generated in the next 60 seconds alone. What do you do with all that data? To extract insights you typically turn to a data scientist. But not necessarily anymore. At least not exclusively. Today the ability to extract value from data is becoming a shared mission. A team effort that spans the organization extending far more widely than ever before. Today, data science is being democratized. >> Data Sciences for All: It's a Whole New Game. >> Welcome everyone, I'm Katie Linendoll. I'm a technology expert writer and I love reporting on all things tech. My fascination with tech started very young. I began coding when I was 12. Received my networking certs by 18 and a degree in IT and new media from Rochester Institute of Technology. So as you can tell, technology has always been a sure passion of mine. Having grown up in the digital age, I love having a career that keeps me at the forefront of science and technology innovations. I spend equal time in the field being hands on as I do on my laptop conducting in depth research. Whether I'm diving underwater with NASA astronauts, witnessing the new ways which mobile technology can help rebuild the Philippine's economy in the wake of super typhoons, or sharing a first look at the newest iPhones on The Today Show, yesterday, I'm always on the hunt for the latest and greatest tech stories. And that's what brought me here. I'll be your host for the next hour and as we explore the new phenomenon that is taking businesses around the world by storm. And data science continues to become democratized and extends beyond the domain of the data scientist. And why there's also a mandate for all of us to become data literate. Now that data science for all drives our AI culture. And we're going to be able to take to the streets and go behind the scenes as we uncover the factors that are fueling this phenomenon and giving rise to a movement that is reshaping how businesses leverage data. And putting organizations on the road to AI. So coming up, I'll be doing interviews with data scientists. We'll see real world demos and take a look at how IBM is changing the game with an open data science platform. We'll also be joined by legendary statistician Nate Silver, founder and editor-in-chief of FiveThirtyEight. Who will shed light on how a data driven mindset is changing everything from business to our culture. We also have a few people who are joining us in our studio, so thank you guys for joining us. Come on, I can do better than that, right? Live studio audience, the fun stuff. And for all of you during the program, I want to remind you to join that conversation on social media using the hashtag DSforAll, it's data science for all. Share your thoughts on what data science and AI means to you and your business. And, let's dive into a whole new game of data science. Now I'd like to welcome my co-host General Manager IBM Analytics, Rob Thomas. >> Hello, Katie. >> Come on guys. >> Yeah, seriously. >> No one's allowed to be quiet during this show, okay? >> Right. >> Or, I'll start calling people out. So Rob, thank you so much. I think you know this conversation, we're calling it a data explosion happening right now. And it's nothing new. And when you and I chatted about it. You've been talking about this for years. You have to ask, is this old news at this point? >> Yeah, I mean, well first of all, the data explosion is not coming, it's here. And everybody's in the middle of it right now. What is different is the economics have changed. And the scale and complexity of the data that organizations are having to deal with has changed. And to this day, 80% of the data in the world still sits behind corporate firewalls. So, that's becoming a problem. It's becoming unmanageable. IT struggles to manage it. The business can't get everything they need. Consumers can't consume it when they want. So we have a challenge here. >> It's challenging in the world of unmanageable. Crazy complexity. If I'm sitting here as an IT manager of my business, I'm probably thinking to myself, this is incredibly frustrating. How in the world am I going to get control of all this data? And probably not just me thinking it. Many individuals here as well. >> Yeah, indeed. Everybody's thinking about how am I going to put data to work in my organization in a way I haven't done before. Look, you've got to have the right expertise, the right tools. The other thing that's happening in the market right now is clients are dealing with multi cloud environments. So data behind the firewall in private cloud, multiple public clouds. And they have to find a way. How am I going to pull meaning out of this data? And that brings us to data science and AI. That's how you get there. >> I understand the data science part but I think we're all starting to hear more about AI. And it's incredible that this buzz word is happening. How do businesses adopt to this AI growth and boom and trend that's happening in this world right now? >> Well, let me define it this way. Data science is a discipline. And machine learning is one technique. And then AI puts both machine learning into practice and applies it to the business. So this is really about how getting your business where it needs to go. And to get to an AI future, you have to lay a data foundation today. I love the phrase, "there's no AI without IA." That means you're not going to get to AI unless you have the right information architecture to start with. >> Can you elaborate though in terms of how businesses can really adopt AI and get started. >> Look, I think there's four things you have to do if you're serious about AI. One is you need a strategy for data acquisition. Two is you need a modern data architecture. Three is you need pervasive automation. And four is you got to expand job roles in the organization. >> Data acquisition. First pillar in this you just discussed. Can we start there and explain why it's so critical in this process? >> Yeah, so let's think about how data acquisition has evolved through the years. 15 years ago, data acquisition was about how do I get data in and out of my ERP system? And that was pretty much solved. Then the mobile revolution happens. And suddenly you've got structured and non-structured data. More than you've ever dealt with. And now you get to where we are today. You're talking terabytes, petabytes of data. >> [Katie] Yottabytes, I heard that word the other day. >> I heard that too. >> Didn't even know what it meant. >> You know how many zeros that is? >> I thought we were in Star Wars. >> Yeah, I think it's a lot of zeroes. >> Yodabytes, it's new. >> So, it's becoming more and more complex in terms of how you acquire data. So that's the new data landscape that every client is dealing with. And if you don't have a strategy for how you acquire that and manage it, you're not going to get to that AI future. >> So a natural segue, if you are one of these businesses, how do you build for the data landscape? >> Yeah, so the question I always hear from customers is we need to evolve our data architecture to be ready for AI. And the way I think about that is it's really about moving from static data repositories to more of a fluid data layer. >> And we continue with the architecture. New data architecture is an interesting buzz word to hear. But it's also one of the four pillars. So if you could dive in there. >> Yeah, I mean it's a new twist on what I would call some core data science concepts. For example, you have to leverage tools with a modern, centralized data warehouse. But your data warehouse can't be stagnant to just what's right there. So you need a way to federate data across different environments. You need to be able to bring your analytics to the data because it's most efficient that way. And ultimately, it's about building an optimized data platform that is designed for data science and AI. Which means it has to be a lot more flexible than what clients have had in the past. >> All right. So we've laid out what you need for driving automation. But where does the machine learning kick in? >> Machine learning is what gives you the ability to automate tasks. And I think about machine learning. It's about predicting and automating. And this will really change the roles of data professionals and IT professionals. For example, a data scientist cannot possibly know every algorithm or every model that they could use. So we can automate the process of algorithm selection. Another example is things like automated data matching. Or metadata creation. Some of these things may not be exciting but they're hugely practical. And so when you think about the real use cases that are driving return on investment today, it's things like that. It's automating the mundane tasks. >> Let's go ahead and come back to something that you mentioned earlier because it's fascinating to be talking about this AI journey, but also significant is the new job roles. And what are those other participants in the analytics pipeline? >> Yeah I think we're just at the start of this idea of new job roles. We have data scientists. We have data engineers. Now you see machine learning engineers. Application developers. What's really happening is that data scientists are no longer allowed to work in their own silo. And so the new job roles is about how does everybody have data first in their mind? And then they're using tools to automate data science, to automate building machine learning into applications. So roles are going to change dramatically in organizations. >> I think that's confusing though because we have several organizations who saying is that highly specialized roles, just for data science? Or is it applicable to everybody across the board? >> Yeah, and that's the big question, right? Cause everybody's thinking how will this apply? Do I want this to be just a small set of people in the organization that will do this? But, our view is data science has to for everybody. It's about bring data science to everybody as a shared mission across the organization. Everybody in the company has to be data literate. And participate in this journey. >> So overall, group effort, has to be a common goal, and we all need to be data literate across the board. >> Absolutely. >> Done deal. But at the end of the day, it's kind of not an easy task. >> It's not. It's not easy but it's maybe not as big of a shift as you would think. Because you have to put data in the hands of people that can do something with it. So, it's very basic. Give access to data. Data's often locked up in a lot of organizations today. Give people the right tools. Embrace the idea of choice or diversity in terms of those tools. That gets you started on this path. >> It's interesting to hear you say essentially you need to train everyone though across the board when it comes to data literacy. And I think people that are coming into the work force don't necessarily have a background or a degree in data science. So how do you manage? >> Yeah, so in many cases that's true. I will tell you some universities are doing amazing work here. One example, University of California Berkeley. They offer a course for all majors. So no matter what you're majoring in, you have a course on foundations of data science. How do you bring data science to every role? So it's starting to happen. We at IBM provide data science courses through CognitiveClass.ai. It's for everybody. It's free. And look, if you want to get your hands on code and just dive right in, you go to datascience.ibm.com. The key point is this though. It's more about attitude than it is aptitude. I think anybody can figure this out. But it's about the attitude to say we're putting data first and we're going to figure out how to make this real in our organization. >> I also have to give a shout out to my alma mater because I have heard that there is an offering in MS in data analytics. And they are always on the forefront of new technologies and new majors and on trend. And I've heard that the placement behind those jobs, people graduating with the MS is high. >> I'm sure it's very high. >> So go Tigers. All right, tangential. Let me get back to something else you touched on earlier because you mentioned that a number of customers ask you how in the world do I get started with AI? It's an overwhelming question. Where do you even begin? What do you tell them? >> Yeah, well things are moving really fast. But the good thing is most organizations I see, they're already on the path, even if they don't know it. They might have a BI practice in place. They've got data warehouses. They've got data lakes. Let me give you an example. AMC Networks. They produce a lot of the shows that I'm sure you watch Katie. >> [Katie] Yes, Breaking Bad, Walking Dead, any fans? >> [Rob] Yeah, we've got a few. >> [Katie] Well you taught me something I didn't even know. Because it's amazing how we have all these different industries, but yet media in itself is impacted too. And this is a good example. >> Absolutely. So, AMC Networks, think about it. They've got ads to place. They want to track viewer behavior. What do people like? What do they dislike? So they have to optimize every aspect of their business from marketing campaigns to promotions to scheduling to ads. And their goal was transform data into business insights and really take the burden off of their IT team that was heavily burdened by obviously a huge increase in data. So their VP of BI took the approach of using machine learning to process large volumes of data. They used a platform that was designed for AI and data processing. It's the IBM analytics system where it's a data warehouse, data science tools are built in. It has in memory data processing. And just like that, they were ready for AI. And they're already seeing that impact in their business. >> Do you think a movement of that nature kind of presses other media conglomerates and organizations to say we need to be doing this too? >> I think it's inevitable that everybody, you're either going to be playing, you're either going to be leading, or you'll be playing catch up. And so, as we talk to clients we think about how do you start down this path now, even if you have to iterate over time? Because otherwise you're going to wake up and you're going to be behind. >> One thing worth noting is we've talked about analytics to the data. It's analytics first to the data, not the other way around. >> Right. So, look. We as a practice, we say you want to bring data to where the data sits. Because it's a lot more efficient that way. It gets you better outcomes in terms of how you train models and it's more efficient. And we think that leads to better outcomes. Other organization will say, "Hey move the data around." And everything becomes a big data movement exercise. But once an organization has started down this path, they're starting to get predictions, they want to do it where it's really easy. And that means analytics applied right where the data sits. >> And worth talking about the role of the data scientist in all of this. It's been called the hot job of the decade. And a Harvard Business Review even dubbed it the sexiest job of the 21st century. >> Yes. >> I want to see this on the cover of Vogue. Like I want to see the first data scientist. Female preferred, on the cover of Vogue. That would be amazing. >> Perhaps you can. >> People agree. So what changes for them? Is this challenging in terms of we talk data science for all. Where do all the data science, is it data science for everyone? And how does it change everything? >> Well, I think of it this way. AI gives software super powers. It really does. It changes the nature of software. And at the center of that is data scientists. So, a data scientist has a set of powers that they've never had before in any organization. And that's why it's a hot profession. Now, on one hand, this has been around for a while. We've had actuaries. We've had statisticians that have really transformed industries. But there are a few things that are new now. We have new tools. New languages. Broader recognition of this need. And while it's important to recognize this critical skill set, you can't just limit it to a few people. This is about scaling it across the organization. And truly making it accessible to all. >> So then do we need more data scientists? Or is this something you train like you said, across the board? >> Well, I think you want to do a little bit of both. We want more. But, we can also train more and make the ones we have more productive. The way I think about it is there's kind of two markets here. And we call it clickers and coders. >> [Katie] I like that. That's good. >> So, let's talk about what that means. So clickers are basically somebody that wants to use tools. Create models visually. It's drag and drop. Something that's very intuitive. Those are the clickers. Nothing wrong with that. It's been valuable for years. There's a new crop of data scientists. They want to code. They want to build with the latest open source tools. They want to write in Python or R. These are the coders. And both approaches are viable. Both approaches are critical. Organizations have to have a way to meet the needs of both of those types. And there's not a lot of things available today that do that. >> Well let's keep going on that. Because I hear you talking about the data scientists role and how it's critical to success, but with the new tools, data science and analytics skills can extend beyond the domain of just the data scientist. >> That's right. So look, we're unifying coders and clickers into a single platform, which we call IBM Data Science Experience. And as the demand for data science expertise grows, so does the need for these kind of tools. To bring them into the same environment. And my view is if you have the right platform, it enables the organization to collaborate. And suddenly you've changed the nature of data science from an individual sport to a team sport. >> So as somebody that, my background is in IT, the question is really is this an additional piece of what IT needs to do in 2017 and beyond? Or is it just another line item to the budget? >> So I'm afraid that some people might view it that way. As just another line item. But, I would challenge that and say data science is going to reinvent IT. It's going to change the nature of IT. And every organization needs to think about what are the skills that are critical? How do we engage a broader team to do this? Because once they get there, this is the chance to reinvent how they're performing IT. >> [Katie] Challenging or not? >> Look it's all a big challenge. Think about everything IT organizations have been through. Some of them were late to things like mobile, but then they caught up. Some were late to cloud, but then they caught up. I would just urge people, don't be late to data science. Use this as your chance to reinvent IT. Start with this notion of clickers and coders. This is a seminal moment. Much like mobile and cloud was. So don't be late. >> And I think it's critical because it could be so costly to wait. And Rob and I were even chatting earlier how data analytics is just moving into all different kinds of industries. And I can tell you even personally being effected by how important the analysis is in working in pediatric cancer for the last seven years. I personally implement virtual reality headsets to pediatric cancer hospitals across the country. And it's great. And it's working phenomenally. And the kids are amazed. And the staff is amazed. But the phase two of this project is putting in little metrics in the hardware that gather the breathing, the heart rate to show that we have data. Proof that we can hand over to the hospitals to continue making this program a success. So just in-- >> That's a great example. >> An interesting example. >> Saving lives? >> Yes. >> That's also applying a lot of what we talked about. >> Exciting stuff in the world of data science. >> Yes. Look, I just add this is an existential moment for every organization. Because what you do in this area is probably going to define how competitive you are going forward. And think about if you don't do something. What if one of your competitors goes and creates an application that's more engaging with clients? So my recommendation is start small. Experiment. Learn. Iterate on projects. Define the business outcomes. Then scale up. It's very doable. But you've got to take the first step. >> First step always critical. And now we're going to get to the fun hands on part of our story. Because in just a moment we're going to take a closer look at what data science can deliver. And where organizations are trying to get to. All right. Thank you Rob and now we've been joined by Siva Anne who is going to help us navigate this demo. First, welcome Siva. Give him a big round of applause. Yeah. All right, Rob break down what we're going to be looking at. You take over this demo. >> All right. So this is going to be pretty interesting. So Siva is going to take us through. So he's going to play the role of a financial adviser. Who wants to help better serve clients through recommendations. And I'm going to really illustrate three things. One is how do you federate data from multiple data sources? Inside the firewall, outside the firewall. How do you apply machine learning to predict and to automate? And then how do you move analytics closer to your data? So, what you're seeing here is a custom application for an investment firm. So, Siva, our financial adviser, welcome. So you can see at the top, we've got market data. We pulled that from an external source. And then we've got Siva's calendar in the middle. He's got clients on the right side. So page down, what else do you see down there Siva? >> [Siva] I can see the recent market news. And in here I can see that JP Morgan is calling for a US dollar rebound in the second half of the year. And, I have upcoming meeting with Leo Rakes. I can get-- >> [Rob] So let's go in there. Why don't you click on Leo Rakes. So, you're sitting at your desk, you're deciding how you're going to spend the day. You know you have a meeting with Leo. So you click on it. You immediately see, all right, so what do we know about him? We've got data governance implemented. So we know his age, we know his degree. We can see he's not that aggressive of a trader. Only six trades in the last few years. But then where it gets interesting is you go to the bottom. You start to see predicted industry affinity. Where did that come from? How do we have that? >> [Siva] So these green lines and red arrows here indicate the trending affinity of Leo Rakes for particular industry stocks. What we've done here is we've built machine learning models using customer's demographic data, his stock portfolios, and browsing behavior to build a model which can predict his affinity for a particular industry. >> [Rob] Interesting. So, I like to think of this, we call it celebrity experiences. So how do you treat every customer like they're a celebrity? So to some extent, we're reading his mind. Because without asking him, we know that he's going to have an affinity for auto stocks. So we go down. Now we look at his portfolio. You can see okay, he's got some different holdings. He's got Amazon, Google, Apple, and then he's got RACE, which is the ticker for Ferrari. You can see that's done incredibly well. And so, as a financial adviser, you look at this and you say, all right, we know he loves auto stocks. Ferrari's done very well. Let's create a hedge. Like what kind of security would interest him as a hedge against his position for Ferrari? Could we go figure that out? >> [Siva] Yes. Given I know that he's gotten an affinity for auto stocks, and I also see that Ferrari has got some terminus gains, I want to lock in these gains by hedging. And I want to do that by picking a auto stock which has got negative correlation with Ferrari. >> [Rob] So this is where we get to the idea of in database analytics. Cause you start clicking that and immediately we're getting instant answers of what's happening. So what did we find here? We're going to compare Ferrari and Honda. >> [Siva] I'm going to compare Ferrari with Honda. And what I see here instantly is that Honda has got a negative correlation with Ferrari, which makes it a perfect mix for his stock portfolio. Given he has an affinity for auto stocks and it correlates negatively with Ferrari. >> [Rob] These are very powerful tools at the hand of a financial adviser. You think about it. As a financial adviser, you wouldn't think about federating data, machine learning, pretty powerful. >> [Siva] Yes. So what we have seen here is that using the common SQL engine, we've been able to federate queries across multiple data sources. Db2 Warehouse in the cloud, IBM's Integrated Analytic System, and Hortonworks powered Hadoop platform for the new speeds. We've been able to use machine learning to derive innovative insights about his stock affinities. And drive the machine learning into the appliance. Closer to where the data resides to deliver high performance analytics. >> [Rob] At scale? >> [Siva] We're able to run millions of these correlations across stocks, currency, other factors. And even score hundreds of customers for their affinities on a daily basis. >> That's great. Siva, thank you for playing the role of financial adviser. So I just want to recap briefly. Cause this really powerful technology that's really simple. So we federated, we aggregated multiple data sources from all over the web and internal systems. And public cloud systems. Machine learning models were built that predicted Leo's affinity for a certain industry. In this case, automotive. And then you see when you deploy analytics next to your data, even a financial adviser, just with the click of a button is getting instant answers so they can go be more productive in their next meeting. This whole idea of celebrity experiences for your customer, that's available for everybody, if you take advantage of these types of capabilities. Katie, I'll hand it back to you. >> Good stuff. Thank you Rob. Thank you Siva. Powerful demonstration on what we've been talking about all afternoon. And thank you again to Siva for helping us navigate. Should be give him one more round of applause? We're going to be back in just a moment to look at how we operationalize all of this data. But in first, here's a message from me. If you're a part of a line of business, your main fear is disruption. You know data is the new goal that can create huge amounts of value. So does your competition. And they may be beating you to it. You're convinced there are new business models and revenue sources hidden in all the data. You just need to figure out how to leverage it. But with the scarcity of data scientists, you really can't rely solely on them. You may need more people throughout the organization that have the ability to extract value from data. And as a data science leader or data scientist, you have a lot of the same concerns. You spend way too much time looking for, prepping, and interpreting data and waiting for models to train. You know you need to operationalize the work you do to provide business value faster. What you want is an easier way to do data prep. And rapidly build models that can be easily deployed, monitored and automatically updated. So whether you're a data scientist, data science leader, or in a line of business, what's the solution? What'll it take to transform the way you work? That's what we're going to explore next. All right, now it's time to delve deeper into the nuts and bolts. The nitty gritty of operationalizing data science and creating a data driven culture. How do you actually do that? Well that's what these experts are here to share with us. I'm joined by Nir Kaldero, who's head of data science at Galvanize, which is an education and training organization. Tricia Wang, who is co-founder of Sudden Compass, a consultancy that helps companies understand people with data. And last, but certainly not least, Michael Li, founder and CEO of Data Incubator, which is a data science train company. All right guys. Shall we get right to it? >> All right. >> So data explosion happening right now. And we are seeing it across the board. I just shared an example of how it's impacting my philanthropic work in pediatric cancer. But you guys each have so many unique roles in your business life. How are you seeing it just blow up in your fields? Nir, your thing? >> Yeah, for example like in Galvanize we train many Fortune 500 companies. And just by looking at the demand of companies that wants us to help them go through this digital transformation is mind-blowing. Data point by itself. >> Okay. Well what we're seeing what's going on is that data science like as a theme, is that it's actually for everyone now. But what's happening is that it's actually meeting non technical people. But what we're seeing is that when non technical people are implementing these tools or coming at these tools without a base line of data literacy, they're often times using it in ways that distance themselves from the customer. Because they're implementing data science tools without a clear purpose, without a clear problem. And so what we do at Sudden Compass is that we work with companies to help them embrace and understand the complexity of their customers. Because often times they are misusing data science to try and flatten their understanding of the customer. As if you can just do more traditional marketing. Where you're putting people into boxes. And I think the whole ROI of data is that you can now understand people's relationships at a much more complex level at a greater scale before. But we have to do this with basic data literacy. And this has to involve technical and non technical people. >> Well you can have all the data in the world, and I think it speaks to, if you're not doing the proper movement with it, forget it. It means nothing at the same time. >> No absolutely. I mean, I think that when you look at the huge explosion in data, that comes with it a huge explosion in data experts. Right, we call them data scientists, data analysts. And sometimes they're people who are very, very talented, like the people here. But sometimes you have people who are maybe re-branding themselves, right? Trying to move up their title one notch to try to attract that higher salary. And I think that that's one of the things that customers are coming to us for, right? They're saying, hey look, there are a lot of people that call themselves data scientists, but we can't really distinguish. So, we have sort of run a fellowship where you help companies hire from a really talented group of folks, who are also truly data scientists and who know all those kind of really important data science tools. And we also help companies internally. Fortune 500 companies who are looking to grow that data science practice that they have. And we help clients like McKinsey, BCG, Bain, train up their customers, also their clients, also their workers to be more data talented. And to build up that data science capabilities. >> And Nir, this is something you work with a lot. A lot of Fortune 500 companies. And when we were speaking earlier, you were saying many of these companies can be in a panic. >> Yeah. >> Explain that. >> Yeah, so you know, not all Fortune 500 companies are fully data driven. And we know that the winners in this fourth industrial revolution, which I like to call the machine intelligence revolution, will be companies who navigate and transform their organization to unlock the power of data science and machine learning. And the companies that are not like that. Or not utilize data science and predictive power well, will pretty much get shredded. So they are in a panic. >> Tricia, companies have to deal with data behind the firewall and in the new multi cloud world. How do organizations start to become driven right to the core? >> I think the most urgent question to become data driven that companies should be asking is how do I bring the complex reality that our customers are experiencing on the ground in to a corporate office? Into the data models. So that question is critical because that's how you actually prevent any big data disasters. And that's how you leverage big data. Because when your data models are really far from your human models, that's when you're going to do things that are really far off from how, it's going to not feel right. That's when Tesco had their terrible big data disaster that they're still recovering from. And so that's why I think it's really important to understand that when you implement big data, you have to further embrace thick data. The qualitative, the emotional stuff, that is difficult to quantify. But then comes the difficult art and science that I think is the next level of data science. Which is that getting non technical and technical people together to ask how do we find those unknown nuggets of insights that are difficult to quantify? Then, how do we do the next step of figuring out how do you mathematically scale those insights into a data model? So that actually is reflective of human understanding? And then we can start making decisions at scale. But you have to have that first. >> That's absolutely right. And I think that when we think about what it means to be a data scientist, right? I always think about it in these sort of three pillars. You have the math side. You have to have that kind of stats, hardcore machine learning background. You have the programming side. You don't work with small amounts of data. You work with large amounts of data. You've got to be able to type the code to make those computers run. But then the last part is that human element. You have to understand the domain expertise. You have to understand what it is that I'm actually analyzing. What's the business proposition? And how are the clients, how are the users actually interacting with the system? That human element that you were talking about. And I think having somebody who understands all of those and not just in isolation, but is able to marry that understanding across those different topics, that's what makes a data scientist. >> But I find that we don't have people with those skill sets. And right now the way I see teams being set up inside companies is that they're creating these isolated data unicorns. These data scientists that have graduated from your programs, which are great. But, they don't involve the people who are the domain experts. They don't involve the designers, the consumer insight people, the people, the salespeople. The people who spend time with the customers day in and day out. Somehow they're left out of the room. They're consulted, but they're not a stakeholder. >> Can I actually >> Yeah, yeah please. >> Can I actually give a quick example? So for example, we at Galvanize train the executives and the managers. And then the technical people, the data scientists and the analysts. But in order to actually see all of the RY behind the data, you also have to have a creative fluid conversation between non technical and technical people. And this is a major trend now. And there's a major gap. And we need to increase awareness and kind of like create a new, kind of like environment where technical people also talks seamlessly with non technical ones. >> [Tricia] We call-- >> That's one of the things that we see a lot. Is one of the trends in-- >> A major trend. >> data science training is it's not just for the data science technical experts. It's not just for one type of person. So a lot of the training we do is sort of data engineers. People who are more on the software engineering side learning more about the stats of math. And then people who are sort of traditionally on the stat side learning more about the engineering. And then managers and people who are data analysts learning about both. >> Michael, I think you said something that was of interest too because I think we can look at IBM Watson as an example. And working in healthcare. The human component. Because often times we talk about machine learning and AI, and data and you get worried that you still need that human component. Especially in the world of healthcare. And I think that's a very strong point when it comes to the data analysis side. Is there any particular example you can speak to of that? >> So I think that there was this really excellent paper a while ago talking about all the neuro net stuff and trained on textual data. So looking at sort of different corpuses. And they found that these models were highly, highly sexist. They would read these corpuses and it's not because neuro nets themselves are sexist. It's because they're reading the things that we write. And it turns out that we write kind of sexist things. And they would sort of find all these patterns in there that were sort of latent, that had a lot of sort of things that maybe we would cringe at if we sort of saw. And I think that's one of the really important aspects of the human element, right? It's being able to come in and sort of say like, okay, I know what the biases of the system are, I know what the biases of the tools are. I need to figure out how to use that to make the tools, make the world a better place. And like another area where this comes up all the time is lending, right? So the federal government has said, and we have a lot of clients in the financial services space, so they're constantly under these kind of rules that they can't make discriminatory lending practices based on a whole set of protected categories. Race, sex, gender, things like that. But, it's very easy when you train a model on credit scores to pick that up. And then to have a model that's inadvertently sexist or racist. And that's where you need the human element to come back in and say okay, look, you're using the classic example would be zip code, you're using zip code as a variable. But when you look at it, zip codes actually highly correlated with race. And you can't do that. So you may inadvertently by sort of following the math and being a little naive about the problem, inadvertently introduce something really horrible into a model and that's where you need a human element to sort of step in and say, okay hold on. Slow things down. This isn't the right way to go. >> And the people who have -- >> I feel like, I can feel her ready to respond. >> Yes, I'm ready. >> She's like let me have at it. >> And the people here it is. And the people who are really great at providing that human intelligence are social scientists. We are trained to look for bias and to understand bias in data. Whether it's quantitative or qualitative. And I really think that we're going to have less of these kind of problems if we had more integrated teams. If it was a mandate from leadership to say no data science team should be without a social scientist, ethnographer, or qualitative researcher of some kind, to be able to help see these biases. >> The talent piece is actually the most crucial-- >> Yeah. >> one here. If you look about how to enable machine intelligence in organization there are the pillars that I have in my head which is the culture, the talent and the technology infrastructure. And I believe and I saw in working very closely with the Fortune 100 and 200 companies that the talent piece is actually the most important crucial hard to get. >> [Tricia] I totally agree. >> It's absolutely true. Yeah, no I mean I think that's sort of like how we came up with our business model. Companies were basically saying hey, I can't hire data scientists. And so we have a fellowship where we get 2,000 applicants each quarter. We take the top 2% and then we sort of train them up. And we work with hiring companies who then want to hire from that population. And so we're sort of helping them solve that problem. And the other half of it is really around training. Cause with a lot of industries, especially if you're sort of in a more regulated industry, there's a lot of nuances to what you're doing. And the fastest way to develop that data science or AI talent may not necessarily be to hire folks who are coming out of a PhD program. It may be to take folks internally who have a lot of that domain knowledge that you have and get them trained up on those data science techniques. So we've had large insurance companies come to us and say hey look, we hire three or four folks from you a quarter. That doesn't move the needle for us. What we really need is take the thousand actuaries and statisticians that we have and get all of them trained up to become a data scientist and become data literate in this new open source world. >> [Katie] Go ahead. >> All right, ladies first. >> Go ahead. >> Are you sure? >> No please, fight first. >> Go ahead. >> Go ahead Nir. >> So this is actually a trend that we have been seeing in the past year or so that companies kind of like start to look how to upscale and look for talent within the organization. So they can actually move them to become more literate and navigate 'em from analyst to data scientist. And from data scientist to machine learner. So this is actually a trend that is happening already for a year or so. >> Yeah, but I also find that after they've gone through that training in getting people skilled up in data science, the next problem that I get is executives coming to say we've invested in all of this. We're still not moving the needle. We've already invested in the right tools. We've gotten the right skills. We have enough scale of people who have these skills. Why are we not moving the needle? And what I explain to them is look, you're still making decisions in the same way. And you're still not involving enough of the non technical people. Especially from marketing, which is now, the CMO's are much more responsible for driving growth in their companies now. But often times it's so hard to change the old way of marketing, which is still like very segmentation. You know, demographic variable based, and we're trying to move people to say no, you have to understand the complexity of customers and not put them in boxes. >> And I think underlying a lot of this discussion is this question of culture, right? >> Yes. >> Absolutely. >> How do you build a data driven culture? And I think that that culture question, one of the ways that comes up quite often in especially in large, Fortune 500 enterprises, is that they are very, they're not very comfortable with sort of example, open source architecture. Open source tools. And there is some sort of residual bias that that's somehow dangerous. So security vulnerability. And I think that that's part of the cultural challenge that they often have in terms of how do I build a more data driven organization? Well a lot of the talent really wants to use these kind of tools. And I mean, just to give you an example, we are partnering with one of the major cloud providers to sort of help make open source tools more user friendly on their platform. So trying to help them attract the best technologists to use their platform because they want and they understand the value of having that kind of open source technology work seamlessly on their platforms. So I think that just sort of goes to show you how important open source is in this movement. And how much large companies and Fortune 500 companies and a lot of the ones we work with have to embrace that. >> Yeah, and I'm seeing it in our work. Even when we're working with Fortune 500 companies, is that they've already gone through the first phase of data science work. Where I explain it was all about the tools and getting the right tools and architecture in place. And then companies started moving into getting the right skill set in place. Getting the right talent. And what you're talking about with culture is really where I think we're talking about the third phase of data science, which is looking at communication of these technical frameworks so that we can get non technical people really comfortable in the same room with data scientists. That is going to be the phase, that's really where I see the pain point. And that's why at Sudden Compass, we're really dedicated to working with each other to figure out how do we solve this problem now? >> And I think that communication between the technical stakeholders and management and leadership. That's a very critical piece of this. You can't have a successful data science organization without that. >> Absolutely. >> And I think that actually some of the most popular trainings we've had recently are from managers and executives who are looking to say, how do I become more data savvy? How do I figure out what is this data science thing and how do I communicate with my data scientists? >> You guys made this way too easy. I was just going to get some popcorn and watch it play out. >> Nir, last 30 seconds. I want to leave you with an opportunity to, anything you want to add to this conversation? >> I think one thing to conclude is to say that companies that are not data driven is about time to hit refresh and figure how they transition the organization to become data driven. To become agile and nimble so they can actually see what opportunities from this important industrial revolution. Otherwise, unfortunately they will have hard time to survive. >> [Katie] All agreed? >> [Tricia] Absolutely, you're right. >> Michael, Trish, Nir, thank you so much. Fascinating discussion. And thank you guys again for joining us. We will be right back with another great demo. Right after this. >> Thank you Katie. >> Once again, thank you for an excellent discussion. Weren't they great guys? And thank you for everyone who's tuning in on the live webcast. As you can hear, we have an amazing studio audience here. And we're going to keep things moving. I'm now joined by Daniel Hernandez and Siva Anne. And we're going to turn our attention to how you can deliver on what they're talking about using data science experience to do data science faster. >> Thank you Katie. Siva and I are going to spend the next 10 minutes showing you how you can deliver on what they were saying using the IBM Data Science Experience to do data science faster. We'll demonstrate through new features we introduced this week how teams can work together more effectively across the entire analytics life cycle. How you can take advantage of any and all data no matter where it is and what it is. How you could use your favorite tools from open source. And finally how you could build models anywhere and employ them close to where your data is. Remember the financial adviser app Rob showed you? To build an app like that, we needed a team of data scientists, developers, data engineers, and IT staff to collaborate. We do this in the Data Science Experience through a concept we call projects. When I create a new project, I can now use the new Github integration feature. We're doing for data science what we've been doing for developers for years. Distributed teams can work together on analytics projects. And take advantage of Github's version management and change management features. This is a huge deal. Let's explore the project we created for the financial adviser app. As you can see, our data engineer Joane, our developer Rob, and others are collaborating this project. Joane got things started by bringing together the trusted data sources we need to build the app. Taking a closer look at the data, we see that our customer and profile data is stored on our recently announced IBM Integrated Analytics System, which runs safely behind our firewall. We also needed macro economic data, which she was able to find in the Federal Reserve. And she stored it in our Db2 Warehouse on Cloud. And finally, she selected stock news data from NASDAQ.com and landed that in a Hadoop cluster, which happens to be powered by Hortonworks. We added a new feature to the Data Science Experience so that when it's installed with Hortonworks, it automatically uses a need of security and governance controls within the cluster so your data is always secure and safe. Now we want to show you the news data we stored in the Hortonworks cluster. This is the mean administrative console. It's powered by an open source project called Ambari. And here's the news data. It's in parquet files stored in HDFS, which happens to be a distributive file system. To get the data from NASDAQ into our cluster, we used IBM's BigIntegrate and BigQuality to create automatic data pipelines that acquire, cleanse, and ingest that news data. Once the data's available, we use IBM's Big SQL to query that data using SQL statements that are much like the ones we would use for any relation of data, including the data that we have in the Integrated Analytics System and Db2 Warehouse on Cloud. This and the federation capabilities that Big SQL offers dramatically simplifies data acquisition. Now we want to show you how we support a brand new tool that we're excited about. Since we launched last summer, the Data Science Experience has supported Jupyter and R for data analysis and visualization. In this week's update, we deeply integrated another great open source project called Apache Zeppelin. It's known for having great visualization support, advanced collaboration features, and is growing in popularity amongst the data science community. This is an example of Apache Zeppelin and the notebook we created through it to explore some of our data. Notice how wonderful and easy the data visualizations are. Now we want to walk you through the Jupyter notebook we created to explore our customer preference for stocks. We use notebooks to understand and explore data. To identify the features that have some predictive power. Ultimately, we're trying to assess what ultimately is driving customer stock preference. Here we did the analysis to identify the attributes of customers that are likely to purchase auto stocks. We used this understanding to build our machine learning model. For building machine learning models, we've always had tools integrated into the Data Science Experience. But sometimes you need to use tools you already invested in. Like our very own SPSS as well as SAS. Through new import feature, you can easily import those models created with those tools. This helps you avoid vendor lock-in, and simplify the development, training, deployment, and management of all your models. To build the models we used in app, we could have coded, but we prefer a visual experience. We used our customer profile data in the Integrated Analytic System. Used the Auto Data Preparation to cleanse our data. Choose the binary classification algorithms. Let the Data Science Experience evaluate between logistic regression and gradient boosted tree. It's doing the heavy work for us. As you can see here, the Data Science Experience generated performance metrics that show us that the gradient boosted tree is the best performing algorithm for the data we gave it. Once we save this model, it's automatically deployed and available for developers to use. Any application developer can take this endpoint and consume it like they would any other API inside of the apps they built. We've made training and creating machine learning models super simple. But what about the operations? A lot of companies are struggling to ensure their model performance remains high over time. In our financial adviser app, we know that customer data changes constantly, so we need to always monitor model performance and ensure that our models are retrained as is necessary. This is a dashboard that shows the performance of our models and lets our teams monitor and retrain those models so that they're always performing to our standards. So far we've been showing you the Data Science Experience available behind the firewall that we're using to build and train models. Through a new publish feature, you can build models and deploy them anywhere. In another environment, private, public, or anywhere else with just a few clicks. So here we're publishing our model to the Watson machine learning service. It happens to be in the IBM cloud. And also deeply integrated with our Data Science Experience. After publishing and switching to the Watson machine learning service, you can see that our stock affinity and model that we just published is there and ready for use. So this is incredibly important. I just want to say it again. The Data Science Experience allows you to train models behind your own firewall, take advantage of your proprietary and sensitive data, and then deploy those models wherever you want with ease. So summarize what we just showed you. First, IBM's Data Science Experience supports all teams. You saw how our data engineer populated our project with trusted data sets. Our data scientists developed, trained, and tested a machine learning model. Our developers used APIs to integrate machine learning into their apps. And how IT can use our Integrated Model Management dashboard to monitor and manage model performance. Second, we support all data. On premises, in the cloud, structured, unstructured, inside of your firewall, and outside of it. We help you bring analytics and governance to where your data is. Third, we support all tools. The data science tools that you depend on are readily available and deeply integrated. This includes capabilities from great partners like Hortonworks. And powerful tools like our very own IBM SPSS. And fourth, and finally, we support all deployments. You can build your models anywhere, and deploy them right next to where your data is. Whether that's in the public cloud, private cloud, or even on the world's most reliable transaction platform, IBM z. So see for yourself. Go to the Data Science Experience website, take us for a spin. And if you happen to be ready right now, our recently created Data Science Elite Team can help you get started and run experiments alongside you with no charge. Thank you very much. >> Thank you very much Daniel. It seems like a great time to get started. And thanks to Siva for taking us through it. Rob and I will be back in just a moment to add some perspective right after this. All right, once again joined by Rob Thomas. And Rob obviously we got a lot of information here. >> Yes, we've covered a lot of ground. >> This is intense. You got to break it down for me cause I think we zoom out and see the big picture. What better data science can deliver to a business? Why is this so important? I mean we've heard it through and through. >> Yeah, well, I heard it a couple times. But it starts with businesses have to embrace a data driven culture. And it is a change. And we need to make data accessible with the right tools in a collaborative culture because we've got diverse skill sets in every organization. But data driven companies succeed when data science tools are in the hands of everyone. And I think that's a new thought. I think most companies think just get your data scientist some tools, you'll be fine. This is about tools in the hands of everyone. I think the panel did a great job of describing about how we get to data science for all. Building a data culture, making it a part of your everyday operations, and the highlights of what Daniel just showed us, that's some pretty cool features for how organizations can get to this, which is you can see IBM's Data Science Experience, how that supports all teams. You saw data analysts, data scientists, application developer, IT staff, all working together. Second, you saw how we support all tools. And your choice of tools. So the most popular data science libraries integrated into one platform. And we saw some new capabilities that help companies avoid lock-in, where you can import existing models created from specialist tools like SPSS or others. And then deploy them and manage them inside of Data Science Experience. That's pretty interesting. And lastly, you see we continue to build on this best of open tools. Partnering with companies like H2O, Hortonworks, and others. Third, you can see how you use all data no matter where it lives. That's a key challenge every organization's going to face. Private, public, federating all data sources. We announced new integration with the Hortonworks data platform where we deploy machine learning models where your data resides. That's been a key theme. Analytics where the data is. And lastly, supporting all types of deployments. Deploy them in your Hadoop cluster. Deploy them in your Integrated Analytic System. Or deploy them in z, just to name a few. A lot of different options here. But look, don't believe anything I say. Go try it for yourself. Data Science Experience, anybody can use it. Go to datascience.ibm.com and look, if you want to start right now, we just created a team that we call Data Science Elite. These are the best data scientists in the world that will come sit down with you and co-create solutions, models, and prove out a proof of concept. >> Good stuff. Thank you Rob. So you might be asking what does an organization look like that embraces data science for all? And how could it transform your role? I'm going to head back to the office and check it out. Let's start with the perspective of the line of business. What's changed? Well, now you're starting to explore new business models. You've uncovered opportunities for new revenue sources and all that hidden data. And being disrupted is no longer keeping you up at night. As a data science leader, you're beginning to collaborate with a line of business to better understand and translate the objectives into the models that are being built. Your data scientists are also starting to collaborate with the less technical team members and analysts who are working closest to the business problem. And as a data scientist, you stop feeling like you're falling behind. Open source tools are keeping you current. You're also starting to operationalize the work that you do. And you get to do more of what you love. Explore data, build models, put your models into production, and create business impact. All in all, it's not a bad scenario. Thanks. All right. We are back and coming up next, oh this is a special time right now. Cause we got a great guest speaker. New York Magazine called him the spreadsheet psychic and number crunching prodigy who went from correctly forecasting baseball games to correctly forecasting presidential elections. He even invented a proprietary algorithm called PECOTA for predicting future performance by baseball players and teams. And his New York Times bestselling book, The Signal and the Noise was named by Amazon.com as the number one best non-fiction book of 2012. He's currently the Editor in Chief of the award winning website, FiveThirtyEight and appears on ESPN as an on air commentator. Big round of applause. My pleasure to welcome Nate Silver. >> Thank you. We met backstage. >> Yes. >> It feels weird to re-shake your hand, but you know, for the audience. >> I had to give the intense firm grip. >> Definitely. >> The ninja grip. So you and I have crossed paths kind of digitally in the past, which it really interesting, is I started my career at ESPN. And I started as a production assistant, then later back on air for sports technology. And I go to you to talk about sports because-- >> Yeah. >> Wow, has ESPN upped their game in terms of understanding the importance of data and analytics. And what it brings. Not just to MLB, but across the board. >> No, it's really infused into the way they present the broadcast. You'll have win probability on the bottom line. And they'll incorporate FiveThirtyEight metrics into how they cover college football for example. So, ESPN ... Sports is maybe the perfect, if you're a data scientist, like the perfect kind of test case. And the reason being that sports consists of problems that have rules. And have structure. And when problems have rules and structure, then it's a lot easier to work with. So it's a great way to kind of improve your skills as a data scientist. Of course, there are also important real world problems that are more open ended, and those present different types of challenges. But it's such a natural fit. The teams. Think about the teams playing the World Series tonight. The Dodgers and the Astros are both like very data driven, especially Houston. Golden State Warriors, the NBA Champions, extremely data driven. New England Patriots, relative to an NFL team, it's shifted a little bit, the NFL bar is lower. But the Patriots are certainly very analytical in how they make decisions. So, you can't talk about sports without talking about analytics. >> And I was going to save the baseball question for later. Cause we are moments away from game seven. >> Yeah. >> Is everyone else watching game seven? It's been an incredible series. Probably one of the best of all time. >> Yeah, I mean-- >> You have a prediction here? >> You can mention that too. So I don't have a prediction. FiveThirtyEight has the Dodgers with a 60% chance of winning. >> [Katie] LA Fans. >> So you have two teams that are about equal. But the Dodgers pitching staff is in better shape at the moment. The end of a seven game series. And they're at home. >> But the statistics behind the two teams is pretty incredible. >> Yeah. It's like the first World Series in I think 56 years or something where you have two 100 win teams facing one another. There have been a lot of parity in baseball for a lot of years. Not that many offensive overall juggernauts. But this year, and last year with the Cubs and the Indians too really. But this year, you have really spectacular teams in the World Series. It kind of is a showcase of modern baseball. Lots of home runs. Lots of strikeouts. >> [Katie] Lots of extra innings. >> Lots of extra innings. Good defense. Lots of pitching changes. So if you love the modern baseball game, it's been about the best example that you've had. If you like a little bit more contact, and fewer strikeouts, maybe not so much. But it's been a spectacular and very exciting World Series. It's amazing to talk. MLB is huge with analysis. I mean, hands down. But across the board, if you can provide a few examples. Because there's so many teams in front offices putting such an, just a heavy intensity on the analysis side. And where the teams are going. And if you could provide any specific examples of teams that have really blown your mind. Especially over the last year or two. Because every year it gets more exciting if you will. I mean, so a big thing in baseball is defensive shifts. So if you watch tonight, you'll probably see a couple of plays where if you're used to watching baseball, a guy makes really solid contact. And there's a fielder there that you don't think should be there. But that's really very data driven where you analyze where's this guy hit the ball. That part's not so hard. But also there's game theory involved. Because you have to adjust for the fact that he knows where you're positioning the defenders. He's trying therefore to make adjustments to his own swing and so that's been a major innovation in how baseball is played. You know, how bullpens are used too. Where teams have realized that actually having a guy, across all sports pretty much, realizing the importance of rest. And of fatigue. And that you can be the best pitcher in the world, but guess what? After four or five innings, you're probably not as good as a guy who has a fresh arm necessarily. So I mean, it really is like, these are not subtle things anymore. It's not just oh, on base percentage is valuable. It really effects kind of every strategic decision in baseball. The NBA, if you watch an NBA game tonight, see how many three point shots are taken. That's in part because of data. And teams realizing hey, three points is worth more than two, once you're more than about five feet from the basket, the shooting percentage gets really flat. And so it's revolutionary, right? Like teams that will shoot almost half their shots from the three point range nowadays. Larry Bird, who wound up being one of the greatest three point shooters of all time, took only eight three pointers his first year in the NBA. It's quite noticeable if you watch baseball or basketball in particular. >> Not to focus too much on sports. One final question. In terms of Major League Soccer, and now in NFL, we're having the analysis and having wearables where it can now showcase if they wanted to on screen, heart rate and breathing and how much exertion. How much data is too much data? And when does it ruin the sport? >> So, I don't think, I mean, again, it goes sport by sport a little bit. I think in basketball you actually have a more exciting game. I think the game is more open now. You have more three pointers. You have guys getting higher assist totals. But you know, I don't know. I'm not one of those people who thinks look, if you love baseball or basketball, and you go in to work for the Astros, the Yankees or the Knicks, they probably need some help, right? You really have to be passionate about that sport. Because it's all based on what questions am I asking? As I'm a fan or I guess an employee of the team. Or a player watching the game. And there isn't really any substitute I don't think for the insight and intuition that a curious human has to kind of ask the right questions. So we can talk at great length about what tools do you then apply when you have those questions, but that still comes from people. I don't think machine learning could help with what questions do I want to ask of the data. It might help you get the answers. >> If you have a mid-fielder in a soccer game though, not exerting, only 80%, and you're seeing that on a screen as a fan, and you're saying could that person get fired at the end of the day? One day, with the data? >> So we found that actually some in soccer in particular, some of the better players are actually more still. So Leo Messi, maybe the best player in the world, doesn't move as much as other soccer players do. And the reason being that A) he kind of knows how to position himself in the first place. B) he realizes that you make a run, and you're out of position. That's quite fatiguing. And particularly soccer, like basketball, is a sport where it's incredibly fatiguing. And so, sometimes the guys who conserve their energy, that kind of old school mentality, you have to hustle at every moment. That is not helpful to the team if you're hustling on an irrelevant play. And therefore, on a critical play, can't get back on defense, for example. >> Sports, but also data is moving exponentially as we're just speaking about today. Tech, healthcare, every different industry. Is there any particular that's a favorite of yours to cover? And I imagine they're all different as well. >> I mean, I do like sports. We cover a lot of politics too. Which is different. I mean in politics I think people aren't intuitively as data driven as they might be in sports for example. It's impressive to follow the breakthroughs in artificial intelligence. It started out just as kind of playing games and playing chess and poker and Go and things like that. But you really have seen a lot of breakthroughs in the last couple of years. But yeah, it's kind of infused into everything really. >> You're known for your work in politics though. Especially presidential campaigns. >> Yeah. >> This year, in particular. Was it insanely challenging? What was the most notable thing that came out of any of your predictions? >> I mean, in some ways, looking at the polling was the easiest lens to look at it. So I think there's kind of a myth that last year's result was a big shock and it wasn't really. If you did the modeling in the right way, then you realized that number one, polls have a margin of error. And so when a candidate has a three point lead, that's not particularly safe. Number two, the outcome between different states is correlated. Meaning that it's not that much of a surprise that Clinton lost Wisconsin and Michigan and Pennsylvania and Ohio. You know I'm from Michigan. Have friends from all those states. Kind of the same types of people in those states. Those outcomes are all correlated. So what people thought was a big upset for the polls I think was an example of how data science done carefully and correctly where you understand probabilities, understand correlations. Our model gave Trump a 30% chance of winning. Others models gave him a 1% chance. And so that was interesting in that it showed that number one, that modeling strategies and skill do matter quite a lot. When you have someone saying 30% versus 1%. I mean, that's a very very big spread. And number two, that these aren't like solved problems necessarily. Although again, the problem with elections is that you only have one election every four years. So I can be very confident that I have a better model. Even one year of data doesn't really prove very much. Even five or 10 years doesn't really prove very much. And so, being aware of the limitations to some extent intrinsically in elections when you only get one kind of new training example every four years, there's not really any way around that. There are ways to be more robust to sparce data environments. But if you're identifying different types of business problems to solve, figuring out what's a solvable problem where I can add value with data science is a really key part of what you're doing. >> You're such a leader in this space. In data and analysis. It would be interesting to kind of peek back the curtain, understand how you operate but also how large is your team? How you're putting together information. How quickly you're putting it out. Cause I think in this right now world where everybody wants things instantly-- >> Yeah. >> There's also, you want to be first too in the world of journalism. But you don't want to be inaccurate because that's your credibility. >> We talked about this before, right? I think on average, speed is a little bit overrated in journalism. >> [Katie] I think it's a big problem in journalism. >> Yeah. >> Especially in the tech world. You have to be first. You have to be first. And it's just pumping out, pumping out. And there's got to be more time spent on stories if I can speak subjectively. >> Yeah, for sure. But at the same time, we are reacting to the news. And so we have people that come in, we hire most of our people actually from journalism. >> [Katie] How many people do you have on your team? >> About 35. But, if you get someone who comes in from an academic track for example, they might be surprised at how fast journalism is. That even though we might be slower than the average website, the fact that there's a tragic event in New York, are there things we have to say about that? A candidate drops out of the presidential race, are things we have to say about that. In periods ranging from minutes to days as opposed to kind of weeks to months to years in the academic world. The corporate world moves faster. What is a little different about journalism is that you are expected to have more precision where people notice when you make a mistake. In corporations, you have maybe less transparency. If you make 10 investments and seven of them turn out well, then you'll get a lot of profit from that, right? In journalism, it's a little different. If you make kind of seven predictions or say seven things, and seven of them are very accurate and three of them aren't, you'll still get criticized a lot for the three. Just because that's kind of the way that journalism is. And so the kind of combination of needing, not having that much tolerance for mistakes, but also needing to be fast. That is tricky. And I criticize other journalists sometimes including for not being data driven enough, but the best excuse any journalist has, this is happening really fast and it's my job to kind of figure out in real time what's going on and provide useful information to the readers. And that's really difficult. Especially in a world where literally, I'll probably get off the stage and check my phone and who knows what President Trump will have tweeted or what things will have happened. But it really is a kind of 24/7. >> Well because it's 24/7 with FiveThirtyEight, one of the most well known sites for data, are you feeling micromanagey on your people? Because you do have to hit this balance. You can't have something come out four or five days later. >> Yeah, I'm not -- >> Are you overseeing everything? >> I'm not by nature a micromanager. And so you try to hire well. You try and let people make mistakes. And the flip side of this is that if a news organization that never had any mistakes, never had any corrections, that's raw, right? You have to have some tolerance for error because you are trying to decide things in real time. And figure things out. I think transparency's a big part of that. Say here's what we think, and here's why we think it. If we have a model to say it's not just the final number, here's a lot of detail about how that's calculated. In some case we release the code and the raw data. Sometimes we don't because there's a proprietary advantage. But quite often we're saying we want you to trust us and it's so important that you trust us, here's the model. Go play around with it yourself. Here's the data. And that's also I think an important value. >> That speaks to open source. And your perspective on that in general. >> Yeah, I mean, look, I'm a big fan of open source. I worry that I think sometimes the trends are a little bit away from open source. But by the way, one thing that happens when you share your data or you share your thinking at least in lieu of the data, and you can definitely do both is that readers will catch embarrassing mistakes that you made. By the way, even having open sourceness within your team, I mean we have editors and copy editors who often save you from really embarrassing mistakes. And by the way, it's not necessarily people who have a training in data science. I would guess that of our 35 people, maybe only five to 10 have a kind of formal background in what you would call data science. >> [Katie] I think that speaks to the theme here. >> Yeah. >> [Katie] That everybody's kind of got to be data literate. >> But yeah, it is like you have a good intuition. You have a good BS detector basically. And you have a good intuition for hey, this looks a little bit out of line to me. And sometimes that can be based on domain knowledge, right? We have one of our copy editors, she's a big college football fan. And we had an algorithm we released that tries to predict what the human being selection committee will do, and she was like, why is LSU rated so high? Cause I know that LSU sucks this year. And we looked at it, and she was right. There was a bug where it had forgotten to account for their last game where they lost to Troy or something and so -- >> That also speaks to the human element as well. >> It does. In general as a rule, if you're designing a kind of regression based model, it's different in machine learning where you have more, when you kind of build in the tolerance for error. But if you're trying to do something more precise, then so much of it is just debugging. It's saying that looks wrong to me. And I'm going to investigate that. And sometimes it's not wrong. Sometimes your model actually has an insight that you didn't have yourself. But fairly often, it is. And I think kind of what you learn is like, hey if there's something that bothers me, I want to go investigate that now and debug that now. Because the last thing you want is where all of a sudden, the answer you're putting out there in the world hinges on a mistake that you made. Cause you never know if you have so to speak, 1,000 lines of code and they all perform something differently. You never know when you get in a weird edge case where this one decision you made winds up being the difference between your having a good forecast and a bad one. In a defensible position and a indefensible one. So we definitely are quite diligent and careful. But it's also kind of knowing like, hey, where is an approximation good enough and where do I need more precision? Cause you could also drive yourself crazy in the other direction where you know, it doesn't matter if the answer is 91.2 versus 90. And so you can kind of go 91.2, three, four and it's like kind of A) false precision and B) not a good use of your time. So that's where I do still spend a lot of time is thinking about which problems are "solvable" or approachable with data and which ones aren't. And when they're not by the way, you're still allowed to report on them. We are a news organization so we do traditional reporting as well. And then kind of figuring out when do you need precision versus when is being pointed in the right direction good enough? >> I would love to get inside your brain and see how you operate on just like an everyday walking to Walgreens movement. It's like oh, if I cross the street in .2-- >> It's not, I mean-- >> Is it like maddening in there? >> No, not really. I mean, I'm like-- >> This is an honest question. >> If I'm looking for airfares, I'm a little more careful. But no, part of it's like you don't want to waste time on unimportant decisions, right? I will sometimes, if I can't decide what to eat at a restaurant, I'll flip a coin. If the chicken and the pasta both sound really good-- >> That's not high tech Nate. We want better. >> But that's the point, right? It's like both the chicken and the pasta are going to be really darn good, right? So I'm not going to waste my time trying to figure it out. I'm just going to have an arbitrary way to decide. >> Serious and business, how organizations in the last three to five years have just evolved with this data boom. How are you seeing it as from a consultant point of view? Do you think it's an exciting time? Do you think it's a you must act now time? >> I mean, we do know that you definitely see a lot of talent among the younger generation now. That so FiveThirtyEight has been at ESPN for four years now. And man, the quality of the interns we get has improved so much in four years. The quality of the kind of young hires that we make straight out of college has improved so much in four years. So you definitely do see a younger generation for which this is just part of their bloodstream and part of their DNA. And also, particular fields that we're interested in. So we're interested in people who have both a data and a journalism background. We're interested in people who have a visualization and a coding background. A lot of what we do is very much interactive graphics and so forth. And so we do see those skill sets coming into play a lot more. And so the kind of shortage of talent that had I think frankly been a problem for a long time, I'm optimistic based on the young people in our office, it's a little anecdotal but you can tell that there are so many more programs that are kind of teaching students the right set of skills that maybe weren't taught as much a few years ago. >> But when you're seeing these big organizations, ESPN as perfect example, moving more towards data and analytics than ever before. >> Yeah. >> You would say that's obviously true. >> Oh for sure. >> If you're not moving that direction, you're going to fall behind quickly. >> Yeah and the thing is, if you read my book or I guess people have a copy of the book. In some ways it's saying hey, there are lot of ways to screw up when you're using data. And we've built bad models. We've had models that were bad and got good results. Good models that got bad results and everything else. But the point is that the reason to be out in front of the problem is so you give yourself more runway to make errors and mistakes. And to learn kind of what works and what doesn't and which people to put on the problem. I sometimes do worry that a company says oh we need data. And everyone kind of agrees on that now. We need data science. Then they have some big test case. And they have a failure. And they maybe have a failure because they didn't know really how to use it well enough. But learning from that and iterating on that. And so by the time that you're on the third generation of kind of a problem that you're trying to solve, and you're watching everyone else make the mistake that you made five years ago, I mean, that's really powerful. But that doesn't mean that getting invested in it now, getting invested both in technology and the human capital side is important. >> Final question for you as we run out of time. 2018 beyond, what is your biggest project in terms of data gathering that you're working on? >> There's a midterm election coming up. That's a big thing for us. We're also doing a lot of work with NBA data. So for four years now, the NBA has been collecting player tracking data. So they have 3D cameras in every arena. So they can actually kind of quantify for example how fast a fast break is, for example. Or literally where a player is and where the ball is. For every NBA game now for the past four or five years. And there hasn't really been an overall metric of player value that's taken advantage of that. The teams do it. But in the NBA, the teams are a little bit ahead of journalists and analysts. So we're trying to have a really truly next generation stat. It's a lot of data. Sometimes I now more oversee things than I once did myself. And so you're parsing through many, many, many lines of code. But yeah, so we hope to have that out at some point in the next few months. >> Anything you've personally been passionate about that you've wanted to work on and kind of solve? >> I mean, the NBA thing, I am a pretty big basketball fan. >> You can do better than that. Come on, I want something real personal that you're like I got to crunch the numbers. >> You know, we tried to figure out where the best burrito in America was a few years ago. >> I'm going to end it there. >> Okay. >> Nate, thank you so much for joining us. It's been an absolute pleasure. Thank you. >> Cool, thank you. >> I thought we were going to chat World Series, you know. Burritos, important. I want to thank everybody here in our audience. Let's give him a big round of applause. >> [Nate] Thank you everyone. >> Perfect way to end the day. And for a replay of today's program, just head on over to ibm.com/dsforall. I'm Katie Linendoll. And this has been Data Science for All: It's a Whole New Game. Test one, two. One, two, three. Hi guys, I just want to quickly let you know as you're exiting. A few heads up. Downstairs right now there's going to be a meet and greet with Nate. And we're going to be doing that with clients and customers who are interested. So I would recommend before the game starts, and you lose Nate, head on downstairs. And also the gallery is open until eight p.m. with demos and activations. And tomorrow, make sure to come back too. Because we have exciting stuff. I'll be joining you as your host. And we're kicking off at nine a.m. So bye everybody, thank you so much. >> [Announcer] Ladies and gentlemen, thank you for attending this evening's webcast. If you are not attending all cloud and cognitive summit tomorrow, we ask that you recycle your name badge at the registration desk. Thank you. Also, please note there are two exits on the back of the room on either side of the room. Have a good evening. Ladies and gentlemen, the meet and greet will be on stage. Thank you.

[Techno Music] >> Narrator: Live, from Orlando, Florida it's the Cube covering Grace Hopper's celebration of women in computing. Brought to you by SiliconANGLE Media >> Hey welcome back everybody, Jeff Frick here with the Cube. We're at the Grace Hopper Celebration of women in computing 2017, 18,000 women and men here at the Orlando Convention Center it gets bigger and bigger every year and we're really excited to have our next guest, the soon-to-be looking for a new job, and former CEO but still employed by AnitaB.org, Telle Whitney, the founder of this fantastic organization and really, the force behind turning it from, as you said, an okay non-profit to really a force. >> Yes So Telle, as always, fantastic to see you. >> Oh it's great to see you, glad to welcome you back and glad to have you here. >> Yes, thank you. So, interesting times, so you're going to be stepping down at the end of the year, you've passed the baton to Brenda. So as you kind of look back, get a moment to reflect, which I guess you can't do until January, they're still working you, what an unbelievable legacy, what an unbelievable baton that you are passing on for Brenda's stewardship for the next chapter. >> Yes, I mean, I've been CEO for the last 15 years and under that time period, we've grown into a global force with impact, well over 700,000 people. We have well over 100,000 people who participated with the Grace Hopper or the Grace Hopper India. It's grown, and what's been really exciting the last few days, is hearing the stories. >> Jeff: Right, right. >> Of how, the impact that this, the AnitaB.org has had on the lives of young women but also mid-career and senior executives. It's very inspiring to me. >> It is, it's fantastic, and I think the mid-career and more senior executive part of the story isn't as well-known, and we've talked to, Work Day was here, I think they said they had 140 people I think I talked to Google, I think they had like 180. And I asked them, I said, is there any other show, besides your own, that you bring that many people to from the company for their own professional development, and growth. And there's nothing like it. >> That's true. The reason why the Grace Hopper celebration has grown as significantly as it has is because more and more organizations, companies, bring a large part of their workforce. I mean, there are some companies that have brought up to 800 people, and sometimes even 1,000. >> Jeff: Wow >> And there's a reason why, because they see the impact that the conference has on retention and advancement of the women who work for them. >> And that's really a growing and increasing important part of the conversation, >> It is. >> Is retention, and two, getting the women who maybe left to have a baby, or talk about military veterans getting back in, so there's a whole group of people kind of outside of the traditional took my four years of college, I got a CS degree, now I need a job, that are also leveraging the benefits of this conference to make that way back in to tech. So important now as autonomous vehicles are coming on board and all these other things that are going to displace a bunch of traditional jobs. The message here is, you can actually get into CS later in life and find a successful career. >> Yes, we have a real diversity of attendees. So about a third of them are students, and that's really, they're brought here by their universities because that makes a difference. We have a great group from the government. So there's this real effort to bring state-of-the-art technology into our government, initially spearheaded by Megan Smith but really has grown. And the government brought quite a few women. And yes, we do have re-entry people. The companies are looking for women who are very interested in getting back in the workforce. The wonder about our profession, is that they're in desperate need of talented computer scientists. And so, because of that, more and more organizations are being innovative in how they reach out to different audiences. >> And outside of you, I don't know that anyone is more enthusiastic about this conference than Megan Smith. >> Yeah (laughs) >> She is a force of nature. We saw her last year, we were fortunate to get her on the Cube this year, which was really exciting. And she just brings so much energy. We're seeing so much activity on the government side, regardless of your partisanship, of using cloud, using new technology, and that's really driving, again, more innovation, more computing, and demand for more great people. >> Yes, we're very blessed that Megan has continued to come here every year. She came back this year, she sat on the main stage, and she has really been, her message to so many of the young women is that, consider government technology as something you do, at least for a while. And I think that that's a very important message if you think about how that impacts our lives. >> Right, for the good. >> Telle: Yes. >> And that was a big part of her message, she went through a classic legal resume, and some other classic resumes where you have that chapter in your career where you do go into government and you do make a contribution to something a little bit bigger than potentially your regular job. It does strike me though, how technology and software engineering specifically is such an unbelievable vehicle in which to change the world. The traditional barriers of distribution, access to capital, the amount of funding that you used to have to have to build a company, all those things are gone now through cloud, and the internet, and now you can write software and change the world pretty easily. >> Yes. Technology has the possibility of being equal access for anybody. Open-source, anybody can start to code through open-source. There are many ways for anybody, but particularly women to get back in. But I also like to think about many of the companies here who bring their diversity, they bring their senior executives, they bring this large number of women and they create this view across the entire company of how to create a company that's impactful as well as, you know, developing the products that they are invested in. >> Jeff: Right. >> I mean you can have impact in many different ways, through companies, through non-profits, through government, through many different ways. >> Right, and not only the diversity of the people, but one of the other things we love about this show is the diversity of the companies that are here. Like you said, as government, as I look out there's industrial equipment companies, there's entertainment companies, MLB is right across from us and has been there the three days. So it's really a fantastic display of this kind of horizontal impact of technology, and then of course, as we know, it does make better business to have diversity in teams. It's not about doing just the right thing, it's actually about having better bottom-line impact and better bottom-line results. And that's been proven time and time again. >> Well yes, and, so what I know is that every company is a technology company. If you think about the entire banking industry, they have this huge technology workforce. Certainly classic technology companies have a lot of engineers, but insurance, and banking, and almost anything. I mean, we have a lot increasing amount of retail, Target, Best Buy, places like that. >> Right. Okay so I tried to order in a horse so you could ride off into the sunset at the end of this interview, but they wouldn't let me get it through security. >> Okay >> But before I let you go, I'd just love to get your thoughts on Brenda, and the passing of the baton. How did you find her, what are some of the things that you feel comfortable, feel good about, beyond comfortable, to give her the mantle, the baton, if you will, for the next chapter of AnitaB.org? >> I've been very blessed to lead this organization for 15 years, and this is my baby. But there is nothing more heart-warming than to be able to talk to a visionary leader like Brenda. Brenda is extraordinary. She really believes in computer science for all. She believes that all women should be at the table creating technologies. She has a vision of where she wants to take it and yes, she just started last Sunday, so we have to give her a little time. (laughs) >> You were right into the deep end right? Swim! (laughs) >> But she is just, I mean, I just feel very blessed to have Brenda in my life and I will be there in any way that she needs for me to be there to work with her. But she is going to be a great leader. >> Oh absolutely. Well Telle as always, great, and as you said, you're more busy than maybe you expected to be here, so to find a few minutes to stop by the Cube again, thank you for inviting us to be here. It is really one of our favorite places to be every year. Finally my youngest daughter turns 18 next year, so I can bring her too. And congratulations for everything you've accomplished. >> I love to be here, thank you for coming. Glad we could talk. >> Alright, she's Telle Whitney, I'm Jeff Frick, if you're looking for a highly-qualified woman in tech, she might be on the market in 2018. (Telle laughs) Give me a call, I'll set you up. Alright, you're watching the Cube, from the Grace Hopper Celebration of women in computing. Thanks for watching. (techno music)

>> Announcer: Live from Las Vegas, its theCUBE, covering Veritas Vision 2017. Brought to you by Veritas. >> Welcome back the the Aria in Las Vegas, everybody. This is theCUBE, the leader in live tech coverage. My name is Dave Vellante, I'm here with Stu Miniman. Angelo Sciascia is here, big Tom Brady fan, Senior Vice President of NetX Information Systems, from Brooklyn, New York, I don't think so. >> Not a Tom Brady fan. >> Thanks for coming on theCUBE do you think it matters, how much it airs at a football. >> No, not at all, Tom Brady doesn't care about that. >> No, well, listen, thanks for coming on. We have a great conversation, we love talking sports on the Cube. So welcome, how's the show going for you? >> Ah, it's fantastic, you know, lots of great material Veritas has been talking about. 360 Data Management, obviously we all know the benefits of that by now. So we have a lot of customers here so I'm glad they they got to see it from a senior leadership perspective, rather than our sales guys and sales engineers going in there and talking to them, and seeing Veritas executives really getting behind what we're talking about. So it backs up our story and, you know, our customers are pretty excited about it, actually. >> What's the nature of your relationship with Veritas. I know you have a relationship, and maybe still do, with Symantec. How's that all, how did it all evolve? >> Yeah, so we are a Veritas Platinum Partner, we would be, what we consider, a solution-provider type partner. A lot of our business today is either directly or indirectly tied to Veritas, which was kind of funny because we started as a security company, so our roots are systems management, you know. That's where we were in 2005 when I joined NetX, that's where we were for many, many years after Symantec acquired a company called Altiris. We just stayed in that vein, you know, managing endpoints, securing endpoints, encrypting data. And then, somewhere in 2013, we said hey, you know, let's try to diversify the portfolio a little bit. And we used to manufacture an endpoint management appliance for Altiris so we said hey, Symantec's got these things called NetBackup Appliances, let's check it out. It's a formed fact that we know how to sell and, shoot, four years later it's been a great partnership for us, great partnership, I'm sure, for Veritas, and for our customers and that's a lot of our business today. >> So, I mean, it's hot market, you know. Data protection is exploding, and security. I mean, you're in two of the sweet spots in the market right now. So how do you approach the business with customers? Do you, are you a specialist around data protection? You deliver services around them. Maybe you can explain it on the model? >> Yeah, you know, that's actually a good question, because it's evolved quite a bit, right? So, you know, when you had a limited portfolio of just one or two products that you can sell to a customer, you're really doing a product sale, right, which, I would say that was probably the most difficult transition from the split from Symantec to Veritas, because at Symantec we had thousands of products in the portfolio, or hundreds of products in the portfolio that we could actually talk to. And for a little while, really we had a handful, you know, we had NetBackup Appliances, Enterprise Vault and ancillary things to bulk on to that, like Clearwell. I think one of the most exciting things for us, as a reseller, is to now be able to go have a discussion with our customers that we were never able to have before. And rather than sit there and try to sell them a backup product or a storage solution, we could sell them a platform that solves many problems for them, right? Rather than sitting there and trying to sell one-off. So, our conversations are significantly more strategic now then they've ever been, and frankly I speak for myself and my whole team, I know everyone enjoys the conversation more now that we have a portfolio to talk about, than just a handful of products. >> Angelo, you've got an interesting viewpoint on this split off of Aritas from Symantec. What have your customers said about it? What's been your interaction with the organization? What can you tell us about kind of the inside going on? >> Yeah, look, I've lived firsthand on a Symantec acquisition of a company, okay. I was, we were not a Symantec partner when they acquired Veritas. Funny enough, I was actually doing Veritas consulting, you know, on my own on the side prior to Symantec purchasing Veritas. So I really, I'd made my career on two products; Veritas for backup and Altiris for systems management. Symantec bought Veritas and I was like okay, you know, I'm just going to stay with Altiris. Symantec bought Altiris and here we are now, so we can talk about all of them. The thing I noticed was Symantec was always going to be a security company, right, and they weren't going to change that no matter how much they try to integrate it. It's two radically different stories. You know, and for many, many years, things that we look at as new products today were kind of already there in the Symantec portfolio, but buried underneath other products that really never saw the light of day because when you have hundreds or thousands of products, like I said earlier, you know, the ones that are going to move the most are the ones that are going to get the attention. So I think the benefit of the split is that it really allowed Veritas to focus on what they do well, which is managing data, and Symantec to do what they do well, which is securing your infrastructure and securing your data. From my perspective, our customers really appreciated that. Sure, a couple of them were a little annoyed that they had to now split contracts and deal with that kind of stuff, but I think that was a momentary blip and for the most part, it's been well-received from everyone we've spoken to. >> Angelo, you said you're having, your conversations are evolving. Who are you talking to? And maybe take us inside some of those conversations. What are the big challenges they're having? >> Yeah, a year ago, a year and a half ago I was talking to either somebody who was on the messaging side and needed to archive emails or IMs, or on the backup side and they just wanted to be able to meet their backup windows and maybe to get some better d dub rates, right. Fun conversation to have, bit mundane. It's not really solving problems as much as backing up data or archiving data. Today, we're having overarching conversations at a C-level, or a senior VP level, or a director level, and talking about dramatic changes to the way they do business, and how we can do business with them. Six months ago, NetX, we weren't doing anything in the Cloud, you know. We were selling to some customers' Vdub space to the Cloud, and that's about it. We weren't talking Cloud strategy with them. Today we're talking to our customers about moving workloads to the Cloud, doing it in a way that's predictable for them, and doing it with Veritas. >> That's a really interesting point. I have to imagine that changed who you're talking with inside the company. Can you walk us through kind of a typical customer's, you know, and how you kind of move up into a more strategic discussion for Cloud strategy? >> You know, so for full transparency, that whole thing's still evolving, right. 360 Data Management is still fairly new. So what we're seeing, the conversations turned, it would start, again we're talking to somebody that we've been talking to historically in the backup side or architecture side, and we talk to them about wanting to do better things than what their backup is, and start to talk about, hey this is what 360 Data Management is. What's relevant to that person he's going to want to talk about but then there's going to be things in there that are not relevant to him. So he'll make that introduction and he'll get other stakeholders in the boat with him. And that's something we've really appreciated because the people you used to talk to are now bringing in stakeholders to offset their own desires and their own budgets, so want to bring in other technology. And typically, when we get to that point when we're starting to talk about strategic pricing, is when you're getting that C-level person to really have that aha moment, and say wow, we're offsetting costs here, we're doing things like truly getting rid of tape, or moving to the Cloud and things like that, and it's a conversation that really evolves and it's still starts at the bottom. But we're figuring out ways to start it at a higher point. >> Well, those strategies are still evolving for most customers; the roles of those people that might have had one role definitely are changing. I'm curious, one of the big transition points, especially for a company like Veritas, is going from licenses to some kind of more of a subscription model. Any commentary you have on your customers; their embrace, or like, dislike of some of those transitions? >> I think the one thing the Cloud has done is it's opened up a different avenue of how people consume IT, right. Cloud is very much consumption-based billing, and while that can complicate our lives from a reseller perspective in terms of how to collect and track monthly billing and things like that, they like it because they feel like, and it's the truth, they're only paying for what they're truly using, rather than paying for products or infrastructure that they're only using part of the day, or software that they're only using for a particular project. A lot of our healthcare systems might have a research project that their going on, and they might like to scale up for some backup licensing and scale back down once that project is done. Consumption licensing allows that, versus having to go to them and saying, hey, well now you got to buy 200 terabytes of perpetual licensing, and justify that capital expense, rather than having an operational expense on just that one particular workload that you have to back up for that one period of time. >> Angelo, Stu and I are always interested in the human capital management aspects of things, and you talked about, you went from sort of talking about having a conversation around email archiving or backup, to one about the Cloud, Cloud strategies. From your internal organization perspective, how did you manage that? Are you rescaling, are you retraining? Is it just you got really supersmart people that can adapt? >> We definitely have supersmart people, because they're all over there, that's right. But I definitely have supersmart people. But, you know, it's a little bit of both. It's a little bit of, you know, you take one of our data protection projects; see Christian Muma, you know, he's been in the data center for god knows how many years, he has seen technology evolve. It was a natural fit to look at Cloud infrastructure. Started taking some classes, consumed it, all the information he could, and now we're out there actively selling it. In some other respects, we had to hire from outside and bring in some services ourselves to actually use, maybe some third party partnerships to help us better understand how we price out Cloud for our customers. So it's a little bit of everything, and I think that that's what's exciting about it, because I think for the first time in a long time, everyone's learning something new at the same time, because, I don't care what anyone said about the Cloud years ago; it's different today, it's going to be different in six months, it's going to be different in nine months. And I think that that's exciting, and I've been in this industry since 1996. I've seen a lot of really cool things come and go. I just think that there's still infancy in the Cloud and I think it's exciting because everyone's still learning. And any time you can still learn, I think that's, I think an important part of your job. >> So when you think about your, sort of, near-term and midterm and long-term plan for the company, how do you sort of describe that? Where do you want to take this thing? >> Near-term, I want to have a solid end of the quarter. >> Business is good, right, I mean market's booming right now. >> Business is very good. Veritas will tell me it's not good enough but they're just never happy. No, business is, business is very good. I think, near-term for us, you said hey, how do we get our head around it? Near-term for us is, as we're absorbing all this information, is start to really figure out what our path is going to be. So near-term, I think we still have to identify other ancillary partners that we need to bring to the table. We've got our partnerships with Azure, Microsoft Azure, and our partnerships with AWS. We'll probably have to look at Google and IBM and see what they're doing, and then we have to look at other partnerships that are not related to Veritas but still drive that home. We maybe look at a different colo partnership or partnerships around outsourcing billing, things like that, that we can make where it's easier for our customers to consume the technology. So I think six to nine months from now if we were to have the same conversation, everything that we're doing today is probably going to be somewhat different. But I just think that there's still a lot of planning to do. >> Angelo, any feedback from your customers on what there's still on the to-do list from the vendors? We talked, you know, the strategy, Cloud's changing a lot, you know. What are some of the pinpoints that they said hey, if we could get this into the offering from Veritas or some of the others it would make our lives a lot easier. >> I mean, that's a tough question, because we're going to them now and changing the conversation already. You know, obviously they're always asking for different features, but I don't like to get into a feature conversation with the customers. I try to solve the problem. >> Dave: You're leading that conversation, is what you're saying. >> Yeah, I don't want to get into the weeds of talking about well, this widget does it at 50% and you do it at 48%. You know, I try to sit a little bit more macro. I think that one of the things our customers have asked us to do a better job at is figure out better ways to make it easier to consume the technology from budget perspective. So we're trying to figure that out now; 360 Data Management is a subscription, Veritas would like them sold in three years, we're trying to figure out ways to get creative with our customers on that. What's the right bundle, what's not the right bundle. One thing that I've noticed, and Veritas have been great at it, is we have to have some flexibility in terms of adding things in and make it seem like it's all part of that bundle. There's been some flexibility and I think that, because of that, we haven't hit that roadblock yet where, well, we really want this product in the bundle. Reality is that we'll work through that and try to add it in there, some way, shape or form, even if behind the scenes. >> The customers see you as the experts, and what we often see is that technology is the technology; it's pretty much understood. What's not understood by the customers is how to apply it to their business, and their business is changing so fast that it seems like they're looking to organizations like yours saying okay, here's our business challenge. How can you help me? You tell me, and then the best answer is somebody he'll be able to work with. Is that a valid, sort of, premise? >> Yeah, it is, it certainly is and I think we're really uniquely positioned in the fact that, here we've got, we've got our partnership with Veritas and we're 100% focused to everything in the Veritas portfolio so we don't compete from within. That's the same thing that we could say, basically, on Symantec and some of our traditional storage partners as well. That'll change most likely, on our storage partners, especially because of what Veritas have been releasing with Access and some of the other software providing storage technology. When we're brought in, we're brought in as the experts in that finite area, so we're not brought in as a generalist-type of reseller. We're brought in as, hey, I've got a data management problem, I've got a data security problem, or I'm trying to do some high-performance workloads on storage. So yeah, we are the experts, but at the same time we're being brought in for those handfuls of things, so we're not having these, hey, can you maximize my span on anti-virus software because I want to sell you commoditized software. It's just not us, it's not our thing. We're not adding any value to the customers, or the poor owners for that matter. >> Angelo, curious that there's a lot of startups in the data protection space. What do you here, your customers asking you about them? You know, what's your thoughts there? >> I guess I got to be nice, right? Because I'm being streamed everywhere. >> Stu: They're not listening, go ahead, be a New Yorker. >> Listen, I challenge Rubrik at any point of time, you know, those guys, Rubrik, Cohesity, those guys, they're new, they're the shiny new toy. The problem, the problem is they have their messaging out there, and the problem we have is that they're the shiny new toy. But when the rubber hits the road and when it's time to actually go and prove out what the technology can do, we'll win all the time. We will win ten out of ten times if we get the seat at the table, right. The problem is is because we were a limited portfolio, a limited product, limited integration type of company before, we weren't getting that seat at the table. I think they see it now, I think they're starting to get a little concerned about, hey, you know what, if this 360 Data Management is what it's going to be, and we all know it is, I think they're going to be concerned. They're new, and they're going to get attention. My honest opinion: I'm glad they came out, I'm glad that Rubrik and Cohesity and all these guys came out and did all this different ways to go to market, because I think it really forced all of us to say hey, we got some real tough decisions to make here, the competition has caught up, in certain ways. Let's change the game, and 360 Data Management does that. I think they should take as much business as they can right now, because it's going to be short-lived. >> You said it makes you rethink your strengths, and like you said, change the game. >> Yeah, it changes the game. >> Yeah. Uh, okay, predictions on the MLB? Yankees won their getaway game today to put the pressure on the Red Sox, two and a half to two and a half games back. You know, the Indians are looking good, my man, Terry Francona. What's your prediction for it? >> The Sox fan's outnumbered two to one here, so go ahead. >> You know, so I shouldn't say that the Yankees are going to win the World Series? >> No, he's a Yankees fan. >> I'm a Yankee fan, too. >> Honestly, as a Yankee fan, I think we all know that they weren't supposed to be this team, so I think this is, that's the team to look out for. >> Dave: Maybe this is their year. >> I think this is the year that they're going to challenge people, I mean, are they going to win? It's Cleveland, do you really think Cleveland's going to win anything? They won one thing in the last, what, 30 years. >> That's what they used to say about us in Boston. Angelo, thanks so much coming on, really appreciate it. Keep right there, buddy, we'll be back with our next guest right after this short break. We're live from-- (electronic music)

(mid-tempo music) >> Announcer: Live, from Los Angeles, it's The Cube. Covering Open source Summit North America 2017. Brought to you by the Linux Foundation and Red Hat. >> Okay welcome back and we're live in Los Angeles for The Cube's exclusive coverage of the Open Source Summit North America. I'm John Furrier, my co-host Stu Miniman, Our next guest is Steve Pousty, who's the Director of Developer Advocacy for Red Hat, Cube alumni, we last spoke at the Cisco Devnet Create, which is their new kind of cloud-native approach. Welcome Back. >> Thank you, thank you, glad to be here. >> We're here at the Open Source Summit, which is a recognition that of all these kind of ... With LinuxCon, all these things, coming events, it's a big ten event, love the direction, >> Yeah Validation to what's already happened and the recognition of open source, where Linux is at the heart of all that, Red Hat also you guys are the Linux standard, and gold standard, but there's more- >> We like to think of it that way, but- >> But there's more than Linux on top of it now, so this is a recognition that open source is so much more. >> For sure, I'm mean you can even see ... Who would've thought that there'd be a whole huge hubbub about Facebook doing a separate license for their react libraries and all the interactions with Apache, the Apache Foundation. Open source is so much ... it's the mainstream now. Like, basically, it's very hard to release a proprietary product right now and come up with some justification about why you have to do it. >> And why, and can it even be as good. >> Steve: Right. >> There's two issues, justification and performance. >> Yeah, quality, all that stuff. And also, customers' acceptability of that. Like, "Oh wait, you mean I can't actually even see the code? "I can't modify the code, I can't pay you to modify the code "and share it with everybody else?" I think customers have come to a whole ... Users of open source stuff, it's so permeated now that I think it's hard to be in the market without ... I mean, look at everybody who's here. Some of the people that are here were some of the biggest closed source people before. >> John: Microsoft is here. >> Exactly. >> John: IBM is here, although they've always been open, they were big on Linux early on. >> Yes. >> But now you're seeing the ecosystem grow, so we see some scale coming, but there's still a lot of work that needs to get done. We see greatness, like Kubernetes and Serverless offering great promise and hope for either multi-cloud workflow, workload management, all those cool stuff. But there's still some work to be done. >> Steve: For sure. >> What's your take on progress, where are we, what's the ... some of those under the hood things that need to get worked on? >> Well so, progress, I think ... the funny part is our expectations have changed so much over time that, so Kubernetes is about a little over two years old, and we're all like, oh it's moving so s-- why is it not doing this, this, and this? Whereas if this was like 10 years ago, the rate at which Kubernetes is moving is phenomenal. So, basically, every quarter there is a new release of Kubernetes, and we basically built OpenShift as a distribution on top of Kubernetes, and so we're delivering to our customers every quarter as well, and a bunch of them are like, "This is too fast, this is too fast, "like, we can't integrate all these changes." But at the same time, they say, "But don't slow down." Because, "Oh, next release we're going to get this thing "that we want and we know we want to go to that release." So, I think Kubernetes definitely has more growing room, but the thing is, how much it's already being seen as the standard, it's the ... so the way I like to talk about it, and I'll talk about this in my talk later, I think for Red Hat, Kubernetes is the cloud Linux kernel. It's the exact same story all over again. It's this infrastructure that everybody's going to build on. Now there are people who are standing up OpenStack on Kubernetes, or on OpenShift. So basically saying, "I don't want to install and manage "my Openstack, it's too difficult. "Give me some JSON and some components "and I'll just use Kubernetes as my operating plane." >> We saw Kubernetes right out of the gates, Stu and I, at the first Cube-Con, we were present at creation, and just on the doorstep of that thing just unfolded, and we saw the orchestration piece is huge, but I want to get your take if you can share with the audience, why Kubernetes has taken the world by storm. Why is it so relevant? What's all the hubbub about with Kubernetes? Share your opinion. >> Okay, so remember ... okay so this is a red shirt, and remember I work at Red Hat, so this obviously a biased opinion. I want to be up front about that. >> John: In your biased opinion ... >> Right, well as opposed to a neutral opinion, right, we definitely, so, I say that in front of my audiences just so that ... go do your own research, but from my perspective and what I've seen in the market place, there was a lot of orchestration and scheduling out there, then it kind of narrowed down, there's three players I would say right now. The three players all end with Kubernetes, but I just started with it (laughs). There's Kubernetes, there is Mesosphere, and there's Docker Swarm. I see those as being the three that are out there right now. And I think the reason we're ... So I won't talk about the others, but I see those ... Why Kubernetes has won is, one, community. So they have done a great job of being upstream, working with all people, being a very open community, open to working with others, not trying to make things just so it benefits Google's business but to benefit everybody. The other reason is the size of that community, right, everybody working together. The third is I think they, so some of it's luck, right? >> John: Yeah, timing is everything. >> Timing is everything. >> John: You're on a wave, and you're on your board and a big wave comes, you surf it, right? >> That's exactly, so I think what happened with Mesosphere is they're a great scheduler, and a lot of people said they were the best scheduler to start with. But they didn't really focus on containers to start with and it seems like they missed ... Like, Kubernetes said, "No, it's all about containers "and we're going to focus on container workload." And that's right where everybody else was. And so it was like, "I don't want to write "all that extra stuff from Mesosphere. "I want to do it with Kubernetes 'cause that's containers." And so that's the bit of luck lining up with the market. So I'd say it's the community but also recognizing that it's about containers to start with and containers are kind of taking over. >> Yeah, Steve, take us inside containers. You're wearing a shirt that says "Linux is Containers" on the front, if our audience could see the back it says "Containers are Linux." >> Steve: Exactly. >> Of course, Red Hat heavily involved. You're in the weeds, dealing with things that we're doing to make stability of containers, make sure it works in other environments. Tell us some of the things you're working on, some of the projects, and the like. >> So, some of the projects I'll be showing today, one is based off of OpenScap, Open S-C-A-P, it's another open consortium for scanning for vulnerabilities. We've written something called Atomic Scan, so it can take any OpenScap provider, plug it in to Atomic Scan, and you can scan a container image without having to actually run it. So, you don't actually have to start it up, it actually just goes in. The other thing I'm going to be talking about today is Bilda, this is part of the CNCF stuff. This is the ability to actually build a runC-compatible container without ever using Docker or MOBI. The way, a totally different approach to it, what you basically do is you say, "I want this container from this other container, or from blank," then you have a container there and then you actually mount the file system. So rather than actually booting a container and doing all sorts of steps in the container itself, you actually mount the file system, do normal operations on your machine like it was your normal file system, and then actually commit at the end. So it's another way for some of our customers that really like that idea of how they want to build and manage containers. But also, there's a bunch more. There's Kryo, which is the common runtime interface, and the implementation of it, so that Kubernetes can now run on an alternative container technology. This is Kryo, it's agnostic. If you looked at Kelsey Hightower's latest "Kubernetes and Anger," I think, or "Kubernetes the Hard Way" or something. His latest is building it all on Kryo. So rather than running on Docker, it runs ... All your container running happens on Kryo. I'm not trying to say, well of course I think it's better, but I think the point that we're really seeing is, by everything moving in to CNCF and the Linux Foundation and getting around standards, it's really enabled the ecosystem to take off. Like, TekTonic and CoreOS have done that with Rocket. We're going to see a lot more blossoming. The fertilizer has been applied, back from our ... >> Yeah, CNCF of two years old, I mean their fertilizer down big time, you got the manure and all the thousand flowers are blooming from that. >> Yeah, between Prometheus, I mean just, Prometheus, Istio, there's just ... I can't even keep track of it all. >> So Steve, you were talking earlier. Customers are having a hard time with that quarterly release. >> Steve: Yes. >> How do they keep up with all these projects, I mean you know, we rattled through all of 'em. You've got 'em all down pat, but the typical customer, do they need to worry about what do they have to focus on, how do they keep up with the pace change, how do they absorb all of this? >> Okay so it highly depends on the customer. There are some customers who are not our customers, I'll just say users, who are advanced enough on their own, who they're out there basically just, they're consuming the tip of what's coming out of CNCF. All that stuff, and they're picking and choosing and they're doing that all. For Red Hat, a lot of our customers are, "I like all that technology, you're our trusted advisor, "when you release it as a product "and I know I can sit on it for three years, "because you'll support it for at least three years, "maybe five years, then I'm going to start to consume it "and you'll actually probably put it into a more usable form for me." 'Cause a lot of the upstream stuff isn't necessary made direct for consumption. >> How are you guys dealing with the growth prospects. We've been talking about this all morning, this has been the big theme of this show is, not only just the renaming of a variety of different events, LinuxCon, but Open Source Summit is an encapsulation of all the projects that are blossoming across the board. So, the scale issues, and as a participant, Red Hat, >> Steve: Yes. >> Your biased opinion, but you're also incentive and you guys are active in the community. The growth that's coming is going to put pressure on the system. It may change the relationship between communities and vendors and how they're all working together, so again, to use the river analogy, there's a lot of water going to be pumping through the system. And so how's that going to impact the ecosystem, is it going to be the great growth that could flood everything, is there a potential for that, I mean you're an ecosystem guy, so the theory is there, it's like, Jim's stepping up with the Linux Foundation. I talked to him yesterday and he recognizes it. >> Steve: Yeah. >> But he also doesn't want to get in the way, either. >> Steve: No, no, no- >> So there's a balance of leadership that's needed. Your thoughts. >> So, I mean I think one of the things ... So I mean you know the Linux kernel has its benevolent dictator, and that works well for that one community, but then you'll see something like Kubernetes, where it's much more of a community base, there is no benevolent dictator for life on Kubernetes. I think one of the nice things that the Linux Foundation has done, and which Red Hat has acknowledged is, you know, let the community govern the way that works for that community. Don't try to force necessarily one model on it. In terms of the flood part that you were talking about, I think, if you want to go back to rivers, there's cycles in terms of 10 year floods, 100 year floods, I think what we're seeing right now is a big flood, and then what'll happen out of this is some things will shake out and other things won't. I don't expect every vendor that's here to be here next year. >> And find the high ground, I mean, I mean the numbers that Jim shared in his opening keynote is by 2026, 400 million libraries are going to be out there versus today's 64 roughly million. >> Steve: Right. >> You know, Ed from Cisco thinks that's understated, but now there's more code coming in, more people, and so a new generation is coming on board. This is going to be the great flood in open source. >> I also think it's a great opportunity for some companies. I mean, I'm not high enough in Red Hat to know what we're doing in that space, but it's also a great opportunity for some companies to help with that. Like, I think, that's one of the other things that Linux Foundation did was set up the Javascript Foundation. That is a community that-- >> But that doesn't have Node.js, it's a little bit separate. >> No, I know, but think-- >> You're talking about the js, okay. >> But I'm talking about, but if you think about the client-side javascript, forget Node. Just think about client-side javascript and how many frameworks are coming up all the time, and new libraries. >> Stu: That's a challenge. >> So I think actually that community could be one that could be good to maybe gain some lessons from, as things happen more in open source. I think there are other open source communities. Like, I'm wondering like GNOME-- >> But the feedback on the js community is that there's a lot of challenges in the volume of things happening. >> And that's coming for us though, right? >> Yeah. >> That's what's coming, that's what's going to come for this larger ecosystem, so I think maybe there's market opportunity, maybe there's new governance models, maybe there's ... I mean, this is where innovation comes from. There's a new problem that's come, it's a good problem. >> Your next point of failure is your opportunity to innovate. >> Exactly, and it's a good problem to have, right, as opposed to, we have too few projects, and we don't really, no one really likes them. Instead, now it's like, we've got so many projects and people are contributing, and everybody's excited, how do we manage that excitement? >> So another dynamic that we're observing, and again we're just speculating, we're pontificating, we're opining ... is fashion. Fashion, fashionable projects. Never fight fashion, my philosophy is. In marketing, don't fight the fashion. >> Steve: Right. >> CNCF is fashionable right now, people love it. It's popular, it's trendy, it's the hip new night club if you will in open source. Other projects are just as relevant. So, relevance and trending sometimes can be misconstrued. How do you guys think about that, because this is a dynamic, everyone wants to go to the best party. There a fear of missing out, I'm going to go check out Kubernetes, but also relevance matters. >> Yes. >> John: Your thoughts. >> So I've seen this discussion internally in engineering all the time, when we're talking about, 'cause you know OpenShift is trying to build a real distribution, not like, "Oh here is Kubernetes," but a real distribution. Like when Red Hat ships you the Linux, gives you Linux, we don't just say, "Here's the Linux kernel, have a good time." We put a whole bunch of stuff around it, and we're trying to do that with Kubernetes as well, so we're constantly evaluating all the like, "Should we switch to Prometheus now, "when's the time to switch to Prometheus? "Oh it's trending really hot. "Oh but does it give us the features?" >> John: It's a balance. >> It's a balance, it's going to have to come down to, I hate to say it-- >> It's a community, people vote with their code, so if something has traction, you got to take a look at it. >> But I would say, and this has been going on for a while, and I've seen other people talk about it, if you are the lead on an open source project, and you want a lot of community, you have to get into marketing. You can't just do-- >> John: You got to market the project. >> You got to, and not in the nasty term of market, which is that I'm going to lie to you and like, what a lot of developers think about like, "Oh I'm just going to give you bullshit and lie to you, "and it's not going to be helpful." No, market in terms of just getting your word out there so at least people know about it. Lead with all your-- >> John: Socialize it. >> Yeah. I mean, that's what you got to get it, so there is a lot of chatter now. How do you get it noticed as a Twitter person, right? You have to do some, it's the same, it's going to be more like that for open source projects. >> John: So we're doing our share to kind of extract the signal from some of the noise out there, and it's great to talk to you about it because you help give perspective. And certainly Red Hat, you're biased, that's okay, you're biased. Now, take your Red Hat off. >> Okay. >> Hat off. Take your Red Hat hat off >> Steve: Propaganda hat off. >> and put your neutral hat on. An observation of Open Source Summit, I'll see that name change kind of significance in the sense it's a big ten event. This event here, what's your thoughts on what it means? >> Hey c'mon Steve, you've got a PhD in ecology, so we want some detailed analysis as to how this all goes together. >> I mean it's good marketing, Open Source Summit, good name change, little bit broader. >> I'm actually glad for it. So, I've gone to some other smaller events, and I actually like this, because it was hard for me to get to the smaller events, or to get quite enough people. Like this actually builds a critical mass, and more cross-fertilization, right, so it's much easier for me to talk to containers to car people. 'Cause automotive Linux is here as well, right? >> John: You can't avoid it, you see 'em in the hallways, you can say, "Hey, let's chat." >> "Let's talk about that stuff," whereas in the small ... So, you know, this is more about conferences. There's a good side and a bad side to everything, just like I tell my kids, "When you pick up a stick, you also have to pick up the other end of the stick." You can't just like have, "Oh this is a great part," but you don't get the bad part. So the great part about this, really easy to see a lot of people, see a lot of interesting things that are happening. Bad part about this, it's going to be hard, like if this was just CNCF, everybody here would be CNCF, all the talks would be CNCF, it's like you could deep dive and really go. So, I think this is great that they have this. I don't think this gets, should get rid of smaller, more focused events. >> Well at CubeCon, our CubeCon, the CNCF event in Austin, we'll be there for The Cube. That will be CNCF all the time. >> Steve: Exactly. I'm glad they're still doing that. >> So they're going to have the satellite event, and I think that's the best way to do it. I think a big ten event like this is good because, this is small even today, but with the growth coming, it'll be convention hall size in a matter of years. >> Well, exactly, and the fact that you made it into a big, and the fact that you've made it into this cohesive event, rather than going to somebody and saying, "Hey, sponsor these five events." Like, No. Sponsor this one big event, and then we'll get most of the people here for you. >> It's also a celebration, too. A lot of these big ten events are ... 'Cause education you can get online, there are all kinds of collaboration tools online, but when you have these big ten events, one of the rare things is it's the face to face, people-centric, in the moment, engagement. So you're learning in a different way. It's a celebration. So I think open source is just too important right now, that this event will grow in my opinion. >> Steve: For sure. >> Bring even thousands and thousands of people. >> I mean, another way-- >> John: 30,000 at some point, easily. >> Yeah, I think definitely it's theirs to lose, let's put it that way. >> John: (laughing) I'll tell that to Jim "Hey, don't screw it up!" >> Don't screw it up. I think the way that you could almost think of this is OSS-Con, right, instead of Comic-Con, this is like, this can become OSS-Con, which is like, they should probably ... In the same way that the Kubernetes Foundation works and grows with a lot of other people, it would be great if they could bring in other Foundations as well to this. I know this is being run by the Linux, but it'd be great if we could get some Apache in here, some Eclipse in here, I mean that would just be-- >> John: A total home run. >> Those foundations bringing it in-- >> That would truly make it an open source summit. >> Yeah, exactly, as opposed to the World Series that's only in the United States. >> Yeah. (laughing) >> Although you know, I was at a hotel recently, and they had baseball on, it was little league baseball though. Their World Series is actually, Little League World Series is actually the World Series. >> John: It's a global World Series. >> Yeah, like their-- >> John: It's the world. >> Yeah, as opposed to the MLB, right? >> Alright, Steve, great to have you on, any final thoughts on interactions you've had, things you've learned from this event you'd like to share and pass on? >> No, I just think the space is great, I'm really excited to be in it. I'm starting to move a little bit more up to the application tier at my role at the company and I'm excited about that, to actually ... So I've been working down at the container tier, and orchestration tier for a while, and now I'm excited to get back to like, "Well now let's actually build some cool stuff "and see what this enables on the up--" >> And DevOps is going mainstream, which is a great trend, you're starting to see that momentum beachhead on the enterprises, so-- >> Oh, one takeaway message, for microservices people, please put an Ops person on your microservice team. Usually they start with the DBA, and then they say the middle person and the front-end people. I really want to make sure that they start including Ops in your microservice teams-- >> John: And why is that, what'd you learn there? >> Well because if you're going to do microservices, you're going to be, the team's going to end up doing Ops-y work. And it's kind of foolish not to bring in someone who already knows ... The reason you want all the team together is because they're going to own that. And you also want them to share knowledge. So, if I was on a microservice team, I would definitely want an Ops person teaching me how to do Ops for our stuff. I don't want to reinvent that myself. >> You got to have the right core competencies on that team. >> Steve: Yeah. It's like having the right people in the right position. >> Steve: Exactly. >> Skill player. >> Steve: Yeah, exactly. Okay we're here live in Los Angeles, The Cube's coverage of Open Source Summit North America. I'm John Furrier, Stu Miniman. More live coverage after this short break. (electronic music)

>> Narrator: Live from Washington D.C. it's the CUBE covering the AWS Public Sector Summit 2017. Brought to you by the Amazon web services and its partner Ecosystem. >> Melvin Greer is with us now he's the director of Data Science and Analytics at Intel. Now Melvin, thank you for being here with us on the CUBE. Good to see you here this morning. >> Thank you John and John I appreciate getting a chance to talk with you it's great to be here at the AWS Public Sector Summit. >> Yeah we make it easy for you. >> I never forget the names. >> John and John. Let's talk just about data science in general and analytics I mean tell us about, give us the broad definition of that. You know the elevator speech about what's being done and then we'll drill down a little bit deeper about Intel and what you're doing with in terms of government work and healthcare work. >> Sure well data science and analytics covers a number of key areas and it's really important to consider the granularity of each of these key areas. Primarily because there's so much confusion about what people think of as artificial intelligence. It's certainly got a number of facets associated with it. So we have core analytics like descriptive, diagnostic, predictive and prescriptive. This describes what happened, what's going to happen next, why is it happening and what should I do about it. So those are core analytics. >> And (mumbles) oh go ahead. >> And a different tech we have machine learning cognitive computing. These things are different than core analytics in that they are recognizing patterns and relying on the concepts of training algorithms and then inference. The use of these trained algorithms to infer new knowledge. And then we have things like deep learning and convolutional neuro networks which use convolutional layers to drive better and better granularity and understanding of data. They often typically don't rely on training and have a large focus area around deep learning and deep cognitive skills. And then all of those actually line up in this discussion around narrow artificial intelligence and you've seen a lot of that already haven't you john? You've seen where we teach a machine how to play poker or we teach a machine how to play Jeopardy or Go. These are narrow AI applications. When we think about general AI however, this is much different. This is when we're actually outsourcing human cognition to a thinking machine at internet speed. >> This is amazing I love this conversation cause couple things, in that thread you just brought up is poker which is great cause it's not just Jeopardy it's poker is unknown conditions. You don't know the personality of the other guy. You don't know their cards their dealing with so it's a lot like unstructured data and you have to think about that so but it really highlights the (mumbles) between super computing paradigm and data and that really kind of changes the game on data science cause the old data warehouse model storing information, pulling it back, latency, and so we're seeing machine learning in these new aps really disrupting old data analytics models. So, I want to get your thoughts on this because and what is Intel doing because you guys have restructured things a bit differently. The AI messages out there as this new revolution takes place with data, how are you guys handling that? >> So Intel formed in late 2016 its artificial intelligence product group and the formation of this group is extremely consistent with our pivot to becoming a data company. So we're certainly not going to be abandoning any of that great performance and strong capabilities that we have in silicon architectures but as a data company it means that now we're going to be using all of these assets in artificial intelligence, machine learning cognitive computing and Intel in fact by using this is really in a unique position to focus on what we have termed and what you'll hear our CEO talk about as the virtuous cycle of growth. This cycle of growth includes cloud computing, data center, and IOT. And our ability to harness the power of artificial intelligence in data science and analytics means that Intel is really capable of driving this discussion around cloud computing and powering the cloud and also driving the work that's required to make a smart and a connected world a reality. Our artificial intelligence product group expands our portfolio and it means that we're bringing all these capabilities that I talked to you that make up data science and analytics. Cognitive, machine learning, artificial intelligence, deep learning, convolutional neuro networks, to bare to solve some of the nation's most significant and important problems and it means that Intel with its partners are really focused on the utilization of our core capabilities to drive government missions. >> Well give us an example then in terms of federal government NAI. How you're applying that to the operation of what's going on in this giant bureaucracy of a town that we have. >> So one of the things that I'm most excited about it that there's really no agency almost every federal agency in the U.S. is doing an investigation of artificial intelligence. It started off with this discussion around business intelligence and as you said data warehousing and other things but clearly the government has come to realize that turning data into a strategic asset is important, very very important. And so there are a number of key domain spaces in the federal government where Intel has made a significant impact. One is in health and life sciences so when you think about health and life sciences and biometrics, genomics, using advanced analytics for phenotype and genotype analysis this is where Intel's strengths are in performance in the ability to deliver. We created a collaborative cancer cloud that allows researches to use Intel hardware and software to accelerate the learnings from all of these health and life sciences advances that they want. Sharing data without compromising that data. We're focused significantly on cyber intelligence where we're applying threat and vulnerability analytics to understanding how to identify real cyber problems and big cyber vulnerabilities. We are now able to use Intel products to encrypt from the bios all the way up through the application stack and what it means is, is that our government clients who typically are hyper sensitive around security, get a chance to have data follow their respective process and meet their mission in a safe and secure way. >> If I can drill down on that for a second cause this is kind of a really sweet area for innovation. Data is now the new development environment the new development >> You said Bacon is the Oil is the new bacon (laughing) >> Versus the gold nuggets so I was talking with >> You hear what he said? >> No. >> It's the new bacon. >> The new bacon (laughs) love that. >> Data's the new bacon. >> Everyone loves bacon, everyone loves data. There's a thirst for the data and this also applies is that I ask you the role of the CDO, the chief data officer is emerging in companies and so we're seeing that also at the federal level. I want to get your thoughts on that but to quote the professor from Carnegie Mellon who I interviewed last week said the problem with a lot of data problems its like looking for a needle in the haystack with there's so much data now you have a haystack of needles so his premise is you can't find everything you got to use machine learning and AI to help with that so this is also going to be an issue for this chief data officer a new role. So is there a chief data officer role is there a need for that is there a CCO? Who handles the data? (laughing) >> Yeah so this is >> it's a tough one cause there's a lot a tech involved but also there's policies. >> Yeah so the federal government has actually mandated that each agency assign a federal chief data officer at the agency level and this person is working very closely with the chief information officer and the agency leaders to insure that they have the ability to take advantage of this large set of data that they collect. Intel's been working with most of the folks in the federal data cabinet who are the CDO's who are working to solve this problem around data and analysis of data. We're excited about the fact that we have chief data officers as an entry point to help discuss this hyper convergence that you described in technology. Where we have large data sets, we have faster hardware, of course Intel's helping to provide much of that and then better mathematics and algorithms. When we converge these three things together it's the soup that makes it possible for us to continue to drive artificial intelligence but that not withstanding federal data officers have a really hard job and we've been engaging them at many levels. We just had our artificial intelligence day in government where we had folks from many federal agencies that are on that cabinet and they shared with us directly how important it is to get Intel's on both hardware, hardware performance but also on software. When we think about artificial intelligence and the chief data officer or the data scientist this is likely a different individual than the person that is buying our silicon architectures. This is a person who is focused primarily on an agency mission and is looking for Intel to provide hardware and software capabilities that drive that mission. >> I got to ask you from an Intel perspective you guys are doing a lot of innovative things you have a great R and D group but also silicon you mentioned is important and you know software is eating the world but data's eating software so what's next what's eating data? We believe it's memory and silica and so one of the trends in big data is real time analytics is moving closer and closer to memory and then and now silicon who have some of those security paradigms with data involved seeing silicon implementations, root security, malware, firmware, kind of innovations. This is an interesting trend cause if software gets on to the silicon to the level that is better security you have fingerprinting all kinds of technologies. How is that going to impact the analytics world? So if you believe that they want faster lower latency data it's going to end up in the silicon. >> John you described exactly why Intel is focused on the virtuous cycle of growth. Because as more cloud enabled data moves itself from the cloud through our 5g networks and out to the edge in IOT devices whether they be autonomous vehicles or drones this is exactly why we have this continuum that allows data to move seamlessly between these three areas and operationalizes the core missions of government as well as provides a unique experience that most people can't even imagine. You likely saw the NBA finals you talked about Kevin Durant and you saw there the Intel 360 demonstration >> Love that! >> Where you're able to see how through different camera angles the entire play is unfolding. That is a prime example of how we use back end cloud hyper connected hardware with networks and edge devices where we're pushing analytics closer and closer to the edge >> by the way that's a real life media example of an IOT situation where it's at the edge of the network AKA stadium. I mean we geek out on that as well as Amazon has the MLB thing Andy (mumbles) knows I love that because it's like we're both baseball fans. >> We're excited about it too we think that along with autonomous vehicles, we think that this whole concept of experiences rather than capabilities and technologies >> but most people don't know that that example of basketball takes massive amounts of compute I mean to make that work at that level. >> In real time. >> This is the CG environment we're seeing with gaming culture the people are expecting an interface that looks more like Call of Duty (laughing) or Minecraft than they are Windows desktop machines what we're used to. We think that's great. >> That's why we say we're building the future John. (men laughing) >> You touched on something you said a little bit ago. A data officer of the federal government has got a tough job, a big job. >> Yes. >> What's the difference between private and public sector somebody who is handling the same kinds of responsibilities but has different compliance pressures different enforcement pressures and those kinds of things so somebody in the public space, what are they facing that somebody on the other side of the fence is not? >> All data officers have a tough job whether it's about cleansing data, being able to ingest it. What we talk about, and you described this, a haystack of needles is the need and ability to create a hyper relevancy to data because hyper relevancy is what makes it possible for personalized medicine and precision medicine. That's what makes it possible for us to do hyper scale personalized retail. This is what makes it possible to drive new innovation is this hyper relevancy and so whether you're working in a highly regulated environment like energy or financial services or whether you're working in the federal government with the department of defense and intelligence agencies or deep space exploration like at NASA you're still solving many data problems that are in common. Of course there are some differences right when you work for the federal government you're a steward of citizen's data that adds a different level of responsibility. There's a legal framework that guides how that data's handled as opposed to just a regulatory and legal one but when it comes to artificial intelligence all of us as practitioners are really focusing on the legal, ethical, and societal implications associate with the implementation of these advanced technologies. >> Quick question end this segment I know we're a little running over time but I wanted to get this last point in and this is something that we've talked on the CUBE a lot me and Dave have been debating because data is very organic innovation. You don't know what your going to do until you get into it, alchemy if you will, but trust and security and policy is a top down slow down mentality so often in the past it's been restricting growth so the balance here that you're getting at is how do you provide the speed and agility of real time experiences while maintaining all the trust and secure requirements that have slowed things down. >> You mention a topic there John and in my last book, 21st Century Leadership I actually described this concept as ambidextrous leadership. This concept of being able to do operational excellence extremely well and focus on delivery of core mission and at the same time be in a position to drive innovation and look forward enough to think about how, not where you are today but where you will be going in the future. This ambidexterity is really a critical factor when we talk about all leadership today, not just leaders in government or people who just work mostly on artificial intelligence. >> It's multidimensional, multi disciplined too right I mean. >> That's right, that's right. >> That's the dev opps ethos, that's the cloud. Move fast, I mean Mark Zuckerberg had the best quote with Facebook, "move fast and break stuff" up until that time he had about a billion users and then changed to move fast and be secure and reliable. (laughing) >> Yeah and don't break anything >> Well he understood you can't just break stuff at some point you got to move fast and be reliable. >> One of five books I want to mention by the way. >> That's right I'm working on my sixth and seventh now but yeah. >> And also the managing of the Greer Institute of Leadership and Management so you've written now almost seven books, you're running this leadership, you're working with Intel what do you do in your spare time Melvin? >> My wife is the chef and >> He eats a lot. (laughing) >> And so I get a chance to chance to enjoy all of the great food she cooks and I have two young sons and they keep me very very busy believe me. >> I think you're busy enough (laughing). Thanks for being on the CUBE. >> I very much appreciate it. >> It's good to have you >> Thank you. >> With us here at the AWS Public Sector Summit back with more coverage live with here on the Cube, Washington D.C. right after this.