 From the SAP Center at San Jose, home of the San Jose Sharks. Extracting the signal from the noise. It's theCUBE, covering HGST, sports data, Silicon Valley. Brought to you by HGST. Now your hosts, John Furrier and Jeff Frick. Okay, welcome back everyone. We are here live in San Jose at the Shark Tank. This is theCUBE Silicon Angles flagship program. We go out to the events, extract the signal from the noise. I'm John Furrier, the founder of Silicon Angles. I'm joined by my co-host Jeff Frick, the general manager of theCUBE. Special presentation here at the Shark Tank. Our next guest is David Tang, SVP and general manager of HGST Cloud. Infrastructure business, welcome to theCUBE. Special presentation. Thanks. It's great to be here. Always great to be back on theCUBE, and especially here at SAP Center. Home of the Shark. Live audience, everybody's excited. So I said on my Facebook broadcast, theCUBE, HGST and your customers, it's a hat trick of innovation. It really is. Thank you so much. Appreciate it. The sports, we love sports because sports now really emphasizes the future of IT and the cloud, managing your employees, managing your fans, customers, and also the experience of that. All that together now is now the holy grail for all businesses. Right, absolutely. Sports is like, it's a microcosm of the whole big data movement, an IoT movement, right? You've got customers or fans and their experience, their engagement can be improved all based on data. And from the perspective of the team, the players, they can make a better product, they can ensure performance at its maximum, and even prevent injuries to their key players. So it's a fantastic opportunity and fantastic way to really emphasize the value of data. You know, data's a competitive advantage, and that's one thing that now has hit mainstream, was kind of in the early adopter, the Silicon Valley, Echo Chamber, and all the elite and the vendors who are out there doing it now, with big data analysts and cloud, and having data available, not just stored, but real-time, we mentioned earlier, real-time communications, mobile devices, but now you have new fan experiences, Oculus Rift, Virtual Reality, those are data-driven devices. So will there be a slowdown in storage and cloud? I'm rhetorical, obviously yes. What's your take on that? I mean, it's never ending. It is never ending. I mean, the amount of data that's being created is growing at an astronomical rate, and the amount of data that's valuable enough to analyze in real-time and store and re-analyze for historical purposes is also growing. So, you know, this whole notion of a data-centric world really equates to a storage-centric data center. So it's fantastic, it's a great time to be in storage. And really the expectations on access to information, speed of that access, richness of that access, you know, we always talk about kind of before Google and after Google, which really change the perception of what people expect to be able to get out of their little mobile phone. And now we've seen that obviously trickle into the enterprise, influence the enterprise. You know, they've got to make that data available to their customers, their employees, customers, partners quickly. It's got to be there. And really expectations on the performance of the applications which are all driven by the data has changed dramatically over the last few years. Yeah, right. The demands on data are just skyrocketing. So it's not just having data available to you as in pieces of information, but it has to be actionable. It has to be to help you make decisions. So driving not only to web-related response times, but driving to real-time analytics, real-time information, real-time decision-making, that's the key. The other piece that keeps coming up over and over we do a lot of big data shows, right? Is it used to be you just couldn't afford to store everything. You just couldn't, the exhaust, right? Talk about the data exhaust, you just let it ride, maybe grab a sampling. But now people don't want to do sampling anymore. They want to be able to get all the data. They want to be able to cut it, slice it, dice it, however they want. So now that's just driving more demand for more data because I don't want to sample, I don't want to throw away. I don't know if I'm going to need this today or tomorrow or down the road. Yeah, absolutely. So the notion of sampling has gone away. Companies, organizations want to store all the data. And not only that, they want to store it in raw form. There used to be, you tried to save space in storage systems by compressing the data, but now you don't know what kind of algorithms are going to come up in the future that can be used to analyze the data and extract more value from the data. So the last thing you want to do is compress something and lose future value. So it's not just more data, it's the fact that that data needs to be stored in its raw state. David, take a step back and talk about any updates in your organization because now obviously the world has moved into this post-client server world. We're seeing things. We saw the big acquisitions are happening, Dell buying EMC, big consolidations, but there's so much new stuff happening. A new era is upon us, cloud, mobile, social, big data. What's new with you guys and some of the things that you guys are doing to take advantage of this next huge wave? Right. So a lot of analysts refer to this new wave as the third platform of computing where client server, as you mentioned, is the second platform of computing. And the key characteristic of the third platform of computing is this massive scale ability to take on the growth in data as well as the ability to stretch computing capabilities when you need to, this elasticity of computing capability. So this all relies on more of a software centric, software-defined infrastructure. So you've heard the term software-defined networking, software-defined storage, software-defined data centers. And the reason for that is that's what enables you to scale at massive levels, petabyte scales, exabyte scales. Prior to that, everything was built in silos where they could only grow so far. So when we're talking about the amount of data doubling every two years or less, we really need environments and architectures that are going to manage that growth and do it in a very, very affordable way as well. Talk about the dynamic as you mentioned silos, right? So data silos don't work well on this new data hoarding and kind of putting the data, putting it out in the far hinterlands of the company. It's got to be real time. So that's one thing. Talk about the openness of data, why is it open? And then talk about this new analytics software market where data analytics and software, the interplay between that software development market and then this open data. And what does that do for customers? Right, so they're very interrelated, those questions. So the openness is important because back in the world of client server and especially in mainframe, the silos were made up of the application as well as the data. And the data that was created was only accessed by that one application. Now we're in a world where you have many, many applications wanting to access the same data. I mean, we see that every day with our own cell phones or smartphones that we have several applications that want to access contacts or calendars. The same thing goes with big data and IoT. You want that data to be accessible for multiple applications. Therefore, you need an openness, open APIs on how to access that data. And in terms of the analytic nature of that structure is you really need two different general categories of analytics to be able to access the data. One is real time, the real time analysis of what's going on to be able to make decisions in real time. And the other one is that you want to store all the data that's gathered from its point of inception and you want the ability to analyze that over longer periods of time or access it over longer periods of time. For example, with video content in sports, being able to access any random play and similar plays, that takes a very open and very scalable architecture. So I wonder if you could follow up on that as content like video has become more pervasive and a more kind of general purpose communication vehicle than it used to be. And what are you seeing from some of your clients in terms of their demands for storage based on simply shifting a greater focus of their communications effort, their documentation, their training, whether that be external or internal HR, welcome to the company. Two things like video in these rich formats. So video as a content of course is gaining in popularity. It's very easy to consume and it's becoming very easy or easier to create. But it's more than just the content. It's the ability to find the content and understand the context in which that content was captured. So actually in addition to just the video streams that are being created, content needs to be indexed as well. So the ability to identify in the sporting realm, identify the players, identify the conditions of play, the opponent, all the things that you would want to search on at a later time to be able to call up past clips or to try to predict what might happen next. That's all important as well. So it's not just a matter of the content or the data in itself. It's really about the data about the data that's becoming you more important, which is causing even stronger demands for storage and computing. So we have some questions on the crowd chat from DPAC. Any plans to leverage IoT to monitor concussions in real time? And then in addition to using next-gen replay, monitoring impacts, this kind of equipment. So have you seen some of your customers doing things like that in the sports world and or giving general comments around IoT in general? Because it brings up a safety issue which is a societal benefit. IoT has that. So tie that together. Yeah, so I certainly think that that's a possibility. I mean, we see a lot of innovation in helmets that can determine what the force of an impact is. Don't necessarily see that coming into professional sports yet, but I think with a lot of what we're seeing in the NFL, as well as in the hockey world, that is probably gonna, it's just a matter of time before that becomes commonplace. And it's not just the obvious impacts. There are wearables that can determine how much strain an athlete is under. Are they over-exerting themselves? Are they becoming more prone to injury? So I think even on a preventative basis, IoT and wearables can help to play into. What about the IoT trend in general? I mean, obviously this being hyped up big time now. How much of that on your radar is all in? How big will it be in your mind? Do you see that as a massive tsunami or is it just over-hyped right now? Oh, I think it's a massive tsunami, not just in terms of the wearable devices that I think are getting a lot of the play, but also other sensors that can detect other characteristics of people, of situations, environment, I mean, fixed cameras and arenas are an example, but we were talking to a company that's developing next generation image sensors, so they can actually do very rich 3D imaging. They can tell the difference between a grimace on a professional athlete that's caused by pain or a grimace that's caused by maybe disappointment of the outcome of the play. Mr. Fieldville, lost again. So those are all important to feeding into that, but we just see a massive explosion for IoT across all industries. So Dave, I wonder if we can talk tech a little bit. We love Moore's Law, we love going to Intel, and Moore's Law is impacting all the sensors, it's impacting the compute capacity, it's impacting networking. What are some of the things that you can share that you're seeing just great technological innovation that's enabling the storage, it's got a whole lot of stuff to keep ahead and to stay current with all these other innovation across the compute cycle? Right, so I think there are a couple dimensions to that. One is the underlying technologies that enable storage devices to store more and operate at higher performance. But I think there are other aspects of innovation as well, and that's really something that HEST is focusing on is the ability to innovate in multiple dimensions. So we not only have the ability to develop hard disk rise, for example, that can store more data because they're helium filled because we're using advanced head and disk technologies, but what we're doing is we're looking at the entire system as a point of innovation. So taking devices and optimizing those devices for custom design hardware, designing software to take full advantage of that underlying hardware, really co-optimizing all of those areas within an architecture to drive the capabilities even further. So with our systems, we're delivering more value than the sum of the parts than what you'd get otherwise without that co-optimization. So we're really trying to take innovation to another level and something that we refer to as vertical innovation because we're covering so much of the vertical stack of the system now. And how much of that is driven by cloud? Because like you said, cloud is so big now. And really the promise of cloud is capacity on demand. That's compute capacity, store capacity, network capacity, that's just there. And the expected performance and behavior is thanks to Amazon, I swipe my card, it's there for me now. How has that really impacted your guys' kind of system approach to looking at storage as part of that whole thing as opposed to just kind of hanging off the side? Well, so the shift from traditional enterprise data center architectures, second platform architectures over to the cloud or third platform architectures is a key enabler to the innovation that we're bringing to market. Because those environments just demand more scalability and elasticity and flexibility, as you mentioned. So we see that as a great opportunity for our efforts in cloud infrastructure. We are David Tang, the SVP General Manager of HGST, Cloud Infrastructure Business Unit. Thanks so much for coming on theCUBE here for, and thanks for putting on this special presentation. Give me the final word. Talk about the fun aspect of, so the shark, Zamboni there, the petabiter, it's a little tricked out, it's got a little fin on it. You guys are humanizing it. You're into sports, you've got the CrossFit thing. Is that part of the strategy? You're humanizing it? Talk a little bit quickly about all that exciting stuff. Well, so a lot of aspects there. So our partnership with CrossFit is fantastic. HGST was recognized as one of the fittest companies in the country, and it's not just the sense of getting exercise and being fit. It's the camaraderie that it creates in the workplace. So even though you may think of CrossFit as a competitive sport, it actually builds camaraderie because you're really competing with yourself, with your last workout when it comes to CrossFit. So you have a full people encouraging you to take your workout to the next level. So that's a great cultural aspect within the company. It also allows people, individuals from different functions to get to know each other, and that results in better, more effective teams. I think in terms of just what we're trying to accomplish with data and being able to enable organizations to extract more value from that data is we're trying to personalize a broad set of experiences. A lot of people think that information technology goes to dilute that. We think that it actually can enhance that because think about it. If a particular workout course benefits maybe 80% of the people, well that's great. But what if I'm in that 20%? Well if I could have big data helping to prescribe a very specific workout arrangement for myself, I can benefit from that. That's a lot more personalized and humanized and prescriptive, so that's really- And that's a big trend, it's not going away. That's right. The eye watches, all kinds of sensors, humanization is personal now. That's right. It's wearables, all that good stuff. David, thanks so much for the Cube. We'll be back with more live coverage of the special Cube presentation. We'll be right back after this short break.