(upbeat music) >> Okay, welcome back everyone. The cube coverage of AWS re:Mars, 2022. I'm John Furrier, host of theCUBE. We got Eric Foellmer, vice president of marketing at Boston Dynamics. Famous for Spot. We all know, we've seen the videos, zillion views. Mega views all over the internet. The dog robotics, it's famous. Rolls over, bounces up and down. I mean, how many TikTok videos are out there? Probably a ton. >> Oh, Spot is- Spot is world famous (John laughs) at this point, right? So it's the dance videos, and all the application videos that we have out there. Spot is become has become world famous. >> Eric, thanks for joining us on theCUBE here at re:Mars. This show really is back. There was still a pandemic hiatus there. But it's not a part of the re's. It's re Mars, reinforcement of security, and then reinvent the flagship show for AWS. But this show is different. It brings together a lot of disciplines. But it's converging in on what we see as the next general- Industrial space is a big poster child for that. Obviously in space, it's highly industrial, highly secure. Machine learning's powering all the devices. You guys have been in this, I mean a leader, in a robotics area. What's this show about? I mean, what's really happening here. What if you had to boil the essence of the top story of what's happening here? What would it be? >> So the way that I look at this show is it really is a convergence of innovation. Like this is really just the cutting edge of the innovation that's really happening throughout robotics, but throughout technology in general. And you know, part of this cultural shift will be to adopt these types of technologies in our everyday life. And I think if you ask any technology specialist here or any innovator here or entrepreneur. They'll tell you that they want their technologies to become ubiquitous in society, right? I mean, that's really what everyone is sort of driving towards from the perspective of- >> And we, and we got some company behind it. Look at this. >> Oh, there we go. >> All right. >> There's a (Eric laughs) There's one of our Spots. >> It's got one of those back there. All right so sorry to interrupt, got a little distracted by the beautiful thing there. >> So they're literally walking around and literally engulfing the show. So when I look at the show, that's what I see. >> Let's see the picture of- >> I see the future of technology. >> Get a camera on our photo bomb here going on. Get a photo bomb action. (Eric chuckles) It's just super exciting because it really, it humanizes, it makes you- Everyone loves dogs. And, you know, I mean, people have more empathy if you kicked Spot than, you know, a human. Because there's so much empathy for just the innovation. But let's get into the innovation because let's- The IOT tech scene has been slow. Cloud computing Amazon web services, the leader hyper scaler. They dominated the back office you know, data centers, all the servers, digital transformation. Now that's coming to the edge. Where robotics is now in play. Space, material handling, devices for helping people who are sick or in healthcare. >> Eric: Mhm. >> So a whole surge of revolutionary or transitionary technologies coming. What's your take on that? >> So I think, you know, data has become the driving force behind technology innovation. And so robotics are an enabler for the tech, for the data collection that is going to drive IOT and manufacturing 4.0 and other important edge related and, you know, futuristic technology innovations, right? So the driver of all of that is data. And so robots like Spot are collectors of data. And so instead of trying to retrofit a manufacturing plant, you know, with 30, 40, 50 year old equipment in some cases. With IOT sensors and, you know, fixed sensors throughout the network. We're bringing the sensors to the equipment in the form of an agile mobile robot that brings that technology forward and is able to assess. >> So explain that a little slower for me. So the one method would be retrofitting all the devices. Or the hardware currently installed. >> Eric: Sure. >> Versus almost like having a mobile unit next to it, kind of thing. Or- >> Right. So, I mean, if you're looking at antiquated equipment which is what most, you know, manufacturing plants are running off of. It's not really practical or feasible to update them with fixed sensors. So sensors that specifically take measurements from that machine. So, we enable Spot with a variety of sensors from audio sensors to listen for audio anomalies. Thermal detectors, to look for thermal hotspots in equipment. Or visual detectors, where it's reading analog gauges, that sort of thing. So by doing that, we are bringing the sensors to the machines. >> Yeah. >> And to be able to walk anywhere where a human can walk throughout a manufacturing plant. To inspect the equipment, take that reading. And then most importantly upload that to the cloud, to the users >> It's a service dog. >> you can apply some- >> It's a service dog. >> It really is. And it serves data for the understanding of how that equipment is operated. >> This is big agility for the customer. Get that data, agile. Talk about the cost impact of that, just alone. What the alternative would be versus say, deploying that scenario. Because I'd imagine the time and cost would be huge. >> Well, if you think, you know, about how much manufacturing facilities put into the predictive maintenance and being able to forecast when their equipment needs maintenance. But also when pieces of equipment are going to fail. Unexpected downtime is one of the biggest money drains of any manufacturing facility. So the ability to be able to forecast and get some insight into when that equipment is starting to perform less than optimally and start to degrade. The ability to forecast that in advance is massive. >> Well I think you just win on just in retrofit cost alone, nevermind the downside scenarios of manufacturing problems. All right, let's zoom out. You guys have been pioneers for a long time. What's changed in your mind now versus just a few years ago. I mean, look at even 5, 10 years ago. The evolution, cost and capability. What's changed the most? >> Yeah, I think the accessibility of robots has really changed. And we're just on the beginning stages of that evolution. We really are. We're at the precipice right now of robots becoming much more ubiquitous in people's lives. And that's really our foundation as a company. Is we really want to bring robots to mankind for the good of humanity, right? So if you think about, you know, taking humans out of harm's way. Or, you know, putting robots in situations where, you know, where it's assessing damage for a building, for example, right. You're taking people out of the, out of that harm's way and really standardizing what you're able to do with technology. So we see it as really being on the very entry point of having not only robotics, but technology in general to become much more prevalent in people's lives. >> Yeah. >> I mean, what, you know. 30 years ago, did you ever think that you would have the power of a supercomputer in your pocket to, you know. Which also happens to allow you to talk to people but it is so much more, right? So the power of a cell phone has changed our lives forever. >> A computer that happens to be a phone. You know, it's like, come on. >> Right. >> What's going on with that. >> That's almost secondary at this point. (John laughing) It really is. So, I mean, when you think about that transition from you know, I think we're at the cusp of that right now. We're at the beginning stages of it. And it's really, it's an exciting time to be part of this. An entire industry. >> Before I get your views on integration and scale. Because that's the next level. We're seeing a lot of action and growth. Talk about the use case. You've mentioned a few of them, take people out of harms way. What have you guys seen as use cases within Boston Dynamics customer base and or your partner network around use cases. That either you knew would happen, or ones that might have surprised you? >> Yeah. One of the biggest use cases for us right now is what we're demonstrating here at re:MARS. Which is the ability to walk through a manufacturing plant and collect data off various pieces of equipment. Whether that's pump or a gauge or seeing whether a valve is open or closed. These are all simple mundane tasks that people are, that manufacturers are having difficulty finding people to be able to perform. So the ability for a robot to go over and do that and standardize that process is really valuable. As companies are trying to collect that data in a consistent way. So that's one of the most prevalent use cases that we're seeing right now. And certainly also in cases where, you know, Spot is going into buildings that have been structurally damaged. Or, you know, assessing situations where we don't want people to be in harm's way. >> John: Yeah. >> You know- >> Bomb scares, or any kind of situation with police or, you know, threatening or danger situations. >> Sure. And fire departments as well. I mean, fire departments are becoming a huge, you know, a huge user of the robots themselves. Fire department in New York recently just adopted some of our robots as well. For that purpose, for search and rescue applications. >> Yeah. Go in, go see what's in there. See what's around the corner. It gives a very tactical edge capability for say the firefighter or law enforcement. I see that- I see the military applications must be really insane. >> Sure. From a search and rescue perspective. Absolutely. I mean, Spot helps you put eyes on situations that will allow a human to be operating at a safe distance. So it's really a great value for protecting human life and making sure that people stay out of harm's way. >> Well Eric, I really appreciate you coming on theCUBE and sharing your insight. One other question I'd like to ask if you don't mind is, you know. The one of the things I see next to your booth is the university piece. And then you see the Amazon, you know, material management. I don't know what to call it, but it's pretty impressive. And then I saw some of the demos on the keynotes. Looking at the scale of synthetic data. Just it's mind blowing what's going on in manufacturing. Amazon is pretty state of the art. I'm sure there are a customer of yours already. But they look complex these manufacturing sites. I mean, it looks like a maze. So how do you... I mean, I could see the consequences of something breaking, to be catastrophic. Because it's almost like, it's so integrated. Is this where you guys see success and how do these manufacturers deal with this? What's the... Is it like one big OS? >> Yeah, so the robots, because the robots are able to act independently. They can traverse difficult terrain and collect data on their own. And then, you know, what happens to that data afterwards is really up to the manufacturing. It can be delivered from the cloud and you can, it can be delivered via the edge. You know, edge devices and really that's where some of the exciting work is being done right now. Because that's where data can scale. And that's where robot deployments can scale as well, right? So you've got instead of a single robot. Now you have an operator deploying multiple robots. Monitoring, controlling, and assessing the data from multiple robots throughout a facility. And it really helps to scale that investment. >> All right, final question for you. This is personal question. Okay, I know- Saw your booth over there. And you have a lot of fan base. Spot's got a huge fan base. What are some of the crazy things that these nerd fans do? I mean, everyone get selfies with the Spot. They want to- I jump over the fence. I see, "Don't touch the dog." signs everywhere. The fan base is off the charts. What are the crazy things that people do to get either access to it. There's probably, been probably some theft, probably. Attempts, or selfies. Share some funny stories. >> I'll say this. My team is responsible for fielding a lot of the inbound inquiries that we get. Much of which comes from the entertainment industry. And as you've seen Spot has been featured in some really prominent, you know, entertainment pieces. You know, we were in that Super Bowl ad with Sam Adams. We were on Jimmy Kimmel, you know, during the Super Bowl time period. So the amount of entertainment... >> Value >> Pitches. Or the amount of entertainment value is immeasurable. But the number of pitches that we turn down is staggering. And when you can think about how most companies would probably pull out all the stops to take, you know. To be able to execute half the things that we're just, from a time perspective, from a resource perspective >> Okay, so Spots an A- not always able to do. >> So Spots an A-lister, I get that. Is there a B-lister now? I mean, that sounds like there's a market developing for Spot two. Is there a Spot two? The B player coming in? Understudy? >> So, I mean, Spot is always evolving. I think, you know, the physical- the physical statue that you see of Spot right now, Is where we're going to be in terms of the hardware, but we continue to move the robot forward. It becomes more and more advanced and more and more capable to do more and more things for people. So. >> All right. Well, we'll roll some B roll on this, on theCUBE. Thanks for coming on theCUBE. Really appreciate it. Boston Dynamics here in theCUBE, famous for Spot. And then here, the show packed here in re:MARS featuring, you know, robotics. It's a big feature hall. It's a set piece here in the show floor. And of course theCUBE's covering it. Thanks for watching. More coverage. I'm John Furrier, your host. After the short break. (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)

from Boston Massachusetts it's the cube covering wtg transform 2018 brought to you by Winslow technology group welcome back I'm Stu minimun and you're watching the cube at wtg transform 2018 happy to welcome to the program two gentlemen from the Boston Architectural College to my left is Carl Jasperson who is the systems administrator and to his left is Jason O'Brien who's the director of IT gentlemen thanks so much for joining us thank you for having us all right so Jason why don't we start with you help us power up this conversation to tell us a little bit about the college so Boston Architectural college we started in the late 1800s it's a small design at school and we offer programs in landscape interior and traditional architecture yeah so I love that to talk to a little bit more about you know that the charter of the school and how IT fits into that so we we are a mission of the schools to provide excellent education to a diverse population technology factors in is very important and over the last ten years the Carll I've been at the school technology has use has increased immensely our students are using it more and more every year and meeting those needs has become you know difficult and it's a challenge we we strive to achieve every year well Design Thinking is is so important these days I I studied engineering as an undergrad in which I've learned more about design one of my favorite authors so I have an interview about a month ago Walter Isaacson you know the ones he studies are the ones that can take that design thinking and technology and bring them together Carles bring us up to speed on from from the IT standpoint you know how big of a team do you have what are you involved with I said you know things have been changing over the last few years yeah so I mean we've got Jason in addition to running the department he runs our online learning system I'm responsible for all the backend its infrastructure servers networking backup virtualization we recently hired a junior systems administrator to help me out we've got a web guy we've got a DBA to the woodshop is under IT because we have a fabrication guy so 3d printing laser cutting we have the help desk and the help desk manager who also does our purchasing and she and I will take escalations so it's there's not a lot of crossover you know skill crossover in the group but we managed to keep everything going yeah but as you said they've been you know woodworking not something you think of in Italy as you know an IT thing IT an OT or you know really converging a lot when you talk about manufacturing as you know we talk about sensors and IOT it's it's hitting everywhere yeah for us you know 3d printing and laser cutting and we also have a CNC router they all started as experiments at the school and have turned into a major factor in for our students it's a resource that they demand and the increasing use every single year and how we meet those demands is is becoming tricky to accomplish in our you know we're in the Back Bay real estate is very expensive and we have to make our space do amazing things Jason that's great points I mean I've talked to lots of higher education and even you talk to the K 2 through 12 it was you know what mobility has had a huge impact you know therefore stresses and strains on wireless you know how do I get devices into the classroom how do I manage it I had gentleman from bu who's here at the show last year we were talking a lot about MOOCs so you know it's that that role of i TS but it's expanding but luckily they're throwing way more money at you I'm sure well we've been flat headcount over the last eight years we lost someone last year and gain someone this year so you know we we basically have to do more with less every year like most IT departments so you know we've we redesign our spaces periodically to meet those our students needs you know and turn returning what was labs just computer labs into more flexible space where students are can move the tables around and you the computers are available sometimes there we have high end alien wares in a in a cabinet they pull out news or they can use it to make models we have they can put up their designs on a 3d TV they're using VR headsets to walk around their own designs it's really fascinating where the technologies okay I wish we could spend more time anywhere in VR stuff and everything like that our production crews gamers my son's into this stuff but but Karl I'm hearing things like space constrained we need to do more with less we need to simplify this environment wow that seems like a really good set up for kind of infrastructure modernization so how long have you guys been there about 10 years right yeah so it's a change don't want one in ten years so walk us back 10 years ago and give us that point when you went to modernize yeah well when we started there's no virtualization 3 server racks in a room in the basement for 10 years that we've been there there's been water in that room twice so that always gave us the warm fuzzies you're saying it wasn't water cooling I mean no we tried for that but it didn't you know it didn't work out last year we moved to Colo facility in Summerville so and by the time we did that move yeah we did we started virtualization with VMware like three five within a year or two of me starting and the racks got you know less and less full and now in the fall we rolled out VX rail and we're in a single rack in a data center and there's I think three physical servers in that rack that aren't the VX rail at this point so it's it's consolidation power savings stuffs in a much better physical location than it used to be moving that server room out we were able to free up that space for you know the students to be able to have it's a it's a meditation space now so it's it's been really interesting kind of going through all that great what I wanted you know we don't have a ton of time but let's talk about that VX rail was your team were you looking for HCI was it you know just time for a server refresh you know what what kind of led to that was there a specific application that you started with so this event two years ago we saw Brian from bu give this presentation on their tan and that really turns us on to the whole hyper-converged option we we worked with Winslow we actually talked to another vendor and we looked at Nutanix we looked at pivot three we looked at rolling our own you know visa non FX 2 and after kind of comparing everything and seeing the pros and cons VX rail made the most sense from management perspective and a price perspective our old cluster was coming up on the five-year mark things were going out of warranty we had ecologic sand with 7200 rpm drives one gig I scuzzy just flow for most of its life we were just doing lightweight servers and applications two years ago we needed to virtualize our database server and we threw her Knicks in there with 800 gig on VM e drives and that was a great stopgap but you know we we needed something more permanent more robust - that's how we got to be X ray from a management standpoint the hyper-converged model gave us more flexibility it's easier to expand and since we're small we're not talking about you know racks and racks working together ryote you started with just three hosts so from a overview standpoint it's easy for us as we grow to just add another node and we get the compute we get the storage and we get the memory all at once as an expansion so it's the model is just fantastic for our workload that we put on it we've got like 70 servers in there the only stuff that's not in there yet is our student file server and exchange and they're going in there in the next six months yeah yeah good great and that's so so it sounds like you're real happy with the solution you've been with Dell for four years so from an Operations standpoint was there you know a lot of steep learning curve or was this pretty straightforward and very easy I mean I was I was already really familiar with the VMware piece going into this so that you know that wasn't a big deal we were already on Ruby sphere 6 and we started in the it's row of B so 6px role manager is it's kind of a stupid easy interface you know you can go in you can see are there alerts is there an update you know can it see my hardware is all that good there's not a whole lot to learn from there if we were doing V San on our own my understanding is that some a lot more complicated to stand up once you have it going you're good until you try to make a change so the VX rail manager extract abstracts all that away and just kind of gives you the the VMware experience that you're used to yeah any commentary on the economic service you know we actually found it was very interesting because our original assessment of our own needs were there was no way we could afford all flash and we started we focused exclusively on hybrid solutions and after a certain point we saw I think a presentation from Rick on the external platform and we saw the VX rail as inline dedupe and compression with the all flash and we thought wait maybe we could make this work with all flash and so we actually had a very slight reduction in RAW storage in our new platform but the percentage that we're actually consuming is far less than on our old platform simply because of those gains and it is the performance is far far faster and it's a we've just been very pleased with the implementation from a cost perspective the all-flash VX rail came in under the hybrid pivot 3 and the hybrid Nutanix products so you know we it was a huge win from that perspective we were shocked we could be able to do it thrilled with it ok final word it sounds like you're real happy with the solution when it smoothly operates well economics were good what final takeaways would you give for your peers I mean I'd say the implementation was you know the VX rail platform the the installation is as advertised it was it's basically a wizard that walks you through the installation process the very few minor issues we encountered the winslow team and the is EMC no support support people had no problem solving for us it was really a pretty easy migration to the new platform and we were able to do it with essentially zero downtime yeah awesome well gentlemen thanks so much for joining that's the promise is to get that easy button for IT HD I definitely helping to move in that direction next time we'll get to talk a little bit more about cloud and everything like that be back with lots more coverage here from wtg transform 2018 I'm Stu minimun thanks for watching the Q

from Boston Massachusetts it's the cube covering wtg transform 2018 brought to you by Winslow technology group welcome back I'm Stu minimun and this is the cube coverage of wdg transform 2018 I'm happy to welcome back to the program probably an interesting who's come all the way from Boston University he said three blocks away about three blocks why yes all right Brian's the director of College of Arts and Sciences information technology great to see you again thank you all right back so good news is we spoke it was just about a year ago it was August last year it's June this year I'm sure nothing's changed in your environment you know students never change technology never changes there's a little bit of change on your end a little bit a little bit last year we'd spoke of quite a bit about hyperconvergence and what's that's gonna mean in terms of Education and how we deliver that and what the experience could be like for these students and I think at this point we're satisfied with everything that Nutanix has brought to us we've deployed VDI and a couple of large deployments for whole bunch of classes so we decided to reassess and reevaluate work what we're doing this year and now we move on to application development that's great so we get many ways they say you need to modernize your platform and then once you do that we can look at what the long haul 210 which is really at the application side right exactly once we knew what we had what we could possibly do with it we decided to move forward and figure out what else can we change and we had a lot of legacy applications for the business and so this past year we hired a developer who's focusing solely on docker izing our applications so we're deploying docker and a whole bunch of applications within the college and then we're going to be doing kubernetes deployment later this year ok and let's be clear where does this live you know is this on the Nutanix platform is it in you know service riders public clouds where does this span because kubernetes can live in all of those environments in the containerized stuff at Casa and currently it's all contained within a handful of VMs within our Nutanix server environment ok we're planning on looking at calm and use using natural blueprints to deploy kubernetes and docker down the road ok so I've got the Nutanix platform what hypervisor am i using HP ok so using the HP using which of courses Newt annexes comes on on the platform and then you know in the VMS you're using containers we are um have you looked at bare metal um you know because that's one of the discussions is like well if I'm doing containers you know do I just do that on Linux on bare metal or do I do it virtual is a virtualized and there's there's pluses and minuses for each of those we did a few of the pluses that my sis had means really enjoy is when our developer is going to go crazy and do new things we can make snapshot so if he happens to do something to the environment we can restore it in ten minutes and I think as far as my developer is concerned he doesn't want to have to rebuild the environment every time he makes a mistake he's had a few close calls so far and having HP and the ability to snapshot restore it's been awesome for him okay what insight can you give us about what you know what sort of applications are they building and you said Dockers in two minute Kruger burn Eddie's you know are they building their own stack are they leveraging you know how are they getting to that state well we're taking some business apps that were focusing on both student and faculty applications dealing with various components of each and he's pulling them apart to figure out what components go into the docker containers what do we have to still reside in VMs for security and long-term use and try to figure out how to reimagine the application stack to move forward we're starting to look at reusing components that he's developing and I'm hoping that we have a lot of pieces that we can do that with so we have a lot of applications to rewrite okay and just to drill in a little bit because I've got we've got a team of the cube that's gonna be at docker con next week I've been go to the kubernetes show for a while so when you say docker are you using just the free containers which is now called mobi or using the dr. CEO as part of that I actually can't tell you that because that's miss all my developers work I did so they're using docker as you said it's like the Kleenex and do you know from kubernetes standpoint have they just built their own do you have a distribution or a platform that you just do Tanic we just downloaded the distro from kubernetes instead of a small cluster himself we're going to be looking at using calm to do a deployment on their channels natively okay really interesting stuff what what is you know you talked a bit about you know you can give a little bit of stability and recovery and things like that for your developers to be able to play in that sandbox is what gives us a little bit of the roadmap as to you know how long do they play with this and then you know how does this roll out for the university so we're looking at probably a three to six month development cycle on a lot of new applications right now part of my developers job is to try to figure out how this environments going to work my sis admins are deeply engaged with him but since most of doctrine kubernetes is developed with faced he has to do most of the legwork and figure out how it's all gonna work and so we're hoping to leverage Nutanix to have multiple environments all with the same back-end so we have dev tests and production all in the same hardware but different pieces of actually physical clusters that'll be separated so he doesn't mess around the production all too much but set up a baseline that we can use to short that development cycle even further yeah one of the things we always look at is right you've got your developers doing their thing how does that fit with the operation side is it DevOps even I interviewed Solomon hikes last year that was the founder of docker and he said actually it was an operation mindset that I had when I created this container format how are you seeing it's actually great you're all working together you're you're in discussion there do you have a DevOps rollout and what you're doing or you do you keep it separate I still keep them somewhat separate but my administrators are writing a little bit more code and scripting than they used to and I think in general that's going to be the in the entire industry where you can't just look at and have your developer do everything in docker and not understand how it works Brian talk to us about your partners for doing this how involved are the likes of Nutanix and Winslet technology and you know in Dell in this discussion of the containers agent and your developers Nutanix we've been utilizing a lot of documentation and we're gonna be leveraging them a lot when we start to look at com Winslow's we haven't really talked to them about it to be honest we probably should because they might have some ideas and other partners we can talk to Dell in it there's really just a hardware to run everything on that's stable we don't have to worry about it I'm so happy with that yeah that's not in any you know oh I don't need to worry about them there's certain pieces we always look at and I'd love your feedback on this if you know when we virtualized first and now even when we containerize how much don't I need to worry about the infrastructure I mean remember back you know 15 years ago it's like oh I'll virtualized that well have you checked the BIOS because the BIOS might not work and the server could break things the OS could cause problem you know virtualization relatively stable these days how are you finding the container stuff it's really interesting and very very unique to virtualize a virtualized environment even further it's it's kind of mind-blowing just I've been doing this for twenty years and this is much further than I've ever expected the industry to go oh yeah just wait and it's you go even further than kubernetes it's like wait is it on top of underneath or side by side with the technologies you're doing from a Cooper nettie standpoint you said today it's all in the note annex what's the value of kubernetes for you is it just kind of the cluster orchestration of containers or you know are you is its portability a piece even part of the concern that you look at there oh it's it's mostly from portability part of the applications that we're looking at down the road are going to be vertical applications especially some student facing ones and certain times of the year we're gonna have to go from maybe a hundred people logged in to several thousand at the same time so we're hoping to stand up something that we can easily move to a cloud provider and still work the same way that we're expecting it to and so I think kubernetes along with the orchestration internally on-prem it's gonna be a huge benefit for us to know the environment it's gonna be exactly the same when we move it to Amazon or Google or adder all right so so Brian you're still kind of in the thick of it here but from what you've learned so far any any learnings or things that you'd recommend to your peers that oh wait if I could turn back the clock three months I might have adjusted or pointed things in a different direction yes yeah well when our developer started he focused more on getting an application up and running before starting to learn docker I would encourage anybody that's just starting down the road get your developer learning doctor and kubernetes first because they might want to rewrite what they're doing in the application okay well Brian this has been fascinating want to give you the final word is that you look out through the rest of the year so it's a lot you know so far since last time we talked but by the time we come around next year you'll be all serverless and you know deploying things off side the globe I'm assuming but I have no idea if you told me your ago that we're gonna be doing what we're doing now I wouldn't believe you it's it's a fantastic journey it's it's amazing what we learn every day all right well Brian appreciate you sharing some of the learnings as we go it's one of the reasons we come to events like this I know yourself to talk to your peers here what's going out thank you for moving forward with thank you all right plus more coverage here at wtg transform 2018 I'm Stu minimun and thanks for watching the Q

>> Announcer: From Gillette Stadium, in Foxborough, Massachusetts, it's theCUBE. Covering VTUG Winter Warmer, 2018. Presented by Silicon Angle. (upbeat music) >> Hi, I'm Stu Miniman, and this is the VTUG Winter Warmer 2018. Happy to welcome to the program Tom Rasmussen, who's an IT director, and an instructor at JATC of Greater Boston. Tom, thanks for joining me. >> Thank you. >> OK, so you wear a couple of hats, like many people in IT. Tell us a little bit about your background and your organization. >> So my background, I come from the electrical engineering, that's my degree, so I used to like the chip-level stuff. And then as time went, I got into computers, networking, and so I kind of, my background is in the server side of it, you know, the Novell, the Microsoft days. And as I became an instructor, because I actually had a service call to the school, and they said, "Oh, you know something "about computers and networking, "would you like to teach here?" And of course, 20-something years later, I'm now the IT director, and part-time instructor. >> Yeah, so I want to dig into both of those. Why don't we start with your IT hat, there? Tell us a little bit about the organization, what kinds of things you deal with, some of kind of the biggest challenges on your plate. >> Yeah, so we're the trade school for the local IBEW in Boston, we've got about 12 to 1,500 apprentices in the school, both electrician and telecommunication. And it's a five-year program, and one of the biggest challenges that kind of brought me on board was just the management of the computer systems. They need someone, you know, they had these computer labs that, as the students did things to them, they no longer worked, and so that machine went off, and that machine, and, you know, they didn't have a full-time IT person, so it was like, OK, this weekend, we're going to re-do everything and so on and so on. Part of me coming on was we implemented a VDI environment, where you might think of it as a cost-type thing, but it was really just a management, where we could manage the desktop, manage the experience. And we're about two years into it, and it's been successful, but it's challenging. >> Yeah, you bring up a real good point, though. When people tend to go in from a cost-savings, a lot of times, they'll be disappointed. There really needs to be some kind of transformational, solving some real business problems, and it sounds like you had that well identified, and while there's always, oh, I've got to fine-tune the performance, oh, the network's got issues, you know, so many devices, and what do I deal with, and churn of what's going on there, it's, you know, changing the paradigm of management, you no longer have, probably, you, running around from all of these places, constantly fiddling with all of these boxes too, I think it would centralize your job a little bit more. >> It did, and one of the kind of benefits was, well, we can't use this lab, because the machines aren't working, or it's not up to date, or we don't have this software, or we don't have the ability to get it up and running, to fighting for the labs now. You know, if a contractor wants to come in, and display, you know, demo a new piece of software, we can put that software on that for the period of time they're there, and then take it away. So we're getting much more utilization out of our systems, which benefits us in production, and it kind of, you know, the students as a whole. >> Yeah, another challenge I hear a lot from education people is, you know, just the wireless infrastructure, how you deal with all the devices, what people get access. Is that running well? You know, challenges, what are you seeing with the abundance of technology that everybody walks in with? >> One of the the things that, we do have a challenge with wireless, we don't have enough, we're not quite sure where we're going with it yet, right now we have a policy that our students aren't allowed to bring wireless devices in, but as we're rolling out new types of products or applications, we're seeing, like, oh, we actually need that tablet, we need you to bring your work, we need that, and so I see this changing very quickly, which is really going to affect us from the wireless management. We had a code update just the past weekend, and they're, again, implementing some type of, you know, OK guys, let's take a quiz. And everyone brings out the phone. Well, they gave out the wireless, and they saturated it, so, we're like, OK, we're going to fix that one too, now. >> Alright, let's flip over and talk about the training that you're working on. What kind of classes are you doing, you know, what skill set, what's kind of the... I know there's never a typical, the typical student look like? >> So, a typical apprentice would be anywhere from someone coming right out of high school, coming out of the military, just deciding to retool. So we could have a 20-something, up to a 40-something. So from an educational standpoint, it is challenging. Some people know things about computers, you know, they know a little bit about network, and it's a range. They know a lot more now than they say, did, five or six years ago, so it's a little easier. From the telcom side, traditional telephone and networking, those apprentices get a full-blown of, you know, this is computers, this is basic networking, this is advanced networking. We're finding that even in the electrical industry, that we need to train our electricians to know about networking, because the lighting system is now in Endpoint, the HVEA system is in Endpoint, the management of the security system, everything is going to be on the internet. So as I say, there's not going to be a lighting switch. You're going to walk in the door, and say, "computer, turn on the lights, mood level five." >> Or even, you have things like Nest, that I don't even have to, a lot of my settings, it's going to learn what's going on. All those IOT devices, does that come into the training today, or is that still kind of a future? >> It's starting to come in, because it has to. Those devices are there. Our heating system in our building went down the other day, and it turned out it was an IP address information, so the joke was, don't let electricians near IP addresses. >> When you said you'd been there 20 years now? >> Tom: Part-time. >> Part-time, but we talk about the rate of change, and there's always change going on, but it definitely feels that things are changing faster. How do you, as a trainer, keep up with it? You want to make sure that when they finish their apprenticeship, they're ready for the new job, how do you manage that? >> The curriculum is constantly changing, it's evolving. We're trying to fit more in, in a shorter period of time. I came out of, I came full time just two years ago, so I was in the thick of things. I'm now focused on VDI and educational resources, which, again, is kind of new to me. What tools, what are all these tools, what are the applications that work in the educational environment, which is kind of above and beyond the traditional IT piece. It is challenging, I read as much as I can, and get involved with places like VTUG, and the other groups, and you can only know so much. I can't be an expert in hardware, or software, or services, or applications, I kind of have to get in the middle, and then hopefully get someone to come and give me a hand. >> Tom, very good point, I think all of us know that there's nobody that can be an expert at everything. You set me up for the last question I have for you. What brings you to an event like the VTUG, what do you get out of it, what would you share to people that didn't come this week? >> I like coming and talking to the vendors, and seeing what's available, but the biggest thing I get is just seeing the other mes out there. Just at lunch today, I met a person that comes from a K to 12 school, and it turns out that we have very similar systems. So, to me, that was probably the best part of the event, there. Because now I have a relationship, because I am the IT guy, I am the IT director, and an instructor, and to have those types of resources is really useful and important to me. Absolutely, which is why, Tom, we appreciate you coming, and sharing with your peers that couldn't come here, what's happening in your environment. We'll be back with lots more coverage here from the VTUG Winter Warmer, 2018. I'm Stu Miniman, you're watching theCUBE. (upbeat music)

(shutter clicking) >> I'm Stu Miniman with theCUBE. We're here at the Winslow Technology Group Dell EMC User Group happy to have one of users here, Brian Anderson, who's the director for the College of Arts and Science Information Technology at Boston University, within a short stone's throw here. Brian, thanks so much for joining us. >> Oh, you're welcome. Thank you for being here and being here while Scott's doing this because it's kind of a fun event for us. >> Well, that's great. Tell us how many times have you been to this? >> It's my third event. I was actually a speaker last year. >> Excellent. >> This year, I'm just coming as a user, listening to the sessions, and being social with the rest of the people who do business with Winslow. >> Yeah, what do you get out of presenting and then attending an event like this? >> Feedback from my peers. I get to hear about what other people are doing, what their solutions are, how they solve some of the same problems we're trying to solve. And it's just a good networking event. >> That's awesome, Brian. And we love how peers can really share with other practitioners. So, the good news, Boston University, I think, we don't need to explain what the university is. But what are some of the drivers happening at the university level. Changes happening, changes happening in every industry. But what, specifically, is happening there that kind of impacts your world? >> Yeah, there's a huge push right now to look at cloud as a solution for a whole variety of areas, replacing infrastructure that's currently in place, trying to figure out how cloud solutions fit into the academics. We have a lot of faculty that want to use cloud solutions to teach. And we've been playing catch-up for the last few years. And we're really taking it seriously and trying to figure out how to provide those resources in both hybrid environments and cloud-only environments. >> Yeah, can you unpack that a little bit? >> Yeah. >> Where are you with cloud today? What are you looking at? What are the criteria? Obviously, cost is always a concern for everyone. But we know how fast in higher education the fees are going up. And therefore, you've got to be under a lot of pressure there. >> Oh we are, we are. We're already using a lot of cloud-based services for things like email, file storage. We now have a Dropbox implementation that we're pushing out to our faculty this year. So it's a combination of what services can we take from on campus and move them up to the cloud and is that feasible financially? It's a big transition to take the capital expenditure and transition over to OP-X. And it's really just the fine line of what services make sense to do so. >> I've talked to lots of, kind of, K through 12 environments. And the students there, obviously, have a lot of high demands there. I have to think it's even more when we get to higher education. You mentioned a little bit the faculty demands and what they're doing. Maybe expand a little bit, faculty and the students themselves, what are they looking for? What do they come into kind of expecting and how are you helping to deliver that? >> Well, I know a lot of students these days are coming from using services like Blackboard throughout most of their career until they get to university. We also have Blackboard, but it's not as widely distributed as students are expecting. We have about a 50% adoption rate of Blackboard in our courses. So it's an effort to try to get faculty to convert their curriculum for the last 20 years into something that's online and that students today can really relate to and want to learn from. There's a lot of integrations with really cool technologies that students like to use and have used in previous schools that we want to try to get up and running so faculty can take advantage of them. So we're fighting the tide between what faculty want to do and their inertia versus what students are expecting when they walk in the door. Knowing how much the university costs per year. And they get a great experience in the dorms and we want to make sure they get the same experience when they're in the classroom. >> Excellent. We heard in the opening remarks this morning really the kind of digital transformation that's going on. Scott Winslow talked about some of those emerging solutions that they're helping to drive. What solutions do you use from WTG? Where do you look to them as a solution partner? >> Well, they introduced us to the Nutanix platform, the Dell XD series, and we've been using that for the last three years to provide VDI solutions for our students. And that's enabling some of our faculty to be very creative in how they teach. We have one faculty who's trying to transform the chemistry lab experience to give the students hands-on experience without actually having to go to one of their prized rooms where all the research is actually done. So we're virtualizing instrumentation where they're able to play around with it and learn how to do it before they sit in front of it. And we're working with them to try to figure out how to expand that for training opportunities for their graduate students and Ph.D. Students. >> Brian, what's the impact of online education, MOOCs, and the like? Is that impacting your group yet? >> A little bit. BU has about ten MOOCs they host per year. They're widely attended at the beginning, and like every MOOC, it dwindles as the semester goes. But it's been a fine line. We haven't accredited them yet, so they're not really worth anything if students take them. But we want to get to that point where that is the case. We see the value. We see that's what the students want. We want to make sure we have the total MOOC experience available for our students and external students. But it's just a lot of distance between where we are now and getting to that point. >> Okay, I appreciate how you've been sharing how cloud is really developing in your environment. As you look into the partners that you work with, what's on your wish list? What would enable you to be able to move this transition even faster, you know, beyond, I'm sure cost is always a concern, but what would you be looking for? What would help you and your organization move even faster? >> Ease of manageability. Right now, a lot of our partners are all siloed applications. If we had a service that could put a bunch of things under the same umbrella and allow ease of management of a whole variety of services, that would be a huge, huge win for us. That would probably make adoption much easier and would accelerate things a lot quicker than we can now. >> All right, what excites you most in technology space these days, Brian? >> I'm going to say the hyperconvergence and what that means for standard technology and how things have been done for the last 25 years. I think that's the future. That's where we are now and that's kind of the nice bridge between what we used to do to the cloud. And I think it's going to be here for a lot longer than people think. >> And when you rolled out the hyperconvergence, is there any specific metrics? What was the impact on your operations and any specific learnings that you would share with your peers? >> Well for us, it was a new service. It was something brand new we were bringing in. And I was amazed at how quickly my system administrators picked up on it and how quickly the faculty started to understand what it was and adopt it to their classes. >> Brian Anderson, really appreciate you sharing with us >> Thank you. >> the journey that BU and your organization are going through. You're watching theCUBE here at the WTG Dell EMC User Group event. (shutter clicking)

>> Announcer: From the Silicon Valley Media Office in Boston, Massachusetts, it's The Cube! Now, here's your host, Dave Vellante. >> Hi, everybody, welcome to a special Silicon Angle, The Cube on the ground. We're going to be talking about data capital with Paul Sonderegger, who is a big data strategist at Oracle, and he leads Oracle's data capital initiative. Paul, thanks for coming in, welcome to The Cube. >> Thank you, Dave, it's good to be here. >> So data capital, it's a topic that's gaining a lot of momentum, people talking about data value, they've talked about that for years, but what is data capital? >> Well, what we're saying with data capital, is that data fulfills the literal economic textbook definition of capital. Capital is a produced good, as opposed to a natural resource that you have to invest to create it, and it is then an necessary input into some other good or service. So when we define data capital, we say that data capital is the recorded information necessary to produce a good or service. Which is really boring, so let me give you an example. So imagine, picture a retailer. A retailer wants to go into a new market. To do that, the retailer has to expand its inventory, it has to extend its supply chain, it has to buy property, all of these kinds of investments. If it lacks the financial capital to make all of those investments, it can't go, cannot go into that new region. By the same token, if this retailer wants to create a new dynamic pricing algorithm, or a new recommendation engine, but lacks the data to feed those algorithms, it cannot create that ability. It cannot provide that service. Data is now a kind of capital. >> And for years, data was viewed by a lot of organizations, particularly general counsel, as a liability, and then the big data meme sort of took off and all of a sudden, data becomes an asset. Are organizations viewing data as an asset? >> A lot of organizations are starting to view data as an asset, even though they can't account for it that way. So by current accounting standards, companies are not allowed to treat the money that they spend on developing information, on capturing data, as an asset. However, what you see with these online consumer services, the ones that we know, Uber, Airbnb, Netflix, Linkedin, these companies absolutely treat data as an asset. They treat it, not just as a record of what happened, but as a raw material for creating new digital products and services. >> You too, you tweeted out an article recently on Uber, and Uber lost about, what is it? 1.2 billion- >> At least. >> Over six months, at least. >> At least. >> And then the article calculated how much it was actually paid, I mean basically, the conclusion was it paid 1.2 billion for data. >> Yeah. >> It was about $1.20 per data for ride record, which actually is not a bad deal, when you think about it that way. >> Well, that's the thing, it's not a bad deal when you consider that the big picture they have in view is the global market for personal transportation, which The Economist estimates is about 10 trillion dollars annually. Well, to go after a 10 trillion dollar market, if you can build up a unique stock of data capital, of a billion records at about a billion dollars per record, that's probably a pretty good deal, yeah. >> So, money obviously is fungible, it's currency. Data is not a currency, but digital data is fungible, right, I mean, you can use data in a lot of different ways, can't you? >> No, no, it's, and this actually is a really important point, it's a really important point. Data is actually not fungible. This is part of data's curious economic identity. So data, contrary to popular wisdom, data is not abundant. Data consists of countless unique observations, and one of the issues here is that, two pieces of data are usually not fungible. You can't replace one with the other because they carry different information. They carry different semantics. So just to make it very, very concrete, one of the things that we see now, a huge use of data capital is in fraud detection. And one of our customers handles the fraud detection for person-to-person mobile payments. So say you go away for a weekend with a friend, you come back, you want to split the tab, and you just want to make a payment directly to the other person. You do this through your phone. Those transactions, that account to account transfer, gets checked for possible fraudulent activity in the moment, as it happens, and there is a scoring algorithm that sniffs those transactions and gives it a score to indicate whether or not it may be fraudulent or if it's legitimate. Well, this company, they use the information they capture about whether their algorithm captured, caught, all of the fraudulent transactions or missed some, and whether that algorithm mistakenly flagged legitimate transactions as fraudulent. They capture all of those false positives and false negatives, feed it back into the system, and improve the performance of the algorithm for the next go around. Here's why this matters: the data created by that algorithm about its own performance, is a proprietary asset. It is unique. And no other data with substitute for it. And in that way, it becomes the basis for a sustainable competitive advantage. >> It's a great example. So the algorithm maybe is free, you can grab an algorithm, it's how you apply it that is proprietary, and now, okay, so we've established that the data is not fungible. But digital data doesn't necessarily have high asset specificity. Do you agree with that? In other words, I can use data in different ways, if it's digital. Yeah, absolutely, as a matter of fact, this is one of the other characteristics of data. It is non-rivalrous, is what economists would call it. And this means that two parties can use the same piece of data at the same time. Which is not the case with, say, a tractor. One guy on a tractor means that none of the other people can ride that tractor. Data's not like that. So data can be put to multiple uses simultaneously. And what becomes very interesting is that different uses of data can command different prices. There's actually a project going on right now where Harvard Law School is scanning and digitizing the entire collection of US case law. Now this is The Law, the law that we all as Americans are bound to. Yet, it is locked up in a way, in just, in all of these 43,000 books. Well, Harvard and a startup called Ravel Law, they are working on scanning and digitizing this data, which can then be searched, for free, all of these, you can search this entire body of case law, for free, so you can go in and search "privacy," for example, and see all of the judgements that mention privacy over the entire history of US case law. But, if you want, for example, to analyze how different judges, current sitting judges, rule on cases related to privacy, well, that's a service that you would pay for from Ravel. The exact same data, their algorithms are working on the same body of data. You can search it for free, but the analysis that you might want on that same data, you can only get for a fee. So different uses of data can command different prices. >> So, some excellent examples there. What are the implications of all of this for competitive strategies, what should companies, how should they apply this for competitive strategies? >> Well, when we think about competitive strategy with data capital, we think in terms of three principles of data capital, is what we call them. The first one is that data comes from activity. The second one is, data tends to make more data, and the third is that platforms tend to win. So these three principles, even if we just run through them in their turn, the first one, data comes from activity, this means that, in order to capture data, your company has to be part of the activity that produces it at the time that activity happens. And the competitive strategy implication here is that, if your company is not part of that activity when it happens, your chance to capture its data is lost, forever. And so this means that interactions with customers are critical targets to digitize and datify before the competition gets in there and shuts you out. The second principle, data tends to make more data, this is what we were talking about with algorithms. Analytics are great, they're very important, analytics provide information to people so that they can make better choices, but the real action is in algorithms. And here is where you're feeding your unique stock of data capital to algorithms, that not only act on that data, but create data about their own performance, that then improve their future performance, and that data capital flywheel becomes a competitive advantage that's very hard to catch. The third principle is that platforms tend to win. So platforms are common in information-intensive industries, we see them with a credit card, for example, we see them in financial services. A credit card is a payment platform between consumers on the one side, merchants on the other. A video game console is a platform between developers on the one side and gamers on the other. The thing about platform competition is that it tends to lead toward a winner-take-all outcome. Not always, but that's how it tends to go. And with the digitization and datification of more activities, platform competition is coming for industries that have never seen it before. >> So platform beats product, but it's winner-take-all, or number two maybe breaks even, right? >> That tends to be the way it goes. >> And number three loses money, okay. The first point you were making about, you've got to be there when the transaction occurs, you've got to show up. The second one's interesting, data tends to make more data. So, and you talked about algorithms and improving and fine-tuning in that feedback loop. I would imagine customers are challenged in terms of investments, do they spend money on acquiring more data, or do they spend money on improving their algorithms, and then the answer is got to do both, but budgets are limited. How are customers dealing with that challenge? >> Well, prioritization becomes really critical here. So not all data is created equal, but it's very difficult to know which data will be more valuable in the future. However, there are ways to improve your guess. And one of the best ways is to, go after data that your competition could get as well. So this is data that comes from activities with customers. Data from activities with suppliers, with partners. Those are all places where the competition could also try to digitize and datify those activities. So companies should really look outside their own four walls. But the next part, you know, figuring out, what do you do with it? This is where companies really need to take a page out of actual science as they approach data science, and science is all about argument. It's all about experimentation, testing, and keeping the hypotheses that are proven and discarding the ones that are disproven. What this means is that companies need a data lab environment, where they can cut the time, the cost, the effort, of forming and testing new hypotheses, getting new answers to new questions from their data. >> Okay, so, data has value, you've got to prioritize. How do you actually value the data so that I can prioritize and figure out what I should be focusing on in the lab and in production? >> Yeah, well, the basic answer is to go where the money is. So there are a couple things you can do with data. One is that you can improve your operational effectiveness, and so here, you should go look at your big cost areas, and focus your limited data science and managerial resources on trying to figure out, hey, can we become more efficient in whatever your big cost driver is? If it's shipping and logistics, if it's inventory management, if it's customer acquisition, if it's marketing and advertising, so that's one way to go. The next big thing that you can do with data is try to create a new product or service, a new ... create new value in a way that generates revenue. Here, there is a little caveat, which is that, companies may also want to consider creating new capabilities, maybe enriching the customer experience, making connections across multiple channels, that they can't actually charge for, not today. But, what they get, is data that no one else has. What they get from, let's say, making an investment into, bring together the in-store shopping experience with the, with the targeted emails, with, with communication through social feeds and through Twitter. Let's say that they invest in trying to tie that data together, to get a richer picture of their consumers' behavior. They might not be able to charge for that today. But, they may get insight into the way that shopping experience works that no one else can see, which then leads to a value-added service tomorrow. And I know it all sounds very speculative, but this is basically the nature of prototyping, of new product creation. >> Well, Uber's overused as an example, but this is a good application of Uber because they, essentially they pay for driver acquisition, which doesn't scale well. >> Yeah. >> But they get data. >> That's right. >> Because they're there at the point of the transaction and the activity and they've got data that nobody else has. >> Yeah, yeah, that's exactly right, and, you know, one of the ways to think about that is that, you're like a blackjack player, counting cards, and every time you play a hand as a company, you get data, information that may help you improve your future bets. This is why Vegas kicks out card counters, because it's an advantage for the future. But what we're talking about here, in digitizing activity with customers, every time you capture data about your interaction with those customers, you gain something simply for having carried out that activity. >> And so, thinking about, back to value for a minute, I mean I can envision some kind of value flow methodology where you assess the data intensity of the activity, and then assign some kind of, I don't know, score or a value to that activity, and then you can then look at that in relation to other activities. Is that a viable approach? >> It absolutely is. What companies need here is a new way to measure how much data they've got, how much they use, and then ascribe ... value created, you know, by that data. So the, how much they've got, you know, we can think about this, we always talk in terms of gigabytes and petabytes. But really we need some finer measurements. Data is an observation about something in the real world. And so, companies should start to think about measuring their data in terms of observations, in terms of attribute-value pairs. So even thinking about the record captured per activity, that's not enough. Companies should start thinking in terms of, how many columns are in that record? How many attributes are captured in these observations we make from that activity? The next issue, you know, how much do they use? Well, now, companies need to look at, how many of these observations are being touched, are being tapped by queries? Whether they're automatically generated, whether they are generated ad hoc by some data scientist, rooting around for some new understanding. So there's a set of questions there about, what percentage of these observations we possess are we actually using in queries of some kind? And then the third piece, how much value do we create from it? This is where ... This is a tough one, and it's really an estimation. It's, most likely what we need here is a new method for attributing the, profitabilty of a particular business unit to its use of that data. And I realize this is an estimation, but this is, there's a precedent for this in brand valuation, this is the coin of the realm when you're talking about putting a value to intangible assets. >> Well, as long as you're consistently applying that methodology across your portfolio, then, then at least you've got a relative measure and you can get back to prioritization, which is a key factor here. Is there an underlying technical architecture that has to be in place to take advantage of all this data capital momentum? >> There is, there is, companies are moving toward a hybrid cloud, big data architecture. >> What does that mean? >> It means that almost all the buzzwords are used, and we're going to need new ones. No, what it means is that, companies are going to find themselves in a situation where some of their computing activities, storage, processing, application execution, analytics, some of those activities will take place in a public cloud environment, some of it will take place within their own data centers, reconfigured to act as private clouds. And there are lots of potential reasons for this. There could be, companies have to deal with, not only existing regulations, which sometimes will prevent them from putting data up into a cloud, but they are also going to have to deal with regulatory arbitrage, maybe the regulations will change, or maybe they've got agreements with partners that are embodied in service level agreements that again require them to keep the data under their own observation. Even in that case, even in that case, the business still wants to consume all of those computing resources inside the data center as if they were services. The business doesn't care where they come from. And so this is one of the things that Oracle is providing, is an architecture for Oracle public cloud, and private cloud in the data center. It is the same on both sides of the wire. And in fact, can even be purchased in the same way so that even these, this Oracle cloud at customer, these machines, they are purchased on a subscription basis, just as public cloud capabilities are. And the reason this is good is because it allows IT leaders to provide to the business, computing capabilities, storage capabilities, you know, as needed, that can be consumed as services, regardless of where they come from. >> Yeah, so you've got the data locality issue, which is speed of light problems, you don't want to move data, then you've got compliance and governance, and you're saying, that hybrid approach allows you to have the cake and eat it, too. >> Yeah. >> Essentially. Are there other sort of benefits to taking this approach? >> Well, one of the, you know, the, one of the other pieces that we should talk about here is the big data aspect, and really what that means is, that, relational, Hadoop, NoSQL, graph database, repositories, they're all going to, they're all peers. They're all peers now, and, you know, this is Oracle's perspective, and as I'm sure you know, Oracle makes a relational database, it's very popular. Yeah, we've been doing it for a while, we're pretty good at it. Oracle's perspective on the future of data management is that Hadoop, NoSQL, graph, relational, all of these methods of data management will be peers and act together in a single high-performance enterprise system. And here's why. The reason is that, as our customers digitize and datify more of their activities, more of the world, they're creating data that's born in shapes and formats that don't necessarily lend themselves to a relational representation. It's more convenient to hold them in a Hadoop file system, and it's more convenient to hold them in just a great big key value store like NoSQL. And yet, they would like to use these data sources as if they were in the same system and not really have to worry about where they are. And we see this with, we see this with telecom providers who want to combine call data records with customer, warehouse, you know, customer data in the data warehouse. We see it with financial services companies who want to do a similar thing of combining research with portfolio investments records of what their high net worth customers have invested, with transaction data from the equities markets. So we see this polyglot future, the future of all of these different data management technologies, and their applications in the analytics built on top, working together, and existing in this hybrid cloud environment. >> So that's different than the historical Oracle, at least perceived messaging, where a lot of people believe that Oracle sees its Oracle database as a hammer, and every opportunity is a nail. You're telling a completely different story now. >> Well, it turns out there are many nails. So, you know, the hammer's still a good thing, but it turns out that, you know, there are also brads and tacks and Philips and flathead screwdrivers too. And this is just one of the consequences of our customers creating more kinds of data. Images, audio, JSON, XML, you know, spectrographic images from drones that are analyzing how much green is in a photograph because that indicates the chlorophyll content. We know, we know that our customers' ability to compete is based on how they create value from data capital. And so Oracle is in the business of making the things that make data more valuable, and we want to reinvent enterprise computing as a set of services that are easier to buy and use. >> And SQL is the lowest common denominator there, because of the skill sets that are available, is that right or? >> Well, it's funny, it's not necessarily a lowest common denominator, it turns out it's just incredibly useful. (laughs) Sequel is not just a technology standard, it's actually, in a manner of speaking, it's sort of a thinking standard. SQL is based on literally hundreds of years of hard thinking about how to think straight. You can trace SQL back to predicate logic, which was one of the critical ideas in the renaissance of mathematics and logic in the 1800s. So SQL embodies this way to think about, to think logically, to think about the attributes of things and their values and to reason about them in an automated fashion. And that is not going away, that in fact is going to become more powerful, more useful. >> Business processes are wired to that way of thinking, is what you're saying. >> That's exactly right. If you want to improve your operational effectiveness as a company, you're going to have to standardize some of your procedures and automate them, and that means you're going to standardize the information component of those activities. You can automate them better. And you're going to want to ask questions about, how's it going? And SQL is incredibly useful for doing that. >> So we went way over our time, this is very interesting discussion, but I have to ask you, what is it you do at Oracle? Do you work with customers to help them understand data strategies and catalyze new thinking? What's your day-to-day like? >> Yeah, I do a lot of this, a lot of telling the story, because we're in a huge time of change. Every 20 years or so, the IT industry goes through an architectural shift, and that changes, not just the technologies used to create value from data, but it changes the very value created from data itself. It changes what you can do with information. So, I spend a lot of time explaining these ideas of data capital, and sitting down with executives at our customers, helping them understand how to look out at the world and see the data that is not there yet, and what that means for the way that they compete, and then we talk through the competitive strategies that follow from that, and the technical architecture required to execute those strategies. >> Excellent. Well, Paul, thanks very much for sharing your knowledge with our Cube audience and coming into the Silicon Angle Media Studios here at Marlborough. >> Well, it's my pleasure. Thanks for having me. >> All right, you're welcome. Okay, thanks for watching, everybody. This is The Cube, Silicon Angle Media's special on the ground production. We'll see you next time. (peppy synth music)

>> Wait. Welcome back to Boston, everybody. This is the Cube. We're live on a special presentation of BMC Day atop of sixty State Street in Boston, Massachusetts. Beautiful view of Boston Harbor. Evelyn Ehrlich is here. She's the vice president and research director for service delivery at Force that we're going to talk about job control, language and cobalt. No, I'm just kidding. We're talking about service delivery. Who'd Evelyn? Yes. So you have a really deep background in it, And I know what J C l stands for, So I had to make that joke. So anyway, uh, welcome to the cubes. Great to see you gave a fantastic presentation today. Who doesn't need better service delivery? It's an imperative for the digital transformation. So, again, welcome to the Cube. Thank you. So tell us a little bit about what you do at Forrester, what your area is, and I want to get into your presentation today. >> Sure. So service delivery. Basically, when the application development team is ready to hand us something, whatever that issa Web service and application a service, we actually make sure that that gets to the work force or to the customer. So anything from Police Management Service Management, the front end relative to the service desk. Tell them anything around management after a performance of the applications operations. Anything like that is all about service delivery. >> And they were two. Two pieces of your talk really struck out to me on Dino. No George for a long time. So two things to majorities that you don't like to use one is users, right end users use it, and then the other really was. So talk about it. Why those terms don't make sense in this digital economy. And what does make sense? >> Yeah, so your users, it almost seems like to me, it is something where people are putting folks into a box that they are that they can like addicts. You know, user. Like I said, in a camp in the drug industry, we have users because they're addicts way have to somehow keep them at bay. We have to somehow keep them low and our engagement with them. It's no, it's not going to be enjoyable. It's not going to be fun, and it's not going to be actually effective. Unfortunately, these users today those are our workforce. There's our employees There's our partners and customers. They have other places to go. They don't need us and technology. So if we don't shift that thinking into that, their customers, so that we can actually enable them, we're might be able to lose our jobs. Because there's outsourcers service providers to workplace services, for example, as many companies out there who provide the service desk who provide of VD I who provide the services cheaper, faster and better. But what we have been lost or what if that's gonna happen? We are losing the understanding of the business for losing the connection to the business, and is that that could be a strategic conversation right? There should be a strategic conversations, not justa cost conversation. And when we think about user, it's all about cost. If you think about customer, its value and relevancy, >> okay, And of course, that leads to not its business. There's no such thing as a project. >> No, there isn't because anything we do if we think of information technology is anything almost like in the back room. It's something which is hidden in a data center somewhere in a storage or a server or in a device and it doesn't really add any value. >> Boiler, the boy, the room >> Exactly and way have done that. We have massaged it, what with whatever way measured the heck out of it. We measure meantime to repair. Well, who cares? It's time to business impact. This what we need to think about. So if we start thinking about customers to empty, TR becomes time to business impact. We're now thinking outside in and the same is true with I t. If we just use it for technology sake to Dr Information, we're not connected if the business, because it is about business technology, is dear to win, retain and sustain our customers. If we don't do that, we become borders. We become the, you know, the companies who all have not focused on the winning technology to make them successful. >> You had a really nice graph, simple sort of digital failing digital masters, and I were in between talked a little about things like I Till and Deb ops, and they feel sometimes like counter counter to each other. Once one's fast one feels home. As you talk to customer, you talk to customers. What can they expect? How long might these transformations take? Or what of the one of those key stepping stones you talked about? It being a journey? >> How do you >> will think about all this change? >> But that that's a good question. It's a very difficult question to have an answer to, and I think it has to. It has to be a little bit more compartmentalized. We have to start thinking a little bit more in smaller boxes, off influences or or areas where we can make some progress. So let's take, for example, Dev Ops and Vital and connect the process release, which is an I told process into this notion. If we combine Deaf ops and Tyto release, we're starting to see that the police management process. It's now a process which is done very agile very much. There is a lot more things behind that process and a lot more collaboration between a D and D and I, you know, to make the process of faster process. So we're now married, I told release management with the journey of Death, Bob's as we're starting to see release cycles off one day. Lookit, lookit Amazon. What they do I mean again, Amazon is a very extreme. Not everybody needs a police processes Amazon has, because it's just not that not every pieces is in the Amazon business. Maybe in ten years, who knows? Maybe in five, but those kinds of things that marriage happens through, more off for design thinking. And I think that's the practical way. Let's not adopt a Iittle blandly and say, All right, we're going to just redo our entire twenty six processes. Let's look at where is the problem? What, where? Where's the pain? What is the ninety day journey to solve that pain? Where's the six months? Nine months, twelve months, twenty four months? And if twenty four months is too far out, which I believe it's staying a twelve month road map and start adjusting it that way and measure it, measure where you are. Measure where you want to go and prove that you have done to Delta. Because if I don't measure that, I won't get funding for support, right? I think that's key. >> Devlin. You talked about the, you know, pray or a predator, right? That's good of a common theme that you hear conferences like this isn't a zero sum game, is is the taxi drivers. You know, the taxi companies screwed is, you know, the hotels in big trouble. I mean, Ken, cos you know who are sort of caught flat footed transform and begin to grow again. Talk about that zero sum game nous. >> Yeah, I think I think there is. There is hope. So I hope it's what dies last week saying right. But there is hope, hope if customers of organizations he's enterprise to see that there's a challenger out there. And if they don't necessarily stand up to fight that challenges start innovating in either copying or leveraging or ten. Gently do something else. Let me give you an example. When about two years we had a two years ago with an event in London and stuff I got Square was completely blocked off by the taxi drivers because uber was there were striking against uber or they were going on. It wasn't really a real strike was in London. It's a little bit of a challenge with unions, but anyway, instead, off going on a strike, why did they not embrace whatever they needed to and example is in the cab At that time, you could not use American Express or discover credit card uber. I never have tipple any money out of my pocket because that's a convenience. It's easy. It's enjoyable. >> Love it, >> We love it. It's simple. So why don't these other companies this cos the taxi cannot? Why don't the equip that technology in such a way? They can at least start adopting some of those innovations to make it a even part right. Some of the other things, maybe they will never get there, because there whatever limitations are there. And so that's what that's what I think needs to happen. These innovators will challenge all these other companies and those who want to stay alive. I mean, they want to because they have for street is forcing them to stay alive. They are the ones who will hopefully create a differentiation because of that >> essay, really invention required. It's applying technology and process that's well established. >> Thinking outside in thinking of you and him and me as >> customers, it becomes, you know, who just does the incumbent get innovation before the the challenger gets distribution? Exactly. You know, Huber, lots of cars. I don't have to buy them, but somebody like Tesla isn't necessarily disrupting forward because they don't have the men. They can't distribute it faster than you know. It depends where you are in the distribution versus innovation. So it's in the brief time. We have love to talk about the landscape. So and that's particularly the transformation of beings. BMC Public Company to private They were under a lot of fire, you know, kind of flattish revenues. Wall Street pound. You got companies like service now picking away at the established SM players. We're talking off camera, saying that's begun to change. Give us the narrative on that that sequence and where we are today. Yeah, we're going. >> Yeah, so if you go back, maybe me way back seven years ago or so you know, it started service now they had a fairly easy game because BMC with a very old platform, it wasn't really it wasn't. There was no fight. Um, and I think they were the enterprises. We're ready for something new, and it is always some new vendor out there is a new shiny object, and I have teenagers, so they always spent the next latest iPhone or whatever. I would >> sort of wave >> so So. And and it kept going in the other vendors into space hp, cia, IBM really had no challenge had no, no, didn't give service now a challenge either because the SAS cloud, the adoption of the cloud in this space was absolutely important. And service now was the first one to be on the cloud. BMC was not really doing much with remedy force at the time. Itis them on demand was in an A S P model. Not really an itis, um, and so service not just took names and numbers and that just grew and grew and steamrolled. Really? All of them and customers just were like, Oh, my God, this is easy. I loved it. Looks it loves it looks beautiful. It's exciting >> over for the >> same thing that innovation, right, That challenge, they served the customers. Then suddenly what happened is service now grew faster than native. You experienced some growing pains Customer saying my account rep. I haven't seen him for a while. They changed the pricing model a little bit too started to blow up their solution. And now board nebula, which is the ninety operations management solution der extending into financials and they're bolstering themselves into more of an enterprise solution, which is where BMC already has been. But they lost the connection to the customer. BMC did not love the customers at that time. Now, through some executive changes to really starting to realize that the install base they need to hug them, they're back in the game >> and watching >> service now. And they're going private. As you were asking the question earlier, try about giving them the funding to invest in R and D. >> It's so necessary if I want to give me your take on icy service now. Is someone on the collision course with sales Force? In a way, where does BMC go for to expand their their tam and to grow? >> Yeah, I said, I think so. So on the first comment Sales force and service. Now, absolutely now the CEO of service now does not think that sales force is his target off competition. I think it has to. He has to, because it is about business applications, everything. It's everything exactly So sales force and service now in I don't know. Is that the year you know, wherever Chris >> No, no, no, >> no. But they will there will collapse. Deborah Crash or you'LL see a fight. I think BMC should stay and really extend in this digital performance management in this operational management and really make it intelligent, intelligent decisions for operation for operations to become automated. To have a staff of eighty eight PM solution the application dependency mapping solution happening to be one of the best, really one of the best in the market. And customers love it. Tying that into two side intelligence, giving them the ability to understand before it happens not when it happens or after and then drive intelligence into different organizations to cmo the CEO, the CFO. Because that's what basis technology is all about. It's not about the journey anymore. They have that capability with products where service now does not have that >> great insight from a sharp analyst. Evan are like Evelyn Evelyn Ehrlich. Thanks very much for coming on the Cube. Forced to research wicked, we find more about the research that you do force the dotcom, obviously, but anything new for you, any upcoming events that we should know about where people should watch >> you go into Crystal Rica, Nicaragua >> mochi ice all right. We'LL leave you alone for a while, right, Evelyn? Great to meet you. Thanks for coming on. I keep right there, buddy. We're back with our next guest Is the Q ber live from BMC Day in Boston right back.

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> Spark became a top level Apache project in 2014, and then shortly thereafter, burst onto the big data scene. Spark, along with the cloud, transformed and in many ways, disrupted the big data market. Databricks optimized its tech stack for Spark and took advantage of the cloud to really cleverly deliver a managed service that has become a leading AI and data platform among data scientists and data engineers. However, emerging customer data requirements are shifting into a direction that will cause modern data platform players generally and Databricks, specifically, we think, to make some key directional decisions and perhaps even reinvent themselves. Hello and welcome to this week's wikibon theCUBE Insights, powered by ETR. In this Breaking Analysis, we're going to do a deep dive into Databricks. We'll explore its current impressive market momentum. We're going to use some ETR survey data to show that, and then we'll lay out how customer data requirements are changing and what the ideal data platform will look like in the midterm future. We'll then evaluate core elements of the Databricks portfolio against that vision, and then we'll close with some strategic decisions that we think the company faces. And to do so, we welcome in our good friend, George Gilbert, former equities analyst, market analyst, and current Principal at TechAlpha Partners. George, good to see you. Thanks for coming on. >> Good to see you, Dave. >> All right, let me set this up. We're going to start by taking a look at where Databricks sits in the market in terms of how customers perceive the company and what it's momentum looks like. And this chart that we're showing here is data from ETS, the emerging technology survey of private companies. The N is 1,421. What we did is we cut the data on three sectors, analytics, database-data warehouse, and AI/ML. The vertical axis is a measure of customer sentiment, which evaluates an IT decision maker's awareness of the firm and the likelihood of engaging and/or purchase intent. The horizontal axis shows mindshare in the dataset, and we've highlighted Databricks, which has been a consistent high performer in this survey over the last several quarters. And as we, by the way, just as aside as we previously reported, OpenAI, which burst onto the scene this past quarter, leads all names, but Databricks is still prominent. You can see that the ETR shows some open source tools for reference, but as far as firms go, Databricks is very impressively positioned. Now, let's see how they stack up to some mainstream cohorts in the data space, against some bigger companies and sometimes public companies. This chart shows net score on the vertical axis, which is a measure of spending momentum and pervasiveness in the data set is on the horizontal axis. You can see that chart insert in the upper right, that informs how the dots are plotted, and net score against shared N. And that red dotted line at 40% indicates a highly elevated net score, anything above that we think is really, really impressive. And here we're just comparing Databricks with Snowflake, Cloudera, and Oracle. And that squiggly line leading to Databricks shows their path since 2021 by quarter. And you can see it's performing extremely well, maintaining an elevated net score and net range. Now it's comparable in the vertical axis to Snowflake, and it consistently is moving to the right and gaining share. Now, why did we choose to show Cloudera and Oracle? The reason is that Cloudera got the whole big data era started and was disrupted by Spark. And of course the cloud, Spark and Databricks and Oracle in many ways, was the target of early big data players like Cloudera. Take a listen to Cloudera CEO at the time, Mike Olson. This is back in 2010, first year of theCUBE, play the clip. >> Look, back in the day, if you had a data problem, if you needed to run business analytics, you wrote the biggest check you could to Sun Microsystems, and you bought a great big, single box, central server, and any money that was left over, you handed to Oracle for a database licenses and you installed that database on that box, and that was where you went for data. That was your temple of information. >> Okay? So Mike Olson implied that monolithic model was too expensive and inflexible, and Cloudera set out to fix that. But the best laid plans, as they say, George, what do you make of the data that we just shared? >> So where Databricks has really come up out of sort of Cloudera's tailpipe was they took big data processing, made it coherent, made it a managed service so it could run in the cloud. So it relieved customers of the operational burden. Where they're really strong and where their traditional meat and potatoes or bread and butter is the predictive and prescriptive analytics that building and training and serving machine learning models. They've tried to move into traditional business intelligence, the more traditional descriptive and diagnostic analytics, but they're less mature there. So what that means is, the reason you see Databricks and Snowflake kind of side by side is there are many, many accounts that have both Snowflake for business intelligence, Databricks for AI machine learning, where Snowflake, I'm sorry, where Databricks also did really well was in core data engineering, refining the data, the old ETL process, which kind of turned into ELT, where you loaded into the analytic repository in raw form and refine it. And so people have really used both, and each is trying to get into the other. >> Yeah, absolutely. We've reported on this quite a bit. Snowflake, kind of moving into the domain of Databricks and vice versa. And the last bit of ETR evidence that we want to share in terms of the company's momentum comes from ETR's Round Tables. They're run by Erik Bradley, and now former Gartner analyst and George, your colleague back at Gartner, Daren Brabham. And what we're going to show here is some direct quotes of IT pros in those Round Tables. There's a data science head and a CIO as well. Just make a few call outs here, we won't spend too much time on it, but starting at the top, like all of us, we can't talk about Databricks without mentioning Snowflake. Those two get us excited. Second comment zeros in on the flexibility and the robustness of Databricks from a data warehouse perspective. And then the last point is, despite competition from cloud players, Databricks has reinvented itself a couple of times over the year. And George, we're going to lay out today a scenario that perhaps calls for Databricks to do that once again. >> Their big opportunity and their big challenge for every tech company, it's managing a technology transition. The transition that we're talking about is something that's been bubbling up, but it's really epical. First time in 60 years, we're moving from an application-centric view of the world to a data-centric view, because decisions are becoming more important than automating processes. So let me let you sort of develop. >> Yeah, so let's talk about that here. We going to put up some bullets on precisely that point and the changing sort of customer environment. So you got IT stacks are shifting is George just said, from application centric silos to data centric stacks where the priority is shifting from automating processes to automating decision. You know how look at RPA and there's still a lot of automation going on, but from the focus of that application centricity and the data locked into those apps, that's changing. Data has historically been on the outskirts in silos, but organizations, you think of Amazon, think Uber, Airbnb, they're putting data at the core, and logic is increasingly being embedded in the data instead of the reverse. In other words, today, the data's locked inside the app, which is why you need to extract that data is sticking it to a data warehouse. The point, George, is we're putting forth this new vision for how data is going to be used. And you've used this Uber example to underscore the future state. Please explain? >> Okay, so this is hopefully an example everyone can relate to. The idea is first, you're automating things that are happening in the real world and decisions that make those things happen autonomously without humans in the loop all the time. So to use the Uber example on your phone, you call a car, you call a driver. Automatically, the Uber app then looks at what drivers are in the vicinity, what drivers are free, matches one, calculates an ETA to you, calculates a price, calculates an ETA to your destination, and then directs the driver once they're there. The point of this is that that cannot happen in an application-centric world very easily because all these little apps, the drivers, the riders, the routes, the fares, those call on data locked up in many different apps, but they have to sit on a layer that makes it all coherent. >> But George, so if Uber's doing this, doesn't this tech already exist? Isn't there a tech platform that does this already? >> Yes, and the mission of the entire tech industry is to build services that make it possible to compose and operate similar platforms and tools, but with the skills of mainstream developers in mainstream corporations, not the rocket scientists at Uber and Amazon. >> Okay, so we're talking about horizontally scaling across the industry, and actually giving a lot more organizations access to this technology. So by way of review, let's summarize the trend that's going on today in terms of the modern data stack that is propelling the likes of Databricks and Snowflake, which we just showed you in the ETR data and is really is a tailwind form. So the trend is toward this common repository for analytic data, that could be multiple virtual data warehouses inside of Snowflake, but you're in that Snowflake environment or Lakehouses from Databricks or multiple data lakes. And we've talked about what JP Morgan Chase is doing with the data mesh and gluing data lakes together, you've got various public clouds playing in this game, and then the data is annotated to have a common meaning. In other words, there's a semantic layer that enables applications to talk to the data elements and know that they have common and coherent meaning. So George, the good news is this approach is more effective than the legacy monolithic models that Mike Olson was talking about, so what's the problem with this in your view? >> So today's data platforms added immense value 'cause they connected the data that was previously locked up in these monolithic apps or on all these different microservices, and that supported traditional BI and AI/ML use cases. But now if we want to build apps like Uber or Amazon.com, where they've got essentially an autonomously running supply chain and e-commerce app where humans only care and feed it. But the thing is figuring out what to buy, when to buy, where to deploy it, when to ship it. We needed a semantic layer on top of the data. So that, as you were saying, the data that's coming from all those apps, the different apps that's integrated, not just connected, but it means the same. And the issue is whenever you add a new layer to a stack to support new applications, there are implications for the already existing layers, like can they support the new layer and its use cases? So for instance, if you add a semantic layer that embeds app logic with the data rather than vice versa, which we been talking about and that's been the case for 60 years, then the new data layer faces challenges that the way you manage that data, the way you analyze that data, is not supported by today's tools. >> Okay, so actually Alex, bring me up that last slide if you would, I mean, you're basically saying at the bottom here, today's repositories don't really do joins at scale. The future is you're talking about hundreds or thousands or millions of data connections, and today's systems, we're talking about, I don't know, 6, 8, 10 joins and that is the fundamental problem you're saying, is a new data error coming and existing systems won't be able to handle it? >> Yeah, one way of thinking about it is that even though we call them relational databases, when we actually want to do lots of joins or when we want to analyze data from lots of different tables, we created a whole new industry for analytic databases where you sort of mung the data together into fewer tables. So you didn't have to do as many joins because the joins are difficult and slow. And when you're going to arbitrarily join thousands, hundreds of thousands or across millions of elements, you need a new type of database. We have them, they're called graph databases, but to query them, you go back to the prerelational era in terms of their usability. >> Okay, so we're going to come back to that and talk about how you get around that problem. But let's first lay out what the ideal data platform of the future we think looks like. And again, we're going to come back to use this Uber example. In this graphic that George put together, awesome. We got three layers. The application layer is where the data products reside. The example here is drivers, rides, maps, routes, ETA, et cetera. The digital version of what we were talking about in the previous slide, people, places and things. The next layer is the data layer, that breaks down the silos and connects the data elements through semantics and everything is coherent. And then the bottom layers, the legacy operational systems feed that data layer. George, explain what's different here, the graph database element, you talk about the relational query capabilities, and why can't I just throw memory at solving this problem? >> Some of the graph databases do throw memory at the problem and maybe without naming names, some of them live entirely in memory. And what you're dealing with is a prerelational in-memory database system where you navigate between elements, and the issue with that is we've had SQL for 50 years, so we don't have to navigate, we can say what we want without how to get it. That's the core of the problem. >> Okay. So if I may, I just want to drill into this a little bit. So you're talking about the expressiveness of a graph. Alex, if you'd bring that back out, the fourth bullet, expressiveness of a graph database with the relational ease of query. Can you explain what you mean by that? >> Yeah, so graphs are great because when you can describe anything with a graph, that's why they're becoming so popular. Expressive means you can represent anything easily. They're conducive to, you might say, in a world where we now want like the metaverse, like with a 3D world, and I don't mean the Facebook metaverse, I mean like the business metaverse when we want to capture data about everything, but we want it in context, we want to build a set of digital twins that represent everything going on in the world. And Uber is a tiny example of that. Uber built a graph to represent all the drivers and riders and maps and routes. But what you need out of a database isn't just a way to store stuff and update stuff. You need to be able to ask questions of it, you need to be able to query it. And if you go back to prerelational days, you had to know how to find your way to the data. It's sort of like when you give directions to someone and they didn't have a GPS system and a mapping system, you had to give them turn by turn directions. Whereas when you have a GPS and a mapping system, which is like the relational thing, you just say where you want to go, and it spits out the turn by turn directions, which let's say, the car might follow or whoever you're directing would follow. But the point is, it's much easier in a relational database to say, "I just want to get these results. You figure out how to get it." The graph database, they have not taken over the world because in some ways, it's taking a 50 year leap backwards. >> Alright, got it. Okay. Let's take a look at how the current Databricks offerings map to that ideal state that we just laid out. So to do that, we put together this chart that looks at the key elements of the Databricks portfolio, the core capability, the weakness, and the threat that may loom. Start with the Delta Lake, that's the storage layer, which is great for files and tables. It's got true separation of compute and storage, I want you to double click on that George, as independent elements, but it's weaker for the type of low latency ingest that we see coming in the future. And some of the threats highlighted here. AWS could add transactional tables to S3, Iceberg adoption is picking up and could accelerate, that could disrupt Databricks. George, add some color here please? >> Okay, so this is the sort of a classic competitive forces where you want to look at, so what are customers demanding? What's competitive pressure? What are substitutes? Even what your suppliers might be pushing. Here, Delta Lake is at its core, a set of transactional tables that sit on an object store. So think of it in a database system, this is the storage engine. So since S3 has been getting stronger for 15 years, you could see a scenario where they add transactional tables. We have an open source alternative in Iceberg, which Snowflake and others support. But at the same time, Databricks has built an ecosystem out of tools, their own and others, that read and write to Delta tables, that's what makes the Delta Lake and ecosystem. So they have a catalog, the whole machine learning tool chain talks directly to the data here. That was their great advantage because in the past with Snowflake, you had to pull all the data out of the database before the machine learning tools could work with it, that was a major shortcoming. They fixed that. But the point here is that even before we get to the semantic layer, the core foundation is under threat. >> Yep. Got it. Okay. We got a lot of ground to cover. So we're going to take a look at the Spark Execution Engine next. Think of that as the refinery that runs really efficient batch processing. That's kind of what disrupted the DOOp in a large way, but it's not Python friendly and that's an issue because the data science and the data engineering crowd are moving in that direction, and/or they're using DBT. George, we had Tristan Handy on at Supercloud, really interesting discussion that you and I did. Explain why this is an issue for Databricks? >> So once the data lake was in place, what people did was they refined their data batch, and Spark has always had streaming support and it's gotten better. The underlying storage as we've talked about is an issue. But basically they took raw data, then they refined it into tables that were like customers and products and partners. And then they refined that again into what was like gold artifacts, which might be business intelligence metrics or dashboards, which were collections of metrics. But they were running it on the Spark Execution Engine, which it's a Java-based engine or it's running on a Java-based virtual machine, which means all the data scientists and the data engineers who want to work with Python are really working in sort of oil and water. Like if you get an error in Python, you can't tell whether the problems in Python or where it's in Spark. There's just an impedance mismatch between the two. And then at the same time, the whole world is now gravitating towards DBT because it's a very nice and simple way to compose these data processing pipelines, and people are using either SQL in DBT or Python in DBT, and that kind of is a substitute for doing it all in Spark. So it's under threat even before we get to that semantic layer, it so happens that DBT itself is becoming the authoring environment for the semantic layer with business intelligent metrics. But that's again, this is the second element that's under direct substitution and competitive threat. >> Okay, let's now move down to the third element, which is the Photon. Photon is Databricks' BI Lakehouse, which has integration with the Databricks tooling, which is very rich, it's newer. And it's also not well suited for high concurrency and low latency use cases, which we think are going to increasingly become the norm over time. George, the call out threat here is customers want to connect everything to a semantic layer. Explain your thinking here and why this is a potential threat to Databricks? >> Okay, so two issues here. What you were touching on, which is the high concurrency, low latency, when people are running like thousands of dashboards and data is streaming in, that's a problem because SQL data warehouse, the query engine, something like that matures over five to 10 years. It's one of these things, the joke that Andy Jassy makes just in general, he's really talking about Azure, but there's no compression algorithm for experience. The Snowflake guy started more than five years earlier, and for a bunch of reasons, that lead is not something that Databricks can shrink. They'll always be behind. So that's why Snowflake has transactional tables now and we can get into that in another show. But the key point is, so near term, it's struggling to keep up with the use cases that are core to business intelligence, which is highly concurrent, lots of users doing interactive query. But then when you get to a semantic layer, that's when you need to be able to query data that might have thousands or tens of thousands or hundreds of thousands of joins. And that's a SQL query engine, traditional SQL query engine is just not built for that. That's the core problem of traditional relational databases. >> Now this is a quick aside. We always talk about Snowflake and Databricks in sort of the same context. We're not necessarily saying that Snowflake is in a position to tackle all these problems. We'll deal with that separately. So we don't mean to imply that, but we're just sort of laying out some of the things that Snowflake or rather Databricks customers we think, need to be thinking about and having conversations with Databricks about and we hope to have them as well. We'll come back to that in terms of sort of strategic options. But finally, when come back to the table, we have Databricks' AI/ML Tool Chain, which has been an awesome capability for the data science crowd. It's comprehensive, it's a one-stop shop solution, but the kicker here is that it's optimized for supervised model building. And the concern is that foundational models like GPT could cannibalize the current Databricks tooling, but George, can't Databricks, like other software companies, integrate foundation model capabilities into its platform? >> Okay, so the sound bite answer to that is sure, IBM 3270 terminals could call out to a graphical user interface when they're running on the XT terminal, but they're not exactly good citizens in that world. The core issue is Databricks has this wonderful end-to-end tool chain for training, deploying, monitoring, running inference on supervised models. But the paradigm there is the customer builds and trains and deploys each model for each feature or application. In a world of foundation models which are pre-trained and unsupervised, the entire tool chain is different. So it's not like Databricks can junk everything they've done and start over with all their engineers. They have to keep maintaining what they've done in the old world, but they have to build something new that's optimized for the new world. It's a classic technology transition and their mentality appears to be, "Oh, we'll support the new stuff from our old stuff." Which is suboptimal, and as we'll talk about, their biggest patron and the company that put them on the map, Microsoft, really stopped working on their old stuff three years ago so that they could build a new tool chain optimized for this new world. >> Yeah, and so let's sort of close with what we think the options are and decisions that Databricks has for its future architecture. They're smart people. I mean we've had Ali Ghodsi on many times, super impressive. I think they've got to be keenly aware of the limitations, what's going on with foundation models. But at any rate, here in this chart, we lay out sort of three scenarios. One is re-architect the platform by incrementally adopting new technologies. And example might be to layer a graph query engine on top of its stack. They could license key technologies like graph database, they could get aggressive on M&A and buy-in, relational knowledge graphs, semantic technologies, vector database technologies. George, as David Floyer always says, "A lot of ways to skin a cat." We've seen companies like, even think about EMC maintained its relevance through M&A for many, many years. George, give us your thought on each of these strategic options? >> Okay, I find this question the most challenging 'cause remember, I used to be an equity research analyst. I worked for Frank Quattrone, we were one of the top tech shops in the banking industry, although this is 20 years ago. But the M&A team was the top team in the industry and everyone wanted them on their side. And I remember going to meetings with these CEOs, where Frank and the bankers would say, "You want us for your M&A work because we can do better." And they really could do better. But in software, it's not like with EMC in hardware because with hardware, it's easier to connect different boxes. With software, the whole point of a software company is to integrate and architect the components so they fit together and reinforce each other, and that makes M&A harder. You can do it, but it takes a long time to fit the pieces together. Let me give you examples. If they put a graph query engine, let's say something like TinkerPop, on top of, I don't even know if it's possible, but let's say they put it on top of Delta Lake, then you have this graph query engine talking to their storage layer, Delta Lake. But if you want to do analysis, you got to put the data in Photon, which is not really ideal for highly connected data. If you license a graph database, then most of your data is in the Delta Lake and how do you sync it with the graph database? If you do sync it, you've got data in two places, which kind of defeats the purpose of having a unified repository. I find this semantic layer option in number three actually more promising, because that's something that you can layer on top of the storage layer that you have already. You just have to figure out then how to have your query engines talk to that. What I'm trying to highlight is, it's easy as an analyst to say, "You can buy this company or license that technology." But the really hard work is making it all work together and that is where the challenge is. >> Yeah, and well look, I thank you for laying that out. We've seen it, certainly Microsoft and Oracle. I guess you might argue that well, Microsoft had a monopoly in its desktop software and was able to throw off cash for a decade plus while it's stock was going sideways. Oracle had won the database wars and had amazing margins and cash flow to be able to do that. Databricks isn't even gone public yet, but I want to close with some of the players to watch. Alex, if you'd bring that back up, number four here. AWS, we talked about some of their options with S3 and it's not just AWS, it's blob storage, object storage. Microsoft, as you sort of alluded to, was an early go-to market channel for Databricks. We didn't address that really. So maybe in the closing comments we can. Google obviously, Snowflake of course, we're going to dissect their options in future Breaking Analysis. Dbt labs, where do they fit? Bob Muglia's company, Relational.ai, why are these players to watch George, in your opinion? >> So everyone is trying to assemble and integrate the pieces that would make building data applications, data products easy. And the critical part isn't just assembling a bunch of pieces, which is traditionally what AWS did. It's a Unix ethos, which is we give you the tools, you put 'em together, 'cause you then have the maximum choice and maximum power. So what the hyperscalers are doing is they're taking their key value stores, in the case of ASW it's DynamoDB, in the case of Azure it's Cosmos DB, and each are putting a graph query engine on top of those. So they have a unified storage and graph database engine, like all the data would be collected in the key value store. Then you have a graph database, that's how they're going to be presenting a foundation for building these data apps. Dbt labs is putting a semantic layer on top of data lakes and data warehouses and as we'll talk about, I'm sure in the future, that makes it easier to swap out the underlying data platform or swap in new ones for specialized use cases. Snowflake, what they're doing, they're so strong in data management and with their transactional tables, what they're trying to do is take in the operational data that used to be in the province of many state stores like MongoDB and say, "If you manage that data with us, it'll be connected to your analytic data without having to send it through a pipeline." And that's hugely valuable. Relational.ai is the wildcard, 'cause what they're trying to do, it's almost like a holy grail where you're trying to take the expressiveness of connecting all your data in a graph but making it as easy to query as you've always had it in a SQL database or I should say, in a relational database. And if they do that, it's sort of like, it'll be as easy to program these data apps as a spreadsheet was compared to procedural languages, like BASIC or Pascal. That's the implications of Relational.ai. >> Yeah, and again, we talked before, why can't you just throw this all in memory? We're talking in that example of really getting down to differences in how you lay the data out on disk in really, new database architecture, correct? >> Yes. And that's why it's not clear that you could take a data lake or even a Snowflake and why you can't put a relational knowledge graph on those. You could potentially put a graph database, but it'll be compromised because to really do what Relational.ai has done, which is the ease of Relational on top of the power of graph, you actually need to change how you're storing your data on disk or even in memory. So you can't, in other words, it's not like, oh we can add graph support to Snowflake, 'cause if you did that, you'd have to change, or in your data lake, you'd have to change how the data is physically laid out. And then that would break all the tools that talk to that currently. >> What in your estimation, is the timeframe where this becomes critical for a Databricks and potentially Snowflake and others? I mentioned earlier midterm, are we talking three to five years here? Are we talking end of decade? What's your radar say? >> I think something surprising is going on that's going to sort of come up the tailpipe and take everyone by storm. All the hype around business intelligence metrics, which is what we used to put in our dashboards where bookings, billings, revenue, customer, those things, those were the key artifacts that used to live in definitions in your BI tools, and DBT has basically created a standard for defining those so they live in your data pipeline or they're defined in their data pipeline and executed in the data warehouse or data lake in a shared way, so that all tools can use them. This sounds like a digression, it's not. All this stuff about data mesh, data fabric, all that's going on is we need a semantic layer and the business intelligence metrics are defining common semantics for your data. And I think we're going to find by the end of this year, that metrics are how we annotate all our analytic data to start adding common semantics to it. And we're going to find this semantic layer, it's not three to five years off, it's going to be staring us in the face by the end of this year. >> Interesting. And of course SVB today was shut down. We're seeing serious tech headwinds, and oftentimes in these sort of downturns or flat turns, which feels like this could be going on for a while, we emerge with a lot of new players and a lot of new technology. George, we got to leave it there. Thank you to George Gilbert for excellent insights and input for today's episode. I want to thank Alex Myerson who's on production and manages the podcast, of course Ken Schiffman as well. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our EIC over at Siliconangle.com, he does some great editing. Remember all these episodes, they're available as podcasts. Wherever you listen, all you got to do is search Breaking Analysis Podcast, we publish each week on wikibon.com and siliconangle.com, or you can email me at David.Vellante@siliconangle.com, or DM me @DVellante. Comment on our LinkedIn post, and please do check out ETR.ai, great survey data, enterprise tech focus, phenomenal. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, and we'll see you next time on Breaking Analysis.

(upbeat music) >> Hello and welcome to theCube's coverage of International Women's Day. I'm John Furrier, your host of "theCUBE." We've got great two remote guests coming into our Palo Alto Studios, some tech athletes, as we say, people that've been in the trenches, years of experience, Lena Smart, CISO at MongoDB, Cube alumni, and Tara Hernandez, VP of Developer Productivity at MongoDB as well. Thanks for coming in to this program and supporting our efforts today. Thanks so much. >> Thanks for having us. >> Yeah, everyone talk about the journey in tech, where it all started. Before we get there, talk about what you guys are doing at MongoDB specifically. MongoDB is kind of gone the next level as a platform. You have your own ecosystem, lot of developers, very technical crowd, but it's changing the business transformation. What do you guys do at Mongo? We'll start with you, Lena. >> So I'm the CISO, so all security goes through me. I like to say, well, I don't like to say, I'm described as the ones throat to choke. So anything to do with security basically starts and ends with me. We do have a fantastic Cloud engineering security team and a product security team, and they don't report directly to me, but obviously we have very close relationships. I like to keep that kind of church and state separate and I know I've spoken about that before. And we just recently set up a physical security team with an amazing gentleman who left the FBI and he came to join us after 26 years for the agency. So, really starting to look at the physical aspects of what we offer as well. >> I interviewed a CISO the other day and she said, "Every day is day zero for me." Kind of goofing on the Amazon Day one thing, but Tara, go ahead. Tara, go ahead. What's your role there, developer productivity? What are you focusing on? >> Sure. Developer productivity is kind of the latest description for things that we've described over the years as, you know, DevOps oriented engineering or platform engineering or build and release engineering development infrastructure. It's all part and parcel, which is how do we actually get our code from developer to customer, you know, and all the mechanics that go into that. It's been something I discovered from my first job way back in the early '90s at Borland. And the art has just evolved enormously ever since, so. >> Yeah, this is a very great conversation both of you guys, right in the middle of all the action and data infrastructures changing, exploding, and involving big time AI and data tsunami and security never stops. Well, let's get into, we'll talk about that later, but let's get into what motivated you guys to pursue a career in tech and what were some of the challenges that you faced along the way? >> I'll go first. The fact of the matter was I intended to be a double major in history and literature when I went off to university, but I was informed that I had to do a math or a science degree or else the university would not be paid for. At the time, UC Santa Cruz had a policy that called Open Access Computing. This is, you know, the late '80s, early '90s. And anybody at the university could get an email account and that was unusual at the time if you were, those of us who remember, you used to have to pay for that CompuServe or AOL or, there's another one, I forget what it was called, but if a student at Santa Cruz could have an email account. And because of that email account, I met people who were computer science majors and I'm like, "Okay, I'll try that." That seems good. And it was a little bit of a struggle for me, a lot I won't lie, but I can't complain with how it ended up. And certainly once I found my niche, which was development infrastructure, I found my true love and I've been doing it for almost 30 years now. >> Awesome. Great story. Can't wait to ask a few questions on that. We'll go back to that late '80s, early '90s. Lena, your journey, how you got into it. >> So slightly different start. I did not go to university. I had to leave school when I was 16, got a job, had to help support my family. Worked a bunch of various jobs till I was about 21 and then computers became more, I think, I wouldn't say they were ubiquitous, but they were certainly out there. And I'd also been saving up every penny I could earn to buy my own computer and bought an Amstrad 1640, 20 meg hard drive. It rocked. And kind of took that apart, put it back together again, and thought that could be money in this. And so basically just teaching myself about computers any job that I got. 'Cause most of my jobs were like clerical work and secretary at that point. But any job that had a computer in front of that, I would make it my business to go find the guy who did computing 'cause it was always a guy. And I would say, you know, I want to learn how these work. Let, you know, show me. And, you know, I would take my lunch hour and after work and anytime I could with these people and they were very kind with their time and I just kept learning, so yep. >> Yeah, those early days remind me of the inflection point we're going through now. This major C change coming. Back then, if you had a computer, you had to kind of be your own internal engineer to fix things. Remember back on the systems revolution, late '80s, Tara, when, you know, your career started, those were major inflection points. Now we're seeing a similar wave right now, security, infrastructure. It feels like it's going to a whole nother level. At Mongo, you guys certainly see this as well, with this AI surge coming in. A lot more action is coming in. And so there's a lot of parallels between these inflection points. How do you guys see this next wave of change? Obviously, the AI stuff's blowing everyone away. Oh, new user interface. It's been called the browser moment, the mobile iPhone moment, kind of for this generation. There's a lot of people out there who are watching that are young in their careers, what's your take on this? How would you talk to those folks around how important this wave is? >> It, you know, it's funny, I've been having this conversation quite a bit recently in part because, you know, to me AI in a lot of ways is very similar to, you know, back in the '90s when we were talking about bringing in the worldwide web to the forefront of the world, right. And we tended to think in terms of all the optimistic benefits that would come of it. You know, free passing of information, availability to anyone, anywhere. You just needed an internet connection, which back then of course meant a modem. >> John: Not everyone had though. >> Exactly. But what we found in the subsequent years is that human beings are what they are and we bring ourselves to whatever platforms that are there, right. And so, you know, as much as it was amazing to have this freely available HTML based internet experience, it also meant that the negatives came to the forefront quite quickly. And there were ramifications of that. And so to me, when I look at AI, we're already seeing the ramifications to that. Yes, are there these amazing, optimistic, wonderful things that can be done? Yes. >> Yeah. >> But we're also human and the bad stuff's going to come out too. And how do we- >> Yeah. >> How do we as an industry, as a community, you know, understand and mitigate those ramifications so that we can benefit more from the positive than the negative. So it is interesting that it comes kind of full circle in really interesting ways. >> Yeah. The underbelly takes place first, gets it in the early adopter mode. Normally industries with, you know, money involved arbitrage, no standards. But we've seen this movie before. Is there hope, Lena, that we can have a more secure environment? >> I would hope so. (Lena laughs) Although depressingly, we've been in this well for 30 years now and we're, at the end of the day, still telling people not to click links on emails. So yeah, that kind of still keeps me awake at night a wee bit. The whole thing about AI, I mean, it's, obviously I am not an expert by any stretch of the imagination in AI. I did read (indistinct) book recently about AI and that was kind of interesting. And I'm just trying to teach myself as much as I can about it to the extent of even buying the "Dummies Guide to AI." Just because, it's actually not a dummies guide. It's actually fairly interesting, but I'm always thinking about it from a security standpoint. So it's kind of my worst nightmare and the best thing that could ever happen in the same dream. You know, you've got this technology where I can ask it a question and you know, it spits out generally a reasonable answer. And my team are working on with Mark Porter our CTO and his team on almost like an incubation of AI link. What would it look like from MongoDB? What's the legal ramifications? 'Cause there will be legal ramifications even though it's the wild, wild west just now, I think. Regulation's going to catch up to us pretty quickly, I would think. >> John: Yeah, yeah. >> And so I think, you know, as long as companies have a seat at the table and governments perhaps don't become too dictatorial over this, then hopefully we'll be in a good place. But we'll see. I think it's a really interest, there's that curse, we're living in interesting times. I think that's where we are. >> It's interesting just to stay on this tech trend for a minute. The standards bodies are different now. Back in the old days there were, you know, IEEE standards, ITF standards. >> Tara: TPC. >> The developers are the new standard. I mean, now you're seeing open source completely different where it was in the '90s to here beginning, that was gen one, some say gen two, but I say gen one, now we're exploding with open source. You have kind of developers setting the standards. If developers like it in droves, it becomes defacto, which then kind of rolls into implementation. >> Yeah, I mean I think if you don't have developer input, and this is why I love working with Tara and her team so much is 'cause they get it. If we don't have input from developers, it's not going to get used. There's going to be ways of of working around it, especially when it comes to security. If they don't, you know, if you're a developer and you're sat at your screen and you don't want to do that particular thing, you're going to find a way around it. You're a smart person. >> Yeah. >> So. >> Developers on the front lines now versus, even back in the '90s, they're like, "Okay, consider the dev's, got a QA team." Everything was Waterfall, now it's Cloud, and developers are on the front lines of everything. Tara, I mean, this is where the standards are being met. What's your reaction to that? >> Well, I think it's outstanding. I mean, you know, like I was at Netscape and part of the crowd that released the browser as open source and we founded mozilla.org, right. And that was, you know, in many ways kind of the birth of the modern open source movement beyond what we used to have, what was basically free software foundation was sort of the only game in town. And I think it is so incredibly valuable. I want to emphasize, you know, and pile onto what Lena was saying, it's not just that the developers are having input on a sort of company by company basis. Open source to me is like a checks and balance, where it allows us as a broader community to be able to agree on and enforce certain standards in order to try and keep the technology platforms as accessible as possible. I think Kubernetes is a great example of that, right. If we didn't have Kubernetes, that would've really changed the nature of how we think about container orchestration. But even before that, Linux, right. Linux allowed us as an industry to end the Unix Wars and as someone who was on the front lines of that as well and having to support 42 different operating systems with our product, you know, that was a huge win. And it allowed us to stop arguing about operating systems and start arguing about software or not arguing, but developing it in positive ways. So with, you know, with Kubernetes, with container orchestration, we all agree, okay, that's just how we're going to orchestrate. Now we can build up this huge ecosystem, everybody gets taken along, right. And now it changes the game for what we're defining as business differentials, right. And so when we talk about crypto, that's a little bit harder, but certainly with AI, right, you know, what are the checks and balances that as an industry and as the developers around this, that we can in, you know, enforce to make sure that no one company or no one body is able to overly control how these things are managed, how it's defined. And I think that is only for the benefit in the industry as a whole, particularly when we think about the only other option is it gets regulated in ways that do not involve the people who actually know the details of what they're talking about. >> Regulated and or thrown away or bankrupt or- >> Driven underground. >> Yeah. >> Which would be even worse actually. >> Yeah, that's a really interesting, the checks and balances. I love that call out. And I was just talking with another interview part of the series around women being represented in the 51% ratio. Software is for everybody. So that we believe that open source movement around the collective intelligence of the participants in the industry and independent of gender, this is going to be the next wave. You're starting to see these videos really have impact because there are a lot more leaders now at the table in companies developing software systems and with AI, the aperture increases for applications. And this is the new dynamic. What's your guys view on this dynamic? How does this go forward in a positive way? Is there a certain trajectory you see? For women in the industry? >> I mean, I think some of the states are trying to, again, from the government angle, some of the states are trying to force women into the boardroom, for example, California, which can be no bad thing, but I don't know, sometimes I feel a bit iffy about all this kind of forced- >> John: Yeah. >> You know, making, I don't even know how to say it properly so you can cut this part of the interview. (John laughs) >> Tara: Well, and I think that they're >> I'll say it's not organic. >> No, and I think they're already pulling it out, right. It's already been challenged so they're in the process- >> Well, this is the open source angle, Tara, you are getting at it. The change agent is open, right? So to me, the history of the proven model is openness drives transparency drives progress. >> No, it's- >> If you believe that to be true, this could have another impact. >> Yeah, it's so interesting, right. Because if you look at McKinsey Consulting or Boston Consulting or some of the other, I'm blocking on all of the names. There has been a decade or more of research that shows that a non homogeneous employee base, be it gender or ethnicity or whatever, generates more revenue, right? There's dollar signs that can be attached to this, but it's not enough for all companies to want to invest in that way. And it's not enough for all, you know, venture firms or investment firms to grant that seed money or do those seed rounds. I think it's getting better very slowly, but socialization is a much harder thing to overcome over time. Particularly, when you're not just talking about one country like the United States in our case, but around the world. You know, tech centers now exist all over the world, including places that even 10 years ago we might not have expected like Nairobi, right. Which I think is amazing, but you have to factor in the cultural implications of that as well, right. So yes, the openness is important and we have, it's important that we have those voices, but I don't think it's a panacea solution, right. It's just one more piece. I think honestly that one of the most important opportunities has been with Cloud computing and Cloud's been around for a while. So why would I say that? It's because if you think about like everybody holds up the Steve Jobs, Steve Wozniak, back in the '70s, or Sergey and Larry for Google, you know, you had to have access to enough credit card limit to go to Fry's and buy your servers and then access to somebody like Susan Wojcicki to borrow the garage or whatever. But there was still a certain amount of upfrontness that you had to be able to commit to, whereas now, and we've, I think, seen a really good evidence of this being able to lease server resources by the second and have development platforms that you can do on your phone. I mean, for a while I think Africa, that the majority of development happened on mobile devices because there wasn't a sufficient supply chain of laptops yet. And that's no longer true now as far as I know. But like the power that that enables for people who would otherwise be underrepresented in our industry instantly opens it up, right? And so to me that's I think probably the biggest opportunity that we've seen from an industry on how to make more availability in underrepresented representation for entrepreneurship. >> Yeah. >> Something like AI, I think that's actually going to take us backwards if we're not careful. >> Yeah. >> Because of we're reinforcing that socialization. >> Well, also the bias. A lot of people commenting on the biases of the large language inherently built in are also problem. Lena, I want you to weigh on this too, because I think the skills question comes up here and I've been advocating that you don't need the pedigree, college pedigree, to get into a certain jobs, you mentioned Cloud computing. I mean, it's been around for you think a long time, but not really, really think about it. The ability to level up, okay, if you're going to join something new and half the jobs in cybersecurity are created in the past year, right? So, you have this what used to be a barrier, your degree, your pedigree, your certification would take years, would be a blocker. Now that's gone. >> Lena: Yeah, it's the opposite. >> That's, in fact, psychology. >> I think so, but the people who I, by and large, who I interview for jobs, they have, I think security people and also I work with our compliance folks and I can't forget them, but let's talk about security just now. I've always found a particular kind of mindset with security folks. We're very curious, not very good at following rules a lot of the time, and we'd love to teach others. I mean, that's one of the big things stem from the start of my career. People were always interested in teaching and I was interested in learning. So it was perfect. And I think also having, you know, strong women leaders at MongoDB allows other underrepresented groups to actually apply to the company 'cause they see that we're kind of talking the talk. And that's been important. I think it's really important. You know, you've got Tara and I on here today. There's obviously other senior women at MongoDB that you can talk to as well. There's a bunch of us. There's not a whole ton of us, but there's a bunch of us. And it's good. It's definitely growing. I've been there for four years now and I've seen a growth in women in senior leadership positions. And I think having that kind of track record of getting really good quality underrepresented candidates to not just interview, but come and join us, it's seen. And it's seen in the industry and people take notice and they're like, "Oh, okay, well if that person's working, you know, if Tara Hernandez is working there, I'm going to apply for that." And that in itself I think can really, you know, reap the rewards. But it's getting started. It's like how do you get your first strong female into that position or your first strong underrepresented person into that position? It's hard. I get it. If it was easy, we would've sold already. >> It's like anything. I want to see people like me, my friends in there. Am I going to be alone? Am I going to be of a group? It's a group psychology. Why wouldn't? So getting it out there is key. Is there skills that you think that people should pay attention to? One's come up as curiosity, learning. What are some of the best practices for folks trying to get into the tech field or that's in the tech field and advancing through? What advice are you guys- >> I mean, yeah, definitely, what I say to my team is within my budget, we try and give every at least one training course a year. And there's so much free stuff out there as well. But, you know, keep learning. And even if it's not right in your wheelhouse, don't pick about it. Don't, you know, take a look at what else could be out there that could interest you and then go for it. You know, what does it take you few minutes each night to read a book on something that might change your entire career? You know, be enthusiastic about the opportunities out there. And there's so many opportunities in security. Just so many. >> Tara, what's your advice for folks out there? Tons of stuff to taste, taste test, try things. >> Absolutely. I mean, I always say, you know, my primary qualifications for people, I'm looking for them to be smart and motivated, right. Because the industry changes so quickly. What we're doing now versus what we did even last year versus five years ago, you know, is completely different though themes are certainly the same. You know, we still have to code and we still have to compile that code or package the code and ship the code so, you know, how well can we adapt to these new things instead of creating floppy disks, which was my first job. Five and a quarters, even. The big ones. >> That's old school, OG. There it is. Well done. >> And now it's, you know, containers, you know, (indistinct) image containers. And so, you know, I've gotten a lot of really great success hiring boot campers, you know, career transitioners. Because they bring a lot experience in addition to the technical skills. I think the most important thing is to experiment and figuring out what do you like, because, you know, maybe you are really into security or maybe you're really into like deep level coding and you want to go back, you know, try to go to school to get a degree where you would actually want that level of learning. Or maybe you're a front end engineer, you want to be full stacked. Like there's so many different things, data science, right. Maybe you want to go learn R right. You know, I think it's like figure out what you like because once you find that, that in turn is going to energize you 'cause you're going to feel motivated. I think the worst thing you could do is try to force yourself to learn something that you really could not care less about. That's just the worst. You're going in handicapped. >> Yeah and there's choices now versus when we were breaking into the business. It was like, okay, you software engineer. They call it software engineering, that's all it was. You were that or you were in sales. Like, you know, some sort of systems engineer or sales and now it's,- >> I had never heard of my job when I was in school, right. I didn't even know it was a possibility. But there's so many different types of technical roles, you know, absolutely. >> It's so exciting. I wish I was young again. >> One of the- >> Me too. (Lena laughs) >> I don't. I like the age I am. So one of the things that I did to kind of harness that curiosity is we've set up a security champions programs. About 120, I guess, volunteers globally. And these are people from all different backgrounds and all genders, diversity groups, underrepresented groups, we feel are now represented within this champions program. And people basically give up about an hour or two of their time each week, with their supervisors permission, and we basically teach them different things about security. And we've now had seven full-time people move from different areas within MongoDB into my team as a result of that program. So, you know, monetarily and time, yeah, saved us both. But also we're showing people that there is a path, you know, if you start off in Tara's team, for example, doing X, you join the champions program, you're like, "You know, I'd really like to get into red teaming. That would be so cool." If it fits, then we make that happen. And that has been really important for me, especially to give, you know, the women in the underrepresented groups within MongoDB just that window into something they might never have seen otherwise. >> That's a great common fit is fit matters. Also that getting access to what you fit is also access to either mentoring or sponsorship or some sort of, at least some navigation. Like what's out there and not being afraid to like, you know, just ask. >> Yeah, we just actually kicked off our big mentor program last week, so I'm the executive sponsor of that. I know Tara is part of it, which is fantastic. >> We'll put a plug in for it. Go ahead. >> Yeah, no, it's amazing. There's, gosh, I don't even know the numbers anymore, but there's a lot of people involved in this and so much so that we've had to set up mentoring groups rather than one-on-one. And I think it was 45% of the mentors are actually male, which is quite incredible for a program called Mentor Her. And then what we want to do in the future is actually create a program called Mentor Them so that it's not, you know, not just on the female and so that we can live other groups represented and, you know, kind of break down those groups a wee bit more and have some more granularity in the offering. >> Tara, talk about mentoring and sponsorship. Open source has been there for a long time. People help each other. It's community-oriented. What's your view of how to work with mentors and sponsors if someone's moving through ranks? >> You know, one of the things that was really interesting, unfortunately, in some of the earliest open source communities is there was a lot of pervasive misogyny to be perfectly honest. >> Yeah. >> And one of the important adaptations that we made as an open source community was the idea, an introduction of code of conducts. And so when I'm talking to women who are thinking about expanding their skills, I encourage them to join open source communities to have opportunity, even if they're not getting paid for it, you know, to develop their skills to work with people to get those code reviews, right. I'm like, "Whatever you join, make sure they have a code of conduct and a good leadership team. It's very important." And there are plenty, right. And then that idea has come into, you know, conferences now. So now conferences have codes of contact, if there are any good, and maybe not all of them, but most of them, right. And the ideas of expanding that idea of intentional healthy culture. >> John: Yeah. >> As a business goal and business differentiator. I mean, I won't lie, when I was recruited to come to MongoDB, the culture that I was able to discern through talking to people, in addition to seeing that there was actually women in senior leadership roles like Lena, like Kayla Nelson, that was a huge win. And so it just builds on momentum. And so now, you know, those of us who are in that are now representing. And so that kind of reinforces, but it's all ties together, right. As the open source world goes, particularly for a company like MongoDB, which has an open source product, you know, and our community builds. You know, it's a good thing to be mindful of for us, how we interact with the community and you know, because that could also become an opportunity for recruiting. >> John: Yeah. >> Right. So we, in addition to people who might become advocates on Mongo's behalf in their own company as a solution for themselves, so. >> You guys had great successful company and great leadership there. I mean, I can't tell you how many times someone's told me "MongoDB doesn't scale. It's going to be dead next year." I mean, I was going back 10 years. It's like, just keeps getting better and better. You guys do a great job. So it's so fun to see the success of developers. Really appreciate you guys coming on the program. Final question, what are you guys excited about to end the segment? We'll give you guys the last word. Lena will start with you and Tara, you can wrap us up. What are you excited about? >> I'm excited to see what this year brings. I think with ChatGPT and its copycats, I think it'll be a very interesting year when it comes to AI and always in the lookout for the authentic deep fakes that we see coming out. So just trying to make people aware that this is a real thing. It's not just pretend. And then of course, our old friend ransomware, let's see where that's going to go. >> John: Yeah. >> And let's see where we get to and just genuine hygiene and housekeeping when it comes to security. >> Excellent. Tara. >> Ah, well for us, you know, we're always constantly trying to up our game from a security perspective in the software development life cycle. But also, you know, what can we do? You know, one interesting application of AI that maybe Google doesn't like to talk about is it is really cool as an addendum to search and you know, how we might incorporate that as far as our learning environment and developer productivity, and how can we enable our developers to be more efficient, productive in their day-to-day work. So, I don't know, there's all kinds of opportunities that we're looking at for how we might improve that process here at MongoDB and then maybe be able to share it with the world. One of the things I love about working at MongoDB is we get to use our own products, right. And so being able to have this interesting document database in order to put information and then maybe apply some sort of AI to get it out again, is something that we may well be looking at, if not this year, then certainly in the coming year. >> Awesome. Lena Smart, the chief information security officer. Tara Hernandez, vice president developer of productivity from MongoDB. Thank you so much for sharing here on International Women's Day. We're going to do this quarterly every year. We're going to do it and then we're going to do quarterly updates. Thank you so much for being part of this program. >> Thank you. >> Thanks for having us. >> Okay, this is theCube's coverage of International Women's Day. I'm John Furrier, your host. Thanks for watching. (upbeat music)

(upbeat music) >> Hi, everyone. Welcome to theCUBE's coverage of International Women's Day. I'm John Furrier, host of theCUBE. As part of International Women's Day, we're featuring some of the leading women in business technology from developer to all types of titles and to the executive level. And one topic that's really important is called Getting a Seat at the Table, board makeup, having representation at corporate boards, private and public companies. It's been a big push. And former technology operating executive and corporate board member, she's a board machine Sue Barsamian, formerly with HPE, Hewlett Packard. Sue, great to see you. CUBE alumni, distinguished CUBE alumni. Thank you for coming on. >> Yes, I'm very proud of my CUBE alumni title. >> I'm sure it opens a lot of doors for you. (Sue laughing) We're psyched to have you on. This is a really important topic, and I want to get into the whole, as women advance up, and they're sitting on the boards, they can implement policy and there's governance. Obviously public companies have very strict oversight, and not strict, but like formal. Private boards have to operate, be nimble. They don't have to share all their results. But still, boards play an important role in the success of scaled up companies. So super important, that representation there is key. >> Yes. >> I want to get into that, but first, before we get started, how did you get into tech? How did it all start for you? >> Yeah, long time ago, I was an electrical engineering major. Came out in 1981 when, you know, opportunities for engineering, if you were kind, I went to Kansas State as an undergrad, and basically in those days you went to Texas and did semiconductors. You went to Atlanta and did communication satellites. You went to Boston or you went to Silicon Valley. And for me, that wasn't too hard a choice. I ended up going west and really, I guess what, embarked on a 40 year career in Silicon Valley and absolutely loved it. Largely software, but some time on the hardware side. Started out in networking, but largely software. And then, you know, four years ago transitioned to my next chapter, which is the corporate board director. And again, focused on technology software and cybersecurity boards. >> For the folks watching, we'll cut through another segment we can probably do about your operating career, but you rose through the ranks and became a senior operating executive at the biggest companies in the world. Hewlett Packard Enterprise, Hewlett Packard Enterprise and others. Very great career, okay. And so now you're kind of like, put that on pause, and you're moving on to the next chapter, which is being a board director. What inspired you to be a board director for multiple public companies and multiple private companies? Well, how many companies are you on? But what's the inspiration? What's the inspiration? First tell me how many board ships you're on, board seats you're on, and then what inspired you to become a board director? >> Yeah, so I'm on three public, and you are limited in terms of the number of publics that you can do to four. So I'm on three public, and I'm on four private from a tech perspective. And those range from, you know, a $4 billion in revenue public company down to a 35 person private company. So I've got the whole range. >> So you're like freelancing, I mean, what is it like? It's a full-time job, obviously. It's a lot of work involved. >> Yeah, yeah, it's. >> John: Why are you doing it? >> Well, you know, so I retired from being an operating executive after 37 years. And, but I loved, I mean, it's tough, right? It's tough these days, particularly with all the pressures out there in the market, not to mention the pandemic, et cetera. But I loved it. I loved working. I loved having a career, and I was ready to back off on, I would say the stresses of quarterly results and the stresses of international travel. You have so much of it. But I wasn't ready to back off from being involved and engaged and continuing to learn new things. I think this is why you come to tech, and for me, why I went to the valley to begin with was really that energy and that excitement, and it's like it's constantly reinventing itself. And I felt like that wasn't over for me. And I thought because I hadn't done boards before I retired from operating roles, I thought, you know, that would fill the bill. And it's honestly, it has exceeded expectations. >> In a good way. You feel good about where you're at and. >> Yeah. >> What you went in, what was the expectation going in and what surprised you? And were there people along the way that kind of gave you some pointers or don't do this, stay away from this. Take us through your experiences. >> Yeah, honestly, there is an amazing network of technology board directors, you know, in the US and specifically in the Valley. And we are all incredibly supportive. We have groups where we get together as board directors, and we talk about topics, and we share best practices and stories, and so I underestimated that, right? I thought I was going to, I thought I was going to enter this chapter where I would be largely giving back after 37 years. You've learned a little bit, right? What I underestimated was just the power of continuing to learn and being surrounded by so many amazing people. When, you know, when you do, you know, multiple boards, your learnings are just multiplied, right? Because you see not just one model, but you see many models. You see not just one problem, but many problems. Not just one opportunity, but many opportunities. And I underestimated how great that would be for me from a learning perspective and then your ability to share from one board to the other board because all of my boards are companies who are also quite close to each other, the executives collaborate. So that has turned out to be really exciting for me. >> So you had the stressful job. You rose to the top of the ranks, quarterly shot clock earnings, and it's hard charging. It's like, it's like, you know, being an athlete, as we say tech athlete. You're a tech athlete. Now you're taking that to the next level, which is now you're juggling multiple operational kind of things, but not with super pressure. But there's still a lot of responsibility. I know there's one board, you got compensation committee, I mean there's work involved. It's not like you're clipping coupons and having pizza. >> Yeah, no, it's real work. Believe me, it's real work. But I don't know how long it took me to not, to stop waking up and looking at my phone and thinking somebody was going to be dropping their forecast, right? Just that pressure of the number, and as a board member, obviously you are there to support and help guide the company and you feel, you know, you feel the pressure and the responsibility of what that role entails, but it's not the same as the frontline pressure every quarter. It's different. And so I did the first type. I loved it, you know. I'm loving this second type. >> You know, the retirement, it's always a cliche these days, but it's not really like what people think it is. It's not like getting a boat, going fishing or whatever. It's doing whatever you want to do, that's what retirement is. And you've chose to stay active. Your brain's being tested, and you're working it, having fun without all the stress. But it's enough, it's like going the gym. You're not hardcore workout, but you're working out with the brain. >> Yeah, no, for sure. It's just a different, it's just a different model. But the, you know, the level of conversations, the level of decisions, all of that is quite high. Which again, I like, yeah. >> Again, you really can't talk about some of the fun questions I want to ask, like what's the valuations like? How's the market, your headwinds? Is there tailwinds? >> Yes, yes, yes. It's an amazing, it's an amazing market right now with, as you know, counter indicators everywhere, right? Something's up, something's down, you know. Consumer spending's up, therefore interest rates go up and, you know, employment's down. And so or unemployment's down. And so it's hard. Actually, I really empathize with, you know, the, and have a great deal of respect for the CEOs and leadership teams of my board companies because, you know, I kind of retired from operating role, and then everybody else had to deal with running a company during a pandemic and then running a company through the great resignation, and then running a company through a downturn. You know, those are all tough things, and I have a ton of respect for any operating executive who's navigating through this and leading a company right now. >> I'd love to get your take on the board conversations at the end if we have more time, what the mood is, but I want to ask you about one more thing real quick before we go to the next topic is you're a retired operating executive. You have multiple boards, so you've got your hands full. I noticed there's a lot of amazing leaders, other female tech athletes joining boards, but they also have full-time jobs. >> Yeah. >> And so what's your advice? Cause I know there's a lot of networking, a lot of sharing going on. There's kind of a balance between how much you can contribute on the board versus doing the day job, but there's a real need for more women on boards, so yet there's a lot going on boards. What's the current state of the union if you will, state of the market relative to people in their careers and the stresses? >> Yeah. >> Cause you left one and jumped in all in there. >> Yeah. >> Some can't do that. They can't be on five boards, but they're on a few. What's the? >> Well, and you know, and if you're an operating executive, you wouldn't be on five boards, right? You would be on one or two. And so I spend a lot of time now bringing along the next wave of women and helping them both in their career but also to get a seat at the table on a board. And I'm very vocal about telling people not to do it the way I do it. There's no reason for it to be sequential. You can, you know, I thought I was so busy and was traveling all the time, and yes, all of that was true, but, and maybe I should say, you know, you can still fit in a board. And so, and what I see now is that your learnings are so exponential with outside perspective that I believe I would've been an even better operating executive had I done it earlier. I know I would've been an even better operating executive had I done it earlier. And so my advice is don't do it the way I did it. You know, it's worked out fine for me, but hindsight's 2020, I would. >> If you can go back and do a mulligan or a redo, what would you do? >> Yeah, I would get on a board earlier, full stop, yeah. >> Board, singular, plural? >> Well, I really, I don't think as an operating executive you can do, you could do one, maybe two. I wouldn't go beyond that, and I think that's fine. >> Yeah, totally makes sense. Okay, I got to ask you about your career. I know technical, you came in at that time in the market, I remember when I broke into the business, very male dominated, and then now it's much better. When you went through the ranks as a technical person, I know you had some blockers and definitely some, probably some people like, well, you know. We've seen that. How did you handle that? What were some of the key pivot points in your journey? And we've had a lot of women tell their stories here on theCUBE, candidly, like, hey, I was going to tell that professor, I'm going to sit in the front row. I'm going to, I'm getting two degrees, you know, robotics and aerospace. So, but they were challenged, even with the aspiration to do tech. I'm not saying that was something that you had, but like have you had experience like that, that you overcome? What were those key points and how did you handle them and how does that help people today? >> Yeah, you know, I have to say, you know, and not discounting that obviously this has been a journey for women, and there are a lot of things to overcome both in the workforce and also just balancing life honestly. And they're all real. There's also a story of incredible support, and you know, I'm the type of person where if somebody blocked me or didn't like me, I tended to just, you know, think it was me and like work harder and get around them, and I'm sure that some of that was potentially gender related. I didn't interpret it that way at the time. And I was lucky to have amazing mentors, many, many, many of whom were men, you know, because they were in the positions of power, and they made a huge difference on my career, huge. And I also had amazing female mentors, Meg Whitman, Ann Livermore at HPE, who you know well. So I had both, but you know, when I look back on the people who made a difference, there are as many men on the list as there are women. >> Yeah, and that's a learning there. Create those coalitions, not just one or the other. >> Yeah, yeah, yeah, absolutely. >> Well, I got to ask you about the, well, you brought up the pandemic. This has come up on some interviews this year, a little bit last year on the International Women's Day, but this year it's resonating, and I would never ask in an interview. I saw an interview once where a host asked a woman, how do you balance it all? And I was just like, no one asked men that. And so it's like, but with remote work, it's come up now the word empathy around people knowing each other's personal situation. In other words, when remote work happened, everybody went home. So we all got a glimpse of the backdrop. You got, you can see what their personal life was on Facebook. We were just commenting before we came on camera about that. So remote work really kind of opened up this personal side of everybody, men and women. >> Yeah. >> So I think this brings this new empathy kind of vibe or authentic self people call it. Is remote work an opportunity or a threat for advancement of women in tech? >> It's a much debated topic. I look at it as an opportunity for many of the reasons that you just said. First of all, let me say that when I was an operating executive and would try to create an environment on my team that was family supportive, I would do that equally for young or, you know, early to mid-career women as I did for early to mid-career men. And the reason is I needed those men, you know, chances are they had a working spouse at home, right? I needed them to be able to share the load. It's just as important to the women that companies give, you know, the partner, male or female, the partner support and the ability to share the love, right? So to me it's not just a woman thing. It's women and men, and I always tried to create the environment where it was okay to go to your soccer game. I knew you would be online later in the evening when the kids were in bed, and that was fine. And I think the pandemic has democratized that and made that, you know, made that kind of an everyday occurrence. >> Yeah the baby walks in. They're in the zoom call. The dog comes in. The leaf blower going on the outside the window. I've seen it all on theCUBE. >> Yeah, and people don't try to pretend anymore that like, you know, the house is clean, the dog's behaved, you know, I mean it's just, it's just real, and it's authentic, and I think that's healthy. >> Yeah. >> I do, you know, I also love, I also love the office, and you know, I've got a 31 year old and a soon to be 27 year old daughter, two daughters. And you know, they love going into the office, and I think about when I was their age, how just charged up I would get from being in the office. I also see how great it is for them to have a couple of days a week at home because you can get a few things done in between Zoom calls that you don't have to end up piling onto the weekend, and, you know, so I think it's a really healthy, I think it's a really healthy mix now. Most tech companies are not mandating five days in. Most tech companies are at two to three days in. I think that's a, I think that's a really good combination. >> It's interesting how people are changing their culture to get together more as groups and even events. I mean, while I got you, I might as well ask you, what's the board conversations around, you know, the old conferences? You know, before the pandemic, every company had like a user conference. Right, now it's like, well, do we really need to have that? Maybe we do smaller, and we do digital. Have you seen how companies are handling the in-person? Because there's where the relationships are really formed face-to-face, but not everyone's going to be going. But now certain it's clearly back to face-to-face. We're seeing that with theCUBE as you know. >> Yeah, yeah. >> But the numbers aren't coming back, and the numbers aren't that high, but the stakeholders. >> Yeah. >> And the numbers are actually higher if you count digital. >> Yeah, absolutely. But you know, also on digital there's fatigue from 100% digital, right? It's a hybrid. People don't want to be 100% digital anymore, but they also don't want to go back to the days when everybody got on a plane for every meeting, every call, every sales call. You know, I'm seeing a mix on user conferences. I would say two-thirds of my companies are back, but not at the expense level that they were on user conferences. We spend a lot of time getting updates on, cause nobody has put, interestingly enough, nobody has put T&E, travel and expense back to pre-pandemic levels. Nobody, so everybody's pulled back on number of trips. You know, marketing events are being very scrutinized, but I think very effective. We're doing a lot of, and, you know, these were part of the old model as well, like some things, some things just recycle, but you know, there's a lot of CIO and customer round tables in regional cities. You know, those are quite effective right now because people want some face-to-face, but they don't necessarily want to get on a plane and go to Las Vegas in order to do it. I mean, some of them are, you know, there are a lot of things back in Las Vegas. >> And think about the meetings that when you were an operating executive. You got to go to the sales kickoff, you got to go to this, go to that. There were mandatory face-to-faces that you had to go to, but there was a lot of travel that you probably could have done on Zoom. >> Oh, a lot, I mean. >> And then the productivity to the family impact too. Again, think about again, we're talking about the family and people's personal lives, right? So, you know, got to meet a customer. All right. Salesperson wants you to get in front of a customer, got to fly to New York, take a red eye, come on back. Like, I mean, that's gone. >> Yeah, and oh, by the way, the customer doesn't necessarily want to be in the office that day, so, you know, they may or may not be happy about that. So again, it's and not or, right? It's a mix. And I think it's great to see people back to some face-to-face. It's great to see marketing and events back to some face-to-face. It's also great to see that it hasn't gone back to the level it was. I think that's a really healthy dynamic. >> Well, I'll tell you that from our experience while we're on the topic, we'll move back to the International Women's Day is that the productivity of digital, this program we're doing is going to be streamed. We couldn't do this face-to-face because we had to have everyone fly to an event. We're going to do hundreds of stories that we couldn't have done. We're doing it remote. Because it's better to get the content than not have it. I mean it's offline, so, but it's not about getting people to the event and watch the screen for seven hours. It's pick your interview, and then engage. >> Yeah. >> So it's self-service. So we're seeing a lot, the new user experience kind of direct to consumer, and so I think there will be an, I think there's going to be a digital first class citizen with events, so that that matches up with the kind of experience, but the offline version. Face-to-face optimized for relationships, and that's where the recruiting gets done. That's where, you know, people can build these relationships with each other. >> Yeah, and it can be asynchronous. I think that's a real value proposition. It's a great point. >> Okay, I want to get, I want to get into the technology side of the education and re-skilling and those things. I remember in the 80s, computer science was software engineering. You learned like nine languages. You took some double E courses, one or two, and all the other kind of gut classes in school. Engineering, you had the four class disciplines and some offshoots of specialization. Now it's incredible the diversity of tracks in all engineering programs and computer science and outside of those departments. >> Yeah. >> Can you speak to the importance of STEM and the diversity in the technology industry and how this brings opportunity to lower the bar to get in and how people can stay in and grow and keep leveling up? >> Yeah, well look, we're constantly working on how to, how to help the incoming funnel. But then, you know, at a university level, I'm on the foundation board of Kansas State where I got my engineering degree. I was also Chairman of the National Action Council for Minorities in Engineering, which was all about diversity in STEM and how do you keep that pipeline going because honestly the US needs more tech resources than we have. And if you don't tap into the diversity of our entire workforce, we won't be able to fill that need. And so we focused a lot on both the funnel, right, that starts at the middle school level, particularly for girls, getting them in, you know, the situation of hands-on comfort level with coding, with robot building, you know, whatever gives them that confidence. And then keeping that going all the way into, you know, university program, and making sure that they don't attrit out, right? And so there's a number of initiatives, whether it's mentoring and support groups and financial aid to make sure that underrepresented minorities, women and other minorities, you know, get through the funnel and stay, you know, stay in. >> Got it. Now let me ask you, you said, I have two daughters. You have a family of girls too. Is there a vibe difference between the new generation and what's the trends that you're seeing in this next early wave? I mean, not maybe, I don't know how this is in middle school, but like as people start getting into their adult lives, college and beyond what's the current point of view, posture, makeup of the talent coming in? >> Yeah, yeah. >> Certain orientations, do you see any patterns? What's your observation? >> Yeah, it's interesting. So if I look at electrical engineering, my major, it's, and if I look at Kansas State, which spends a lot of time on this, and I think does a great job, but the diversity of that as a major has not changed dramatically since I was there in the early 80s. Where it has changed very significantly is computer science. There are many, many university and college programs around the country where, you know, it's 50/50 in computer science from a gender mix perspective, which is huge progress. Huge progress. And so, and to me that's, you know, I think CS is a fantastic degree for tech, regardless of what function you actually end up doing in these companies. I mean, I was an electrical engineer. I never did core electrical engineering work. I went right into sales and marketing and general management roles. So I think, I think a bunch of, you know, diverse CS graduates is a really, really good sign. And you know, we need to continue to push on that, but progress has been made. I think the, you know, it kind of goes back to the thing we were just talking about, which is the attrition of those, let's just talk about women, right? The attrition of those women once they got past early career and into mid-career then was a concern, right? And that goes back to, you know, just the inability to, you know, get it all done. And that I am hopeful is going to be better served now. >> Well, Sue, it's great to have you on. I know you're super busy. I appreciate you taking the time and contributing to our program on corporate board membership and some of your story and observations and opinions and analysis. Always great to have you and call you a contributor for theCUBE. You can jump on on one more board, be one of our board contributors for our analysts. (Sue laughing) >> I'm at capacity. (both laughing) >> Final, final word. What's the big seat at the table issue that's going well and areas that need to be improved? >> So I'll speak for my boards because they have made great progress in efficiency. You know, obviously with interest rates going up and the mix between growth and profitability changing in terms of what investors are looking for. Many, many companies have had to do a hard pivot from grow at all costs to healthy balance of growth and profit. And I'm very pleased with how my companies have made that pivot. And I think that is going to make much better companies as a result. I think diversity is something that has not been solved at the corporate level, and we need to keep working it. >> Awesome. Thank you for coming on theCUBE. CUBE alumni now contributor, on multiple boards, full-time job. Love the new challenge and chapter you're on, Sue. We'll be following, and we'll check in for more updates. And thank you for being a contributor on this program this year and this episode. We're going to be doing more of these quarterly, so we're going to move beyond once a year. >> That's great. (cross talking) It's always good to see you, John. >> Thank you. >> Thanks very much. >> Okay. >> Sue: Talk to you later. >> This is theCUBE coverage of IWD, International Women's Day 2023. I'm John Furrier, your host. Thanks for watching. (upbeat music)

(intro music) >> "theCUBE's" live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music) >> We're not going to- >> Hey everybody, welcome back to the Fira in Barcelona. My name is Dave Vellante, I'm here with Dave Nicholson, day four of MWC23. I mean, it's Dave, it's, it's still really busy. And you walking the floors, you got to stop and start. >> It's surprising. >> People are cheering. They must be winding down, giving out the awards. Really excited. Pier, look at you and Elias here. He's the vice president of Engineering Technology for Edge Computing Offers Strategy and Execution at Dell Technologies, and he's joined by Dan Cummins, who's a fellow and vice president of, in the Edge Business Unit at Dell Technologies. Guys, welcome. >> Thank you. >> Thank you. >> I love when I see the term fellow. You know, you don't, they don't just give those away. What do you got to do to be a fellow at Dell? >> Well, you know, fellows are senior technical leaders within Dell. And they're usually tasked to help Dell solve you know, a very large business challenge to get to a fellow. There's only, I think, 17 of them inside of Dell. So it is a small crowd. You know, previously, really what got me to fellow, is my continued contribution to transform Dell's mid-range business, you know, VNX two, and then Unity, and then Power Store, you know, and then before, and then after that, you know, they asked me to come and, and help, you know, drive the technology vision for how Dell wins at the Edge. >> Nice. Congratulations. Now, Pierluca, I'm looking at this kind of cool chart here which is Edge, Edge platform by Dell Technologies, kind of this cube, like cubes course, you know. >> AK project from here. >> Yeah. So, so tell us about the Edge platform. What, what's your point of view on all that at Dell? >> Yeah, absolutely. So basically in a, when we create the Edge, and before even then was bringing aboard, to create this vision of the platform, and now building the platform when we announced project from here, was to create solution for the Edge. Dell has been at the edge for 30 years. We sold a lot of compute. But the reality was people want outcome. And so, and the Edge is a new market, very exciting, but very siloed. And so people at the Edge have different personas. So quickly realize that we need to bring in Dell, people with expertise, quickly realize as well that doing all these solution was not enough. There was a lot of problem to solve because the Edge is outside of the data center. So you are outside of the wall of the data center. And what is going to happen is obviously you are in the land of no one. And so you have million of device, thousand of million of device. All of us at home, we have all connected thing. And so we understand that the, the capability of Dell was to bring in technology to secure, manage, deploy, with zero touch, zero trust, the Edge. And all the edge the we're speaking about right now, we are focused on everything that is outside of a normal data center. So, how we married the computer that we have for many years, the new gateways that we create, so having the best portfolio, number one, having the best solution, but now, transforming the way that people deploy the Edge, and secure the Edge through a software platform that we create. >> You mentioned Project Frontier. I like that Dell started to do these sort of project, Project Alpine was sort of the multi-cloud storage. I call it "The Super Cloud." The Project Frontier. It's almost like you develop, it's like mission based. Like, "Okay, that's our North Star." People hear Project Frontier, they know, you know, internally what you're talking about. Maybe use it for external communications too, but what have you learned since launching Project Frontier? What's different about the Edge? I mean you're talking about harsh environments, you're talking about new models of connectivity. So, what have you learned from Project Frontier? What, I'd love to hear the fellow perspective as well, and what you guys are are learning so far. >> Yeah, I mean start and then I left to them, but we learn a lot. The first thing we learn that we are on the right path. So that's good, because every conversation we have, there is nobody say to us, you know, "You are crazy. "This is not needed." Any conversation we have this week, start with the telco thing. But after five minutes it goes to, okay, how I can solve the Edge, how I can bring the compute near where the data are created, and how I can do that secure at scale, and with the right price. And then can speak about how we're doing that. >> Yeah, yeah. But before that, we have to really back up and understand what Dell is doing with Project Frontier, which is an Edge operations platform, to simplify your Edge use cases. Now, Pierluca and his team have a number of verticalized applications. You want to be able to securely deploy those, you know, at the Edge. But you need a software platform that's going to simplify both the life cycle management, and the security at the Edge, with the ability to be able to construct and deploy distributed applications. Customers are looking to derive value near the point of generation of data. We see a massive explosion of data. But in particular, what's different about the Edge, is the different computing locations, and the constraints that are on those locations. You know, for example, you know, in a far Edge environment, the people that service that equipment are not trained in the IT, or train, trained in it. And they're also trained in the safety and security protocols of that environment. So you necessarily can't apply the same IT techniques when you're managing infrastructure and deploying applications, or servicing in those locations. So Frontier was designed to solve for those constraints. You know, often we see competitors that are doing similar things, that are starting from an IT mindset, and trying to shift down to cover Edge use cases. What we've done with Frontier, is actually first understood the constraints that they have at the Edge. Both the operational constraints and technology constraints, the service constraints, and then came up with a, an architecture and technology platform that allows them to start from the Edge, and bleed into the- >> So I'm laughing because you guys made the same mistake. And you, I think you learned from that mistake, right? You used to take X86 boxes and throw 'em over the fence. Now, you're building purpose-built systems, right? Project Frontier I think is an example of the learnings. You know, you guys an IT company, right? Come on. But you're learning fast, and that's what I'm impressed about. >> Well Glenn, of course we're here at MWC, so it's all telecom, telecom, telecom, but really, that's a subset of Edge. >> Yes. >> Fair to say? >> Yes. >> Can you give us an example of something that is, that is, orthogonal to, to telecom, you know, maybe off to the side, that maybe overlaps a little bit, but give us an, give us an example of Edge, that isn't specifically telecom focused. >> Well, you got the, the Edge verticals. and Pierluca could probably speak very well to this. You know, you got manufacturing, you got retail, you got automotive, you got oil and gas. Every single one of them are going to make different choices in the software that they're going to use, the hyperscaler investments that they're going to use, and then write some sort of automation, you know, to deploy that, right? And the Edge is highly fragmented across all of these. So we certainly could deploy a private wireless 5G solution, orchestrate that deployment through Frontier. We can also orchestrate other use cases like connected worker, or overall equipment effectiveness in manufacturing. But Pierluca you have a, you have a number. >> Well, but from your, so, but just to be clear, from your perspective, the whole idea of, for example, private 5g, it's a feature- >> Yes. >> That might be included. It happened, it's a network topology, a network function that might be a feature of an Edge environment. >> Yes. But it's not the center of the discussion. >> So, it enables the outcome. >> Yeah. >> Okay. >> So this, this week is a clear example where we confirm and establish this. The use case, as I said, right? They, you say correctly, we learned very fast, right? We brought people in that they came from industry that was not IT industry. We brought people in with the things, and we, we are Dell. So we have the luxury to be able to interview hundreds of customers, that just now they try to connect the OT with the IT together. And so what we learn, is really, at the Edge is different personas. They person that decide what to do at the Edge, is not the normal IT administrator, is not the normal telco. >> Who is it? Is it an engineer, or is it... >> It's, for example, the store manager. >> Yeah. >> It's, for example, the, the person that is responsible for the manufacturing process. Those people are not technology people by any means. But they have a business goal in mind. Their goal is, "I want to raise my productivity by 30%," hence, I need to have a preventive maintenance solution. How we prescribe this preventive maintenance solution? He doesn't prescribe the preventive maintenance solution. He goes out, he has to, a consult or himself, to deploy that solution, and he choose different fee. Now, the example that I was doing from the houses, all of us, we have connected device. The fact that in my house, I have a solar system that produce energy, the only things I care that I can read, how much energy I produce on my phone, and how much energy I send to get paid back. That's the only thing. The fact that inside there is a compute that is called Dell or other things is not important to me. Same persona. Now, if I can solve the security challenge that the SI, or the user need to implement this technology because it goes everywhere. And I can manage this in extensively, and I can put the supply chain of Dell on top of that. And I can go every part in the world, no matter if I have in Papua New Guinea, or I have an oil ring in Texas, that's the winning strategy. That's why people, they are very interested to the, including Telco, the B2B business in telco is looking very, very hard to how they recoup the investment in 5g. One of the way, is to reach out with solution. And if I can control and deploy things, more than just SD one or other things, or private mobility, that's the key. >> So, so you have, so you said manufacturing, retail, automotive, oil and gas, you have solutions for each of those, or you're building those, or... >> Right now we have solution for manufacturing, with for example, PTC. That is the biggest company. It's actually based in Boston. >> Yeah. Yeah, it is. There's a company that the market's just coming right to them. >> We have a, very interesting. Another solution with Litmus, that is a startup that, that also does manufacturing aggregation. We have retail with Deep North. So we can do detecting in the store, how many people they pass, how many people they doing, all of that. And all theses solution that will be, when we will have Frontier in the market, will be also in Frontier. We are also expanding to energy, and we going vertical by vertical. But what is they really learn, right? You said, you know you are an IT company. What, to me, the Edge is a pre virtualization area. It's like when we had, you know, I'm, I've been in the company for 24 years coming from EMC. The reality was before there was virtualization, everybody was starting his silo. Nobody thought about, "Okay, I can run this thing together "with security and everything, "but I need to do it." Because otherwise in a manufacturing, or in a shop, I can end up with thousand of devices, just because someone tell to me, I'm a, I'm a store manager, I don't know better. I take this video surveillance application, I take these things, I take a, you know, smart building solution, suddenly I have five, six, seven different infrastructure to run this thing because someone say so. So we are here to democratize the Edge, to secure the Edge, and to expand. That's the idea. >> So, the Frontier platform is really the horizontal platform. And you'll build specific solutions for verticals. On top of that, you'll, then I, then the beauty is ISV's come in. >> Yes. >> 'Cause it's open, and the developers. >> We have a self certification program already for our solution, as well, for the current solution, but also for Frontier. >> What does that involve? Self-certification. You go through you, you go through some- >> It's basically a, a ISV can come. We have a access to a lab, they can test the thing. If they pass the first screen, then they can become part of our ecosystem very easily. >> Ah. >> So they don't need to spend days or months with us to try to architect the thing. >> So they get the premature of being certified. >> They get the Dell brand associated with it. Maybe there's some go-to-market benefits- >> Yes. >> As well. Cool. What else do we need to know? >> So, one thing I, well one thing I just want to stress, you know, when we say horizontal platform, really, the Edge is really a, a distributed edge computing problem, right? And you need to almost create a mesh of different computing locations. So for example, even though Dell has Edge optimized infrastructure, that we're going to deploy and lifecycle manage, customers may also have compute solutions, existing compute solutions in their data center, or at a co-location facility that are compute destinations. Project Frontier will connect to those private cloud stacks. They'll also collect to, connect to multiple public cloud stacks. And then, what they can do, is the solutions that we talked about, they construct that using an open based, you know, protocol, template, that describes that distributed application that produces that outcome. And then through orchestration, we can then orchestrate across all of these locations to produce that outcome. That's what the platform's doing. >> So it's a compute mesh, is what you just described? >> Yeah, it's, it's a, it's a software orchestration mesh. >> Okay. >> Right. And allows customers to take advantage of their existing investments. Also allows them to, to construct solutions based on the ISV of their choice. We're offering solutions like Pierluca had talked about, you know, in manufacturing with Litmus and PTC, but they could put another use case that's together based on another ISV. >> Is there a data mesh analog here? >> The data mesh analog would run on top of that. We don't offer that as part of Frontier today, but we do have teams working inside of Dell that are working on this technology. But again, if there's other data mesh technology or packages, that they want to deploy as a solution, if you will, on top of Frontier, Frontier's extensible in that way as well. >> The open nature of Frontier is there's a, doesn't, doesn't care. It's just a note on the mesh. >> Yeah. >> Right. Now, of course you'd rather, you'd ideally want it to be Dell technology, and you'll make the business case as to why it should be. >> They get additional benefits if it's Dell. Pierluca talked a lot about, you know, deploying infrastructure outside the walls of an IT data center. You know, this stuff can be tampered with. Somebody can move it to another room, somebody can open up. In the supply chain with, you know, resellers that are adding additional people, can open these devices up. We're actually deploying using an Edge technology called Secure Device Onboarding. And it solves a number of things for us. We, as a manufacturer can initialize the roots of trust in the Dell hardware, such that we can validate, you know, tamper detection throughout the supply chain, and securely transfer ownership. And that's different. That is not an IT technique. That's an edge technique. And that's just one example. >> That's interesting. I've talked to other people in IT about how they're using that technique. So it's, it's trickling over to that side of the business. >> I'm almost curious about the friction that you, that you encounter because the, you know, you paint a picture of a, of a brave new world, a brave new future. Ideally, in a healthy organization, they have, there's a CTO, or at least maybe a CIO, with a CTO mindset. They're seeking to leverage technology in the service of whatever the mission of the organization is. But they've got responsibilities to keep the lights on, as well as innovate. In that mix, what are you seeing as the inhibitors? What's, what's the push back against Frontier that you're seeing in most cases? Is it, what, what is it? >> Inside of Dell? >> No, not, I'm saying out, I'm saying with- >> Market friction. >> Market, market, market friction. What is the push back? >> I think, you know, as I explained, do yourself is one of the things that probably is the most inhibitor, because some people, they think that they are better already. They invest a lot in this, and they have the content. But those are again, silo solutions. So, if you go into some of the huge things that they already established, thousand of store and stuff like that, there is an opportunity there, because also they want to have a refresh cycle. So when we speak about softer, softer, softer, when you are at the Edge, the software needs to run on something that is there. So the combination that we offer about controlling the security of the hardware, plus the operating system, and provide an end-to-end platform, allow them to solve a lot of problems that today they doing by themselves. Now, I met a lot of customers, some of them, one actually here in Spain, I will not make the name, but it's a large automotive. They have the same challenge. They try to build, but the problem is this is just for them. And they want to use something that is a backup and provide with the Dell service, Dell capability of supply chain in all the world, and the diversity of the portfolio we have. These guys right now, they need to go out and find different types of compute, or try to adjust thing, or they need to have 20 people there to just prepare the device. We will take out all of this. So I think the, the majority of the pushback is about people that they already established infrastructure, and they want to use that. But really, there is an opportunity here. Because the, as I said, the IT/OT came together now, it's a reality. Three years ago when we had our initiative, they've pointed out, sarcastically. We, we- >> Just trying to be honest. (laughing) >> I can't let you get away with that. >> And we, we failed because it was too early. And we were too focused on, on the fact to going. Push ourself to the boundary of the IOT. This platform is open. You want to run EdgeX, you run EdgeX, you want OpenVINO, you want Microsoft IOT, you run Microsoft IOT. We not prescribe the top. We are locking down the bottom. >> What you described is the inertia of, of sunk dollars, or sunk euro into an infrastructure, and now they're hanging onto that. >> Yeah. >> But, I mean, you know, I, when we say horizontal, we think scale, we think low cost, at volume. That will, that will win every time. >> There is a simplicity at scale, right? There is a, all the thing. >> And the, and the economics just overwhelm that siloed solution. >> And >> That's inevitable. >> You know, if you want to apply security across the entire thing, if you don't have a best practice, and a click that you can do that, or bring down an application that you need, you need to touch each one of these silos. So, they don't know yet, but we going to be there helping them. So there is no pushback. Actually, this particular example I did, this guy said you know, there are a lot of people that come here. Nobody really described the things we went through. So we are on the right track. >> Guys, great conversation. We really appreciate you coming on "theCUBE." >> Thank you. >> Pleasure to have you both. >> Okay. >> Thank you. >> All right. And thank you for watching Dave Vellante for Dave Nicholson. We're live at the Fira. We're winding up day four. Keep it right there. Go to siliconangle.com. John Furrier's got all the news on "theCUBE.net." We'll be right back right after this break. "theCUBE," at MWC 23. (outro music)

>> Narrator: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Hey, welcome back to the Fira in Barcelona. My name is Dave Vellante. I'm here with David Nicholson, day four of MWC '23. Show's winding down a little bit, but it's still pretty packed here. Lot of innovation, planes, trains, automobiles, and we're talking 5G all week, private networks, connected breweries. It's super exciting. Really happy to have Warren Jackson here as the Edge Gateway Product Technologist at Dell Technologies, and Scott Waller, the CTO of the 5G Open Innovation Lab. Folks, welcome to theCUBE. >> Good to be here. >> Really interesting stories that we're going to talk about. Let's start, Scott, with you, what is the Open Innovation Lab? >> So it was hatched three years ago. Ideated about a bunch of guys from Microsoft who ran startup ventures program, started the developers program over at Microsoft, if you're familiar with MSDN. And they came three years ago and said, how does CSPs working with someone like T-Mobile who's in our backyard, I'm from Seattle. How do they monetize the edge? You need a developer ecosystem of applications and use cases. That's always been the thing. The carriers are building the networks, but where's the ecosystem of startups? So we built a startup ecosystem that is sponsored by partners, Dell being one sponsor, Intel, Microsoft, VMware, Aspirant, you name it. The enterprise folks who are also in the connectivity business. And with that, we're not like a Y Combinator or a Techstars where it's investment first and it's all about funding. It's all about getting introductions from a startup who might have a VR or AI type of application or observability for 5G slicing, and bring that in front of the Microsoft's of the world, or the Intel's and the Dell's of the world that they might not have the capabilities to do it because they're still a small little startup with an MVP. So we really incubate. We're the connectors and build a network. We've had 101 startups over the last three years. They've raised over a billion dollars. And it's really valuable to our partners like T-Mobile and Dell, et cetera, where we're bringing in folks like Expedo and GenXComm and Firecell. Start up private companies that are around here they were cohorts from our program in the past. >> That's awesome because I've often, I mean, I've seen Dell get into this business and I'm like, wow, they've done a really good job of finding these guys. I wonder what the pipeline is. >> We're trying to create the pipeline for the entire industry, whether it's 5G on the edge for the CSPs, or it's for private enterprise networks. >> Warren, what's this cool little thing you got here? >> Yeah, so this is very unique in the Dell portfolio. So when people think of Dell, they think of servers laptops, et cetera. But what this does is it's designed to be deployed at the edge in harsh environments and it allows customers to do analytics, data collection at the edge. And what's unique about it is it's got an extended temperature range. There's no fan in this and there's lots of ports on it for data ingestion. So this is a smaller box Edge Gateway 3200. This is the product that we're using in the brewery. And then we have a bigger brother of this, the Edge Gateway 5200. So the value of it, you can scale depending on what your edge compute requirements are at the edge. >> So tell us about the brewery story. And you covered it, I know you were in the Dell booth, but it's basically an analog brewery. They're taking measurements and temperatures and then writing it down and then entering it in and somebody from your company saw it and said, "We can help you with this problem." Explain the story. >> Yeah, so Scott and I did a walkthrough of the brewery back in November timeframe. >> It's in Framingham, Mass. >> Framingham, Mass, correct. And basically, we talked to him, and we said, what keeps you guys up at night? What's a problem that we can solve? Very simple, a kind of a lower budget, didn't have a lot money to spend on it, but what problem can we solve that will realize great benefit for you? So we looked at their fermentation process, which was completely analog. Somebody was walking around with a clipboard looking at analog gauges. And what we did is we digitized that process. So what this did for them rather than being completely reactive, and by the time they realized there was something going wrong with the fermentation process, it's too late. A batch of scrap. This allowed them to be proactive. So anytime, anywhere on the tablet or a phone, they can see if that fermentation process is going out of range and do something about it before the batch gets scrapped. >> Okay. Amazing. And Scott, you got a picture of this workflow here? >> Yeah, actually this is the final product. >> Explain that. >> As Warren mentioned, the data is actually residing in the industrial side of the network So we wanted to keep the IT/OT separation, which is critical on the factory floor. And so all the data is brought in from the sensors via digital connection once it's converted and into the edge gateway. Then there's a snapshot of it using Telit deviceWISE, their dashboarding application, that is decoding all the digital readings, putting them in a nice dashboard. And then when we gave them, we realized another problem was they're using cheap little Chromebooks that they spill beer on once a week and throw them out. That's why they bought the cheap ones 'cause they go through them so fast. So we got a Dell Latitude Rugged notebook. This is a brand new tablet, but they have the dashboarding software. So no matter if they're out there on the floor, but because the data resides there on the factory they have access to be able to change the parameters. This one's in the maturation cycle. This one's in the crashing cycle where they're bringing the temperature back down, stopping the fermentation process, getting it ready to go to the canning side of the house. >> And they're doing all that from this dashboard. >> They're doing all from the dashboard. They also have a giant screen that we put up there that in the floor instead of walking a hundred yards back behind a whole bunch of machinery equipment from a safety perspective, now they just look up on the screen and go, "Oh, that's red. That's out of range." They're actually doing a bunch of cleaning and a bunch of other things right now, too. So this is real time from Boston. >> Dave: Oh okay. >> Scott: This is actually real time from Boston. >> I'm no hop master, but I'm looking at these things flashing at me and I'm thinking something's wrong with my beer. >> We literally just lit this up last week. So we're still tweaking a few things, but they're also learning around. This is a new capability they never had. Oh, we have the ability to alert and monitor at different processes with different batches, different brews, different yeast types. Then now they're also training and learning. And we're going to turn that into eventually a product that other breweries might be able to use. >> So back to the kind of nuts and bolts of the system. The device that you have here has essentially wifi antennas on the back. >> Warren: Correct. >> Pull that up again if you would, please. >> Now I've seen this, just so people are clear, there are also paddle 5G antennas that go on the other side. >> Correct. >> That's sort of the connection from the 5G network that then gets transmogrified, technical term guys, into wifi so the devices that are physically connected to the brew vats, don't know what they're called. >> Fermentation tanks. >> Fermentation tanks, thank you. Those are wifi. That's a wifi signal that's going into this. Is that correct? >> Scott: No. >> No, it's not. >> It's a hard wire. >> Okay, okay. >> But, you're right. This particular gateway. >> It could be wifi if it's hard wire. >> It could be, yes. Could be any technology really. >> This particular gateway is not outfitted with 5G, but something that was very important in this application was to isolate the IT network, which is on wifi and physically connected from the OT network, which is the 5G connection. So we're sending the data directly from the gateway up to the cloud. The two partners that we worked with on this project were ifm, big sensor manufacturer that actually did the wired sensors into an industrial network called IO-Link. So they're physically wired into the gateway and then in the gateway we have a solution from our partner Telit that has deviceWISE software that actually takes the data in, runs the analytics on it, the logic, and then visualizes that data locally on those panels and also up to their cloud, which is what we're looking at. So they can look at it locally, they're in the plant and then up in the cloud on a phone or a tablet, whatever, when they're at home. >> We're talking about a small business here. I don't know how many employees they have, but it's not thousands. And I love that you're talking about an IT network and an OT network. And so they wanted, it is very common when we talk about industrial internet of things use cases, but we're talking about a tiny business here. >> Warren: Correct. >> They wanted to separate those networks because of cost, because of contention. Explain why. >> Yeah, just because, I mean, they're running their ERP system, their payroll, all of their kind of the way they run their business on their IT network and you don't want to have the same traffic out on the factory floor on that network, so it was pretty important. And the other thing is we really, one of the things that we didn't want to do in this project is interrupt their production process at all. So we installed this entire system in two days. They didn't have to shut down, they didn't have to stop. We didn't have to interrupt their process at all. It was like we were invisible there and we spun the thing up and within two days, very simple, easy, but tremendous value for their business. >> Talk about new markets here. I mean, it's like any company that's analog that needs to go digital. It's like 99% of the companies on the planet. What are you guys seeing out there in terms of the types of examples beyond breweries? >> Yeah, I could talk to that. So I spent a lot of time over the last couple years running my own little IoT company and a lot of it being in agriculture. So like in Washington state, 70% of the world's hops is actually grown in Washington state. It's my hometown. But in the Ag producing regions, there's lack of connectivity. So there's interest in private networks because the carriers aren't necessarily deploying it. But because we have the vast amount of hops there's a lot of IPAs, a lot of hoppy IPAs that come out of Seattle. And with that, there's a ton of craft breweries that are about the same size, some are a little larger. Anheuser-Busch and InBev and Heineken they've got great IoT platforms. They've done it. They're mass scale, they have to digitize. But the smaller shops, they don't, when we talk about IT/OT separation, they're not aware of that. They think it's just, I get local broadband and I get wifi and one hotspot inside my facility and it works. So a little bit of it was the education. I have got years in IT/OT security in my background so that education and we come forward with a solution that actually does that for them. And now they're aware of it. So now when they're asking questions of other vendors that are trying to sell them some type of solution, they're inherently aware of what should be done so they're not vulnerable to ransomware attacks, et cetera. So it's known as the Purdue Model. >> Well, what should they do? >> We came in and keep it completely separated and educated them because in the end too we'll build a design guide and a starter kit out of this that other brewers can use. Because I've toured dozens of breweries in Washington, the exact same scenario, analog gauges, analog process, very manual. And in the end, when you ask the brewer, what do they want out of this? It keeps them up at night because if the temperature goes out of range, because the chiller fails, >> They ruined. >> That's $30,000 lost in beer. That's a lot to a small business. However, it's also once they start digitizing the data and to Warren's point, it's read-only. We're not changing any of the process. We augmented on top of their existing systems. We didn't change their process. But now they have the ability to look at the data and see batch to batch consistency. Quality doesn't always mean best, it means consistency from batch to batch. Every beer from exhibit A from yesterday to two months from now of the same style of beer should be the same taste, flavor, boldness, et cetera. This is giving them the insights on it. >> It's like St. Louis Buds, when we were kids. We would buy the St. Louis Buds 'cause they tasted better than the Merrimack Buds. And then Budweiser made them all the same. >> Must be an East coast thing. >> It's an old guy thing, Dave. You weren't born yet. >> I was in high school. Yeah, I was in high school. >> We like the hops. >> We weren't 21. Do me a favor, clarify OT versus IT. It's something we talk about all the time, but not everyone's familiar with that separation. Define OT for me. >> It's really the factory floor. You got IT systems that are ERP systems, billing, you're getting your emails, stuff like that. Where the ransomware usually gets infected in. The OT side is the industrial control network. >> David: What's the 'O' stand for? >> Operation. >> David: Operation? >> Yeah, the operations side. >> 'Cause some people will think objects 'cause we think internet of things. >> The industrial operations, think of it that way. >> But in a sense those are things that are connected. >> And you think of that as they are the safety systems as well. So a machine, if someone doesn't push the stop button, you'd think if there's a lot of traffic on that network, it isn't guaranteed that that stop button actually stops that blade from coming down, someone's going to lose their arm. So it's very tied to safety, reliability, low latency. It is crafted in design that it never touches the internet inherently without having to go through a security gateway which is what we did. >> You mentioned the large companies like InBev, et cetera. You're saying they're already there. Are they not part of your target market? Or are there ways that you can help them? Is this really more of a small to mid-size company? >> For this particular solution, I think so, yeah. Because the cost to entry is low. I mean, you talk about InBev, they have millions of dollars of budgets to spend on OT. So they're completely automated from top to bottom. But these little craft brewers, which they're everywhere in the US. Vermont, Washington state, they're completely manual. A lot of these guys just started in their garage. And they just scaled up and they got a cult kind of following around their beers. One thing that we found here this week, when you talk around edge and 5G and beer, those things get people excited. In our booth we're serving beer, and all these kind of topics, it brings people together. >> And it lets the little guy compete more effectively with the big giants. >> Correct. >> And how do you do more with less as the little guy is kind of the big thing and to Warren's point, we have folks come up and say, "Great, this is for beer, but what about wine? What about the fermentation process of wine?" Same materials in the end. A vessel of some sort, maybe it's stainless steel. The clamps are the same, the sensors are the same. The parameters like temperature are key in any type of fermentation. We had someone talking about olive oil and using that. It's the same sanitary beverage style equipment. We grabbed sensors that were off the shelf and then we integrated them in and used the set of platforms that we could. How do we rapidly enable these guys at the lowest possible cost with stuff that's at the shelf. And there's four different companies in the solution. >> We were having a conversation with T-Mobile a little earlier and she mentioned the idea of this sounding scary. And this is a great example of showing that in fact, at a relatively small scale, this technology makes a lot of sense. So from that perspective, of course you can implement private 5G networks at an industrial scale with tens of millions of dollars of investment. But what about all of the other things below? And that seems to be a perfect example. >> Yeah, correct. And it's one of the things with the gateway and having flexibility the way Dell did a great job of putting really good modems in it. It had a wide spectrum range of what bands they support. So being able to say, at a larger facility, I mean, if Heineken wants to deploy something like this, oh, heck yeah, they probably could do it. And they might have a private 5G network, but let's say T-Mobile offers a private offering on their public via a slice. It's easy to connect that radio to it. You just change the sims. >> Is that how the CSPs fit here? How are they monetized? >> Yeah, correct. So one of our partners is T-Mobile and so we're working with them. We've got other telco partners that are coming on board in our lab. And so we'll do the same thing. We're going to take this back and put it in the lab and offer it up as others because the baseline building blocks or Lego blocks per se can be used in a bunch of different industries. It's really that starter point of giving folks the idea of what's possible. >> So small manufacturing, agriculture you mentioned, any other sort of use cases we should tune into? >> I think it's environmental monitoring, all of that stuff, I see it in IoT deployments all over the world. Just the simple starter kits 'cause a farmer doesn't want to get sold a solution, a platform, where he's got to hire a bunch of coders and partner with the big carriers. He just wants something that works. >> Another use case that we see a lot, a high cost in a lot of these places is the cost of energy. And a lot of companies don't know what they're spending on electricity. So a very simple energy monitoring system like that, it's a really good ROI. I'm going to spend five or $10,000 on a system like this, but I'm going to save $20,000 over a year 'cause I'm able to see, have visibility into that data. That's a lot of what this story's about, just giving visibility into the process. >> It's very cool, and like you said, it gets people excited. Is it a big market? How do you size it? Is it a big TAM? >> Yeah, so one thing that Dell brings to the table in this space is people are buying their laptops, their servers and whatnot from Dell and companies are comfortable in doing business with Dell because of our model direct to customer and whatnot. So our ability to bring a device like this to the OT space and have them have that same user experience they have with laptops and our client products in a ruggedized solution like this and bring a lot of partners to the table makes it easy for our customers to implement this across all kinds of industries. >> So we're talking to billions, tens of billions. Do we know how big this market is? What's the TAM? I mean, come on, you work for Dell. You have to do a TAM analysis. >> Yes, no, yeah. I mean, it really is in the billions. The market is huge for this one. I think we just tapped into it. We're kind of focused in on the brewery piece of it and the liquor piece of it, but the possibilities are endless. >> Yeah, that's tip of the spear. Guys, great story. >> It's scalable. I think the biggest thing, just my final feedback is working and partnering with Dell is we got something as small as this edge gateway that I can run a Packet Core on and run a 5G standalone node and then have one of the small little 5G radios out there. And I've got these deployed in a farm. Give the farmer an idea of what's possible, give him a unit on his tractor, and now he can do something that, we're providing connectivity he had never had before. But as we scale up, we've got the big brother to this. When we scale up from that, we got the telco size units that we can put. So it's very scalable. It's just a great suite of offerings. >> Yeah, outstanding. Guys, thanks for sharing the story. Great to have you on theCUBE. >> Good to be with you today. >> Stop by for beer later. >> You know it. All right, Dave Vellante for Dave Nicholson and the entire CUBE team, we're here live at the Fira in Barcelona MWC '23 day four. Keep it right there. (upbeat music)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> While never really meant to be a consumer tech event, the rapid ascendancy of smartphones sucked much of the air out of Mobile World Congress over the years, now MWC. And while the device manufacturers continue to have a major presence at the show, the maturity of intelligent devices, longer life cycles, and the disaggregation of the network stack, have put enterprise technologies front and center in the telco business. Semiconductor manufacturers, network equipment players, infrastructure companies, cloud vendors, software providers, and a spate of startups are eyeing the trillion dollar plus communications industry as one of the next big things to watch this decade. Hello, and welcome to this week's Wikibon CUBE Insights, powered by ETR. In this Breaking Analysis, we bring you part two of our ongoing coverage of MWC '23, with some new data on enterprise players specifically in large telco environments, a brief glimpse at some of the pre-announcement news and corresponding themes ahead of MWC, and some of the key announcement areas we'll be watching at the show on theCUBE. Now, last week we shared some ETR data that showed how traditional enterprise tech players were performing, specifically within the telecoms vertical. Here's a new look at that data from ETR, which isolates the same companies, but cuts the data for what ETR calls large telco. The N in this cut is 196, down from 288 last week when we included all company sizes in the dataset. Now remember the two dimensions here, on the y-axis is net score, or spending momentum, and on the x-axis is pervasiveness in the data set. The table insert in the upper left informs how the dots and companies are plotted, and that red dotted line, the horizontal line at 40%, that indicates a highly elevated net score. Now while the data are not dramatically different in terms of relative positioning, there are a couple of changes at the margin. So just going down the list and focusing on net score. Azure is comparable, but slightly lower in this sector in the large telco than it was overall. Google Cloud comes in at number two, and basically swapped places with AWS, which drops slightly in the large telco relative to overall telco. Snowflake is also slightly down by one percentage point, but maintains its position. Remember Snowflake, overall, its net score is much, much higher when measuring across all verticals. Snowflake comes down in telco, and relative to overall, a little bit down in large telco, but it's making some moves to attack this market that we'll talk about in a moment. Next are Red Hat OpenStack and Databricks. About the same in large tech telco as they were an overall telco. Then there's Dell next that has a big presence at MWC and is getting serious about driving 16G adoption, and new servers, and edge servers, and other partnerships. Cisco and Red Hat OpenShift basically swapped spots when moving from all telco to large telco, as Cisco drops and Red Hat bumps up a bit. And VMware dropped about four percentage points in large telco. Accenture moved up dramatically, about nine percentage points in big telco, large telco relative to all telco. HPE dropped a couple of percentage points. Oracle stayed about the same. And IBM surprisingly dropped by about five points. So look, I understand not a ton of change in terms of spending momentum in the large sector versus telco overall, but some deltas. The bottom line for enterprise players is one, they're just getting started in this new disruption journey that they're on as the stack disaggregates. Two, all these players have experience in delivering horizontal solutions, but now working with partners and identifying big problems to be solved, and three, many of these companies are generally not the fastest moving firms relative to smaller disruptive disruptors. Now, cloud has been an exception in fairness. But the good news for the legacy infrastructure and IT companies is that the telco transformation and the 5G buildout is going to take years. So it's moving at a pace that is very favorable to many of these companies. Okay, so looking at just some of the pre-announcement highlights that have hit the wire this week, I want to give you a glimpse of the diversity of innovation that is occurring in the telecommunication space. You got semiconductor manufacturers, device makers, network equipment players, carriers, cloud vendors, enterprise tech companies, software companies, startups. Now we've included, you'll see in this list, we've included OpeRAN, that logo, because there's so much buzz around the topic and we're going to come back to that. But suffice it to say, there's no way we can cover all the announcements from the 2000 plus exhibitors at the show. So we're going to cherry pick here and make a few call outs. Hewlett Packard Enterprise announced an acquisition of an Italian private cellular network company called AthoNet. Zeus Kerravala wrote about it on SiliconANGLE if you want more details. Now interestingly, HPE has a partnership with Solana, which also does private 5G. But according to Zeus, Solona is more of an out-of-the-box solution, whereas AthoNet is designed for the core and requires more integration. And as you'll see in a moment, there's going to be a lot of talk at the show about private network. There's going to be a lot of news there from other competitors, and we're going to be watching that closely. And while many are concerned about the P5G, private 5G, encroaching on wifi, Kerravala doesn't see it that way. Rather, he feels that these private networks are really designed for more industrial, and you know mission critical environments, like factories, and warehouses that are run by robots, et cetera. 'Cause these can justify the increased expense of private networks. Whereas wifi remains a very low cost and flexible option for, you know, whatever offices and homes. Now, over to Dell. Dell announced its intent to go hard after opening up the telco network with the announcement that in the second half of this year it's going to begin shipping its infrastructure blocks for Red Hat. Remember it's like kind of the converged infrastructure for telco with a more open ecosystem and sort of more flexible, you know, more mature engineered system. Dell has also announced a range of PowerEdge servers for a variety of use cases. A big wide line bringing forth its 16G portfolio and aiming squarely at the telco space. Dell also announced, here we go, a private wireless offering with airspan, and Expedo, and a solution with AthoNet, the company HPE announced it was purchasing. So I guess Dell and HPE are now partnering up in the private wireless space, and yes, hell is freezing over folks. We'll see where that relationship goes in the mid- to long-term. Dell also announced new lab and certification capabilities, which we said last week was going to be critical for the further adoption of open ecosystem technology. So props to Dell for, you know, putting real emphasis and investment in that. AWS also made a number of announcements in this space including private wireless solutions and associated managed services. AWS named Deutsche Telekom, Orange, T-Mobile, Telefonica, and some others as partners. And AWS announced the stepped up partnership, specifically with T-Mobile, to bring AWS services to T-Mobile's network portfolio. Snowflake, back to Snowflake, announced its telecom data cloud. Remember we showed the data earlier, it's Snowflake not as strong in the telco sector, but they're continuing to move toward this go-to market alignment within key industries, realigning their go-to market by vertical. It also announced that AT&T, and a number of other partners, are collaborating to break down data silos specifically in telco. Look, essentially, this is Snowflake taking its core value prop to the telco vertical and forming key partnerships that resonate in the space. So think simplification, breaking down silos, data sharing, eventually data monetization. Samsung previewed its future capability to allow smartphones to access satellite services, something Apple has previously done. AMD, Intel, Marvell, Qualcomm, are all in the act, all the semiconductor players. Qualcomm for example, announced along with Telefonica, and Erickson, a 5G millimeter network that will be showcased in Spain at the event this coming week using Qualcomm Snapdragon chipset platform, based on none other than Arm technology. Of course, Arm we said is going to dominate the edge, and is is clearly doing so. It's got the volume advantage over, you know, traditional Intel, you know, X86 architectures. And it's no surprise that Microsoft is touting its open AI relationship. You're going to hear a lot of AI talk at this conference as is AI is now, you know, is the now topic. All right, we could go on and on and on. There's just so much going on at Mobile World Congress or MWC, that we just wanted to give you a glimpse of some of the highlights that we've been watching. Which brings us to the key topics and issues that we'll be exploring at MWC next week. We touched on some of this last week. A big topic of conversation will of course be, you know, 5G. Is it ever going to become real? Is it, is anybody ever going to make money at 5G? There's so much excitement around and anticipation around 5G. It has not lived up to the hype, but that's because the rollout, as we've previous reported, is going to take years. And part of that rollout is going to rely on the disaggregation of the hardened telco stack, as we reported last week and in previous Breaking Analysis episodes. OpenRAN is a big component of that evolution. You know, as our RAN intelligent controllers, RICs, which essentially the brain of OpenRAN, if you will. Now as we build out 5G networks at massive scale and accommodate unprecedented volumes of data and apply compute-hungry AI to all this data, the issue of energy efficiency is going to be front and center. It has to be. Not only is it a, you know, hot political issue, the reality is that improving power efficiency is compulsory or the whole vision of telco's future is going to come crashing down. So chip manufacturers, equipment makers, cloud providers, everybody is going to be doubling down and clicking on this topic. Let's talk about AI. AI as we said, it is the hot topic right now, but it is happening not only in consumer, with things like ChatGPT. And think about the theme of this Breaking Analysis in the enterprise, AI in the enterprise cannot be ChatGPT. It cannot be error prone the way ChatGPT is. It has to be clean, reliable, governed, accurate. It's got to be ethical. It's got to be trusted. Okay, we're going to have Zeus Kerravala on the show next week and definitely want to get his take on private networks and how they're going to impact wifi. You know, will private networks cannibalize wifi? If not, why not? He wrote about this again on SiliconANGLE if you want more details, and we're going to unpack that on theCUBE this week. And finally, as always we'll be following the data flows to understand where and how telcos, cloud players, startups, software companies, disruptors, legacy companies, end customers, how are they going to make money from new data opportunities? 'Cause we often say in theCUBE, don't ever bet against data. All right, that's a wrap for today. Remember theCUBE is going to be on location at MWC 2023 next week. We got a great set. We're in the walkway in between halls four and five, right in Congress Square, stand CS-60. Look for us, we got a full schedule. If you got a great story or you have news, stop by. We're going to try to get you on the program. I'll be there with Lisa Martin, co-hosting, David Nicholson as well, and the entire CUBE crew, so don't forget to come by and see us. I want to thank Alex Myerson, who's on production and manages the podcast, and Ken Schiffman, as well, in our Boston studio. Kristen Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our editor-in-chief over at SiliconANGLE.com. He does some great editing. Thank you. All right, remember all these episodes they are available as podcasts wherever you listen. All you got to do is search Breaking Analysis podcasts. I publish each week on Wikibon.com and SiliconANGLE.com. All the video content is available on demand at theCUBE.net, or you can email me directly if you want to get in touch David.Vellante@SiliconANGLE.com or DM me @DVellante, or comment on our LinkedIn posts. And please do check out ETR.ai for the best survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights, powered by ETR. Thanks for watching. We'll see you next week at Mobile World Congress '23, MWC '23, or next time on Breaking Analysis. (bright music)

>> Hello and welcome to theCUBE's coverage of International Women's Day. I'm John Furrier, host of theCUBE. Got a variety of interviews across the gamut from topics, women in tech, mentoring, pipelining, developers, open source, executives. Stanford's having International Women's Day celebration with the women in data science, which we're streaming that live as well. Variety of programs. In this segment, Meagen Eisenberg, friend of theCUBE, she's the CMO of Laceworks, is an amazing executive, got a great journey story as a CMO but she's also actively advising startups, companies and really pays it forward. I want to say Meagen, thank you for coming on the program and thanks for sharing. >> Yeah, thank you for having me. I'm happy to be here. >> Well, we're going to get into some of the journey celebrations that you've gone through and best practice what you've learned is pay that forward. But I got to say, one of the things that really impresses me about you as an executive is you get stuff done. You're a great CMO but also you're advised a lot of companies, you have a lot of irons in the fires and you're advising companies and sometimes they're really small startups to bigger companies, and you're paying it forward, which I love. That's kind of the spirit of this day. >> Yeah, I mean, I agree with you. When I think about my career, a lot of it was looking to mentors women out in the field. This morning I was at a breakfast by Eileen and we had the CEO of General Motors on, and she was talking about her journey nine years as a CEO. And you know, and she's paying it forward with us. But I think about, you know, when you're advising startups, you know, I've gathered knowledge and pattern recognition and to be able to share that is, you know, I enjoy it. >> Yeah. And the startups are also fun too, but it's not always easy and it can get kind of messy as you know. Some startups don't make it some succeed and it's always like the origination story is kind of rewritten and then that's that messy middle. And then it's like that arrows that don't look like a straight line but everyone thinks it's great and you know, it's not for the faint of heart. And Teresa Carlson, who I've interviewed many times, former Amazon, now she's the president of Flexport, she always says, sometimes startups on certain industries aren't for the faint of heart so you got to have a little bit of metal, right? You got to be tough. And some cases that you don't need that, but startups, it's not always easy. What have you learned? >> Yeah, I mean, certainly in the startup world, grit, creativity. You know, when I was at TripActions travel company, pandemic hits, nobody's traveling. You cut budget, you cut heads, but you focus on the core, right? You focus on what you need to survive. And creativity, I think, wins. And, you know, as a CMO when you're marketing, how do you get through that noise? Even the security space, Lacework, it's a fragmented market. You've got to be differentiated and position yourself and you know, be talking to the right target audience and customers. >> Talk about your journey over the years. What have you learned? What's some observations? Can you share any stories and best practices that someone watching could learn from? I know there's a lot of people coming into the tech space with the generative AI things going on in Cloud computing, scaling to the edge, there's a lot more aperture for technical jobs as well as just new roles and new roles that haven't, you really don't go to college for anymore. You got cybersecurity you're in. What are some of the things that you've done over your career if you can share and some best practices? >> Yeah, I think number one, continual learning. When I look through my career, I was constantly reading, networking. Part of the journey is who you're meeting along the way. As you become more senior, your ability to hire and bring in talent matters a lot. I'm always trying to meet with new people. Yeah, if I look at my Amazon feed of books I've bought, right, it kind of chronicle of my history of things I was learning about. Right now I'm reading a lot about cybersecurity, how the, you know, how how they tell me the world ends is the one I'm reading most recently. But you've got to come up to speed and then know the product, get in there and talk to customers. Certainly on the marketing front, anytime I can talk with the customer and find out how they're using us, why they love us, that, you know, helps me better position and differentiate our company. >> By the way, that book is amazing. I saw Nicole speak on Tuesday night with John Markoff and Palo Alto here. What a great story she told there. I recommend that book to everyone. It goes in and she did eight years of research into that book around zero day marketplaces to all the actors involved in security. And it was very interesting. >> Yeah, I mean, it definitely wakes you up, makes you think about what's going on in the world. Very relevant. >> It's like, yeah, it was happening all the time, wasn't it. All the hacking. But this brings me, this brings up an interesting point though, because you're in a cybersecurity area, which by the way, it's changing very fast. It's becoming a bigger industry. It's not just male dominated, although it is now, it's still male dominated, but it's becoming much more and then just tech. >> Yeah, I mean it's a constantly evolving threat landscape and we're learning, and I think more than ever you need to be able to use the data that companies have and, you know, learn from it. That's one of the ways we position ourselves. We're not just about writing rules that won't help you with those zero day attacks. You've got to be able to understand your particular environment and at any moment if it changes. And that's how we help you detect a threat. >> How is, how are things going with you? Is there any new things you guys got going on? Initiatives or programs for women in tech and increasing the range of diversity inclusion in the industry? Because again, this industry's getting much wider too. It's not just specialized, it's also growing. >> Yes, actually I'm excited. We're launching secured by women, securedbywomen.com and it's very much focused on women in the industry, which some studies are showing it's about 25% of security professionals are women. And we're going to be taking nominations and sponsoring women to go to upcoming security events. And so excited to launch that this month and really celebrate women in security and help them, you know, part of that continual learning that I talked about, making sure they're there learning, having the conversations at the conferences, being able to network. >> I have to ask you, what inspired you to pursue the career in tech? What was the motivation? >> You know, if I think way back, originally I wanted to be on the art side and my dad said, "You can do anything as long as it's in the sciences." And so in undergrad I did computer science and MIS. Graduated with MIS and computer science minor. And when I came out I was a IT engineer at Cisco and you know, that kind of started my journey and decided to go back and get my MBA. And during that process I fell in love with marketing and I thought, okay, I understand the buyer, I can come out and market technology to the IT world and developers. And then from there went to several tech companies. >> I mean my father was an engineer. He had the same kind of thing. You got to be an engineer, it's a steady, stable job. But that time, computer science, I mean we've seen the evolution of computer science now it's the most popular degree at Berkeley we've heard and around the world and the education formats are changing. You're seeing a lot of people's self-training on YouTube. The field has really changed. What are some of the challenges you see for folks trying to get into the industry and how would you advise today if you were talking to your young self, what would you, what would be the narrative? >> Yeah, I mean my drawback then was HTML pages were coming out and I thought it would be fun to design, you know, webpages. So you find something you're passionate about in the space today, whether it's gaming or it's cybersecurity. Go and be excited about it and apply and don't give up, right? Do whatever you can to read and learn. And you're right, there are a ton of online self-help. I always try to hire women and people who are continual learners and are teaching themselves something. And I try to find that in an interview to know that they, because when you come to a business, you're there to solve problems and challenges. And the folks that can do that and be innovative and learn, those are the ones I want on my team. >> It's interesting, you know, technology is now impacting society and we need everyone involved to participate and give requirements. And that kind of leads my next question for you is, like, in your opinion, or let me just step back, let me rephrase. What are some of the things that you see technology being used for, for society right now that will impact people's lives? Because this is not a gender thing. We need everybody involved 'cause society is now digital. Technology's pervasive. The AI trends now we're seeing is clearly unmasking to the mainstream that there's some cool stuff happening. >> Yeah, I mean, I think ChatGPT, think about that. All the different ways we're using it we're writing content and marketing with it. We're, you know, I just read an article yesterday, folks are using it to write children's stories and then selling those stories on Amazon, right? And the amount that they can produce with it. But if you think about it, there's unlimited uses with that technology and you've got all the major players getting involved on it. That one major launch and piece of technology is going to transform us in the next six months to a year. And it's the ability to process so much data and then turn that into just assets that we use and the creativity that's building on top of it. Even TripActions has incorporated ChatGPT into your ability to figure out where you want when you're traveling, what's happening in that city. So it's just, you're going to see that incorporated everywhere. >> I mean we've done an interview before TripAction, your other company you were at. Interesting point you don't have to type in a box to say, I'm traveling, I want a hotel. You can just say, I'm going to Barcelona for Mobile World Congress, I want to have a good time. I want some tapas and a nice dinner out. >> Yes. Yeah. That easy. We're making it easy. >> It's efficiency. >> And actually I was going to say for women specifically, I think the reason why we can do so much today is all the technology and apps that we have. I think about DoorDash, I think about Waze you know, when I was younger you had to print out instructions. Now I get in the car real quick, I need to go to soccer practice, I enter it, I need to pick them up at someone's house. I enter it. It's everything's real time. And so it takes away all the things that I don't add value to and allows me to focus on what I want in business. And so there's a bunch of, you know, apps out there that have allowed me to be so much more efficient and productive that my mother didn't have for sure when I was growing up. >> That is an amazing, I think that actually illustrates, in my opinion, the best example of ChatGPT because the maps and GPS integration were two techs, technologies merged together that replace driving and looking at the map. You know, like how do you do that? Like now it's automatically. This is what's going to happen to creative, to writing, to ideation. I even heard Nicole from her book read said that they're using ChatGPT to write zero day exploits. So you seeing it... >> That's scary stuff. You're right. >> You're seeing it everywhere. Super exciting. Well, I got to ask you before you get into some of the Lacework things that you're involved with, cause I think you're doing great work over there is, what was the most exciting projects you've worked on in your career? You came in Cisco, very technical company, so got the technical chops, CSMIS which stands for Management of Information Science for all the young people out there, that was the state of the art back then. What are some of the exciting things you've done? >> Yeah, I mean, I think about, I think about MongoDB and learning to market to developers. Taking the company public in 2017. Launching Atlas database as a service. Now there's so much more of that, you know, the PLG motion, going to TripActions, you know, surviving a pandemic, still being able to come out of that and all the learnings that went with it. You know, they recently, I guess rebranded, so they're Navan now. And then now back in the security space, you know, 14 years ago I was at ArcSite and we were bought by HP. And so getting back into the security world is exciting and it's transformed a ton as you know, it's way more complicated than it was. And so just understanding the pain of our customers and how we protect them as is fun. And I like, you know, being there from a marketing standpoint. >> Well we really appreciate you coming on and sharing that. I got to ask you, for folks watching they might be interested in some advice that you might have for them and their career in tech. I know a lot of young people love the tech. It's becoming pervasive in our lives, as we mentioned. What advice would you give for folks watching that want to start a career in tech? >> Yeah, so work hard, right? Study, network, your first job, be the best at it because every job after that you get pulled into a network. And every time I move, I'm hiring people from the last job, two jobs before, three jobs before. And I'm looking for people that are working hard, care, you know, are continual learners and you know, add value. What can you do to solve problems at your work and add value? >> What's your secret networking hack or growth hack or tip that you can share? Because you're a great networker by the way. You're amazing and you do add a lot of value. I've seen you in action. >> Well, I try never to eat alone. I've got breakfast, I've got lunch, I've got coffee breaks and dinner. And so when I'm at work, I try and always sit and eat with a team member, new group. If I'm out on the road, I'm, you know, meeting people for lunch, going for dinner, just, you know, don't sit at your desk by yourself and don't sit in the hotel room. Get out and meet with people. >> What do you think about now that we're out of the pandemic or somewhat out of the pandemic so to speak, events are back. >> Yes. >> RSA is coming up. It's a big event. The bigger events are getting bigger and then the other events are kind of smaller being distributed. What's your vision of how events are evolving? >> Yeah, I mean, you've got to be in person. Those are the relationships. Right now more than ever people care about renewals and you are building that rapport. And if you're not meeting with your customers, your competitors are. So what I would say is get out there Lacework, we're going to be at RSA, we're going to be at re:Inforce, we're going to be at all of these events, building relationships, you know, coffee, lunch, and yeah, I think the future of events are here to stay and those that don't embrace in person are going to give up business. They're going to lose market share to us. >> And networking is obviously very key on events as well. >> Yes. >> A good opportunity as always get out to the events. What's the event networking trick or advice do you give folks that are going to get out to the networking world? >> Yeah, schedule ahead of time. Don't go to an event and expect people just to come by for great swag. You should be partnering with your sales team and scheduling ahead of time, getting on people's calendars. Don't go there without having 100 or 200 meetings already booked. >> Got it. All right. Let's talk about you, your career. You're currently at Lacework. It's a very hot company in a hot field, security, very male dominated, you're a leader there. What's it like? What's the strategies? How does a woman get in there and be successful? What are some tricks, observations, any data you can share? What's the best practice? What's the secret sauce from Meagen Eisenberg? >> Yes. Yeah, for Meagen Eisenberg. For Lacework, you know, we're focused on our customers. There's nothing better than getting, being close to them, solving their pain, showcasing them. So if you want to go into security, focus on their, the issues and their problems and make sure they're aware of what you're delivering. I mean, we're focused on cloud security and we go from build time to run time. And that's the draw for me here is we had a lot of, you know, happy, excited customers by what we were doing. And what we're doing is very different from legacy security providers. And it is tapping into the trend of really understanding how much data you have and what's happening in the data to detect the anomalies and the threats that are there. >> You know, one of the conversations that I was just having with a senior leader, she was amazing and I asked her what she thought of the current landscape, the job market, the how to get promoted through the careers, all those things. And the response was interesting. I want to get your reaction. She said interdisciplinary skills are critical. And now more than ever, the having that, having a set of skills, technical and social and emotional are super valuable. Do you agree? What's your reaction to that and what would, how would you reframe that? >> Yeah, I mean, I completely agree. You can't be a leader without balance. You've got to know your craft because you're developing and training your team, but you also need to know the, you know, how to build relationships. You're not going to be successful as a C-level exec if you're not partnering across the functions. As a CMO I need to partner with product, I need to partner with the head of sales, I need to partner with finance. So those relationships matter a ton. I also need to attract the right talent. I want to have solid people on the team. And what I will say in the security, cybersecurity space, there's a talent shortage and you cannot hire enough people to protect your company in that space. And that's kind of our part of it is we reduce the number of alerts that you're getting. So you don't need hundreds of people to detect an issue. You're using technology to show, you know, to highlight the issue and then your team can focus on those alerts that matter. >> Yeah, there's a lot of emerging markets where leveling up and you don't need pedigree. You can just level up skill-wise pretty quickly. Which brings me to the next question for you is how do you keep up with all the tech day-to-day and how should someone watching stay on top of it? Because I mean, you got to be on top of this stuff and you got to ride the wave. It's pretty turbulent, but it's still growing and changing. >> Yeah, it's true. I mean, there's a lot of reading. I'm watching the news. Anytime something comes out, you know, ChatGPT I'm playing with it. I've got a great network and sharing. I'm on, you know, LinkedIn reading articles all the time. I have a team, right? Every time I hire someone, they bring new information and knowledge in and I'm you know, Cal Poly had this learn by doing that was the philosophy at San Luis Obispo. So do it. Try it, don't be afraid of it. I think that's the advice. >> Well, I love some of the points you mentioned community and network. You mentioned networking. That brings up the community question, how could people get involved? What communities are out there? How should they approach communities? 'Cause communities are also networks, but also they're welcoming people in that form networks. So it's a network of networks. So what's your take on how to engage and work with communities? How do you find your tribe? If someone's getting into the business, they want support, they might want technology learnings, what's your approach? >> Yeah, so a few, a few different places. One, I'm part of the operator collective, which is a strong female investment group that's open and works a lot with operators and they're in on the newest technologies 'cause they're investing in it. Chief I think is a great organization as well. You've got a lot of, if you're in marketing, there's a ton of CMO networking events that you can go to. I would say any field, even for us at Lacework, we've got some strong CISO networks and we do dinners around you know, we have one coming up in the Bay area, in Boston, New York, and you can come and meet other CISOs and security leaders. So when I get an invite and you know we all do, I will go to it. I'll carve out the time and meet with others. So I think, you know, part of the community is get out there and, you know, join some of these different groups. >> Meagen, thank you so much for spending the time. Final question for you. How do you see the future of tech evolving and how do you see your role in it? >> Yeah, I mean, marketing's changing wildly. There's so many different channels. You think about all the social media channels that have changed over the last five years. So when I think about the future of tech, I'm looking at apps on my phone. I have three daughters, 13, 11, and 8. I'm telling you, they come to me with new apps and new technology all the time, and I'm paying attention what they're, you know, what they're participating in and what they want to be a part of. And certainly it's going to be a lot more around the data and AI. I think we're only at the beginning of that. So we will continue to, you know, learn from it and wield it and deal with the mass amount of data that's out there. >> Well, you saw TikTok just got banned by the European Commission today around their staff. Interesting times. >> It is. >> Meagen, thank you so much as always. You're a great tech athlete. Been following your career for a while, a long time. You're an amazing leader. Thank you for sharing your story here on theCUBE, celebration of International Women's Day. Every day is IWD and thanks for coming on. >> Thank you for having me. >> Okay. I'm John Furrier here in theCUBE Studios in Palo Alto. Thank you for watching, more to come stay with us. (bright music)