David Shacochis, Lumen | AWS re:Invent 2022
(upbeat music) >> Hello, friends. Welcome back to The Cube's live coverage of AWS re:Invent 2022. We're in Vegas. Lovely Las Vegas. Beautiful outside, although I have only seen outside today once, but very excited to be at re:Invent. We're hearing between 50,000 and 70,000 attendees and it's insane, but people are ready to be back. This morning's keynote by CEO Adam Selipsky was full of great messages, big focus on data, customers, partners, the ecosystem. So excited. And I'm very pleased to welcome back one of our alumni to the program, David Shacochis, VP Enterprise Portfolio Strategy Product Management at Lumen. David, welcome back. >> Lisa, good to be here. The Five Timers Club. >> You are in the Five Timers Club. This is David's fifth appearance on the show. And we were talking before we went live- >> Do we do the jacket now and do we do the jacket later? >> Yeah, the jacket will come later. >> Okay. >> The Five Timers Club, like on SNL. We're going to have that for The Cube. We'll get you measured up and get that all fitted for you. >> That'd be better. >> So talk a little bit about Lumen. 'Cause last time you hear it wasn't Lumen. >> We weren't Lumen last time. So this is the first time... last time we were here on The Cube at re:Invent. This was probably 2019 or so. We were a different company. The company was called CenturyLink back then. We rebranded in 2020 to really represent our identity as a delivery of...as a solutions provider over our fiber network. So Lumen is the corporate brand, the company name. It represents basically a lot of the fiber that's been laid throughout the world and in North America and in enterprise metropolitan areas over the past 10 to 15 years. You know, companies like CenturyLink and Quest and Level 3, all those companies have really rolled up into building that core asset of the network. So Lumen is really the brand for the 21st century for the company, really focused on delivering services for the enterprise and then delivering a lot of value added services around that core network asset. >> So rebranding during the pandemic, what's been the customer feedback and sentiment? >> Yeah, I think customers have really actually appreciated it as certainly a more technology oriented brand, right? Sort of shifting away a little bit from some of the communications and telecom background of the company and the heritage. And while those assets that were built up during that period of time have been substantial, and we still build off of those assets going forward, really what a lot of the customer feedback has been is that it puts us in a posture to be a little bit more of a business solutions provider for customers, right? So there's a lot of things that we can do with that core network asset, the fiber networking a lot of the services that we launch on that in terms of public IP, you know, public internet capacity, private networking, private VPNs, VoIP and voice services. These are services that you'd expect from a company like that. But there's a lot of services inside the Lumen brand that you might surprise you, right? There's an edge computing capability that can deliver five milliseconds of latency within 95% of North American enterprise. >> Wow. >> There's a threat detection lab that goes and takes all of the traffic flowing over the public side of our network and analyzes it in a data lake and turns it into threat intelligence that we then offer off to our customers on a subscription basis. There's a production house that goes and, you know, does production networking for major sports arenas and sports events. There's a wide range of services inside of Lumen that really what the Lumen brand allows us to do is start talking about what those services can do and what networking can do for our customers in the enterprise in a more comprehensive way. >> So good changes, big brand changes for Lumen in the last couple of years. Also, I mean, during a time of such turmoil in the world, we've seen work change dramatically. You know, everybody...companies had to pivot massively quickly a couple years ago. >> Yep. >> Almost approaching three years ago, which is crazy amazing to be digital because they had to be able to survive. >> They did >> Now they're looking at being able to thrive, but now we're also in this hybrid work environment. The future of work has changed. >> Totally. >> Almost permanently. >> Yep. >> How is Lumen positioned to address some of the permanent changes to the work environments? Like the last time we were at re:Invented- >> Yeah. >> In person. This didn't exist. >> That's right. So really, it's one of the things we talk to our customers almost the most about is this idea of the future of work. And, you know, we really think about the future of work as about, you know, workers and workloads and the networks that connect them. You think about how much all of those demands are shifting and changing, right? What we were talking about, and it's very easy for all of us to conceptualize what the changing face of the worker looks like, whether those are knowledge workers or frontline workers the venues in which people are working the environments and that connectivity, predictability of those work desk environments changes so significantly. But workloads are changing and, you know we're sitting here at a trade show that does nothing but celebrate the transformation of workloads. Workloads running in ways in business logic and capturing of data and analysis of data. The changing methodologies and the changing formats of workloads, and then the changing venues for workloads. So workloads are running in places that never used to be data centers before. Workloads are running in interesting places and in different and challenging locations for what didn't used to be the data center. And so, you know, the workloads and the workloads are in a very dynamic situation. And the networks that connect them have to be dynamic, and they have to be flexible. And that's really why a lot of what Lumen invests in is working on the networks that connect workers and workloads both from a visibility and a managed services perspective to make sure that we're removing blind spots and then removing potential choke points and capacity issues, but then also being adaptable and dynamic enough to be able to go and reconfigure that network to reach all of the different places that, you know, workers and workloads are going to evolve into. What you'll find in a lot of cases, you know, the workers...a common scenario in the enterprise. A 500 person company with, you know, five offices and maybe one major facility. You know, that's now a 505 office company. >> Right. >> Right? The challenge of the network and the challenge of connecting workers and workloads is really one of the main conversations we have with our customers heading into this 21st century. >> What are some of the things that they're looking forward to in terms of embracing the future of work knowing this is probably how it's going to remain? >> Yeah, I think companies are really starting to experiment carefully and start to think about what they can do and certainly think about what they can do in the cloud with things like what the AWS platform allows them to do with some of the AWS abstractions and the AWS services allow them to start writing software for, and they're starting to really carefully, but very creatively and reach out into their you know, their base of enterprise data, their base of enterprise value to start running some experiments. We actually had a really interesting example of that in a session that Lumen shared here at re:Invent yesterday. You know, for the few hundred people that were there. You know, I think we got a lot of great feedback. It was really interesting session about the...really gets at this issue of the future of work and the changing ways that people are working. It actually was a really cool use case we worked on with Major League Baseball, Fox Sports, and AWS with the... using the Lumen network to essentially virtualize the production truck. Right? So you've all heard that, you know, the sports metaphor of, you know, the folks in the booth were sitting there started looking down and they're saying, oh great job by the guys or the gals in the truck. >> Yep. >> Right? That are, you know, that bring in that replay or great camera angle. They're always talking about the team and their production truck. Well, that production truck is literally a truck sitting outside the stadium. >> Yep. >> Full of electronics and software and gear. We were able to go and for a Major League Baseball game in...back in August, we were able to go and work with AWS, using the Lumen network, working with our partners and our customers at Fox Sports and virtualize all of that gear inside the truck. >> Wow. That's outstanding. >> Yep. So it was a live game. You know, they simulcast it, right? So, you know, we did our part of the broadcast and many hundreds of people, you know, saw that live broadcast was the first time they tried doing it. But, you know, to your point, what are enterprises doing? They're really starting to experiment, sort to push the envelope, right? They're kind of running things in new ways, you know, obviously hedging their bets, right? And sort of moving their way and sort of blue-green testing their way into the future by trying things out. But, you know, this is a massive revenue opportunity for a Major League Baseball game. You know, a premier, you know, Sunday night baseball contest between the Yankees and the Cardinals. We were able to go and take the entire truck, virtualize it down to a small rack of connectivity gear. Basically have that production network run over redundant fiber paths on the Lumen network up into AWS. And AWS is where all that software worked. The technical director of the show sitting in his office in North Carolina. >> Wow. >> The sound engineer is sitting in, you know, on his porch in Connecticut. Right? They were able to go and do the work of production anywhere while connected to AWS and then using the Lumen network, right? You know, the high powered capabilities of Lumens network underlay to be able to, you know, go and design a network topology and a worked topology that really wasn't possible before. >> Right. It's nice to hear, to your point, that customers are really embracing experimentation. >> Right. >> That's challenging to, obviously there was a big massive forcing function a couple of years ago where they didn't have a choice if they wanted to survive and eventually succeed and grow. >> Yeah. >> But the mindset of experimentation requires cultural change and that's a hard thing to do especially for I would think legacy organizations like Major League Baseball, but it sounds like they have the appetite. >> Yeah. They have the interest. >> They've been a fairly innovative organization for some time. But, you know, you're right. That idea of experimenting and that idea of trying out new things. Many people have observed, right? It's that forcing function of the pandemic that really drove a lot of organizations to go and make a lot of moves really quickly. And then they realized, oh, wait a minute. You know... I guess there's some sort of storytelling metaphor in there at some point of people realizing, oh wait, I can swim in these waters, right? I can do this. And so now they're starting to experiment and push the envelope even more using platforms like AWS, but then using a lot of the folks in the AWS partner network like Lumen, who are designing and sort of similarly inspired to deliver, you know, on demand and virtualized and dynamic capabilities within the core of our network and then within the services that our network can and the ways that our network connects to AWS. All of that experimentation now is possible because a lot of the things you need to do to try out the experiment are things you can get on demand and you can kind of pat, you can move back, you can learn. You can try new things and you can evolve. >> Right. >> Yep. >> Right. Absolutely. What are some of the things that you're excited about as, you know, here was this forcing function a couple years ago, we're coming out of that now, but the world has changed. The future of work as you are so brilliantly articulated has changed permanently. What are you excited about in terms of Lumen and AWS going forward? As we saw a lot of announcements this morning, big focus on data, vision of AWS is really that flywheel with Adams Selipsky is really, really going. What are you excited about going forward into 2023? >> Yeah, I mean we've been working with AWS for so long and have been critical partners for so long that, you know, I think a lot of it is continuation of a lot of the great work we've been doing. We've been investing in our own capabilities around the AWS partner network. You know, we're actually in a fairly unique position, you know, and we like to think that we're that unique position around the future of work where between workers, workloads and the networks that connect them. Our fingers are on a lot of those pulse points, right? Our fingers are on at really at the nexus of a lot of those dynamics. And our investment with AWS even puts us even more so in a position to go where a lot of the workloads are being transformed, right? So that's why, you know, we've invested in being one of the few network operators that is in the AWS partner network at the advanced tier that have the managed services competency, that have the migration competency and the network competency. You can count on one hand the number of network operators that have actually invested at that level with AWS. And there's an even smaller number that is, you know, based here in the United States. So, you know, I think that investment with AWS, investment in their partner programs and then investment co-innovation with AWS on things like that MLB use case really puts us in a position to keep on doing these kinds of things within the AWS partner network. And that's one of the biggest things we could possibly be excited about. >> So what does the go to market look like? Is it Lumen goes in, brings in AWS, vice versa? Both? >> Yeah, so a lot of being a member of the AWS partner network you have a lot of flexibility. You know, we have a lot of customers that are, you know, directly working with AWS. We have a lot of customers that would basically look to us to deliver the solution and, you know, and buy it all as a complete turnkey capability. So we have customers that do both. We have customers that, you know, just look to Lumen for the Lumen adjacent services and then pay, you know, pay a separate bill with AWS. So there's a lot of flexibility in the partner network in terms of what Lumen can deliver as a service, Lumen can deliver as a complete solution and then what parts of its with AWS and their platform factors into on an on-demand usage basis. >> And that would all be determined I imagine by what the customer really needs in their environment? >> Yeah, and sort of their own cloud strategy. There's a lot of customers who are all in on AWS and are really trying to driving and innovating and using some of the higher level services inside the AWS platform. And then there are customers who kind of looked at AWS as one of a few cloud platforms that they want to work with. The Lumen network is compatible and connected to all of them and our services teams are, you know, have the ability to go and let customers sort of take on whatever cloud posture they need. But if they are all in on AWS, there's, you know. Not many networks better to be on than Lumen in order to enable that. >> With that said, last question for you is if you had a bumper sticker or a billboard. Lumen's rebranded since we last saw you. What would that tagline or that phrase of impact be on that bumper sticker? >> Yeah, I'd get in a lot of trouble with our marketing team if I didn't give the actual bumper sticker for the company. But we really think of ourselves as the platform for amazing things. The fourth industrial revolution, everything going on in terms of the future of work, in terms of the future of industrial innovation, in terms of all the data that's being gathered. You know, Adam in the keynote this morning really went into a lot of detail on, you know, the depth of data and the mystery of data and how to harness it all and wrangle it all. It requires a lot of networking and a lot of connectivity. You know, for us to acquire, analyze and act on all that data and Lumen's platform for amazing things really helps forge that path forward to that fourth industrial revolution along with great partners like AWS. >> Outstanding. David, it's been such a pleasure having you back on The Cube. We'll get you fitted for that five timers club jacket. >> It sounds good. (Lisa laughs) >> I'll be back. >> Thanks so much for your insights and your time and well done with what you guys are doing at Lumen and AWS. >> Thanks Lisa. >> For David Shacochis, I'm Lisa Martin. You've been watching The Cube hopefully all day. This is our first full day of coverage at AWS re:Invent '22. Stick around. We'll be back tomorrow, and we know we're going to see you then. Have a great night. (upbeat music)
SUMMARY :
partners, the ecosystem. Lisa, good to be here. You are in the Five Timers Club. We're going to have that for The Cube. 'Cause last time you hear it wasn't Lumen. over the past 10 to 15 years. a lot of the services and takes all of the traffic for Lumen in the last couple of years. because they had to be able to survive. The future of work has changed. This didn't exist. of the different places that, you know, of the main conversations we have the sports metaphor of, you know, about the team and their production truck. gear inside the truck. Wow. of the broadcast and many to be able to, you know, It's nice to hear, to your point, a couple of years ago where But the mindset of experimentation They have the interest. because a lot of the things The future of work as you are and the networks that connect them. of the AWS partner network have the ability to go and be on that bumper sticker? into a lot of detail on, you know, We'll get you fitted for It sounds good. and well done with what you guys are doing and we know we're going to see you then.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
David Shacochis | PERSON | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
Lisa Martin | PERSON | 0.99+ |
CenturyLink | ORGANIZATION | 0.99+ |
David | PERSON | 0.99+ |
Connecticut | LOCATION | 0.99+ |
2020 | DATE | 0.99+ |
Yankees | ORGANIZATION | 0.99+ |
Adam | PERSON | 0.99+ |
2019 | DATE | 0.99+ |
Lumen | ORGANIZATION | 0.99+ |
Quest | ORGANIZATION | 0.99+ |
North Carolina | LOCATION | 0.99+ |
Fox Sports | ORGANIZATION | 0.99+ |
Lisa | PERSON | 0.99+ |
Adam Selipsky | PERSON | 0.99+ |
North America | LOCATION | 0.99+ |
21st century | DATE | 0.99+ |
2023 | DATE | 0.99+ |
Vegas | LOCATION | 0.99+ |
tomorrow | DATE | 0.99+ |
Las Vegas | LOCATION | 0.99+ |
five offices | QUANTITY | 0.99+ |
Both | QUANTITY | 0.99+ |
Cardinals | ORGANIZATION | 0.99+ |
today | DATE | 0.99+ |
United States | LOCATION | 0.99+ |
five milliseconds | QUANTITY | 0.99+ |
first time | QUANTITY | 0.99+ |
both | QUANTITY | 0.99+ |
95% | QUANTITY | 0.98+ |
Sunday night | DATE | 0.98+ |
Major League Baseball | EVENT | 0.98+ |
500 person | QUANTITY | 0.98+ |
three years ago | DATE | 0.98+ |
August | DATE | 0.98+ |
pandemic | EVENT | 0.98+ |
Major League Baseball | ORGANIZATION | 0.98+ |
Lumen | TITLE | 0.97+ |
re:Invent | EVENT | 0.97+ |
SNL | TITLE | 0.97+ |
CEO | PERSON | 0.97+ |
one | QUANTITY | 0.97+ |
Kevin Mandia, Mandiant & Shawn Henry, CrowdStrike | CrowdStrike Fal.Con 2022
>>Welcome back to the aria in Las Vegas, Dave Valante with Dave Nicholson, Falcon 22, the Cube's continuous coverage. Sean Henry is here. He's the president of the services division and he's the chief security officer at CrowdStrike. And he's joined by Kevin mania, CEO of Mandy. Now part of Google Jens. Welcome to the cube. Thank you. Congrats on closing the Google deal. Thank you. That's great. New chapter, >>New >>Chapter coming fresh off the keynote, you and George. I really en enjoyed that. Let's start there. One of the things you talked about was the changes you've been, you've been in this business for a while. I think you were talking about, you know, doing some of these early stuff in the nineties. Wow. Things have changed a lot the queen, right? Right. You used to put the perimeter around the queen. Yeah. Build the Mo the Queen's left or castle new ballgame. But you were talking about the board level knowledge of security in the organization. Talk about that change. That's occurred in the last >>Decade. You know, boards are all about governance, right? Making sure everybody's doing the right things. And they've kind of had a haul pass on cybersecurity for a long time. Like we expect them to be great at financial diligence, they understand the financials of an organization. You're gonna see a maturity, I think in cybersecurity where I think board members all know, Hey, there's risk out there. And we're on our own to kind of defend ourselves from it, but they don't know how to quantify it. And they don't know how to express it. So bottom line boards are interested in cyber and we just have to mature as an industry to give them the tools they need to measure it appropriately. >>Sean, one of the things I wanted to ask you. So Steven Schmidt, I noticed changed his title from CISOs chief inf information security officer, the chief security officer. Your title is chief security officer. Is that a nuance that has meaning to you or is it just less acronym? >>It depends on the organization that you're in, in our organization, the chief security officer owns all risks. So I have a CISO that comes underneath me. Yep. And I've got a security folks that are handling our facilities, our personnel, those sorts of things, all, all of our offices around the globe. So it's all things security. One of the things that we've found and Kevin and I were actually talking about this earlier is this intersection between the physical world and the virtual world. And if you've got adversaries that want gain access to your organization, they might do it remotely by trying to hack into your network. But they also might try to get one of your employees to take an action on their behalf, or they might try to get somebody hired into your company to take some nefarious acts. So from a security perspective, it's about building an envelope around all things valuable and then working it in a collaborative way. So there's a lot of interface, a lot of interaction and a lot of value in putting those things together. And, >>And you're also president of the services division. Is that a P and L role or >>It is, we have a it's P P O P and L. And we have an entire organization that's doing incident response and it's a lot of the work that we're doing with, with Kevin's folks now. So I've got both of those hats today. >>Okay. So self-funded so in a way, okay. Where are companies most at risk today? >>Huh? You wanna go on that one first? Sean, you talk fast than me. So it's bigger bang for the buck. If >>You >>Talk, you know, when I, when I think about, about companies in terms of, of their risk, it's a lot of it has to do with the expansion of the network. Companies are adding new applications, new devices, they're expanding into new areas. There are new technologies that are being developed every day and that are being embraced every day. And all of those technologies, all of those applications, all of that hardware is susceptible to attack. Adversaries are looking for the vulnerabilities they can exploit. And I think just kind of that sprawl is something that is, is disconcerting to me from a security perspective, we need to know where our assets are, where the vulnerabilities lie, how do we plug the holes? And having that visibility is really critical to ensure that you're you're in, involved in mitigating that, that new architecture, >>Anything you >>Did. Yeah. I would like when I, so I can just tell you what I'm hearing from CISOs out there. They're worried about identity, the lateral movement. That's been kind of part of every impactful breach. So in identity's kind of top three of mind, I would say zero trust, whatever that means. And we all have our own definitions of migration to zero trust and supply chain risk. You know, whether they're the supplier, they wanna make sure they can prove to their customers, they have great security practices. Or if they're a consumer of a supply chain, you need to understand who's in their supply chain. What are their dependencies? How secure are they? Those are just three topics that come up all the time. >>As we extend, you know, talking about XDR the X being extend. Do you see physical security as something that's being extended into? Or is it, or is it already kind of readily accepted that physical security goes hand in hand with information security? >>I, I don't think a lot of people think that way there certainly are some and Dave mentions Amazon and Steve Schmidt as a CSO, right? There's a CSO that works for him as well. CJ's clear integration. There's an intelligence component to that. And I think that there are certain organizations that are starting to recognize and understand that when we say there's no real perimeter, it, it expands the network expands into the physical space. And if you're not protecting that, you know, if you don't protect the, the server room and somebody can actually walk in the doors unlocked, you've got a vulnerability that might be exploited. So I think to, to recognize the value of that integration from a security perspective, to be holistic and for organizations to adopt a security first philosophy that all the employees recognize they're, they're the, the first line of defense. Oftentimes not just from a fish, but by somebody catching up with them and handing 'em a thumb drive, Hey, can you take a look at this document? For me, that's a potential vulnerability as well. So those things need to be integrated. >>I thought the most interesting part of the keynote this morning is when George asked you about election security and you immediately went to the election infrastructure. I was like, yeah. Okay. Yeah. But then I was so happy to hear you. You went to the disinformation, I learned something there about your monitoring, the network effects. Sure. And, and actually there's a career stream around that. Right. The reason I had so years ago I interviewed was like, this was 2016, Robert Gates. Okay. Former defense. And I, I said, yeah, but don't we have the best cyber can't we go on the offense. He said, wait a minute, we have the most to lose. Right. But, but you gave an example where you can identify the bots. Like let's say there's disinformation out there. You could actually use bots in a positive way to disseminate the, the truth in theory. Good. Is, is that something that's actually happening >>Out there? Well, I think we're all still learning. You know, you can have deep fakes, both audible files or visual files, right. And images. And there's no question. The next generation, you do have to professionalize the news that you consume. And we're probably gonna have to professionalize the other side critical thinking because we are a marketplace of ideas in an open society. And it's hard to tell where's the line between someone's opinion and intentional deception, you know, and sometimes it could be the source, a foreign threat, trying to influence the hearts and minds of citizens, but there's gonna be an internal threat or domestic threat as well to people that have certain ideas and concepts that they're zealots about. >>Is it enough to, is it enough to simply expose where the information is coming from? Because, you know, look, I, I could make the case that the red Sox, right. Or a horrible baseball team, and you should never go to Fenway >>And your Yankees Jersey. >>Right. Right. So is that disinformation, is that misinformation? He'd say yes. Someone else would say no, but it would be good to know that a thousand bots from some troll farm, right. Are behind us. >>There's, it's helpful to know if something can be tied to identity or is totally anonymous. Start just there. Yeah. Yeah. You can still protect the identity over time. I think all of us, if you're gonna trust the source, you actually know the source. Right. So I do believe, and, and by the way, much longer conversation about anonymity versus privacy and then trust, right. And all three, you could spend this whole interview on, but we have to have a trustworthy internet as well. And that's not just in the tech and the security of it, but over time it could very well be how we're being manipulated as citizens and people. >>When you guys talk to customers and, and peers, when somebody gets breached, what's the number one thing that you hear that they wished they'd done that they didn't. >>I think we talked about this earlier, and I think identity is something that we're talking about here. How are you, how are you protecting your assets? How do you know who's authorized to have access? How do you contain the, the access that they have? And the, the area we see with, with these malware free attacks, where adversaries are using the existing capabilities, the operating system to move laterally through the network. I mean, Kevin's folks, my folks, when we respond to an incident, it's about looking at that lateral movement to try and get a full understanding of where the adversary's been, where they're going, what they're doing, and to try to, to find a root cause analysis. And it really is a, a critical part. >>So part of the reason I was asking you about, was it a P and L cuz you, you wear two hats, right? You've got revenue generation on one side and then you've got you protect, you know, the company and you've got peer relationships. So the reason I bring this up is I felt like when stucks net occurred, there was a lot of lip service around, Hey, we, as an industry are gonna work together. And then what you saw was a lot of attempts to monetize, you know, private data, sell private reports and things of that nature you were referencing today, Kevin, that you think the industry's doing a much better job of, of collaboration. Is it, can you talk about that and maybe give some examples? >>Absolutely. I mean, you know, I lived through it as a victim of a breach couple years ago. If you see something new and novel, I, I just can't imagine you getting away with keeping it a secret. I mean, I would even go, what are you doing? Harboring that if you have it, that doesn't mean you tell the whole world, you don't come on your show and say, Hey, we got something new novel, everybody panic, you start contacting the people that are most germane to fixing the problem before you tell the world. So if I see something that's new in novel, certainly con Sean and the team at CrowdStrike saying, Hey, there's because they protect so many endpoints and they defend nations and you gotta get to Microsoft. You have to talk to pan. You have to get to the companies that have a large capability to do shields up. And I think you do that immediately. You can't sit on new and novel. You get to the vendor where the vulnerability is, all these things have to happen at a great rate to speak. >>So you guys probably won't comment, but I'm betting dollars to donuts. This Uber lapses hack you guys knew about. >>I turned to you. >>No comment. I'm guessing. I'm guessing that the, that wasn't novel. My point being, let me, let me ask it in a more generic fashion that you can maybe comment you you're. I think you're my, my inference is we're com the industry is compressing the time between a zero day and a fix. Absolutely. Absolutely. Like dramatically. >>Yes. Oh, awareness of it and AIX. Yes. Yeah. >>Okay. Yeah. And a lot of the hacks that we see as lay people in the media you've known about for quite some time, is that fair or no, not necessarily. >>It's, you know, it's harder to handle an intrusion quietly and discreetly these days, especially with what you're up against and, and most CEOs, by the way, their intent isn't, let's handle it quietly and discreetly it's what do we do about it? And what's the right way to handle it. And they wanna inform their customers and they wanna inform people that might be impacted. I wouldn't say we know it all that far ahead of time >>And, and depends. And, and I, I think companies don't know it. Yeah. Companies don't know they've been breached for weeks or months or years in some cases. Right. Which talks about a couple things, first of all, some of the sophistication of the adversaries, but it also talks about the inability of companies to often detect this type of activity when we're brought in. It's typically very quickly after the company finds out because they recognize they've gotta take action. They've got liability, they've got brand protection. There, whole sorts of, of things they need to take care of. And we're brought in it may or may not be, become public, but >>CrowdStrike was founded on the premise that the unstoppable breach is a myth. Now that's a, that's a bold sort of vision. We're not there yet, obviously. And a and a, and a, a CSO can't, you know, accept that. Right. You've gotta always be vigilant, but is that something that is, that we're gonna actually see manifest, you know, in any, any time in the near term? I mean, thinking about the Falcon platform, you guys are users of that. I don't know if that is part of the answer, but part of it's technology, but without the cultural aspects, the people side of things, you're never gonna get there. >>I can tell you, I started Maning in 2004 at the premise security breaches are inevitable, far less marketable. Yeah. You know, stop breaches. >>So >>Yeah. I, I think you have to learn how to manage this, right? It's like healthcare, you're not gonna stop every disease, but there's a lot of things that you can do to mitigate the consequences of those things. The same thing with network security, there's a lot of actions that organizations can take to help protect them in a way that allows them to live and, and operate in a, in a, a strong position. If companies are lackadaisical that irresponsible, they don't care. Those are companies that are gonna suffer. But I think you can manage this if you're using the right technology, the right people, you've got the right philosophy security first >>In, in the culture. >>Well, I can tell you very quickly, three reasons why people think, why is there an intrusion? It should just go away. Well, wherever money goes, crime follows. We still have crime. So you're still gonna have intrusions, whether it has to be someone on the inside or faulty software and people being paid the right faulty software, you're gonna have war. That's gonna create war in the cyber domain. So information warriors are gonna try to have intrusions to get to command and control. So wherever you have command and control, you'll have a war fighter. And then wherever you have information, you have ESP Espino. So you're gonna have people trying to break in at all times. >>And, and to tie that up because everything Kevin said is absolutely right. And what he just said at the very end was people, there are human beings that are on the other side of every single attack. And think about this until you physically get physically get to the people that are doing it and stop them. Yes, this will go on forever because you can block them, but they're gonna move and you can block them again. They're gonna move their objectives. Don't change because the information you have, whether it's financial information, intellectual property, strategic military information, that's still there. They will always come at it, which is where that physical component comes in. If you're able to block well enough and they can't get you remotely, they might send somebody in. Well, >>I, in the keynote, I, I'm not kidding. I'm looking around the room and I'm thinking there's at least one person here that is here primarily to gather intelligence, to help them defeat. What's being talked about here. >>Well, you said it's, >>It's kind >>Of creepy. You said the adversary is, is very well equipped and motivated. Why do you Rob banks? Well, that's where the money is, but it's more than that. Now with state sponsored terrorism and, you know, exfiltration of state secrets, I mean, there's, it's high stake's games. You got, this >>Has become a tool of nation states in terms from a political perspective, from a military perspective, if you look at what happened with Ukraine and Russia, all the work that was done in advanced by the Russians to soften up the Ukrainians, not just collection of intelligence, not just denial of services, but then disruptive attacks to change the entire complexity of the battlefield. This, this is a, an area that's never going away. It's becoming ingrained in our lives. And it's gonna be utilized for nefarious acts for many, many decades to come. >>I mean, you're right, Sean, we're seeing the future of war right before us is, is there's. There is going to be, there is a cyber component now in war, >>I think it signals the cyber component signals the silent intention of nations period, the silent projection of power probably before you see kinetics. >>And this is where gates says we have a lot more to lose as a country. So it's hard for us to go on the offense. We have to be very careful about our offensive capabilities because >>Of one of the things that, that we do need to, to do though, is we need to define what the red lines are to adversaries. Because when you talk about human beings, you've gotta put a deterrent in place so that if the adversaries know that if you cross this line, this is what the response is going to be. It's the way things were done during nuclear proliferation, right? Right. During the cold war, here's what the actions are gonna be. It's gonna be, it's gonna be mutual destruction and you can't do it. And we didn't have a nuclear war. We're at a point now where adversaries are pushing the envelope constantly, where they're turning off the lights in certain countries where they're taking actions that are, are quite detrimental to the host governments and those red lines have to be very clear, very clearly defined and acted upon if they're >>Crossed as security experts. Can you always tie that signature back to say a particular country or a particular group? >>Absolutely. 100% every >>Time I know. Yeah. No, it it's. It's a great question. You, you need to get attribution right. To get to deterrence, right. And without attribution, where do you proportionate respond to whatever act you're responding to? So attribution's critical. Both our companies work hard at doing it and it, and that's why I think you're not gonna see too many false flag operations in cyberspace, but when you do and they're well crafted or one nation masquerades is another, it, it, it's one of the last rules of the playground I haven't seen broken yet. And that that'll be an unfortunate day. >>Yeah. Because that mutually assure destruction, a death spot like Putin can say, well, it wasn't wasn't me. Right. So, and ironically, >>It's human intelligence, right. That ultimately is gonna be the only way to uncover >>That human intelligence is a big component. >>For sure. Right. And, and David, like when you go back to, you were referring to Robert Gates, it's the asymmetry of cyberspace, right? One person in one nation. That's not a control by asset could still do an act. And it, it just adds to the complexity of, we have attribution it's from that nation, but was it in order? Was it done on behalf of that nation? Very complicated. >>So this is an industry of superheroes. Thank you guys for all you do and appreciate you coming on the cube. Wow. >>I love your Cape. >>Thank all right. Keep it right there. Dave Nicholson and Dave ante be right back from Falcon 22 from the area you watching the cue.
SUMMARY :
He's the president of the services division and he's One of the things you talked about was the changes you've been, you've been in this business for a while. Making sure everybody's doing the right things. meaning to you or is it just less acronym? One of the things that we've found and Kevin and I were actually talking about this earlier is And you're also president of the services division. an entire organization that's doing incident response and it's a lot of the work that we're Where are companies most at risk today? So it's bigger bang for the buck. all of that hardware is susceptible to attack. Or if they're a consumer of a supply chain, you need to understand who's in their supply chain. As we extend, you know, talking about XDR the X being extend. And I think that there are certain organizations that are starting to recognize I thought the most interesting part of the keynote this morning is when George asked you about election the news that you consume. and you should never go to Fenway So is that disinformation, is that misinformation? And all three, you could spend this whole interview on, but we have to have a trustworthy internet as well. When you guys talk to customers and, and peers, when somebody gets breached, it's about looking at that lateral movement to try and get a full understanding of where the adversary's So part of the reason I was asking you about, was it a P and L cuz you, you wear two hats, And I think you do that immediately. So you guys probably won't comment, but I'm betting dollars to donuts. let me, let me ask it in a more generic fashion that you can maybe comment you you're. Yeah. you've known about for quite some time, is that fair or no, not necessarily. It's, you know, it's harder to handle an intrusion quietly and discreetly these days, but it also talks about the inability of companies to often detect this type of activity when And a and a, and a, a CSO can't, you know, accept that. I can tell you, I started Maning in 2004 at the premise security breaches are inevitable, But I think you can manage this if you're using the right technology, And then wherever you have information, And think about this until you physically get physically get to the people that are doing it at least one person here that is here primarily to gather intelligence, you know, exfiltration of state secrets, I mean, there's, it's high stake's games. from a military perspective, if you look at what happened with Ukraine and Russia, all the work that I mean, you're right, Sean, we're seeing the future of war right before us is, is there's. the silent projection of power probably before you see kinetics. And this is where gates says we have a lot more to lose as a country. that if the adversaries know that if you cross this line, this is what the response is going to be. Can you always tie that signature back to say a Absolutely. where do you proportionate respond to whatever act you're responding to? So, and ironically, It's human intelligence, right. And, and David, like when you go back to, you were referring to Robert Gates, it's the asymmetry of cyberspace, Thank you guys for all you do and appreciate you coming on the cube. Dave Nicholson and Dave ante be right back from Falcon 22 from the area you watching the cue.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
David | PERSON | 0.99+ |
Kevin | PERSON | 0.99+ |
Sean Henry | PERSON | 0.99+ |
Steven Schmidt | PERSON | 0.99+ |
Putin | PERSON | 0.99+ |
George | PERSON | 0.99+ |
Dave | PERSON | 0.99+ |
Dave Nicholson | PERSON | 0.99+ |
Sean | PERSON | 0.99+ |
Dave Valante | PERSON | 0.99+ |
2004 | DATE | 0.99+ |
Steve Schmidt | PERSON | 0.99+ |
Robert Gates | PERSON | 0.99+ |
2016 | DATE | 0.99+ |
100% | QUANTITY | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Las Vegas | LOCATION | 0.99+ |
CrowdStrike | ORGANIZATION | 0.99+ |
Microsoft | ORGANIZATION | 0.99+ |
Kevin Mandia | PERSON | 0.99+ |
both | QUANTITY | 0.99+ |
red Sox | ORGANIZATION | 0.99+ |
Both | QUANTITY | 0.99+ |
Shawn Henry | PERSON | 0.99+ |
ORGANIZATION | 0.99+ | |
Kevin mania | PERSON | 0.99+ |
zero day | QUANTITY | 0.99+ |
Uber | ORGANIZATION | 0.99+ |
One | QUANTITY | 0.99+ |
One person | QUANTITY | 0.99+ |
zero trust | QUANTITY | 0.99+ |
Yankees Jersey | ORGANIZATION | 0.99+ |
three topics | QUANTITY | 0.98+ |
one | QUANTITY | 0.98+ |
three reasons | QUANTITY | 0.98+ |
one side | QUANTITY | 0.98+ |
Ukrainians | PERSON | 0.98+ |
one nation | QUANTITY | 0.98+ |
CJ | PERSON | 0.97+ |
today | DATE | 0.97+ |
couple years ago | DATE | 0.97+ |
three | QUANTITY | 0.97+ |
first line | QUANTITY | 0.96+ |
Falcon 22 | ORGANIZATION | 0.96+ |
Russians | PERSON | 0.95+ |
Mandy | ORGANIZATION | 0.93+ |
two hats | QUANTITY | 0.92+ |
CrowdStrike | EVENT | 0.91+ |
AIX | ORGANIZATION | 0.9+ |
Russia | ORGANIZATION | 0.9+ |
Mandiant | PERSON | 0.9+ |
this morning | DATE | 0.86+ |
first philosophy | QUANTITY | 0.86+ |
first | QUANTITY | 0.85+ |
Ukraine | ORGANIZATION | 0.83+ |
single attack | QUANTITY | 0.8+ |
years ago | DATE | 0.79+ |
Falcon | ORGANIZATION | 0.77+ |
nineties | DATE | 0.77+ |
a thousand bots | QUANTITY | 0.77+ |
at least one person | QUANTITY | 0.76+ |
Fal.Con 2022 | EVENT | 0.7+ |
ESP Espino | ORGANIZATION | 0.69+ |
CEO | PERSON | 0.68+ |
Google Jens | ORGANIZATION | 0.67+ |
cold | EVENT | 0.67+ |
couple | QUANTITY | 0.53+ |
every | QUANTITY | 0.52+ |
Fenway | LOCATION | 0.52+ |
Queen | PERSON | 0.5+ |
Maning | ORGANIZATION | 0.39+ |
Rob | PERSON | 0.36+ |
Raj Rajkotia, LootMogul | Monaco Crypto Summit 2022
>>Hello, welcome back to the cubes coverage of Monaco, crypto summit presented by digital bits. It's a conference where a lot of the people using digital bits and the industry coming together around the future of crypto in the applicates got a great guest garage, rod cot, founder, and CEO of an innovative company. Love this co I love this company, Luke mogul, Rob, thanks for coming on the queue. Appreciate it. Oh, >>Thank you for having >>Us. Yeah. So I checked out what you guys are doing. You've got the sports metaverse angle going on with super valuable, cuz sports is super entertaining. Uh, people are engaged. There's huge fan base, huge online now, digital convergence going on with the physical, you know, you see all kinds of sports betting going on now everything's going digital. There's a whole nother consumer experience going on with sports and the game is still the same on the, on the field or so to, or the court. That's correct. Yeah. Now it's going to digital take a minute to explain what you guys are working on. >>Yeah, so yes, we are building out a sports ERs where we are bringing athletes, whether they're NBA stars, NFL stars, w N B a many of those athletes into meows giving them the ownership of the entire, um, meows commerce along with gameplay. So that's something from our perspective, this, uh, this is something that we're focused on. We're building out stadiums. Athletes can own stadiums. Athlete can create their own training centers, media hubs. Um, and imagine Lisa, Leslie for example, is building out a woman leadership sports academy, right? We have Michael Cooper building out defensive academy. So those are all the brands. We have 174 NBA w N B stars. And, um, and we are building out this, >>The brand is the brand, is the platform that's correct. That's the trend we're seeing. And it's, it's also an extension of their reach in community. So there's, they can convert their star power and athlete with owner's approval. If they probably write it on to the contracts, he, they can imagine all the complications, but they bring that online and extend that energy and brand equity yep. To fans and social network. Yeah. >>And many of these athletes are tremendous successful in their web two careers, right? Yeah. Um, some are current athletes, some are former athletes, but they have built such a brand persona where people are following them on Instagram. For example, Carlos Boozer. He has like almost 6 million followers between Twitter and Instagram and those kind of brands are looking or how do I give back to the community? How do I engage with my community and web three? And especially with our platform, we are giving that power back to the players. >>So you guys got some big names booers on there. You mentioned Carlos Boozer. You mentioned that Lisa, Leslie others among others, Michael Cooper throw back to the old Lakers, uh, magic. Johnson's kind actually here in crypto. We just saw him in the lobbies and in dinner and the other night, um, at Nobu, um, you got a lot of NBA support. Take a take, take, even explain how you're working this angle. Uh, you got some great traction, uh, momentum. Um, you got great pedigree, riot games in your career. Uh, you kind of get the world, the tech world, the media world, as it comes together. What's the secret sauce here? Is it the NBA relationship combination of the team explained >>It's really focusing on what, uh, we are building on me was focusing on players first, right? So players are literally, we call our platform as, uh, owned by the players, made for the players. Uh, and engagement is really all done through the players, right? So that's our key sauce. And when we worked out with NBA, we, we are part of the NBA BPA acceleration program for 2022 that is funded by a six Z, uh, and, and many others. Um, and our partnership with league is very critical. So it's not only partnered with player association partnered with leagues, whether it's NBA, w N B a NFL. So those are the venues. And this becomes almost a program, especially for athletes to really generate this lifetime engagement and royalty model because some of this famous athletes really want to give back to the communities. So like for example, I use Lisa Leslie a lot, but Lisa, Leslie really wants to empower women leadership, leadership, and really help, um, women in sports, for example. Right? So those are the angles that, um, that really people are excited about. >>Well, for the people watching that might not understand some of the ins and outs of sports and, and rod, your background in your team, it's interesting. The sports teams have been on the big day to train for many, many years. You look at all the stadiums. Now they've got mobile devices, they got wifi under the chairs. They use data and technology to manage the team. Mm-hmm, <affirmative> manage the stadium and venue and operations suppliers, whatnot. And then also the fans. So you, they, they got about a decade or so experience already in the digital world. This is not new to the, to the sports world. Yeah. So you guys come to the table kind of at a good time. >>Yeah. Especially the defi of the sports, right? So there's a defi of the finance, but this is the really, uh, a, a decentralization of the sports is something that there's a lot of traction. And there are many companies that are really focusing on that. Our focus obviously is players first, right? How do we give power to the players? Uh, and those are really driving the entire engagement. And also the brands >>How's the NBA feel about this because, you know, you got the NBA and you get the team, you got the owners. I mean, the democratization of the players, which I love by the way that angle kind of brings their power. Now's the new kind of balance of power. How is the NBA handling this? What's some of the conversations you've had with the, the organization. >>Yeah. So obviously there are a lot of things that, uh, people have to be careful about, right? They have existing contracts, existing, digital media rights. Um, so that's something that, uh, we have to be very tactful when we are working with NBA and NPA, uh, on what we can say, we cannot say. So that is obviously they have a lot of existing multimillion or billion dollar contracts that they cannot void with the web because the evolution of web three, >>You know, I love, uh, riffing on the notion of contract compliance when there's major structural change happening. Remember back in baseball, back in the days before the internet, the franchise rights was geographic territory. Mm-hmm <affirmative> well, if you're the New York Yankees, you're doing great. If you're Milwaukee, you're not doing too good, but then comes the internet. That's good. That's no geography. There's no boundaries. That's good. So you're gonna have stadiums have virtual Bo. So again, how do they keep up with the contracts? Yeah. I mean, this is gonna be a fundamental issue. >>That's >>Good. Good. And I think if they don't move, the players are gonna fill that void. >>That's correct. Yeah. And especially with this, this an IL deal, right. That happened for the players, uh, especially college athletes. So we are in process of onboarding 1.5 million college athletes. Uh, and those athletes are looking for not only paying for the tuition for the colleges, but also for engagement and generating this early on, uh, >>More okay. Rod, we're gonna make a prediction here in the cube, 20, 20 we're in Monaco, all the NBA, NHL, the teams they're gonna be run by player Dows. Yeah. What do you think? A very good prediction. Yeah. Very good prediction. Yeah. I mean you, I mean, that's a joke, I'm joking aside. I mean, it's kind of connecting the dots, but you know, whether that happens or not, what this means is if this continues to go down this road, that's correct. Get the players collectively could come together. Yeah. And flip the script. >>Yeah. And that's the entire decentralization, right. So it's like the web three has really disrupted this industry as you know. Um, and, and I know your community knows that too. >>Of course, course we do. We love it. >>Something from sports perspective, we are very excited. >>Well, I love it. Love talking. Let's get to the, to the weeds here on the product, under the hood, tell about the roadmap, obviously NFTs are involved. That's kind of sexy right now. I get the digital asset model on there. Uh, but there's a lot more under the coverage. You gotta have a platform, you gotta have the big data and then ultimately align into connecting other systems together. How do you view the tech roadmap and the product roadmap? What's your vision? >>Yeah. So the, the one thing that you had to be T full, uh, as a company, whether it's LUT, mogul or any other startup, is you have to be really part of the ecosystem. So the reason why we are here at Monaco is that we obviously are looking at partnership with digital bits, um, and those kind of partnership, whether it's fourth centric, centric are very critical for the ecosystem in the community to grow. Um, and that's one thing you cannot build a, another, uh, isolated metaverse right? So that's one thing. Many companies have done it, but obviously not. >>It's a wall garden doesn't work. >>Exactly. So you have to be more open platform. So one things that we did early on in our platform, we have open APIs and SDKs where not only you as an athlete can bring in your, uh, other eCommerce or web, uh, NFTs or anything you want, but you can also bring in other real estate properties. So when we are building out this metaverse, you start with real estate, then you build out obviously stadiums and arenas and academies training academies, but then athletes can bring their, uh, web commerce, right. Where it's NFT wearables shoe line. So >>Not an ecosystem on top of Luke Mo. So you're like, I'm almost like you think about a platform as a service and a cloud computing paradigm. Yeah. Look different, not decentralized, but similarly enabling others, do the heavy lifting on their behalf. Yeah. Is that right? >>So that's correct. Yes. So we are calling ourself as the sports platform as a service, right. So we want to add the word sports because we, uh, in, in many contexts, right. When you're building metaverse, you can get distracted with them, especially we are in Los Angeles. Right. >>Can I get a luxury box for the cube and some of the metaverse islands and the stadiums you're doing? >>We, we are working >>On it. We're >>Definitely working on, especially the, uh, Los Angeles, uh, stadium. Yeah. >>Well, we're looking for some hosts, anyone out there looking for some hosts, uh, for the metaverse bring your avatar. You can host the cube, bro. Thanks for coming on the cube. Really appreciate. What's the, what's next for you guys, obviously, continuing to build momentum. You got your playful, how many people on the team what's going on, give a plug for the company. What are you looking for share with the audience, some of the, some of your goals. Yeah. >>So, uh, the main thing we're looking for is really, um, from a brand perspective, if you are looking at buying properties, this would be an amazing time to buy virtual sports stadium. Um, so we are, obviously we have 175 stadiums in roadmap right now. We started with Los Angeles. Then we are in San Francisco, New York, Qatar, Dubai. So all those sports stadiums, whether they're basketball, football, soccer are all the properties. And, uh, from a community perspective, if you want to get an early access, we are all about giving back to the community. Uh, so you can buy it at a much better presale price right now. Uh, so that's one, the second thing is that if you have any innovative ideas or a player that you want to integrate into, we have an very open platform from a community engagement perspective. If you have something unique from a land sale perspective yeah. Or the NFD perspective plug, contact us at, at Raj lumo.com. >>And I'm assuming virtual team, you in LA area where where's your home. >>So, yeah, so I live in Malibu, um, and our office is in Santa Monica. We have an office in India. Uh, we have few developers also in Europe. So, uh, and then we are team of 34 people right now >>Looking to hire some folks >>We are looking for, what >>Are you, what are you looking for? >>So, uh, we are looking for a passionate sports, uh, fanatics. >>It's a lot, not hard to find. Yeah. >><laugh> who knows how to also code. Right? So from blockchain perspective, we are, uh, chain agnostic. Uh, but obviously right now we are building on polygon, but we are chain agnostic. So if you have any blockchain development experience, uh, that's something we, we are looking for. Yeah. >>RA, thanks for coming out. Luke Mo check him out. I'm John furry with the cube here in Monaco for the mono crypto summit presented by digital bits. We got all the action, a lot of great guests going on, stay with us for more coverage. Um, John furrier, thanks for watching.
SUMMARY :
It's a conference where a lot of the people using digital bits and the industry coming together around the future of crypto in the applicates Now it's going to digital take a minute to explain what you guys are working on. So that's something from our perspective, this, uh, this is something that we're focused on. The brand is the brand, is the platform that's correct. we are giving that power back to the players. So you guys got some big names booers on there. So players are literally, we call our platform as, uh, So you guys come to the And also the brands How's the NBA feel about this because, you know, you got the NBA and you get the team, you got the owners. Um, so that's something that, uh, we have to be very tactful when we are So again, how do they keep up with the contracts? So we are in process of onboarding 1.5 million college athletes. I mean, it's kind of connecting the dots, but you know, whether that happens or not, what this means is if So it's like the web three has really Of course, course we do. I get the digital asset model on there. So the reason why we are So you have to be more open platform. do the heavy lifting on their behalf. So we want to add the word sports because we, uh, in, in many contexts, On it. Yeah. You can host the cube, bro. Uh, so that's one, the second thing is that if you have any innovative ideas or a player that you want to integrate into, So, uh, and then we are team of It's a lot, not hard to find. So if you have any blockchain development experience, uh, that's something we, We got all the action, a lot of great guests going on, stay with us for more coverage.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Michael Cooper | PERSON | 0.99+ |
Europe | LOCATION | 0.99+ |
Leslie | PERSON | 0.99+ |
Carlos Boozer | PERSON | 0.99+ |
Malibu | LOCATION | 0.99+ |
Lisa | PERSON | 0.99+ |
Rob | PERSON | 0.99+ |
San Francisco | LOCATION | 0.99+ |
Santa Monica | LOCATION | 0.99+ |
India | LOCATION | 0.99+ |
Raj Rajkotia | PERSON | 0.99+ |
NBA | ORGANIZATION | 0.99+ |
New York Yankees | ORGANIZATION | 0.99+ |
Lisa Leslie | PERSON | 0.99+ |
174 | QUANTITY | 0.99+ |
Luke Mo | PERSON | 0.99+ |
LA | LOCATION | 0.99+ |
NPA | ORGANIZATION | 0.99+ |
Dubai | LOCATION | 0.99+ |
Los Angeles | LOCATION | 0.99+ |
Rod | PERSON | 0.99+ |
Qatar | LOCATION | 0.99+ |
Monaco | LOCATION | 0.99+ |
Johnson | PERSON | 0.99+ |
175 stadiums | QUANTITY | 0.99+ |
New York | LOCATION | 0.99+ |
Lakers | ORGANIZATION | 0.99+ |
LootMogul | PERSON | 0.99+ |
34 people | QUANTITY | 0.98+ |
Nobu | LOCATION | 0.98+ |
20 | QUANTITY | 0.97+ |
two careers | QUANTITY | 0.97+ |
billion dollar | QUANTITY | 0.97+ |
Luke mogul | PERSON | 0.96+ |
Monaco Crypto Summit 2022 | EVENT | 0.96+ |
second thing | QUANTITY | 0.96+ |
ORGANIZATION | 0.95+ | |
one thing | QUANTITY | 0.94+ |
Milwaukee | LOCATION | 0.94+ |
2022 | DATE | 0.94+ |
John furry | PERSON | 0.94+ |
first | QUANTITY | 0.94+ |
metaverse | ORGANIZATION | 0.93+ |
almost 6 million followers | QUANTITY | 0.92+ |
Dows | PERSON | 0.92+ |
baseball | TITLE | 0.92+ |
Raj lumo.com | OTHER | 0.91+ |
about a decade | QUANTITY | 0.91+ |
NFT | ORGANIZATION | 0.91+ |
ORGANIZATION | 0.9+ | |
John furrier | PERSON | 0.9+ |
multimillion | QUANTITY | 0.88+ |
mono crypto summit | EVENT | 0.87+ |
1.5 million college athletes | QUANTITY | 0.85+ |
one | QUANTITY | 0.85+ |
one things | QUANTITY | 0.78+ |
three | QUANTITY | 0.73+ |
NBA | EVENT | 0.73+ |
crypto | EVENT | 0.7+ |
fourth centric | QUANTITY | 0.67+ |
RA | PERSON | 0.67+ |
IL | LOCATION | 0.66+ |
NFL | EVENT | 0.64+ |
LUT | ORGANIZATION | 0.61+ |
N B | TITLE | 0.59+ |
NHL | ORGANIZATION | 0.58+ |
Monaco | EVENT | 0.55+ |
TITLE | 0.54+ | |
six | QUANTITY | 0.53+ |
N B | EVENT | 0.51+ |
BPA acceleration program | TITLE | 0.4+ |
Peter McKay, Snyk & Adi Sharabani, Snyk | AWS re:Inforce 2022
>>Okay. We're back in Boston covering AWS reinvent 2022. This is our second live reinvent. We've done the other ones, uh, in between as digital. Uh, my name is Dave Lanta and you're watching the cube. Peter McKay is here. He's the CEO of sneaking ad Shani is the chief technical officer guys. Great to see you again. Awesome. Being here in Boston >>In July. It is Peter. You can't be weather's good weather. Yeah, red SOS. Aren't good. But everything else >>Is SOS are ruin in our sub, you know, >>Hey, they're still in the playoff, the hunt, you >>Know, all you gotta do is make it in. Yes. >>Right. And there's a new season. Simple >>Kinda like hockey, but you know, I'm worried they're gonna be selling at the trading >>Deadline. Yeah. I think they should be. I think it's you think so it's not looking good. Oh, >>You usually have a good angle on this stuff, but uh, well, Hey, we'll see. We'll go. I got a lot of tickets. We'll go and see the Yankees at least we'll see a winning team. Anyway, we last talked, uh, after your fundraising. Yeah. You know, big, big round at your event last night, a lot of buzz, one of the largest, I think the largest event I saw around here, a lot of good customers there. >>It's great. Great time. >>So what's new. Give us the update. You guys have made some, an acquisition since then. Integration. We're gonna talk >>About that. Yeah. It's been, uh, a lot has happened. So, uh, the business itself has done extremely well. We've been growing at 170% year, over year, a hundred percent growth in our number of customers added. We've done six acquisitions. So now we have, uh, five products that we've added to the mix. We've tripled the size of the company. Now we're 1300 people, uh, in the organization. So quite a bit in a very short period of time. >>Well, and of course my, in my intro, I, I said, reinvent, I'm getting ahead of myself. Right. >>Of course we'll >>Reinforced. We'll be at reinve >>In November. Are that's the next one at >>Reinforced. We've done a lot of reinvents by the way, you know? >>So there's a lot, lot of reinvention >>Here. So of course, well, you're reinventing security, right? Yes. So, you know, I try to, I think about when I go to these events, like, what's the takeaway, what's the epiphany. And we're really seeing the, the developer security momentum, and it's a challenge. They gotta worry about containers. They gotta worry about run time. They gotta worry about platform. Yeah. You guys are attacking that problem. Maybe describe that a >>Little bit for us. Yeah. I mean, for years it was always, um, you know, after the fact production fixing security in run time and billions and billions of dollars spent in fixing after the fact. Right. And so the realization early on with the was, you know, you gotta fix these issues earlier and earlier, we started with open source was the first product at wait. Then six, six years ago, then we added container security and we added infrastructure's code. We added code security. We added, um, most recently cloud security with the F acquisition. So one platform, one view that a developer can look at to fix all the issues through the, be from the beginning, all the way through the software development life cycle. So we call it developer security. So allowing developers to develop fast, but stay secure at the same time. >>So I like the fact that you're using some of your capital to do acquisitions. Yeah. Now a lot of M and a is, okay, we're gonna buy this company. We're gonna leave them alone. You guys chose to integrate them. Maybe describe what that process was like. Yeah. Why you chose that. Yeah. How hard it was, how long it took. Take us through that. >>Yeah. Yeah. I'll give, uh, two examples, maybe one on sneak, which was an acquisition of, of the company that was focused on, uh, code analysis, actually not for security. And we have identified the merit of what we need in terms of the first security solution, not an ability to take a security product and put it in the end of developer, but rather build something that will build into the dev motion, which means very fast, very accurate things that it can rely on source and not just on the build code and so on. And we have built that into the platform and by that our customers can gain all of their code related issues together with all of their ISE related issues together with all of the container issues in one platform that they can prioritize accordingly. >>Yeah. Okay. So, so talk more about the, the, the call, the few, the sneak cloud, right? Yeah. So the few name goes away. I presume, right. Or yes, it does. Okay. So you retire that and bring it in the brand is sneak. Yeah. Right. So talk about the cloud, what it does, what problems >>It's solving. Yeah. Awesome. And, and this goes exactly the same. As we mentioned on, on the code, we have looked at the, the, the cloud security solutions for a while now. And what we loved about the few team is that they were building their product with their first approach. Okay. So the notion is as followed as you are, you know, you're a CSO, you have your pro you have your program, you're looking, you have different types of controls and capabilities. And your team is constantly looking for threats. When we are monitoring your cloud environment, we can detect problems like, you know, your FL bucket is not exposing the right permissions and is exposed to the world or things like that. But from a security perspective, it might be okay to stop there. But if you're looking at an operation perspective, you need to know who needs to fix, how do they need to fix it? >>Where do they need to fix it? What will the be the impact if they would fix it? So what do we actually doing is we are connecting all the dots of the platform. So on one end, you know, the actual resources that are running and what's the implication in the actual deployed environment. On the other end, we get correlation back to the actual code that generates that. And then I can give that context both to the security person, the context of how it affects the application. But more importantly, the context for the developer is required to fix the problem. What's the context of the cloud. Yeah. And a lot of things are being exposed this way. And we can talk about that. Uh, >>So this is really interesting because, and look, I love AWS to do an amazing job. One of the other things I really like about 'em is it seems like they're not trying to go hard and monetize their security products. Mm-hmm, they're leaving that to the ecosystem, which I like. Yeah. Microsoft taken a little different approach, right? Yeah, yeah, yeah. Ton a lot. But this, this, this example you're giving ad about the S3 bucket. So we heard in the keynotes yesterday about, you know, reasoning, AI reasoning, they said, we can say, is this S3 bucket exposed to the public? We can do that with math. Right. Yeah. But you're what I'm inferring is you don't stop there. Yeah. Yeah. There's a lot of other stuff that has to, >>And sometimes have to, not as simple, just as a configuration change, sometimes the correlation between what your application is doing affects what is the resulted experience of, you know, the remote user or in this case, the attacker, right. I mean, >>The application has access, who has access to the application, is this, this the chain. >>So propagates, you have to, you have to have a, a solution that looks both at have very good understanding of the application context. A very good understanding of what we refer to as the application graph, like understanding how it works, being able to analyze that and apply the same policies, both at development time, as well as run time. >>So there's, there's human to app. There's also a machine to machine. Can you guys help with that problem as well? Or is that sort of a futures thing or >>Could you, I'm not sure. I understand what >>Referring, so machines talking to machines, right. I mean, there's data flowing. Yep. You know, between those machines, right. It's not just the humans interacting with the application. Is that a trend that you see and is that something that you guys can solve? >>So at, at the end of the day, there is a lot of automation that happens both for, by humans for good reasons, as well as by humans for bads. Right. <laugh> and, and the notion is that we are really trying to focus on what matters to the developer as they're trying to improve their business around that. So both improves making sure they know, you know, quality problems or things of this kind. But as part of that, more importantly, when we're looking at security as a quality problem, making sure that we have a flow in the development life cycle that streamline what the developer is expecting to do as they're building the solution. And if every single point, whether it's the ID, whether it's the change management, whether it's the actual build, whether it's the deployed instance on the cloud, making sure that we identify with that and connect that back to the code. >>Okay. So if there's machine automation coming in, that shouldn't be there, you can sort of identify that and then notify remediate or whatever action should be >>Taken. Yeah. Identify, identify remediate. Yep. >>Yeah. We, we really focus on making sure that we help developers build better products. So our core focus is identify areas where the product is not built way in a good way, and then suggest the corrective action that is required to make that happen. >>And I think part of this is the, you know, just, uh, the speed of the software development today. I mean, you look at developers are constantly and not just look at sneak you're, you're trying to get so much more productivity outta the developers that you have. Every company is trying to get more productivity out of developers, incredible innovation, incredible pace, get those is a competitive advantage. And so what we're trying to do is we make it easier for developers to go fast innovate, but also do it securely and embed it without slowing them down, develop fast and secure. >>So again, I love, I love AWS love what they're doing. We heard, uh, yesterday from, from CJ, you know, a lot of talk about, you know, threat detection and, you know, some talk about DevOps, et cetera. But yeah, I, I, I didn't hear a lot about how to reduce the complexity for the CSO. And the reason I bring this up is it feels like the cloud is now the first level of defense and the CISO is, is becoming the next level, which is on the developer. So the developer is becoming responsible for security at a whole shift left, maybe shield. Right. But, but shift left is becoming critical. Seems like your role and maybe others in the ecosystem is to address my concern about simplifying the life of the CISO. Is that a reasonable way to think about it? I >>Think it's changing the role of the CISO. How so? You know, really it's, I, I think it's before it, in this, in the security organization and D you should chime in here is, you know, it used to be, I did, I owned all application security, I owned the whole thing and they couldn't keep up. Like, I think it's just every security organization is totally overwhelmed. And so they have to share the responsibility. They have to get that fix the issues earlier and earlier, because it's waiting too long. It's after the fact. And then you gotta throw this over the fence and developers have to fix it. So they've gotta find a new way because they're the bottleneck they're slowing down the company from, in innovating and bringing these applications to market. So we are the kind of this bridge between the security teams that wanna make sure the, that we're staying secure and the development organizations and engineering and CEOs go fast. We need you guys to go faster and faster. So we, we tend to be the bridge between the two of them. >>One of the things I really love happening these days is that we change the culture of the organization from a culture where the CSO is trying to, you know, push and enforce and dictate the policy, which, which they should, but they really wanna see the development team speak up like that. The whole motion of DevOps is that we are empowering them to make the decisions that are right for the business, right? And then there is a gap because on one hand, this is always like, you need to do this, you need to do this. You need to do that. And the dev teams don't understand how that impacts their business. Good enough. And they don't have the tools and, you know, the ability to add a source problem. So with the solution liken, we really empower the developers to bake security as part of their cycle, which is what was done in many other fields, quality, other things, everything, it, everything moves into development already, right? So we're doing that. And the entire discussion now changes into an enablement discussion. >>So interesting. Cause you saw, this is the role of the CSOs changing. How so? I see that in a way like frees, sneak the CSO with the cloud is becoming a compliance officer. Like you do this, you do this, you do this, you do this, you third >>One would take a responsibility >>Trying. Yeah. Right, right. And so you're flipping that equation saying, Hey, we're gonna actually make this an accelerant to your business. >>So, so set the policy, determine compliance, but make sure that the teams, the developers are building applications in compliance with your policy. Right. So make sure and, and don't allow them to do something. If they're doing, if they're developing an application with a number of vulnerabilities, you can stop that from happening so you can oversee it, but you don't have to be the one who owns it all the way through from beginning to, >>Or, or get it before it's deployed. So you don't have to go back after the fact and, and remediate it with, you know, but, >>But think about deploy, they're deploying apps today. I mean, they're updating by the hour, right? Where, you know, six years ago, five years ago, two years ago was every six to nine months. Right? So the pace of this innovation from developers is so fast that the old way of doing security can't keep up. Like they're built for six month release cycles. This is six hour release cycles. And so we had to, it has to change security. Can't stay the way it is. So what we've been doing for se seven years for application security is exactly what we're doing for cloud security is moving all that earlier. All these products that we've been building over the years is really taking these afterthought security components and bringing 'em all earlier, you know, bringing everything like cloud security is done after the fact. Now we can take those issues and bring 'em right to the developers who created that and can fix the issues. So it's code to cloud back to code in a very automated fashion. So doesn't slow developers down. >>Okay. So what's the experience. We all know there's, everybody has more than one cloud. What's the experience across clouds. Can you create a consistent, continuous experience, cloud agnostic, >>Agnostic, cloud agnostic, uh, development environment, agnostic, you know, language agnostic. So that's kind of the beauty oft where you have maybe other certain tools for certain clouds, uh, or certain languages or certain development environments, but you have to learn different tools, you know, and, and they all roll up to security in a different way. And so what we have done is consolidated all that spend for open source security, container security infrastructure, now, cloud security, all that spend and all that fragmentation all under one platform. So it's one company that brings all those pieces >>Together. So it's a single continuous experience. Yeah. The developer experience you're saying is identical. Yes. >>Actually one product >>It's entitlement that we're getting. Yes. So you're hiding the underlying complexities of the respective clouds and those primitives developer doesn't have to worry about them. No, I call that a super cloud super >>Cloud. >>Okay. But no, but essentially that's what you're, you're building, building on the, on this ed Walsh would say on the shoulders of giants. Yeah, exactly. You know, you don't have to worry about the hyperscale infrastructure. Yep. Right. That you're building a layer of value on top of that. Yes. Is, is that essentially a PAs layer or is it, is it, can I think of it that way or is it not? Hmm. Is it platform? I >>Mean, yeah. I, I, I would say that at the end of the day, the, the way developers want to use a security tool is the same. Right. So we expose our functionality to them in those ways, if you're using, you know, uh, uh, one GI repository or another, if you're using one cloud or we, we are agnostic to data, don't, it's not, it doesn't really affect us in that manner. Um, I want to add another thing about the, the experience and associated with the consolidation that Peter referred to, uh, earlier, when you have a motion that automatically assess, you know, uh, problems that the developer is putting as part of the change management, as example, you do creating pool request. Now adding more capabilities into that motion is easy. So from enablement of the team, you can add another functionality, add cloud at ISC, add code and so on like that, because you already, you already made the decisions on how you are looking at that. And now you're integrated at, into your developer workflows, >>Right? So it's, it's already, it's already integrated for open source, adding container and ISD is real easy. It's all, you've already done all the integrations. And so for us going to five products and eventually 6, 7, 8, all, all based on the integrations that you already have in the same workflows that developers have become a use accustomed >>To. And that's what we, a lot of work from the company perspective. Right. >>I can ask you about another sort of trend we're seeing where you see Goldman Sachs last reinvent announced a cloud product, essentially bringing their data, their tools, their software. They're gonna run it on AWS at the snowflake summit, uh, capital one announced the service running on snowflake, Oracle by Cerner, right? Yeah. You know, they're gonna be, do something on OCI. Of course, make 'em do that. But it's, it's a spin on Andreessens every company's a software company. It's like every company's now becoming digital, a software company building their own SAS, essentially building their own clouds, or maybe, maybe something they'll be super clouds. Are you seeing industry come to sneak and say, Hey, help us build products that we can monetize >>There companies. So, first off, I think kind of the first iteration is, you know, all these industries of becoming software driven, like you said, and more software is more software risk. And so that kind of led us down this journey of now financial services, you know, tech, you know, media and entertainment, financial services, healthcare. Now it's this long tail of, of low tech. Yeah. Within those companies, they are offering services to the other parts of the organization. We have >>So far, mostly >>Internal, mostly internal, other than the global SI. And some of the companies who do that for a living, you know, they build the apps for companies and they are offering a sneak service. So before I give you these, I update these applications. I'm gonna make sure I'm running. I'm, I'm, I'm signifying those applications to make sure that they're secure before you get them. And so that now a company like a capital one coming to us saying, I wanna offer this to others. I think that's a, that's a leap because you know, companies are taking on security of someone else's and I think that's a, that's not there yet. It may be, >>Do you think it'll happen? >>We do have the, uh, uh, threat Intel that we, we have a very, a very strong security group that constantly monitors and analyzing the threat. And we create this vulnerability database. So in open sources, an example, we're the fact of standard, uh, in the field. So many of our partners are utilizing the threat Intel feed of snake as part of their offering. Okay. If you go to dock as an example, you can scan with, with snake intelligence immediately out of the gate over there, right? Yeah. >>And tenable, rapid seven trend micro. They all use the vulnerability database as well. Okay. So a lot of financial institutions use it because they had, they'd have seven, 10 people doing re security research on their own. And now they can say, well, I don't have to have those seven. I've got the industry standard for vulnerability database from Steve. >>And they don't have to throw out their existing tool sets where they have skills. >>Yes, exactly. >>Peter bring us homes, give us the bumper sticker, summarize, you know, reinforce and kind what we can expect going forward. >>Yeah, no, I mean, we're gonna continue the pace. We don't see anything slowing, slowing us down in terms of, um, just the number of customers that are, that are shifting left. Everybody's talking about, Hey, I need to embed this earlier and earlier. And I think what they're finding is this, this need to rein reinnovate like get innovation back into their business. And a lot of it had to slow down because, well, you know, you, we can't let developers develop an app without it going through security. And that takes time. It slows you down and allows you not to like slow the pace of innovation. And so for us, it's it help developers go fast, incredibly, you know, quickly, aggressively, creatively, but do it in a secure way. And I think that balance, you know, making sure that they're doing what they're doing, they're increasing developer productivity, increasing the amount of innovation that developers are trying to do, but you gotta do it securely. And that's where we compliment really what every CEO is pushing companies. I need more productivity. I need more aggressive creativity, innovation, but you better be secure at the same time. And that's what we bring together for our customers. >>And you better do that without slowing us down. That's >>Don't trade off, slow >>Us down. Always had to make. Yes, guys. Thanks so much for coming to the cube. Thanks, David. Always great to see you guys see ID. Appreciate it. All right. Keep it right there. This is the Cube's coverage of reinforced 2022 from Boston. We'll be right back right after the short break.
SUMMARY :
Great to see you again. You can't be weather's good weather. Know, all you gotta do is make it in. And there's a new season. I think it's you think so it's not looking good. a lot of buzz, one of the largest, I think the largest event I saw around here, a lot of good customers there. It's great. So what's new. So now we have, uh, Well, and of course my, in my intro, I, I said, reinvent, I'm getting ahead of myself. We'll be at reinve Are that's the next one at We've done a lot of reinvents by the way, you know? So, you know, I mean, for years it was always, um, you know, after the fact production So I like the fact that you're using some of your capital to do acquisitions. And we have identified the merit of what we need in terms of the first security So you retire that and bring it in the brand is sneak. So the notion is as followed as you are, you know, you're a CSO, you have your pro you have your program, So on one end, you know, the actual resources that the keynotes yesterday about, you know, reasoning, AI reasoning, of, you know, the remote user or in this case, the attacker, right. So propagates, you have to, you have to have a, a solution that looks both at have very good understanding So there's, there's human to app. I understand what is that something that you guys can solve? So both improves making sure they know, you know, quality problems or things of this kind. that and then notify remediate or whatever action should be Yep. that is required to make that happen. And I think part of this is the, you know, just, uh, the speed of the software development you know, a lot of talk about, you know, threat detection and, you know, some talk about DevOps, et cetera. And then you gotta throw this over the fence and developers have And they don't have the tools and, you know, the ability to add a source Like you do this, you do this, you do this, you do this, And so you're flipping that equation saying, an application with a number of vulnerabilities, you can stop that from happening so you can oversee So you don't have to go back after the fact and, So the pace of this innovation from developers is Can you create a consistent, continuous experience, So that's kind of the beauty oft where you have maybe other certain tools So it's a single continuous experience. So you're hiding the underlying complexities of the You know, you don't have to worry about the hyperscale infrastructure. So from enablement of the team, you can add another functionality, on the integrations that you already have in the same workflows that developers have become a use accustomed To. And that's what we, a lot of work from the company perspective. I can ask you about another sort of trend we're seeing where you see Goldman Sachs last reinvent you know, tech, you know, media and entertainment, financial services, healthcare. And so that now a company like a capital one coming to us saying, If you go to dock as an example, you can scan with, with snake intelligence So a lot of financial institutions use it because they had, they'd have seven, Peter bring us homes, give us the bumper sticker, summarize, you know, reinforce and kind And a lot of it had to slow down because, well, you know, you, And you better do that without slowing us down. Always great to see you guys see ID.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
David | PERSON | 0.99+ |
Dave Lanta | PERSON | 0.99+ |
Shani | PERSON | 0.99+ |
Steve | PERSON | 0.99+ |
Peter | PERSON | 0.99+ |
six month | QUANTITY | 0.99+ |
Peter McKay | PERSON | 0.99+ |
Boston | LOCATION | 0.99+ |
Snyk | PERSON | 0.99+ |
six hour | QUANTITY | 0.99+ |
seven | QUANTITY | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
Goldman Sachs | ORGANIZATION | 0.99+ |
Adi Sharabani | PERSON | 0.99+ |
Yankees | ORGANIZATION | 0.99+ |
November | DATE | 0.99+ |
seven years | QUANTITY | 0.99+ |
yesterday | DATE | 0.99+ |
five products | QUANTITY | 0.99+ |
Microsoft | ORGANIZATION | 0.99+ |
billions | QUANTITY | 0.99+ |
first product | QUANTITY | 0.99+ |
July | DATE | 0.99+ |
six acquisitions | QUANTITY | 0.99+ |
1300 people | QUANTITY | 0.99+ |
two examples | QUANTITY | 0.99+ |
One | QUANTITY | 0.99+ |
one platform | QUANTITY | 0.99+ |
one platform | QUANTITY | 0.99+ |
five years ago | DATE | 0.99+ |
six | DATE | 0.98+ |
both | QUANTITY | 0.98+ |
six years ago | DATE | 0.98+ |
last night | DATE | 0.98+ |
ISE | TITLE | 0.98+ |
two years ago | DATE | 0.98+ |
first approach | QUANTITY | 0.98+ |
Oracle | ORGANIZATION | 0.97+ |
one | QUANTITY | 0.97+ |
2022 | DATE | 0.97+ |
billions of dollars | QUANTITY | 0.97+ |
Cerner | ORGANIZATION | 0.97+ |
Intel | ORGANIZATION | 0.97+ |
one company | QUANTITY | 0.96+ |
single | QUANTITY | 0.96+ |
first iteration | QUANTITY | 0.96+ |
nine months | QUANTITY | 0.95+ |
OCI | ORGANIZATION | 0.95+ |
first level | QUANTITY | 0.95+ |
today | DATE | 0.94+ |
SAS | ORGANIZATION | 0.94+ |
first | QUANTITY | 0.93+ |
more than one cloud | QUANTITY | 0.93+ |
10 people | QUANTITY | 0.92+ |
second live reinvent | QUANTITY | 0.92+ |
one product | QUANTITY | 0.91+ |
one view | QUANTITY | 0.9+ |
one end | QUANTITY | 0.89+ |
first security solution | QUANTITY | 0.89+ |
single point | QUANTITY | 0.87+ |
Cube | ORGANIZATION | 0.87+ |
one cloud | QUANTITY | 0.86+ |
170% year | QUANTITY | 0.85+ |
six | QUANTITY | 0.85+ |
third | QUANTITY | 0.84+ |
M | ORGANIZATION | 0.84+ |
hundred percent | QUANTITY | 0.78+ |
Walsh | PERSON | 0.76+ |
S3 | TITLE | 0.74+ |
two of | QUANTITY | 0.74+ |
6 | QUANTITY | 0.73+ |
DevOps | TITLE | 0.73+ |
Andreessens | PERSON | 0.67+ |
cube | ORGANIZATION | 0.67+ |
Brian Shield, Boston Red Sox | Acronis Global Cyber Summit 2019
>> 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)
SUMMARY :
Brought to you by Acronis. We are in Miami Beach, the Fontainebleau Hotel. It's great to be here. John: So congratulations on the rings. Hey we appreciate that. You got to show Which camera is the good one? Bummer about this year. Again, things move on, but you know. Fenway Park, the cathedral of baseball parks. because of the threats. So you got business, team, fans. sort of relish the nostalgia of sports But over the last six, seven years, you know and I think it really speaks to sort of and digital has certainly consumed the world. You speak to a theater. So therefore, the technology has to be seamless. Well the data's got to be ubiquitous, right? about Fenway Park and how we modernize, and having things on brand as well. Saying being on brand, not kind of tearing down the old. that you may not have had before. One of the challenges that you guys have in Boston, that you guys are looking at Yeah so Fenway Park, we struggle as you know, Bentley, Babson, all the schools in the area. and the role that technology can play in the future. to cyber protection. What is the security kind of posture that you guys have? These guys are the lifeblood of our, you know, so those are end points now connecting to your network. for both ourselves and for all the touchpoints to fans. So I got to ask you the modernization question. So has digital blurred the lines So I mean, first off, the relationship of the franchise agreement, isn't it? really hats off to those guys, That's a huge, kind of shows the power of data One of the things that Major League Baseball does What new innovations that the casual fan or IT person and in some portions of the major leagues, You wear a ring now to tell you if you're sleeping well. and our managers to really make the wise decisions. that you think is going to be game-changing and so being able to leverage the best of both of those and kind of what that can mean. like in the movie "The Town"? I know it's not in the room that they would to cover the games, next to NESN? We're looking good on the pipes. articulate all that to the fans. and also the complications and challenges
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Venezuela | LOCATION | 0.99+ |
Verizon | ORGANIZATION | 0.99+ |
David | PERSON | 0.99+ |
John Furrier | PERSON | 0.99+ |
Brian Shield | PERSON | 0.99+ |
Red Sox | ORGANIZATION | 0.99+ |
2018 | DATE | 0.99+ |
Boston | LOCATION | 0.99+ |
California | LOCATION | 0.99+ |
Acronis | ORGANIZATION | 0.99+ |
John | PERSON | 0.99+ |
Brian | PERSON | 0.99+ |
Dell | ORGANIZATION | 0.99+ |
Andy Jassy | PERSON | 0.99+ |
Yankees | ORGANIZATION | 0.99+ |
two games | QUANTITY | 0.99+ |
Aramark | ORGANIZATION | 0.99+ |
David Ortiz | PERSON | 0.99+ |
Red sox | ORGANIZATION | 0.99+ |
Miami | LOCATION | 0.99+ |
Statcast | ORGANIZATION | 0.99+ |
5,400-seat | QUANTITY | 0.99+ |
Las Vegas | LOCATION | 0.99+ |
ten | QUANTITY | 0.99+ |
London | LOCATION | 0.99+ |
two days | QUANTITY | 0.99+ |
Scudder Investments | ORGANIZATION | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Miami Beach | LOCATION | 0.99+ |
Boston Red Sox | ORGANIZATION | 0.99+ |
England | LOCATION | 0.99+ |
The Town | TITLE | 0.99+ |
southeast Asia | LOCATION | 0.99+ |
Miami Beach, Florida | LOCATION | 0.99+ |
Fenway Park | LOCATION | 0.99+ |
Brad Pitt | PERSON | 0.99+ |
ESPN | ORGANIZATION | 0.99+ |
EMC | ORGANIZATION | 0.99+ |
Giants | ORGANIZATION | 0.99+ |
Bentley | ORGANIZATION | 0.99+ |
Latin America | LOCATION | 0.99+ |
Beacon | ORGANIZATION | 0.99+ |
both | QUANTITY | 0.99+ |
World Series | EVENT | 0.99+ |
first time | QUANTITY | 0.99+ |
both fans | QUANTITY | 0.99+ |
weather.com | ORGANIZATION | 0.99+ |
Major League Baseball | ORGANIZATION | 0.99+ |
One | QUANTITY | 0.99+ |
125 scouts | QUANTITY | 0.98+ |
First | QUANTITY | 0.98+ |
Acronis Global Cyber Summit 2019 | EVENT | 0.98+ |
1912 | DATE | 0.98+ |
Ipswich | LOCATION | 0.98+ |
30 clubs | QUANTITY | 0.98+ |
Last decade | DATE | 0.98+ |
The Cube | ORGANIZATION | 0.98+ |
Global Cyber Summit | EVENT | 0.98+ |
Christmas | EVENT | 0.97+ |
Mark Phillip, Are You Watching This?! | Sports Tech Tokyo World Demo Day 2019
>> Hey, welcome back, everybody. Jeffrey here with the Cube were Rhetorical Park in San Francisco on the shores of McCovey Cove. I just love saying that we >> haven't been here since >> 2014. We're excited to be back for a really interesting event is called Sports Tech Tokyo World Demo Day. This next guest has been at it for a number of years. A really cool technology. We're excited for the conversation and to welcome Mark Philip. He's the founder and CEO of Are >> You watching this Mark? >> Great to see you. Good to see you, too. Absolutely. So, first off, you've been Thio Park before. Here I have. It's been way too long. >> There are >> a few iconic stadiums in the world, and this has got to be one of the great. So let's get into it. So what is are you watching this all about? >> We are the best friend that is >> giving the digital tap on the shoulder when it's time to run to the couch. We monitor pitch by pitch, shot by shot data to figure out when the game gets exciting. I love my Yankees till death, but the >> Yankees Red Sox occasionally tend to >> take over my entire night when they play each other. So being able to get that tap on the shoulder saying, Hey, it's time to tune in or stop raking the leaves, there's a no hitter through eight. Okay, that's what we try to do. Okay, so let's break it down before we get some of the applications into which actor doing So You guys air, You're actively watching these games. You've got some type of an algorithm based on scoring plays. Pitch count. Are we? What are some of the things that drive? Whether this is an exciting game or not, it's a great question. The easiest way to think about it is if you imagine what a win probability graph looks like. So game probably starts off in the middle. Might go up or down based on who's winning, the more violently that graph goes up and down generally, the more exciting the game is, so when probability is a big factor. But also you think about rarity whether it's we had a no hitter last night, we had the Astros with a four picture no hitter a few weeks ago. You know, those sort of things that you don't see often, even if the game's nine nothing, even if the wind probabilities and changing. If that's a no hitter, that's something you want to turn into, right? And so are you tapping into just kind of some of the feeds that are out there in terms of what's happening in the game or you actually watching and using a I in terms of actually looking at a screen and making judgments? Sure, thankfully, I'm not watching or else I would never leave the house. But for us, it's about getting that real time live data. Okay, so I can see balls and strikes on my servers faster than I can see it on live TV, which is a little bit mind bending of time. So we work with the the official data sources. So whether it's a company like sport radar or stats or opt or Abels and pretty much anyone around the globe, we pull in that real time data so we can give people that tap on. The show says Hey, run to the couch. Run to the bar, tune in. Something interesting is about to happen, right? But what's entering your B to B play. So your customers are not me. Jeff, go to the couch. You're working through other people that might be motivated to have me run to the count. So how does your business model work? Who are some of your customers? What are some of the ways that they use your service? >> I'm I'm the guy behind the guy. I'm behind the >> Red Curtain, pulling the strings, you know, for us not to paint with an overly broad brush. But we're based in Austin, Texas, and one of the big things about a city like ours versus the city like this is that our companies tend to skew very B to B versus the Bay Area, which generally excuse a lot more B to C. So pitching to the cable companies, the sports providers, probably CBS Sports is our oldest customer right now. We work with small startups, more established folks, and everyone uses this differently. But the goal is the vision. Is that whether it's your DVR recording automatically when the game gets good or just making sure that, you know, maybe you want to place a bet on the Giants or if you are, ah, glutton for punishment my lowly Knicks if the if the spreads. Good enough, you know, getting that nudge when games get exciting is an accelerant. Not just for watching in, but I think, for fandom. Yeah, well, when Kevin Durant comes back, you'll get a bit more exciting >> Nets, not Nick's. I'm gonna give you one free one. So we had a conversation >> before we turn the cameras on about, you know, kind of this. This never ending attention span competition and the never ending shrinking of consumable media. And how you guys really play an interesting role in that evolution, where if you can give us a little bit deeper background, >> I think it's fascinating. You look at >> the N B A. That really any league. If you rewind five years ago, you have to pay to 5300 bucks to get access to anything digitally, and then you got access to everything, and then the NBA's said, Well, maybe just want to buy one team, so we'll let you pay things around 80 bucks and they just want to watch. One game will sell it to you for eight. I just want 1/4 with such for dollar 99 if you just want a few minutes with silty for 99 >> cents, and now they've done that really, really quietly. >> But I think it's seismic because I think all leagues we're gonna have to follow and do this. So if you look at these snack passes and especially as thes NFL rights are coming up, I could easily imagine someone like a YouTube or, I should say, a Google if they were to grab these rights, how easy would be to go to YouTube and get a game for a few bucks and how well their entire infrastructure would work. But rewind to today when you have 10 to 20 states that are online. As far as gambling goes, you take gambling. You take excitement analytics and you take the snack passes and you kind of mix him up in a pot and you get this vision of I can send you a Texas is Hey, LeBron has 60 points with 3/4. Do you want to pay 99 cents tow, Watch the finish, or do you want, let's say, place a wager on if he's gonna be Kobe's 81 point Lakers record and then we'll let you watch for free. And so getting both sides of that equation, whether your die hard or casual fan, it's hard to say no to both those options, right? And do you see within your customer base that drive to the smaller segmentation of snack packs? Is that driven by customer demand, or are they trying to get ahead of it a little bit and offer, you know, kind of different sizes of consumption, I guess, would be the right. >> Sure, I think the horse is out of the barn. I mean, imagine if >> we were still buying complete albums. Of course, we're buying tracks when we just wanna track the idea that we have to buy an entire season. No foul, 2430 games in an MLB season. Why won't you let me buy just one game? I say MLB leaves a million dollars on the table every single time is no hit bid because there's tons of people who have cut the cord, don't want to run to the bar, but would happily pay 99 cents to stream the last inning of a game on their phone on their commute. So I think it is a combination of digital. What shoring in that We're able to do these three single track sort of purchases, but also its people continue to cut the cord and rethink about how they spend their media dollars. It makes sense really interesting. So we're here. It's sports Tech, World Demo Day. What do you hope to get out of today? Why are you here? Gosh, at least to pay homage to the reason why I went to Tokyo for the first time and had life changing Rama and I feel like I need to sort of complete >> the cycle. Uh, sports like >> Tokyo is an amazing program. There's lots of different events that have shaped different ways. But there's something really unique about this. And when we all lands in Tokyo, I think it was something like 80 different entrepreneurs that came into met to meet with all of the Japanese sponsors. Everyone had the same vibe of just really happy >> to be there. >> They didn't take a percentage of these startups coming in, so you really saw different sizes, not just early stage, but late stages well and everyone was there, too. Connects and innovate and do interesting things together. So many of us were there for the first time that there's just a vibe to this event that I haven't seen in my 10 plus years in sports. Tak interesting. Well, Mark, great to sit down with you. Really cool story. And, um, I guess I'll be watching for your watching for your app. Is the man behind the man coming through my phone? Real sand Sounds great. >> All right. He's >> Mark. I'm Jeff. You're watching the Cube World. World Tech demo today here at Oracle Park. Thanks for watching. We'll see you next time.
SUMMARY :
I just love saying that we We're excited for the conversation and to welcome Mark Philip. Great to see you. So what is are you watching this all about? giving the digital tap on the shoulder when it's time to run to the couch. So being able to get that tap on the shoulder saying, I'm I'm the guy behind the guy. the game gets good or just making sure that, you know, maybe you want to place a bet I'm gonna give you one free one. before we turn the cameras on about, you know, kind of this. I think it's fascinating. bucks to get access to anything digitally, and then you got access to everything, But rewind to today when you have 10 I mean, imagine if Why are you here? the cycle. entrepreneurs that came into met to meet with all of the Japanese sponsors. They didn't take a percentage of these startups coming in, so you really saw different sizes, He's We'll see you next time.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Jeff | PERSON | 0.99+ |
LeBron | PERSON | 0.99+ |
Tokyo | LOCATION | 0.99+ |
10 | QUANTITY | 0.99+ |
Mark | PERSON | 0.99+ |
99 cents | QUANTITY | 0.99+ |
Mark Phillip | PERSON | 0.99+ |
Kevin Durant | PERSON | 0.99+ |
Jeffrey | PERSON | 0.99+ |
5300 bucks | QUANTITY | 0.99+ |
60 points | QUANTITY | 0.99+ |
Mark Philip | PERSON | 0.99+ |
San Francisco | LOCATION | 0.99+ |
Oracle Park | LOCATION | 0.99+ |
2430 games | QUANTITY | 0.99+ |
ORGANIZATION | 0.99+ | |
CBS Sports | ORGANIZATION | 0.99+ |
Yankees | ORGANIZATION | 0.99+ |
today | DATE | 0.99+ |
One game | QUANTITY | 0.99+ |
eight | QUANTITY | 0.99+ |
YouTube | ORGANIZATION | 0.99+ |
99 | QUANTITY | 0.99+ |
10 plus years | QUANTITY | 0.99+ |
one game | QUANTITY | 0.99+ |
80 different entrepreneurs | QUANTITY | 0.99+ |
Bay Area | LOCATION | 0.99+ |
Giants | ORGANIZATION | 0.99+ |
first time | QUANTITY | 0.99+ |
81 point | QUANTITY | 0.98+ |
both | QUANTITY | 0.98+ |
one team | QUANTITY | 0.98+ |
20 states | QUANTITY | 0.98+ |
2014 | DATE | 0.98+ |
five years ago | DATE | 0.98+ |
Texas | LOCATION | 0.98+ |
both sides | QUANTITY | 0.98+ |
last night | DATE | 0.98+ |
dollar 99 | QUANTITY | 0.97+ |
World Demo Day | EVENT | 0.97+ |
Yankees Red Sox | ORGANIZATION | 0.97+ |
Sports Tech | EVENT | 0.97+ |
Sports Tech Tokyo World Demo Day | EVENT | 0.97+ |
Lakers | ORGANIZATION | 0.97+ |
MLB | EVENT | 0.96+ |
Knicks | ORGANIZATION | 0.95+ |
Kobe | PERSON | 0.95+ |
one | QUANTITY | 0.95+ |
around 80 bucks | QUANTITY | 0.95+ |
World Tech | EVENT | 0.95+ |
NBA | ORGANIZATION | 0.95+ |
one free | QUANTITY | 0.93+ |
1/4 | QUANTITY | 0.93+ |
first | QUANTITY | 0.92+ |
Thio Park | LOCATION | 0.92+ |
a million dollars | QUANTITY | 0.88+ |
Japanese | OTHER | 0.87+ |
few weeks ago | DATE | 0.86+ |
Nick | PERSON | 0.86+ |
Tokyo World Demo Day 2019 | EVENT | 0.86+ |
Austin, | LOCATION | 0.85+ |
NFL | ORGANIZATION | 0.85+ |
Rama | PERSON | 0.83+ |
Astros | TITLE | 0.82+ |
tons of people | QUANTITY | 0.81+ |
three single track | QUANTITY | 0.79+ |
single time | QUANTITY | 0.75+ |
nine | QUANTITY | 0.75+ |
Rhetorical Park | LOCATION | 0.71+ |
Cube World. | EVENT | 0.69+ |
four picture | QUANTITY | 0.66+ |
few bucks | QUANTITY | 0.66+ |
Cube | ORGANIZATION | 0.65+ |
McCovey Cove | LOCATION | 0.63+ |
cents | QUANTITY | 0.56+ |
3/4 | QUANTITY | 0.52+ |
Curtain | PERSON | 0.42+ |
Matt Kobe, Chicago Bulls | MIT CDOIQ 2019
>> from Cambridge, Massachusetts. It's the Cube covering M. I. T. Chief Data officer and Information Quality Symposium 2019. Brought to you by Silicon Angle Media. >> Welcome back to M. I. T. In Cambridge, Massachusetts. Everybody You're watching The Cube, the Leader and Live Tech coverage. My name is Dave Volante, and it's my pleasure to introduce Matt Kobe, who's the vice president of business strategy Analytics of Chicago Bulls. We love talking sports. We love talking data. Matt. Thanks for coming on. >> No problem getting a date. So talk about >> your role. Is the head of analytics for the Bulls? >> Sure. So I work exclusively on the business side of the operation. So we have a separate team that those the basketball side, which is kind of your players stuff. But on the business side, um, what we're focused on is really two things. One is being essentially internal consultants for the rest of the customer facing functions. So we work a lot with ticketing, allow its sponsorship, um, marketing digital, all of those folks that engage with our customer base and then on the backside back end of it, we're building out the technical infrastructure for the organization right. So everything from data warehouse to C. R M to email marketing All of that sits with my team. And so we were a lot of hats, which is exciting. But at the end of the day, we're trying to use data to enhance the customer and fan experience. Um and that's our aim. And that's what we're driving towards >> success in sports. In a larger respect. It's come down to don't be offended by this. Who's got the best geeks? So now your side of the house is not about like you say, player performance about the business performances. But that's it. That's a big part of getting the best players. I mean, if it's successful and all the nuances of the N B, A salary cap and everything else, but I think there is one, and so that makes it even more important. But you're helping fund. You know that in various ways, but so are the other two teams that completely separate. Is there a Chinese wall between them? Are you part of the sort of same group? >> Um, we're pretty separate. So the basketball folks do their thing. The business folks do their thing from an analytic standpoint. We meet and we collaborate on tools and other methods of actually doing the analysis. But in terms of, um, the analysis itself, there is a little bit of separation there, and mainly that is from priority standpoint. Obviously, the basketball stuff is the most important stuff. And so if we're working on both sides that we'd always be doing the basketball stuff and the business stuff needs to get done, >> drag you into exactly okay. But which came first? The chicken or the egg was It was the sort of post Moneyball activity applied to the N B. A. And I want to ask you a question about that. And then somebody said, Hey, we should do this for the business side. Or was the business side of sort of always there? >> I think I think, the business side and probably the last 5 to 7 years you've really seen it grown. So if you look at the N. B. A. I've been with the Bulls for five years. If you look at the N. B. A. 78 years ago, there was a handful of Business analytics teams and those those teams had one or two people at him. Now every single team in the NBA has some sort of business analytics team, and the average staff is seven. So my staff is six full time folks pushed myself, so we'll write it right at the average. And I think what you've seen is everything has become more complex in sports. Right? If you look at ticketing, you've got all the secondary markets. You have all this data flowing in, and they need someone to make sense of all that data. If you look at sponsorship sponsorship, his transition from selling a sign that sits on the side of the court for these truly integrated partnerships, where our partners are coming to us and saying, What do we get out of? This was our return. And so you're seeing a lot more part lot more collaboration between analytics and sponsorship to go back to those partners and say, Hey, here's what we delivered And so I think you it started on the basketball side, certainly because that's that's where the, you know that is the most important piece. But it quickly followed on the business side because they saw the value that that type of thinking can bring in the business. >> So I know this is not, you know, your swim lane, but But, you know, the lore of Billy Beane and Moneyball and all that, a sort of the starting point for sports analytics. Is that Is that Is that a fair characterization? Yeah. I mean, was that Was that really the main spring? >> I think it It probably started even before that. I think if you have got to see Billy being at the M I t Sports Analytics conference and him thought he always references kind of Bill James is first, and so I think it started. Baseball was I wouldn't say the easiest place to start, But it was. It's a one versus one, right? It's pitcher versus batter. In a lot of cases, basketball is a little bit more fluid. It's a team. Sport is a little harder, but I think as technology has advanced, there's been more and more opportunities to do the analytics on the basketball side and on the business side. I think what you're seeing is this huge. What we've heard the first day and 1/2 here, this huge influx of data, not nearly to the levels of the MasterCard's and others of the world. But as more and more things moved to the mobile phone, I think you're going to see this huge influx of data on the business side, and you're going to need the same systems in the same sort of approach to tackle it. >> S O. Bill James is the ultimate sports geek, and he's responsible for all these stats that, no, none of us understand. He's why we don't pay attention to batting average anymore. Of course, I still do. So let's talk about the business side of things. If you think about the business of baseball, you know it's all about maximizing the gate. Yeah, there's there's some revenue, a lot of revenue course from TV. But it's not like football, which is dominated by the by the TV. Basketball, I think, is probably a mix right. You got 80 whatever 82 game season, so filling up the stadium is important. Obviously, N v A has done a great job of of really getting it right. Free agency is like, fascinating. Now >> it's 12 months a year >> scored way. Talk about the NBA all the time and of course, you know, people like celebrities like LeBron have certainly helped, and now a whole batch of others. But what's the money side of the n ba look like? Where's the money coming from? >> Yeah, I mean, I think you certainly have broadcast right, but in many ways, like national broadcast sort of takes care of it itself. In some ways, from the standpoint of my team, doesn't have a lot of control over national broadcast money. That's a league level thing. And so the things that we have control over the two big buckets are ticketing and sponsorship. Those those are the two big buckets of revenue that my team spends a lot of time on. Ticketing is, is one that is important from the standpoint, as you say, which is like, How do we fill the building right? We've got 41 home game, supposed three preseason games. We got 44 events a year. Our goal is to fill the building for all 44 of those events. We do a pretty good job of doing it, but that has cascading effects into other revenue streams. Right, As you think about concessions and merchandise and sponsorship, it's a lot easier to spell spot cell of sponsorship when you're building is full, then if you're building isn't full. And so our focus is on. How do we? How do we fill the building in the most efficient way possible? And as you have things like the secondary market and people have access to tickets in different ways than they did 10 to 15 years ago, I think that becomes increasingly complex. Um, but that's the fun area that's like, That's where we spend a lot of time. There's the pricing, There's inventory management. It's a lot of, you know, is you look a traditional cpg. There's there's some of those same principles being applied, which is how do you are you looking airline right there? They're selling a plane. It's an asset you have to fill. We have ah, building. That's an asset we have to fill, and how do we fill it in the most optimal way? >> So the idea of surge pricing demand supply, But so several years ago, the Red Sox went to a tiered pricing. You guys do the same If the Sox are playing Kansas City Royals tickets way cheaper than if they're playing the Yankees. You guys do a similar. So >> we do it for single game tickets. So far are season ticket holders. It's the same price for every game, but on the price for primary tickets for single games, right? So if we're playing, you know this year will be the Clippers and the Lakers. That price is going to be much more expensive, so we dynamically price on a game to game basis. But our season ticket holders pay this. >> Why don't you do it for the season ticket holders? Um, just haven't gone there yet. >> Yeah, I mean, there's some teams have, right, so there's a few different approaches you convey. Lovely price. Those tickets, I think, for for us, the there's in years past. In the last few years, in particular, there's been a couple of flagship games, and then every other game feels similar. I think this will be the first year where you have 8 to 10 teams that really have a shot at winning the title, and so I think you'll see a more balanced schedule. Um, and so we've We've talked about it a lot. We just haven't gone to that made that move yet? >> Well, a season ticket holder that shares his tickets with seven other guys with red sauce. You could buy a BMW. You share the tickets, so but But I would love it if they didn't do the tiered. Pricing is a season ticket holder, so hope you hold off a while, but I don't know. It could maximize revenues if the Red Sox that was probably not a stupid thing is they're smart people. What about the sponsorships? Is fascinating about the partners looking for our ally. How are you measuring that? You're building your forging a tighter relationship, obviously, with the sponsors in these partners. Yeah, what's that are? Why look like it's >> measured? A variety of relies, largely based on the assets that they deliver. But I think every single partner we talk to these days, I also leave the sponsorship team. So I oversee. It's It's rare in sports, but I stayed over business strategy and Alex and sponsorship team. Um, it's not my title, but in practice, that's what I do. And I think everyone we talked to wants digital right? They want we've got over 25,000,000 social media followers with the Bulls, right? We've got 19,000,000 on Facebook alone. And so sponsors see those numbers and they know that we can deliver impression. They know we can deliver engagement and they want access to those channels. And so, from a return on, I always call a return on objectives, right? Return on investment is a little bit tricky, but return on objectives is if we're trying to reel brand awareness, we're gonna go back to them and say, Here's how many people came to our arena and saw your logo and saw the feature that you had on the scoreboard. If you're on our social media channels or a website, here's the number of impressions you got. Here is the number of engagements you got. I think where we're at now is Maura's Bad Morris. Still better, right? Everyone wants the big numbers. I think where you're starting to see it move, though, is that more isn't always better. We want the right folks engaging with our brands, and that's really what we're starting to think about is if you get 10,000,000 impressions, but they're 10,000,000 impressions to the wrong group of potential customers, that's not terribly helpful. for a brand. We're trying to work with our brands to reach the right demographics that they want to reach in order to actually build that brand awareness they want to build. >> What, What? Your primary social channels. Twitter, Obviously. >> So every platform has a different purpose way. Have Facebook, Twitter, instagram, Snapchat. We're in a week. We bow in in China and you know, every platform has a different function. Twitter's obviously more real time news. Um, you know the timeline stuff, it falls off really quick. Instagram is really the artistic piece of it on, and then Facebook is a blend of both, and so that's kind of how we deploy our channels. We have a whole social team that generates content and pushes that content out. But those are the channels we use and those air incredibly valuable. Now what you're starting to see is those channels are changing very rapidly, based on their own set of algorithms, of how they deliver content of fans. And so we're having to continue to adapt to those changing environments in those social >> show impressions. In the term, impressions varies by various platforms. So so I know. I know I'm more familiar with Twitter impressions. They have the definition. It's not just somebody who might have seen it. It's somebody that they believe actually spent a few seconds looking at. They have some algorithm to figure that out. Yeah. Is that a metric that you finding your brands are are buying into, for example? >> Yeah. I mean, I think certainly there they view it's kind of the old, you know, when you bought TV ads, it's how many households. So my commercial right, it's It's a similar type of metric of how many eyeballs saw a piece of content that we put out. I think we're the metrics. More people are starting to care about his engagements, which is how many of you actually engaged with that piece of content, whether it's a like a common a share, because then that's actual. Yeah, you might have seen it for three seconds, but we know how things work. You're scrolling pretty fast, But if you actually stopped to engage it with something, that's where I think brands are starting to see value. And as we think about our content, we have ah framework that our digital team uses. But one of the pillars of that is thumb stopping. We want to create content that is some stopping that people actually engage with. And that's been a big focus of ours. Last couple years, >> I presume. Using video, huge >> video We've got a whole graphics team that does custom graphics for whether it's stats or for history, historical anniversaries. We have a hole in house production team that does higher end, and then our digital team does more kind of straight from the phone raw footage. So we're using a variety of different mediums toe reach our fans >> that What's your background? How'd you get into all of this? >> I spent seven years in consulting, so I worked for Deloitte on their strategy group out of Chicago, And I worked for CPG companies like at the intersection of Retailer and CPG. So a lot of in store promotional work helping brands think through just General Revenue management, pricing strategy, promotional strategy and, um stumbled upon greatness with the Bulls job. A friend gave me the heads up that they were looking to fill this type of role and I was able to get my resume in the mix and I was lucky enough to get get the job, and it's been when I started. We're single, single, single, so it's a team of one. Five years later, we're a team of six, and we'll probably keep growing. So it's been an exciting ride and >> your background is >> maths. That's eyes business. Undergrad. And then I got a went Indian undergrad business and then went to Kellogg. Northwestern got an MBA on strategy, so that's my background. But it's, you know, I've dabbled in sports. I worked for the Chicago 2016 Olympic bid back in the day when I was at Deloitte. Um, and so it's been It's always been a dream of mine. I just never knew how I get there like I was wanted to work in sports. They just don't know the path. And I'm lucky enough to find the path a lot earlier than I thought. >> How about this conference? I know you have been the other M I T. Event. How about this one? How we found some of the key takeaways. Think you >> think it's been great because a lot of the conferences we go to our really sports focus? So you've got the M. I T Sports Analytics conference. You have seat. You have n b a type, um, programming that they put on. But it's nice to get out of sports and sort of see how other bigger industries are thinking about some of the problems specifically around data management and the influx of data and how they're thinking about it. It's always nice to kind of elevated. Just have some room to breathe and think and meet people that are not in sports and start to build those, you know, relationships and with thought leaders and things like that. So it's been great. It's my first time here. What are probably back >> good that Well, hopefully get to see a game, even though that stocks are playing that well. Thanks so much for coming in Cuba. No problems here on your own. You have me. It was great to have you. All right. Keep right, everybody. I'll be back with our next guest with Paul Gill on day Volante here in the house. You're watching the cue from M I T CEO. I cube. Right back
SUMMARY :
Brought to you by Silicon Angle Media. Welcome back to M. I. T. In Cambridge, Massachusetts. So talk about Is the head of analytics for the Bulls? But on the business side, um, what we're focused on is really two things. the house is not about like you say, player performance about the business performances. always be doing the basketball stuff and the business stuff needs to get done, A. And I want to ask you a question about that. it started on the basketball side, certainly because that's that's where the, you know that is the most important So I know this is not, you know, your swim lane, but But, you know, the lore of Billy Beane I think if you have got to see Billy being at the M So let's talk about the business side of things. Talk about the NBA all the time and of course, you know, And so the things that we have control over the two big buckets are So the idea of surge pricing demand supply, But so several years ago, It's the same price for every game, Why don't you do it for the season ticket holders? I think this will be the first year where you have 8 to 10 teams that really have a shot at winning so hope you hold off a while, but I don't know. Here is the number of engagements you got. Twitter, Obviously. Um, you know the timeline stuff, it falls off really quick. Is that a metric that you finding your brands are are More people are starting to care about his engagements, which is how many of you actually engaged with that piece of content, I presume. We have a hole in house production team A friend gave me the heads up that they were looking to fill this type of role and I was able to get my resume in the But it's, you know, I've dabbled I know you have been the other M I T. Event. you know, relationships and with thought leaders and things like that. good that Well, hopefully get to see a game, even though that stocks are playing that well.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Dave Volante | PERSON | 0.99+ |
Matt Kobe | PERSON | 0.99+ |
19,000,000 | QUANTITY | 0.99+ |
Cuba | LOCATION | 0.99+ |
8 | QUANTITY | 0.99+ |
Deloitte | ORGANIZATION | 0.99+ |
Red Sox | ORGANIZATION | 0.99+ |
Clippers | ORGANIZATION | 0.99+ |
China | LOCATION | 0.99+ |
Billy | PERSON | 0.99+ |
five years | QUANTITY | 0.99+ |
Bill James | PERSON | 0.99+ |
seven | QUANTITY | 0.99+ |
Chicago | LOCATION | 0.99+ |
Matt | PERSON | 0.99+ |
Yankees | ORGANIZATION | 0.99+ |
Paul Gill | PERSON | 0.99+ |
Lakers | ORGANIZATION | 0.99+ |
seven years | QUANTITY | 0.99+ |
BMW | ORGANIZATION | 0.99+ |
three seconds | QUANTITY | 0.99+ |
one | QUANTITY | 0.99+ |
Chicago Bulls | ORGANIZATION | 0.99+ |
80 | QUANTITY | 0.99+ |
Silicon Angle Media | ORGANIZATION | 0.99+ |
Cambridge, Massachusetts | LOCATION | 0.99+ |
single | QUANTITY | 0.99+ |
MasterCard | ORGANIZATION | 0.99+ |
two teams | QUANTITY | 0.99+ |
two big buckets | QUANTITY | 0.99+ |
82 game | QUANTITY | 0.99+ |
Sox | ORGANIZATION | 0.99+ |
seven other guys | QUANTITY | 0.99+ |
M. I T Sports Analytics | EVENT | 0.99+ |
10,000,000 impressions | QUANTITY | 0.99+ |
Bulls | ORGANIZATION | 0.99+ |
three preseason games | QUANTITY | 0.99+ |
M I t Sports Analytics | EVENT | 0.99+ |
two things | QUANTITY | 0.99+ |
two people | QUANTITY | 0.99+ |
first | QUANTITY | 0.99+ |
single games | QUANTITY | 0.99+ |
Five years later | DATE | 0.98+ |
ORGANIZATION | 0.98+ | |
several years ago | DATE | 0.98+ |
10 teams | QUANTITY | 0.98+ |
41 home game | QUANTITY | 0.98+ |
Northwestern | ORGANIZATION | 0.98+ |
both sides | QUANTITY | 0.98+ |
first time | QUANTITY | 0.98+ |
ORGANIZATION | 0.98+ | |
LeBron | PERSON | 0.98+ |
both | QUANTITY | 0.98+ |
10 | DATE | 0.98+ |
Alex | PERSON | 0.98+ |
this year | DATE | 0.97+ |
Kansas City Royals | ORGANIZATION | 0.97+ |
One | QUANTITY | 0.97+ |
12 months a year | QUANTITY | 0.97+ |
first year | QUANTITY | 0.97+ |
78 years ago | DATE | 0.95+ |
single game tickets | QUANTITY | 0.95+ |
M I T. Event | EVENT | 0.94+ |
1/2 | QUANTITY | 0.94+ |
Indian | OTHER | 0.94+ |
ORGANIZATION | 0.94+ | |
ORGANIZATION | 0.93+ | |
7 years | QUANTITY | 0.92+ |
first day | QUANTITY | 0.92+ |
15 years ago | DATE | 0.92+ |
44 of those events | QUANTITY | 0.91+ |
six full | QUANTITY | 0.91+ |
Maura's Bad Morris | ORGANIZATION | 0.9+ |
a week | QUANTITY | 0.9+ |
Snapchat | ORGANIZATION | 0.9+ |
M. I. T. | PERSON | 0.9+ |
over 25,000,000 social media followers | QUANTITY | 0.88+ |
seconds | QUANTITY | 0.88+ |
Last couple years | DATE | 0.88+ |
N. B. | LOCATION | 0.87+ |
Joe Caserta & Doug Laney, Caserta | MIT CDOIQ 2019
>> from Cambridge, Massachusetts. It's three Cube covering M I T. Chief data officer and information quality Symposium 2019. Brought to you by Silicon Angle Media. >> Hi already. We're back in Cambridge, Massachusetts at the M I t. Chief data officer Information quality event. Hashtag m i t cdo i Q. And I'm David Dante. He's Paul Gillen. Day one of our two day coverage of this event. This is the Cube, the leader in live tech coverage. Joe Caserta is here is the president of Caserta and Doug Laney, who is principal data strategist at Caserta, both Cube alarm guys. Great to see you again, Joe. What? Did you pick up this guy? How did that all came on here a couple of years ago? We had a great conversation. I read the book, Loved it. So congratulations. A nice pickup. >> We're very fortunate to have. >> Thanks. So I'm fortunate to be here, >> so Okay, well, what attracted you to Cassard? Oh, >> it's Joe's got a tremendous reputation. His his team of consultants has a great reputation. We both felt there was an opportunity to build some data strategy competency on top of that and leverage some of those in Phanom. Its ideas that I've been working on over the years. >> Great. Well, congratulations. And so, Joe, you and I have talked many times. And the reason I like talking because you know what's going on in the market place? You could you could siphon. What's riel? What's hype? So what do you see? It is the big trends in this data space, and then we'll get into it. Yeah, sure. Um, trends >> are chief data officer has been evolving over the last couple of years. You know, when we started doing this several years ago, there was just a handful of people, maybe 30 40 people. Now, there's 450 people here today, and it's been evolving. People are still trying to find their feet. Exactly what the chief date officers should be doing where they are in the hierarchy. Should they report to the c e o the C I O u the other CDO, which is a digital officer. So I think you know, hierarchically. That's still figuring it out politically. They're figuring it out, but technically also, they're still trying to figure it out. You know what's been happening over the past three years is the evolution of data going from traditional data warehousing and business intelligence. To get inside out of data just isn't working anymore. Eso evolving that moving it forward to more modern data engineering we've been doing for the past couple of years with quote unquote big data on That's not working anymore either, right? Because it's been evolving so fast. So now we're on, like, maybe Data three dato. And now we're talking about just pure automate everything. We have to automate everything. And we have to change your mindset from from having output of a data solution to an outcome to date a solution. And that's why I hired Doug, because way have to figure out not only had to get this data and look at it and analyze really had to monetize it, right? It's becoming a revenue stream for your business if you're doing it right and Doug is the leader in the industry, how to figure that >> you keep keep premise of your book was you gotta start valuing data and its fundamental you put forth a number of approaches and techniques and examples of companies doing that. Since you've published in phenomena Microsoft Apple, Amazon, Google and Facebook. Of the top five market value cos they've surpassed all the financial service is guys all ExxonMobil's and any manufacturer? Automobile makers? And what of a data companies, right? Absolutely. But intrinsically we know there's value their way any closer to the prescription that you put forth. >> Yeah, it's really no surprise and extra. We found that data companies have, ah, market to book value. That's nearly 33 times the market average, so Apple and others are much higher than that. But on average, if you look at the data product companies, they're valued much higher than other companies, probably because data can be reused in multiple ways. That's one of the core tenets of intra nomics is that Data's is non depleted ble regenerative, reusable asset and that companies that get that an architect of businesses based on those economics of information, um, can really perform well and not just data companies, but >> any company. That was a key takeaway of the book. The data doesn't conform to the laws of scarcity. Every says data is the new oil. It's like, No, it's not more valuable. So what are some examples in writing your book and customers that you work with. Where do you see Cos outside of these big data driven firms, breaking new ground and uses of data? I >> think the biggest opportunity is really not with the big giant Cos it's really with. Most of our most valuable clients are small companies with large volumes of data. You know if and the reason why they can remain small companies with large volumes of data is the thing that holds back the big giant enterprises is they have so much technical. Dad, it's very hard. They're like trying to, you know, raise the Titanic, right? You can't really. It's not agile enough. You need something that small and agile in order to pivot because it is changing so fast every time there's a solution created, it's obsolete. We have to greet the new solution on dhe when you have a big old processes. Big old technologies, big old mind sets on big old cultures. It's very hard to be agile. >> So is there no hope? I mean, the reason I ask the question was, What hope can you give some of these smokestack companies that they can become data centric? Yeah, What you >> see is that there was a There was a move to build big, monolithic data warehouses years ago and even Data Lakes. And what we find is that through the wealth of examples of companies that have benefited in significant ways from data and analytics, most of those solutions are very vocational. They're very functionally specific. They're not enterprise class, yada, yada, kind of kind of projects. They're focused on a particular business problem or monetizing or leveraging data in a very specific way, and they're generating millions of dollars of value. But again they tend to be very, very functionally specific. >> The other trend that we're seeing is also that the technology and the and the end result of what you're doing with your data is one thing. But really, in order to make that shift, if your big enterprises culture to really change all of the people within the organization to migrate from being a conventional wisdom run company to be a data really analytics driven company, and that takes a lot of change management, a lot of what we call data therapy way actually launched a new practice within the organization that Doug is actually and I are collaborating on to really mature because that is the next wave is really we figured out the data part. We figured out the technology part, but now it's the people part people. Part is really why we're not way ahead of where we even though we're way ahead of where we were a couple of years ago, we should be even further. Culturally, it's very, very challenging, and we need to address that head on. >> And that zeta skills issue that they're sort of locked into their existing skill sets and processes. Or is it? It's fear of the unknown what we're doing, you know? What about foam? Oh, yeah, Well, I mean, there are people >> jumping into bed to do this, right? So there is that part in an exciting part of it. But there's also just fear, you know, and fear of the unknown and, you know, part of what we're trying to do. And why were you trying Thio push Doug's book not for sales, but really just to share the knowledge and remove the mystery and let people see what they can actually do with this data? >> Yeah, it's more >> than just date illiteracy. So there's a lot of talk of the industry about data literacy programs and educating business people on the data and educating data people on the business. And that's obviously important. But what Joe is talking about is something bigger than that. It's really cultural, and it's something that is changed to the company's DNA. >> So where do you attack that problem? It doesn't have to go from the top down. You go into the middle. It has to >> be from the top down. It has to be. It has to be because my boss said to do it all right. >> Well, otherwise they well, they might do it. But the organization's because if you do, it >> is a grassroots movement on Lee. The folks who are excited, right? The foam of people, right? They're the ones who are gonna be excited. But they're going to evolve in adopt anyway, right? But it's the rest of the organization, and that needs to be a top down, Um, approach. >> It was interesting hearing this morning keynote speakers. You scored a throw on top down under the bus, but I had the same reaction is you can't do it without that executive buying. And of course, we defined, I guess in the session what that was. Amazon has an interesting concept for for any initiative, like every initiative that's funded has to have what they call a threaded leader. Another was some kind of And if they don't, if they don't have a threat of leader, there's like an incentive system tau dime on initiative. Kill it. It kind of forces top down. Yeah, you know, So >> when we interview our clients, we have a litmus test and the limits. It's kind of a ready in this test. Do you have the executive leadership to actually make this project successful? And in a lot of cases, they don't And you know, we'll have to say will call us when you're ready, you know, or because one of the challenges another part of the litmus test is this IittIe driven. If it's I t driven is gonna be very tough to get embraced by the rest of the business. So way need to really be able to have that executive leadership from the business to say this is something that we need >> to do to survive. Yeah, and, you know, with without the top down support. You could play small ball. But if you're playing the Yankees, you're gonna win one >> of the reasons why when it's I t driven, it's very challenging is because the people part right is a different budget from the i T budget. And when we start talking about data therapy, right and human resource is and training and education of just culture and data literacy, which is not necessary technical, that that becomes a challenge internally figuring out, like how to pay for Andi how to get it done with a corporate politics. >> So So the CDO crowd definitely parts of your book that they should be adopting because to me, there their main job is okay. How does data support the monetization of my organization? Raising revenue, cutting costs, improving productivity, saving lives. You call it value. And so that seems to be the starting point. At the same time. In this conference, you grew out of the ashes of back room information quality of the big data height, but exploded and have kind of gone full circle. So But I wonder, I mean, is the CDO crowd still focused on that monetization? Certainly I think we all agree they should be, but they're getting sucked back into a governance role. Can they do both, I guess, is >> my question. Well, governance has been, has been a big issue the past few years with all of the new compliance regulation and focus on on on ensuring compliance with them. But there's often a just a pendulum swing back, and I think there's a swing back to adding business value. And so we're seeing a lot of opportunities to help companies monetize their data broadly in a variety of ways. A CZ you mentioned not just in one way and, um, again those you need to be driven from the top. We have a process that we go through to generate ideas, and that's wonderful. Generating ideas. No is fairly straightforward enough. But then running them through kind of a feasibility government, starting with you have the executive support for that is a technology technologically feasible, managerially feasible, ethically feasible and so forth. So we kind of run them through that gauntlet next. >> One of my concerns is that chief data officer, the level of involvement that year he has in these digital initiatives again is digital initiative of Field of Dreams. Maybe it is. But everywhere you go the CEO is trying to get digital right, and it seems like the chief data officer is not necessarily front and center in those. Certainly a I projects, which are skunk works. But it's the chief digital officer that's driving it. So how how do you see in those roles playoff >> In the less panel that I've just spoken, very similar question was asked. And again, we're trying to figure out the hierarchy of where the CDO should live in an organization. Um, I find that the biggest place it fails typically is if it rolls up to a C I. O. Right. If you think the data is a technical issue, you're wrong, Right? Data is a business issue, Andi. I also think for any company to survive today, they have to have a digital presence. And so digital presence is so tightly coupled to data that I find the best success is when the chief date officer reports directly to the chief digital officer. Chief Digital officer has a vision for the user experience for the customer customers Ella to figure out. How do we get that customer engaged and that directly is dependent on insight. Right on analytics. You know, if the four of us were to open up, any application on our phone, even for the same product, would have four different experiences based on who we are, who are peers are what we bought in the past, that's all based on analytics. So the business application of the digital presence is tightly couple tow Analytics, which is driven by the chief state officer. >> That's the first time I've heard that. I think that's the right organizational structure. Did see did. JJ is going to be sort of the driver, right? The strategy. That's where the budget's gonna go and the chief date office is gonna have that supporting role that's vital. The enabler. Yeah, I think the chief data officer is a long term play. Well, we have a lot of cheap date officers. Still, 10 years from now, I think that >> data is not a fad. I think Data's just become more and more important. And will they ultimately leapfrog the chief digital officer and report to the CEO? Maybe someday, but for now, I think that's where they belong. >> You know what's company started managing their labor and workforce is as an actual asset, even though it's not a balance sheet. Asked for obvious reasons in the 19 sixties that gave rise to the chief human resource officer, which we still see today and his company start to recognize information as an asset, you need an executive leader to oversee and be responsible for that asset. >> Conceptually, it's always been data is an asset and a liability. And, you know, we've always thought about balancing terms. Your book sort of put forth a formula for actually formalizing. That's right. Do you think it's gonna happen our lifetime? What exactly clear on it, what you put forth in your book in terms of organizations actually valuing data specifically on the balance sheet. So that's >> an accounting question and one that you know that you leave to the accounting professionals. But there have been discussion papers published by the accounting standards bodies to discuss that issue. We're probably at least 10 years away, but I think respective weather data is that about what she'd asked or not. It's an imperative organizations to behave as if it is one >> that was your point it's probably not gonna happen, but you got a finger in terms that you can understand the value because it comes >> back to you can't manage what you don't measure and measuring the value of potential value or quality of your information. Or what day do you have your in a poor position to manage it like one. And if you're not manage like an asset, then you're really not probably able to leverage it like one. >> Give us a little commercial for I do want to say that I do >> think in our lifetime we will see it become an asset. There are lots of intangible assets that are on the books, intellectual property contracts. I think data that supports both of those things are equally is important. And they will they will see the light. >> Why are those five companies huge market cap winners, where they've surpassed all the evaluation >> of a business that the data that they have is considered right? So it should be part of >> the assets in the books. All right, we gotta wraps, But give us Give us the The Caserta Commercial. Well, concert is >> a consultancy that does essentially three things. We do data advisory work, which, which Doug is heading up. We do data architecture and strategy, and we also do just implementation of solutions. Everything from data engineering gate architecture and data science. >> Well, you made a good bet on data. Thanks for coming on, you guys. Great to see you again. Thank you. That's a wrap on day one, Paul. And I'll be back tomorrow for day two with the M I t cdo m I t cdo like you. Thanks for watching. We'll see them all.
SUMMARY :
Brought to you by Great to see you again, Joe. Its ideas that I've been working on over the years. And the reason I like talking because you know what's going on in the market place? So I think you that you put forth. We found that data companies have, ah, market to book value. The data doesn't conform to the laws of scarcity. We have to greet the new solution on dhe when you have a big old processes. But again they tend to be very, very functionally specific. But really, in order to make that shift, if your big enterprises It's fear of the unknown what we're But there's also just fear, you know, and fear of the unknown and, people on the data and educating data people on the business. It doesn't have to go from the top down. It has to be because my boss said to do it all But the organization's because if you do, But it's the rest of the organization, and that needs to be a top down, And of course, we defined, I guess in the session what that was. And in a lot of cases, they don't And you know, we'll have to say will call us when you're ready, Yeah, and, you know, with without the top down support. of the reasons why when it's I t driven, it's very challenging is because the people part And so that seems to be the starting point. Well, governance has been, has been a big issue the past few years with all of the new compliance regulation One of my concerns is that chief data officer, the level of involvement experience for the customer customers Ella to figure out. JJ is going to be sort of the driver, right? data is not a fad. to the chief human resource officer, which we still see today and his company start to recognize information What exactly clear on it, what you put forth in your book in terms of an accounting question and one that you know that you leave to the accounting professionals. back to you can't manage what you don't measure and measuring the value of potential value or quality of your information. assets that are on the books, intellectual property contracts. the assets in the books. a consultancy that does essentially three things. Great to see you again.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Joe | PERSON | 0.99+ |
Paul Gillen | PERSON | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
David Dante | PERSON | 0.99+ |
Microsoft | ORGANIZATION | 0.99+ |
Apple | ORGANIZATION | 0.99+ |
ExxonMobil | ORGANIZATION | 0.99+ |
ORGANIZATION | 0.99+ | |
ORGANIZATION | 0.99+ | |
Joe Caserta | PERSON | 0.99+ |
Paul | PERSON | 0.99+ |
Silicon Angle Media | ORGANIZATION | 0.99+ |
five companies | QUANTITY | 0.99+ |
Doug | PERSON | 0.99+ |
450 people | QUANTITY | 0.99+ |
Cambridge, Massachusetts | LOCATION | 0.99+ |
four | QUANTITY | 0.99+ |
Yankees | ORGANIZATION | 0.99+ |
JJ | PERSON | 0.99+ |
tomorrow | DATE | 0.99+ |
both | QUANTITY | 0.99+ |
two day | QUANTITY | 0.99+ |
Lee | PERSON | 0.99+ |
Doug Laney | PERSON | 0.99+ |
today | DATE | 0.98+ |
One | QUANTITY | 0.98+ |
Cassard | PERSON | 0.98+ |
Andi | PERSON | 0.97+ |
Cube | ORGANIZATION | 0.97+ |
The Caserta Commercial | ORGANIZATION | 0.97+ |
one | QUANTITY | 0.97+ |
day one | QUANTITY | 0.97+ |
first time | QUANTITY | 0.97+ |
day two | QUANTITY | 0.96+ |
several years ago | DATE | 0.96+ |
one thing | QUANTITY | 0.93+ |
Day one | QUANTITY | 0.93+ |
three things | QUANTITY | 0.92+ |
Phanom | LOCATION | 0.92+ |
Caserta | ORGANIZATION | 0.91+ |
this morning | DATE | 0.91+ |
nearly 33 times | QUANTITY | 0.9+ |
couple of years ago | DATE | 0.9+ |
millions of dollars | QUANTITY | 0.9+ |
last couple of years | DATE | 0.9+ |
Doug Laney, | PERSON | 0.9+ |
wave | EVENT | 0.89+ |
19 sixties | DATE | 0.87+ |
2019 | DATE | 0.86+ |
Thio push | PERSON | 0.85+ |
past couple of years | DATE | 0.84+ |
years ago | DATE | 0.84+ |
Data three dato | ORGANIZATION | 0.84+ |
one way | QUANTITY | 0.84+ |
next | EVENT | 0.83+ |
past three years | DATE | 0.81+ |
Titanic | COMMERCIAL_ITEM | 0.8+ |
30 40 people | QUANTITY | 0.8+ |
least 10 years | QUANTITY | 0.75+ |
top | QUANTITY | 0.75+ |
M I T. | EVENT | 0.75+ |
MIT CDOIQ | EVENT | 0.7+ |
Field of Dreams | ORGANIZATION | 0.7+ |
past few years | DATE | 0.7+ |
three | QUANTITY | 0.7+ |
five market | QUANTITY | 0.69+ |
CDO | ORGANIZATION | 0.68+ |
of people | QUANTITY | 0.66+ |
M I t. | EVENT | 0.65+ |
years | QUANTITY | 0.64+ |
Caserta | PERSON | 0.63+ |
Cos | ORGANIZATION | 0.56+ |
Ella | PERSON | 0.56+ |
k | ORGANIZATION | 0.53+ |
Luigi Danakos, VMware | VTUG Summer Slam 2019
>> Hi. I'm stupid, man. And this is a special on the ground here a the be Tugg Summer Slam and happy to welcome Thio, the program A longtime friend. But first time on the program. Somebody that's known this community for many years. Louisiana Coast is a senior systems engineer in the hyper convert infrastructure space at BM. Where Luigi great to talk >> to you again. >> Thank you. Stew. Actually, this has been one of my bucket list item since e. M. C. World 2010 when the Cube actually first started. >> Yeah. So you've been watching since the beginning. You knew me back from, you know, disclosure. I used to work at AMC, and I've been working with being work for a long time. So you've had a number of jobs. One of those consistencies out there is. I know when I would go to the winter warmer, I would usually see them. There are. Your wife is helped out at the event here also, So give us a way to start off a little bit. Like what is this event being met? You, Your career. Oh, and your friendships over the years. Oh, >> man, that's That's a great question to do. Actually, um, I don't think I would be where I am today without this particular user group. It was my first ever user group in my first ever, really major exposure into the M. We're in January 2010 at the first winter warmer that I attended. So for me, it it actually gave me exposure into the technology and then to see the community and the user's behind that. And I was already following you on Twitter at the time. And you were kind of my mentor into the social space, Ian getting involved in there and to have it all accumulate together. And it was just for me, honestly was amazing. And it was life changing >> liberty. My apologies for introducing to the quagmire that is currently Twitter. But you know l series, right? You know, you got on. You've been in a huge proponent of community activities there. You've now attended. You really think so? You've been at PM world of numbers. Free tip. There one you've been Tonto discovers with H P. When you were there. You know what's different about, you know, a regional event like this compared >> to some of the big ones. >> Well, I think the conversations that you have at most of those events of the same, I think where the benefit regionally is, you can meet up with these people afterwards for coffee, for tea. You can continue that conversation in person a lot easier on and also having the same being in the same geographical region. It helps you relate to some of it. You can. You can laugh about some of the nuances with weather or just, you know, the local sports and what's happening there. And you could just It's more like home, Right? And you get that sense of comfort when you go out to a big conference, right? Yes, you're gonna know people. Were you in a strange environment? You kind of like your little more reserved. >> Like when I talked to Chris Giladi here. He says they don't like when we talk about the Patriots, but your big patriots, >> I have diarrhea. >> Okay. All right. The other thing, you really talk about jobs here. You know something? I know over the years, I've loved helping introducing people on helping them get jobs. The S E positions are always something that every company is going to walk around this expo floor. You're always going to see people that are hiring, and you're gonna find people that that that need jobs. You know what, your >> ears I I would say that's >> the biggest thing about the regional area is when you're actually in the market for a new job. I mean, for me, if you look at me. I started out years ago as a sys admin. Then I went to Tech marketing, and I went to Social Media Marketing. And now I'm doing Essie work for GM wear, which is still a dream, in my opinion, to be working at GM where but for me, it's you build those connections and you have those conversations, those real world conversations. I was just speaking with a gentleman earlier who's possibly contemplating a job change, right? That's not a conversation he would have. Just normally he feels comfortable with these users in the experiences that they've had and and he wants to learn from that. And I'm happily to share that information with anyone. >> Yeah, Luigi, what are some of the things that you've seen? You change the industry, that impact, you know, you were involved with, You know, Matt and Sean hoping Thio, with the social media aspect of this event, Really? You know, being an open 10 toe embrace, not just >> virtualization cloud computing, obviously things like Dev ops, achieving work words or something that a heavily focused on it. >> Yeah, I would think from, if I look at it, I was actually >> having this conversation last night with Hans and are a friend of his, and I was explaining to her about the V tug and how it came about. And, you know, if you really think about back in 2012 you know, companies weren't talking multi cloud or multi virtualization technologies and the user groups started that. And if you look at where the the trend is now in the marketplace, it's plowed. It's this. It's that, you know. So the user's started to dictate that back then. So for me, it's really about that right? He and you know it allows you to stay abreast with the thing. And I don't know if I really entered your question because I'm a went off on a tangent with my a d d. But it was more about that watching the technology change and being ableto have those conversations with with people in from from NSC roll perspective, it keeps you in the touch of actually what the user's they're going through because you listen to them, you know, they start talking to you, even if you could sit in on some of these sessions like they start posing real challenges to you. >> All right, So, Luigi, you know what? I want to give you the final word. You know, we talk a little about the community, how you participated in at the end of an error. So you know what? You're takeaways here in any final memories >> that you want from the >> final memories would have to be my very first V tug. Or at the time was New England. The mug summer slammed. It was my wife's birthday. And I said, Your baby, I'm going to Maine for the day. And she's like, What's my birthday? Yeah, but this is gonna be important for us in the long run, from a career perspective. And here it is, nine years later. You know, I came home that that day with three lobsters for her. You know, I got a sweet talker. >> Um, but, >> you know, nine years later, she works and participates in the user group and gets back. And I now work for the company that we were supporting as a user in community. So for me, that's gotta go full circle. It's pretty surreal if you ask me. >> I >> had a question for you. Stay. >> Oh, I don't know if you turn the mike on, >> I know that I'm a diehard Yankees fan, But which way do you go? Yankees Red Sox? >> Well, come on, we do. You know that Like you. And like a certain Tom Brady, I am still a Yankee fan born and raised in New Jersey S o. Just don't talk about it and we win too much. But my boss is a die hard Red Sox fan, and New England fans are pretty fanatical. And don't don't you understand? Like Patriots fans have become just like 80 perennial winners. You think that they're always going to drive that and a little bit too arrogant. So looking forward to the banner unveiling for the Patriots number nine. Number six for TB 12 man, Team it, of course I will be there I've been lucky enough to be. It was actually it was the Giants connection with a tree. It's that got me there. But I do love football, and I'll miss having the V tug event. There was fun, you know, not meeting one with the alumni from there s so, uh, already, you know, sharing my share in my allegiance is there. I have not converted to the Red Sox, then was a nice place to go. But I'm more of a football God and the Patriots are my number one t never. Yeah, I think I >> think that's the other thing that I respect about. Yours were both patriots in Yankee things that I had to throw that out there. >> All right, well, Luigi, welcome to the Cube, Alumni. Thanks so much always for your >> support over the year and your contributions community. >> And be sure to check out the cute Dunnett were, of course, at PM world. We've got the entire executive team on all the big flower shows. I'm student event as always. Thank you so >> much for watching
SUMMARY :
and happy to welcome Thio, the program A longtime friend. Thank you. You knew me back from, you know, disclosure. And I was already following you on Twitter at the time. You know what's different about, you know, a regional event like this compared I think where the benefit regionally is, you can meet up with these people afterwards He says they don't like when we talk about the Patriots, but your big patriots, I know over the years, I've loved helping introducing people on helping them I mean, for me, if you look at me. work words or something that a heavily focused on it. And if you look at where the the trend is now in the marketplace, I want to give you the final word. And I said, Your baby, I'm going to Maine for the day. you know, nine years later, she works and participates in the user group and gets back. had a question for you. There was fun, you know, not meeting one with the alumni from there s so, think that's the other thing that I respect about. Thanks so much always for your And be sure to check out the cute Dunnett were, of course, at PM world.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Chris Giladi | PERSON | 0.99+ |
January 2010 | DATE | 0.99+ |
Hans | PERSON | 0.99+ |
2012 | DATE | 0.99+ |
Luigi | PERSON | 0.99+ |
Ian | PERSON | 0.99+ |
Red Sox | ORGANIZATION | 0.99+ |
Tom Brady | PERSON | 0.99+ |
Matt | PERSON | 0.99+ |
New England | LOCATION | 0.99+ |
Maine | LOCATION | 0.99+ |
Sean | PERSON | 0.99+ |
first | QUANTITY | 0.99+ |
nine years later | DATE | 0.99+ |
Thio | PERSON | 0.99+ |
Giants | ORGANIZATION | 0.99+ |
Patriots | ORGANIZATION | 0.99+ |
three lobsters | QUANTITY | 0.99+ |
AMC | ORGANIZATION | 0.99+ |
Yankees | ORGANIZATION | 0.98+ |
Dunnett | PERSON | 0.98+ |
Stew | PERSON | 0.98+ |
today | DATE | 0.98+ |
Yankees Red Sox | ORGANIZATION | 0.98+ |
first time | QUANTITY | 0.97+ |
both | QUANTITY | 0.97+ |
ORGANIZATION | 0.96+ | |
Luigi Danakos | PERSON | 0.94+ |
last night | DATE | 0.94+ |
New Jersey S | LOCATION | 0.93+ |
Essie | ORGANIZATION | 0.93+ |
VMware | ORGANIZATION | 0.93+ |
Yankee | LOCATION | 0.93+ |
one | QUANTITY | 0.92+ |
Tugg Summer Slam | EVENT | 0.91+ |
One | QUANTITY | 0.91+ |
VTUG Summer Slam 2019 | EVENT | 0.89+ |
GM wear | ORGANIZATION | 0.89+ |
H P. | PERSON | 0.89+ |
V tug | EVENT | 0.87+ |
Yankee | ORGANIZATION | 0.85+ |
GM | ORGANIZATION | 0.83+ |
80 perennial | QUANTITY | 0.83+ |
years | DATE | 0.82+ |
Louisiana Coast | LOCATION | 0.81+ |
Cube | ORGANIZATION | 0.79+ |
Number six | QUANTITY | 0.78+ |
nine | QUANTITY | 0.73+ |
10 toe | QUANTITY | 0.73+ |
first V tug | QUANTITY | 0.68+ |
2010 | DATE | 0.63+ |
M. C. World | EVENT | 0.62+ |
TB 12 | PERSON | 0.61+ |
tug | ORGANIZATION | 0.51+ |
Tonto | PERSON | 0.49+ |
BM | ORGANIZATION | 0.46+ |
Matt Kozloski, Winslow Technology Group | WTG Transform 2019
>> from Boston, Massachusetts. It's the queue covering W T. G transformed 2019 by Winslow Technology Group. >> Hi. I'm Stew Minutemen. And this is the Cuban W. T. G. Transformed 2019 here home game in Boston, Massachusetts, our third year. The event happened a Welcome back to the program. Second time on the program in less than a year. Matt Kozlowski, Who's the vice president? Professional services, Winslow Technology Group. Thanks so much for joining. Thank you. Alright, uh, second tie I've had on the program, but first vest and cufflinks you like today. So, you know, showing your own individual style for, >> like, the Ted talk. Look, >> Absolutely. So we will keep this under 18 minutes. Okay? Probably be more like about 12 theirs and no slide. But you tell us a story of change and inspiration. Uh, you know, in all seriousness there what? I actually want to hear the story of change that we're seeing inside of Winslow attack. So, um, you know, question I asked, You know, some of your peers in the company is, you know, if I thought about Winslow attack, you know, just a couple of years ago, it's like, Oh, hey, great deal, partner. No, the pellet side, you know, picking up the servers and some of the other pieces. Yeah, Here, you bring it on Brook board on board. You know, professional services security. Uh, you know, tell us a little bit about you know what? What were you doing since last time we caught up? >> Sure. So if you think about years ago where we had not just winslow but like bars as a whole came from it was, like, way sell boxes and we sell things. And now we're transitioning where people are using cloud or the hybrid cloud models. And they're actually using software in infrastructure as services and way need, like professional services and consulting to help people on that journey. That's like the simplified version of it. >> Yeah, and just, you know, I want to play something back for you and see if it resonates with you. You know, if I go back, you know, let's say 5 to 10 years ago, it was, you know, we get the boxes and the bar gets it, and they've got to spend a lot of work to configure it and do all the pieces. And, you know, that kind of day. One roll out when we talked about OK, how many months from when the equipment got to the bar versus when we're up and running? When we rolled out converged infrastructure, hyper converged infrastructure and all this cloudy stuff, it actually shifted things backwards. Now, before it gets there, there's a lot of work that either the customer or the partner with the customer needs to do so. It shifted it because once it gets on site, well, there's less wiring and cabling. You configuration I need to do. But it just shifted where that engagement service happened. It did not eliminated that what you're saying? >> Yeah, so there's a lot in terms of like planning. I mean, even, like integration work that we do ahead of time. >> I would say things that have changed even over the last, like three or four years is like the complexity of everything is gone up like we're trying to simplify it. We're simplifying maybe the delivery of it and users. But behind the scenes, certainly it's It's more complicated, I would say, than than ever. >> Yeah, you know it. We're no longer just, you know, let's lock the door and Hafiz of Security and put the firewall in place. Right now, it's like, Oh, well, it's micro segmentation in all the places and my application spread out across. You know how many locations, how many services from and therefore write everything has become a little bit >> more and more >> complicated, eh? So how do we make sure we stay secure in 2019? >> So I think there's a couple areas they're so first is, like maintaining that same kind of sense of securing people, infrastructure and things along those lines that we've kind of been doing for a while now that your basic like firewalls and even vulnerability assessments and things like that. But I think over the last couple years and this as we move to like more of like distributed workforce, like people working from home, people working remotely, finding like the right people, there's gonna be more of a focus on like and point protection and, like protecting users at, like the end point >> or the mobile level on them than ever before. >> Um, >> a lot of talking the keynote this morning, amount cloud. Yeah, and you said, you know, where does that put things so, you know, give us from your standpoint. You know, obviously services were hugely important piece of it, you know, a CZ the box. And the location becomes a little bit less important, despite the fact that even when you have things like server list, we know that there's ultimately hardware sure runs underneath it somewhere. You know, what were those Winslow play today and in the future? >> Okay, so I'm gonna give you two kind of conflicting answers to that. So the 1st 1 is, if you look at reasons why people don't go to the cloud, it's there not comfortable in the security of it. I'll say in like the my like, real world, not in the academic or statistical version of it. One of the reasons people do go to the cloud is for security, right? Look a like a lot of health care organizations are goingto like cloud based electronic medical record systems. I feel like that in some ways has insulated or shifted >> some of the burden of the risk and keeping those systems secure to the provider that's hosting them. >> Which is probably better for us, his patients, right, And for the health >> care providers in general. In that case, >> yeah. You know, one of the things we know is that what you need to do as user is you can't just keep doing things the old way because your competition will move faster. Right? And we know from a security standpoint, my friends that aren't even security is like you need to be able to move fast. One of the great things about the cloud is you know, if I'm running on Azure eight of us Hey, that latticed latest patch in that security vulnerability did that get rolled out? Well, I'm not responsible. Yes, they absolutely right. I didn't have to wait for that roll out, you know? So So there's that piece of it. So you know, just how do I keep up obtained? I need to, as as user, do some updates, and therefore, I'm not saying everything goes in the public cloud, but how do I make sure that it's not? Oh, I update my software every two years, or it's I need to make sure that I'm closing those gaps and vulnerabilities of taking advantage of words. I >> think there's going to be like a shift in changing from like normal. CIS admits they're thinking about like patching Windows and patching Lennox and operating systems. But, like once we move information to the cloud and you think about it, more is like information security. So now data is in the cloud. I'm not patching the system's anymore because we'll just assume that, you know, eight of us Microsoft. They're doing a great job with that. But like once data say is in one drive like how my governing, like where that data's going, who's accessing it, who it's being shared with, how it's being backed up things along those lines. It's just a different mindset that people need to adopt, you know, in relation to securing information, not systems. All right, >> man, I'm trying to figure we gotta replace Patch Tuesday with some celebration or some battering event where we can try to tackle some of the some of these new challenges there, You know? What does that mean to some of the changing roles that you're seeing in the customers, though? I guess here here went to attack. You know, I was talking to Arctic wolf in a typical customer, you know, doesn't have their whole security team that runs 24 7 That's where your partner with that. So you know, we're just security fit in. The organization has said, If it was a large enterprise, you know, it's a four level discussion. You know you've got your sea. So where somebody like that, what does the typical kind of mid to small sized company security team look? >> Yeah, it looks like I'm gonna partner with someone. Or that's what it should look like because, like even if companies have like a managed provider, that's doing like patch management and things along those lines, there's something to be said for having like 1/3 party in another party party, like as your security partner, Because if the people that air like doing the patching, they're probably doing a great job at it. But, like you might not want them being the ones also doing like your vulnerability assessments. It's good to have, like different parties in there, So I feel like for smaller medium businesses, it's getting comfortable partnering on and using like professional services. Frankly, Tio to do that. All >> right, so it's really interest Matt next week. Actually, Amazon is holding a cloud security show here in Boston called Reinforced. So, uh, you know, Boston seems an interesting place, You know, the arse. A conference has always been out in San Francisco. Give us kind of the state of security here in the area. >> Okay, so I think I have a unique perspective on this because I'm not from the area. Like I'm from Connecticut. So I come up here. >> You really most people in the United States would be like Connecticut is a suburb of Austin. You know where you are? Yeah, that's that's the one you need to know. Where we are. You on the Yankees Red Sox line that goes down the middle of the state, right? Right around Hartford. >> Yeah, are are like, claim to fame is being in between both city. So yes, um, way do see, though, like Boston emerging as, like, a regional tech hub, if not like the tech hub of the East Coast. Frankly, so I feel like why not have it here? Like, why wouldn't we have it here? Compared to everywhere else? Like there's so many tech companies, and this just doesn't feel like a tech hub of the region's. >> Okay, Well, you know I'm all in favor of things where I could take the trainer drive to rather than have to fly around the president. Huge is part of you Give a session here on Talked about some branch somewhere Give give us so some of the key takeaways and thanks for the audience that they should be thinking about. >> So So in that session, I kind of invented a completely fictional account of a ransomware attack on a hospital. It was Bill on real world scenarios that I just kind of, like merged together. So I would say up front things that I would say that were important to talk about and that we're, you know, cyber security awareness training. I'm making sure people you know are understand. Like the risks involved with female security advance like modern and point protection. We kind of touched on that a little earlier. So, like older, signature based detection is just not not really effective anymore. Um, having a good tamper proof backup strategy is important, too. So let's say, like, systems get ransomware it. Everything's encrypted, like you need a way to restore that data without necessarily paying the ransom on DH like tamperproof backups >> are are the way to do that. Really? So >> all right, that I want to give you the final word. Uh, w t g transform 2019 gives a little inside some of the customers you're talking to. Some of the top of mine, diffuse or any. I don't work >> for me. A lot of the top mine issues around security seriously, but also like modernizing People's Data Center so that delivering on the hybrid cloud message of like installing hardware and software that not just provides, like data storage services on Prem but could do a lot of cloud tearing >> cloud archiving. Also >> because last, we really appreciate the updates. Thank you. Money for Sarah. We're all initiated. I want to thank our audience here. We've had a full day here. Got to talk to some of the users, some of the partners and, of course, our host for the event. Winslow Technology Group. Scott Winslow and the team. Great to see the growth. Always love to be able to dig in with the users and what's happening locally for myself, stupid. And want to thank the whole team here at the Cube for helping us to be ableto support these events and be sure to check out the cute dot net. You could do some searches there. You could find all the guests here and see previously what they've been talking about. See what future events were going out and dig their archive and is always if you have any questions, feel free to reach out myself, the rest of the team and always a pleasure to be able to share with you and thank you for watching.
SUMMARY :
It's the queue covering W So, you know, showing your own individual style for, like, the Ted talk. No, the pellet side, you know, picking up the servers and some of the other pieces. That's like the simplified version of it. You know, if I go back, you know, let's say 5 to 10 years ago, it was, Yeah, so there's a lot in terms of like planning. We're simplifying maybe the delivery of We're no longer just, you know, let's lock the door and Hafiz of Security and put like the end point a little bit less important, despite the fact that even when you have things like server list, One of the reasons people do go to the cloud is for security, In that case, You know, one of the things we know is that what you need to do I'm not patching the system's anymore because we'll just assume that, you know, eight of us Microsoft. You know, I was talking to Arctic wolf in a typical customer, you know, doesn't have their whole security But, like you might not want them being the ones also doing like your vulnerability assessments. So, uh, you know, So I come up here. Yeah, that's that's the one you if not like the tech hub of the East Coast. Okay, Well, you know I'm all in favor of things where I could take the trainer drive to rather you know, cyber security awareness training. are are the way to do that. all right, that I want to give you the final word. but also like modernizing People's Data Center so that delivering on the hybrid cloud message of the rest of the team and always a pleasure to be able to share with you and thank you for watching.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Matt Kozlowski | PERSON | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Connecticut | LOCATION | 0.99+ |
Matt Kozloski | PERSON | 0.99+ |
Austin | LOCATION | 0.99+ |
San Francisco | LOCATION | 0.99+ |
2019 | DATE | 0.99+ |
Hartford | LOCATION | 0.99+ |
Sarah | PERSON | 0.99+ |
Microsoft | ORGANIZATION | 0.99+ |
Boston | LOCATION | 0.99+ |
United States | LOCATION | 0.99+ |
three | QUANTITY | 0.99+ |
Winslow Technology Group | ORGANIZATION | 0.99+ |
Boston, Massachusetts | LOCATION | 0.99+ |
Scott Winslow | PERSON | 0.99+ |
Winslow Technology Group | ORGANIZATION | 0.99+ |
next week | DATE | 0.99+ |
Yankees Red Sox | ORGANIZATION | 0.99+ |
One | QUANTITY | 0.99+ |
four years | QUANTITY | 0.99+ |
Windows | TITLE | 0.99+ |
third year | QUANTITY | 0.99+ |
Second time | QUANTITY | 0.99+ |
less than a year | QUANTITY | 0.99+ |
eight | QUANTITY | 0.99+ |
Matt | PERSON | 0.98+ |
first | QUANTITY | 0.98+ |
Data Center | ORGANIZATION | 0.98+ |
East Coast | LOCATION | 0.98+ |
5 | DATE | 0.97+ |
second tie | QUANTITY | 0.96+ |
under 18 minutes | QUANTITY | 0.96+ |
today | DATE | 0.96+ |
one | QUANTITY | 0.96+ |
couple of years ago | DATE | 0.95+ |
one drive | QUANTITY | 0.95+ |
both city | QUANTITY | 0.94+ |
1st 1 | QUANTITY | 0.93+ |
Cube | ORGANIZATION | 0.93+ |
Azure | TITLE | 0.91+ |
CIS | ORGANIZATION | 0.91+ |
two kind | QUANTITY | 0.91+ |
10 years ago | DATE | 0.9+ |
Cuban | OTHER | 0.9+ |
this morning | DATE | 0.86+ |
Prem | ORGANIZATION | 0.81+ |
last couple years | DATE | 0.81+ |
four level | QUANTITY | 0.81+ |
first vest | QUANTITY | 0.79+ |
Winslow | TITLE | 0.79+ |
Tio | PERSON | 0.72+ |
every two years | QUANTITY | 0.71+ |
about years ago | DATE | 0.71+ |
24 7 | QUANTITY | 0.71+ |
Lennox | ORGANIZATION | 0.69+ |
Stew Minutemen | PERSON | 0.68+ |
about 12 | QUANTITY | 0.67+ |
1/3 | QUANTITY | 0.65+ |
Ted | TITLE | 0.65+ |
Bill | PERSON | 0.64+ |
W. T. G. | PERSON | 0.62+ |
Winslow | ORGANIZATION | 0.59+ |
Arctic | LOCATION | 0.57+ |
WTG | ORGANIZATION | 0.52+ |
once | QUANTITY | 0.5+ |
W | PERSON | 0.49+ |
Tuesday | DATE | 0.48+ |
Brook | ORGANIZATION | 0.31+ |
T. | EVENT | 0.3+ |
Patrick Osborne, HPE | VeeamON 2018
(upbeat electronic music) >> Announcer: Live from Chicago, Illinois, it's theCUBE, covering Veeamon 2018. Brought to you by Veeam. >> Welcome back to Chicago everybody, the Windy City, you're watching theCUBE, the leader in live tech coverage and we're here day two at Veeamon 2018, theCUBE's second year doing Veeamon, and I'm Dave Vellante, with my cohost, Stu Miniman. Patrick Osborne is here, the newly minted VP and GM of big data and secondary storage. >> And CUBE alumni. >> HPE and many time CUBE alumni, did you get a sticker? >> Yeah, it's already on my laptop. >> Oh, awesome, great to see you again. >> Good to see you guys. >> Thanks so much for coming on, always fun at Veeamon. >> Yep. >> They have a big presence. Your show, HPE Discover, they painted the Chi-Town green. >> Patrick: Yep. >> What's going on at the show for you guys? >> So a huge partner for us, in our ecosystem, as you guys know, HPE and the world of virtualized workloads, like, you know, we definitely own the space in terms of the number of Veeams sitting on our infrastructure and they are a great partner. You know, we've got thousands of customers, and I think what we're seeing, too, is that as Veeam grows up into the midsize and enterprise space, that is, you know, that's where our wheelhouse is. And so we're getting a lot of customer interactions in that space, and then, with some of our offerings around Nimble and SimpliVity, where they play very well in the commercial segments, that's a great way for us to go grab new logos, be present in the channel. So it's a really good partnership for us on both ends. >> I definitely want to understand what's going on in big data, but before we get there, let's talk a little bit about secondary storage and your point of view there. We know that data protection is moving way up on the list of CXO priorities, we also know there's a dissonance in the customer base, between the expectations of how much automation is actually there from the line of business, versus what IT can deliver. >> Patrick: Yeah, yeah. >> And so there's this gap and now you have multi-cloud coming on in a big way, digital transformation, and so it feels like backup and recovery and data protection is transforming. Throw in security and it even complicates it further. What's your point of view on what's going on in this mix? >> Well, certainly the sands are shifting in the secondary storage market. I think because of a heightened customer expectation in this area, whether it's, you know, I want to do more with my data, running things that we do at Veeam, like test data, automation, Sandboxing, security, you know, ransomware. All those are higher level data services than just what people were doing in the past around backup and recovery. So for us, we're really focused a lot on automation right in this space. The death of backup and recovery in that traditional space is essentially caused by comPlexxity, right? So automate or die in this space, nobody wants to deal with backup, right? What you want is outcomes, and what we're doing is, for our product line, we've got sort of this three-tiered mantra, of predictive, cloud-ready and timeless. So we want to be able to, through platforms like InfoSite, be able to heavily, heavily automate all those activities. Cloud-ready, because, you know, as we talked before, it's a hybrid world. People, especially in secondary storage, want to have some data on-prem, and certainly a lot of it for archival and retention off-prem. And then, timeless is sort of this scenario around, even though I'm operating a data center, I want the purchasing experience to be elastic, and like, again, the cloud, right? So consumption-based as a service. So that's what we're trying to bring to the market for secondary storage and storage in general. >> Dave: Awesome. >> Patrick, as I look at this space, you talk about that hybrid, multi-cloud world that we talked about. The two big, main things are data and my applications. So you talked a bit about the data, connect for us, kind of the applications and things, cloud native and 12 factor microservices, versus traditional applications. And you've got that whole spectrum, what are you seeing from your customers and how are you helping them? >> Yeah, so, we're definitely seeing a lot of the tech leading customers in the enterprise from HPE, you know, the big logos, right? They're out there disrupting themselves, disrupting industry, are massively betting on analytics, right? So, they've moved certainly from databases to batch now, it's all, you know, I think people call it fast data, streaming analytics, Kafka, Spark. So we're seeing, that part of our business that HPE's growing, like, non-sequentially, right? So it's really good business for us. But what's going on right now, is that the customers who are doing this, these are all net new apps. Kubernetes, you know, new styles of application, it's not a rip and replace, it's more of an augmentation scenario, where you're providing new services on top of existing apps. So that is very new and I think one of the things we'll see over the next couple of years is, how do I protect those workloads? How do I provide multi-cloud for them? So it's an interesting space, it's very nascent, a lot of tech-heavy investment going on for the, you know, the big players in the market. But that's going to have a long tail into the mid range. >> How will the data protection architecture sort of change for those new emerging applications? You know, maybe IoT is another piece of that. And maybe, where does your partnership with Veeam fit into that? >> Yeah, so we are having a number of strategy discussions on that this morning, you know. And I think that space is, you know, there's a lot of identification that has to go on. Do I want to back it up, do I care? Right, are those persistent streams? Or that IoT data that's coming in, do I really have to back it up at the end of the day or can I back up the results? So, a lot of it is not just an availability issue, it's certainly a data management issue. But a lot of the tools that we would need to do that, today, they're focused on bare-metal, VM wear, virtualization, a lot of stuff that hasn't been written yet, right? So I think there's a lot of actual tech development that has to go on in this space and I think we're kind of poised together as partners to deliver in that area the next couple years. >> You guys have this tagline, "We Make Hybrid IT Simple." >> Patrick: Yes. >> IT, you know-- >> Patrick: Very quantifiable. >> It ain't simple. (laughter) So, where does storage fit into that equation? >> Yeah, the stats that blow my mind was, I think IBC came out with this, was that there's essentially around 500 million apps in the data center today. And then, in any sort of spectrum of bare-metal, being virtualized, maybe being containerized, in the next four years there's going to be 500 million net new apps, right? So that's like, it's mind blowing, in terms of, most people have a flat budget, maybe a little increase. So you think that you're doubling the amount of apps you have and all the services around it. So for us, the automation piece is absolutely key, right? So anything we can do with InfoSite as a platform, we're going to be extending that to other products, you see we've done it for 3PAR, we'll be bringing that experience. But anything we can do around automation, analytics, that's going to take a lot of the mystery and comPlexxity out of managing these apps and services, I think is a win for the customers, and that's why they're going to buy into the platforms. >> Yeah, it's like, imagine if you're a young family, you've got two kids and you have twins. >> Patrick: Yeah. (laughter) >> Uh-oh. (laughs) >> Or you decide to have two more, like I did. (laughter) >> Patrick, we've been talking about intelligence in the storage world for decades. >> Yes. >> Why is it real, you know, more real and different now, than it was in some of the previous generations? >> Yeah, I think, you know, some of the techniques... So, we've had systems that have called home and brought telemetry home forever, right? But I think what's going on is that, as you take the tools that we've developed, and a lot of them are new, right, that are allowing you to do this, it's the practition of the data science, which is like the key, at the end of the day. InfoSite is an amazing piece of technology, a lot of the magic is in the way that you set up your teams, and to be able to take that on, right? So, it's no longer a product manager, an engineering guy, support person in a different organization, right? What we have is what's called a peak team, right? Which just takes all the functions, brings them together with a data scientist, to be able to take a look at, how can I do machine learning, AI, a more predictive model, to actually take use of this data, right? And I think the techniques and the organizational design is the big change that's happened over the last couple of years. Data's always been there, right? But now we know what to do with that. >> Yeah, and like you said before, the curve is reshaping, it's not this linear Moore's Law curve anymore. >> Patrick: Yeah. >> It's this exponential curve. >> Patrick: Exactly. >> I can't even draw it anymore you know, it used to be easy, just put the dotted line straight out, now it's twisting. So, that increases the need obviously, for automation. Now talk about how HPE's automation play is differentiable in the marketplace. >> So I think a couple of things from a differentiated perspective. Obviously we talked a lot about InfoSite as a platform, as a portfolio company, we're definitely trying to take out the friction, in terms of the deployment and automation of some of these big data environments. So our mission is to be able to, like you would stand up some analytic workloads in the public cloud, to provide that same experience, on-prem, right? And essentially be the broker for that user experience. So that's an area that we're going to differentiate, and then, you know, in general, there's not that many mega portfolio companies, right, anymore. And I feel like, that we're exploiting that for our customers, bringing together compute networking and storage. And certainly on the automation side. So you know, for us, I really feel that you're no longer going to be buying on horizontal lines anymore. You know, best of breed servers, best of breed networking, best of breed storage, but bringing together a complete, vetted stack for a set of workloads, from a vendor like HPE. >> Yeah, and it was just announced, the deal's not closed yet, but just to mention to the audience, HPE just made an acquisition of Plexxi, a networking specialist-- >> Patrick: Yeah, a good friend, too, Rich Napolitano. >> Rich Napolitano. Just this week, which is interesting, because that brings cloud scale to some of the hyperconvergence infrastructure. It's essentially hyperconverge networking, so really interested to see how that plays out. HPE has made a number of really effective acquisitions over the last several years, starting really with 3PAR, was the one. Clearly Aruba, you know, the Nimble acquisition, you know, SimpliVity, so, SGI. So some really strong, both tactical and strategic moves for HPE, really interested to see how Plexxi sorts out. Okay, we got to talk sports for a minute. I asked Peter McKay this question, I asked his boss, some sports fans, if you were Robert Kraft, would you have traded Tom Brady? >> (sharp inhale) No. >> No way? >> No way, no way. >> Okay, that's consistent with McKay. >> Yeah, no way, that's like trading Montana, that didn't work out. >> That did work out, right? They traded Montana, then they won another Superbowl. >> Yeah, I know, I mean, I think, for me, he's an icon and then he's still operating at maximum efficiency, which is amazing, but I think he got a lot of legs in him. >> What do you think of the... Well hopefully he stays, hopefully he does play 'til 45. What do you think of the Garoppolo trade, though? Are you disappointed that they didn't get more, or do you think it was the right move to hang on, just in case Brady went down again? >> I think it's the right move at the end of the day, right? You're not going to get much from him anyways, and they're certainly not going to pay him out as a backup quarterback. What I don't like, though, is the fact that he's gone to the 49ers, and that's where most of my engineering team is in the Bay Area. So, to have to deal with yahoo 49ers fans, you know, for the next couple years, is going to be painful. But it's good, it's a good renewed rivalry. >> So you're not a-- >> Celtics, Warriors, you know, Patriots, Niners. >> You're not an instant transplanted 49ers fan, because of Garoppolo, right? >> Patrick: No, absolutely not. >> He's a carpet-bagger, right? >> He's out, he's off the team, he's out of the house. >> I love it, okay, Bruins were a big disappointment this year. >> Yeah, yeah. >> We thought that, you know, the Celtics were super exciting, let's go there, I mean. You know, you watched the Celtics early in the year, 'cause your like, after Hayward went down, you're like, kind of' we were all walking around like this. And then you-- >> I felt like, it's like where Kennedy was shot, right? I know exactly where I was, right? >> Right, and you had people blaming Danny Ainge for, like, making a move, I'm like, come on, guys. And you see what happened with the young players, and then they sort of tailed off a little bit, they were struggling, you know, Ky was trying to find his way and now they're the exciting team. Up to on Cleveland, I mean, you got to believe that Lebron is going to step up his game with a little home cooking. But let's assume for a second that they get by Cleveland (laughs) which will be a huge task. I mean, I don't think there's anybody in the NBA who can stop Kevin Durant, but I'd love to see Marcus Smart try. >> So two things in that scenario. One is that, who needs Kyrie Irving more right now, Cleveland or Boston, right? (laughter) Which is amazing, can you imagine saying that a couple months ago? It blows my mind. And then, for me, it's a revamping of the NBA, right? If you get the Celtics versus the Warriors in that style of play, I mean, it's definitely, it's changed the whole game, right? Shooting guards, ballers, I think it's fantastic to see, you know, a whole new style of play in the NBA. >> It's so exciting to see the Celtics back in. >> Team basketball, defense, passing, all of it, it's great. >> And ESPN is losing their minds, they don't know what to do. Stephen A Smith doesn't know what to say. >> Patrick: ESPN Live. >> He's actually pissed I think, yeah. (laughter) So, now, Stu, you're a Yankees fan, of course, and you know my line on the Yankees. Stu's kind of a weekend Yankees fan. My line on the Yankees is, that sucks you can't beat us in April. (laughs) Here it is in May. >> Dave, I'm just quiet around you, because I know where my paycheck comes from. >> I appreciate that perspective, Stu, okay. >> Patriots win, we're in agreement. >> Think about all these renewed rivalries, it's great. Celtics, Sixers, Red Sox, Yankees, it's unbelievable. >> And like I said, San Francisco-- >> Patrick: Phillies! >> And the Pats. >> The Pats! >> Well Patrick, always a pleasure seeing you, thanks for making time out of your busy schedule. >> Yeah, absolutely, it was great. >> For coming on theCUBE. Alright, keep it right there everybody, we'll be back with our next guest, right after this brief break. You're watching theCUBE, Live from Veeamon 2018. (upbeat electronic music)
SUMMARY :
Brought to you by Veeam. Patrick Osborne is here, the newly minted VP and GM Your show, HPE Discover, they painted the Chi-Town green. and enterprise space, that is, you know, in the customer base, between the expectations of how much And so there's this gap and now you have multi-cloud in this area, whether it's, you know, So you talked a bit about the data, it's all, you know, I think people call it fast data, And maybe, where does your partnership And I think that space is, you know, So, where does storage fit into that equation? So you think that you're doubling the amount Yeah, it's like, imagine if you're a young family, (laughs) Or you decide to have two more, like I did. in the storage world for decades. a lot of the magic is in the way that you set up your teams, Yeah, and like you said before, the curve is reshaping, I can't even draw it anymore you know, it used to be easy, So our mission is to be able to, like you would stand up Patrick: Yeah, a good friend, too, Clearly Aruba, you know, the Nimble acquisition, that didn't work out. That did work out, right? Yeah, I know, I mean, I think, for me, What do you think of the... So, to have to deal with yahoo 49ers fans, you know, I love it, okay, Bruins were a big disappointment We thought that, you know, Up to on Cleveland, I mean, you got to believe that Lebron you know, a whole new style of play in the NBA. And ESPN is losing their minds, and you know my line on the Yankees. because I know where my paycheck comes from. Celtics, Sixers, Red Sox, Yankees, it's unbelievable. thanks for making time out of your busy schedule. we'll be back with our next guest,
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Danny Ainge | PERSON | 0.99+ |
Patrick | PERSON | 0.99+ |
McKay | PERSON | 0.99+ |
Dave | PERSON | 0.99+ |
Dave Vellante | PERSON | 0.99+ |
Peter McKay | PERSON | 0.99+ |
Robert Kraft | PERSON | 0.99+ |
Yankees | ORGANIZATION | 0.99+ |
Rich Napolitano | PERSON | 0.99+ |
Kennedy | PERSON | 0.99+ |
Brady | PERSON | 0.99+ |
HPE | ORGANIZATION | 0.99+ |
Celtics | ORGANIZATION | 0.99+ |
Kevin Durant | PERSON | 0.99+ |
two kids | QUANTITY | 0.99+ |
Kyrie Irving | PERSON | 0.99+ |
Patrick Osborne | PERSON | 0.99+ |
Sixers | ORGANIZATION | 0.99+ |
Stu Miniman | PERSON | 0.99+ |
Veeams | ORGANIZATION | 0.99+ |
Red Sox | ORGANIZATION | 0.99+ |
Veeam | ORGANIZATION | 0.99+ |
IBC | ORGANIZATION | 0.99+ |
Patriots | ORGANIZATION | 0.99+ |
Stephen A Smith | PERSON | 0.99+ |
Tom Brady | PERSON | 0.99+ |
Marcus Smart | PERSON | 0.99+ |
Garoppolo | PERSON | 0.99+ |
CUBE | ORGANIZATION | 0.99+ |
Stu | PERSON | 0.99+ |
ESPN | ORGANIZATION | 0.99+ |
April | DATE | 0.99+ |
Bay Area | LOCATION | 0.99+ |
Ky | PERSON | 0.99+ |
May | DATE | 0.99+ |
two | QUANTITY | 0.99+ |
yahoo | ORGANIZATION | 0.99+ |
Lebron | PERSON | 0.99+ |
Warriors | ORGANIZATION | 0.99+ |
Plexxi | PERSON | 0.99+ |
SGI | ORGANIZATION | 0.99+ |
Hayward | PERSON | 0.99+ |
Nimble | ORGANIZATION | 0.99+ |
second year | QUANTITY | 0.99+ |
Chicago | LOCATION | 0.99+ |
Niners | ORGANIZATION | 0.99+ |
twins | QUANTITY | 0.99+ |
49ers | ORGANIZATION | 0.99+ |
around 500 million apps | QUANTITY | 0.98+ |
One | QUANTITY | 0.98+ |
3PAR | ORGANIZATION | 0.98+ |
Cleveland | ORGANIZATION | 0.98+ |
Boston | ORGANIZATION | 0.98+ |
this week | DATE | 0.98+ |
Aruba | ORGANIZATION | 0.98+ |
12 factor | QUANTITY | 0.98+ |
Superbowl | EVENT | 0.98+ |
Spark | TITLE | 0.97+ |
both ends | QUANTITY | 0.97+ |
Windy City | LOCATION | 0.97+ |
two things | QUANTITY | 0.97+ |
Veeamon | ORGANIZATION | 0.97+ |
Dante Orsini, iland | VeeamOn 2018
>> Announcer: Live from Chicago, Illinois, it's theCUBE! Covering VeeamON 2018. Brought to you by Veeam. >> Welcome back to Day Two of VeeamON 2018 in Chicago. My name is Dave Vellante, and I'm here with Stu Miniman. You're watching theCUBE, the leader in live tech coverage. Dante Orsini is here. He's the Senior Vice President of Biz Dev at iland. CUBE alum. Good friend of theCUBE. Great to see you again. >> Great to see ya. >> Thanks for coming on. >> Yeah, thanks for having me. >> What's happening with iland these days, in the world of cloud service providers? >> Well Dave, it's been insane for us. Obviously Veeam's a huge partner of ours. We've been working together for what, seven years now I think. And it's just amazing to see the growth of this company. Right? We've integrated Veeam -- our relationship. We started off basically providing managed backup many, many moons ago. But six years ago we started to build our own platform, on top of Veeam, on top of Cisco, on top of HPE. Customers really wanted to see more control. They wanted greater levels of security. They really wanted a true enterprise cloud. To do that we had to enhance the VMware stack. We had chose to take Veeam and integrate them via their API. Today if somebody deploys anything in the world with iland, it's automatically backed up by Veeam. If you fast forward a bit, as you see what Veeam's done to innovate with cloud and multi cloud, they've really helped build our business. >> Dante, if you go and look back before the whole cloud wave, the typical service provider. They would have one of everything. You'd walk down the aisles and there'd be whatever it was. An EMC box. A digital box. Whatever it was. Did virtualization change that? Were you able to consolidate? Create a platform. Create a simpler environment to manage. Or is there still a lot of bespoke infrastructure lying around? >> Yeah, that's a great question. For us, I'd love to tell you we hit it right the first time twelve years ago. But no. Just like you said. There's all sorts of different technologies right? But I think what we've done is we quickly standardized. We leverage Cisco UCS from a compute perspective. We leverage some of their storage platforms for the things that we do with Veeam Cloud Connect Backup. We actually help them drive the validation of that product before it came to market. We operate at scale with them. Same thing with Veeam. We're their the largest cloud provider in the world right now. As far as leveraging Veeam technologies. In addition to that on the storage front, we also because of the demands of the environment, we really want to deliver a secure cloud service. Encryption is table stakes, and has been for years. HPE Nimble plays a critical role for us there. That's really our stack. Cisco from a network and a compute perspective, VMware with the hypervisor, and HPE from a storage perspective. >> It's sounds like you've taken some very cost effective platforms. Nimble, Veeam, etc. And then architected an enterprise class solution. You guys are adding value around that as an integrator and obviously a service provider. >> Yup, correct. And I think the market is demanding more and more from a cloud provider. People want true transparency. They want control over the infrastructure. For us it's like, how can we develop an API? So we can make this platform extensible. And then still work with the customers that are struggling with the promise of cloud. And Stu, you see this all the time, right? >> Yeah, and Dante, one of the things we're discussing here is it's a very hybrid world. As Veeam said, customers are doing lots of SAAS. They're using service providers. They have their own data centers. They're using a few public clouds. One of the things I've been watching real closely is companies like iland and the other cloud service providers Amazon and Microsoft aren't the enemy anymore. It's, well we actually have to partner with them on some services. We do some things locally. Maybe give us your viewpoint on how that's changed in the last couple of years. >> Yeah, great question. I would tell you that we're not quite there yet, Stu. From my perspective. You guys know, we're known best for providing disaster recovery as a service. That's where we've made a name in the space. But the irony is we've really focused on building this cloud infrastructure. So an I as platform. And ironically that's the majority of our revenue. When we look at public, clearly it is a hybrid world. Where we spend a lot of time, is investing in how can we highly automate the integration? Because we know that people are going to have workloads everywhere. The idea is, think about it from a recovery perspective. If I'm protecting your traditional workloads. And you've got a dev team that's using various different services that are proprietary to a public cloud, that stuff's got to talk to each other in a true resiliency capacity. We wanted to make sure that people could actually highly automate and orchestrate a failover to us, a test to us. But also integrate the connectivity portion of that. Right? Making sure that all these things can talk together is important. You understand as well as I do, as these cloud architectures change, become more modern, and they're more service driven. The traditional, I'm going to move from point A to point B is no longer in play. It's how can I have more diversity amongst my vendor base? If I'm using containers. You've got a globally distributed architecture. If I can deploy some of that with iland, and some of that maybe using Kubernetes, that gives me diversity for recovery. >> Dante, you've hit one of the key things we've been as an industry struggling with. That pace of change is just so rapid. How do you internally deal with that pace of change? As to I architected something today, and tomorrow there's something new. Tell us what you're hearing from your customers as to how they make their decisions and sort through this constantly changing Rubrik? >> Well it's definitely insane. We see all sorts of various different use cases, depending on the industry. And that pressure to innovate at the speed of light is, really people struggle with it. I think from our perspective, there's a couple things that we're doing. One, we actually wrote our own assessment application. We call it iland Catalyst. This was really designed to help both our customers as well as our partners. Cause we go to market through a lot of partners as well, to help streamline this pre-sales process for a customer. Again, we focus squarely on the VMware infrastructure stack. Being able to pull an inventory of what somebody has in their environment. And then go through and select resource pools and VM's, for whatever the purpose. Whether they're looking to work and shift workloads. Or whether they're looking to protect them from a backup or DR perspective, we're able to mitigate all the challenges associated with that. To your point. As people are looking at cloud, it's like okay. Is this cloud thing real? And how's it apply to my business? What can I really do with this? And by the way, I got to deal with my budget also. What's this stuff cost? We've got some really smart people. But you can't scale our smartest people globally. We wanted to really drive that into an application. It's really helped get people to outcomes much quicker. So do it right first. >> Dante, if you reverse back a few years ago, VMware was calling Amazon a book seller. Amazon was calling guys like VMware the old guard. The old way. They kissed and hugged last year. You must've loved that first of all. Because it was like, great, VMware specialist. We'll just drive truck through that opportunity, because we get service provision, cloud, VMware stack, boom. Now fast forward. They've got this little kumbaya thing going on. How do you now differentiate from that? >> Yeah, that's a great question. First of all, VMware, obviously a very strategic partner. I think they've got a long road ahead of them. On some of the things that they're doing. I think the promise of where they're going is great. But I still think there's a lot of folks that struggle with the idea. Think about co-mingling my traditional workloads. And then trying to integrate cloud native services on top of it. I think it's a tall order. We'll see where it goes. We're keeping a close eye on it. But in the interim for us, we continue to see folks that are saying, look I want to get out of the data center business. I've built my data center on VMware. I need to have much greater levels of control and visibility. And you need to make this easy on me. From that perspective, we've been able to do really, really well. We work with a lot of service providers that are looking for that level of a consultative approach. But also want to realize the benefits of a cloud. The point being is, I want a great cloud but it needs to be enterprise class. And I also need to know that I might need help architecting that migration. >> Well that's the key, right? You're not going to get that from an Amazon. They're not going to come into your shop. They're not going to hold your hand through it. They're not going to help you build the architecture route. And help you manage it on an ongoing basis. >> Dante, it's May 2018, so I'd be remiss if I didn't ask about GDPR. >> Hey Stu, I love you man! This is great. You guys know we operate globally, and have for over a decade. GDPR we were way out in front of this. I'm not sure if you follow, The BSI just came out with a new standard. 10012, I believe. I think our Compliance and DPO Officer would be pretty proud of me for remembering that one. >> Dave: I'm proud of ya. >> It's tailor made for GDPR. We've been pre-certified, one of four companies that did it. We do a ton in the security side and the compliance side. And I know they go hand in hand. We went through a global audit last year. On the back of some of the ISO work we do with the CSA, the Cloud Security Alliance. And actually came out with a gold star certification. Sounds juvenile, right? A gold star, woo hoo! But it's a big deal. Only iland and Microsoft have actually achieved that level of certification. Yeah. On the compliance side we're way out in front of GDPR. We're doing a lot from a thought leadership perspective in educating both the partners and the marketplace. I think it's going to see what happens with Brexit also. I think you'll see the rest of the world kind of find their way to their own type of regulation. >> What do all those acronyms mean for your customers in terms of GDPR compliance? How does that turn into value for them, and make their life easier? Can you explain? >> I think right now the whole market's been in my opinion has been ill prepared for this. You see a lot of people scrambling. Being able to identify what data is going to fall under that regulation. How you treat the data. How you're able to account for the data. And also destroy the data. And validate that. Is frankly I see some of the biggest sweeping change in marketing. I see marketing people really scrambling. Because they have to make sure that they double-opt in. Cause the fines for breaching this are unbelievable. I think you're going to see the regulators make an example out of certain people. >> No doubt. >> Quickly. >> There's going to be some examples. They're going to go after the guys with deep pockets first. But the fines are... What are the fines? Four, is it 10% of the turnover? No, 4% of turnover. >> 4% of your previous year's turnover. >> Which is insane. >> Yep, yep. >> That's going to hurt. >> Or something like 20 million pounds, something like that. >> Which ever is greater. >> Which ever is greater. Yes! Yes, exactly. Yup. >> It's pretty onerous. Dante, VeeamON 2018, we'll give you closing thoughts. >> Fantastic event, right. Just super appreciative for our relationship with Veeam. They've been behind us. They've been behind this whole cloud provider community. I mean guys, you know this. Raat Mere and team had the ability to go take this stuff to a public cloud many moons ago. They chose to enable a managed cloud provider market first. We are very grateful for that. >> Awesome. Hey thanks so much for coming on theCUBE. Great to see you. >> My pleasure. >> As always. >> Yup, go Yankees! >> Oh whoa, time out. >> Go Yankees. >> While we're on the topic. Listen, you can't beat the Red Sox in April. Okay, you know that, right? >> Yeah, here we go. >> So it's going to be interesting to see. I mean I have predicted the Yankees take the east, and they go to the World Series. But you got to be excited as a Yankees fan. >> Could be a good year. >> I've always liked Brian Cashman. I think he's one of the best GM's in the business. Watch his moves at the trading deadline. He's going to beef up the bullpen. I hope the Sox can hang tough with him because anything can happen. >> It's true, anything can happen. >> Hey, great to see ya. >> Great to see you guys, thank you. >> Go Sox. >> Dig it. >> Keep it right there everybody. We'll be back with our next guest right after this short break.
SUMMARY :
Brought to you by Veeam. Great to see you again. And it's just amazing to see Create a simpler environment to manage. for the things that we do And then architected an And I think the market is demanding One of the things I've been And ironically that's the as to how they make their decisions And that pressure to innovate like VMware the old guard. And I also need to know that They're not going to help you Dante, it's May 2018, I think our Compliance and DPO Officer I think it's going to see And also destroy the data. Four, is it 10% of the turnover? Or something like 20 million Which ever is greater. we'll give you closing thoughts. Raat Mere and team had the ability Great to see you. the Red Sox in April. and they go to the World Series. I hope the Sox can hang tough with him We'll be back with our next guest
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Microsoft | ORGANIZATION | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Dave Vellante | PERSON | 0.99+ |
Dante Orsini | PERSON | 0.99+ |
Dave | PERSON | 0.99+ |
Red Sox | ORGANIZATION | 0.99+ |
Cisco | ORGANIZATION | 0.99+ |
May 2018 | DATE | 0.99+ |
Dante | PERSON | 0.99+ |
Brian Cashman | PERSON | 0.99+ |
Cloud Security Alliance | ORGANIZATION | 0.99+ |
Stu Miniman | PERSON | 0.99+ |
iland | ORGANIZATION | 0.99+ |
Chicago | LOCATION | 0.99+ |
10% | QUANTITY | 0.99+ |
Stu | PERSON | 0.99+ |
April | DATE | 0.99+ |
tomorrow | DATE | 0.99+ |
Yankees | ORGANIZATION | 0.99+ |
VMware | ORGANIZATION | 0.99+ |
Veeam | PERSON | 0.99+ |
CSA | ORGANIZATION | 0.99+ |
Veeam | ORGANIZATION | 0.99+ |
last year | DATE | 0.99+ |
World Series | EVENT | 0.99+ |
seven years | QUANTITY | 0.99+ |
Nimble | ORGANIZATION | 0.99+ |
Sox | ORGANIZATION | 0.99+ |
20 million pounds | QUANTITY | 0.99+ |
Chicago, Illinois | LOCATION | 0.99+ |
iland | LOCATION | 0.99+ |
GDPR | TITLE | 0.99+ |
4% | QUANTITY | 0.99+ |
one | QUANTITY | 0.99+ |
Today | DATE | 0.99+ |
Brexit | EVENT | 0.99+ |
both | QUANTITY | 0.99+ |
six years ago | DATE | 0.99+ |
today | DATE | 0.99+ |
One | QUANTITY | 0.98+ |
Four | QUANTITY | 0.98+ |
four companies | QUANTITY | 0.97+ |
BSI | ORGANIZATION | 0.97+ |
Biz Dev | ORGANIZATION | 0.97+ |
10012 | OTHER | 0.96+ |
twelve years ago | DATE | 0.96+ |
theCUBE | ORGANIZATION | 0.92+ |
ISO | ORGANIZATION | 0.92+ |
few years ago | DATE | 0.91+ |
first time | QUANTITY | 0.9+ |
point B | OTHER | 0.9+ |
First | QUANTITY | 0.89+ |
2018 | DATE | 0.89+ |
Cisco UCS | ORGANIZATION | 0.89+ |
Day Two | QUANTITY | 0.88+ |
VeeamON 2018 | EVENT | 0.87+ |
Vitaly Tsivin, AMC | Machine Learning Everywhere 2018
>> Voiceover: Live from New York it's theCUBE, covering Machine Learning Everywhere: Build Your Ladder to AI. Brought to you by IBM. (upbeat techno music) >> Welcome back to New York City as theCUBE continues our coverage here at IBM's Machine Learning Everywhere: Build Your Ladder to AI. Along with Dave Vellante, I'm John Walls. We're now joined by Vitaly Tsivan who is Executive Vice President at AMC Networks. And Vitaly, thanks for joining us here this morning. >> Thank you. >> I don't know how this interview is going to go, frankly. Because we've got a die-hard Yankee fan in our guest, and a Red Sox fans who bleeds Red Sox Nation. Can you guys get along for about 15 minutes? >> Dave: Maybe about 15. >> I'm glad there's a bit of space between us. >> Dave: It's given us the off-season and the Yankees have done so well. I'll be humble. Okay? (John laughs) We'll wait and see. >> All right. Just in case, I'm ready to jump in if we have to separate here. But it is good to have you here with us this morning. Thanks for making the time. First off, talk about AMC Networks a little bit. So, five U.S. networks. You said multiple international networks and great presence there. But you've had to make this transition to becoming a data company, in essence. You have content and you're making this merger in the data. How has that gone for you? And how have you done that? >> First of all, you make me happy when you say that AMC Networks have made a transition to be a data company. So, we haven't. We are using data to help our primary business, which is obviously broadcasting our content to our viewers. But yes, we use data to help to tune our business, to follow the lead that viewers are giving us. As you can imagine, in the last so many years, viewers have actually dictating how they want to watch. Whether it's streaming video rather than just turning their satellite boxes or TV boxes on, and pretty much dictating what content they want to watch. So, we have to follow, we have to adjust and be at the cutting edge all for our business. And this is where data come into play. >> How did you get there? You must have done a lot of testing, right? I mean, I remember when binge watching didn't even exist, and then all of a sudden now everybody drops 10 episodes at once. Was that a lot of A-B testing? Just analyzing data? How does a company like yours come to that realization? Or is it just, wow, the competition is doing it, we should too. Explain how -- >> Vitaly: Interesting. So, when I speak to executives, I always tell them that business intelligence and data analytics for any company is almost like an iceberg. So, you can actually see the top of it, and you enjoy it very much but there's so much underwater. So, that's what you're referring to which is that in order to be able to deliver that premium thing that's the tip of the iceberg is that we have to have state of the art data management platforms. We have to curate our own first by data. We have to acquire meaningful third party data. We have to mingle it all together. We have to employ optimization predictive algorithms on top of that. We have to employ statistics, and arm business with data-driven decisions. And then it all comes to fruition. >> Now, your company's been around for awhile. You've got an application -- You're a developer. You're an application development executive. So, you've sort of made your personal journey. I'm curious as to how the company made its journey. How did you close that gap between the data platforms that we all know, the Googles, the Facebooks, etc., which data is the central part of their organization, to where you used to be? Which probably was building, looking back doing a lot of business intelligence, decision support, and a lot of sort of asynchronous activities. How did you get from there to where you are today? >> Makes sense. So, I've been with AMC Networks for four years. Prior to that I'd been with Disney, ABC, ESPN four, six years, doing roughly the same thing. So, number one, we're utilizing ever rapidly changing technologies to get us to the right place. Number two is during those four years with AMC, we've employed various tactics. Some of them are called data democratization. So, that's actually not only get the right data sources not only process them correctly, but actually arm everyone in the company with immediate, easy access to this data. Because the entire business, data business, is all about insights. So, the insights -- And if you think of the business, if you for a minute separate business and business intelligence, then business doesn't want to know too much about business intelligence. What they want insights on a silver plate that will tell them what to do next. Now, that's the hardest thing, you can imagine, right? And so the search and drive for those insights has to come from every business person in the organization. Now, obviously, you don't expect them to build their own statistical algorithms and see the results in employee and machine learning. But if you arm them with that data at the tip of their fingers, they'll make many better decisions on a daily basis which means that they're actually coming up with their own small insights. So, there are small insights, big insights, and they're all extremely valuable. >> A big part of that is cultural as well, that mindset. Many companies that I work with, they're data is very siloed. I don't know if that was the case with your firm, maybe less prior to your joining. I'd be curious as to how you've achieved that cultural mindset shift. Cause a lot of times, people try to keep their own data. They don't want to share it. They want to keep it in a silo, gain political power. How did you address that? >> Vitaly: Absolutely. One of my conversations with the president, we were discussing the fact that if we were to go make recordings of how people talk about data in their organization today and go back in time and show them what they will be doing three years from now, they would be shocked. They wouldn't believe that. So, absolutely. So, culturally, educationally, bringing everyone into the place where they can understand data. They can take advantage of the data. It's an undertaking. But we are successful in doing that. >> Help me out here. Maybe I just have never acquired a little translation here, or simplification. So, you think about AMC. You've got programming. You've got your line up. I come on, I click, I go, I watch a movie and I enjoy it or watch my program, whatever. So, now in this new world of viewer habits changing, my behaviors are changing. What have you done? What have you looked for in terms of data and telling you about me that has now allowed you to modify your business and adapt to that. So, I mean, health data shouldn't drive that on a day to day basis in terms of how I access your programming. >> So, good example to that would be something we called TV everywhere. So, you said it yourself, obviously users or viewers are used to watching television as when the shows were provided via television. So, with new technologies, with streaming opportunities, today, they want to watch when they want to watch, and what they want to watch. So, one of the ways we accommodate them with that is that we don't just television, so we are on every available platform today and we are allowing viewers to watch our content on demand, digitally, when they want to watch it. So, that is one of the ways how we are reacting to it. And so, that puts us in the position as one of the B to C type of businesses, where we're now speaking directly to our consumers not via just the television. So, we're broadcasting, their watching which means that we understand how they watch and we try to react accordingly to that. Which is something that Netflix is bragging about is that they know the patterns, they actually kind of promote their business so we on that business too. >> Can you describe your innovation formula, if you will? How do you go about innovating? Obviously, there's data, there's technology. Presumably, there's infrastructure that scales. You have to be able to scale and have massive speed and infrastructure that heals itself. All those other things. But what's your innovation formula? How would you describe it? So, informally simple. It starts with business. I'm fortunate that business has desire to innovate. So, formulating goals is something that drives us to respond to it. So, we don't just walk around the thing, and look around and say, "Let's innovate." So, we follow the business goals with innovation. A good example is when we promote our shows. So, the major portion of our marketing campaigns falls on our own air. So, we promote our shows to our AMC viewers or WE tv viewers. When we do that, we try to optimize our campaigns to the highest level possible, to get the most out of ROI out of that. And so, we've succeeded and we managed today to get about 30% ROI on that and either just do better with our promotional campaigns or reallocate that time for other businesses. >> You were saying that after the first question, or during responding to the first question, about you saying we're really not ... We're a content company still. And we have incorporated data, but you really aren't, Dave and I have talked about this a lot, everybody's a data company now, in a way. Because you have to be. Cause you've got this hugely competitive landscape that you're operating in, right? In terms of getting more odd calls. >> That's right. >> So, it's got to be no longer just a part of what you do or a section of what you do. It's got to be embedded in what you do. Does it not? Oh, it absolutely is. I still think that it's a bit premature to call AMC Networks a data company. But to a degree, every company today is a data company. And with the culture change over the years, if I used to solicit requests and go about implementing them, today it's more of a prioritization of work because every department in the company got educated to the degree that they all want to get better. And they all want those insights from the data. They want their parts of the business to be improved. And we're venturing into new businesses. And it's quite a bit in demand. >> So, is it your aspiration to become a data company? Or is it more data-driven sort of TV network? How would you sort of view that? >> I'd like to say data-driven TV network. Of course. >> Dave: Okay. >> It's more in tune with reality. >> And so, talk about aligning with the business goals. That's kind of your starting point. You were talking earlier about a gut feel. We were joking about baseball. Moneyball for business. So, you're a data person. The data doesn't lie, etc. But insights sometimes are hard. They don't just pop out. Is that true? Do you see that changing as the time to insight, from insight to decision going to compress? What do you see there? >> The search for insights will never stop. And the more dense we are in that journey the better we are going to be as a company. The data business is so much depends on technologies. So, that when technologies matures, and we manage to employ them in a timely basis, so we simply get better from that. So, good example is machine learning. There are a ton of optimizations, optimization algorithms, forecasting algorithms that we put in place. So, for awhile it was a pinnacle of our deliveries. Now, with machine learning maturing today. We are able or trying to be in tune with the audience that is changing their behavior. So, the patterns that we would be looking for manually in the past, machine is now looking for those patterns. So, that's the perfect example for our strength to catch up with the reality. What I'm hoping for, and that's where the future is, is that one day we won't be just reacting utilizing machine learning to the change in patterns in behavior. We are actually going to be ahead of those patterns and anticipate those changes to come, and react properly. >> I was going to say, yeah, what is the next step? Because you said that you are reacting. >> Vitaly: I was ahead of your question. >> Yeah, you were. (laughter) So, I'm going to go ahead and re-ask it. >> Dave: Data guy. (laughter) >> But you've got to get to that next step of not just anticipating but almost creating, right, in your way. Creating new opportunities, creating news data to develop these insights into almost shaping viewer behavior, right? >> Vitaly: Totally. So, like I said, optimization is one avenue that we pursue and continue to pursue. Forecasting is another. But I'm talking about true predictability. I mean, something goes beyond just to say how our show will do. Even beyond, which show would do better. >> John: Can you do that? Even to the point and say these are the elements that have been successful for this genre and for this size of audience, and therefore as we develop programming, whether it's in script and casting, whatever. I mean, take it all the way down to that micro-level to developing almost these ideals, these optimal programs that are going to be better received by your audience. >> Look, it's not a big secret. Every company that is in the content business is trying to get as many The Walking Deads as they can in their portfolio. Is there a direct path to success? Probably not, otherwise everyone would have been-- >> John: Over do it. >> Yeah, would be doing that. But yeah, so those are the most critical and difficult insights to get ahold of and we're working toward that. >> Are you finding that your predictive capabilities are getting meaningfully better? Maybe you could talk about that a little bit in terms of predicting those types of successes. Or is it still a lot of trial and error? >> I'd like to say they are meaningfully better. (laughter) Look, we do, there are obviously interesting findings. There are sometimes setbacks and we learn from it, and we move forward. >> Okay, as good as the weather or better? Or worse? (laughs) >> Depends on the morning and the season. (laughter) >> Vitaly, how have your success or have your success measurements changed as we enter this world of digital and machine learning and artificial intelligence? And if so, how? >> Well, they become more and more challenging and complex. Like, I gave an example for data democratization. It was such an interesting and telling company-wide initiative. And at the time, it felt as a true achievement when everybody get access to their data on their desktops and laptops. When we look back now a few years, it was a walk in the park to achieve. So, the more complex data and objectives we set in front of ourselves, the more educated people in the company become, the more challenging it is to deliver and take the next step. And we strive to do that. >> I wonder if I can ask you a question from a developers perspective. You obviously understand the developer mindset. We were talking to Dennis earlier. He's like, "Yeah, you know, it's really the data scientists that are loving the data, taking a bath in it. The data engineers and so forth." And I was kind of pushing on that saying, "Well, but eventually the developers have to be data-oriented. Data is the new development kit. What's your take? I mean, granted the 10 million Java developers most of them are not focused on the data per se. Will that change? Is that changing? >> So, first of all, I want separate the classical IT that you just referred to, which are developers. Because this discipline has been well established whether it's Waterfall or Agile. So, every company has those departments and they serve companies well. Business intelligence is a different animal. So, most of the work, if not all of the work we do is more of an R&D type of work. It is impossible to say, in three months I'll arrive with the model that will transform this business. So, we're driving there. That's the major distinction between the two. Is it the right path for some of the data-oriented developers to move on from, let's say, IT disciplines and into BI disciplines? I would highly encourage that because the job is so much more challenging, so interesting. There's very little routine as we said. It's actually challenge, challenge, and challenge. And, you know, you look at the news the way I do, and you see that data scientists becomes the number one desired job in America. I hope that there will be more and more people in that space because as every other department was struggling to find good people, right people for the space, and even within that space, you have as you mentioned, data engineers. You have data scientists or statisticians. And now it's maturing to the point that you have people who are above and beyond that. Those who actually can envision models not to execute on them. >> Are you investigating blockchain and playing around with that at all? Is there an application in your business? >> It hasn't matured fully yet in our hands but we're looking into it. >> And the reason I ask is that there seems to me that blockchain developers are data-oriented. And those two worlds, in my view, are coming together. But it's earlier days. >> Look, I mean, we are in R&D space. And like I said, we don't know exactly, we can't fully commit to a delivery. But it's always a balance between being practical and dreaming. So, if I were to say, you know, let me jump into a blockchain right now and be ahead of the game. Maybe. But then my commitments are going to be sort of farther ahead and I'm trying to be pragmatic. >> Before we let you go, I got to give you 30 seconds on your Yankees. How do you feel about the season coming up? >> As for with every season, I'm super-excited. And I can't wait until the season starts. >> We're always excited when pitchers and catchers show up. >> That's right. (laughter) >> If I were a Yankee fan, I'd be excited too. I must admit. >> Nobody's lost a game. >> That's right. >> Vitaly, thank you for being with us here. We appreciate it. And continued success at AMC Networks. Thank you for having me. >> Back with more on theCUBE right after this. (upbeat techno music)
SUMMARY :
Brought to you by IBM. Build Your Ladder to AI. I don't know how this interview is going to go, frankly. and the Yankees have done so well. But it is good to have you here with us this morning. So, we have to follow, How did you get there? that's the tip of the iceberg is that we have to have to where you used to be? Now, that's the hardest thing, you can imagine, right? I don't know if that was the case with your firm, But we are successful in doing that. that has now allowed you to modify your business So, that is one of the ways how we are reacting to it. So, we follow the business goals with innovation. or during responding to the first question, So, it's got to be no longer just a part of what you do I'd like to say data-driven TV network. Do you see that changing as the time to insight, So, the patterns that we would be looking for Because you said that you are reacting. So, I'm going to go ahead and re-ask it. (laughter) creating news data to develop these insights So, like I said, optimization is one avenue that we pursue and therefore as we develop programming, Every company that is in the content business and difficult insights to get ahold of Are you finding that your predictive capabilities and we move forward. and the season. So, the more complex have to be data-oriented. And now it's maturing to the point that but we're looking into it. And the reason I ask is that there seems to me and be ahead of the game. Before we let you go, I got to give you 30 seconds And I can't wait until the season starts. and catchers show up. That's right. I must admit. Vitaly, thank you for being with us here. Back with more on theCUBE right after this.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
AMC | ORGANIZATION | 0.99+ |
Dave | PERSON | 0.99+ |
Disney | ORGANIZATION | 0.99+ |
Vitaly | PERSON | 0.99+ |
Vitaly Tsivin | PERSON | 0.99+ |
Dennis | PERSON | 0.99+ |
AMC Networks | ORGANIZATION | 0.99+ |
Vitaly Tsivan | PERSON | 0.99+ |
ABC | ORGANIZATION | 0.99+ |
Dave Vellante | PERSON | 0.99+ |
John Walls | PERSON | 0.99+ |
John | PERSON | 0.99+ |
America | LOCATION | 0.99+ |
10 episodes | QUANTITY | 0.99+ |
Netflix | ORGANIZATION | 0.99+ |
Red Sox | ORGANIZATION | 0.99+ |
ESPN | ORGANIZATION | 0.99+ |
first question | QUANTITY | 0.99+ |
four years | QUANTITY | 0.99+ |
30 seconds | QUANTITY | 0.99+ |
10 million | QUANTITY | 0.99+ |
IBM | ORGANIZATION | 0.99+ |
Yankees | ORGANIZATION | 0.99+ |
New York City | LOCATION | 0.99+ |
two | QUANTITY | 0.99+ |
Googles | ORGANIZATION | 0.99+ |
Facebooks | ORGANIZATION | 0.99+ |
Yankee | ORGANIZATION | 0.99+ |
today | DATE | 0.99+ |
six years | QUANTITY | 0.99+ |
five | QUANTITY | 0.99+ |
Red Sox Nation | ORGANIZATION | 0.99+ |
first | QUANTITY | 0.99+ |
One | QUANTITY | 0.98+ |
three months | QUANTITY | 0.98+ |
one | QUANTITY | 0.98+ |
two worlds | QUANTITY | 0.96+ |
about 15 minutes | QUANTITY | 0.96+ |
First | QUANTITY | 0.96+ |
The Walking Deads | TITLE | 0.96+ |
Machine Learning Everywhere: Build Your Ladder to AI | TITLE | 0.93+ |
this morning | DATE | 0.92+ |
four | QUANTITY | 0.91+ |
about 30% | QUANTITY | 0.91+ |
about 15 | QUANTITY | 0.9+ |
Number two | QUANTITY | 0.88+ |
Java | TITLE | 0.88+ |
2018 | DATE | 0.81+ |
one avenue | QUANTITY | 0.81+ |
Agile | TITLE | 0.81+ |
New York | LOCATION | 0.81+ |
Executive Vice President | PERSON | 0.79+ |
three years | QUANTITY | 0.73+ |
one of the ways | QUANTITY | 0.72+ |
U.S. | LOCATION | 0.67+ |
Machine Learning Everywhere | TITLE | 0.63+ |
number one | QUANTITY | 0.63+ |
theCUBE | TITLE | 0.59+ |
Voiceover | TITLE | 0.56+ |
theCUBE | ORGANIZATION | 0.43+ |
years | QUANTITY | 0.35+ |
Data Science for All: It's a Whole New Game
>> There's a movement that's sweeping across businesses everywhere here in this country and around the world. And it's all about data. Today businesses are being inundated with data. To the tune of over two and a half million gigabytes that'll be generated in the next 60 seconds alone. What do you do with all that data? To extract insights you typically turn to a data scientist. But not necessarily anymore. At least not exclusively. Today the ability to extract value from data is becoming a shared mission. A team effort that spans the organization extending far more widely than ever before. Today, data science is being democratized. >> Data Sciences for All: It's a Whole New Game. >> Welcome everyone, I'm Katie Linendoll. I'm a technology expert writer and I love reporting on all things tech. My fascination with tech started very young. I began coding when I was 12. Received my networking certs by 18 and a degree in IT and new media from Rochester Institute of Technology. So as you can tell, technology has always been a sure passion of mine. Having grown up in the digital age, I love having a career that keeps me at the forefront of science and technology innovations. I spend equal time in the field being hands on as I do on my laptop conducting in depth research. Whether I'm diving underwater with NASA astronauts, witnessing the new ways which mobile technology can help rebuild the Philippine's economy in the wake of super typhoons, or sharing a first look at the newest iPhones on The Today Show, yesterday, I'm always on the hunt for the latest and greatest tech stories. And that's what brought me here. I'll be your host for the next hour and as we explore the new phenomenon that is taking businesses around the world by storm. And data science continues to become democratized and extends beyond the domain of the data scientist. And why there's also a mandate for all of us to become data literate. Now that data science for all drives our AI culture. And we're going to be able to take to the streets and go behind the scenes as we uncover the factors that are fueling this phenomenon and giving rise to a movement that is reshaping how businesses leverage data. And putting organizations on the road to AI. So coming up, I'll be doing interviews with data scientists. We'll see real world demos and take a look at how IBM is changing the game with an open data science platform. We'll also be joined by legendary statistician Nate Silver, founder and editor-in-chief of FiveThirtyEight. Who will shed light on how a data driven mindset is changing everything from business to our culture. We also have a few people who are joining us in our studio, so thank you guys for joining us. Come on, I can do better than that, right? Live studio audience, the fun stuff. And for all of you during the program, I want to remind you to join that conversation on social media using the hashtag DSforAll, it's data science for all. Share your thoughts on what data science and AI means to you and your business. And, let's dive into a whole new game of data science. Now I'd like to welcome my co-host General Manager IBM Analytics, Rob Thomas. >> Hello, Katie. >> Come on guys. >> Yeah, seriously. >> No one's allowed to be quiet during this show, okay? >> Right. >> Or, I'll start calling people out. So Rob, thank you so much. I think you know this conversation, we're calling it a data explosion happening right now. And it's nothing new. And when you and I chatted about it. You've been talking about this for years. You have to ask, is this old news at this point? >> Yeah, I mean, well first of all, the data explosion is not coming, it's here. And everybody's in the middle of it right now. What is different is the economics have changed. And the scale and complexity of the data that organizations are having to deal with has changed. And to this day, 80% of the data in the world still sits behind corporate firewalls. So, that's becoming a problem. It's becoming unmanageable. IT struggles to manage it. The business can't get everything they need. Consumers can't consume it when they want. So we have a challenge here. >> It's challenging in the world of unmanageable. Crazy complexity. If I'm sitting here as an IT manager of my business, I'm probably thinking to myself, this is incredibly frustrating. How in the world am I going to get control of all this data? And probably not just me thinking it. Many individuals here as well. >> Yeah, indeed. Everybody's thinking about how am I going to put data to work in my organization in a way I haven't done before. Look, you've got to have the right expertise, the right tools. The other thing that's happening in the market right now is clients are dealing with multi cloud environments. So data behind the firewall in private cloud, multiple public clouds. And they have to find a way. How am I going to pull meaning out of this data? And that brings us to data science and AI. That's how you get there. >> I understand the data science part but I think we're all starting to hear more about AI. And it's incredible that this buzz word is happening. How do businesses adopt to this AI growth and boom and trend that's happening in this world right now? >> Well, let me define it this way. Data science is a discipline. And machine learning is one technique. And then AI puts both machine learning into practice and applies it to the business. So this is really about how getting your business where it needs to go. And to get to an AI future, you have to lay a data foundation today. I love the phrase, "there's no AI without IA." That means you're not going to get to AI unless you have the right information architecture to start with. >> Can you elaborate though in terms of how businesses can really adopt AI and get started. >> Look, I think there's four things you have to do if you're serious about AI. One is you need a strategy for data acquisition. Two is you need a modern data architecture. Three is you need pervasive automation. And four is you got to expand job roles in the organization. >> Data acquisition. First pillar in this you just discussed. Can we start there and explain why it's so critical in this process? >> Yeah, so let's think about how data acquisition has evolved through the years. 15 years ago, data acquisition was about how do I get data in and out of my ERP system? And that was pretty much solved. Then the mobile revolution happens. And suddenly you've got structured and non-structured data. More than you've ever dealt with. And now you get to where we are today. You're talking terabytes, petabytes of data. >> [Katie] Yottabytes, I heard that word the other day. >> I heard that too. >> Didn't even know what it meant. >> You know how many zeros that is? >> I thought we were in Star Wars. >> Yeah, I think it's a lot of zeroes. >> Yodabytes, it's new. >> So, it's becoming more and more complex in terms of how you acquire data. So that's the new data landscape that every client is dealing with. And if you don't have a strategy for how you acquire that and manage it, you're not going to get to that AI future. >> So a natural segue, if you are one of these businesses, how do you build for the data landscape? >> Yeah, so the question I always hear from customers is we need to evolve our data architecture to be ready for AI. And the way I think about that is it's really about moving from static data repositories to more of a fluid data layer. >> And we continue with the architecture. New data architecture is an interesting buzz word to hear. But it's also one of the four pillars. So if you could dive in there. >> Yeah, I mean it's a new twist on what I would call some core data science concepts. For example, you have to leverage tools with a modern, centralized data warehouse. But your data warehouse can't be stagnant to just what's right there. So you need a way to federate data across different environments. You need to be able to bring your analytics to the data because it's most efficient that way. And ultimately, it's about building an optimized data platform that is designed for data science and AI. Which means it has to be a lot more flexible than what clients have had in the past. >> All right. So we've laid out what you need for driving automation. But where does the machine learning kick in? >> Machine learning is what gives you the ability to automate tasks. And I think about machine learning. It's about predicting and automating. And this will really change the roles of data professionals and IT professionals. For example, a data scientist cannot possibly know every algorithm or every model that they could use. So we can automate the process of algorithm selection. Another example is things like automated data matching. Or metadata creation. Some of these things may not be exciting but they're hugely practical. And so when you think about the real use cases that are driving return on investment today, it's things like that. It's automating the mundane tasks. >> Let's go ahead and come back to something that you mentioned earlier because it's fascinating to be talking about this AI journey, but also significant is the new job roles. And what are those other participants in the analytics pipeline? >> Yeah I think we're just at the start of this idea of new job roles. We have data scientists. We have data engineers. Now you see machine learning engineers. Application developers. What's really happening is that data scientists are no longer allowed to work in their own silo. And so the new job roles is about how does everybody have data first in their mind? And then they're using tools to automate data science, to automate building machine learning into applications. So roles are going to change dramatically in organizations. >> I think that's confusing though because we have several organizations who saying is that highly specialized roles, just for data science? Or is it applicable to everybody across the board? >> Yeah, and that's the big question, right? Cause everybody's thinking how will this apply? Do I want this to be just a small set of people in the organization that will do this? But, our view is data science has to for everybody. It's about bring data science to everybody as a shared mission across the organization. Everybody in the company has to be data literate. And participate in this journey. >> So overall, group effort, has to be a common goal, and we all need to be data literate across the board. >> Absolutely. >> Done deal. But at the end of the day, it's kind of not an easy task. >> It's not. It's not easy but it's maybe not as big of a shift as you would think. Because you have to put data in the hands of people that can do something with it. So, it's very basic. Give access to data. Data's often locked up in a lot of organizations today. Give people the right tools. Embrace the idea of choice or diversity in terms of those tools. That gets you started on this path. >> It's interesting to hear you say essentially you need to train everyone though across the board when it comes to data literacy. And I think people that are coming into the work force don't necessarily have a background or a degree in data science. So how do you manage? >> Yeah, so in many cases that's true. I will tell you some universities are doing amazing work here. One example, University of California Berkeley. They offer a course for all majors. So no matter what you're majoring in, you have a course on foundations of data science. How do you bring data science to every role? So it's starting to happen. We at IBM provide data science courses through CognitiveClass.ai. It's for everybody. It's free. And look, if you want to get your hands on code and just dive right in, you go to datascience.ibm.com. The key point is this though. It's more about attitude than it is aptitude. I think anybody can figure this out. But it's about the attitude to say we're putting data first and we're going to figure out how to make this real in our organization. >> I also have to give a shout out to my alma mater because I have heard that there is an offering in MS in data analytics. And they are always on the forefront of new technologies and new majors and on trend. And I've heard that the placement behind those jobs, people graduating with the MS is high. >> I'm sure it's very high. >> So go Tigers. All right, tangential. Let me get back to something else you touched on earlier because you mentioned that a number of customers ask you how in the world do I get started with AI? It's an overwhelming question. Where do you even begin? What do you tell them? >> Yeah, well things are moving really fast. But the good thing is most organizations I see, they're already on the path, even if they don't know it. They might have a BI practice in place. They've got data warehouses. They've got data lakes. Let me give you an example. AMC Networks. They produce a lot of the shows that I'm sure you watch Katie. >> [Katie] Yes, Breaking Bad, Walking Dead, any fans? >> [Rob] Yeah, we've got a few. >> [Katie] Well you taught me something I didn't even know. Because it's amazing how we have all these different industries, but yet media in itself is impacted too. And this is a good example. >> Absolutely. So, AMC Networks, think about it. They've got ads to place. They want to track viewer behavior. What do people like? What do they dislike? So they have to optimize every aspect of their business from marketing campaigns to promotions to scheduling to ads. And their goal was transform data into business insights and really take the burden off of their IT team that was heavily burdened by obviously a huge increase in data. So their VP of BI took the approach of using machine learning to process large volumes of data. They used a platform that was designed for AI and data processing. It's the IBM analytics system where it's a data warehouse, data science tools are built in. It has in memory data processing. And just like that, they were ready for AI. And they're already seeing that impact in their business. >> Do you think a movement of that nature kind of presses other media conglomerates and organizations to say we need to be doing this too? >> I think it's inevitable that everybody, you're either going to be playing, you're either going to be leading, or you'll be playing catch up. And so, as we talk to clients we think about how do you start down this path now, even if you have to iterate over time? Because otherwise you're going to wake up and you're going to be behind. >> One thing worth noting is we've talked about analytics to the data. It's analytics first to the data, not the other way around. >> Right. So, look. We as a practice, we say you want to bring data to where the data sits. Because it's a lot more efficient that way. It gets you better outcomes in terms of how you train models and it's more efficient. And we think that leads to better outcomes. Other organization will say, "Hey move the data around." And everything becomes a big data movement exercise. But once an organization has started down this path, they're starting to get predictions, they want to do it where it's really easy. And that means analytics applied right where the data sits. >> And worth talking about the role of the data scientist in all of this. It's been called the hot job of the decade. And a Harvard Business Review even dubbed it the sexiest job of the 21st century. >> Yes. >> I want to see this on the cover of Vogue. Like I want to see the first data scientist. Female preferred, on the cover of Vogue. That would be amazing. >> Perhaps you can. >> People agree. So what changes for them? Is this challenging in terms of we talk data science for all. Where do all the data science, is it data science for everyone? And how does it change everything? >> Well, I think of it this way. AI gives software super powers. It really does. It changes the nature of software. And at the center of that is data scientists. So, a data scientist has a set of powers that they've never had before in any organization. And that's why it's a hot profession. Now, on one hand, this has been around for a while. We've had actuaries. We've had statisticians that have really transformed industries. But there are a few things that are new now. We have new tools. New languages. Broader recognition of this need. And while it's important to recognize this critical skill set, you can't just limit it to a few people. This is about scaling it across the organization. And truly making it accessible to all. >> So then do we need more data scientists? Or is this something you train like you said, across the board? >> Well, I think you want to do a little bit of both. We want more. But, we can also train more and make the ones we have more productive. The way I think about it is there's kind of two markets here. And we call it clickers and coders. >> [Katie] I like that. That's good. >> So, let's talk about what that means. So clickers are basically somebody that wants to use tools. Create models visually. It's drag and drop. Something that's very intuitive. Those are the clickers. Nothing wrong with that. It's been valuable for years. There's a new crop of data scientists. They want to code. They want to build with the latest open source tools. They want to write in Python or R. These are the coders. And both approaches are viable. Both approaches are critical. Organizations have to have a way to meet the needs of both of those types. And there's not a lot of things available today that do that. >> Well let's keep going on that. Because I hear you talking about the data scientists role and how it's critical to success, but with the new tools, data science and analytics skills can extend beyond the domain of just the data scientist. >> That's right. So look, we're unifying coders and clickers into a single platform, which we call IBM Data Science Experience. And as the demand for data science expertise grows, so does the need for these kind of tools. To bring them into the same environment. And my view is if you have the right platform, it enables the organization to collaborate. And suddenly you've changed the nature of data science from an individual sport to a team sport. >> So as somebody that, my background is in IT, the question is really is this an additional piece of what IT needs to do in 2017 and beyond? Or is it just another line item to the budget? >> So I'm afraid that some people might view it that way. As just another line item. But, I would challenge that and say data science is going to reinvent IT. It's going to change the nature of IT. And every organization needs to think about what are the skills that are critical? How do we engage a broader team to do this? Because once they get there, this is the chance to reinvent how they're performing IT. >> [Katie] Challenging or not? >> Look it's all a big challenge. Think about everything IT organizations have been through. Some of them were late to things like mobile, but then they caught up. Some were late to cloud, but then they caught up. I would just urge people, don't be late to data science. Use this as your chance to reinvent IT. Start with this notion of clickers and coders. This is a seminal moment. Much like mobile and cloud was. So don't be late. >> And I think it's critical because it could be so costly to wait. And Rob and I were even chatting earlier how data analytics is just moving into all different kinds of industries. And I can tell you even personally being effected by how important the analysis is in working in pediatric cancer for the last seven years. I personally implement virtual reality headsets to pediatric cancer hospitals across the country. And it's great. And it's working phenomenally. And the kids are amazed. And the staff is amazed. But the phase two of this project is putting in little metrics in the hardware that gather the breathing, the heart rate to show that we have data. Proof that we can hand over to the hospitals to continue making this program a success. So just in-- >> That's a great example. >> An interesting example. >> Saving lives? >> Yes. >> That's also applying a lot of what we talked about. >> Exciting stuff in the world of data science. >> Yes. Look, I just add this is an existential moment for every organization. Because what you do in this area is probably going to define how competitive you are going forward. And think about if you don't do something. What if one of your competitors goes and creates an application that's more engaging with clients? So my recommendation is start small. Experiment. Learn. Iterate on projects. Define the business outcomes. Then scale up. It's very doable. But you've got to take the first step. >> First step always critical. And now we're going to get to the fun hands on part of our story. Because in just a moment we're going to take a closer look at what data science can deliver. And where organizations are trying to get to. All right. Thank you Rob and now we've been joined by Siva Anne who is going to help us navigate this demo. First, welcome Siva. Give him a big round of applause. Yeah. All right, Rob break down what we're going to be looking at. You take over this demo. >> All right. So this is going to be pretty interesting. So Siva is going to take us through. So he's going to play the role of a financial adviser. Who wants to help better serve clients through recommendations. And I'm going to really illustrate three things. One is how do you federate data from multiple data sources? Inside the firewall, outside the firewall. How do you apply machine learning to predict and to automate? And then how do you move analytics closer to your data? So, what you're seeing here is a custom application for an investment firm. So, Siva, our financial adviser, welcome. So you can see at the top, we've got market data. We pulled that from an external source. And then we've got Siva's calendar in the middle. He's got clients on the right side. So page down, what else do you see down there Siva? >> [Siva] I can see the recent market news. And in here I can see that JP Morgan is calling for a US dollar rebound in the second half of the year. And, I have upcoming meeting with Leo Rakes. I can get-- >> [Rob] So let's go in there. Why don't you click on Leo Rakes. So, you're sitting at your desk, you're deciding how you're going to spend the day. You know you have a meeting with Leo. So you click on it. You immediately see, all right, so what do we know about him? We've got data governance implemented. So we know his age, we know his degree. We can see he's not that aggressive of a trader. Only six trades in the last few years. But then where it gets interesting is you go to the bottom. You start to see predicted industry affinity. Where did that come from? How do we have that? >> [Siva] So these green lines and red arrows here indicate the trending affinity of Leo Rakes for particular industry stocks. What we've done here is we've built machine learning models using customer's demographic data, his stock portfolios, and browsing behavior to build a model which can predict his affinity for a particular industry. >> [Rob] Interesting. So, I like to think of this, we call it celebrity experiences. So how do you treat every customer like they're a celebrity? So to some extent, we're reading his mind. Because without asking him, we know that he's going to have an affinity for auto stocks. So we go down. Now we look at his portfolio. You can see okay, he's got some different holdings. He's got Amazon, Google, Apple, and then he's got RACE, which is the ticker for Ferrari. You can see that's done incredibly well. And so, as a financial adviser, you look at this and you say, all right, we know he loves auto stocks. Ferrari's done very well. Let's create a hedge. Like what kind of security would interest him as a hedge against his position for Ferrari? Could we go figure that out? >> [Siva] Yes. Given I know that he's gotten an affinity for auto stocks, and I also see that Ferrari has got some terminus gains, I want to lock in these gains by hedging. And I want to do that by picking a auto stock which has got negative correlation with Ferrari. >> [Rob] So this is where we get to the idea of in database analytics. Cause you start clicking that and immediately we're getting instant answers of what's happening. So what did we find here? We're going to compare Ferrari and Honda. >> [Siva] I'm going to compare Ferrari with Honda. And what I see here instantly is that Honda has got a negative correlation with Ferrari, which makes it a perfect mix for his stock portfolio. Given he has an affinity for auto stocks and it correlates negatively with Ferrari. >> [Rob] These are very powerful tools at the hand of a financial adviser. You think about it. As a financial adviser, you wouldn't think about federating data, machine learning, pretty powerful. >> [Siva] Yes. So what we have seen here is that using the common SQL engine, we've been able to federate queries across multiple data sources. Db2 Warehouse in the cloud, IBM's Integrated Analytic System, and Hortonworks powered Hadoop platform for the new speeds. We've been able to use machine learning to derive innovative insights about his stock affinities. And drive the machine learning into the appliance. Closer to where the data resides to deliver high performance analytics. >> [Rob] At scale? >> [Siva] We're able to run millions of these correlations across stocks, currency, other factors. And even score hundreds of customers for their affinities on a daily basis. >> That's great. Siva, thank you for playing the role of financial adviser. So I just want to recap briefly. Cause this really powerful technology that's really simple. So we federated, we aggregated multiple data sources from all over the web and internal systems. And public cloud systems. Machine learning models were built that predicted Leo's affinity for a certain industry. In this case, automotive. And then you see when you deploy analytics next to your data, even a financial adviser, just with the click of a button is getting instant answers so they can go be more productive in their next meeting. This whole idea of celebrity experiences for your customer, that's available for everybody, if you take advantage of these types of capabilities. Katie, I'll hand it back to you. >> Good stuff. Thank you Rob. Thank you Siva. Powerful demonstration on what we've been talking about all afternoon. And thank you again to Siva for helping us navigate. Should be give him one more round of applause? We're going to be back in just a moment to look at how we operationalize all of this data. But in first, here's a message from me. If you're a part of a line of business, your main fear is disruption. You know data is the new goal that can create huge amounts of value. So does your competition. And they may be beating you to it. You're convinced there are new business models and revenue sources hidden in all the data. You just need to figure out how to leverage it. But with the scarcity of data scientists, you really can't rely solely on them. You may need more people throughout the organization that have the ability to extract value from data. And as a data science leader or data scientist, you have a lot of the same concerns. You spend way too much time looking for, prepping, and interpreting data and waiting for models to train. You know you need to operationalize the work you do to provide business value faster. What you want is an easier way to do data prep. And rapidly build models that can be easily deployed, monitored and automatically updated. So whether you're a data scientist, data science leader, or in a line of business, what's the solution? What'll it take to transform the way you work? That's what we're going to explore next. All right, now it's time to delve deeper into the nuts and bolts. The nitty gritty of operationalizing data science and creating a data driven culture. How do you actually do that? Well that's what these experts are here to share with us. I'm joined by Nir Kaldero, who's head of data science at Galvanize, which is an education and training organization. Tricia Wang, who is co-founder of Sudden Compass, a consultancy that helps companies understand people with data. And last, but certainly not least, Michael Li, founder and CEO of Data Incubator, which is a data science train company. All right guys. Shall we get right to it? >> All right. >> So data explosion happening right now. And we are seeing it across the board. I just shared an example of how it's impacting my philanthropic work in pediatric cancer. But you guys each have so many unique roles in your business life. How are you seeing it just blow up in your fields? Nir, your thing? >> Yeah, for example like in Galvanize we train many Fortune 500 companies. And just by looking at the demand of companies that wants us to help them go through this digital transformation is mind-blowing. Data point by itself. >> Okay. Well what we're seeing what's going on is that data science like as a theme, is that it's actually for everyone now. But what's happening is that it's actually meeting non technical people. But what we're seeing is that when non technical people are implementing these tools or coming at these tools without a base line of data literacy, they're often times using it in ways that distance themselves from the customer. Because they're implementing data science tools without a clear purpose, without a clear problem. And so what we do at Sudden Compass is that we work with companies to help them embrace and understand the complexity of their customers. Because often times they are misusing data science to try and flatten their understanding of the customer. As if you can just do more traditional marketing. Where you're putting people into boxes. And I think the whole ROI of data is that you can now understand people's relationships at a much more complex level at a greater scale before. But we have to do this with basic data literacy. And this has to involve technical and non technical people. >> Well you can have all the data in the world, and I think it speaks to, if you're not doing the proper movement with it, forget it. It means nothing at the same time. >> No absolutely. I mean, I think that when you look at the huge explosion in data, that comes with it a huge explosion in data experts. Right, we call them data scientists, data analysts. And sometimes they're people who are very, very talented, like the people here. But sometimes you have people who are maybe re-branding themselves, right? Trying to move up their title one notch to try to attract that higher salary. And I think that that's one of the things that customers are coming to us for, right? They're saying, hey look, there are a lot of people that call themselves data scientists, but we can't really distinguish. So, we have sort of run a fellowship where you help companies hire from a really talented group of folks, who are also truly data scientists and who know all those kind of really important data science tools. And we also help companies internally. Fortune 500 companies who are looking to grow that data science practice that they have. And we help clients like McKinsey, BCG, Bain, train up their customers, also their clients, also their workers to be more data talented. And to build up that data science capabilities. >> And Nir, this is something you work with a lot. A lot of Fortune 500 companies. And when we were speaking earlier, you were saying many of these companies can be in a panic. >> Yeah. >> Explain that. >> Yeah, so you know, not all Fortune 500 companies are fully data driven. And we know that the winners in this fourth industrial revolution, which I like to call the machine intelligence revolution, will be companies who navigate and transform their organization to unlock the power of data science and machine learning. And the companies that are not like that. Or not utilize data science and predictive power well, will pretty much get shredded. So they are in a panic. >> Tricia, companies have to deal with data behind the firewall and in the new multi cloud world. How do organizations start to become driven right to the core? >> I think the most urgent question to become data driven that companies should be asking is how do I bring the complex reality that our customers are experiencing on the ground in to a corporate office? Into the data models. So that question is critical because that's how you actually prevent any big data disasters. And that's how you leverage big data. Because when your data models are really far from your human models, that's when you're going to do things that are really far off from how, it's going to not feel right. That's when Tesco had their terrible big data disaster that they're still recovering from. And so that's why I think it's really important to understand that when you implement big data, you have to further embrace thick data. The qualitative, the emotional stuff, that is difficult to quantify. But then comes the difficult art and science that I think is the next level of data science. Which is that getting non technical and technical people together to ask how do we find those unknown nuggets of insights that are difficult to quantify? Then, how do we do the next step of figuring out how do you mathematically scale those insights into a data model? So that actually is reflective of human understanding? And then we can start making decisions at scale. But you have to have that first. >> That's absolutely right. And I think that when we think about what it means to be a data scientist, right? I always think about it in these sort of three pillars. You have the math side. You have to have that kind of stats, hardcore machine learning background. You have the programming side. You don't work with small amounts of data. You work with large amounts of data. You've got to be able to type the code to make those computers run. But then the last part is that human element. You have to understand the domain expertise. You have to understand what it is that I'm actually analyzing. What's the business proposition? And how are the clients, how are the users actually interacting with the system? That human element that you were talking about. And I think having somebody who understands all of those and not just in isolation, but is able to marry that understanding across those different topics, that's what makes a data scientist. >> But I find that we don't have people with those skill sets. And right now the way I see teams being set up inside companies is that they're creating these isolated data unicorns. These data scientists that have graduated from your programs, which are great. But, they don't involve the people who are the domain experts. They don't involve the designers, the consumer insight people, the people, the salespeople. The people who spend time with the customers day in and day out. Somehow they're left out of the room. They're consulted, but they're not a stakeholder. >> Can I actually >> Yeah, yeah please. >> Can I actually give a quick example? So for example, we at Galvanize train the executives and the managers. And then the technical people, the data scientists and the analysts. But in order to actually see all of the RY behind the data, you also have to have a creative fluid conversation between non technical and technical people. And this is a major trend now. And there's a major gap. And we need to increase awareness and kind of like create a new, kind of like environment where technical people also talks seamlessly with non technical ones. >> [Tricia] We call-- >> That's one of the things that we see a lot. Is one of the trends in-- >> A major trend. >> data science training is it's not just for the data science technical experts. It's not just for one type of person. So a lot of the training we do is sort of data engineers. People who are more on the software engineering side learning more about the stats of math. And then people who are sort of traditionally on the stat side learning more about the engineering. And then managers and people who are data analysts learning about both. >> Michael, I think you said something that was of interest too because I think we can look at IBM Watson as an example. And working in healthcare. The human component. Because often times we talk about machine learning and AI, and data and you get worried that you still need that human component. Especially in the world of healthcare. And I think that's a very strong point when it comes to the data analysis side. Is there any particular example you can speak to of that? >> So I think that there was this really excellent paper a while ago talking about all the neuro net stuff and trained on textual data. So looking at sort of different corpuses. And they found that these models were highly, highly sexist. They would read these corpuses and it's not because neuro nets themselves are sexist. It's because they're reading the things that we write. And it turns out that we write kind of sexist things. And they would sort of find all these patterns in there that were sort of latent, that had a lot of sort of things that maybe we would cringe at if we sort of saw. And I think that's one of the really important aspects of the human element, right? It's being able to come in and sort of say like, okay, I know what the biases of the system are, I know what the biases of the tools are. I need to figure out how to use that to make the tools, make the world a better place. And like another area where this comes up all the time is lending, right? So the federal government has said, and we have a lot of clients in the financial services space, so they're constantly under these kind of rules that they can't make discriminatory lending practices based on a whole set of protected categories. Race, sex, gender, things like that. But, it's very easy when you train a model on credit scores to pick that up. And then to have a model that's inadvertently sexist or racist. And that's where you need the human element to come back in and say okay, look, you're using the classic example would be zip code, you're using zip code as a variable. But when you look at it, zip codes actually highly correlated with race. And you can't do that. So you may inadvertently by sort of following the math and being a little naive about the problem, inadvertently introduce something really horrible into a model and that's where you need a human element to sort of step in and say, okay hold on. Slow things down. This isn't the right way to go. >> And the people who have -- >> I feel like, I can feel her ready to respond. >> Yes, I'm ready. >> She's like let me have at it. >> And the people here it is. And the people who are really great at providing that human intelligence are social scientists. We are trained to look for bias and to understand bias in data. Whether it's quantitative or qualitative. And I really think that we're going to have less of these kind of problems if we had more integrated teams. If it was a mandate from leadership to say no data science team should be without a social scientist, ethnographer, or qualitative researcher of some kind, to be able to help see these biases. >> The talent piece is actually the most crucial-- >> Yeah. >> one here. If you look about how to enable machine intelligence in organization there are the pillars that I have in my head which is the culture, the talent and the technology infrastructure. And I believe and I saw in working very closely with the Fortune 100 and 200 companies that the talent piece is actually the most important crucial hard to get. >> [Tricia] I totally agree. >> It's absolutely true. Yeah, no I mean I think that's sort of like how we came up with our business model. Companies were basically saying hey, I can't hire data scientists. And so we have a fellowship where we get 2,000 applicants each quarter. We take the top 2% and then we sort of train them up. And we work with hiring companies who then want to hire from that population. And so we're sort of helping them solve that problem. And the other half of it is really around training. Cause with a lot of industries, especially if you're sort of in a more regulated industry, there's a lot of nuances to what you're doing. And the fastest way to develop that data science or AI talent may not necessarily be to hire folks who are coming out of a PhD program. It may be to take folks internally who have a lot of that domain knowledge that you have and get them trained up on those data science techniques. So we've had large insurance companies come to us and say hey look, we hire three or four folks from you a quarter. That doesn't move the needle for us. What we really need is take the thousand actuaries and statisticians that we have and get all of them trained up to become a data scientist and become data literate in this new open source world. >> [Katie] Go ahead. >> All right, ladies first. >> Go ahead. >> Are you sure? >> No please, fight first. >> Go ahead. >> Go ahead Nir. >> So this is actually a trend that we have been seeing in the past year or so that companies kind of like start to look how to upscale and look for talent within the organization. So they can actually move them to become more literate and navigate 'em from analyst to data scientist. And from data scientist to machine learner. So this is actually a trend that is happening already for a year or so. >> Yeah, but I also find that after they've gone through that training in getting people skilled up in data science, the next problem that I get is executives coming to say we've invested in all of this. We're still not moving the needle. We've already invested in the right tools. We've gotten the right skills. We have enough scale of people who have these skills. Why are we not moving the needle? And what I explain to them is look, you're still making decisions in the same way. And you're still not involving enough of the non technical people. Especially from marketing, which is now, the CMO's are much more responsible for driving growth in their companies now. But often times it's so hard to change the old way of marketing, which is still like very segmentation. You know, demographic variable based, and we're trying to move people to say no, you have to understand the complexity of customers and not put them in boxes. >> And I think underlying a lot of this discussion is this question of culture, right? >> Yes. >> Absolutely. >> How do you build a data driven culture? And I think that that culture question, one of the ways that comes up quite often in especially in large, Fortune 500 enterprises, is that they are very, they're not very comfortable with sort of example, open source architecture. Open source tools. And there is some sort of residual bias that that's somehow dangerous. So security vulnerability. And I think that that's part of the cultural challenge that they often have in terms of how do I build a more data driven organization? Well a lot of the talent really wants to use these kind of tools. And I mean, just to give you an example, we are partnering with one of the major cloud providers to sort of help make open source tools more user friendly on their platform. So trying to help them attract the best technologists to use their platform because they want and they understand the value of having that kind of open source technology work seamlessly on their platforms. So I think that just sort of goes to show you how important open source is in this movement. And how much large companies and Fortune 500 companies and a lot of the ones we work with have to embrace that. >> Yeah, and I'm seeing it in our work. Even when we're working with Fortune 500 companies, is that they've already gone through the first phase of data science work. Where I explain it was all about the tools and getting the right tools and architecture in place. And then companies started moving into getting the right skill set in place. Getting the right talent. And what you're talking about with culture is really where I think we're talking about the third phase of data science, which is looking at communication of these technical frameworks so that we can get non technical people really comfortable in the same room with data scientists. That is going to be the phase, that's really where I see the pain point. And that's why at Sudden Compass, we're really dedicated to working with each other to figure out how do we solve this problem now? >> And I think that communication between the technical stakeholders and management and leadership. That's a very critical piece of this. You can't have a successful data science organization without that. >> Absolutely. >> And I think that actually some of the most popular trainings we've had recently are from managers and executives who are looking to say, how do I become more data savvy? How do I figure out what is this data science thing and how do I communicate with my data scientists? >> You guys made this way too easy. I was just going to get some popcorn and watch it play out. >> Nir, last 30 seconds. I want to leave you with an opportunity to, anything you want to add to this conversation? >> I think one thing to conclude is to say that companies that are not data driven is about time to hit refresh and figure how they transition the organization to become data driven. To become agile and nimble so they can actually see what opportunities from this important industrial revolution. Otherwise, unfortunately they will have hard time to survive. >> [Katie] All agreed? >> [Tricia] Absolutely, you're right. >> Michael, Trish, Nir, thank you so much. Fascinating discussion. And thank you guys again for joining us. We will be right back with another great demo. Right after this. >> Thank you Katie. >> Once again, thank you for an excellent discussion. Weren't they great guys? And thank you for everyone who's tuning in on the live webcast. As you can hear, we have an amazing studio audience here. And we're going to keep things moving. I'm now joined by Daniel Hernandez and Siva Anne. And we're going to turn our attention to how you can deliver on what they're talking about using data science experience to do data science faster. >> Thank you Katie. Siva and I are going to spend the next 10 minutes showing you how you can deliver on what they were saying using the IBM Data Science Experience to do data science faster. We'll demonstrate through new features we introduced this week how teams can work together more effectively across the entire analytics life cycle. How you can take advantage of any and all data no matter where it is and what it is. How you could use your favorite tools from open source. And finally how you could build models anywhere and employ them close to where your data is. Remember the financial adviser app Rob showed you? To build an app like that, we needed a team of data scientists, developers, data engineers, and IT staff to collaborate. We do this in the Data Science Experience through a concept we call projects. When I create a new project, I can now use the new Github integration feature. We're doing for data science what we've been doing for developers for years. Distributed teams can work together on analytics projects. And take advantage of Github's version management and change management features. This is a huge deal. Let's explore the project we created for the financial adviser app. As you can see, our data engineer Joane, our developer Rob, and others are collaborating this project. Joane got things started by bringing together the trusted data sources we need to build the app. Taking a closer look at the data, we see that our customer and profile data is stored on our recently announced IBM Integrated Analytics System, which runs safely behind our firewall. We also needed macro economic data, which she was able to find in the Federal Reserve. And she stored it in our Db2 Warehouse on Cloud. And finally, she selected stock news data from NASDAQ.com and landed that in a Hadoop cluster, which happens to be powered by Hortonworks. We added a new feature to the Data Science Experience so that when it's installed with Hortonworks, it automatically uses a need of security and governance controls within the cluster so your data is always secure and safe. Now we want to show you the news data we stored in the Hortonworks cluster. This is the mean administrative console. It's powered by an open source project called Ambari. And here's the news data. It's in parquet files stored in HDFS, which happens to be a distributive file system. To get the data from NASDAQ into our cluster, we used IBM's BigIntegrate and BigQuality to create automatic data pipelines that acquire, cleanse, and ingest that news data. Once the data's available, we use IBM's Big SQL to query that data using SQL statements that are much like the ones we would use for any relation of data, including the data that we have in the Integrated Analytics System and Db2 Warehouse on Cloud. This and the federation capabilities that Big SQL offers dramatically simplifies data acquisition. Now we want to show you how we support a brand new tool that we're excited about. Since we launched last summer, the Data Science Experience has supported Jupyter and R for data analysis and visualization. In this week's update, we deeply integrated another great open source project called Apache Zeppelin. It's known for having great visualization support, advanced collaboration features, and is growing in popularity amongst the data science community. This is an example of Apache Zeppelin and the notebook we created through it to explore some of our data. Notice how wonderful and easy the data visualizations are. Now we want to walk you through the Jupyter notebook we created to explore our customer preference for stocks. We use notebooks to understand and explore data. To identify the features that have some predictive power. Ultimately, we're trying to assess what ultimately is driving customer stock preference. Here we did the analysis to identify the attributes of customers that are likely to purchase auto stocks. We used this understanding to build our machine learning model. For building machine learning models, we've always had tools integrated into the Data Science Experience. But sometimes you need to use tools you already invested in. Like our very own SPSS as well as SAS. Through new import feature, you can easily import those models created with those tools. This helps you avoid vendor lock-in, and simplify the development, training, deployment, and management of all your models. To build the models we used in app, we could have coded, but we prefer a visual experience. We used our customer profile data in the Integrated Analytic System. Used the Auto Data Preparation to cleanse our data. Choose the binary classification algorithms. Let the Data Science Experience evaluate between logistic regression and gradient boosted tree. It's doing the heavy work for us. As you can see here, the Data Science Experience generated performance metrics that show us that the gradient boosted tree is the best performing algorithm for the data we gave it. Once we save this model, it's automatically deployed and available for developers to use. Any application developer can take this endpoint and consume it like they would any other API inside of the apps they built. We've made training and creating machine learning models super simple. But what about the operations? A lot of companies are struggling to ensure their model performance remains high over time. In our financial adviser app, we know that customer data changes constantly, so we need to always monitor model performance and ensure that our models are retrained as is necessary. This is a dashboard that shows the performance of our models and lets our teams monitor and retrain those models so that they're always performing to our standards. So far we've been showing you the Data Science Experience available behind the firewall that we're using to build and train models. Through a new publish feature, you can build models and deploy them anywhere. In another environment, private, public, or anywhere else with just a few clicks. So here we're publishing our model to the Watson machine learning service. It happens to be in the IBM cloud. And also deeply integrated with our Data Science Experience. After publishing and switching to the Watson machine learning service, you can see that our stock affinity and model that we just published is there and ready for use. So this is incredibly important. I just want to say it again. The Data Science Experience allows you to train models behind your own firewall, take advantage of your proprietary and sensitive data, and then deploy those models wherever you want with ease. So summarize what we just showed you. First, IBM's Data Science Experience supports all teams. You saw how our data engineer populated our project with trusted data sets. Our data scientists developed, trained, and tested a machine learning model. Our developers used APIs to integrate machine learning into their apps. And how IT can use our Integrated Model Management dashboard to monitor and manage model performance. Second, we support all data. On premises, in the cloud, structured, unstructured, inside of your firewall, and outside of it. We help you bring analytics and governance to where your data is. Third, we support all tools. The data science tools that you depend on are readily available and deeply integrated. This includes capabilities from great partners like Hortonworks. And powerful tools like our very own IBM SPSS. And fourth, and finally, we support all deployments. You can build your models anywhere, and deploy them right next to where your data is. Whether that's in the public cloud, private cloud, or even on the world's most reliable transaction platform, IBM z. So see for yourself. Go to the Data Science Experience website, take us for a spin. And if you happen to be ready right now, our recently created Data Science Elite Team can help you get started and run experiments alongside you with no charge. Thank you very much. >> Thank you very much Daniel. It seems like a great time to get started. And thanks to Siva for taking us through it. Rob and I will be back in just a moment to add some perspective right after this. All right, once again joined by Rob Thomas. And Rob obviously we got a lot of information here. >> Yes, we've covered a lot of ground. >> This is intense. You got to break it down for me cause I think we zoom out and see the big picture. What better data science can deliver to a business? Why is this so important? I mean we've heard it through and through. >> Yeah, well, I heard it a couple times. But it starts with businesses have to embrace a data driven culture. And it is a change. And we need to make data accessible with the right tools in a collaborative culture because we've got diverse skill sets in every organization. But data driven companies succeed when data science tools are in the hands of everyone. And I think that's a new thought. I think most companies think just get your data scientist some tools, you'll be fine. This is about tools in the hands of everyone. I think the panel did a great job of describing about how we get to data science for all. Building a data culture, making it a part of your everyday operations, and the highlights of what Daniel just showed us, that's some pretty cool features for how organizations can get to this, which is you can see IBM's Data Science Experience, how that supports all teams. You saw data analysts, data scientists, application developer, IT staff, all working together. Second, you saw how we support all tools. And your choice of tools. So the most popular data science libraries integrated into one platform. And we saw some new capabilities that help companies avoid lock-in, where you can import existing models created from specialist tools like SPSS or others. And then deploy them and manage them inside of Data Science Experience. That's pretty interesting. And lastly, you see we continue to build on this best of open tools. Partnering with companies like H2O, Hortonworks, and others. Third, you can see how you use all data no matter where it lives. That's a key challenge every organization's going to face. Private, public, federating all data sources. We announced new integration with the Hortonworks data platform where we deploy machine learning models where your data resides. That's been a key theme. Analytics where the data is. And lastly, supporting all types of deployments. Deploy them in your Hadoop cluster. Deploy them in your Integrated Analytic System. Or deploy them in z, just to name a few. A lot of different options here. But look, don't believe anything I say. Go try it for yourself. Data Science Experience, anybody can use it. Go to datascience.ibm.com and look, if you want to start right now, we just created a team that we call Data Science Elite. These are the best data scientists in the world that will come sit down with you and co-create solutions, models, and prove out a proof of concept. >> Good stuff. Thank you Rob. So you might be asking what does an organization look like that embraces data science for all? And how could it transform your role? I'm going to head back to the office and check it out. Let's start with the perspective of the line of business. What's changed? Well, now you're starting to explore new business models. You've uncovered opportunities for new revenue sources and all that hidden data. And being disrupted is no longer keeping you up at night. As a data science leader, you're beginning to collaborate with a line of business to better understand and translate the objectives into the models that are being built. Your data scientists are also starting to collaborate with the less technical team members and analysts who are working closest to the business problem. And as a data scientist, you stop feeling like you're falling behind. Open source tools are keeping you current. You're also starting to operationalize the work that you do. And you get to do more of what you love. Explore data, build models, put your models into production, and create business impact. All in all, it's not a bad scenario. Thanks. All right. We are back and coming up next, oh this is a special time right now. Cause we got a great guest speaker. New York Magazine called him the spreadsheet psychic and number crunching prodigy who went from correctly forecasting baseball games to correctly forecasting presidential elections. He even invented a proprietary algorithm called PECOTA for predicting future performance by baseball players and teams. And his New York Times bestselling book, The Signal and the Noise was named by Amazon.com as the number one best non-fiction book of 2012. He's currently the Editor in Chief of the award winning website, FiveThirtyEight and appears on ESPN as an on air commentator. Big round of applause. My pleasure to welcome Nate Silver. >> Thank you. We met backstage. >> Yes. >> It feels weird to re-shake your hand, but you know, for the audience. >> I had to give the intense firm grip. >> Definitely. >> The ninja grip. So you and I have crossed paths kind of digitally in the past, which it really interesting, is I started my career at ESPN. And I started as a production assistant, then later back on air for sports technology. And I go to you to talk about sports because-- >> Yeah. >> Wow, has ESPN upped their game in terms of understanding the importance of data and analytics. And what it brings. Not just to MLB, but across the board. >> No, it's really infused into the way they present the broadcast. You'll have win probability on the bottom line. And they'll incorporate FiveThirtyEight metrics into how they cover college football for example. So, ESPN ... Sports is maybe the perfect, if you're a data scientist, like the perfect kind of test case. And the reason being that sports consists of problems that have rules. And have structure. And when problems have rules and structure, then it's a lot easier to work with. So it's a great way to kind of improve your skills as a data scientist. Of course, there are also important real world problems that are more open ended, and those present different types of challenges. But it's such a natural fit. The teams. Think about the teams playing the World Series tonight. The Dodgers and the Astros are both like very data driven, especially Houston. Golden State Warriors, the NBA Champions, extremely data driven. New England Patriots, relative to an NFL team, it's shifted a little bit, the NFL bar is lower. But the Patriots are certainly very analytical in how they make decisions. So, you can't talk about sports without talking about analytics. >> And I was going to save the baseball question for later. Cause we are moments away from game seven. >> Yeah. >> Is everyone else watching game seven? It's been an incredible series. Probably one of the best of all time. >> Yeah, I mean-- >> You have a prediction here? >> You can mention that too. So I don't have a prediction. FiveThirtyEight has the Dodgers with a 60% chance of winning. >> [Katie] LA Fans. >> So you have two teams that are about equal. But the Dodgers pitching staff is in better shape at the moment. The end of a seven game series. And they're at home. >> But the statistics behind the two teams is pretty incredible. >> Yeah. It's like the first World Series in I think 56 years or something where you have two 100 win teams facing one another. There have been a lot of parity in baseball for a lot of years. Not that many offensive overall juggernauts. But this year, and last year with the Cubs and the Indians too really. But this year, you have really spectacular teams in the World Series. It kind of is a showcase of modern baseball. Lots of home runs. Lots of strikeouts. >> [Katie] Lots of extra innings. >> Lots of extra innings. Good defense. Lots of pitching changes. So if you love the modern baseball game, it's been about the best example that you've had. If you like a little bit more contact, and fewer strikeouts, maybe not so much. But it's been a spectacular and very exciting World Series. It's amazing to talk. MLB is huge with analysis. I mean, hands down. But across the board, if you can provide a few examples. Because there's so many teams in front offices putting such an, just a heavy intensity on the analysis side. And where the teams are going. And if you could provide any specific examples of teams that have really blown your mind. Especially over the last year or two. Because every year it gets more exciting if you will. I mean, so a big thing in baseball is defensive shifts. So if you watch tonight, you'll probably see a couple of plays where if you're used to watching baseball, a guy makes really solid contact. And there's a fielder there that you don't think should be there. But that's really very data driven where you analyze where's this guy hit the ball. That part's not so hard. But also there's game theory involved. Because you have to adjust for the fact that he knows where you're positioning the defenders. He's trying therefore to make adjustments to his own swing and so that's been a major innovation in how baseball is played. You know, how bullpens are used too. Where teams have realized that actually having a guy, across all sports pretty much, realizing the importance of rest. And of fatigue. And that you can be the best pitcher in the world, but guess what? After four or five innings, you're probably not as good as a guy who has a fresh arm necessarily. So I mean, it really is like, these are not subtle things anymore. It's not just oh, on base percentage is valuable. It really effects kind of every strategic decision in baseball. The NBA, if you watch an NBA game tonight, see how many three point shots are taken. That's in part because of data. And teams realizing hey, three points is worth more than two, once you're more than about five feet from the basket, the shooting percentage gets really flat. And so it's revolutionary, right? Like teams that will shoot almost half their shots from the three point range nowadays. Larry Bird, who wound up being one of the greatest three point shooters of all time, took only eight three pointers his first year in the NBA. It's quite noticeable if you watch baseball or basketball in particular. >> Not to focus too much on sports. One final question. In terms of Major League Soccer, and now in NFL, we're having the analysis and having wearables where it can now showcase if they wanted to on screen, heart rate and breathing and how much exertion. How much data is too much data? And when does it ruin the sport? >> So, I don't think, I mean, again, it goes sport by sport a little bit. I think in basketball you actually have a more exciting game. I think the game is more open now. You have more three pointers. You have guys getting higher assist totals. But you know, I don't know. I'm not one of those people who thinks look, if you love baseball or basketball, and you go in to work for the Astros, the Yankees or the Knicks, they probably need some help, right? You really have to be passionate about that sport. Because it's all based on what questions am I asking? As I'm a fan or I guess an employee of the team. Or a player watching the game. And there isn't really any substitute I don't think for the insight and intuition that a curious human has to kind of ask the right questions. So we can talk at great length about what tools do you then apply when you have those questions, but that still comes from people. I don't think machine learning could help with what questions do I want to ask of the data. It might help you get the answers. >> If you have a mid-fielder in a soccer game though, not exerting, only 80%, and you're seeing that on a screen as a fan, and you're saying could that person get fired at the end of the day? One day, with the data? >> So we found that actually some in soccer in particular, some of the better players are actually more still. So Leo Messi, maybe the best player in the world, doesn't move as much as other soccer players do. And the reason being that A) he kind of knows how to position himself in the first place. B) he realizes that you make a run, and you're out of position. That's quite fatiguing. And particularly soccer, like basketball, is a sport where it's incredibly fatiguing. And so, sometimes the guys who conserve their energy, that kind of old school mentality, you have to hustle at every moment. That is not helpful to the team if you're hustling on an irrelevant play. And therefore, on a critical play, can't get back on defense, for example. >> Sports, but also data is moving exponentially as we're just speaking about today. Tech, healthcare, every different industry. Is there any particular that's a favorite of yours to cover? And I imagine they're all different as well. >> I mean, I do like sports. We cover a lot of politics too. Which is different. I mean in politics I think people aren't intuitively as data driven as they might be in sports for example. It's impressive to follow the breakthroughs in artificial intelligence. It started out just as kind of playing games and playing chess and poker and Go and things like that. But you really have seen a lot of breakthroughs in the last couple of years. But yeah, it's kind of infused into everything really. >> You're known for your work in politics though. Especially presidential campaigns. >> Yeah. >> This year, in particular. Was it insanely challenging? What was the most notable thing that came out of any of your predictions? >> I mean, in some ways, looking at the polling was the easiest lens to look at it. So I think there's kind of a myth that last year's result was a big shock and it wasn't really. If you did the modeling in the right way, then you realized that number one, polls have a margin of error. And so when a candidate has a three point lead, that's not particularly safe. Number two, the outcome between different states is correlated. Meaning that it's not that much of a surprise that Clinton lost Wisconsin and Michigan and Pennsylvania and Ohio. You know I'm from Michigan. Have friends from all those states. Kind of the same types of people in those states. Those outcomes are all correlated. So what people thought was a big upset for the polls I think was an example of how data science done carefully and correctly where you understand probabilities, understand correlations. Our model gave Trump a 30% chance of winning. Others models gave him a 1% chance. And so that was interesting in that it showed that number one, that modeling strategies and skill do matter quite a lot. When you have someone saying 30% versus 1%. I mean, that's a very very big spread. And number two, that these aren't like solved problems necessarily. Although again, the problem with elections is that you only have one election every four years. So I can be very confident that I have a better model. Even one year of data doesn't really prove very much. Even five or 10 years doesn't really prove very much. And so, being aware of the limitations to some extent intrinsically in elections when you only get one kind of new training example every four years, there's not really any way around that. There are ways to be more robust to sparce data environments. But if you're identifying different types of business problems to solve, figuring out what's a solvable problem where I can add value with data science is a really key part of what you're doing. >> You're such a leader in this space. In data and analysis. It would be interesting to kind of peek back the curtain, understand how you operate but also how large is your team? How you're putting together information. How quickly you're putting it out. Cause I think in this right now world where everybody wants things instantly-- >> Yeah. >> There's also, you want to be first too in the world of journalism. But you don't want to be inaccurate because that's your credibility. >> We talked about this before, right? I think on average, speed is a little bit overrated in journalism. >> [Katie] I think it's a big problem in journalism. >> Yeah. >> Especially in the tech world. You have to be first. You have to be first. And it's just pumping out, pumping out. And there's got to be more time spent on stories if I can speak subjectively. >> Yeah, for sure. But at the same time, we are reacting to the news. And so we have people that come in, we hire most of our people actually from journalism. >> [Katie] How many people do you have on your team? >> About 35. But, if you get someone who comes in from an academic track for example, they might be surprised at how fast journalism is. That even though we might be slower than the average website, the fact that there's a tragic event in New York, are there things we have to say about that? A candidate drops out of the presidential race, are things we have to say about that. In periods ranging from minutes to days as opposed to kind of weeks to months to years in the academic world. The corporate world moves faster. What is a little different about journalism is that you are expected to have more precision where people notice when you make a mistake. In corporations, you have maybe less transparency. If you make 10 investments and seven of them turn out well, then you'll get a lot of profit from that, right? In journalism, it's a little different. If you make kind of seven predictions or say seven things, and seven of them are very accurate and three of them aren't, you'll still get criticized a lot for the three. Just because that's kind of the way that journalism is. And so the kind of combination of needing, not having that much tolerance for mistakes, but also needing to be fast. That is tricky. And I criticize other journalists sometimes including for not being data driven enough, but the best excuse any journalist has, this is happening really fast and it's my job to kind of figure out in real time what's going on and provide useful information to the readers. And that's really difficult. Especially in a world where literally, I'll probably get off the stage and check my phone and who knows what President Trump will have tweeted or what things will have happened. But it really is a kind of 24/7. >> Well because it's 24/7 with FiveThirtyEight, one of the most well known sites for data, are you feeling micromanagey on your people? Because you do have to hit this balance. You can't have something come out four or five days later. >> Yeah, I'm not -- >> Are you overseeing everything? >> I'm not by nature a micromanager. And so you try to hire well. You try and let people make mistakes. And the flip side of this is that if a news organization that never had any mistakes, never had any corrections, that's raw, right? You have to have some tolerance for error because you are trying to decide things in real time. And figure things out. I think transparency's a big part of that. Say here's what we think, and here's why we think it. If we have a model to say it's not just the final number, here's a lot of detail about how that's calculated. In some case we release the code and the raw data. Sometimes we don't because there's a proprietary advantage. But quite often we're saying we want you to trust us and it's so important that you trust us, here's the model. Go play around with it yourself. Here's the data. And that's also I think an important value. >> That speaks to open source. And your perspective on that in general. >> Yeah, I mean, look, I'm a big fan of open source. I worry that I think sometimes the trends are a little bit away from open source. But by the way, one thing that happens when you share your data or you share your thinking at least in lieu of the data, and you can definitely do both is that readers will catch embarrassing mistakes that you made. By the way, even having open sourceness within your team, I mean we have editors and copy editors who often save you from really embarrassing mistakes. And by the way, it's not necessarily people who have a training in data science. I would guess that of our 35 people, maybe only five to 10 have a kind of formal background in what you would call data science. >> [Katie] I think that speaks to the theme here. >> Yeah. >> [Katie] That everybody's kind of got to be data literate. >> But yeah, it is like you have a good intuition. You have a good BS detector basically. And you have a good intuition for hey, this looks a little bit out of line to me. And sometimes that can be based on domain knowledge, right? We have one of our copy editors, she's a big college football fan. And we had an algorithm we released that tries to predict what the human being selection committee will do, and she was like, why is LSU rated so high? Cause I know that LSU sucks this year. And we looked at it, and she was right. There was a bug where it had forgotten to account for their last game where they lost to Troy or something and so -- >> That also speaks to the human element as well. >> It does. In general as a rule, if you're designing a kind of regression based model, it's different in machine learning where you have more, when you kind of build in the tolerance for error. But if you're trying to do something more precise, then so much of it is just debugging. It's saying that looks wrong to me. And I'm going to investigate that. And sometimes it's not wrong. Sometimes your model actually has an insight that you didn't have yourself. But fairly often, it is. And I think kind of what you learn is like, hey if there's something that bothers me, I want to go investigate that now and debug that now. Because the last thing you want is where all of a sudden, the answer you're putting out there in the world hinges on a mistake that you made. Cause you never know if you have so to speak, 1,000 lines of code and they all perform something differently. You never know when you get in a weird edge case where this one decision you made winds up being the difference between your having a good forecast and a bad one. In a defensible position and a indefensible one. So we definitely are quite diligent and careful. But it's also kind of knowing like, hey, where is an approximation good enough and where do I need more precision? Cause you could also drive yourself crazy in the other direction where you know, it doesn't matter if the answer is 91.2 versus 90. And so you can kind of go 91.2, three, four and it's like kind of A) false precision and B) not a good use of your time. So that's where I do still spend a lot of time is thinking about which problems are "solvable" or approachable with data and which ones aren't. And when they're not by the way, you're still allowed to report on them. We are a news organization so we do traditional reporting as well. And then kind of figuring out when do you need precision versus when is being pointed in the right direction good enough? >> I would love to get inside your brain and see how you operate on just like an everyday walking to Walgreens movement. It's like oh, if I cross the street in .2-- >> It's not, I mean-- >> Is it like maddening in there? >> No, not really. I mean, I'm like-- >> This is an honest question. >> If I'm looking for airfares, I'm a little more careful. But no, part of it's like you don't want to waste time on unimportant decisions, right? I will sometimes, if I can't decide what to eat at a restaurant, I'll flip a coin. If the chicken and the pasta both sound really good-- >> That's not high tech Nate. We want better. >> But that's the point, right? It's like both the chicken and the pasta are going to be really darn good, right? So I'm not going to waste my time trying to figure it out. I'm just going to have an arbitrary way to decide. >> Serious and business, how organizations in the last three to five years have just evolved with this data boom. How are you seeing it as from a consultant point of view? Do you think it's an exciting time? Do you think it's a you must act now time? >> I mean, we do know that you definitely see a lot of talent among the younger generation now. That so FiveThirtyEight has been at ESPN for four years now. And man, the quality of the interns we get has improved so much in four years. The quality of the kind of young hires that we make straight out of college has improved so much in four years. So you definitely do see a younger generation for which this is just part of their bloodstream and part of their DNA. And also, particular fields that we're interested in. So we're interested in people who have both a data and a journalism background. We're interested in people who have a visualization and a coding background. A lot of what we do is very much interactive graphics and so forth. And so we do see those skill sets coming into play a lot more. And so the kind of shortage of talent that had I think frankly been a problem for a long time, I'm optimistic based on the young people in our office, it's a little anecdotal but you can tell that there are so many more programs that are kind of teaching students the right set of skills that maybe weren't taught as much a few years ago. >> But when you're seeing these big organizations, ESPN as perfect example, moving more towards data and analytics than ever before. >> Yeah. >> You would say that's obviously true. >> Oh for sure. >> If you're not moving that direction, you're going to fall behind quickly. >> Yeah and the thing is, if you read my book or I guess people have a copy of the book. In some ways it's saying hey, there are lot of ways to screw up when you're using data. And we've built bad models. We've had models that were bad and got good results. Good models that got bad results and everything else. But the point is that the reason to be out in front of the problem is so you give yourself more runway to make errors and mistakes. And to learn kind of what works and what doesn't and which people to put on the problem. I sometimes do worry that a company says oh we need data. And everyone kind of agrees on that now. We need data science. Then they have some big test case. And they have a failure. And they maybe have a failure because they didn't know really how to use it well enough. But learning from that and iterating on that. And so by the time that you're on the third generation of kind of a problem that you're trying to solve, and you're watching everyone else make the mistake that you made five years ago, I mean, that's really powerful. But that doesn't mean that getting invested in it now, getting invested both in technology and the human capital side is important. >> Final question for you as we run out of time. 2018 beyond, what is your biggest project in terms of data gathering that you're working on? >> There's a midterm election coming up. That's a big thing for us. We're also doing a lot of work with NBA data. So for four years now, the NBA has been collecting player tracking data. So they have 3D cameras in every arena. So they can actually kind of quantify for example how fast a fast break is, for example. Or literally where a player is and where the ball is. For every NBA game now for the past four or five years. And there hasn't really been an overall metric of player value that's taken advantage of that. The teams do it. But in the NBA, the teams are a little bit ahead of journalists and analysts. So we're trying to have a really truly next generation stat. It's a lot of data. Sometimes I now more oversee things than I once did myself. And so you're parsing through many, many, many lines of code. But yeah, so we hope to have that out at some point in the next few months. >> Anything you've personally been passionate about that you've wanted to work on and kind of solve? >> I mean, the NBA thing, I am a pretty big basketball fan. >> You can do better than that. Come on, I want something real personal that you're like I got to crunch the numbers. >> You know, we tried to figure out where the best burrito in America was a few years ago. >> I'm going to end it there. >> Okay. >> Nate, thank you so much for joining us. It's been an absolute pleasure. Thank you. >> Cool, thank you. >> I thought we were going to chat World Series, you know. Burritos, important. I want to thank everybody here in our audience. Let's give him a big round of applause. >> [Nate] Thank you everyone. >> Perfect way to end the day. And for a replay of today's program, just head on over to ibm.com/dsforall. I'm Katie Linendoll. And this has been Data Science for All: It's a Whole New Game. Test one, two. One, two, three. Hi guys, I just want to quickly let you know as you're exiting. A few heads up. Downstairs right now there's going to be a meet and greet with Nate. And we're going to be doing that with clients and customers who are interested. So I would recommend before the game starts, and you lose Nate, head on downstairs. And also the gallery is open until eight p.m. with demos and activations. And tomorrow, make sure to come back too. Because we have exciting stuff. I'll be joining you as your host. And we're kicking off at nine a.m. So bye everybody, thank you so much. >> [Announcer] Ladies and gentlemen, thank you for attending this evening's webcast. If you are not attending all cloud and cognitive summit tomorrow, we ask that you recycle your name badge at the registration desk. Thank you. Also, please note there are two exits on the back of the room on either side of the room. Have a good evening. Ladies and gentlemen, the meet and greet will be on stage. Thank you.
SUMMARY :
Today the ability to extract value from data is becoming a shared mission. And for all of you during the program, I want to remind you to join that conversation on And when you and I chatted about it. And the scale and complexity of the data that organizations are having to deal with has It's challenging in the world of unmanageable. And they have to find a way. AI. And it's incredible that this buzz word is happening. And to get to an AI future, you have to lay a data foundation today. And four is you got to expand job roles in the organization. First pillar in this you just discussed. And now you get to where we are today. And if you don't have a strategy for how you acquire that and manage it, you're not going And the way I think about that is it's really about moving from static data repositories And we continue with the architecture. So you need a way to federate data across different environments. So we've laid out what you need for driving automation. And so when you think about the real use cases that are driving return on investment today, Let's go ahead and come back to something that you mentioned earlier because it's fascinating And so the new job roles is about how does everybody have data first in their mind? Everybody in the company has to be data literate. So overall, group effort, has to be a common goal, and we all need to be data literate But at the end of the day, it's kind of not an easy task. It's not easy but it's maybe not as big of a shift as you would think. It's interesting to hear you say essentially you need to train everyone though across the And look, if you want to get your hands on code and just dive right in, you go to datascience.ibm.com. And I've heard that the placement behind those jobs, people graduating with the MS is high. Let me get back to something else you touched on earlier because you mentioned that a number They produce a lot of the shows that I'm sure you watch Katie. And this is a good example. So they have to optimize every aspect of their business from marketing campaigns to promotions And so, as we talk to clients we think about how do you start down this path now, even It's analytics first to the data, not the other way around. We as a practice, we say you want to bring data to where the data sits. And a Harvard Business Review even dubbed it the sexiest job of the 21st century. Female preferred, on the cover of Vogue. And how does it change everything? And while it's important to recognize this critical skill set, you can't just limit it And we call it clickers and coders. [Katie] I like that. And there's not a lot of things available today that do that. Because I hear you talking about the data scientists role and how it's critical to success, And my view is if you have the right platform, it enables the organization to collaborate. And every organization needs to think about what are the skills that are critical? Use this as your chance to reinvent IT. And I can tell you even personally being effected by how important the analysis is in working And think about if you don't do something. And now we're going to get to the fun hands on part of our story. And then how do you move analytics closer to your data? And in here I can see that JP Morgan is calling for a US dollar rebound in the second half But then where it gets interesting is you go to the bottom. data, his stock portfolios, and browsing behavior to build a model which can predict his affinity And so, as a financial adviser, you look at this and you say, all right, we know he loves And I want to do that by picking a auto stock which has got negative correlation with Ferrari. Cause you start clicking that and immediately we're getting instant answers of what's happening. And what I see here instantly is that Honda has got a negative correlation with Ferrari, As a financial adviser, you wouldn't think about federating data, machine learning, pretty And drive the machine learning into the appliance. And even score hundreds of customers for their affinities on a daily basis. And then you see when you deploy analytics next to your data, even a financial adviser, And as a data science leader or data scientist, you have a lot of the same concerns. But you guys each have so many unique roles in your business life. And just by looking at the demand of companies that wants us to help them go through this And I think the whole ROI of data is that you can now understand people's relationships Well you can have all the data in the world, and I think it speaks to, if you're not doing And I think that that's one of the things that customers are coming to us for, right? And Nir, this is something you work with a lot. And the companies that are not like that. Tricia, companies have to deal with data behind the firewall and in the new multi cloud And so that's why I think it's really important to understand that when you implement big And how are the clients, how are the users actually interacting with the system? And right now the way I see teams being set up inside companies is that they're creating But in order to actually see all of the RY behind the data, you also have to have a creative That's one of the things that we see a lot. So a lot of the training we do is sort of data engineers. And I think that's a very strong point when it comes to the data analysis side. And that's where you need the human element to come back in and say okay, look, you're And the people who are really great at providing that human intelligence are social scientists. the talent piece is actually the most important crucial hard to get. It may be to take folks internally who have a lot of that domain knowledge that you have And from data scientist to machine learner. And what I explain to them is look, you're still making decisions in the same way. And I mean, just to give you an example, we are partnering with one of the major cloud And what you're talking about with culture is really where I think we're talking about And I think that communication between the technical stakeholders and management You guys made this way too easy. I want to leave you with an opportunity to, anything you want to add to this conversation? I think one thing to conclude is to say that companies that are not data driven is And thank you guys again for joining us. And we're going to turn our attention to how you can deliver on what they're talking about And finally how you could build models anywhere and employ them close to where your data is. And thanks to Siva for taking us through it. You got to break it down for me cause I think we zoom out and see the big picture. And we saw some new capabilities that help companies avoid lock-in, where you can import And as a data scientist, you stop feeling like you're falling behind. We met backstage. And I go to you to talk about sports because-- And what it brings. And the reason being that sports consists of problems that have rules. And I was going to save the baseball question for later. Probably one of the best of all time. FiveThirtyEight has the Dodgers with a 60% chance of winning. So you have two teams that are about equal. It's like the first World Series in I think 56 years or something where you have two 100 And that you can be the best pitcher in the world, but guess what? And when does it ruin the sport? So we can talk at great length about what tools do you then apply when you have those And the reason being that A) he kind of knows how to position himself in the first place. And I imagine they're all different as well. But you really have seen a lot of breakthroughs in the last couple of years. You're known for your work in politics though. What was the most notable thing that came out of any of your predictions? And so, being aware of the limitations to some extent intrinsically in elections when It would be interesting to kind of peek back the curtain, understand how you operate but But you don't want to be inaccurate because that's your credibility. I think on average, speed is a little bit overrated in journalism. And there's got to be more time spent on stories if I can speak subjectively. And so we have people that come in, we hire most of our people actually from journalism. And so the kind of combination of needing, not having that much tolerance for mistakes, Because you do have to hit this balance. And so you try to hire well. And your perspective on that in general. But by the way, one thing that happens when you share your data or you share your thinking And you have a good intuition for hey, this looks a little bit out of line to me. And I think kind of what you learn is like, hey if there's something that bothers me, It's like oh, if I cross the street in .2-- I mean, I'm like-- But no, part of it's like you don't want to waste time on unimportant decisions, right? We want better. It's like both the chicken and the pasta are going to be really darn good, right? Serious and business, how organizations in the last three to five years have just And man, the quality of the interns we get has improved so much in four years. But when you're seeing these big organizations, ESPN as perfect example, moving more towards But the point is that the reason to be out in front of the problem is so you give yourself Final question for you as we run out of time. And so you're parsing through many, many, many lines of code. You can do better than that. You know, we tried to figure out where the best burrito in America was a few years Nate, thank you so much for joining us. I thought we were going to chat World Series, you know. And also the gallery is open until eight p.m. with demos and activations. If you are not attending all cloud and cognitive summit tomorrow, we ask that you recycle your
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Tricia Wang | PERSON | 0.99+ |
Katie | PERSON | 0.99+ |
Katie Linendoll | PERSON | 0.99+ |
Rob | PERSON | 0.99+ |
ORGANIZATION | 0.99+ | |
Joane | PERSON | 0.99+ |
Daniel | PERSON | 0.99+ |
Michael Li | PERSON | 0.99+ |
Nate Silver | PERSON | 0.99+ |
Apple | ORGANIZATION | 0.99+ |
Hortonworks | ORGANIZATION | 0.99+ |
Trump | PERSON | 0.99+ |
Nate | PERSON | 0.99+ |
Honda | ORGANIZATION | 0.99+ |
Siva | PERSON | 0.99+ |
McKinsey | ORGANIZATION | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Larry Bird | PERSON | 0.99+ |
2017 | DATE | 0.99+ |
Rob Thomas | PERSON | 0.99+ |
Michigan | LOCATION | 0.99+ |
Yankees | ORGANIZATION | 0.99+ |
New York | LOCATION | 0.99+ |
Clinton | PERSON | 0.99+ |
IBM | ORGANIZATION | 0.99+ |
Tesco | ORGANIZATION | 0.99+ |
Michael | PERSON | 0.99+ |
America | LOCATION | 0.99+ |
Leo | PERSON | 0.99+ |
four years | QUANTITY | 0.99+ |
five | QUANTITY | 0.99+ |
30% | QUANTITY | 0.99+ |
Astros | ORGANIZATION | 0.99+ |
Trish | PERSON | 0.99+ |
Sudden Compass | ORGANIZATION | 0.99+ |
Leo Messi | PERSON | 0.99+ |
two teams | QUANTITY | 0.99+ |
1,000 lines | QUANTITY | 0.99+ |
one year | QUANTITY | 0.99+ |
10 investments | QUANTITY | 0.99+ |
NASDAQ | ORGANIZATION | 0.99+ |
The Signal and the Noise | TITLE | 0.99+ |
Tricia | PERSON | 0.99+ |
Nir Kaldero | PERSON | 0.99+ |
80% | QUANTITY | 0.99+ |
BCG | ORGANIZATION | 0.99+ |
Daniel Hernandez | PERSON | 0.99+ |
ESPN | ORGANIZATION | 0.99+ |
H2O | ORGANIZATION | 0.99+ |
Ferrari | ORGANIZATION | 0.99+ |
last year | DATE | 0.99+ |
18 | QUANTITY | 0.99+ |
three | QUANTITY | 0.99+ |
Data Incubator | ORGANIZATION | 0.99+ |
Patriots | ORGANIZATION | 0.99+ |
John Willis, SJ Technologies | Serverlessconf 2017
>> Announcer: From Hell's Kitchen in New York City, it's theCUBE, on the ground at Serverlessconf. Brought to you by Silicon Angle Media. >> Hi, I'm Stu Miniman with theCUBE, here at Serverless Conference in Hell's Kitchen in New York City. Happy to welcome back to the program. keynote speaker at the event, and a guest that we've had on a couple times before, John Willis, who's the vice president of DevOps and digital practices at Eastray Technologies. John. >> In Hell's Kitchen. >> Stu: In Hell's Kitchen, and go Yankees. >> Yeah, man. I was at the game last night, the other night. Yeah. You'll see tonight. Yeah. Thank you. Glad to be here. >> Great to see you. So look, you've been talking to audiences about DevOps for as long as I can remember, as long as I've known you, definitely. Tell us, what's so important about serverless and how that fits into the world of the developer these days. >> Yeah, I mean, my interest, you know, I was invited to do a keynote, and my interest is to break down the tribal nature of new things. And I sound like a hypocrite because I'm the DevOps tribe, but I prefer to stop calling it DevOps, because there are super patterns that exist, and as I watch serverless, I spend a lot of time having these conversations around that yeah, we don't need that DevOps anymore, because we got serverless. It was the same reason like we didn't need any of the infrastructure stuff because we got cloud. And like, we keep throwing the baby out with the bathwater, and my presentation this morning was like, it's not about the technology, stupid. Like the principles of business value, how you understand value stream, how you inject the governance, the policy, the security, the values and the outcomes that you want. I know those sound like platitudes, like I get a sense that we're making the same mistake over again, and hey, sorry folks, Serverless is just another form of compute. Sorry to get you all wound up and then let you down. It's just compute, folks. And so all the core principles that we've really learned about high-performance organizations apply, they apply differently. Monitoring is differently. How do we deliver? But the principles stay the same. And that was my core message today. >> Yeah, no, very passionate, definitely came through in the keynote. I just have to ask you just on the tech for a second, I mean you were heavily involved in containers, you were part of a company that got acquired by Docker, you were a big proponent of unikernels, now it's serverless, how do you kind of paint that picture >> I think it's amazing tech, and more these days. So I left Docker and I'm going back to something I did 10 years ago, which is kind of consulting but transformation type consulting. It sounds platitudish, but like, I'm back in the mode of looking at things at bigger scale. How do you change an organization to think differently about things? So I've kind of taken a little bit of my tech hat off. I mean, I love containers and minimal delivery, right, I've been yacking about that for like the last two or three years, right? About how minimal delivery models work. And serverless is like, amazing too, like unikernels was an interesting model of function as a service. I think serverless will eat up a good portion, you know I've said this, and I don't know, I may have to modify it. You know, I would say four years ago, three years ago, and you guys been a big part of this discussion. The world went to most companies would say we're a cloud-first organization. I've been saying for the last couple of years, I think most organizations should now thinking that they're a container-first organization. So that doesn't say everything, it just means, and I think the world now should be kind of still container first, and I know that might sound horrible to serverless people, but then look at serverless functions as a place where it fits in the architecture, repeatability, and containers. And there's actually kind of a.. >> Is that just from a maturity standpoint, you know, containers a little bit more mature than serverless? >> I don't know that it's, I think there are like, there are models of architecture, right, and I don't know that, I mean I know there's a lot of successful startups in certain value streams and enterprises that are all serverless. I know a couple of friends that have built complete infrastructure on Amazon Lambda. It works. I just don't know that all value stream delivery of services will go complete serverless. I'm pretty certain that today, almost all applications can run on containers. So I'm not creating a division of war. I'm just saying that I think, and I could be dead wrong on this, but I think in this future like placeholder where we're container first, it's going to be, give me an exception of why it can't be containers left, like it has to be cloud, or it has to be bare metal, or it has to be (mumbles) and the right side is about mapping reusable functionality in functions. So I think you have like a container-first world assumes that smart architecture mandates repeatable functions in a function-like world. Does that make sense? >> Yeah, it does. So I think back on my career, there's so many times we said like, oh, we've got this new way to really simplify the environment and get rid of things you don't need to worry about. You know, I lived through the whole virtualization, oh wait, networking storage took us a decade to fix that. >> Yeah, yeah, yeah, yeah. >> Containers, oh we're going to just focus on the application. Oh wait, networking really important, you worked on a whole company focused specifically on that. >> DevOps for networking, yeah. >> Serverless, the question is, what's the rule of operations when it comes to serverless? >> Again, that's my thoughts on serverless and if it ain't right that's secondary to my real passion right now, which is when I hear the word NoOps for serverless, I cringe. Like this idea that you don't... I mean it's different. Do you need observability and telemetry in a serverless world? I ask you. Of course you do. Do you need to have repeatable patterns of delivery to make sure you don't have vulnerabilities in your code? Of course you do. That's Ops folks. And it's about supply chain and building repeatable, structured delivery with all the gates and the checks and the units, and none of that I believe goes away with serverless. Just like it didn't go away with cloud, just the way it didn't go with virtualization, right? So I think you know, we make a big mistake to think serverless means we don't need operations now. Does it mean that our providers, we have a different relationship with our providers? We don't own the server anymore. So we can't run detrace or those kind of things in that environment. But we still own the service. So who's the site reliability engineer for the service that's running on Lambda? Or functions of serverless, right? If it ain't, I mean if you don't got one, like you're going to have a bad service. >> Yeah, what are you hearing organizationally, what's happening in companies that you're talking to? You know, I was a at a show recently, I think it was Kelsey Hightower I think, it was like DevOps is a given at this point. So do you see that, you know, where's the line from what you've seen? >> Well the curse and the blessing of DevOps, the curse is we've never had a clear definition of it. I say we, you know, everybody, but. And the blessing is we've never had a clear definition. Like it's always emerged. And the problem is, I will tell you what my definition of DevOps is, it has really very little to do with technology. It has to do with human capital and how you create high-performing organizations and the principles and practices that lead to that. The DevOps handbook, if you will, is a lot about, that I co-authored with Gene and Patrick and Jez. Those things, that's my definition of DevOps, but the problem is, when you hear people have discussion about DevOps in lieu of a good definition, you can't really get upset when somebody thinks DevOps is like Jenkins and Sheffer Puppet and Ansable, and like oh no, you're wrong, right, like that's their view. So the problem that you run into then is, if your definition is that it's pure technology and it's tied to kind of cloud, and it's something like infrastructure is code, then in your world and your definition, serverless is going to make all that obsolete, or a good portion obsolete. But if your definition is more about how you create patterns and practices around humans who deliver services a certain way, then nothing about serverless makes any of that obsolete. >> All right, Jon, want to give you final word. What do you think people, that you know, just hearing about serverless first time, where do they start, what kind of things should they look at, or you know, if there's other things you think they should probably look at first? >> You know, I think you're asking the wrong guy for that really. I think there's far better people that you've interviewed take care of that. I mean I would go with Peters Brook, the founder of this conference. That was a book I read, he gave me a copy, it made sense to me, I was able to do some labs and then you know, as they say, the rest, Bob's your uncle, you know, there's a ton of stuff out there to figure out how to navigate. >> Anything, any commentary you'd make on the community for here, a couple of people just you know, it's new but very vibrant, reminds me a lot of the emerging tech where, you know, a lot of help from the community, it's pretty easy to get started. >> So yeah, so in the technology, yes. A lot of vendors, a lot of good stuff, great conversations, and I was actually pleasantly surprised there was less discussion about NoOps or you don't need operations, and I got kind of a little bit of a cheer when I mentioned that this morning. So it seems like there are some good lessons learned that I think the message loud and clear is that operations still exist, it just has to be thought about. The keynote yesterday, the gentleman in the keynote yesterday said, day one, closing keynote, said serverless things are different, in some case easier, but harder in other things, and that was through a cloud. Cloud was much easier from getting infrastructure but we ran into a whole lot of operational issues around how to match this cloud to scale. So serverless is easy to create a function, get it set up, cost-effective, but we're starting to learn all of the complex operational issues of MTTR, how do you restore stuff, what does SRE look like, I mean this is why we get paid the big bucks, dammit man. >> All right, John Willis, always a pleasure to catch up with you. I'm Stu Miniman, thank you so much for watching theCUBE.
SUMMARY :
Brought to you by Silicon Angle Media. and a guest that we've had on a couple times before, I was at the game last night, the other night. and how that fits into the security, the values and the outcomes that you want. I just have to ask you just on the tech for a second, and you guys been a big part of this discussion. So I think you have like a container-first world you don't need to worry about. you worked on a whole company focused specifically on that. So I think you know, we make a big mistake So do you see that, you know, where's the line So the problem that you run into then is, if there's other things you think they should and then you know, as they say, of the emerging tech where, you know, and that was through a cloud. I'm Stu Miniman, thank you so much
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Stu Miniman | PERSON | 0.99+ |
John Willis | PERSON | 0.99+ |
Jon | PERSON | 0.99+ |
Silicon Angle Media | ORGANIZATION | 0.99+ |
yesterday | DATE | 0.99+ |
John | PERSON | 0.99+ |
New York City | LOCATION | 0.99+ |
Eastray Technologies | ORGANIZATION | 0.99+ |
Docker | ORGANIZATION | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
three years ago | DATE | 0.99+ |
tonight | DATE | 0.99+ |
four years ago | DATE | 0.99+ |
this morning | DATE | 0.99+ |
10 years ago | DATE | 0.99+ |
Stu | PERSON | 0.98+ |
today | DATE | 0.98+ |
Bob | PERSON | 0.97+ |
SJ Technologies | ORGANIZATION | 0.97+ |
last night | DATE | 0.97+ |
2017 | DATE | 0.97+ |
Patrick | PERSON | 0.95+ |
Jez | PERSON | 0.95+ |
Gene | PERSON | 0.95+ |
DevOps | TITLE | 0.94+ |
first | QUANTITY | 0.94+ |
first time | QUANTITY | 0.94+ |
Lambda | TITLE | 0.94+ |
Hell's Kitchen | TITLE | 0.91+ |
one | QUANTITY | 0.9+ |
NoOps | TITLE | 0.89+ |
last couple of years | DATE | 0.89+ |
unikernels | ORGANIZATION | 0.84+ |
three years | QUANTITY | 0.82+ |
Yankees | ORGANIZATION | 0.82+ |
Sheffer Puppet | TITLE | 0.81+ |
Jenkins | TITLE | 0.79+ |
theCUBE | ORGANIZATION | 0.79+ |
first organization | QUANTITY | 0.77+ |
two | QUANTITY | 0.77+ |
a decade | QUANTITY | 0.72+ |
Hell | LOCATION | 0.72+ |
Kelsey Hightower | PERSON | 0.71+ |
SRE | ORGANIZATION | 0.7+ |
Kitchen | ORGANIZATION | 0.68+ |
times | DATE | 0.66+ |
DevOps | ORGANIZATION | 0.65+ |
Hell's | EVENT | 0.65+ |
a second | QUANTITY | 0.61+ |
Kitchen | LOCATION | 0.55+ |
Ansable | TITLE | 0.55+ |
Peters Brook | PERSON | 0.55+ |
couple | QUANTITY | 0.54+ |
Serverless | ORGANIZATION | 0.53+ |
Serverlessconf | ORGANIZATION | 0.48+ |
last | DATE | 0.38+ |
Angelo Sciascia, NetX Information Systems | Veritas Vision 2017
>> Announcer: Live from Las Vegas, its theCUBE, covering Veritas Vision 2017. Brought to you by Veritas. >> Welcome back the the Aria in Las Vegas, everybody. This is theCUBE, the leader in live tech coverage. My name is Dave Vellante, I'm here with Stu Miniman. Angelo Sciascia is here, big Tom Brady fan, Senior Vice President of NetX Information Systems, from Brooklyn, New York, I don't think so. >> Not a Tom Brady fan. >> Thanks for coming on theCUBE do you think it matters, how much it airs at a football. >> No, not at all, Tom Brady doesn't care about that. >> No, well, listen, thanks for coming on. We have a great conversation, we love talking sports on the Cube. So welcome, how's the show going for you? >> Ah, it's fantastic, you know, lots of great material Veritas has been talking about. 360 Data Management, obviously we all know the benefits of that by now. So we have a lot of customers here so I'm glad they they got to see it from a senior leadership perspective, rather than our sales guys and sales engineers going in there and talking to them, and seeing Veritas executives really getting behind what we're talking about. So it backs up our story and, you know, our customers are pretty excited about it, actually. >> What's the nature of your relationship with Veritas. I know you have a relationship, and maybe still do, with Symantec. How's that all, how did it all evolve? >> Yeah, so we are a Veritas Platinum Partner, we would be, what we consider, a solution-provider type partner. A lot of our business today is either directly or indirectly tied to Veritas, which was kind of funny because we started as a security company, so our roots are systems management, you know. That's where we were in 2005 when I joined NetX, that's where we were for many, many years after Symantec acquired a company called Altiris. We just stayed in that vein, you know, managing endpoints, securing endpoints, encrypting data. And then, somewhere in 2013, we said hey, you know, let's try to diversify the portfolio a little bit. And we used to manufacture an endpoint management appliance for Altiris so we said hey, Symantec's got these things called NetBackup Appliances, let's check it out. It's a formed fact that we know how to sell and, shoot, four years later it's been a great partnership for us, great partnership, I'm sure, for Veritas, and for our customers and that's a lot of our business today. >> So, I mean, it's hot market, you know. Data protection is exploding, and security. I mean, you're in two of the sweet spots in the market right now. So how do you approach the business with customers? Do you, are you a specialist around data protection? You deliver services around them. Maybe you can explain it on the model? >> Yeah, you know, that's actually a good question, because it's evolved quite a bit, right? So, you know, when you had a limited portfolio of just one or two products that you can sell to a customer, you're really doing a product sale, right, which, I would say that was probably the most difficult transition from the split from Symantec to Veritas, because at Symantec we had thousands of products in the portfolio, or hundreds of products in the portfolio that we could actually talk to. And for a little while, really we had a handful, you know, we had NetBackup Appliances, Enterprise Vault and ancillary things to bulk on to that, like Clearwell. I think one of the most exciting things for us, as a reseller, is to now be able to go have a discussion with our customers that we were never able to have before. And rather than sit there and try to sell them a backup product or a storage solution, we could sell them a platform that solves many problems for them, right? Rather than sitting there and trying to sell one-off. So, our conversations are significantly more strategic now then they've ever been, and frankly I speak for myself and my whole team, I know everyone enjoys the conversation more now that we have a portfolio to talk about, than just a handful of products. >> Angelo, you've got an interesting viewpoint on this split off of Aritas from Symantec. What have your customers said about it? What's been your interaction with the organization? What can you tell us about kind of the inside going on? >> Yeah, look, I've lived firsthand on a Symantec acquisition of a company, okay. I was, we were not a Symantec partner when they acquired Veritas. Funny enough, I was actually doing Veritas consulting, you know, on my own on the side prior to Symantec purchasing Veritas. So I really, I'd made my career on two products; Veritas for backup and Altiris for systems management. Symantec bought Veritas and I was like okay, you know, I'm just going to stay with Altiris. Symantec bought Altiris and here we are now, so we can talk about all of them. The thing I noticed was Symantec was always going to be a security company, right, and they weren't going to change that no matter how much they try to integrate it. It's two radically different stories. You know, and for many, many years, things that we look at as new products today were kind of already there in the Symantec portfolio, but buried underneath other products that really never saw the light of day because when you have hundreds or thousands of products, like I said earlier, you know, the ones that are going to move the most are the ones that are going to get the attention. So I think the benefit of the split is that it really allowed Veritas to focus on what they do well, which is managing data, and Symantec to do what they do well, which is securing your infrastructure and securing your data. From my perspective, our customers really appreciated that. Sure, a couple of them were a little annoyed that they had to now split contracts and deal with that kind of stuff, but I think that was a momentary blip and for the most part, it's been well-received from everyone we've spoken to. >> Angelo, you said you're having, your conversations are evolving. Who are you talking to? And maybe take us inside some of those conversations. What are the big challenges they're having? >> Yeah, a year ago, a year and a half ago I was talking to either somebody who was on the messaging side and needed to archive emails or IMs, or on the backup side and they just wanted to be able to meet their backup windows and maybe to get some better d dub rates, right. Fun conversation to have, bit mundane. It's not really solving problems as much as backing up data or archiving data. Today, we're having overarching conversations at a C-level, or a senior VP level, or a director level, and talking about dramatic changes to the way they do business, and how we can do business with them. Six months ago, NetX, we weren't doing anything in the Cloud, you know. We were selling to some customers' Vdub space to the Cloud, and that's about it. We weren't talking Cloud strategy with them. Today we're talking to our customers about moving workloads to the Cloud, doing it in a way that's predictable for them, and doing it with Veritas. >> That's a really interesting point. I have to imagine that changed who you're talking with inside the company. Can you walk us through kind of a typical customer's, you know, and how you kind of move up into a more strategic discussion for Cloud strategy? >> You know, so for full transparency, that whole thing's still evolving, right. 360 Data Management is still fairly new. So what we're seeing, the conversations turned, it would start, again we're talking to somebody that we've been talking to historically in the backup side or architecture side, and we talk to them about wanting to do better things than what their backup is, and start to talk about, hey this is what 360 Data Management is. What's relevant to that person he's going to want to talk about but then there's going to be things in there that are not relevant to him. So he'll make that introduction and he'll get other stakeholders in the boat with him. And that's something we've really appreciated because the people you used to talk to are now bringing in stakeholders to offset their own desires and their own budgets, so want to bring in other technology. And typically, when we get to that point when we're starting to talk about strategic pricing, is when you're getting that C-level person to really have that aha moment, and say wow, we're offsetting costs here, we're doing things like truly getting rid of tape, or moving to the Cloud and things like that, and it's a conversation that really evolves and it's still starts at the bottom. But we're figuring out ways to start it at a higher point. >> Well, those strategies are still evolving for most customers; the roles of those people that might have had one role definitely are changing. I'm curious, one of the big transition points, especially for a company like Veritas, is going from licenses to some kind of more of a subscription model. Any commentary you have on your customers; their embrace, or like, dislike of some of those transitions? >> I think the one thing the Cloud has done is it's opened up a different avenue of how people consume IT, right. Cloud is very much consumption-based billing, and while that can complicate our lives from a reseller perspective in terms of how to collect and track monthly billing and things like that, they like it because they feel like, and it's the truth, they're only paying for what they're truly using, rather than paying for products or infrastructure that they're only using part of the day, or software that they're only using for a particular project. A lot of our healthcare systems might have a research project that their going on, and they might like to scale up for some backup licensing and scale back down once that project is done. Consumption licensing allows that, versus having to go to them and saying, hey, well now you got to buy 200 terabytes of perpetual licensing, and justify that capital expense, rather than having an operational expense on just that one particular workload that you have to back up for that one period of time. >> Angelo, Stu and I are always interested in the human capital management aspects of things, and you talked about, you went from sort of talking about having a conversation around email archiving or backup, to one about the Cloud, Cloud strategies. From your internal organization perspective, how did you manage that? Are you rescaling, are you retraining? Is it just you got really supersmart people that can adapt? >> We definitely have supersmart people, because they're all over there, that's right. But I definitely have supersmart people. But, you know, it's a little bit of both. It's a little bit of, you know, you take one of our data protection projects; see Christian Muma, you know, he's been in the data center for god knows how many years, he has seen technology evolve. It was a natural fit to look at Cloud infrastructure. Started taking some classes, consumed it, all the information he could, and now we're out there actively selling it. In some other respects, we had to hire from outside and bring in some services ourselves to actually use, maybe some third party partnerships to help us better understand how we price out Cloud for our customers. So it's a little bit of everything, and I think that that's what's exciting about it, because I think for the first time in a long time, everyone's learning something new at the same time, because, I don't care what anyone said about the Cloud years ago; it's different today, it's going to be different in six months, it's going to be different in nine months. And I think that that's exciting, and I've been in this industry since 1996. I've seen a lot of really cool things come and go. I just think that there's still infancy in the Cloud and I think it's exciting because everyone's still learning. And any time you can still learn, I think that's, I think an important part of your job. >> So when you think about your, sort of, near-term and midterm and long-term plan for the company, how do you sort of describe that? Where do you want to take this thing? >> Near-term, I want to have a solid end of the quarter. >> Business is good, right, I mean market's booming right now. >> Business is very good. Veritas will tell me it's not good enough but they're just never happy. No, business is, business is very good. I think, near-term for us, you said hey, how do we get our head around it? Near-term for us is, as we're absorbing all this information, is start to really figure out what our path is going to be. So near-term, I think we still have to identify other ancillary partners that we need to bring to the table. We've got our partnerships with Azure, Microsoft Azure, and our partnerships with AWS. We'll probably have to look at Google and IBM and see what they're doing, and then we have to look at other partnerships that are not related to Veritas but still drive that home. We maybe look at a different colo partnership or partnerships around outsourcing billing, things like that, that we can make where it's easier for our customers to consume the technology. So I think six to nine months from now if we were to have the same conversation, everything that we're doing today is probably going to be somewhat different. But I just think that there's still a lot of planning to do. >> Angelo, any feedback from your customers on what there's still on the to-do list from the vendors? We talked, you know, the strategy, Cloud's changing a lot, you know. What are some of the pinpoints that they said hey, if we could get this into the offering from Veritas or some of the others it would make our lives a lot easier. >> I mean, that's a tough question, because we're going to them now and changing the conversation already. You know, obviously they're always asking for different features, but I don't like to get into a feature conversation with the customers. I try to solve the problem. >> Dave: You're leading that conversation, is what you're saying. >> Yeah, I don't want to get into the weeds of talking about well, this widget does it at 50% and you do it at 48%. You know, I try to sit a little bit more macro. I think that one of the things our customers have asked us to do a better job at is figure out better ways to make it easier to consume the technology from budget perspective. So we're trying to figure that out now; 360 Data Management is a subscription, Veritas would like them sold in three years, we're trying to figure out ways to get creative with our customers on that. What's the right bundle, what's not the right bundle. One thing that I've noticed, and Veritas have been great at it, is we have to have some flexibility in terms of adding things in and make it seem like it's all part of that bundle. There's been some flexibility and I think that, because of that, we haven't hit that roadblock yet where, well, we really want this product in the bundle. Reality is that we'll work through that and try to add it in there, some way, shape or form, even if behind the scenes. >> The customers see you as the experts, and what we often see is that technology is the technology; it's pretty much understood. What's not understood by the customers is how to apply it to their business, and their business is changing so fast that it seems like they're looking to organizations like yours saying okay, here's our business challenge. How can you help me? You tell me, and then the best answer is somebody he'll be able to work with. Is that a valid, sort of, premise? >> Yeah, it is, it certainly is and I think we're really uniquely positioned in the fact that, here we've got, we've got our partnership with Veritas and we're 100% focused to everything in the Veritas portfolio so we don't compete from within. That's the same thing that we could say, basically, on Symantec and some of our traditional storage partners as well. That'll change most likely, on our storage partners, especially because of what Veritas have been releasing with Access and some of the other software providing storage technology. When we're brought in, we're brought in as the experts in that finite area, so we're not brought in as a generalist-type of reseller. We're brought in as, hey, I've got a data management problem, I've got a data security problem, or I'm trying to do some high-performance workloads on storage. So yeah, we are the experts, but at the same time we're being brought in for those handfuls of things, so we're not having these, hey, can you maximize my span on anti-virus software because I want to sell you commoditized software. It's just not us, it's not our thing. We're not adding any value to the customers, or the poor owners for that matter. >> Angelo, curious that there's a lot of startups in the data protection space. What do you here, your customers asking you about them? You know, what's your thoughts there? >> I guess I got to be nice, right? Because I'm being streamed everywhere. >> Stu: They're not listening, go ahead, be a New Yorker. >> Listen, I challenge Rubrik at any point of time, you know, those guys, Rubrik, Cohesity, those guys, they're new, they're the shiny new toy. The problem, the problem is they have their messaging out there, and the problem we have is that they're the shiny new toy. But when the rubber hits the road and when it's time to actually go and prove out what the technology can do, we'll win all the time. We will win ten out of ten times if we get the seat at the table, right. The problem is is because we were a limited portfolio, a limited product, limited integration type of company before, we weren't getting that seat at the table. I think they see it now, I think they're starting to get a little concerned about, hey, you know what, if this 360 Data Management is what it's going to be, and we all know it is, I think they're going to be concerned. They're new, and they're going to get attention. My honest opinion: I'm glad they came out, I'm glad that Rubrik and Cohesity and all these guys came out and did all this different ways to go to market, because I think it really forced all of us to say hey, we got some real tough decisions to make here, the competition has caught up, in certain ways. Let's change the game, and 360 Data Management does that. I think they should take as much business as they can right now, because it's going to be short-lived. >> You said it makes you rethink your strengths, and like you said, change the game. >> Yeah, it changes the game. >> Yeah. Uh, okay, predictions on the MLB? Yankees won their getaway game today to put the pressure on the Red Sox, two and a half to two and a half games back. You know, the Indians are looking good, my man, Terry Francona. What's your prediction for it? >> The Sox fan's outnumbered two to one here, so go ahead. >> You know, so I shouldn't say that the Yankees are going to win the World Series? >> No, he's a Yankees fan. >> I'm a Yankee fan, too. >> Honestly, as a Yankee fan, I think we all know that they weren't supposed to be this team, so I think this is, that's the team to look out for. >> Dave: Maybe this is their year. >> I think this is the year that they're going to challenge people, I mean, are they going to win? It's Cleveland, do you really think Cleveland's going to win anything? They won one thing in the last, what, 30 years. >> That's what they used to say about us in Boston. Angelo, thanks so much coming on, really appreciate it. Keep right there, buddy, we'll be back with our next guest right after this short break. We're live from-- (electronic music)
SUMMARY :
Brought to you by Veritas. Welcome back the the Aria in Las Vegas, everybody. do you think it matters, how much it airs at a football. we love talking sports on the Cube. So it backs up our story and, you know, I know you have a relationship, We just stayed in that vein, you know, So how do you approach the business with customers? that we have a portfolio to talk about, What can you tell us about kind of the inside going on? are the ones that are going to get the attention. What are the big challenges they're having? doing anything in the Cloud, you know. I have to imagine that changed because the people you used to talk to is going from licenses to and they might like to scale up for some backup licensing and you talked about, you went from sort of and bring in some services ourselves to actually use, Business is good, right, I mean But I just think that there's still a lot of planning to do. What are some of the pinpoints that they said and changing the conversation already. is what you're saying. is we have to have some flexibility is somebody he'll be able to work with. That's the same thing that we could say, What do you here, your customers asking you about them? I guess I got to be nice, right? and the problem we have is that they're the shiny new toy. and like you said, change the game. to put the pressure on the Red Sox, two to one here, so go ahead. so I think this is, that's the team to look out for. are they going to win? That's what they used to say about us in Boston.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Dave Vellante | PERSON | 0.99+ |
IBM | ORGANIZATION | 0.99+ |
ORGANIZATION | 0.99+ | |
Symantec | ORGANIZATION | 0.99+ |
Terry Francona | PERSON | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
2013 | DATE | 0.99+ |
Altiris | ORGANIZATION | 0.99+ |
Veritas | ORGANIZATION | 0.99+ |
Angelo Sciascia | PERSON | 0.99+ |
Boston | LOCATION | 0.99+ |
Dave | PERSON | 0.99+ |
2005 | DATE | 0.99+ |
Stu Miniman | PERSON | 0.99+ |
Red Sox | ORGANIZATION | 0.99+ |
Angelo | PERSON | 0.99+ |
Yankees | ORGANIZATION | 0.99+ |
NetX | ORGANIZATION | 0.99+ |
Stu | PERSON | 0.99+ |
hundreds | QUANTITY | 0.99+ |
50% | QUANTITY | 0.99+ |
100% | QUANTITY | 0.99+ |
200 terabytes | QUANTITY | 0.99+ |
NetX Information Systems | ORGANIZATION | 0.99+ |
ten times | QUANTITY | 0.99+ |
one | QUANTITY | 0.99+ |
two | QUANTITY | 0.99+ |
Today | DATE | 0.99+ |
48% | QUANTITY | 0.99+ |
ten | QUANTITY | 0.99+ |
World Series | EVENT | 0.99+ |
a year and a half ago | DATE | 0.99+ |
1996 | DATE | 0.99+ |
a year ago | DATE | 0.99+ |
Las Vegas | LOCATION | 0.99+ |
Yankee | ORGANIZATION | 0.99+ |
Cleveland | ORGANIZATION | 0.99+ |
Tom Brady | PERSON | 0.99+ |
Six months ago | DATE | 0.99+ |
three years | QUANTITY | 0.99+ |
Clearwell | ORGANIZATION | 0.99+ |
30 years | QUANTITY | 0.99+ |
nine months | QUANTITY | 0.99+ |
first time | QUANTITY | 0.99+ |
two products | QUANTITY | 0.99+ |
Christian Muma | PERSON | 0.98+ |
one role | QUANTITY | 0.98+ |
Vish Muichand, HPE & Eric Burgener, IDC | VMworld 2017
>> Narrator: Live from Las Vegas. It's the Cube. Covering VMWorld 2017, brought to you by VMWare and it's ecosystem partners. >> Okay welcome back everyone live here at VMWorld 2017 behind us we got the stage here set on the VMVillage, a lot of people hanging out, I'm John Furrier with Dave Alante our next guest is Vish Muichand who's the Senior Director of Product Manager HPE, Cube alumni Eric Burgener, Research Director at IDC. Guys welcome to the Cube. >> Thanks very much John. >> Vish, lot of storage action going on VMWare, you see Vsan, the cloud's here, true private cloud report from Wikibonds off the charts, showing a huge growth on prem, cloud operations, storage is impacted. What's the dots that we're connecting here this week? What's the storage story this week? >> So clearly there's a lot of different things happening in the marketplace right, different modes of operation and that in itself is demanding different approaches to infrastructure. So I think what you are seeing in the industry a variety of different approaches in storage, right? Whether it's external storage, whether it's software-defined storage, whether it's hyperconversions, or that's all flash storage. All of these things are coming together and trying to respond to the needs of data and how you want to process that data. >> We've been talking with, we talk to you guys a lot on the Cube, HP Discover, and we always say software's eating the world, we just heard Sanjay Punin from VMWare talking about it, he likes to drop that soundbyte. We take it one step further. He's a Harvard MBA, we got the bapsen mojo here. We say if software's eating the world, then data's eating software. So you guys have had a software core competence and you mentioned data. What is the impact and compromise, more and more data comes in from the edge, this primary, this secondary storage, this backup this data protection, it seems to be like this melting pot of changing architectures. How are you guys handling that at HP? >> Filling software is a very key element because it provides you with those capabilities, right? To really deal with the logical instantiation of assets and in this very virtualized world, this very dynamic world right now, gone are the days where you can do hardware type desegregation. Software gives you that speed, that agility, it gives you that flexibility. Gives you the changeability to move quickly. >> Eric you're at IDC you guys, this is your job. You guys track the market share, you guys have the pulse it's like keeping track of the baseball game. What inning, how are the Red Sox doing? Are they in first place are the Yankees catching up? What is the current state of the server virtualization because you know certainly the game's changing a little bit the world's going to cloud. What are you guys seeing in your research? >> Well so obviously most mainstream computing is running on virtualization, whether that's in the cloud or that's on prem. There's very little physical infrastructure left. There is still some of that but clearly that is not the future, virtualization is the future. >> So I wonder if I may, so you're saying virtualization is the future, so I wonder if we can unpack that a little bit because the theme here is cloud and everything is cloud related. Is your feeling, Eric, that that's sort of over your skis marketing, getting ahead of where the customer really is, I wonder if you could sort of elaborate. >> I think what the customers are really looking for is an easier way to do their jobs for less cost. And cloud provides that flexibility that you don't necessarily get if you're managing your own on-premise infrastructure, that's not 100% true based on some scale issues, but by and large, I think that's really what cloud brings to the table is a different payment model, and a flexibility that you wouldn't necessarily have with on prem infrastructure. >> So what are you guys seeing, do you feel as though the on-prem infrastructure leaders like HP, there are others obviously, are going to be able to bring that cloud-like simplicity to what do you call private cloud or whatever on-prem, is that happening, how fast is it happening, is it viable? >> Yeah so I absolutely think that's happening, in fact that's one of the reasons why software-defined storage is growing so fast is those type of products give you the kind of agility that you would normally get from a cloud environment and if you're running that on prem and you've implemented the right infrastructure around it then you're getting many of those same kind of benefits. Now you're paying for that hardware and software in a different manner than you do for the cloud, but you're getting many of those IT agility benefits that you might otherwise get from the cloud. >> And Dave, you know HP's tagline is Making Hybrid IT Simple right and so our point of view is that there is both on premise and off premise, just depending on what the usage models are and what the problems you're trying to solve, right. And bringing that simplicity where you may be going from a 100% on premise to maybe 20% off, but we've also seen some people at 50% off premise trying to come back a little bit on premise, right? So both directions I think are very very key. >> Is your point of view and I want Eric if you could chime in as well, from HPE's perspective, is hybrid IT sort of horses for courses in other words, workloads on prem versus workloads off prem, or is it beyond that some kind of federation model? >> So we see three key use cases. The first is of course wholesale, applications running on the cloud. Office 365, the perfect example of that, Sharepoint, Dropbox right, that's one. Then there is what I would call disaster recovery as a service, where you may want to have your third site in the cloud even though you got two sites on premise. Then there's also the third use case or in archiving that says how do I archive a portion of my data maybe into the cloud so it is online, but I don't have to manage it and I don't have to maybe deal with some of the associated costs around it. So these are the three sort of cases I see. >> Dave: Okay, what are you seeing in the customer base, Eric? >> Well so I completely agree that hybrid cloud is the way data centers are going to be built going forward. There are reasons to keep certain workloads on prem, generally there's performance, security or some kind of regulatory requirements that might make you put workloads on prem versus putting them in the cloud. It also depends on how often you're using the data. So Vish mentioned archive use cases. So that's a case where you need a lot of storage capacity that you keep for a long time but you may not necessarily be accessing it that much. If you're going to be accessing data a lot, that's another reason why you might consider bringing it on prem, as opposed to leaving it off prem. And of course the access, the costing access models that you get from people like Amazon and Azure are going to impact where you draw the line on that. >> So is there a difference between multi-cloud, I got a bunch of different clouds in my organization, I'm going to choose where to put stuff and cross-cloud sometimes you call it inter-clouding was, I like that term. >> Vish: You could dual source your cloud. >> And either dual source or federate or actually split application work. >> So I have seen several different aspects of that. So a customer has said to me that they need to move 20% of their data off premise, to do that they need two cloud vendors, and to get to two cloud vendors they need to see four or five of them so they can narrow it down and they they says okay, HPE all of the data that I have today is in your premise or with your equipment, how are you helping us broker that kind of arrangement. What are you doing to help federate some of that data? And work with some of these cloud vendors. So I think that's an interesting customer ask. >> Okay, well there's also cost consideration because if you multi-source or you have the opportunity to multi-source, you've got a competitive environment that's going to drive lower costs for you. As opposed to if you just got one choice. The other issue there is data mobility. If I'm locked into cloud vendor one, and it's very difficult, there's major switching costs to move, then that's another reason that might offset the potential price advantage I get from being able to go to any vendor. So there's a lot of vendors out there now, infrastructure vendors that are talking about making it easier to move data on prem to off prem, into different clouds from cloud to cloud and I think that's something that creates a more level playing field that really is going to ultimately result in lower costs. >> That's a great point about the costs, we'll just double down a quick question on that. Where are customers tripping over themselves in terms of total cost of ownership because what you're getting at here is hidden costs, right in plain sight. What are those trip fault wires if you will? What's the pitfalls what should they be looking for? >> Well, so I'll give you a general answer to that, but I think that it's very specific to workload type and the regulatory requirements that you're in but I'll tell ya one of the cases where we see repatriation, workloads moving from the cloud back into on prem is when you get to a certain level of scale. And the largest enterprises. >> John: Scale in terms of when to bring it back? >> Well just in terms of how >> or when to leave >> So how much data do I need to basically maintain in this environment and use on a regular basis. And the larger scale environments are the one where larger enterprises are able to actually bring back, create their own cloud infrastructure on prem, with their own environments and actually manage that for less cost than what they could otherwise pay a public cloud provider. >> So just to take it one step further, connect the next dot, the CXO, the CIO has to try to get some stability and there's some uncontrollable things certainly in retail it's predictable that the holiday season needs bursting or whatever so you do some things in the cloud but that's a known pattern, so you're saying that they're starting to recognize some of these scale issues for predictability they bring them on prem. Is that kind of what I'm getting? >> Well so the scale from a cost point of view, so if you're creating your own private cloud infrastructure and you're using the same kind of highly agile software to find storage designs to build that environment, you somewhat have the same ability to burst. Now yeah, you have to buy the hardware and there's redeployment issues and hopefully when we move forward towards much more composable infrastructure that becomes a lot easier problem to solve but that's you know some years in the future. But what I'm really talking about it's the cost. If I'm going to be maintaining a five petabyte data set over a ten year period, and I know what my access patterns are, is it cheaper to put that in Amazon or is it cheaper for me to build an infrastructure in house and maintain that myself. >> That's a great point. That's huge and Vish what's your reaction, is this basically validates all the action going on on the private cloud right now, on prem activity is setting up the cloud models. They can't do that unless you have the operating model. >> I'll talk about two things right, one called Cloud Bank and another one called Nimble Cloud Volumes and soon to be called HPE Cloud Volumes. So Cloud Bank allows you to take on premise data running on a three part array, and actually take a portion of that data onto either an on premise object store or an off premise object store. And we call that Cloud Bank working together with something called Recovery Managed Central and store once bringing that cloud picture together. Now the HPE cloud volumes on Nimble Cloud Volumes, it's another interesting concept where you have a cloud service that's block storage service, but it gives you the six nines SLA, it gives you the ability to do snapshots and transform data without a lot of charges that Eric talked about. It gives you the ability to move the data to different clouds because it's disagregated from the major cloud providers, it's connected via a close proximity connection so these are just two examples I think that show you how putting these used cases into action. >> Hey can we geek out a little bit here? (laughter) >> Aren't we geeking out now? You want to go deeper? >> So people want simplicity, we know that, we're talking about bringing cloud on prem. How do they get there? Well one of the ways is VVOLs, we sort of been talking about this, they haven't really taken off. Eric you've written some content around this. Like you said off camera, customers don't wake up in the morning and say I got to get me some VVOLs. But they do want simplicity. >> Absolutely, yeah. >> What are VVOLs, why do they matter, and how does it relate to simplicity. >> So yeah, let's talk a little bit about that. So what everybody no matter whether they're putting storage in the cloud, they're building on prem, they're building a private cloud, everybody wants to be able to manage their environments more easily, more intuitively, and one of the things that we've seen as a trend over the last five years is in general across the industry, storage mangement tasks are migrating away from dedicated storage admin teams, more towards IT generalists. In many cases, those are the virtual administrators. To enable that kind of a move, you need to make storage much easier to manage. So the whole idea behind VVOLs is to basically allow a non-storage person who maybe thinks about things in terms of I'd like to do this operation to an application for example, I've got Oracle running or I've got this file system here and I want to create a snapshot of it or I want to do some other task on it. To be able to just select it at the application level and perform that operation, that's very intuitive, it's easy for a non-storage person to understand and VVOLs effectively enables that kind of an ease of use management in block based environments. >> An application view of the storage? >> That's right, and I mean it's effectively it ties storage operations to a single virtual machine, and basically you're running an app on a virtual machine and so that's how you get that tie in in that way. But one other thing I'll say about VVOLs is that so it's not just what VMWare provides, there's some work that needs to be done on the storage array side to integrate with that management framework. And then how that vendor has chosen to integrate with that framework is going to determine the functionality that you have access to when you're using that VVOLs API. >> And how have you chosen to integrate with that framework? >> Yeah so Dave if you look at VVOLs, both HPE and HPE 3Par nimble have bene very very strongly focused on VVOLs in fact we've been working with VMWare gosh over the last five years now, on the reference architecture for VVOLs. Most recently we've now introduced replication support for both 3Parand nimble platforms with VVOLs and I think that capability now within VVOLs is a very important watershed capability because everybody needs resilience, disaster recovery. >> Automation's right around the corner, orchestration all big topics here at VMWorld. >> Correct and so that's a very key piece. And I think if you look at to Eric's point around simplicity, VVOLs is one key area. Two layers maybe I'd like to highlight as well. Number one is the visibility to what the application sees and within the Nimble community, they've talked about this app data gap, which is the applications not knowing why they can't get access to data and so this notion of bringing that level of understanding visibility to that gap saying is it in your computer infrastructure, is it in storage, is it in the network? So this notion of VMVision, Infosight, the Nimble (inaudible) because you're going to bring out the rest of the HPE portfolio I think is very key around simplicity. The third thing let's not forget, VMWare's built a whole ecosystem of management platforms around V-Center, V-Realize operations, all the orchestration and operation pieces and so continuing to integrate and offer customers that view is very key, right, so three prong vector I would say on making things simple. >> Also it gives HPE discovers coming up in Madrid shortly. Congratulations good to see you, Eric thanks so much for stopping by and sharing the IDC perspective. Great job, live coverage here at VMWorld 2017, I'm John Furrier, Dave Alante we'll be right back with more live coverage after this short break. >> Thank you.
SUMMARY :
Covering VMWorld 2017, brought to you by VMWare the Senior Director of Product Manager HPE, Cube alumni Vish, lot of storage action going on VMWare, you see So I think what you are seeing in the industry a So you guys have had a software core competence and Gives you the changeability to move quickly. What are you guys seeing in your research? the future, virtualization is the future. is the future, so I wonder if we can unpack that a little And cloud provides that flexibility that you don't the kind of agility that you would normally get from And bringing that simplicity where you may be going in the cloud even though you got two sites on premise. going to impact where you draw the line on that. sometimes you call it inter-clouding was, I like that term. And either dual source or federate or actually split So a customer has said to me that they need to move As opposed to if you just got one choice. What are those trip fault wires if you will? into on prem is when you get to a certain level of scale. And the larger scale environments are the one where connect the next dot, the CXO, the CIO has to try a lot easier problem to solve but that's you know They can't do that unless you have the operating model. the six nines SLA, it gives you the ability to do Well one of the ways is VVOLs, we sort of been talking it relate to simplicity. To enable that kind of a move, you need to make storage that you have access to when you're using that VVOLs API. Yeah so Dave if you look at VVOLs, both HPE and HPE Automation's right around the corner, orchestration And I think if you look at to Eric's point around for stopping by and sharing the IDC perspective.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Eric Burgener | PERSON | 0.99+ |
Dave | PERSON | 0.99+ |
Eric | PERSON | 0.99+ |
Dave Alante | PERSON | 0.99+ |
Red Sox | ORGANIZATION | 0.99+ |
Vish Muichand | PERSON | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
John | PERSON | 0.99+ |
20% | QUANTITY | 0.99+ |
five | QUANTITY | 0.99+ |
four | QUANTITY | 0.99+ |
Yankees | ORGANIZATION | 0.99+ |
John Furrier | PERSON | 0.99+ |
two sites | QUANTITY | 0.99+ |
Madrid | LOCATION | 0.99+ |
Sanjay Punin | PERSON | 0.99+ |
50% | QUANTITY | 0.99+ |
Las Vegas | LOCATION | 0.99+ |
100% | QUANTITY | 0.99+ |
third site | QUANTITY | 0.99+ |
two things | QUANTITY | 0.99+ |
two examples | QUANTITY | 0.99+ |
HP | ORGANIZATION | 0.99+ |
HPE | ORGANIZATION | 0.99+ |
Cloud Bank | ORGANIZATION | 0.99+ |
Infosight | ORGANIZATION | 0.99+ |
two cloud vendors | QUANTITY | 0.99+ |
first | QUANTITY | 0.99+ |
this week | DATE | 0.99+ |
Two layers | QUANTITY | 0.99+ |
Office 365 | TITLE | 0.99+ |
VMVision | ORGANIZATION | 0.98+ |
Oracle | ORGANIZATION | 0.98+ |
VMWare | ORGANIZATION | 0.98+ |
VVOLs | TITLE | 0.98+ |
both | QUANTITY | 0.98+ |
one | QUANTITY | 0.98+ |
five petabyte | QUANTITY | 0.98+ |
VMWorld 2017 | EVENT | 0.98+ |
IDC | ORGANIZATION | 0.97+ |
Nimble | ORGANIZATION | 0.97+ |
Dropbox | ORGANIZATION | 0.97+ |
Vish | PERSON | 0.97+ |
Harvard | ORGANIZATION | 0.97+ |
one choice | QUANTITY | 0.97+ |
single | QUANTITY | 0.97+ |
VMWorld | ORGANIZATION | 0.97+ |
Wikibonds | ORGANIZATION | 0.96+ |
VMWare | TITLE | 0.96+ |
today | DATE | 0.96+ |
third use case | QUANTITY | 0.96+ |
Azure | ORGANIZATION | 0.96+ |
both directions | QUANTITY | 0.94+ |
Cube | ORGANIZATION | 0.94+ |
three key use cases | QUANTITY | 0.92+ |
Sharepoint | ORGANIZATION | 0.92+ |
Lenovo Transform 2017 Keynote
(upbeat techno music) >> Announcer: Good morning ladies and gentlemen. This is Lenovo Transform. Please welcome to the stage Lenovo's Rod Lappin. (upbeat instrumental) >> Alright, ladies and gentlemen. Here we go. I was out the back having a chat. A bit faster than I expected. How are you all doing this morning? (crowd cheers) >> Good? How fantastic is it to be in New York City? (crowd applauds) Excellent. So my name's Rod Lappin. I'm with the Data Center Group, obviously. I do basically anything that touches customers from our sales people, our pre-sales engineers, our architects, et cetera, all the way through to our channel partner sales engagement globally. So that's my job, but enough of that, okay? So the weather this morning, absolutely fantastic. Not a cloud in the sky, perfect. A little bit different to how it was yesterday, right? I want to thank all of you because I know a lot of you had a lot of commuting issues getting into New York yesterday with all the storms. We have a lot of people from international and domestic travel caught up in obviously the network, which blows my mind, actually, but we have a lot of people here from Europe, obviously, a lot of analysts and media people here as well as customers who were caught up in circling around the airport apparently for hours. So a big round of applause for our team from Europe. (audience applauds) Thank you for coming. We have some people who commuted a very short distance. For example, our own server general manager, Cameron (mumbles), he's out the back there. Cameron, how long did it take you to get from Raleigh to New York? An hour-and-a-half flight? >> Cameron: 17 hours. >> 17 hours, ladies and gentleman. That's a fantastic distance. I think that's amazing. But I know a lot of us, obviously, in the United States have come a long way with the storms, obviously very tough, but I'm going to call out one individual. Shaneil from Spotless. Where are you Shaneil, you're here somewhere? There he is from Australia. Shaneil how long did it take you to come in from Australia? 25 hour, ladies and gentleman. A big round of applause. That's a pretty big effort. Shaneil actually I want you to stand up, if you don't mind. I've got a seat here right next to my CEO. You've gone the longest distance. How about a big round of applause for Shaneil. We'll put him in my seat, next to YY. Honestly, Shaneil, you're doing me a favor. Okay ladies and gentlemen, we've got a big day today. Obviously, my seat now taken there, fantastic. Obviously New York City, the absolute pinnacle of globalization. I first came to New York in 1996, which was before a lot of people in the room were born, unfortunately for me these days. Was completely in awe. I obviously went to a Yankees game, had no clue what was going on, didn't understand anything to do with baseball. Then I went and saw Patrick Ewing. Some of you would remember Patrick Ewing. Saw the Knicks play basketball. Had no idea what was going on. Obviously, from Australia, and somewhat slightly height challenged, basketball was not my thing but loved it. I really left that game... That was the first game of basketball I'd ever seen. Left that game realizing that effectively the guy throws the ball up at the beginning, someone taps it, that team gets it, they run it, they put it in the basket, then the other team gets it, they put it in the basket, the other team gets it, and that's basically the entire game. So I haven't really progressed from that sort of learning or understanding of basketball since then, but for me, personally, being here in New York, and obviously presenting with all of you guys today, it's really humbling from obviously some of you would have picked my accent, I'm also from Australia. From the north shore of Sydney. To be here is just a fantastic, fantastic event. So welcome ladies and gentlemen to Transform, part of our tech world series globally in our event series and our event season here at Lenovo. So once again, big round of applause. Thank you for coming (audience applauds). Today, basically, is the culmination of what I would classify as a very large journey. Many of you have been with us on that. Customers, partners, media, analysts obviously. We've got quite a lot of our industry analysts in the room. I know Matt Eastwood yesterday was on a train because he sent a Tweet out saying there's 170 people on the WIFI network. He was obviously a bit concerned he was going to get-- Pat Moorhead, he got in at 3:30 this morning, obviously from traveling here as well with some of the challenges with the transportation, so we've got a lot of people in the room that have been giving us advice over the last two years. I think all of our employees are joining us live. All of our partners and customers through the stream. As well as everybody in this packed-out room. We're very very excited about what we're going to be talking to you all today. I want to have a special thanks obviously to our R&D team in Raleigh and around the world. They've also been very very focused on what they've delivered for us today, and it's really important for them to also see the culmination of this great event. And like I mentioned, this is really the feedback. It's not just a Lenovo launch. This is a launch based on the feedback from our partners, our customers, our employees, the analysts. We've been talking to all of you about what we want to be when we grow up from a Data Center Group, and I think you're going to hear some really exciting stuff from some of the speakers today and in the demo and breakout sessions that we have after the event. These last two years, we've really transformed the organization, and that's one of the reasons why that theme is part of our Tech World Series today. We're very very confident in our future, obviously, and where the company's going. It's really important for all of you to understand today and take every single snippet that YY, Kirk, and Christian talk about today in the main session, and then our presenters in the demo sections on what Lenovo's actually doing for its future and how we're positioning the company, obviously, for that future and how the transformation, the digital transformation, is going ahead globally. So, all right, we are now going to step into our Transform event. And I've got a quick agenda statement for you. The very first thing is we're going to hear from YY, our chairman and CEO. He's going to discuss artificial intelligence, the evolution of our society and how Lenovo is clearly positioning itself in the industry. Then, obviously, you're going to hear from Kirk Skaugen, our president of the Data Center Group, our new boss. He's going to talk about how long he's been with the company and the transformation, once again, we're making, very specifically to the Data Center Group and how much of a difference we're making to society and some of our investments. Christian Teismann, our SVP and general manager of our client business is going to talk about the 25 years of ThinkPad. This year is the 25-year anniversary of our ThinkPad product. Easily the most successful brand in our client branch or client branch globally of any vendor. Most successful brand we've had launched, and this afternoon breakout sessions, obviously, with our keynotes, fantastic sessions. Make sure you actually attend all of those after this main arena here. Now, once again, listen, ask questions, and make sure you're giving us feedback. One of the things about Lenovo that we say all the time... There is no room for arrogance in our company. Every single person in this room is a customer, partner, analyst, or an employee. We love your feedback. It's only through your feedback that we continue to improve. And it's really important that through all of the sessions where the Q&As happen, breakouts afterwards, you're giving us feedback on what you want to see from us as an organization as we go forward. All right, so what were you doing 25 years ago? I spoke about ThinkPad being 25 years old, but let me ask you this. I bet you any money that no one here knew that our x86 business is also 25 years old. So, this year, we have both our ThinkPad and our x86 anniversaries for 25 years. Let me tell you. What were you guys doing 25 years ago? There's me, 25 years ago. It's a bit scary, isn't it? It's very svelte and athletic and a lot lighter than I am today. It makes me feel a little bit conscious. And you can see the black and white shot. It shows you that even if you're really really short and you come from the wrong side of the tracks to make some extra cash, you can still do some modeling as long as no one else is in the photo to give anyone any perspective, so very important. I think I might have got one photo shoot out of that, I don't know. I had to do it, I needed the money. Let me show you another couple of photos. Very interesting, how's this guy? How cool does he look? Very svelte and athletic. I think there's no doubt. He looks much much cooler than I do. Okay, so ladies and gentlemen, without further ado, it gives me great honor to obviously introduce our very very first guest to the stage. Ladies and gentlemen, our chairman and CEO, Yuanqing Yang. or as we like to call him, YY. A big round of applause, thank you. (upbeat techno instrumental) >> Good morning everyone. Thank you, Rod, for your introduction. Actually, I didn't think I was younger than you (mumbles). I can't think of another city more fitting to host the Transform event than New York. A city that has transformed from a humble trading post 400 years ago to one of the most vibrant cities in the world today. It is a perfect symbol of transformation of our world. The rapid and the deep transformations that have propelled us from the steam engine to the Internet era in just 200 years. Looking back at 200 years ago, there was only a few companies that operated on a global scale. The total value of the world's economy was around $188 billion U.S. dollars. Today, it is only $180 for each person on earth. Today, there are thousands of independent global companies that compete to sell everything, from corn and crude oil to servers and software. They drive a robust global economy was over $75 trillion or $1,000 per person. Think about it. The global economy has multiplied almost 450 times in just two centuries. What is even more remarkable is that the economy has almost doubled every 15 years since 1950. These are significant transformation for businesses and for the world and our tiny slice of pie. This transformation is the result of the greatest advancement in technology in human history. Not one but three industrial revolutions have happened over the last 200 years. Even though those revolutions created remarkable change, they were just the beginning. Today, we are standing at the beginning of the fourth revolution. This revolution will transform how we work (mumbles) in ways that no one could imagine in the 18th century or even just 18 months ago. You are the people who will lead this revolution. Along with Lenovo, we will redefine IT. IT is no longer just information technology. It's intelligent technology, intelligent transformation. A transformation that is driven by big data called computing and artificial intelligence. Even the transition from PC Internet to mobile Internet is a big leap. Today, we are facing yet another big leap from the mobile Internet to the Smart Internet or intelligent Internet. In this Smart Internet era, Cloud enables devices, such as PCs, Smart phones, Smart speakers, Smart TVs. (mumbles) to provide the content and the services. But the evolution does not stop them. Ultimately, almost everything around us will become Smart, with building computing, storage, and networking capabilities. That's what we call the device plus Cloud transformation. These Smart devices, incorporated with various sensors, will continuously sense our environment and send data about our world to the Cloud. (mumbles) the process of this ever-increasing big data and to support the delivery of Cloud content and services, the data center infrastructure is also transforming to be more agile, flexible, and intelligent. That's what we call the infrastructure plus Cloud transformation. But most importantly, it is the human wisdom, the people learning algorithm vigorously improved by engineers that enables artificial intelligence to learn from big data and make everything around us smarter. With big data collected from Smart devices, computing power of the new infrastructure under the trend artificial intelligence, we can understand the world around us more accurately and make smarter decisions. We can make life better, work easier, and society safer and healthy. Think about what is already possible as we start this transformation. Smart Assistants can help you place orders online with a voice command. Driverless cars can run on the same road as traditional cars. (mumbles) can help troubleshoot customers problems, and the virtual doctors already diagnose basic symptoms. This list goes on and on. Like every revolution before it, intelligent transformation, will fundamentally change the nature of business. Understanding and preparing for that will be the key for the growth and the success of your business. The first industrial revolution made it possible to maximize production. Water and steam power let us go from making things by hand to making them by machine. This transformed how fast things could be produced. It drove the quantity of merchandise made and led to massive increase in trade. With this revolution, business scale expanded, and the number of customers exploded. Fifty years later, the second industrial revolution made it necessary to organize a business like the modern enterprise, electric power, and the telegraph communication made business faster and more complex, challenging businesses to become more efficient and meeting entirely new customer demands. In our own lifetimes, we have witnessed the third industrial revolution, which made it possible to digitize the enterprise. The development of computers and the Internet accelerated business beyond human speed. Now, global businesses have to deal with customers at the end of a cable, not always a handshake. While we are still dealing with the effects of a digitizing business, the fourth revolution is already here. In just the past two or three years, the growth of data and advancement in visual intelligence has been astonishing. The computing power can now process the massive amount of data about your customers, suppliers, partners, competitors, and give you insights you simply could not imagine before. Artificial intelligence can not only tell you what your customers want today but also anticipate what they will need tomorrow. This is not just about making better business decisions or creating better customer relationships. It's about making the world a better place. Ultimately, can we build a new world without diseases, war, and poverty? The power of big data and artificial intelligence may be the revolutionary technology to make that possible. Revolutions don't happen on their own. Every industrial revolution has its leaders, its visionaries, and its heroes. The master transformers of their age. The first industrial revolution was led by mechanics who designed and built power systems, machines, and factories. The heroes of the second industrial revolution were the business managers who designed and built modern organizations. The heroes of the third revolution were the engineers who designed and built the circuits and the source code that digitized our world. The master transformers of the next revolution are actually you. You are the designers and the builders of the networks and the systems. You will bring the benefits of intelligence to every corner of your enterprise and make intelligence the central asset of your business. At Lenovo, data intelligence is embedded into everything we do. How we understand our customer's true needs and develop more desirable products. How we profile our customers and market to them precisely. How we use internal and external data to balance our supply and the demand. And how we train virtual agents to provide more effective sales services. So the decisions you make today about your IT investment will determine the quality of the decisions your enterprise will make tomorrow. So I challenge each of you to seize this opportunity to become a master transformer, to join Lenovo as we work together at the forefront of the fourth industrial revolution, as leaders of the intelligent transformation. (triumphant instrumental) Today, we are launching the largest portfolio in our data center history at Lenovo. We are fully committed to the (mumbles) transformation. Thank you. (audience applauds) >> Thanks YY. All right, ladies and gentlemen. Fantastic, so how about a big round of applause for YY. (audience applauds) Obviously a great speech on the transformation that we at Lenovo are taking as well as obviously wanting to journey with our partners and customers obviously on that same journey. What I heard from him was obviously artificial intelligence, how we're leveraging that integrally as well as externally and for our customers, and the investments we're making in the transformation around IoT machine learning, obviously big data, et cetera, and obviously the Data Center Group, which is one of the key things we've got to be talking about today. So we're on the cusp of that fourth revolution, as YY just mentioned, and Lenovo is definitely leading the way and investing in those parts of the industry and our portfolio to ensure we're complimenting all of our customers and partners on what they want to be, obviously, as part of this new transformation we're seeing globally. Obviously now, ladies and gentlemen, without further ado once again, to tell us more about what's going on today, our announcements, obviously, that all of you will be reading about and seeing in the breakout and the demo sessions with our segment general managers this afternoon is our president of the data center, Mr. Kirk Skaugen. (upbeat instrumental) >> Good morning, and let me add my welcome to Transform. I just crossed my six months here at Lenovo after over 24 years at Intel Corporation, and I can tell you, we've been really busy over the last six months, and I'm more excited and enthusiastic than ever and hope to share some of that with you today. Today's event is called "Transform", and today we're announcing major new transformations in Lenovo, in the data center, but more importantly, we're celebrating the business results that these platforms are going to have on society and with international supercomputing going on in parallel in Frankfurt, some of the amazing scientific discoveries that are going to happen on some of these platforms. Lenovo has gone through some significant transformations in the last two years, since we acquired the IBM x86 business, and that's really positioning us for this next phase of growth, and we'll talk more about that later. Today, we're announcing the largest end-to-end data center portfolio in Lenovo's history, as you heard from YY, and we're really taking the best of the x86 heritage from our IBM acquisition of the x86 server business and combining that with the cost economics that we've delivered from kind of our China heritage. As we've talked to some of the analysts in the room, it's really that best of the east and best of the west is combining together in this announcement today. We're going to be announcing two new brands, building on our position as the number one x86 server vendor in both customer satisfaction and in reliability, and we're also celebrating, next month in July, a very significant milestone, which will we'll be shipping our 20 millionth x86 server into the industry. For us, it's an amazing time, and it's an inflection point to kind of look back, pause, but also share the next phase of Lenovo and the exciting vision for the future. We're also making some declarations on our vision for the future today. Again, international supercomputing's going on, and, as it turns out, we're the fastest growing supercomputer company on earth. We'll talk about that. Our goal today that we're announcing is that we plan in the next several years to become number one in supercomputing, and we're going to put the investments behind that. We're also committing to our customers that we're going to disrupt the status quo and accelerate the pace of innovation, not just in our legacy server solutions, but also in Software-Defined because what we've heard from you is that that lack of legacy, we don't have a huge router business or a huge sand business to protect. It's that lack of legacy that's enabling us to invest and get ahead of the curb on this next transition to Software-Defined. So you're going to see us doing that through building our internal IP, through some significant joint ventures, and also through some merges and acquisitions over the next several quarters. Altogether, we're driving to be the most trusted data center provider in the industry between us and our customers and our suppliers. So a quick summary of what we're going to dive into today, both in my keynote as well as in the breakout sessions. We're in this transformation to the next phase of Lenovo's data center growth. We're closing out our previous transformation. We actually, believe it or not, in the last six months or so, have renegotiated 18,000 contracts in 160 countries. We built out an entire end-to-end organization from development and architecture all the way through sales and support. This next transformation, I think, is really going to excite Lenovo shareholders. We're building the largest data center portfolio in our history. I think when IBM would be up here a couple years ago, we might have two or three servers to announce in time to market with the next Intel platform. Today, we're announcing 14 new servers, seven new storage systems, an expanded set of networking portfolios based on our legacy with Blade Network Technologies and other companies we've acquired. Two new brands that we'll talk about for both data center infrastructure and Software-Defined, a new set of premium premiere services as well as a set of engineered solutions that are going to help our customers get to market faster. We're going to be celebrating our 20 millionth x86 server, and as Rod said, 25 years in x86 server compute, and Christian will be up here talking about 25 years of ThinkPad as well. And then a new end-to-end segmentation model because all of these strategies without execution are kind of meaningless. I hope to give you some confidence in the transformation that Lenovo has gone through as well. So, having observed Lenovo from one of its largest partners, Intel, for more than a couple decades, I thought I'd just start with why we have confidence on the foundation that we're building off of as we move from a PC company into a data center provider in a much more significant way. So Lenovo today is a company of $43 billion in sales. Absolutely astonishing, it puts us at about Fortune 202 as a company, with 52,000 employees around the world. We're supporting and have service personnel, almost a little over 10,000 service personnel that service our servers and data center technologies in over 160 countries that provide onsite service and support. We have seven data center research centers. One of the reasons I came from Intel to Lenovo was that I saw that Lenovo became number one in PCs, not through cost cutting but through innovation. It was Lenovo that was partnering on the next-generation Ultrabooks and two-in-ones and tablets in the modem mods that you saw, but fundamentally, our path to number one in data center is going to be built on innovation. Lastly, we're one of the last companies that's actually building not only our own motherboards at our own motherboard factories, but also with five global data center manufacturing facilities. Today, we build about four devices a second, but we also build over 100 servers per hour, and the cost economics we get, and I just visited our Shenzhen factory, of having everything from screws to microprocessors come up through the elevator on the first floor, go left to build PCs and ThinkPads and go right to build server technology, means we have some of the world's most cost effective solutions so we can compete in things like hyperscale computing. So it's with that that I think we're excited about the foundation that we can build off of on the Data Center Group. Today, as we stated, this event is about transformation, and today, I want to talk about three things we're going to transform. Number one is the customer experience. Number two is the data center and our customer base with Software-Defined infrastructure, and then the third is talk about how we plan to execute flawlessly with a new transformation that we've had internally at Lenovo. So let's dive into it. On customer experience, really, what does it mean to transform customer experience? Industry pundits say that if you're not constantly innovating, you can fall behind. Certainly the technology industry that we're in is transforming at record speed. 42% of business leaders or CIOs say that digital first is their top priority, but less than 50% actually admit that they have a strategy to get there. So people are looking for a partner to keep pace with that innovation and change, and that's really what we're driving to at Lenovo. So today we're announcing a set of plans to take another step function in customer experience, and building off of our number one position. Just recently, Gartner shows Lenovo as the number 24 supply chains of companies over $12 billion. We're up there with Amazon, Coca-Cola, and we've now completely re-architected our supply chain in the Data Center Group from end to end. Today, we can deliver 90% of our SKUs, order to ship in less than seven days. The artificial intelligence that YY mentioned is optimizing our performance even further. In services, as we talked about, we're now in 160 countries, supporting on-site support, 50 different call centers around the world for local language support, and we're today announcing a whole set of new premiere support services that I'll get into in a second. But we're building on what's already better than 90% customer satisfaction in this space. And then in development, for all the engineers out there, we started foundationally for this new set of products, talking about being number one in reliability and the lowest downtime of any x86 server vendor on the planet, and these systems today are architected to basically extend that leadership position. So let me tell you the realities of reliability. This is ITIC, it's a reliability report. 750 CIOs and IT managers from more than 20 countries, so North America, Europe, Asia, Australia, South America, Africa. This isn't anything that's paid for with sponsorship dollars. Lenovo has been number one for four years running on x86 reliability. This is the amount of downtime, four hours or more, in mission-critical environments from the leading x86 providers. You can see relative to our top two competitors that are ahead of us, HP and Dell, you can see from ITIC why we are building foundationally off of this, and why it's foundational to how we're developing these new platforms. In customer satisfaction, we are also rated number one in x86 server customer satisfaction. This year, we're now incentivizing every single Lenovo employee on customer satisfaction and customer experience. It's been a huge mandate from myself and most importantly YY as our CEO. So you may say well what is the basis of this number one in customer satisfaction, and it's not just being number one in one category, it's actually being number one in 21 of the 22 categories that TBR talks about. So whether it's performance, support systems, online product information, parts and availability replacement, Lenovo is number one in 21 of the 22 categories and number one for six consecutive studies going back to Q1 of 2015. So this, again, as we talk about the new product introductions, it's something that we absolutely want to build on, and we're humbled by it, and we want to continue to do better. So let's start now on the new products and talk about how we're going to transform the data center. So today, we are announcing two new product offerings. Think Agile and ThinkSystem. If you think about the 25 years of ThinkPad that Christian's going to talk about, Lenovo has a continuous learning culture. We're fearless innovators, we're risk takers, we continuously learn, but, most importantly, I think we're humble and we have some humility. That when we fail, we can fail fast, we learn, and we improve. That's really what drove ThinkPad to number one. It took about eight years from the acquisition of IBM's x86 PC business before Lenovo became number one, but it was that innovation, that listening and learning, and then improving. As you look at the 25 years of ThinkPad, there were some amazing successes, but there were also some amazing failures along the way, but each and every time we learned and made things better. So this year, as Rod said, we're not just celebrating 25 years of ThinkPad, but we're celebrating 25 years of x86 server development since the original IBM PC servers in 1992. It's a significant day for Lenovo. Today, we're excited to announce two new brands. ThinkSystem and ThinkAgile. It's an important new announcement that we started almost three years ago when we acquired the x86 server business. Why don't we run a video, and we'll show you a little bit about ThinkSystem and ThinkAgile. >> Narrator: The status quo is comfortable. It gets you by, but if you think that's good enough for your data center, think again. If adoption is becoming more complicated when it should be simpler, think again. If others are selling you technology that's best for them, not for you, think again. It's time for answers that win today and tomorrow. Agile, innovative, different. Because different is better. Different embraces change and makes adoption simple. Different designs itself around you. Using 25 years of innovation and design and R&D. Different transforms, it gives you ThinkSystem. World-record performance, most reliable, easy to integrate, scales faster. Different empowers you with ThinkAgile. It redefines the experience, giving you the speed of Cloud and the control of on-premise IT. Responding faster to what your business really needs. Different defines the future. Introducing Lenovo ThinkSystem and ThinkAgile. (exciting and slightly aggressive digital instrumental) >> All right, good stuff, huh? (audience applauds) So it's built off of this 25-year history of us being in the x86 server business, the commitment we established three years ago after acquiring the x86 server business to be and have the most reliable, the most agile, and the most highest-performing data center solutions on the planet. So today we're announcing two brands. ThinkSystem is for the traditional data center infrastructure, and ThinkAgile is our brand for Software-Defined infrastructure. Again, the teams challenge themselves from the start, how do we build off this rich heritage, expanding our position as number one in customer satisfaction, reliability, and one of the world's best supply chains. So let's start and look at the next set of solutions. We have always prided ourself that little things don't mean a lot. Little things mean everything. So today, as we said on the legacy solutions, we have over 30 world-record performance benchmarks on Intel architecture, and more than actually 150 since we started tracking this back in 2001. So it's the little pieces of innovation. It's the fine tuning that we do with our partners like an Intel or a Microsoft, an SAP, VMware, and Nutanix that's enabling us to get these world-record performance benchmarks, and with this next generation of solutions we think we'll continue to certainly do that. So today we're announcing the most comprehensive portfolio ever in our data center history. There's 14 servers, seven storage devices, and five network switches. We're also announcing, which is super important to our customer base, a set of new premiere service options. That's giving you fast access directly to a level two support person. No automated response system involved. You get to pick up the phone and directly talk to a level two support person that's going to have end-to-end ownership of the customer experience for ThinkSystem. With ThinkAgile, that's going to be completely bundled with every ThinkAgile you purchase. In addition, we're having white glove service on site that will actually unbox the product for you and get it up and running. It's an entirely new set of solutions for hybrid Cloud, for big data analytics and database applications around these engineered solutions. These are like 40- to 50-page guides where we fine-tuned the most important applications around virtual desktop infrastructure and those kinds of applications, working side by side with all of our ISP partners. So significantly expanding, not just the hardware but the software solutions that, obviously, you, as our customers, are running. So if you look at ThinkSystem innovation, again, it was designed for the ultimate in flexibility, performance, and reliability. It's a single now-unified brand that combines what used to be the Lenovo Think server and the IBM System x products now into a single brand that spans server, storage, and networking. We're basically future-proofing it for the next-generation data center. It's a significantly simplified portfolio. One of the big pieces that we've heard is that the complexity of our competitors has really been overwhelming to customers. We're building a more flexible, more agile solution set that requires less work, less qualification, and more future proofing. There's a bunch of things in this that you'll see in the demos. Faster time-to-service in terms of the modularity of the systems. 12% faster service equating to almost $50 thousand per hour of reduced downtime. Some new high-density options where we have four nodes and a 2U, twice the density to improve and reduce outbacks and mission-critical workloads. And then in high-performance computing and supercomputing, we're going to spend some time on that here shortly. We're announcing new water-cooled solutions. We have some of the most premiere water-cooled solutions in the world, with more than 25 patents pending now, just in the water-cooled solutions for supercomputing. The performance that we think we're going to see out of these systems is significant. We're building off of that legacy that we have today on the existing Intel solutions. Today, we believe we have more than 50% of SAP HANA installations in the world. In fact, SAP just went public that they're running their internal SAP HANA on Lenovo hardware now. We're seeing a 59% increase in performance on SAP HANA generation on generation. We're seeing 31% lower total cost to ownership. We believe this will continue our position of having the highest level of five-nines in the x86 server industry. And all of these servers will start being available later this summer when the Intel announcements come out. We're also announcing the largest storage portfolio in our history, significantly larger than anything we've done in the past. These are all available today, including some new value class storage offerings. Our network portfolio is expanding now significantly. It was a big surprise when I came to Lenovo, seeing the hundreds of engineers we had from the acquisition of Blade Network Technologies and others with our teams in Romania, Santa Clara, really building out both the embedded portfolio but also the top racks, which is around 10 gig, 25 gig, and 100 gig. Significantly better economics, but all the performance you'd expect from the largest networking companies in the world. Those are also available today. ThinkAgile and Software-Defined, I think the one thing that has kind of overwhelmed me since coming in to Lenovo is we are being embraced by our customers because of our lack of legacy. We're not trying to sell you one more legacy SAN at 65% margins. ThinkAgile really was founded, kind of born free from the shackles of legacy thinking and legacy infrastructure. This is just the beginning of what's going to be an amazing new brand in the transformation to Software-Defined. So, for Lenovo, we're going to invest in our own internal organic IP. I'll foreshadow: There's some significant joint ventures and some mergers and acquisitions that are going to be coming in this space. And so this will be the foundation for our Software-Defined networking and storage, for IoT, and ultimately for the 5G build-out as well. This is all built for data centers of tomorrow that require fluid resources, tightly integrated software and hardware in kind of an appliance, selling at the rack level, and so we'll show you how that is going to take place here in a second. ThinkAgile, we have a few different offerings. One is around hyperconverged storage, Hybrid Cloud, and also Software-Defined storage. So we're really trying to redefine the customer experience. There's two different solutions we're having today. It's a Microsoft Azure solution and a Nutanix solution. These are going to be available both in the appliance space as well as in a full rack solution. We're really simplifying and trying to transform the entire customer experience from how you order it. We've got new capacity planning tools that used to take literally days for us to get the capacity planning done. It's now going down to literally minutes. We've got new order, delivery, deployment, administration service, something we're calling ThinkAgile Advantage, which is the white glove unboxing of the actual solutions on prem. So the whole thing when you hear about it in the breakout sessions about transforming the entire customer experience with both an HX solution and an SX solution. So again, available at the rack level for both Nutanix and for Microsoft Solutions available in just a few months. Many of you in the audience since the Microsoft Airlift event in Seattle have started using these things, and the feedback to date has been fantastic. We appreciate the early customer adoption that we've seen from people in the audience here. So next I want to bring up one of our most important partners, and certainly if you look at all of these solutions, they're based on the next-generation Intel Xeon scalable processor that's going to be announcing very very soon. I want to bring on stage Rupal Shah, who's the corporate vice president and general manager of Global Data Center Sales with Intel, so Rupal, please join me. (upbeat instrumental) So certainly I have long roots at Intel, but why don't you talk about, from Intel's perspective, why Lenovo is an important partner for Lenovo. >> Great, well first of all, thank you very much. I've had the distinct pleasure of not only working with Kirk for many many years, but also working with Lenovo for many years, so it's great to be here. Lenovo is not only a fantastic supplier and leader in the industry for Intel-based servers but also a very active partner in the Intel ecosystem. In the Intel ecosystem, specifically, in our partner programs and in our builder programs around Cloud, around the network, and around storage, I personally have had a long history in working with Lenovo, and I've seen personally that PC transformation that you talked about, Kirk, and I believe, and I know that Intel believes in Lenovo's ability to not only succeed in the data center but to actually lead in the data center. And so today, the ThinkSystem and ThinkAgile announcement is just so incredibly important. It's such a great testament to our two companies working together, and the innovation that we're able to bring to the market, and all of it based on the Intel Xeon scalable processor. >> Excellent, so tell me a little bit about why we've been collaborating, tell me a little bit about why you're excited about ThinkSystem and ThinkAgile, specifically. >> Well, there are a lot of reasons that I'm excited about the innovation, but let me talk about a few. First, both of our companies really stand behind the fact that it's increasingly a hybrid world. Our two companies offer a range of solutions now to customers to be able to address their different workload needs. ThinkSystem really brings the best, right? It brings incredible performance, flexibility in data center deployment, and industry-leading reliability that you've talked about. And, as always, Xeon has a history of being built for the data center specifically. The Intel Xeon scalable processor is really re-architected from the ground up in order to enhance compute, network, and storage data flows so that we can deliver workload optimized performance for both a wide range of traditional workloads and traditional needs but also some emerging new needs in areas like artificial intelligence. Second is when it comes to the next generation of Cloud infrastructure, the new Lenovo ThinkAgile line offers a truly integrated offering to address data center pain points, and so not only are you able to get these pretested solutions, but these pretested solutions are going to get deployed in your infrastructure faster, and they're going to be deployed in a way that's going to meet your specific needs. This is something that is new for both of us, and it's an incredible innovation in the marketplace. I think that it's a great addition to what is already a fantastic portfolio for Lenovo. >> Excellent. >> Finally, there's high-performance computing. In high-performance computing. First of all, congratulations. It's a big week, I think, for both of us. Fantastic work that we've been doing together in high-performance computing and actually bringing the best of the best to our customers, and you're going to hear a whole lot more about that. We obviously have a number of joint innovation centers together between Intel and Lenovo. Tell us about some of the key innovations that you guys are excited about. >> Well, Intel and Lenovo, we do have joint innovation labs around the world, and we have a long and strong history of very tight collaboration. This has brought a big wave of innovation to the marketplace in areas like software-defined infrastructure. Yet another area is working closely on a joint vision that I think our two companies have in artificial intelligence. Intel is very committed to the world of AI, and we're committed in making the investments required in technology development, in training, and also in R&D to be able to deliver end-to-end solutions. So with Intel's comprehensive technology portfolio and Lenovo's development and innovation expertise, it's a great combination in this space. I've already talked a little bit about HPC and so has Kirk, and we're going to hear a little bit more to come, but we're really building the fastest compute solutions for customers that are solving big problems. Finally, we often talk about processors from Intel, but it's not just about the processors. It's way beyond that. It's about engaging at the solution level for our customers, and I'm so excited about the work that we've done together with Lenovo to bring to market products like Intel Omni-Path Architecture, which is really the fabric for high-performance data centers. We've got a great showing this week with Intel Omni-Path Architecture, and I'm so grateful for all the work that we've done to be able to bring true solutions to the marketplace. I am really looking forward to our future collaboration with Lenovo as we have in the past. I want to thank you again for inviting me here today, and congratulations on a fantastic launch. >> Thank you, Rupal, very much, for the long partnership. >> Thank you. (audience applauds) >> Okay, well now let's transition and talk a little bit about how Lenovo is transforming. The first thing we've done when I came on board about six months ago is we've transformed to a truly end-to-end organization. We're looking at the market segments I think as our customers define them, and we've organized into having vice presidents and senior vice presidents in charge of each of these major groups, thinking really end to end, from architecture all the way to end of life and customer support. So the first is hyperscale infrastructure. It's about 20% on the market by 2020. We've hired a new vice president there to run that business. Given we can make money in high-volume desktop PCs, it's really the manufacturing prowess, deep engineering collaboration that's enabling us to sell into Baidu, and to Alibaba, Tencent, as well as the largest Cloud vendors on the West Coast here in the United States. We believe we can make money here by having basically a deep deep engineering engagement with our key customers and building on the PC volume economics that we have within Lenovo. On software-defined infrastructure, again, it's that lack of legacy that I think is propelling us into this space. We're not encumbered by trying to sell one more legacy SAN or router, and that's really what's exciting us here, as we transform from a hardware to a software-based company. On HPC and AI, as we said, we'll talk about this in a second. We're the fastest-growing supercomputing company on earth. We have aspirations to be the largest supercomputing company on earth, with China and the U.S. vying for number one in that position, it puts us in a good position there. We're going to bridge that into artificial intelligence in our upcoming Shanghai Tech World. The entire day is around AI. In fact, YY has committed $1.2 billion to artificial intelligence over the next few years of R&D to help us bridge that. And then on data center infrastructure, is really about moving to a solutions based infrastructure like our position with SAP HANA, where we've gone deep with engineers on site at SAP, SAP running their own infrastructure on Lenovo and building that out beyond just SAP to other solutions in the marketplace. Overall, significantly expanding our services portfolio to maintain our number one customer satisfaction rating. So given ISC, or International Supercomputing, this week in Frankfurt, and a lot of my team are actually over there, I wanted to just show you the transformation we've had at Lenovo for delivering some of the technology to solve some of the most challenging humanitarian problems on earth. Today, we are the fastest-growing supercomputer company on the planet in terms of number of systems on the Top 500 list. We've gone from zero to 92 positions in just a few short years, but IDC also positions Lenovo as the fast-growing supercomputer and HPC company overall at about 17% year on year growth overall, including all of the broad channel, the regional universities and this kind of thing, so this is an exciting place for us. I'm excited today that Sergi has come all the way from Spain to be with us today. It's an exciting time because this week we announce the fastest next-generation Intel supercomputer on the planet at Barcelona Supercomputer. Before I bring Sergi on stage, let's run a video and I'll show you why we're excited about the capabilities of these next-generation supercomputers. Run the video please. >> Narrator: Different creates one of the most powerful supercomputers for the Barcelona Supercomputer Center. A high-performance, high-capacity design to help shape tomorrow's world. Different designs what's best for you, with 25 years of end-to-end expertise delivering large-scale solutions. It integrates easily with technology from industry partners, through deep collaboration with the client to manufacture, test, configure, and install at global scale. Different achieves the impossible. The first of a new series. A more energy-efficient supercomputer yet 10 times more powerful than its predecessor. With over 3,400 Lenovo ThinkSystem servers, each performing over two trillion calculations per second, giving us 11.1 petaflop capacity. Different powers MareNostrum, a supercomputer that will help us better understand cancer, help discover disease-fighting therapies, predict the impact of climate change. MareNostrom 4.0 promises to uncover answers that will help solve humanities greatest challenges. (audience applauds) >> So please help me in welcoming operations director of the Barcelona Supercomputer Center, Sergi Girona. So welcome, and again, congratulations. It's been a big week for both of us. But I think for a long time, if you haven't been to Barcelona, this has been called the world's most beautiful computer because it's in one of the most gorgeous chapels in the world as you can see here. Congratulations, we now are number 13 on the Top500 list and the fastest next-generation Intel computer. >> Thank you very much, and congratulations to you as well. >> So maybe we can just talk a little bit about what you've done over the last few months with us. >> Sure, thank you very much. It is a pleasure for me being invited here to present to you what we've been doing with Lenovo so far and what we are planning to do in the next future. I'm representing here Barcelona Supercomputing Center. I am presenting high-performance computing services to science and industry. How we see these science services has changed the paradigm of science. We are coming from observation. We are coming from observation on the telescopes and the microscopes and the building of infrastructures, but this is not affordable anymore. This is very expensive, so it's not possible, so we need to move to simulations. So we need to understand what's happening in our environment. We need to predict behaviors only going through simulation. So, at BSC, we are devoted to provide services to industry, to science, but also we are doing our own research because we want to understand. At the same time, we are helping and developing the new engineers of the future on the IT, on HPC. So we are having four departments based on different topics. The main and big one is wiling to understand how we are doing the next supercomputers from the programming level to the performance to the EIA, so all these things, but we are having also interest on what about the climate change, what's the air quality that we are having in our cities. What is the precision medicine we need to have. How we can see that the different drugs are better for different individuals, for different humans, and of course we have an energy department, taking care of understanding what's the better optimization for a cold, how we can save energy running simulations on different topics. But, of course, the topic of today is not my research, but it's the systems we are building in Barcelona. So this is what we have been building in Barcelona so far. From left to right, you have the preparation of the facility because this is 160 square meters with 1.4 megabytes, so that means we need new piping, we need new electricity, at the same time in the center we have to install the core services of the system, so the management practices, and then on the right-hand side you have installation of the networking, the Omni-Path by Intel. Because all of the new racks have to be fully integrated and they need to come into operation rapidly. So we start deployment of the system May 15, and we've now been ending and coming in production July first. All the systems, all the (mumbles) systems from Lenovo are coming before being open and available. What we've been installing here in Barcelona is general purpose systems for our general workload of the system with 3,456 nodes. Everyone of those having 48 cores, 96 gigabytes main memory for a total capacity of about 400 terabytes memory. The objective of this is that we want to, all the system, all the processors, to work together for a single execution for running altogether, so this is an example of the platinum processors from Intel having 24 cores each. Of course, for doing this together with all the cores in the same application, we need a high-speed network, so this is Omni-Path, and of course all these cables are connecting all the nodes. Noncontention, working together, cooperating. Of course, this is a bunch of cables. They need to be properly aligned in switches. So here you have the complete presentation. Of course, this is general purpose, but we wanted to invest with our partners. We want to understand what the supercomputers we wanted to install in 2020, (mumbles) Exascale. We want to find out, we are installing as well systems with different capacities with KNH, with power, with ARM processors. We want to leverage our obligations for the future. We want to make sure that in 2020 we are ready to move our users rapidly to the new technologies. Of course, this is in total, giving us a total capacity of 13.7 petaflops that it's 12 times the capacity of the former MareNostrum four years ago. We need to provide the services to our scientists because they are helping to solve problems for humanity. That's the place we are going to go. Last is inviting you to come to Barcelona to see our place and our chapel. Thank you very much (audience applauds). >> Thank you. So now you can all go home to your spouses and significant others and say you have a formal invitation to Barcelona, Spain. So last, I want to talk about what we've done to transform Lenovo. I think we all know the history is nice but without execution, none of this is going to be possible going forward, so we have been very very busy over the last six months to a year of transforming Lenovo's data center organization. First, we moved to a dedicated end-to-end sales and marketing organization. In the past, we had people that were shared between PC and data center, now thousands of sales people around the world are 100% dedicated end to end to our data center clients. We've moved to a fully integrated and dedicated supply chain and procurement organization. A fully dedicated quality organization, 100% dedicated to expanding our data center success. We've moved to a customer-centric segment, again, bringing in significant new leaders from outside the company to look end to end at each of these segments, supercomputing being very very different than small business, being very very different than taking care of, for example, a large retailer or bank. So around hyperscale, software-defined infrastructure, HPC, AI, and supercomputing and data center solutions-led infrastructure. We've built out a whole new set of global channel programs. Last year, or a year passed, we have five different channel programs around the world. We've now got one simplified channel program for dealer registration. I think our channel is very very energized to go out to market with Lenovo technology across the board, and a whole new set of system integrator relationships. You're going to hear from one of them in Christian's discussion, but a whole new set of partnerships to build solutions together with our system integrative partners. And, again, as I mentioned, a brand new leadership team. So look forward to talking about the details of this. There's been a significant amount of transformation internal to Lenovo that's led to the success of this new product introduction today. So in conclusion, I want to talk about the news of the day. We are transforming Lenovo to the next phase of our data center growth. Again, in over 160 countries, closing on that first phase of transformation and moving forward with some unique declarations. We're launching the largest portfolio in our history, not just in servers but in storage and networking, as everything becomes kind of a software personality on top of x86 Compute. We think we're very well positioned with our scale on PCs as well as data center. Two new brands for both data center infrastructure and Software-Defined, without the legacy shackles of our competitors, enabling us to move very very quickly into Software-Defined, and, again, foreshadowing some joint ventures in M&A that are going to be coming up that will further accelerate ourselves there. New premiere support offerings, enabling you to get direct access to level two engineers and white glove unboxing services, which are going to be bundled along with ThinkAgile. And then celebrating the milestone of 25 years in x86 server compute, not just ThinkPads that you'll hear about shortly, but also our 20 million server shipping next month. So we're celebrating that legacy and looking forward to the next phase. And then making sure we have the execution engine to maintain our position and grow it, being number one in customer satisfaction and number one in quality. So, with that, thank you very much. I look forward to seeing you in the breakouts today and talking with many of you, and I'll bring Rod back up to transition us to the next section. Thank you. (audience applauds) >> All right, Kirk, thank you, sir. All right, ladies and gentlemen, what did you think of that? How about a big round of applause for ThinkAgile, ThinkSystems new brands? (audience applauds) And, obviously, with that comes a big round of applause, for Kirk Skaugen, my boss, so we've got to give him a big round of applause, please. I need to stay employed, it's very important. All right, now you just heard from Kirk about some of the new systems, the brands. How about we have a quick look at the video, which shows us the brand new DCG images. >> Narrator: Legacy thinking is dead, stuck in the past, selling the same old stuff, over and over. So then why does it seem like a data center, you know, that thing powering all our little devices and more or less everything interaction today is still stuck in legacy thinking because it's rigid, inflexible, slow, but that's not us. We don't do legacy. We do different. Because different is fearless. Different reduces Cloud deployment from days to hours. Different creates agile technology that others follow. Different is fluid. It uses water-cooling technology to save energy. It co-innovates with some of the best minds in the industry today. Different is better, smarter. Maybe that's why different already holds so many world-record benchmarks in everything. From virtualization to database and application performance or why it's number one in reliability and customer satisfaction. Legacy sells you what they want. Different builds the data center you need without locking you in. Introducing the Data Center Group at Lenovo. Different... Is better. >> All right, ladies and gentlemen, a big round of applause, once again (mumbles) DCG, fantastic. And I'm sure all of you would agree, and Kirk mentioned it a couple of times there. No legacy means a real consultative approach to our customers, and that's something that we really feel is differentiated for ourselves. We are effectively now one of the largest startups in the DCG space, and we are very much ready to disrupt. Now, here in New York City, obviously, the heart of the fashion industry, and much like fashion, as I mentioned earlier, we're different, we're disruptive, we're agile, smarter, and faster. I'd like to say that about myself, but, unfortunately, I can't. But those of you who have observed, you may have noticed that I, too, have transformed. I don't know if anyone saw that. I've transformed from the pinstripe blue, white shirt, red tie look of the, shall we say, our predecessors who owned the x86 business to now a very Lenovo look. No tie and consequently a little bit more chic New York sort of fashion look, shall I say. Nothing more than that. So anyway, a bit of a transformation. It takes a lot to get to this look, by the way. It's a lot of effort. Our next speaker, Christian Teismann, is going to talk a lot about the core business of Lenovo, which really has been, as we've mentioned today, our ThinkPad, 25-year anniversary this year. It's going to be a great celebration inside Lenovo, and as we get through the year and we get closer and closer to the day, you'll see a lot more social and digital work that engages our customers, partners, analysts, et cetera, when we get close to that birthday. Customers just generally are a lot tougher on computers. We know they are. Whether you hang onto it between meetings from the corner of the Notebook, and that's why we have magnesium chassis inside the box or whether you're just dropping it or hypothetically doing anything else like that. We do a lot of robust testing on these products, and that's why it's the number one branded Notebook in the world. So Christian talks a lot about this, but I thought instead of having him talk, I might just do a little impromptu jump back stage and I'll show you exactly what I'm talking about. So follow me for a second. I'm going to jaunt this way. I know a lot of you would have seen, obviously, the front of house here, what we call the front of house. Lots of videos, et cetera, but I don't think many of you would have seen the back of house here, so I'm going to jump through the back here. Hang on one second. You'll see us when we get here. Okay, let's see what's going on back stage right now. You can see one of the team here in the back stage is obviously working on their keyboard. Fantastic, let me tell you, this is one of the key value props of this product, obviously still working, lots of coffee all over it, spill-proof keyboard, one of the key value propositions and why this is the number one laptop brand in the world. Congratulations there, well done for that. Obviously, we test these things. Height, distances, Mil-SPEC approved, once again, fantastic product, pick that up, lovely. Absolutely resistant to any height or drops, once again, in line with our Mil-SPEC. This is Charles, our producer and director back stage for the absolute event. You can see, once again, sand, coincidentally, in Manhattan, who would have thought a snow storm was occurring here, but you can throw sand. We test these things for all of the elements. I've obviously been pretty keen on our development solutions, having lived in Japan for 12 years. We had this originally designed in 1992 by (mumbles), he's still our chief development officer still today, fantastic, congratulations, a sand-enhanced notebook, he'd love that. All right, let's get back out front and on with the show. Watch the coffee. All right, how was that? Not too bad (laughs). It wasn't very impromptu at all, was it? Not at all a set up (giggles). How many people have events and have a bag of sand sitting on the floor right next to a Notebook? I don't know. All right, now it's time, obviously, to introduce our next speaker, ladies and gentlemen, and I hope I didn't steal his thunder, obviously, in my conversations just now that you saw back stage. He's one of my best friends in Lenovo and easily is a great representative of our legendary PC products and solutions that we're putting together for all of our customers right now, and having been an ex-Pat with Lenovo in New York really calls this his second home and is continually fighting with me over the fact that he believes New York has better sushi than Tokyo, let's welcome please, Christian Teismann, our SVP, Commercial Business Segment, and PC Smart Office. Christian Teismann, come on up mate. (audience applauds) >> So Rod thank you very much for this wonderful introduction. I'm not sure how much there is to add to what you have seen already back stage, but I think there is a 25-year of history I will touch a little bit on, but also a very big transformation. But first of all, welcome to New York. As Rod said, it's my second home, but it's also a very important place for the ThinkPad, and I will come back to this later. The ThinkPad is thee industry standard of business computing. It's an industry icon. We are celebrating 25 years this year like no other PC brand has done before. But this story today is not looking back only. It's a story looking forward about the future of PC, and we see a transformation from PCs to personalized computing. I am privileged to lead the commercial PC and Smart device business for Lenovo, but much more important beyond product, I also am responsible for customer experience. And this is what really matters on an ongoing basis. But allow me to stay a little bit longer with our iconic ThinkPad and history of the last 25 years. ThinkPad has always stand for two things, and it always will be. Highest quality in the industry and technology innovation leadership that matters. That matters for you and that matters for your end users. So, now let me step back a little bit in time. As Rod was showing you, as only Rod can do, reliability is a very important part of ThinkPad story. ThinkPads have been used everywhere and done everything. They have survived fires and extreme weather, and they keep surviving your end users. For 25 years, they have been built for real business. ThinkPad also has a legacy of first innovation. There are so many firsts over the last 25 years, we could spend an hour talking about them. But I just want to cover a couple of the most important milestones. First of all, the ThinkPad 1992 has been developed and invented in Japan on the base design of a Bento box. It was designed by the famous industrial designer, Richard Sapper. Did you also know that the ThinkPad was the first commercial Notebook flying into space? In '93, we traveled with the space shuttle the first time. For two decades, ThinkPads were on every single mission. Did you know that the ThinkPad Butterfly, the iconic ThinkPad that opens the keyboard to its size, is the first and only computer showcased in the permanent collection of the Museum of Modern Art, right here in New York City? Ten years later, in 2005, IBM passed the torch to Lenovo, and the story got even better. Over the last 12 years, we sold over 100 million ThinkPads, four times the amount IBM sold in the same time. Many customers were concerned at that time, but since then, the ThinkPad has remained the best business Notebook in the industry, with even better quality, but most important, we kept innovating. In 2012, we unveiled the X1 Carbon. It was the thinnest, lightest, and still most robust business PC in the world. Using advanced composited materials like a Formula One car, for super strengths, X1 Carbon has become our ThinkPad flagship since then. We've added an X1 Carbon Yoga, a 360-degree convertible. An X1 Carbon tablet, a detachable, and many new products to come in the future. Over the last few years, many new firsts have been focused on providing the best end-user experience. The first dual-screen mobile workstation. The first Windows business tablet, and the first business PC with OLED screen technology. History is important, but a massive transformation is on the way. Future success requires us to think beyond the box. Think beyond hardware, think beyond notebooks and desktops, and to think about the future of personalized computing. Now, why is this happening? Well, because the business world is rapidly changing. Looking back on history that YY gave, and the acceleration of innovation and how it changes our everyday life in business and in personal is driving a massive change also to our industry. Most important because you are changing faster than ever before. Human capital is your most important asset. In today's generation, they want to have freedom of choice. They want to have a product that is tailored to their specific needs, every single day, every single minute, when they use it. But also IT is changing. The Cloud, constant connectivity, 5G will change everything. Artificial intelligence is adding things to the capability of an infrastructure that we just are starting to imagine. Let me talk about the workforce first because it's the most important part of what drives this. The millennials will comprise more than half of the world's workforce in 2020, three years from now. Already, one out of three millennials is prioritizing mobile work environment over salary, and for nearly 60% of all new hires in the United States, technology is a very important factor for their job search in terms of the way they work and the way they are empowered. This new generation of new employees has grown up with PCs, with Smart phones, with tablets, with touch, for their personal use and for their occupation use. They want freedom. Second, the workplace is transforming. The video you see here in the background. This is our North America headquarters in Raleigh, where we have a brand new Smart workspace. We have transformed this to attract the new generation of workers. It has fewer traditional workspaces, much more meaning and collaborative spaces, and Lenovo, like many companies, is seeing workspaces getting smaller. An average workspace per employee has decreased by 30% over the last five years. Employees are increasingly mobile, but, if they come to the office, they want to collaborate with their colleagues. The way we collaborate and communicate is changing. Investment in new collaboration technology is exploding. The market of collaboration technology is exceeding the market of personal computing today. It will grow in the future. Conference rooms are being re-imagined from a ratio of 50 employees to one large conference room. Today, we are moving into scenarios of four employees to one conference room, and these are huddle rooms, pioneer spaces. Technology is everywhere. Video, mega-screens, audio, electronic whiteboards. Adaptive technologies are popping up and change the way we work. As YY said earlier, the pace of the revolution is astonishing. So personalized computing will transform the PC we all know. There's a couple of key factors that we are integrating in our next generations of PC as we go forward. The most important trends that we see. First of all, choose your own device. We talked about this new generation of workforce. Employees who are used to choosing their own device. We have to respond and offer devices that are tailored to each end user's needs without adding complexity to how we operate them. PC is a service. Corporations increasingly are looking for on-demand computing in data center as well as in personal computing. Customers want flexibility. A tailored management solution and a services portfolio that completes the lifecycle of the device. Agile IT, even more important, corporations want to run an infrastructure that is agile, instant respond to their end-customer needs, that is self provisioning, self diagnostic, and remote software repair. Artificial intelligence. Think about artificial intelligence for you personally as your personal assistant. A personal assistant which does understand you, your schedule, your travel, your next task, an extension of yourself. We believe the PC will be the center of this mobile device universe. Mobile device synergy. Each of you have two devices or more with you. They need to work together across different operating systems, across different platforms. We believe Lenovo is uniquely positioned as the only company who has a Smart phone business, a PC business, and an infrastructure business to really seamlessly integrate all of these devices for simplicity and for efficiency. Augmented reality. We believe augmented reality will drive significantly productivity improvements in commercial business. The core will be to understand industry-specific solutions. New processes, new business challenges, to improve things like customer service and sales. Security will remain the foundation for personalized computing. Without security, without trust in the device integrity, this will not happen. One of the most important trends, I believe, is that the PC will transform, is always connected, and always on, like a Smart phone. Regardless if it's open, if it's closed, if you carry it, or if you work with it, it always is capable to respond to you and to work with you. 5G is becoming a reality, and the data capacity that will be out there is by far exceeding today's traffic imagination. Finally, Smart Office, delivering flexible and collaborative work environments regardless on where the worker sits, fully integrated and leverages all the technologies we just talked before. These are the main challenges you and all of your CIO and CTO colleagues have to face today. A changing workforce and a new set of technologies that are transforming PC into personalized computing. Let me give you a real example of a challenge. DXC was just formed by merging CSE company and HP's Enterprise services for the largest independent services company in the world. DXC is now a 25 billion IT services leader with more than 170,000 employees. The most important capital. 6,000 clients and eight million managed devices. I'd like to welcome their CIO, who has one of the most challenging workforce transformation in front of him. Erich Windmuller, please give him a round of applause. (audience applauds). >> Thank you Christian. >> Thank you. >> It's my pleasure to be here, thank you. >> So first of all, let me congratulation you to this very special time. By forming a new multi-billion-dollar enterprise, this new venture. I think it has been so far fantastically received by analysts, by the press, by customers, and we are delighted to be one of your strategic partners, and clearly we are collaborating around workforce transformation between our two companies. But let me ask you a couple of more personal questions. So by bringing these two companies together with nearly 200,00 employees, what are the first actions you are taking to make this a success, and what are your biggest challenges? >> Well, first, again, let me thank you for inviting me and for DXC Technology to be a part of this very very special event with Lenovo, so thank you. As many of you might expect, it's been a bit of a challenge over the past several months. My goal was really very simple. It was to make sure that we brought two companies together, and they could operate as one. We need to make sure that could continue to support our clients. We certainly need to make sure we could continue to sell, our sellers could sell. That we could pay our employees, that we could hire people, we could do all the basic foundational things that you might expect a company would want to do, but we really focused on three simple areas. I called it the three Cs. Connectivity, communicate, and collaborate. So we wanted to make sure that we connected our legacy data centers so we could transfer information and communicate back and forth. We certainly wanted to be sure that our employees could communicate via WIFI, whatever locations they may or may not go to. We certainly wanted to, when we talk about communicate, we need to be sure that everyone of our employees could send and receive email as a DXC employee. And that we had a single-enterprise directory and people could communicate, gain access to calendars across each of the two legacy companies, and then collaborate was also key. And so we wanted to be sure, again, that people could communicate across each other, that our legacy employees on either side could get access to many of their legacy systems, and, again, we could collaborate together as a single corporation, so it was challenging, but very very, great opportunity for all of us. And, certainly, you might expect cyber and security was a very very important topic. My chairman challenged me that we had to be at least as good as we were before from a cyber perspective, and when you bring two large companies together like that there's clearly an opportunity in this disruptive world so we wanted to be sure that we had a very very strong cyber security posture, of which Lenovo has been very very helpful in our achieving that. >> Thank you, Erich. So what does DXC consider as their critical solutions and technology for workplace transformation, both internally as well as out on the market? >> So workplace transformation, and, again, I've heard a lot of the same kinds of words that I would espouse... It's all about making our employees productive. It's giving the right tools to do their jobs. I, personally, have been focused, and you know this because Lenovo has been a very very big part of this, in working with our, we call it our My Style Workplace, it's an offering team in developing a solution and driving as much functionality as possible down to the workstation. We want to be able, for me, to avoid and eliminate other ancillary costs, audio video costs, telecommunication cost. The platform that we have, the digitized workstation that Lenovo has provided us, has just got a tremendous amount of capability. We want to streamline those solutions, as well, on top of the modern server. The modern platform, as we call it, internally. I'd like to congratulate Kirk and your team that you guys have successfully... Your hardware has been certified on our modern platform, which is a significant accomplishment between our two companies and our partnership. It was really really foundational. Lenovo is a big part of our digital workstation transformation, and you'll continue to be, so it's very very important, and I want you to know that your tools and your products have done a significant job in helping us bring two large corporations together as one. >> Thank you, Erich. Last question, what is your view on device as a service and hardware utility model? >> This is the easy question, right? So who in the room doesn't like PC or device as a service? This is a tremendous opportunity, I think, for all of us. Our corporation, like many of you in the room, we're all driven by the concept of buying devices in an Opex versus a Capex type of a world and be able to pay as you go. I think this is something that all of us would like to procure, product services and products, if you will, personal products, in this type of a mode, so I am very very eager to work with Lenovo to be sure that we bring forth a very dynamic and constructive device as a service approach. So very eager to do that with Lenovo and bring that forward for DXC Technology. >> Erich, thank you very much. It's a great pleasure to work with you, today and going forward on all sides. I think with your new company and our lineup, I think we have great things to come. Thank you very much. >> My pleasure, great pleasure, thank you very much. >> So, what's next for Lenovo PC? We already have the most comprehensive commercial portfolio in the industry. We have put the end user in the core of our portfolio to finish and going forward. Ultra mobile users, like consultants, analysts, sales and service. Heavy compute users like engineers and designers. Industry users, increasingly more understanding. Industry-specific use cases like education, healthcare, or banking. So, there are a few exciting things we have to announce today. Obviously, we don't have that broad of an announcement like our colleagues from the data center side, but there is one thing that I have that actually... Thank you Rod... Looks like a Bento box, but it's not a ThinkPad. It's a first of it's kind. It's the world's smallest professional workstation. It has the power of a tower in the Bento box. It has the newest Intel core architecture, and it's designed for a wide range of heavy duty workload. Innovation continues, not only in the ThinkPad but also in the desktops and workstations. Second, you hear much about Smart Office and workspace transformation today. I'm excited to announce that we have made a strategic decision to expand our Think portfolio into Smart Office, and we will soon have solutions on the table in conference rooms, working with strategic partners like Intel and like Microsoft. We are focused on a set of devices and a software architecture that, as an IoT architecture, unifies the management of Smart Office. We want to move fast, so our target is that we will have our first product already later this year. More to come. And finally, what gets me most excited is the upcoming 25 anniversary in October. Actually, if you go to Japan, there are many ThinkPad lovers. Actually beyond lovers, enthusiasts, who are collectors. We've been consistently asked in blogs and forums about a special anniversary edition, so let me offer you a first glimpse what we will announce in October, of something we are bring to market later this year. For the anniversary, we will introduce a limited edition product. This will include throwback features from ThinkPad's history as well as the best and most powerful features of the ThinkPad today. But we are not just making incremental adjustments to the Think product line. We are rethinking ThinkPad of the future. Well, here is what I would call a concept card. Maybe a ThinkPad without a hinge. Maybe one you can fold. What do you think? (audience applauds) but this is more than just design or look and feel. It's a new set of advanced materials and new screen technologies. It's how you can speak to it or write on it or how it speaks to you. Always connected, always on, and can communicate on multiple inputs and outputs. It will anticipate your next meeting, your next travel, your next task. And when you put it all together, it's just another part of the story, which we call personalized computing. Thank you very much. (audience applauds) Thank you, sir. >> Good on ya, mate. All right, ladies and gentlemen. We are now at the conclusion of the day, for this session anyway. I'm going to talk a little bit more about our breakouts and our demo rooms next door. But how about the power with no tower, from Christian, huh? Big round of applause. (audience applauds) And what about the concept card, the ThinkPad? Pretty good, huh? I love that as well. I tell you, it was almost like Leonardo DiCaprio was up on stage at one stage. He put that big ThinkPad concept up, and everyone's phones went straight up and took a photo, the whole audience, so let's be very selective on how we distribute that. I'm sure it's already on Twitter. I'll check it out in a second. So once again, ThinkPad brand is a core part of the organization, and together both DCG and PCSD, what we call PCSD, which is our client side of the business and Smart device side of the business, are obviously very very linked in transforming Lenovo for the future. We want to also transform the industry, obviously, and transform the way that all of us do business. Lenovo, if you look at basically a summary of the day, we are highly committed to being a top three data center provider. That is really important for us. We are the largest and fastest growing supercomputing company in the world, and Kirk actually mentioned earlier on, committed to being number one by 2020. So Madhu who is in Frankfurt at the International Supercomputing Convention, if you're watching, congratulations, your targets have gone up. There's no doubt he's going to have a lot of work to do. We're obviously very very committed to disrupting the data center. That's obviously really important for us. As we mentioned, with both the brands, the ThinkSystem, and our ThinkAgile brands now, highly focused on disrupting and ensuring that we do things differently because different is better. Thank you to our customers, our partners, media, analysts, and of course, once again, all of our employees who have been on this journey with us over the last two years that's really culminating today in the launch of all of our new products and our profile and our portfolio. It's really thanks to all of you that once again on your feedback we've been able to get to this day. And now really our journey truly begins in ensuring we are disrupting and enduring that we are bringing more value to our customers without that legacy that Kirk mentioned earlier on is really an advantage for us as we really are that large startup from a company perspective. It's an exciting time to be part of Lenovo. It's an exciting time to be associated with Lenovo, and I hope very much all of you feel that way. So a big round of applause for today, thank you very much. (audience applauds) I need to remind all of you. I don't think I'm going to have too much trouble getting you out there, because I was just looking at Christian on the streaming solutions out in the room out the back there, and there's quite a nice bit of lunch out there as well for those of you who are hungry, so at least there's some good food out there, but I think in reality all of you should be getting up into the demo sessions with our segment general managers because that's really where the rubber hits the road. You've heard from YY, you've heard from Kirk, and you've heard from Christian. All of our general managers and our specialists in our product sets are going to be out there to obviously demonstrate our technology. As we said at the very beginning of this session, this is Transform, obviously the fashion change, hopefully you remember that. Transform, we've all gone through the transformation. It's part of our season of events globally, and our next event obviously is going to be in Tech World in Shanghai on the 20th of July. I hope very much for those of you who are going to attend have a great safe travel over there. We look forward to seeing you. Hope you've had a good morning, and get into the sessions next door so you get to understand the technology. Thank you very much, ladies and gentlemen. (upbeat innovative instrumental)
SUMMARY :
This is Lenovo Transform. How are you all doing this morning? Not a cloud in the sky, perfect. One of the things about Lenovo that we say all the time... from the mobile Internet to the Smart Internet and the demo sessions with our segment general managers and the cost economics we get, and I just visited and the control of on-premise IT. and the feedback to date has been fantastic. and all of it based on the Intel Xeon scalable processor. and ThinkAgile, specifically. and it's an incredible innovation in the marketplace. the best of the best to our customers, and also in R&D to be able to deliver end-to-end solutions. Thank you. some of the technology to solve some of the most challenging Narrator: Different creates one of the most powerful in the world as you can see here. So maybe we can just talk a little bit Because all of the new racks have to be fully integrated from outside the company to look end to end about some of the new systems, the brands. Different builds the data center you need in the DCG space, and we are very much ready to disrupt. and change the way we work. and we are delighted to be one of your strategic partners, it's been a bit of a challenge over the past several months. and technology for workplace transformation, I've heard a lot of the same kinds of words Last question, what is your view on device and be able to pay as you go. It's a great pleasure to work with you, and most powerful features of the ThinkPad today. and get into the sessions next door
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Shaneil | PERSON | 0.99+ |
Erich Windmuller | PERSON | 0.99+ |
Richard Sapper | PERSON | 0.99+ |
Lenovo | ORGANIZATION | 0.99+ |
Europe | LOCATION | 0.99+ |
1992 | DATE | 0.99+ |
two | QUANTITY | 0.99+ |
Patrick Ewing | PERSON | 0.99+ |
Microsoft | ORGANIZATION | 0.99+ |
Data Center Group | ORGANIZATION | 0.99+ |
Dell | ORGANIZATION | 0.99+ |
Romania | LOCATION | 0.99+ |
Rupal Shah | PERSON | 0.99+ |
Matt Eastwood | PERSON | 0.99+ |
Christian Teismann | PERSON | 0.99+ |
May 15 | DATE | 0.99+ |
Rod | PERSON | 0.99+ |
Erich | PERSON | 0.99+ |
Australia | LOCATION | 0.99+ |
Rupal | PERSON | 0.99+ |
Alibaba | ORGANIZATION | 0.99+ |
Japan | LOCATION | 0.99+ |
IBM | ORGANIZATION | 0.99+ |
Pat Moorhead | PERSON | 0.99+ |
Spain | LOCATION | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Raleigh | LOCATION | 0.99+ |
Tencent | ORGANIZATION | 0.99+ |
Asia | LOCATION | 0.99+ |
2001 | DATE | 0.99+ |
25 gig | QUANTITY | 0.99+ |
Blade Network Technologies | ORGANIZATION | 0.99+ |
New York | LOCATION | 0.99+ |
Madhu | PERSON | 0.99+ |
DCG | ORGANIZATION | 0.99+ |
Leonardo DiCaprio | PERSON | 0.99+ |
40 | QUANTITY | 0.99+ |
Kirk | PERSON | 0.99+ |
100% | QUANTITY | 0.99+ |
14 servers | QUANTITY | 0.99+ |
Barcelona | LOCATION | 0.99+ |
12 times | QUANTITY | 0.99+ |
2020 | DATE | 0.99+ |
12 years | QUANTITY | 0.99+ |
Ken Cornick, CLEAR - Zuora Subscribed 2017 (old)
>> Hey welcome back everybody, Jeff Frick here with theCUBE. We're at Zuora Subscribe 2017 in San Francisco. You know, I go to these events a lot. We love to talk to customers and clients and there's just some customers that are a little bit more personal than others. And this is one here. We're really excited to have Ken Cornick on. He's the co-founder, president and CFO, a busy guy, of Clear or affectionately known as ClearMe. >> ClearMe >> In the twitter-sphere. >> ClearMe.com, that's right. >> Jeff: Ken, great to meet you in person. >> Nice to meet you as well, thanks for your support as a customer. >> As you say, I'm an unabashed happy customer. >> That's great. >> Except when you get the nasty looks from people when they escort you past them all in the security line. >> Well, everybody can be a Clear member if they want. >> Exactly. >> And we give free trials, so they don't have to pay. >> How can you miss? So, where'd you come up with the idea? Just give us a little bit of the history for people that aren't familiar with Clear. >> Actually we don't have a not-invented-here mentality. We actually bought the business out of bankruptcy. >> Oh that's right >> 'Cause it was completely shut down. >> I actually ran into someone the other day at the airport, she said, "I had Clear before and then it went away." And then she was so happy you brought it back. >> Right and for our, we call them, legacy members that were members of the old company, we give their time back for free. So, I shouldn't say free because they paid for it. So, if you had a year remaining when the old company went under, we'll honor that year and you can use Clear for a year without paying and then hopefully you'll continue to pay us as an ongoing customer. >> And what people maybe don't know or are not as familiar with, is it's not just for airports anymore. I was so thrilled, not that long ago, I went to a Giants game at AT&T and I see the ClearMe sign. >> That's right. So we're in eight stadiums across the country with more to come. I live in New York so we have Yankees and Mets which makes me happy. I'm a Yankee fan, my kids are Mets fans so we're covered there. But we're looking to increase the number of places you can use Clear and to increase value, add to our members. So the more you use it, the happier you'll be, and the longer you'll stay with us. >> Right and how do you describe the service? Is it identity as a service? Which is something that just popped into my mind. How do you describe what Clear is all about? >> Funny enough, we do talk about identity as a service not relative to the airport business. The airport business is what we're known for. But really, we bought the business out of bankruptcy and we started it to become a biometric identity platform. Our view is, we want to remove friction. Wherever identity is important, up until now, any time you want to increase security, it diminishes the consumer experience. >> Right. >> So we think, our technology can change all that. We can increase security while making better consumer experiences as you witnessed at the Giants game. >> Or the Orlando airport which is my favorite Clear airport. >> So we are expanding in the airport but we are also looking to expand outside of the airport, even beyond stadiums. So things like, payment applications or it could be healthcare applications, we're building a biometric ecosystem. You've enrolled in Clear once, you can use that enrollment wherever we are. >> God, I can imagine you could integrate with building access points? All these types of things. >> That's exactly right. So there's smart cities, smart cars, all of those applications have biometric angles to them. >> So, good space to be in, good move. >> We think so. >> But we're here at Zuora Subscribe. So you guys chose to have a subscription relationship with your customers. So, why and what are some of the things that have come out of that that you've learned both kind of surprises as well as validations? >> Well, we're big believers in the subscription economy which is the sort of buzz word here. But for us, we want Clear members to not have to think about it. Part of the draw of Clear, is obviously you are saving time in the airport, but it's also the mentality of no stress going to the airport. So I flew out of JFK the other day at a seven AM flight. I live downtown. And I woke up at 5:15 for a seven AM flight, knowing that I could get through JFK, through the Clear lane in five minutes or less. That change in behavior is the true value add, that once our members experience that they love the service. And so, I don't want you to have to think about, well, it's a monthly, am I active am I not active? It's an annual, once a year subscription. You pay it, you don't worry about it again until you renew the year later. >> Yeah that's funny too that you put it in kind of an experience point of view. Because it is the experience. We just had the No-Stress Guy put a thing on the back of your head. Get the Clear card and that'll lower your stress on the way to the airport. >> Absolutely. >> Quite a bit because you just never know what's waiting for you at those security lines. >> You never know and it could be five minutes. It could be 30 minutes. And that uncertainty causes you to carve out a bunch of your time ahead of getting to the airport. You know that you can look at Waze and see what the traffic is. You know you can check online to see what kind of delays there are for your flight. But you just don't know what's going to happen at the security checkpoint. >> Right, right. >> It's the last frontier. >> So, any special, exciting new places that you want to highlight before we have to go? >> Sure so, we started in 2010 with two airports. Denver and Orlando were our first two airports back. We've been growing fairly rapidly. And we're about to open our 22nd airport in about a week to 10 days and that's Los Angeles which is a huge airport. >> Male: Oh, you're not at Los Angeles. >> We are not at Los Angeles yet. So that is a big piece of the network for us and especially if your in Bay Area base, really, really important. >> Right, how many terminals do you have to go? 'Cause you guys do it kind of terminal by terminal right? >> Yeah, we're going to be ubiquitous in L.A., besides the international terminal, we're going to be in seven check-points I believe. It's a very big operation, a big undertaking. >> Alright, well Ken like I say, I'm an unabashed fan so I won't pretend to be bias at all. Love the service. >> Great, thank you so much. >> And congratulations and again, great opportunities to go way beyond the airport. >> Thanks for hosting me. >> Alright my pleasure, Ken Cornick, I'm Jeff Frick. He's from ClearMe, I'm from theCUBE. Thanks for watching.
SUMMARY :
He's the co-founder, president and CFO, a busy guy, Nice to meet you as well, Except when you get the nasty looks from people So, where'd you come up with the idea? We actually bought the business out of bankruptcy. And then she was so happy you brought it back. we'll honor that year and you can use Clear And what people maybe don't know So the more you use it, the happier you'll be, Right and how do you describe the service? up until now, any time you want to increase security, as you witnessed at the Giants game. you can use that enrollment wherever we are. God, I can imagine you could integrate all of those applications have biometric angles to them. So you guys chose to have a subscription relationship And so, I don't want you to have to think about, that you put it in kind of an experience point of view. Quite a bit because you just never know And that uncertainty causes you to carve out Sure so, we started in 2010 with two airports. So that is a big piece of the network for us besides the international terminal, Love the service. great opportunities to go way beyond the airport. Thanks for watching.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Ken Cornick | PERSON | 0.99+ |
Jeff Frick | PERSON | 0.99+ |
Ken | PERSON | 0.99+ |
L.A. | LOCATION | 0.99+ |
five minutes | QUANTITY | 0.99+ |
New York | LOCATION | 0.99+ |
30 minutes | QUANTITY | 0.99+ |
2010 | DATE | 0.99+ |
Los Angeles | LOCATION | 0.99+ |
Jeff | PERSON | 0.99+ |
JFK | LOCATION | 0.99+ |
San Francisco | LOCATION | 0.99+ |
two airports | QUANTITY | 0.99+ |
Bay Area | LOCATION | 0.99+ |
2017 | DATE | 0.99+ |
Yankees | ORGANIZATION | 0.99+ |
seven check-points | QUANTITY | 0.99+ |
both | QUANTITY | 0.99+ |
seven AM | DATE | 0.99+ |
10 days | QUANTITY | 0.99+ |
22nd airport | QUANTITY | 0.99+ |
a year | QUANTITY | 0.98+ |
Clear | ORGANIZATION | 0.98+ |
Mets | ORGANIZATION | 0.98+ |
Yankee | ORGANIZATION | 0.98+ |
ClearMe | ORGANIZATION | 0.98+ |
first two airports | QUANTITY | 0.97+ |
Denver | LOCATION | 0.96+ |
CLEAR - Zuora | PERSON | 0.96+ |
Giants | ORGANIZATION | 0.95+ |
5:15 | DATE | 0.95+ |
Orlando airport | LOCATION | 0.95+ |
once a year | QUANTITY | 0.95+ |
Orlando | LOCATION | 0.94+ |
five mi | QUANTITY | 0.94+ |
about a week | QUANTITY | 0.92+ |
one | QUANTITY | 0.91+ |
Zuora Subscribe | ORGANIZATION | 0.86+ |
ClearMe.com | OTHER | 0.84+ |
theCUBE | ORGANIZATION | 0.84+ |
Clear lane | LOCATION | 0.82+ |
year later | DATE | 0.82+ |
Clear airport | LOCATION | 0.8+ |
AT&T | ORGANIZATION | 0.79+ |
Clear | TITLE | 0.73+ |
eight stadiums | QUANTITY | 0.73+ |
ORGANIZATION | 0.67+ | |
ClearMe | TITLE | 0.56+ |
Waze | ORGANIZATION | 0.54+ |
God | PERSON | 0.53+ |
Clear | LOCATION | 0.48+ |
Subscribe 2017 | EVENT | 0.47+ |
Zuora | ORGANIZATION | 0.43+ |
Frank Palumbo, Cisco Systems & Andy Vandeveld, Veeam - VeeamOn 2017 - #VeeamOn - #theCUBE
>> Voiceover: Live from New Orleans, it's the Cube covering VeeamON 2017 brought to you by Veeam. >> Welcome back to New Orleans everybody. This is the Cube, the leader in live tech coverage. We go out to the events and extract the signal from the noise. My name is Dave Vellante, and I'm here with my cohost Stu Miniman. Frank Palumbo is here. He's the senior vice president at Cisco Systems. And Andy Vandeveld is the vice president of Global Alliances at Veeam Software. Gents, welcome to The Cube. >> How we doing? >> Thank you. >> It's great to be here. >> Good, Frank, hot off the keynote. It was great, Yankees fan, love it. The rivalry continues. Of course you guys know the Cube, Red Sox fans, some of us. Stu's not. >> Not all of us. >> So we love it. We love the action, and it's always fun. But Frank we had to cut out a little bit before your keynote because we had to get ready to do the Cube. But you put up a slide that was awesome. We could do an hour on The Cube on that, and it's all about the apps, I mean really. But you had this great slide with apps and microservices and virtualization and bare metal and OnPrim and really laying out the complexity today. And you guys are at the heart of that. Maybe give us a quick summary of how you guys see the world. >> When you're talking about the applications, the application profile, it's important, the network kind of brings this together because we do touch everything. Where people are in this kind of application history is some of them are on legacy, mainframe. Some of them are on RISC processors. But as a network provider, we have to bring those in too even with the more modern applications. So you look at what the platforms or workloads are on so move those in. And then you're looking at workload placement, on Prim or in the Cloud. Do we put data in a colo? Do we put the application in the Cloud? There's different hybrid mentalities to do that. Then you get into the systems management where there's just too much stuff out there. Humans can't manage it anymore so the machines and the software have to manage the machines and the software. We'd like to think we're right in the middle of that because of the way we bring things together with the network. >> So Andy, I look at the... Stu and I walked the floor before we come in here, the ecosystem is really quite impressive-- >> Andy: Thank you. >> for a relatively small company. I mean not that small anymore. It didn't just happen overnight. Maybe you could talk a little bit about themes and philosophy with partnerships and some of the things that you're doing with Alliances generally and specifically get into the Cisco partnership. >> Well I think partnerships have been in our DNA since the beginning of the company. We're a 100% channel-lead company. We don't have a direct sales force. That's an important piece of the company's philosophy. These alliances are really key for us because as we start to move into markets that are maybe a little bit higher than where we've been into the large enterprise and mid-enterprise and large enterprise, we really look at partnerships like the one with Cisco that are going to benefit Veeam and the customers by us being together doing joint developments. Some of the things that Frank talked about in his keynote speech, those are the sorts of things that create solutions for that level of customer where Cisco's been resident for many, many years. So we look at these partnerships as really central to where Veeam wants to go as a company and where we think customers want Veeam to participate with the partners. >> What's the specific nature of the partnership? Can you unpack that a little bit for us? >> From my side, certainly we have a robust go-to-market relationship in terms of when we're positioning UCS or Hyperflex, our server and hyper converged platforms, now we can bring to bear the Veeam value problem as we go forward with customers. And customers look to Cisco really to complete the story and offer an end-to-end solution. We weren't able to complete it without the Veeam technology. Then on the development side, some of the things that we're doing, we've integrated so now the Veeam software can work with our Snap technology and hyper converge. So you're starting to see it come together at the screen level with the bits and bytes in terms of the integration. >> Dave: So there's a greater degree of technical integration as well. >> Frank: Yes. >> It's not just go-to, I mean that's important because a lot of times back-up data protection is kind of an afterthought. It's a bolt-on. But if you're going to be a complete solution provider, that's fundamental and it's becoming more important. >> I think you know I was just mentioning to Frank back in the green room before we came out here I look at the start of this partnership as really being about 18 months ago. Although we'd had a partnership for a while, we really kind of started about 18 months ago in this meeting that we had at their partner conference in Maui. And Radmeer and I sat down with Frank and kind of explained why we thought data protection was a solution that Cisco could get behind particularly now that they were coming out with their S-Series devices. But that's just the start of it. It has to come with integration as well. Then we started with Hyperflex. It was a new product for them, 1.0 version. With the 2.0 version, we got integrated with snapshot technology like Frank mentioned. I look at this short runway of time in this relationship that kicked off with our meeting with Frank and he got it right away. We didn't have to explain it. >> Dave: It resignated. >> Frank: Oh, no question. We're very proud of our S-Series storage server. The hardware is nice. The infrastructure piece is nice, but it really doesn't come together unless you got the application on a run with it. That's where Veeam just jumps in and fills that gap perfectly for us. >> Frank, I think back to when virtualization really took off. Networking was one of the things that we had to fix. It put a lot of stress on the network. It's one of the reasons Cisco created UCS and backup also creates a lot of strain on the network. So it seems a natural fit. Can you talk about all the complexities that are coming and how you're going to be, what can we expect to see from jointly going forward? >> I think we've learned a lot from Veeam in terms of they've been able to really attack complex issues in a very simple fashion. Simplicity is the game with customers right now. Things are moving so fast. If you can't be simple, you're going to have a tough time out there. So I think that's where it's really come together for us in that vein. But when you look at the value of data and whether it's a second old or two years old or a year old, there's so many different more paradigms coming out about what you can do with this data. And customers and even customers of customers have now found ways to use this data either to make better decisions, monetize it, to stay away from things. So that's why this whole lifecycle for us is so important. This is where Veeam and us can really do some nice things for customers. >> Andy, can you build on that about the multi-Cloud position that Veeam has? How many of those, do you know, touch what Cisco's doing here and how does the partnership help drive that value of data type offering? >> For Veeam, our message is all about availability, availability of the data which makes the applications available and which basically makes the business stay up and running. One analogy we use is a cell phone. When you're cell phone dies, you can't get access to your email. You can't get access to your instant messages. >> Dave: You freak bascially. >> You feel like you're lost, right? >> Frank: It's getting kind of pathetic. >> Yeah. >> Dave: It is pretty bad. >> So think about not being able to get access to your data or access to your applications because of some outage, not being able to backup and recover. Your business could go out of business. Working with Cisco on solutions that are on premise, that are in the Cloud, that are multi-Cloud is really the value of the partnership that we have that we bring together. It's just at the beginning. We've got solutions that we're building now. We got solutions that are on the horizon. We've got a very strong go-to-market partnership in a very short period of time that are targeting enterprise customers, service providers, the whole gamut. It's really that sort of relationship that you find in an industry every so often. When it comes together like it has with us and Cisco, it's really a very strong, strong value prop. >> Well Veeam capitalized on the original virtualization trend with VMware that was a big transformation, the server infrastructure. You're seeing a huge network transformation now. There are so many forces affecting the network that I wonder, Frank, if you could comment on. You got ScaleOut. There's Flash. There's Cloud. There's Microservice. There's DevOps makes everything go faster. The flattening of the network. Describe what's happening and then maybe you can talk about how your ecosystem is going to take advantage of that. From what were the challenges the network has is exactly like you said. You have certainly the virtualized workloads now. The Microservices containerize workloads. I think the one people forget about is there's still a ton of bare metal out there, right? You look at the Hadoop workloads and such. A lot of these are bare metal oriented, right? Quite frankly, moving a VM around a fabric is actually pretty easy to do. But when you got to move a bare metal workload around a fabric, and that's something we can do with UCS the way we do it statelessly, that's much harder. That's why we have the extraction layer with what we call the fabric interconnection with UCS to do that kind of stuff. I think that's sometimes lost in the translation in terms of how you're going to handle all these different workloads. >> If I understand it, the link then to the opportunity for you guys, Andy, is that the stakes are just much higher now, right? You could do so much more around the networks. Stakes are so much higher. That increases the need for your products and services. Carry that through if you would. >> Well, it is. As we make our way up-market into the enterprise, the amount of data that businesses are spinning off of, their infrastructure and their data center or from robo offices or wherever, is growing immensely. Being able to have a partnership with an infrastructure provider like Cisco, where we can put solutions together that really give the customers the rock solid base for backing up their data and making sure that it's available is really critical for us as we move into those larger enterprise and larger environments. So this is an essential relationship I would say. >> I think, too, if I could mention, this is something our channel wanted to see, too. We're the same. We're at about 98% of our business goes through the channel. So they're selling our full line of infrastructure products. This completes the story for them. So we got a lot of guides to them say, "Hey, yes, Cisco. "We'd like to see you come together with Veeam "so we can start bundling offers out there in the market "and be that kind of end-end-to supplier, too." That was a big impetus especially from mid-market up to enterprise customers. >> Excellent, well, we got to wrap there. The partnerships give you huge leverage as a small, again not so small company anymore. The fact that you can get somebody like Frank to come down, talk about the partnership, is a testament to what you guys have built. So congratulations. Really appreciate you guys coming on The Cube. >> No, my pleasure, our pleasure. >> All right, keep it right there, everybody. We'll be back with our next guest. This is The Cube. We're live from New Orleans, VeeamON 2017. We'll be right back. (tinkling music)
SUMMARY :
Voiceover: Live from New Orleans, it's the Cube and extract the signal from the noise. Good, Frank, hot off the keynote. and really laying out the complexity today. because of the way we bring things together the ecosystem is really quite impressive-- and some of the things Some of the things that Frank talked about at the screen level with the bits and bytes Dave: So there's a greater degree But if you're going to be a complete solution provider, back in the green room before we came out here and fills that gap perfectly for us. and backup also creates a lot of strain on the network. Simplicity is the game with customers right now. availability of the data We got solutions that are on the horizon. on the original virtualization trend with VMware You could do so much more around the networks. that really give the customers the rock solid base "We'd like to see you come together with Veeam The fact that you can get somebody like Frank to come down, We'll be back with our next guest.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Dave Vellante | PERSON | 0.99+ |
Frank Palumbo | PERSON | 0.99+ |
Andy Vandeveld | PERSON | 0.99+ |
Cisco | ORGANIZATION | 0.99+ |
Dave | PERSON | 0.99+ |
Frank | PERSON | 0.99+ |
Andy | PERSON | 0.99+ |
Red Sox | ORGANIZATION | 0.99+ |
New Orleans | LOCATION | 0.99+ |
100% | QUANTITY | 0.99+ |
Stu Miniman | PERSON | 0.99+ |
Cisco Systems | ORGANIZATION | 0.99+ |
Maui | LOCATION | 0.99+ |
Veeam Software | ORGANIZATION | 0.99+ |
Veeam | ORGANIZATION | 0.99+ |
a year | QUANTITY | 0.99+ |
Stu | PERSON | 0.99+ |
S-Series | COMMERCIAL_ITEM | 0.99+ |
UCS | ORGANIZATION | 0.99+ |
Yankees | ORGANIZATION | 0.99+ |
Cube | COMMERCIAL_ITEM | 0.98+ |
one | QUANTITY | 0.98+ |
Hyperflex | ORGANIZATION | 0.98+ |
The Cube | ORGANIZATION | 0.98+ |
about 98% | QUANTITY | 0.97+ |
an hour | QUANTITY | 0.96+ |
One analogy | QUANTITY | 0.95+ |
today | DATE | 0.94+ |
Cube | ORGANIZATION | 0.93+ |
about 18 months ago | DATE | 0.93+ |
Global Alliances | ORGANIZATION | 0.9+ |
DevOps | TITLE | 0.87+ |
ScaleOut | TITLE | 0.83+ |
VeeamON 2017 | EVENT | 0.82+ |
second old | QUANTITY | 0.81+ |
two years old | QUANTITY | 0.79+ |
Radmeer | PERSON | 0.75+ |
Veeam | PERSON | 0.73+ |
1.0 | QUANTITY | 0.73+ |
a ton of bare metal | QUANTITY | 0.7+ |
VMware | TITLE | 0.59+ |
2.0 | QUANTITY | 0.57+ |
Ansa Sekharan, Informatica - Informatica World 2017 - #INFA17 - #theCUBE
>> Announcer: Live from San Francisco, it's theCUBE. Covering Informatica World 2017. Brought to you by Informatica. (light techno music) >> Welcome back to theCUBE. We're here at Informatica World 2017. We're going from the morning to the night, today and tomorrow, to talk about some of the things that are happening in the world of data management, analytics, master data management, etc. Very, very important topics. And I'm Peter Burris, and we're going to spend a few minutes now talking with Ansa Sekharan... >> Got it, Sekharan >> Sekharan, sorry Ansa, I got it earlier. Ansa Sekharan, who's the executive vice president of Informatica global customer support and the head of the Informatica University. Thank you for coming on theCUBE . >> Good afternoon, Peter. Thank you for having me on theCUBE . >> So, global customer support. Big issue when a company's going through a lot of transformation, compounded by the fact that your customer base is going through a lot of transformation. Business as well as technology. When you take a look at what's happening, 3000 people to show, what is the most important set of messages coming out about global customer support? >> At Informatica, the tagline says great products are just the beginning. As customers make this investment, we have a great services arc which looks at the investments customers make, and see how they can help their desired outcomes. At Informatica, when you look at innovation, you hear a lot about products. You see a lot of great launches. We have a very similar strategy in support. Every four years, we kind of come up with a major version of support offerings to keep up in line with our product innovations, and also to meet customer innovations. Right, so in every two years we have a minor release. So we look at our services as a product. Like the saying goes, we want to make sure our customers do not have to call in. So we have a lot of emphasis on quality, and the great interlock with RND. Make sure, we have been ranked number one in customer loyalty for eleven straight years in that regard. So, we want our customers to take away that support and services is viewed as a product here at Informatica. >> Well I want to push you on that a little bit, and I think this is an important point. In the world of, characterized by a significant amount of change, it's important, I think, that we draw distinction between inventing something and innovating, where invention's an engineering duty, or an activity, and then innovating is a social activity. So we create something new, and then through the innovation process, we get people to use it. So I like the idea of looking at support as a source of innovation in of itself, but talk about how that lines up with the idea of support to help make or ensure that customers are successful. >> Right, it's two parts. It's like how you build the relationships, along with automation. In this age of customers, a lot of emphasis is placed on how customers can do self-service and so on. So a lot of great innovation has been built on the portal. We leverage machine learning and AI, and we have built a great platform to have the customers learn best practices, and find the needs and answers for the most common questions. But, we're an enterprise software company. About 85% of business comes from existing customers, and we enjoy great renewal rates of about mid-nineties. This is only possible if customers are realizing value from our products. So, we pride ourselves on our relationship. We have a customer success team, which also is emphasizing how do we drive desired outcomes. People ask what is desired outcomes? When you make a purchase, there is an expectation of an outcome. That outcome, in conjunction with your effort, the experience makes it desired. So, that is where as we pivot to a subscription company, that is all the more important. Customers now sort of rent our software, when they are on subscription. The onus is on the vendor to make sure you build on the relationship, and you deliver value back to our customers. That is where we our very different. I think, to answer your question around innovation and we combine that with relationships, it's a great combination. >> So let me push you on one other feature there. So, the difference is in innovation on premise or license software is a little bit different than the innovation process associated with Cloud oriented or subscription oriented software. On the one, you get the invention, customer installs it, you might help them install it, you might help with a little bit of support on it, or they are largely responsible. But in the Cloud, the whole notion is you're actually getting the service itself and not necessarily the software. How does the concept of customer support change as you move in to a subscription Cloud oriented world. >> So when you are on the Cloud solutions, you have the meta data of the customer. You can measure every click, you know exactly what the customer is doing and not doing. So we have a product called Discovery IQ, which mines that information and offers recommendations on how the customers could better leverage our products. >> To your team. >> To your team and back to the customer. >> And back to the customer. >> Now on an on-prem product, we help in installation configuration. But the software is running on the customer's premises. That's where we have built in supportability tools which can share meta data back, so that we can understand what phase of the project the customer is in. You heard of a product called Ops Insight, which we just launched. That's a Cloud based product which connects with our on-prem products so that it gives you a window into what the customer is even doing on-prem. The more we know about the customer, the better we can serve them. Some customers are very forthcoming to partner with us, and whenever we have a customer success manager we have great collaboration, we know the milestones, we can orchestrate, how we should march the customers towards the milestones. But, if that level of communication is not there then we have to rely on supportability tools to get the meta data back, and then we push information back to the customer. >> And that notion of a road map or a journey to get to the outcome is crucially important. >> Extremely important, and in fact, we want to build those features in the product. Today if you take a master data management product, the data model is the foundation. Today we are able to collect the data model and look for patterns to see if there is a better data model that we can recommend to the customers. Because if the foundation is not right, months later, potentially there could be issues around scale and so on. What we've been able to do is detect that very early on to offer better solutions to customers and we're talking about solutions data models varied by life sciences, varied by health care, financials. We are able to leverage this knowledge and share across customers. This is not customer proprietary information, just the foundation data models and this what our consulting services team is also able to go on-site and leverage it further. >> So the historical interaction between a software vendor and a customer, typically was around those characteristics of the product. The speeds, the performance of the product, what was required of it, how to configure, how users used it, the interfaces what not. As you move more towards solutions, especially in a period of significant transformation. Now you're talking about how a product does or does not support a business capability. In the world of analytics, it's becoming increasingly obvious that is a strategic business capability that has to be put in place. That means that your support people are moving from deep understanding of the product, and being able to convey that, to having to have a better understanding of the capabilities that the customer is trying to achieve and helping them work through that process. Have I got that right? >> Right, so one of our focus areas currently is the topic of services convergence. In the past customers would make a product investment, support is mandatory, it gets bundled in. They have to make separate purchases for professional services and education. As we pivot to subscription, we're kind of bundling the services along with the subscription. So we are coming up with some innovative solutions later in the year, where as part of the subscription which the customer is signing up for, we're going to offer a five-day consulting services package, or a ten-day services consulting package, included in the subscription. Why are we doing that? When we talk about driving business outcomes, we are talking about, if you are really serious about accelerating those outcomes, you ought to make that investment up-front. And in the case of ... >> Both parties do. >> Both parties. It's a partnership you got to build. >> In many respects, it's a test of almost the seriousness of the customers. That the customers. Are you going to invest your time, and not just your money in to this process. >> Ansa: It's not a one-way relationship. >> Absolutely >> It has to happen both ways. So when the professional services goes on-site, tries to understand what's the business imperative the customer is embarking on. That information is shared back with customer support. So we have an idea. The support folks are still going to be product line focused but the domain knowledge, in terms of solutions, we're trying to address it through our solution architects in professional services. So what is unique is, beginning of this year we launched something called a Support Accelerator. >> Peter: Support >> Accelerator >> Peter: Okay, Accelerator, yup. >> Yes, so you talk about big data. In my experience, like I said, I have been with Informatica for 21 years. When it comes to big data, I have never seen a technology which is changing so rapidly. It's getting disrupted every quarter I would say. So we realized customers have to look at security, the hadoop distribution, and those hadoop distributions change pretty rapidly. It used to take them, could take them weeks, just to install and configure the product. >> Peter: Correct >> No fault of Informatica. Just the complex ecosystem. So we come up with the Support Accelerator, we have some checklist. We'll get this information from the customer, we'll remotely install and configure the product in days. >> So you just gave a great example of exactly what I mean by the difference between invention and innovation, where hadoop is constantly inventing but the customers need help with the innovation side. To get it adopted, to get it applied, to get it used. So they can create value in and of itself embedded in their business practices, and that's essentially what your focusing on with some of the support regimes. >> This notion of support accelerator is focused on installation and configuration. With the example I gave you, we just could shave off a couple of weeks. We are expanding this to other product lines, ideal EIC, and then we are going to be offering upgrade services. When I talk to CIOs, they want to know as I upgrade to the latest version, you have my meta data. Tell me what value am I going to get with the upgrade. I know it's going to be supported, the latest certifications if you can tell me if this feature is going to run X times faster. If there is some configuration that I need to change so that I am better leveraging the features in the product. That's the path we are on. I think we have made great strides on the Cloud side of the house. We have a product called Informatica Discovery IQ, which can make the recommendations we have to replicate the success on our on-premises solutions. That's what we're trying to do with Ops Insight product. >> So I used to do a lot of research around a particular topic, and that was a customer journey with an IT organization. Turns out, that the CIO is most involved in the discovery process, and then that first application process. Discovering the characteristics solution and then ensuring that they are going to get value out of the product, that first project plan. And the reason for the discovery is because the business is typically is finding out that something is not working right, and brings it to the CIO's attention. But interestingly, it's not at the moment that they buy, it's after they buy and sitting down with the team and making sure that the business gets value out of the purchases, and that's where your guys shine. >> Right, and do you know? We want to come up with a success plan with the right milestones along the journey. Through our customer success team, we want to orchestrate this journey. The role of customer success management is like, how do you orchestrate this journey as you go through these various steps. Customers' outcomes are also evolving. Especially in the case of big data. I read an article that said companies, only if they have a business strategy which leverages big data, they have a higher degree of success. Not the other way around. >> Peter: Right >> You know what I'm saying. >> Peter: Oh totally, 100%! >> And when customers make this investment sometime it comes from top down and working with the customer success team understanding with what they want to do. The good news is most of our customers are very happy with our current implementation strategy. So they have a mandate to go big data. So we kind of tell them, "Hey what's your work loads? "You want to do data warehouse optimization, "you're going to shift from teradata to hadoop. "Here is how we will do it, here is the blue print." We've been able to share some of our success stories with other customers to them. It's all about accelerating the journey for them. >> But it certainly is not about getting a cluster. >> Ansa: No >> Deploying hadoop and looking at it and say, we are done. >> Ansa: That's step point one. >> That's exactly right. And increasingly because you can now buy a lot of that as a service, it may not even be step one anymore. >> Ansa: Exactly >> It's an option that you may not choose. So as you think about where customer support, in the context of Informatica's journey, can you give us just a couple of insights as to where you think the customer support concept is going to be in a couple of years? >> A lot of emphasis is going to be on service automation, and the other big board level priority at Informatica is this customer experience. You talked about the journey mapping. It has a story-telling element, and it has a visualization element. As customers come to our website, have awareness, become a prospect, a lead, make a purchase, we land, adopt, expand and renew. A gamut of interactions across the board. We're now going to be focusing on optimization, every step of the journey. We're going to find the moment of truth, which would yield the biggest value to the customer have an outset in approach to validate that. What this has given us, the customer experiences have a cohesive strategy which cuts across all functions. Before we had KPIs on a functional basis, now we have KPIs on a horizontal basis. >> Peter: Tied back to customer experience. >> Tied back to customer success. Can we get them to go live faster. >> Right. >> Are we getting them to renew on time. So these are metrics which are shared by every function within Informatica, not just the renewals team, not just the support team. I think with the emphasis from the board and with the support and investments we are making, I think this is going to take us to the next level and I'm pretty excited about it. >> Excellent! So Ansa Sekharan. >> Sekharan >> Thank you very much. Just to let everybody know, with Informatica longer than Derek Jeter was with the New York Yankees. >> Here you go. >> 21 years. >> Thank you Peter. >> Thank you very much for coming on theCUBE . So, Ansa Sekharan is the executive vice president of Informatica's global support and service organization. Once again, thank you for being here and we'll be right back with more from Informatica World 2017, in a few moments. >> Ansa: Thank you. (light techno music)
SUMMARY :
Brought to you by Informatica. We're going from the morning to the night, and the head of the Informatica University. Thank you for having me on theCUBE . compounded by the fact that your customer base and the great interlock with RND. So I like the idea of looking and we combine that with relationships, and not necessarily the software. So we have a product called Discovery IQ, the better we can serve them. to get to the outcome is crucially important. and in fact, we want to build those features in the product. of the capabilities that the customer is trying to achieve So we are coming up with some innovative solutions It's a partnership you got to build. of almost the seriousness of the customers. So we have an idea. So we realized customers have to look at security, So we come up with the Support Accelerator, but the customers need help with the innovation side. That's the path we are on. and then ensuring that they are going to Right, and do you know? So they have a mandate to go big data. And increasingly because you can now buy as to where you think the customer support concept and the other big board level priority at Informatica Can we get them to go live faster. not just the renewals team, not just the support team. So Ansa Sekharan. Just to let everybody know, with Informatica longer So, Ansa Sekharan is the executive vice president Ansa: Thank you.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Peter Burris | PERSON | 0.99+ |
Ansa Sekharan | PERSON | 0.99+ |
Informatica | ORGANIZATION | 0.99+ |
Peter | PERSON | 0.99+ |
Derek Jeter | PERSON | 0.99+ |
Ansa | PERSON | 0.99+ |
Sekharan | PERSON | 0.99+ |
100% | QUANTITY | 0.99+ |
San Francisco | LOCATION | 0.99+ |
21 years | QUANTITY | 0.99+ |
New York Yankees | ORGANIZATION | 0.99+ |
Today | DATE | 0.99+ |
Both parties | QUANTITY | 0.99+ |
two parts | QUANTITY | 0.99+ |
Informatica University | ORGANIZATION | 0.99+ |
eleven straight years | QUANTITY | 0.99+ |
tomorrow | DATE | 0.99+ |
both ways | QUANTITY | 0.99+ |
3000 people | QUANTITY | 0.98+ |
Ansa | ORGANIZATION | 0.98+ |
today | DATE | 0.98+ |
one | QUANTITY | 0.98+ |
About 85% | QUANTITY | 0.97+ |
#INFA17 | EVENT | 0.97+ |
Ops Insight | ORGANIZATION | 0.96+ |
step one | QUANTITY | 0.95+ |
months later | DATE | 0.95+ |
one-way | QUANTITY | 0.94+ |
first application | QUANTITY | 0.92+ |
two years | QUANTITY | 0.89+ |
first project | QUANTITY | 0.89+ |
Informatica World 2017 | EVENT | 0.88+ |
2017 | EVENT | 0.87+ |
ten-day services | QUANTITY | 0.86+ |
four years | QUANTITY | 0.86+ |
five-day consulting | QUANTITY | 0.86+ |
Informatica Discovery IQ | ORGANIZATION | 0.84+ |
this year | DATE | 0.8+ |
theCUBE | ORGANIZATION | 0.8+ |
step point one | QUANTITY | 0.78+ |
about mid-nineties | QUANTITY | 0.77+ |
Informatica | EVENT | 0.76+ |
Discovery IQ | ORGANIZATION | 0.72+ |
number | QUANTITY | 0.69+ |
Cloud | TITLE | 0.62+ |
World | ORGANIZATION | 0.48+ |
years | QUANTITY | 0.39+ |
Greg Pepper, Check Point Software Technologies - IBM Interconnect 2017 - #ibminterconnect - #theCUBE
>> Announcer: Live from Las Vegas, it's theCUBE, covering InterConnect 2017. Brought to you by IBM. >> Hey, welcome back, everyone. Here live at the Mandalay Bay in Las Vegas for theCUBE's three-day exclusive coverage of IBM InterConnect 2017. I'm John Furrier. My co-host, Dave Vellante. Our next guest here is Greg Pepper, head of cloud security architects at Check Point Software Technologies. >> You got it. Good afternoon, gentlemen. >> Welcome, welcome to theCUBE. So, security obviously is big. You're seeing compel all the networks, every company out there is buying security, so there's been a security sprawl. But now you guys have a stock that's trading at a very high, 52-week high. Congratulations. >> Yeah, thank you. You know, some people forget about us. We've been doing this for 24 years, we've been the leaders in this industry for over two decades, but sometimes, we're the best kept secret in the industry. >> Unleash some of those secrets here. I know you guys probably can't go into too much secret sauce as a public company, but what's the software secret? Obviously, relationship with IBM is part of why you're here, but what's the Check Point secret sauce right now? >> I think first and foremost, we've built upon a legacy for the last 20 years. We didn't just acquire technology through acquisition, duct tape and paper clips and call it an architecture for our customers. We've built upon a consistent common platform building on our core strengths. I think the second thing that really differentiates us from some of the other guys you mentioned is our commitment and focus to security first. We are a security company end to end, and everything we do is built off of those tenets. And especially with the growth in security in the data center, its migration to cloud, the industry has kind of come back around to software, and though for a while we delivered hardware appliance to customers, 'cause it was the preferred consumption model, when customers go to the cloud, whether it's SoftLayer, Azure, Amazon, Google, and others, we don't have hardware to bring with you, so you need a software defined security strategy to play in the cloud today. >> What is that software defined security strategy? What's the hottest product that you guys have that's working best? >> Everything we have built on our core competencies of management and the gateways themselves. But these days, it's not enough to just be a firewall vendor, so advanced threat prevention, the ability to both prevent and detect malware from getting on the network, rather than just alerting you that something bad happened. We're providing additional access controls with data awareness. I don't need to plug into the network to tell you people are going to YouTube, Netflix, but what's the information about your organization that's being posted out there? Those are the interesting things that we can help differentiate and alert customers to what's going on. >> So, the perimeter's, with the cloud, all these APIs, microservices coming down the pike with cloud, that's the challenge. I mean, this whole idea of being data and software focused. How do you guys play in that world, and what's this focus there? >> The biggest change is moving away from the traditional management architecture to one that's driven by code. These days especially in the cloud to be agile with dev-ops, you have to have security be able to be deployed, programmed, managed, and monitored all through an API, and this is something over the last few years we've enhanced our products to enable automatic deployment in the cloud providers, automatic management, and also integration with people like IBM QRadar in a highly automated way. >> The big discussion in the last couple years in security has been, hey, it's not enough just to dig a moat around the castle. The queen wants to leave her castle, so we've got to, security's got to be everywhere, it's got to follow the data, and also response is another major focus of discussion, we've got to shift spending there. How has that impacted, first of all, you buy that, second of all, how has that impacted your business and your strategy? >> We definitely do agree, which is why as part of our end to end security strategy, the laptops, the desktops, the mobile devices is an area of increased focus for us. Where really just having the traditional perimeter alone is not adequate. The second thing we started to talk about is the ability to move into the cloud. A lot of the competitive solutions out there don't play as well in the cloud because they're dependent on proprietary hardware. If you're a vendor that has custom ASICs, well, you don't have those ASICs when you go to the cloud. Whereas for us, our software defined security strategy, when we go to Amazon, Azure, SoftLayer, and other cloud providers, 100% of our core capabilities moves along with us. >> Talk that through the value proposition and the customer impact. So, it's more flexibility. Is it lower cost, is it speed, is it better response? >> I believe the primary driver for cloud adoption is agility, not always cost savings, although in some cases that is the case. However, the ability to grow and shrink on demand. In the past, our traditional enterprise customers would consume technology for their max resources. If I'm a large department store, I need to be able to handle Black Friday. Well, that's one week a year that you need that peak utilization. That ability to scale up and scale down is one of the major things driving people to the cloud. Well, security has to have the same model. We have to be able to automatically deploy, scale up for those large-scale events, but then also come back down to an average run-time use to help customers save money. >> How about analytics? How does that play into the security business? >> Yeah, I mean look, the whole reason we exist is to give interesting information for technology to be able to chew on, and the ability to provide the forensic auditing accounting for access controls and for our threat prevention, whether it's on the perimeter, in the cloud, in the core, on mobile and end-point devices, there's a reason after 20 years we've been the lead in the industry is 'cause we provide the best forensics data and integration with all the major leading SIM vendors out there. >> Yeah, the 20-year stair with Check Point. Obviously, the company's evolved a lot since then. Talk about the relationship with IBM, obviously we're here at IBM InterConnect, what are you guys doing with IBM? >> IBM's one of our best partners for over the last two decades. For over 18 years now, they've been a customer, a reseller, and a managed services security partner, so there's multiple organization within IBM that have relationship with Check Point to help secure the corporate assets, customer projects in our managed data centers, or even just purely security managed services. One of the exciting projects that we've been working on that was demonstrated at the security booth was an automated security deployment for the hybrid cloud, where the IBM team worked with us to help take security, automatically roll it out into Amazon and Azure, but also bring it into their MSS environment, their managed security services with zero touch, and they're able to provision, have it managed, monitored, and ready to rock and roll in less than 30 seconds. >> And they were doing that all in software? >> Greg: 100% in software, 100% in code with no human intervention. >> So take us through some of those use cases going forward. As you go talk to customers with IBM or on your own, you write on a lot of white board, I can imagine, so what are some of the white board conversations you're having, 'cause security architecture's one of these, kind of a moving train right now. What are some of the patterns you're seeing right now? >> First and foremost, there's a lot of cloud novice, this is new for all of us. So in the walk-jog-run mentality, we all need to come up with the basic terminology and fundamentals so we can have a more advanced conversation. Once we provide the basic knowledge transfer, the second step is how can you help me lift this legacy application and move it to a cloud-centric application, yet still give me the same levels of security and visibility, 'cause I can't go to the board and tell 'em, "Oh, we screwed up. "We moved to the cloud, and now our apps are not secure." As a matter of fact, for our largest customers, the most critical applications will not move to the cloud unless they have a clearly defined security strategy in place. >> So you lay out those parameters up front, then you kind of walk through it, I'd say crawl, walk, run, then jog. >> Greg: Absolutely. >> However you had it, but I mean, lot of people are kind of crawling, but now also, multi-cloud's a big theme here. So now, you're looking at multiple clouds, and some workloads might make sense for cloud one, two, or three depending on the workloads, but some stay on prem. >> 100%. >> And now you got the true private cloud trend where I'm going to have a cloud-like environment on prem. That's cool, development environment looks the same as the cloud, but I got multiple clouds. How do you guys deal with the multi-cloud and this idea of being consistent on prem and on cloud? >> First and foremost, being a software defined gateway, we have this unique capabilities that's the same on premise, Amazon, Azure, Google, SoftLayer, and others as well. Since we're not dependent upon hardware, we have consistent capabilities across all the clouds. The second thing I want to add is from a management perspective, we've built, excuse me, tight integrations with all the data center and cloud providers, so we're able to trust Amazon, VMware, Cisco, OpenStack, Google, and others and real-time integrate their applications and objects and metadata into our security policies, further tightening the integration and automation capabilities between those cloud providers. >> So, you're actively working with all the clouds to integrate in tightly to manage the security. You become the Switzerland for-- >> Look, we were the first of the major security vendors to both be in Amazon and Azure. We were the first achieve Amazon security competency. We were the first to support basic things like clustering and scale set support, which has been a very common deployment in the cloud as well. We've been in this cloud game for the last seven or eight years now, or as I like to joke, we've cloud up-times longer than some of my competitors have been in business. >> Microsoft was actually down on the cloud. We published a report today on siliconangle.com. Three cloud vendors down in a week. I'll give Amazon a little week there, but it's still, you're still going to see some these bumps in the road, but security, you can't have bumps, you got to be rock solid. >> The thing with today in cloud, whether it's the application, the servers, the storage and securities, you have to anticipate for that total failure situation. Heaven forbid, what happens if an east region went down? Case in point, when Amazon had their storage outage, Netflix was not interrupted at all. Now, other organizations that were only deployed in a single region, we were impacted. This is where, I think from an application architecture, one, we have to think beyond single region, single cloud provider. We have to anticipate the total catastrophic failure and how does our business continuity and disaster recovery work. And then, security has to be an integral portion of that. We can't bolt it on after the fact, it's got to be part of the foundation. >> Greg, great point. And by having software, gives you so much flexibility, I love that hybrid cloud example, but I want to get your thoughts on what you said earlier about lift and shift. That seems to be the parlance of the generation. It used to be rip and replace on the enterprise side, but that's not as easy as it is. To your point, you can't just throw it to the cloud, you might have some gaps. As people look to lift and shift, which I always say is be careful, you got to have some concerns. How do you advise your customers when you say, "Hey, we're lifting and shifting to the cloud." >> For those people, I say don't bother. Right, if I'm going to move the same applications and same products and processes from my private data center to the cloud, why bother? If we're not taking advantage of the agility, elasticity, automation, and all the benefits that clouds has to offer, companies should be building new cloud-ready applications for the cloud. We should not just be lifting our legacy applications and like for like moving them to the cloud, 'cause we're not going to get the benefit in return on investment. >> And it's risky, too, by the way. I would agree with you. So, net new applications, no brainer. If the cloud's available, why not? >> Absolutely. >> Let's go back to the workload. Some clouds have better, like analytics use case is a great cloud, just throw IOT data into Amazon or Azure or Office 365 is Azure, and Amazon gets Kinesis, good stuff, and you've got Bluemix over here. You're starting to see that swim lanes of the different vendors. How do you view the differentiation between the vendors, and how do you advise customers? "Hey Greg, I don't know which cloud to go to. "What's your advice?" >> First and foremost, there's pros and cons to everyone's offering. >> It's kind of like Red Sox, Yankees, you know. It's like trying to-- >> Well, let's stop right there, Yankees for sure. >> Dave: You think? >> Absolutely. >> Dave: You really think? >> Well, maybe not in 2017, but-- >> Who's the Yankees, Microsoft or AWS? >> Microsoft probably the Yankees right now. Then again, from my perspective as a Red Sox fan, I'd say it's a tough call. >> (muttering) is the Yankee-killer. Anywhere, let's... >> Alright, go back. >> We digress. >> What I was I going to make a comment of is look for the adjunct services behind the basics, beyond the basic storage, compute and networking services that everybody has as kind of table stakes. For example, if you're someone who's a very heavy Microsoft Office 365 SharePoint user, you're using their business application suite, well, probably migration to Azure is a more natural transition, right. People who are similarly in the Google environment and using the Google suite of applications, it's a benefit to moving the applications there. And to be honest, people who are purely just into the raw compute horsepower and probably the most mature and largest cloud platform, well, Amazon has probably got a five-year head start on the rest of the guys. So, we try not to sit here and determine which of the three clouds is better, 'cause for us, we play in all of them, and our security footprint has to be consistent across all of them. I'll share with you an anecdotal use case from one of my retail customers is building a commerce platform in AWS. But all the corporate applications are moving to Azure, and separately now, they're looking at Google for other global applications as well. So for them, they're going to be in all three cloud providers, just with different applications finding more natural homes. >> Justin Youngblood was just on. He said, the IBM data said 70% of all organizations, or 70% of the organizations have three or more clouds, infrastructure clouds, right. >> I would believe that. >> Back to the security, I mean, the market's booming. In a way, it's unfortunate that the market's booming is 'cause it's such a huge problem that doesn't end. It's great for you. Each year, we look back at last year and say, okay, we feel more secure, and we don't. So, what's happening in the market? Are we finally going to get a handle on sort of how to deal with this, or is it just always going to be this good guy, bad guy, leap-frogging sort of endless loop? >> The big change these days are the bad guys are pros. This is their full-time job, they're very well funded, trained, and able. >> Dave: And they only have to succeed once. >> And remember, the cost of defense is exponentially higher than the cost of offense. So what it costs my banks and hospitals to secure their environment is 10 to 100-fold over what it costs the bad guys, either in the U.S. or some other nation-state, to attack those environments. I think the biggest challenge that most of our customers face, to be honest, is technology saturation. They've bought every product known to mankind. As I like to joke, for every threat, there's an app for that, and most of our customers have bought all three of them. But then they struggle operationally with the technology, and this is more of a people and a process issue than it is a product issue. There's a lot of great technology out there, ours and other vendors as well, but if it's not implemented and maintained properly, those potentially represent the weakest links. >> And there's new threats emerging, ransomware, for instance, is to your point they're overmanned, and the cost to even compare, or defend against that, but they're already hacked. They'll pay the ransom in bit coin to get their stuff back. >> And look, it's cheaper, quicker, and faster to maybe just whack the system and try and do some forensics clean-up than deploy a next generation end-point to try and detect and mitigate against ransomware, disk encryption, or other bots that may get on the end-points themselves. >> But I almost feel like the mitigation, I mean, you've got to have perimeter security, obviously, and continue to invest in that, but I feel like you're never going to stop somebody from penetrating your organization. What's the status on average, the company's penetrated for 200 and whatever end days before they know? 220, 250, whatever number you want. There's got to be more investment in remediating, responding, managing that complexity. And so, I guess the answer to my earlier question was, well, not any time soon. We're going to have to continue to invest in new approaches, new methodologies to deal with this inundation of data, which isn't going to subside. >> Well, but part of it too is in the past, most of the security controls that companies invested in, they put at the perimeter. So, they're overprotecting on the perimeter, but now, the attacks are coming in through the side door. Spearfishing attempts >> Dave: Or internally. >> They're coming in from laptops or mobile devices that leave the organization and come back in, and since most customers lack internal segmentation, a very small infection becomes a very big problem very quickly. So, a lot of customers now are trying to figure out how do I take what I've done in the perimeter and treat my data center, my campus as untrusted, segment and silo and create smaller fault-isolation domains so that heaven forbid there is a breach or an outbreak, it's contained to a smaller subzone, rather than, look at the Target situation, which came in from an HVAC vendor, moved into a payment system, and then exfiltrated millions of credit card records. >> And, or, and not or, but, and techniques to allow the response to focus on the things that matter, and like you said, organizations, CCOS, are inundated with technology, and they don't know necessarily which threats to go deal with. They've got so much data, and to the extent that they can narrow down those high value threats, that's going to help solve the problem. That's why I was asking the question about analytics before. >> That's where I think the partnership with IBM is so important for us, right, 'cause both what they do with Watson and big data analytics and QRadar as well, it's one thing to just create a bunch of alerts, but for most customers, that's a lot of noise. Give me the interesting bits of information. I don't care about these 10 million alerts over the last week. What are the most critical things that my team needs to address right now? And those are the things that collectively IBM and Check Point help. >> How about the competitive landscape? And you guys are kickin' butt, you're well over a billion, what, $1.7 billion company, roughly? >> A little more, but yeah. >> A little more than that, almost a $20 billion market cap, which you said earlier, John, stocks almost at an all-time high, so obviously compete with Palo Alto. Do you compete with HPE, with ArcSight a little bit? I mean, that acquistion, they sort of, that's-- >> They jettisoned some of their core products that were competitive, like TippingPoint. They've kept some of their ArcSight and other big data analytics, the drive service and storage and services out there. But they're as much a partner as they are a competitor. >> Dave: They are? Okay. >> I mean, I would say the usual competitive suspects, some of the guys you mentioned, some of the big route switch vendors like a Cisco or a Juniper out there. Actually, we're in the end-point mobile space as well, which brings in the Symantec and McAfee and Kaspersky. >> And so, right, okay, so what's your big differentiation? >> I think first and foremost is that we have an enterprise management solution that goes from the mobile to the end-point to the cloud to the network. We do it all through a singular console. We have the most scalable security platform in the marketplace today, and to be honest, we have the best security solution out there, both in terms of the effectiveness as well as the manageability. >> Dave: And you're profitable and you're growing. I'm going to throw that in. >> Greg: We've been profitable since day one. >> Greg, thanks for coming onto theCUBE. We really appreciate, give you the final word on the segment as the outlook going forward. Obviously, all the cloud vendors, you work with them all, all trying to be enterprise-ready. >> Yes. >> And they're all, we're the enterprise cloud. Amazon's now the enterprise cloud, Google was flaunting it at Google Next, they got some work to do. IBM certainly is in the enterprise, Oracle's in the enterprise, Microsoft's in the enterprise. Enterprise readiness and the next few years as security evolves, what are the key table stakes that the cloud guys need to continue to work on, continue to invest in, continue to innovate? >> I think the first thing, and this is across all technology, not just cloud, is that interoperability is the new best of breed. All of our customers are going to have a couple of trusted partners. No one enterprise is single-vendor end to end. But we have to be able to play nicely in the sandox. So, whether it's working with Cisco or McAfee or Microsoft or Symantec, if I don't work well with the other investments my companies and customers have invested in, they're not going to have me around for very long. >> And that's the truth. And multi-cloud, and workloads will fit best, 'cause the SaaS also defines some of these big cloud vendors as well. Microsoft SaaS is Office 365, if you have Microsoft, that's going to be some things for ya. Greg, thanks so much, appreciate it. Great commentary with Check Point Software Technologies, talking security, head of architecture here. Greg Pepper, thanks for joining us. This is theCUBE, more live coverage here, day three coverage from theCUBE after this short break. (electronic keyboard music)
SUMMARY :
Brought to you by IBM. Here live at the Mandalay Bay You got it. You're seeing compel all the networks, You know, some people forget about us. I know you guys probably can't go into too much secret sauce in the data center, its migration to cloud, I don't need to plug into the network So, the perimeter's, with the cloud, to be agile with dev-ops, The big discussion in the last couple years in security is the ability to move into the cloud. and the customer impact. is one of the major things driving people to the cloud. and the ability to provide the forensic auditing accounting Yeah, the 20-year stair with Check Point. One of the exciting projects that we've been working on with no human intervention. What are some of the patterns you're seeing right now? the second step is how can you help me So you lay out those parameters up front, and some workloads might make sense as the cloud, but I got multiple clouds. all the data center and cloud providers, You become the Switzerland for-- in the cloud as well. but security, you can't have bumps, it's got to be part of the foundation. That seems to be the parlance of the generation. and like for like moving them to the cloud, If the cloud's available, why not? Let's go back to the workload. to everyone's offering. It's kind of like Red Sox, Yankees, you know. Microsoft probably the Yankees (muttering) is the Yankee-killer. But all the corporate applications are moving to Azure, or 70% of the organizations have three or more clouds, sort of how to deal with this, This is their full-time job, most of our customers face, to be honest, ransomware, for instance, is to your point that may get on the end-points themselves. And so, I guess the answer to my earlier question most of the security controls that companies invested in, that leave the organization and come back in, and to the extent that they can narrow down that my team needs to address right now? How about the competitive landscape? which you said earlier, John, the drive service and storage and services out there. Dave: They are? some of the guys you mentioned, that goes from the mobile to the end-point I'm going to throw that in. Obviously, all the cloud vendors, you work with them all, table stakes that the cloud guys is that interoperability is the new best of breed. And that's the truth.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Dave Vellante | PERSON | 0.99+ |
IBM | ORGANIZATION | 0.99+ |
Symantec | ORGANIZATION | 0.99+ |
Cisco | ORGANIZATION | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Microsoft | ORGANIZATION | 0.99+ |
Greg Pepper | PERSON | 0.99+ |
McAfee | ORGANIZATION | 0.99+ |
Justin Youngblood | PERSON | 0.99+ |
Dave | PERSON | 0.99+ |
Kaspersky | ORGANIZATION | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
Oracle | ORGANIZATION | 0.99+ |
Greg | PERSON | 0.99+ |
Netflix | ORGANIZATION | 0.99+ |
Yankees | ORGANIZATION | 0.99+ |
ORGANIZATION | 0.99+ | |
100% | QUANTITY | 0.99+ |
$1.7 billion | QUANTITY | 0.99+ |
24 years | QUANTITY | 0.99+ |
10 | QUANTITY | 0.99+ |
70% | QUANTITY | 0.99+ |
2017 | DATE | 0.99+ |
John Furrier | PERSON | 0.99+ |
Red Sox | ORGANIZATION | 0.99+ |
three | QUANTITY | 0.99+ |
five-year | QUANTITY | 0.99+ |
20-year | QUANTITY | 0.99+ |
Juniper | ORGANIZATION | 0.99+ |
three-day | QUANTITY | 0.99+ |
Check Point Software Technologies | ORGANIZATION | 0.99+ |
200 | QUANTITY | 0.99+ |
YouTube | ORGANIZATION | 0.99+ |
52-week | QUANTITY | 0.99+ |
last year | DATE | 0.99+ |
second step | QUANTITY | 0.99+ |
less than 30 seconds | QUANTITY | 0.99+ |
first | QUANTITY | 0.99+ |
today | DATE | 0.99+ |
U.S. | LOCATION | 0.99+ |
Office 365 | TITLE | 0.99+ |
Las Vegas | LOCATION | 0.99+ |
both | QUANTITY | 0.99+ |
Bruno Aziza & Josh Klahr, AtScale - Big Data SV 17 - #BigDataSV - #theCUBE1
>> Announcer: Live from San Jose, California, it's The Cube. Covering Big Data, Silicon Valley, 2017. (electronic music) >> Okay, welcome back everyone, live at Silicon Valley for the big The Cube coverage, I'm John Furrier, with me Wikibon analyst George Gilbert, Bruno Aziza, who's on the CMO of AtScale, Cube alumni, and Josh Klahr VP at AtScale, welcome to the Cube. >> Welcome back. >> Thank you. >> Thanks, Brian. >> Bruno, great to see you. You look great, you're smiling as always. Business is good? >> Business is great. >> Give us the update on AtScale, what's up since we last saw you in New York? >> Well, thanks for having us, first of all. And, yeah, business is great, we- I think Last time I was here on The Cube we talked about the Hadoop Maturity Survey and at the time we'd just launched the company. And, so now you look about a year out and we've grown about 10x. We have large enterprises across just about any vertical you can think of. You know, financial services, your American Express, healthcare, think about ETNA, SIGNA, GSK, retail, Home Depot, Macy's and so forth. And, we've also done a lot of work with our partner Ecosystem, so Mork's- OEM's AtScale technology which is a great way for us to get you AtScale across the US, but also internationally. And then our customers are getting recognized for the work that they are doing with AtScale. So, last year, for instance, Yellowpages got recognized by Cloudera, on their leadership award. And Macy's got a leadership award as well. So, things are going the right trajectory, and I think we're also benefitting from the fact that the industry is changing, it's maturing on the the big data side, but also there's a right definition of what business intelligence means. This idea that you can have analytics on large-scale data without having to change your visualization tools and make that work with existing stock you have in place. And, I think that's been helping us in growing- >> How did you guys do it? I mean, you know, we've talked many times in there's some secret sauce there, but, at the time when you guys were first starting it was kind of crowded field, right? >> Bruno: Yeah. >> And all these BI tools were out there, you had front end BI tools- >> Bruno: Yep. But everyone was still separate from the whole batch back end. So, what did you guys do to break out? >> So, there's two key differentiators with AtScale. The first one is we are the only platform that does not have a visualization tool. And, so people think about this as, that's a bug, that's actually a feature. Because, most enterprises have already that stuff made with traditional BI tools. And so our ability to talk to MDX and SQL types of BI tools, without any changes is a big differentiator. And then the other piece of our technology, this idea that you can get the speed, the scale and security on large data sets without having to move the data. It's a big differentiation for our enterprise to get value out of the data. They already have in Hadoop as well as non-Hadoop systems, which we cover. >> Josh, you're the VP of products, you have the roadmaps, give us a peek into what's happening with the current product. And, where's the work areas? Where are you guys going? What's the to-do list, what's the check box, and what's the innovation coming around the corner? >> Yeah, I think, to follow up on what Bruno said about how we hit the sweet spot. I think- we made a strategic choice, which is we don't want to be in the business of trying to be Tableu or Excel or be a better front end. And there's so much diversity on the back end if you look at the ecosystem right now, whether it's Spark Sequel, or Hive, or Presto, or even new cloud based systems, the sweet spot is really how do you fit into those ecosystems and support the right level of BI on top of those applications. So, what we're looking at, from a road map perspective is how do we expand and support the back end data platforms that customers are asking about? I think we saw a big white space in BI on Hadoop in particular. And that's- I'd say, we've nailed it over the past year and a half. But, we see customers now that are asking us about Google Big Query. They're asking us about Athena. I think these server-less data platforms are really, really compelling. They're going to take a while to get adoption. So, that's a big investment area for us. And then, in terms of supporting BI front ends, we're kind of doubling down on making sure our Tableau integration is great, Power BI is I think getting really big traction. >> Well, two great products, you've got Microsoft and Tableau, leaders in that area. >> The self-service BI revolution has, I would say, has won. And the business user wants their tool of choice. Where we come in is the folks responsible for data platforms on the back end, they want some level of control and consistency and so they're trying to figure out, where do you draw the line? Where do you provide standards? Where do you provide governance, and where do you let the business lose? >> All right, so, Bruno and Josh, I want you to answer the questions, be a good quiz. So, define next generation BI platforms from a functional standpoint and then under the hood. >> Yeah, there's a few things you can look at. I think if you were at the Gartner BI conference last week you saw that there was 24 vendors in the magic quadrant and I think in general people are now realizing that this is a space that is extremely crowded and it's also sitting on technology that was built 20 years ago. Now, when you talk to enterprises like the ones we work with, like, as I named earlier, you realize that they all have multiple BI tools. So, the visualization war, if you will, kind of has been set up and almost won by Microsoft and Tableau at this point. And, the average enterprise is 15 different BI tools. So, clearly, if you're trying to innovate on the visualization side, I would say you're going to have a very hard time. So, you're dealing with that level of complexity. And then, at the back end standpoint, you're now having to deal with database from the past - that's the Teradata of this world - data sources from today - Hadoop - and data sources from the future, like Google Big Query. And, so, I think the CIO answer of what is the next gen BI platform I want is something that is enabling me to simplify this very complex world. I have lots of BI tools, lots of data, how can I standardize in the middle in order to provide security, provide scale, provide speed to my business users and, you know, that's really radically going to change the space, I think. If you're trying to sell a full stack that's integrated from the bottom all the way to visualization, I don't think that's what enterprises want anymore >> Josh, under the hood, what's the next generation- you know, key leverage for the tech, and, just the enabler. >> Yeah, so, for me the end state for the next generation GI platform is a user can log in, they can point to their data, wherever that data is, it's on Prime, it's in the cloud, it's in a relational database, it's a flat file, they can design their business model. We spend a lot of time making sure we can support the creation of business models, what are the key metrics, what are the hierarchies, what are the measures, it may sound like I'm talking about OLAP. You know, that's what our history is steeped in. >> Well, faster data is coming, that's- streaming and data is coming together. >> So, I should be able to just point at those data sets and turn around and be able to analyze it immediately. On the back end that means we need to have pretty robust modeling capabilities. So that you can define those complex metrics, so you can functionally do what are traditional business analytics, period over period comparisons, rolling averages, navigate up and down business hierarchies. The optimizations should be built in. It shouldn't be the responsibility of the designer to figure out, do I need to create indeces, do I need to create aggregates, do I need to create summarization? That should all be handled for you automatically. Shouldn't think about data movement. And so that's really what we've built in from an AtScale perspective on the back end. Point to data, we're smart about creating optimal data structure so you get fast performance. And then, you should be able to connect whatever BI tool you want. You should be able to connect Excel, we can talk the MDX Query language. We can talk Sequel, we can talk Dax, whatever language you want to talk. >> So, take the syntax out of the hands of the user. >> Yeah. >> Yeah. >> And getting in the weeds on that stuff. Make it easier for them- >> Exactly. >> And the key word I think, for the future of BI is open, right? We've been buying tools over the last- >> What do you mean by that, explain. >> Open means that you can choose whatever BI tool you want, and you can choose whatever data you want. And, as a business user there's no real compromise. But, because you're getting an open platform it doesn't mean that you have to trade off complexity. I think some of the stuff that Josh was talking about, period analysis, the type of multidimensional analysis that you need, calendar analysis, historical data, that's still going to be needed, but you're going to need to provide this in a world where the business, user, and IT organization expects that the tools they buy are going to be open to the rest of the ecosystem, and that's new, I think. >> George, you want to get a question in, edgewise? Come on. (group laughs) >> You know, I've been sort of a single-issue candidate, I guess, this week on machine learning and how it's sort of touching all the different sectors. And, I'm wondering, are you- how do you see yourselves as part of a broader pipeline of different users adding different types of value to data? >> I think maybe on the machine learning topic there is a few different ways to look at it. The first is we do use machine learning in our own product. I talked about this concept of auto-optimization. One of the things that AtScale does is it looks at end-user query patterns. And we look at those query patterns and try to figure out how can we be smart about anticipating the next thing they're going to ask so we can pre-index, or pre-materialize that data? So, there's machine learning in the context of making AtScale a better product. >> Reusing things that are already done, that's been the whole machine-learning- >> Yes. >> Demos, we saw Google Next with the video editing and the video recognition stuff, that's been- >> Exactly. >> Huge part of it. >> You've got users giving you signals, take that information and be smart with it. I think, in terms of the customer work flow - Comcast, for example, a customer of ours - we are in a data discovery phase, there's a data science group that looks at all of their set top box data, and they're trying to discover programming patterns. Who uses the Yankees' network for example? And where they use AtScale is what I would call a descriptive element, where they're trying to figure out what are the key measures and trends, and what are the attributes that contribute to that. And then they'll go in and they'll use machine learning tools on top of that same data set to come up with predictive algorithms. >> So, just to be clear there, they're hypotehsizing about, like, say, either the pattern of users that might be- have an affinity for a certain channel or channels, or they're looking for pathways. >> Yes. And I'd say our role in that right now is a descriptive role. We're supporting the descriptive element of that analytics life cycle. I think over time our customers are going to push us to build in more of our own capabilities, when it comes to, okay, I discovered something descriptive, can you come up with a model that helps me predict it the next time around? Honestly, right now people want BI. People want very traditional BI on the next generation data platform. >> Just, continuing on that theme, leaving machine learning aside, I guess, as I understand it, when we talked about the old school vendors, Care Data, when they wanted to support data scientists they grafted on some machine learning, like a parallel version of our- in the core Teradata engine. They also bought Astro Data, which was, you know, for a different audience. So, I guess, my question is, will we see from you, ultimately, a separate product line to support a new class of users? Or, are you thinking about new functionality that gets integrated into the core product. I think it's more of the latter. So, the way that we view it- and this is really looking at, like I said, what people are asking for today is, kind of, the basic, traditional BI. What we're building is essentially a business model. So, when someone uses AtScale, they're designing and they're telling us, they're asserting, these are the things I'm interested in measuring, and these are the attributes that I think might contribute to it. And, so that puts us in a pretty good position to start using, whether it's Spark on the back end, or built in machine learning algorithms on the Hadoop cluster, let's start using our knowledge of that business model to help make predictions on behalf of the customer. So, just a follow-up, and this really leaves out the machine learning part, which is, it sounds like, we went- in terms of big data we we first to archive it- supported more data retension than could do affordably with the data warehouse. Then we did the ETL offload, now we're doing more and more of the visualization, the ad-hoc stuff. >> That's exactly right. So, what- in a couple years time, what remains in the classic data warehouse, and what's in the Hadoop category? >> Well, so there is, I think what you're describing is the pure evolution, of, you know, any technology where you start with the infrastructure, you know, we've been in this for over ten years, now, you've got cloud. They are going APO and then going into the data science workbench. >> That's not official yet. >> I think we read about this, or at least they filed. But I think the direction is showing- now people are relying on the platform, the Hadoop platform, in order to build applications on top of it. And, so, I think, just like Josh is saying, the mainstream application on top of the database - and I think this is true for non-Hadoop systems as well - is always going to be analytics. Of course, data science is something that provides a lot of value, but it typically provides a lot of value to a few set of people that will then scale it out to the rest of their organization. I think if you now project out to what does this mean for the CIO and their environment, I don't think any of these platforms, Teradata or Hadoop, or Google, or Amazon or any of those, I don't think do 100% replace. And, I think that's where it becomes interesting, because you're now having to deal with a hetergeneous environment, where the business user is up, they're using Excel, they're using they're standard net application, they might be using the result of machine learning models, but they're also having to deal with the heterogeneous environment at the data level. Hadoop on Prime, Hadoop in the cloud, non-Hadoop in the cloud and non-Hadoop on Prime. And, of course that's a market that I think is very interesting for us as a simplification platform for that world. >> I think you guys are really thinking about it in a new way, and I think that's kind of a great, modern approach, let the freedom- and by the way, quick question on the Microsoft tool and Tableau, what percentage share do you think they are of the market? 50? Because you mentioned those are the two top ones. >> Are they? >> Yeah, I mentioned them, because if you look at the magic quadrant, clearly Microsoft, Power BI and Tableau have really shot up all the way to the right. >> Because it's easy to use, and it's easy to work with data. >> I think so, I think- look, from a functionality standpoint, you see Tableau's done a very good job on the visualization side. I think, from a business standpoint, and a business model execution, and I can talk from my days at Microsoft, it's a very great distribution model to get thousands and thousands of users to use power BI. Now, the guys that we didn't talk about on the last magic quadrant. People who are like Google Data Studio, or Amazon Quicksite, and I think that will change the ecosystem as well. Which, again, is great news for AtScale. >> More muscle coming in. >> That's right. >> For you guys, just more rising tide floats all boats. >> That's right. >> So, you guys are powering it. >> That's right. >> Modern BI would be safe to say? >> That's the idea. The idea is that the visualization is basically commoditized at this point. And what business users want and what enterprise leaders want is the ability to provide freedom and openness to their business users and never have to compromise security, speed and also the complexity of those models, which is what we- we're in the business of. >> Get people working, get people productive faster. >> In whatever tool they want. >> All right, Bruno. Thanks so much. Thanks for coming on. AtScale. Modern BI here in The Cube. Breaking it down. This is The Cube covering bid data SV strata Hadoop. Back with more coverage after this short break. (electronic music)
SUMMARY :
it's The Cube. live at Silicon Valley for the big The Cube coverage, Bruno, great to see you. Hadoop Maturity Survey and at the time So, what did you guys do to break out? this idea that you can get the speed, What's the to-do list, what's the check box, the sweet spot is really how do you Microsoft and Tableau, leaders in that area. and where do you let the business lose? I want you to answer the questions, So, the visualization war, if you will, and, just the enabler. for the next generation GI platform is and data is coming together. of the designer to figure out, So, take the syntax out of the hands And getting in the weeds on that stuff. the type of multidimensional analysis that you need, George, you want to get a question in, edgewise? all the different sectors. the next thing they're going to ask You've got users giving you signals, either the pattern of users that might be- on the next generation data platform. So, the way that we view it- and what's in the Hadoop category? is the pure evolution, of, you know, the Hadoop platform, in order to build applications I think you guys are really thinking about it because if you look at the magic quadrant, and it's easy to work with data. Now, the guys that we didn't talk about For you guys, just more The idea is that the visualization This is The Cube covering bid data
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
George Gilbert | PERSON | 0.99+ |
Bruno | PERSON | 0.99+ |
Bruno Aziza | PERSON | 0.99+ |
George | PERSON | 0.99+ |
Comcast | ORGANIZATION | 0.99+ |
ETNA | ORGANIZATION | 0.99+ |
Brian | PERSON | 0.99+ |
John Furrier | PERSON | 0.99+ |
New York | LOCATION | 0.99+ |
Josh Klahr | PERSON | 0.99+ |
SIGNA | ORGANIZATION | 0.99+ |
GSK | ORGANIZATION | 0.99+ |
Josh | PERSON | 0.99+ |
Home Depot | ORGANIZATION | 0.99+ |
24 vendors | QUANTITY | 0.99+ |
Microsoft | ORGANIZATION | 0.99+ |
Yankees' | ORGANIZATION | 0.99+ |
thousands | QUANTITY | 0.99+ |
US | LOCATION | 0.99+ |
Excel | TITLE | 0.99+ |
last year | DATE | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
100% | QUANTITY | 0.99+ |
San Jose, California | LOCATION | 0.99+ |
last week | DATE | 0.99+ |
Silicon Valley | LOCATION | 0.99+ |
AtScale | ORGANIZATION | 0.99+ |
American Express | ORGANIZATION | 0.99+ |
first one | QUANTITY | 0.99+ |
first | QUANTITY | 0.99+ |
20 years ago | DATE | 0.99+ |
50 | QUANTITY | 0.98+ |
2017 | DATE | 0.98+ |
Tableau | TITLE | 0.98+ |
Macy's | ORGANIZATION | 0.98+ |
One | QUANTITY | 0.98+ |
Mork | ORGANIZATION | 0.98+ |
power BI | TITLE | 0.98+ |
Ecosystem | ORGANIZATION | 0.98+ |
Sequel | PERSON | 0.97+ |
ORGANIZATION | 0.97+ | |
this week | DATE | 0.97+ |
Power BI | TITLE | 0.97+ |
Cloudera | ORGANIZATION | 0.96+ |
15 different BI tools | QUANTITY | 0.95+ |
past year and a half | DATE | 0.95+ |
over ten years | QUANTITY | 0.95+ |
today | DATE | 0.95+ |
Tableu | TITLE | 0.94+ |
Tableau | ORGANIZATION | 0.94+ |
SQL | TITLE | 0.93+ |
Astro Data | ORGANIZATION | 0.93+ |
Cube | ORGANIZATION | 0.92+ |
Wikibon | ORGANIZATION | 0.92+ |
two key differentiators | QUANTITY | 0.92+ |
AtScale | TITLE | 0.91+ |
Care Data | ORGANIZATION | 0.9+ |
about 10x | QUANTITY | 0.9+ |
Spark Sequel | TITLE | 0.89+ |
two top ones | QUANTITY | 0.89+ |
Hadoop | TITLE | 0.88+ |
Athena | ORGANIZATION | 0.87+ |
two great products | QUANTITY | 0.87+ |
Big Query | TITLE | 0.86+ |
The Cube | ORGANIZATION | 0.85+ |
Big Data | ORGANIZATION | 0.85+ |
Mike Gualtieri, Forrester Research - Spark Summit East 2017 - #sparksummit - #theCUBE
>> Narrator: Live from Boston, Massachusetts, this is the Cube, covering Spark Summit East 2017, brought to you by Databricks. Now, here are your hosts, Dave Vellante and George Gilbert. >> Welcome back to Boston, everybody, where the town is still euphoric. Mike Gualtieri is here, he's the principal analyst at Forrester Research, attended the parade yesterday. How great was that, Mike? >> Yes. Yes. It was awesome. >> Nothing like we've ever seen before. All right, the first question is what was the bigger shocking surprise, upset, greatest win, was it the Red Sox over the Yankees or was it the Superbowl this weekend? >> That's the question, I think it's the Superbowl. >> Yeah, who knows, right? Who knows. It was a lot of fun. So how was the parade yesterday? >> It was magnificent. I mean, it was freezing. No one cared. I mean--but it was, yeah, it was great. Great to see that team in person. >> That's good, wish we could talk, We can, but we'll get into it. So, we're here at Spark Summit, and, you know, the show's getting bigger, you're seeing more sponsors, still heavily a technical audience, but what's your take these days? We were talking off-camera about the whole big data thing. It used to be the hottest thing in the world, and now nobody wants to have big data in their title. What's Forrester's take on that? >> I mean, I think big data-- I think it's just become mainstream, so we're just back to data. You know, because all data is potentially big. So, I don't think it's-- it's not the thing anymore. I mean, what do you do with big data? You analyze it, right? And part of what this whole Spark Summit is about-- look at all the sessions. Data science, machine learning, streaming analytics, so it's all about sort of using that data now, so big data is still important, but the value of big data comes from all this advanced analytics. >> Yeah, and we talked earlier, I mean, a lot of the value of, you know, Hadoop was cutting costs. You know, you've mentioned commodity components and reduction in denominator, and breaking the need for some kind of big storage container. OK, so that-- we got there. Now, shifting to new sources of value, what are you spending your time on these days in terms of research? >> Artificial intelligence, machine learning, so those are really forms of advanced analytics, so that's been-- that's been very hot. We did a survey last year, an AI survey, and we asked a large group of people, we said, oh, you know, what are you doing with AI? 58% said they're researching it. 19% said they're training a model. Right, so that's interesting. 58% are researching it, and far fewer are actually, you know, actually doing something with it. Now, the reality is, if you phrase that a little bit differently, and you said, oh, what are you doing with machine learning? Many more would say yes, we're doing machine learning. So it begs the question, what do enterprises think of AI? And what do they think it is? So, a lot of my inquiries are spent helping enterprises understand what AI is, what they should focus on, and the other part of it is what are the technologies used for AI, and deep learning is the hottest. >> So, you wrote a piece late last year, what's possible today in AI. What's possible today in AI? >> Well, you know, before understanding was possible, it's important to understand what's not possible, right? And so we sort of characterize it as there's pure AI, and there's pragmatic AI. So it's real simple. Pure AI is the sci-fi stuff, we've all seen it, Ex Machina, Star Wars, whatever, right? That's not what we're talking about. That's not what enterprises can do today. We're talking about pragmatic AI, and pragmatic AI is about building predictive models. It's about conversational APIs, to interact in a natural way with humans, it's about image analysis, which is something very hot because of deep learning. So, AI is really about the building blocks that companies have been using, but then using them in combination to create even more intelligent solutions. And they have more options on the market, both from open source, both from cloud services that-- from Google, Microsoft, IBM, and now Amazon, at their re-- Were you guys at their reinvent conference? >> I wasn't, personally, but we were certainly there. >> Yeah, they announced the Amazon AI, which is a set of three services that developers can use without knowing anything about AI or being a data scientist. But, I mean, I think the way to think about AI is that it is data science. It requires the expertise of a data scientist to do AI. >> Following up on that comment, which was really interesting, is we try and-- whereas vendors try and democratize access to machine learning and AI, and I say that with two terms because usually the machine learning is the stuff that's sort of widely accessible and AI is a little further out, but there's a spectrum when you can just access an API, which is like a pre-trained model-- >> Pre-trained model, yep. >> It's developer-accessible, you don't need to be a data scientist, and then at the other end, you know, you need to pick your algorithms, you need to pick your features, you need to find the right data, so how do you see that horizon moving over time? >> Yeah, no, I-- So, these machine learning services, as you say, they're pre-trained models, totally accessible by anyone, anyone who can call an API or a restful service can access these. But their scope is limited, right? So, if, for example, you take the image API, you know, the imaging API that you can get from Google or now Amazon, you can drop an image in there and it will say, oh, there's a wine bottle on a picnic table on the beach. Right? It can identify that. So that's pretty cool, there might be a lot of use cases for that, but think of an enterprise use case. No. You can't do it, and let me give you this example. Say you're an insurance company, and you have a picture of a steel roof that's caved in. If you give that to one of these APIs, it might say steel roof, it may say damage, but what it's not going to do is it's not going to be able to estimate the damage, it's not going to be able to create a bill of materials on how to repair it, because Google hasn't trained it at that level. OK, so, enterprises are going to have to do this themselves, or an ISV is going to have to do it, because think about it, you've got 10 years worth of all these pictures taken of damage. And with all of those pictures, you've got tons of write-ups from an adjuster. Whoa, if you could shove that into a deep learning algorithm, you could potentially have consumers take pictures, or someone untrained, and have this thing say here's what the estimate damage is, this is the situation. >> And I've read about like insurance use cases like that, where the customer could, after they sort of have a crack up, take pictures all around the car, and then the insurance company could provide an estimate, tell them where the nearest repair shops are-- >> Yeah, but right now it's like the early days of e-commerce, where you could send an order in and then it would fax it and they'd type it in. So, I think, yes, insurance coverage is taking those pictures, and the question is can we automate it, and-- >> Well, let me actually iterate on that question, which is so who can build a more end-to-end solution, assuming, you know, there's a lot of heavy lifting that's got to go on for each enterprise trying to build a use case like that. Is it internal development and only at big companies that have a few of these data science gurus? Would it be like an IBM Global Services or an EXIN SURE, or would it be like a vertical ISV where it's semi-custom, semi-patent? >> I think it's both, but I also think it's two or three people walking around this conference, right, understanding Spark, maybe understanding how to use TensorFlow in conjunction with Spark that will start to come up with these ideas as well. So I think-- I think we'll see all of those solutions. Certainly, like IBM with their cognitive computing-- oh, and by the way, so we think that cognitive computing equals pragmatic AI, right, because it has similar characteristics. So, we're already seeing the big ISVs and the big application developers, SAP, Oracle, creating AI-infused applications or modules, but yeah, we're going to see small ISVs do it. There's one in Austin, Texas, called InteractiveTel. It's like 10 people. What they do is they use the Google-- so they sell to large car dealerships, like Ernie Boch. And they record every conversation, phone conversation with customers. They use the Google pre-trained model to convert the speech to text, and then they use their own machine learning to analyze that text to find out if there's a customer service problem or if there's a selling opportunity, and then they alert managers or other people in the organization. So, small company, very narrowly focused on something like car buying. >> So, I wonder if we could come back to something you said about pragmatic AI. We love to have someone like you on the Cube, because we like to talk about the horses on the track. So, if Watson is pragmatic AI, and we all-- well, I think you saw the 60 Minutes show, I don't know, whenever it was, three or four months ago, and IBM Watson got all the love. They barely mentioned Amazon and Google and Facebook, and Microsoft didn't get any mention. So, and there seems to be sentiment that, OK, all the real action is in Silicon Valley. But you've got IBM doing pragmatic AI. Do those two worlds come together in your view? How does that whole market shake up? >> I don't think they come together in the way I think you're suggesting. I think what Google, Microsoft, Facebook, what they're doing is they're churning out fundamental technology, like one of the most popular deep learning frameworks, TensorFlow, is a Google thing that they open sourced. And as I pointed out, those image APIs, that Amazon has, that's not going to work for insurance, that's not going to work for radiology. So, I don't think they're in-- >> George Gilbert: Facebook's going to apply it differently-- >> Yeah, I think what they're trying to do is they're trying to apply it to the millions of consumers that use their platforms, and then I think they throw off some of the technology for the rest of the world to use, fundamentally. >> And then the rest of the world has to apply those. >> Yeah, but I don't think they're in the business of building insurance solutions or building logistical solutions. >> Right. >> But you said something that was really, really potentially intriguing, which was you could take the horizontal Google speech to text API, and then-- >> Mike Gualtieri: And recombine it. >> --put your own model on top of that. And that's, techies call that like ensemble modeling, but essentially you're taking, almost like an OS level service, and you're putting in a more vertical application on top of it, to relate it to our old ways of looking at software, and that's interesting. >> Yeah, because what we're talking about right now, but this conversation is now about applications. Right, we're talking about applications, which need lots of different services recombined, whereas mostly the data science conversation has been narrowly about building one customer lifetime value model or one churn model. Now the conversation, when we talk about AI, is becoming about combining many different services and many different models. >> Dave Vellante: And the platform for building applications is really-- >> Yeah, yeah. >> And that platform, the richest platform, or the platform that is, that is most attractive has the most building blocks to work with, or the broadest ones? >> The best ones, I would say, right now. The reason why I say it that way is because this technology is still moving very rapidly. So for an image analysis, deep learning, very good for image, nothing's better than deep learning for image analysis. But if you're doing business process models or like churn models, well, deep learning hasn't played out there yet. So, right now I think there's some fragmentation. There's so much innovation. Ultimately it may come together. What we're seeing is, many of these companies are saying, OK, look, we're going to bring in the open source. It's pretty difficult to create a deep learning library. And so, you know, a lot of the vendors in the machine learning space, instead of creating their own, they're just bringing in MXNet or TensorFlow. >> I might be thinking of something from a different angle, which is not what underlying implementation they're using, whether it's deep learning or whether it's just random forest, or whatever the terminology is, you know, the traditional statistical stuff. The idea, though, is you want a platform-- like way, way back, Windows, with the Win32 API had essentially more widgets for helping you build graphical applications than any other platform >> Mike Gualtieri: Yeah, I see where you're going. >> And I guess I'm thinking it doesn't matter what the underlying implementation is, but how many widgets can you string together? >> I'm totally with you there, yeah. And so I think what you're saying is look, a platform that has the most capabilities, but abstracts, the implementations, and can, you know, can be somewhat pluggable-- right, good, to keep up with the innovation, yeah. And there's a lot of new companies out there, too, that are tackling this. One of them's called Bonsai AI, you know, small startup, they're trying to abstract deep learning, because deep learning right now, like TensorFlow and MXNet, that's a little bit of a challenge to learn, so they're abstracting it. But so are a lot of the-- so is SAS, IBM, et cetera. >> So, Mike, we're out of time, but I want to talk about your talk tomorrow. So, AI meets Spark, give us a little preview. >> AI meets Spark. Basically, the prerequisite to AI is a very sophisticated and fast data pipeline, because just because we're talking about AI doesn't mean we don't need data to build these models. So, I think Spark gives you the best of both worlds, right? It's designed for these sort of complex data pipelines that you need to prep data, but now, with MLlib for more traditional machine learning, and now with their announcement of TensorFrames, which is going to be an interface for TensorFlow, now you've got deep learning, too. And you've got it in a cluster architecture, so it can scale. So, pretty cool. >> All right, Mike, thanks very much for coming on the Cube. You know, way to go Pats, awesome. Really a pleasure having you back. >> Thanks. >> All right, keep right there, buddy. We'll be back with our next guest right after this short break. This is the Cube. (peppy music)
SUMMARY :
brought to you by Databricks. Mike Gualtieri is here, he's the principal analyst It was awesome. All right, the first question is So how was the parade yesterday? Great to see that team in person. and, you know, the show's getting bigger, I mean, what do you do with big data? what are you spending your time on Now, the reality is, if you phrase that So, you wrote a piece late last year, So, AI is really about the building blocks It requires the expertise of a data scientist to do AI. So, if, for example, you take the image API, of e-commerce, where you could send an order in assuming, you know, there's a lot of heavy lifting and the big application developers, SAP, Oracle, We love to have someone like you on the Cube, that Amazon has, that's not going to work for insurance, Yeah, I think what they're trying to do Yeah, but I don't think they're in the business and you're putting in a more vertical application Yeah, because what we're talking about right now, And so, you know, a lot of the vendors you know, the traditional statistical stuff. and can, you know, can be somewhat pluggable-- So, Mike, we're out of time, So, I think Spark gives you the best of both worlds, right? Really a pleasure having you back. This is the Cube.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
IBM | ORGANIZATION | 0.99+ |
Mike Gualtieri | PERSON | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Dave Vellante | PERSON | 0.99+ |
George Gilbert | PERSON | 0.99+ |
ORGANIZATION | 0.99+ | |
Microsoft | ORGANIZATION | 0.99+ |
two | QUANTITY | 0.99+ |
Mike | PERSON | 0.99+ |
Red Sox | ORGANIZATION | 0.99+ |
ORGANIZATION | 0.99+ | |
Boston | LOCATION | 0.99+ |
Star Wars | TITLE | 0.99+ |
10 years | QUANTITY | 0.99+ |
Silicon Valley | LOCATION | 0.99+ |
two terms | QUANTITY | 0.99+ |
Oracle | ORGANIZATION | 0.99+ |
Yankees | ORGANIZATION | 0.99+ |
10 people | QUANTITY | 0.99+ |
Superbowl | EVENT | 0.99+ |
last year | DATE | 0.99+ |
IBM Global Services | ORGANIZATION | 0.99+ |
one | QUANTITY | 0.99+ |
both | QUANTITY | 0.99+ |
Ex Machina | TITLE | 0.99+ |
Boston, Massachusetts | LOCATION | 0.99+ |
Win32 | TITLE | 0.99+ |
first question | QUANTITY | 0.99+ |
Austin, Texas | LOCATION | 0.99+ |
19% | QUANTITY | 0.99+ |
millions | QUANTITY | 0.99+ |
yesterday | DATE | 0.99+ |
three | DATE | 0.99+ |
58% | QUANTITY | 0.99+ |
Forrester Research | ORGANIZATION | 0.99+ |
three people | QUANTITY | 0.99+ |
Spark | TITLE | 0.99+ |
One | QUANTITY | 0.99+ |
SAS | ORGANIZATION | 0.98+ |
tomorrow | DATE | 0.98+ |
three services | QUANTITY | 0.98+ |
Databricks | ORGANIZATION | 0.98+ |
Spark Summit | EVENT | 0.98+ |
both worlds | QUANTITY | 0.98+ |
TensorFrames | TITLE | 0.97+ |
MLlib | TITLE | 0.97+ |
SAP | ORGANIZATION | 0.97+ |
today | DATE | 0.96+ |
each enterprise | QUANTITY | 0.96+ |
TensorFlow | TITLE | 0.96+ |
four months ago | DATE | 0.95+ |
two worlds | QUANTITY | 0.95+ |
Windows | TITLE | 0.95+ |
Cube | COMMERCIAL_ITEM | 0.94+ |
late last year | DATE | 0.93+ |
Ernie Boch | PERSON | 0.91+ |
Reggie Jackson | SAP SapphireNow 2016
(mumbling) >> Voiceover: Covering Sapphire now. Headline sponsored by SAP HANA Cloud, the leader in platform as a service. With support from Console Inc., the cloud internet company. Now, here are your hosts, John Furrier and Peter Burris. >> We are here live at SAP Sapphire. This is SiliconANGLE Media's The Cube. It's our flagship program. We go out to the events and extract the signal to noise and want to do a shoutout to our sponsors SAP HANA Cloud and Console Inc. at console cloud, connecting the clouds together. I'm John Furrier with my co-host Peter Burris. Our next guest is Reggie Jackson, winner, athlete, tech athlete now, entrepreneur, overall great guy, and a cube alumni. Four years ago, we interviewed him here at SAP Sapphire. Welcome back, Reggie, to The Cube. Thanks for coming on. John, thank you very much. It's good to be here with old friends. We were havin' a little conversation about baseball there, but good to see you guys. Yeah, and obviously, the baseball, we were just talkin' about the whole fisticuffs and the glee of the grand slam walk-off. >> Reggie: Good stuff, good stuff. >> It's a good pivot point in some of the things that you're workin' on in here, the conversations in the tech world, which is social media and that notion of celebrating in a world of Instagram and Snapchat and social media. Certainly, ya flip the bat, the views go up. But then, baseball has these (laughing) unwritten rules, right. So does corporations. And so we're now a new era. Is baseball safe now with these unwritten rules and should they maintain those, certain things that have kept the game in balance? But yet with social media, the players are their own brand. And you certainly were a brand, even back in your day, which is a pioneer. What's your thoughts on that? >> You know John, Peter, I don't like the idea of someone going out of their way to promote their brand. Some of the great brands to me in history, Babe Ruth, Ty Cobb, the great Jim Brown, Joe Montana, Michael Jordan. And Michael Jordan would be a prominent example where technology and TV enhanced who he was. And he had someone behind him to enhance his brand, Nike, Phil Knight, who was a real pioneer. I'm not so in favor, I'm not in favor at all of someone manufacturing themselves as a brand. And I hear players talk about their brand and about trying to create something. If you're great, if you deserve it, I don't think Stephen Curry works on his brand. I think he works on bein' a great player. I think he works on bein' a great teammate. I think he does his best to maximize his skill set. And he's nothing but a gentleman along the way. He'll celebrate with joy once in awhile, with the Curry moves, which we've come to recognize. But for guys that talk about the manufacturing of their brand, there's something about it that's manufactured. It's not real, it's false. And I don't like it. I think it's okay, the Snapchats and the Google+ and all of the stuff, Twitter and Facebook and all that stuff, all of the things that go along with trying to create some hubbub, etc. I'm okay with that. >> So you're saying if it's not deserved. People are overplaying their hand before earning it. >> A lot of it, John, a lot of it. Joe Montana didn't work on his brand, he was great. Jim Brown didn't work on his brand, he was great. I don't want to use Jimmy Brown. I want to use Montana because even young people today will know Joe Montana. Tom Brady, Peyton Manning, they're not about their brand. They're about being classy, being great, being part of a team, being a leader, presenting themselves as something that's respected in the NFL, across the United States. Go ahead, Pete. >> So even though it's cheaper to get your name out there, you still believe in let your performance speak for itself. >> You got to be real about it. Ya got to be who you are. If you're not a great player, get out of the way. Get out of the space. So manufacturing your brand. I played with the Yankees. I was in the era of Cosell and Billy Martin and George Steinbrenner. We won championships with the team. I was part of something that helped me become recognized. And so in our era, the Sandy Koufax's became brands because they were associated with greatness around them. They stood out and so they earned that tremendous brand. >> We were just watching Graig Nettles gettin' taken out by George Brett in that big game and also the pine tar, we kind of gettin' some good laughs at it. You look at the balance of personalities. Certainly, Brett and Nettles and your team and you had a great personality, winning championships. Worked together as a team. And so I want to ask you that question about the balance, about the in baseball, certainly, the unwritten rules are a legacy and that has worked. And now in a era of personalities, in some cases, people self-promoting themselves, people are questioning that. Your thoughts on that because that applies to business too 'cause tech athletes or business athletes have a team, there are some unwritten rules. Thoughts on this baseball debate about unwritten rules. >> Pete and John, I'll try to correlate it between some tech giants that have a brand. I just left a guy with a brand, Bill McDermott, that runs SAP. Even Hasso, the boss. The face now of SAP is Bill McDermott. Dapper, slender, stylish, bright. It comes across well. So maintaining that brand, to me, relates to SAP, bills a great image for it. He's stylish, he's smooth, he's smart. He's about people. He presents himself with care. So that is a brand. I don't think it's manufactured. That's who he is in real life. If you take a look, and I'll go back to Steph Curry because that name resonates and everyone recognize it. That style of cool, that style of control, that style of team and care. And he presents to us all that he cares about us, the fan, his team, his family. And so those are things and I think you can go from the tech world. Bill Gates had a brand. Brilliant, somewhat reclusive, concerned about the world, concerned about the country, concerned about his company. And so that resonated it Microsoft because that's who he really was. Some of the people today don't really recognize that Jobs was thrown out of Apple. He was pushed out. All of his brilliance, which was marketing. And the gentleman there that really was the mind for the company, Steve Wozniak, happens to be here at SAP Sapphire. Today, I think he speaks. But those brands were real, not manufactured. And so, in today's world, I think you can manufacture a brand. And then all of a sudden, it'll crumble. It'll go away in the future. But the great brands of whether it's Jackie Robinson or whether it's Jack Welch or whether it's George Steinbrenner and the Yankee brand, those brands were real. They were not manufactured. Those guys were eccentric. They were brilliant. Go ahead. >> And also, they work hard. And I want to point out a comment you made yesterday here at the event. You were asked a question up on stage about that moment when you hit the home runs. I think we talked about it last time. I don't necessarily want to talk about the home runs. But you made a comment I'd like you to expand on and share with the audience. 'Cause you said, "I worked hard," but that day during warm-ups, you had batting practice. You made a comment that you were in the zone. So working hard and being great as it leads up to that. But also, in the moment, 'cause that's a theme these days, in the moment, being ready and prepared. Share your thoughts on what you meant by you had a great batting practice and you just felt it. >> I'm going to take it to what you say is in the moment. I remember when I was talkin' about it yesterday, which you reference to, when I had such a fantastic batting practice. I walked by a coupla sports writers in that era. Really well-known guys, Dave Anderson, New York Times. I can't think of his name right now, but it'll come to me, of the Daily News. It was like hey man. >> John: You were rockin' it out there. >> I kind of hope I didn't leave it out here. (laughing) That was in the moment and at the same time, >> I mean, you were crushing it. >> Yes, when the game started, I got back in that moment. I got back in what was live, what was now, what was going on. Certainly, I think our world now with the instant gratification of sending out a message or tweeting to someone or whatever certainly in the moment is about what our youth is and who we are today as a country, as a universe. >> But you didn't make that up. You worked hard, but you pulled it together in the moment. >> A comment with that is I went and did something with ESPN earlier this year in San Francisco, in Oakland with Stephen Curry. They said, "Reggie, we want ya to come up "and watch his practice, his pre-game." And it was very similar to your batting practice, where people come out and watch, etc. And so I was looking forward to it and I like to go to the games about an hour and a half or two hours early so I can see warm-up and see some of the guys and say hello. And I got a chance to watch Steph Curry. I know his dad. And happened to be the first time I went this year, the dad, Carolina, the Panthers were in town. Not the Panthers. Come on, help me, help me, help me. >> Peter: The Wizards? >> No, no, no, the Carolina. >> Peter: Carolina Panthers. >> The Carolina Hornets. >> John: Hornets. >> Were there and I know his dad, Dell Curry. And we talked a little bit. But then, Steph came out and I watched him. And I watched the dribbling exhibition. I watched the going between the legs and behind the back and the fancy passing, etc. And I watched the shots, the high-arcing threes, the normal trajectory threes, the high shots off the backboard and things like that that he did. The left-handed shots, the right-handed shots. And the guy asked me what I thought of the show. And I said, "Well, it's a cool show, "but I'm going to see all that tonight." And me watching him, the behind the backs, the between the legs, the passes, the high-arching shots from three, the high-arching touches off the glass. He does all that. >> John: He brought it into the game. >> Yeah, I said so, (laughing) >> Peter: That is his game. >> It's not a show, but that's his game. >> So Reggie, you did an interesting promotion, Reggie's Garage, where you bought a virtual reality camera and you created a really nice show of your garage demonstrating your love >> Reggie: 360. >> Peter: of cars, 360. Talk a little bit about that. And then if ya get a second, imagine what baseball's going to be like as that technology becomes available and how some of the conversation that we're having about authenticity, the fan coming into the game. >> An experience. >> Is going to change baseball. Start with the garage and how that went and then how ya think that's going to translate into baseball, if you've had any thoughts on that. >> In the technology that was used, certainly I enjoyed it. While I was doing it, I noticed where the cameras were in different spots. There was one on the floor of my car. There was one in the backseat. And then there was someone following us as closely as they could. But you could see everything. You'd see the shift and you could see my feet. It was like you were with me. When we did the 360 inside the garage as well, you could listen to me and then you could use your finger and spin around. And they had these special headset and special glasses that you could look around, just with your headset on, and see all around the room. Behind you, in front of you. And so it's an experience that I think is going to become part of who we are as a nation, who we are as a people watching television, that you're going to really feel like you're in the room. I think it's going to be exciting. And I think it's going to be fun. And when you're talking about products, when you're talking about my website, if you will, with the focus on automotive parts, where a guy can go in and shop and get any part he wants for a vehicle, you really can build a complete car from my website. You can buy a frame. You can buy body parts. You can buy a horn, an engine, brakes, tires, grills, turn signals, the whole nine yards. And it gives you an experience through 360 video of really walking into the store, walking into the building, walking into the stadium and looking around to see the hot dog stand, see the dugout, see the pitcher and the hitter, to see the parts in the garage, to see the cars and take a look and view at everything that's there. >> How are players going to react to havin' the fans virtually right there with them? >> I don't think it bothers you. I don't think ya notice. I don't think they'll show anything that will affect the player that he's going to be concerned about. I think you'd have to be sensitive if they start microphoning, start micing up and then the looseness of the language would impact. So I don't think they'll go that far. But I do think the more that you can see, the more attractive the game becomes, the more interested that you can get people. When I broadcast baseball for ABC back in the 80's, I always tried to broadcast for the lady of the house, while she worked, while she cooked the meal, she didn't have time to think about a backup slider or the fastball that painted the outside corner, the changeup, etc., the sinker. I tried to broadcast for her interpretation so I could attract another fan to the game. So I think that the technology and the viewing that you'll see from behind home plate, from under the player's feet while he's running down the bases and the slides and things of that nature, Pete, I think are going to be exciting for the fan and it'll attract more fans, attract a new type of television it's going to produce, etc. So it's exciting. >> Reggie, thanks for comin' on The Cube again. Appreciate your time. I ask ya final two questions that I want to get your thoughts on. One is obviously the cars. Reggie's Garage is goin' great. And you shared with us last time on The Cube, it's on YouTube, about you when you grew up and decide football and baseball. But when you were growin' up, what was your favorite car? What was that car that you wanted that was out of reach? That car that was your hot rod? And then the second question is, we'll get to the second question. Answer that one first. What was you dream car at the time? How did ya get >> Reggie: The dream car >> John: hooked on this? >> at the time. I had a '55 Chevrolet that I bought from a buddy by the name of Ronny Fog. I don't even know if he's still around anymore. Out of Pennsylvania. I had $300 and my dad gave me $200. I'd saved up mine from workin' for my dad. But my dream car was I went to school with a guy named Wayne Gethman and another guy named Irwin Croyes. I don't know Wayne Gethman anymore. But from the age of 16, I reengaged with Irwin Croyes, who happens to be a business investing type guy in the city of Philadelphia, right where we're still from. He's a car collector. And he drove a '62 Corvette and so did Wayne Gethman. And I always wanted one. And I now happen to have four. (laughing) >> He who get the most toys wins. Final question, 'cause you're such a legend and you're awesome and you're doin' so much work. And you're very active, engaged, appreciate that. Advice to young athletes coming up, whether they're also in business or a tech athlete or a business athlete. But the sports athletes today got travel ball, you got all this stuff goin' on. The idols like Stephen Curry are lookin' great. Great role models now emerging. What advice do you give them? >> John's got a freshman in high school. I got a junior in high school. What would ya say to 'em? >> You know, I'll tell ya. When you're young, the people you want to listen to are Mom and Dad. No one, and I'll say this to any child from the age of eight or nine years old, five, six years old to 17, 18, 19, 20, all the way up, now my daughter's 25. All the way up to the end of your parents' days. No one cares for you more than your mother or your father. Any parent, whether it's a job or whether their success in life, number one in that man or woman, mom or dad, number one in their life is their children. And so for kids, I say if there's any person you're going to listen to for advice in any path you want to walk down, it's the one that your parents talk to you about or how they show you. That is what I would leave as being most important. For kids, anything, idea that you have that you believe you can do, whether it's the athlete like Stephen Curry that has created shots and done things on the basketball court that he envisioned, that he thought about. Or whether it's the next Steve Jobs who happens to be Mark Zuckerman, who I don't know Mark is 30 years old yet. >> John: He just turned 30. >> It's an idea. He's born around the same time. He's born this week. His birthday is in this week. My birthday's tomorrow. >> John: Happy birthday. >> But thank you. Anything that you can think of in today's world of technology. With places like Silicon Valley where they take dreams and create foundations for them. I had a dream about a website that would sell automotive parts and you could go to my site and buy anything for your car. We've got about 75,000 items now. We'll get to 180,000 in a few months. We'll get to a half a million as soon as my technology is ready for it. But we have things to pay attention to and look into and issues to make sure that we iron out that aren't there for our consumer, for ease of navigation, ease of consumption and purchasing. Any idea that you have, take time to dream. It's much more so than taking time to dream when I was a young kid. Because my father would say, "Stop daydreamin' "and wastin' time." >> John: Get to work. >> Reggie: In today's world, for our children, I say take time to create a vision or to create something new. And go to someone that's in the tech world and they'll figure out a way of helping you manifest it into something that's a reality. >> Listen to your parents, kids. And folks out there, dream, build the foundation, go for it. Reggie Jackson, congratulations for being a Cube alumni again, multi-return. >> Peter: Thank you very much. >> John: Appreciate it. Congratulate on all your continued success. You're a legend. Great to have you on. And thanks so much for comin' on The Cube. >> Peter: And happy 70th birthday. >> John, Pete, always a pleasure. >> John: Happy birthday. >> Thank you very much. >> Have some cake for Reggie. It's The Cube, live here in Orlando. Bringin' all the action here on The Cube. I'm John Furrier with Peter Burris with Reggie Jackson. We'll be right back. (electronic music)
SUMMARY :
the leader in platform as a service. and extract the signal to noise in some of the things that Some of the great brands to me in history, So you're saying if it's not deserved. that's respected in the NFL, to get your name out there, Ya got to be who you are. And so I want to ask you that question And the gentleman there that really was But also, in the moment, 'cause that's I can't think of his name right now, and at the same time, I got back in that moment. But you didn't make that up. And I got a chance to watch Steph Curry. And the guy asked me what and how some of the conversation Is going to change baseball. And I think it's going to be fun. But I do think the more that you can see, And you shared with us And I now happen to have four. But the sports athletes I got a junior in high school. it's the one that your He's born around the same time. Anything that you can think of I say take time to create a vision build the foundation, go for it. Great to have you on. Bringin' all the action here on The Cube.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Jim Brown | PERSON | 0.99+ |
Steve Wozniak | PERSON | 0.99+ |
Mark Zuckerman | PERSON | 0.99+ |
John | PERSON | 0.99+ |
Dave Anderson | PERSON | 0.99+ |
Joe Montana | PERSON | 0.99+ |
Steve Jobs | PERSON | 0.99+ |
Steph | PERSON | 0.99+ |
Stephen Curry | PERSON | 0.99+ |
Reggie Jackson | PERSON | 0.99+ |
Michael Jordan | PERSON | 0.99+ |
George Steinbrenner | PERSON | 0.99+ |
Peter | PERSON | 0.99+ |
George Steinbrenner | PERSON | 0.99+ |
Peter Burris | PERSON | 0.99+ |
Jimmy Brown | PERSON | 0.99+ |
Reggie | PERSON | 0.99+ |
second question | QUANTITY | 0.99+ |
Tom Brady | PERSON | 0.99+ |
Stephen Curry | PERSON | 0.99+ |
San Francisco | LOCATION | 0.99+ |
Bill McDermott | PERSON | 0.99+ |
Bill Gates | PERSON | 0.99+ |
Irwin Croyes | PERSON | 0.99+ |
George Brett | PERSON | 0.99+ |
five | QUANTITY | 0.99+ |
Yankees | ORGANIZATION | 0.99+ |
Wayne Gethman | PERSON | 0.99+ |
Jack Welch | PERSON | 0.99+ |
Silicon Valley | LOCATION | 0.99+ |
John Furrier | PERSON | 0.99+ |
180,000 | QUANTITY | 0.99+ |
30 | QUANTITY | 0.99+ |
Orlando | LOCATION | 0.99+ |
Console Inc. | ORGANIZATION | 0.99+ |
United States | LOCATION | 0.99+ |
$200 | QUANTITY | 0.99+ |
Today | DATE | 0.99+ |
six years | QUANTITY | 0.99+ |
Peyton Manning | PERSON | 0.99+ |
Microsoft | ORGANIZATION | 0.99+ |
25 | QUANTITY | 0.99+ |
Pennsylvania | LOCATION | 0.99+ |
Mark | PERSON | 0.99+ |
$300 | QUANTITY | 0.99+ |
nine years | QUANTITY | 0.99+ |
17 | QUANTITY | 0.99+ |
Billy Martin | PERSON | 0.99+ |
yesterday | DATE | 0.99+ |
ESPN | ORGANIZATION | 0.99+ |
eight | QUANTITY | 0.99+ |
Pete | PERSON | 0.99+ |
Philadelphia | LOCATION | 0.99+ |
Apple | ORGANIZATION | 0.99+ |
tomorrow | DATE | 0.99+ |
Nike | ORGANIZATION | 0.99+ |
20 | QUANTITY | 0.99+ |
Ronny Fog | PERSON | 0.99+ |
Oakland | LOCATION | 0.99+ |
Phil Knight | PERSON | 0.99+ |
Chevrolet | ORGANIZATION | 0.99+ |
this week | DATE | 0.99+ |