 Live from San Jose, California, it's theCUBE. Covering, innovating to fuel the next decade of big data. Brought to you by Western Digital. Hey, welcome back everybody. Jeff Frick here with theCUBE. We're at the Western Digital headquarters in San Jose, the Alameda campus, a really historic place in the history of Silicon Valley and computing. It's the innovating to fuel the next generation of big data event with Western Digital. We're really excited to be joined by our next guest, Mike Cardano, he is the president and chief operating officer of Western Digital. Mike, great to see you. Great to see you as well. Happy you guys could be here. Exciting day. And first off, I think kind of the whole merger thing is about done, right? That's got to feel good. It's done, but there's legs to it, right? So we've combined these companies, now three of them, three large ones. So obviously Western Digital and Hitachi Global Storage. Now we've added Sandis into one Western Digital. So we're all together, obviously more to do as you expect in a large scale integration. There'll be a year or two of bringing all those business processes and systems together. But I got to say, the teams are coming together great, showing up in our financial performance and our product execution. So things are really coming together. Yeah, and not an easy task by any stretch of imagination. Not easy, but certainly a compliment to our team. I mean, we've got great people. And like anything, if you can sort of harness the capabilities of your team, there's a lot you can accomplish and it really is a compliment to the team. Excellent. Congratulations on that. And talking about this event here today, you even use big data in the title of the event. So you guys are obviously in a really unique place Western Digital. You make systems and big systems. You also make the media that feeds a lot of other people's systems. But as the big data grows, the demand for data grows, it's got to live somewhere. So you're sitting right at the edge where the stuff's got to sit. Yeah, that's right. And that's central to our strategy, right? So if you think about it, there's sort of three fundamental technologies that we think are just inherent in all of the evolution of compute and IT architecture. Obviously, there is compute, there is storage or memory, and then there's sort of movement or interconnect. We obviously live in the storage and memory node, and we have a very broad set of capabilities, both all the way from rotating magnetic media, which was our heritage, now including non-volatile memory and flash, and that's just foundational to sort of kind of everything that is going to come, right? And as you said, we're not going to stop there. It's not just a devices or component company. We're going to continue to innovate above that into platforms and systems. And why that becomes important to us is there's a lot of technology innovation we can do that enhances the offering that we can bring to market when we control the entire technology stack. Right. Now, we've had some other guests on and people can get more information in kind of the nitty gritty details that he announced about today. The mayor announcement, basically in a nutshell, enabling you to get a lot more capacity in hard drives. But I thought in your opening remarks this morning, there were some more high level things I wanted to dig into with you. And specifically, you made an analogy of the data economy and compared it to the petroleum economy. I've never, you know, a lot of talk about big data, but no one really talks about it or that I've heard in those terms, because when you think about the petroleum economy, it's so much more than fuel and cars and the second order impacts and the third order impacts on society are tremendous. And you're basically saying we're going to do this all over again, but now it's based on data. Yeah, that's right. And I think it puts it into a form that people can understand, right? I think it's well proven what happened around petroleum. So the discovery of petroleum and then the derivative industries, whether it be automobiles, whether it be plastics, you pick it, the entire economy revolved around and to some degree still revolves around petroleum. The same thing will occur around data. You're seeing it with investments, you hear now things like machine learning or artificial intelligence, that is always to transform and mine data to create value. And we're going to see industries change rapidly, autonomous cars, that's going to be enabled by data and capabilities here. So sort of pick your domain, there's going to be innovation across a lot of fronts, across a lot of traditional vertical industries that is all going to be about data and driven by data. What's interesting with Janet, Dr. Janet George talked about too a little bit is the types of data and the analysis of the data is also evolving very quickly from data at rest, to data in motion, to real time analytics, like you say the machine learning and the AI, which is based on modeling prior data, but then adjusting new data and adjusting those models. So even the types and the rate and the speed of the data is under a dramatic change right now. Yeah, that's right. And I think one of the things that we are helping enable is you kind of get to this sort of concept of what do you need to do to do what you described? There has to be an infrastructure layer that actually enables it. So when you think about the scale of data we're dealing with that's one thing that we're innovating around. Then the issue is how do you allow multiple applications to simultaneously access and update and transform that? Those are all problems that need to be solved in the infrastructure to enable things like AI, right? And so where we come into play is creating that infrastructure layer that actually makes that possible. The other thing I talked about briefly in the Q and A was, well think about the problem of the future where the data set is just too large to actually move it in a substantive way to the compute. We actually have to invert that model over time architecturally and bring the compute to the data. Because it becomes too complicated and too expensive to continue to move from sort of the storage layer up to compute and back. That is a complex operation. That's why those sort of three pillars of technology are so important. And you've talked, and we're seeing it in cloud, right? Because it's this continuing kind of optimization atomic, not automatic, but making these more atomic, right? Smaller units, that cloud is really popular, right? So you need a lot, you need a little, right? Really by having smaller bits and bytes, it makes that much more easy. But another concept you've delved into a little bit is fast data versus big data. And clearly, you know, flash has been the bright shiny object for the last couple years and you guys play in that market as well. But it is two very different ways to think of the data. And I thought the other statistic that was shared is that, you know, the amount of data coming off machines and people dwarfs the business data, which has been the driver of IT spin for the last, you know, several decades. Yeah, no, that's right. And sort of that sort of, you know, you think about that and the best analogy is sort of the broader definition of IoT, right? Where you've got all of these sensors, whether it be a camera sensor, because that's just a sensor, right? Creating an image or a video, or if it's more industrialized, so you've got all these sources of data and they're going to proliferate at an exponential rate and our ability to aggregate that in some sort of an organized way and then act upon it. Again, let's use the autonomous car as the example. So you have all these sensors that are in constant motion. You've got to be able to aggregate the data and then make decisions on it at the edge, right? So that's not something you can't deal with the latency up to the cloud if it's an automobile and it needs to make an instantaneous decision. So you got to create that capability locally. And so when you think about the evolution of all this, it's really the integration of the cloud, which as Janet talked about, is the ability to tap into all this historical and legacy data to help inform a decision. But then there's things happening out at the edge that are real-time. And you have to have the capability to ingest the content, make a decision on it very quickly and then act on it. Here's a great example. We went to the autonomous vehicle, just navigation for autonomous vehicles. It's own subset. I think Goldman Sachs said it's a $7 billion industry in the not too distant future. And the great example is this combination of the big data and the wide data is when they actually are working on the road. So you've got maps that tell you and are updated kind of what the road looks like, but on Tuesday, they were shifting the lane and that particular lane now has cones in it. So this combination of the two is such a powerful thing. That's right. But I wanted to dive into another topic you talked about which is really architecting for the future. Unlike oil, data doesn't get consumed and is no longer available. It's a reusable asset. And you talked about classic stove topping of data within an application-centric world where now you want that data available for multiple applications. So a very different architecture to be able to use it across many fronts, some of which you don't even know yet. That's right. Well, I think that's a key point. So one of the things when we talk to CEOs, I should say, what they're realizing, to the extent you can enable a cost-effective mechanism for me to store and keep everything, I don't know how I'll drive value from it sometime in the future because as applications evolve, we're finding new insights into what can help drive decisions or innovation or take it to healthcare, some sort of innovation that cures disease. So that's one of the things that everybody wants to do. I want to be able to aggregate everything. If I can do that cost-effectively enough, I'll find a way to get value out of it over time. And that's something where when we think about big data and what we talked about today, that's central to that idea and enabling it. Right. And digital transformation, right, all the hot buzzwords. But we hear time and time again, such a big piece of that is giving the democratization, democratization of the data, so more people have access to it, democratization of the tools to manipulate that data, not just the mahogany row, super smart people, and then to have a culture that lets people actually try, experiment, feel fast. And there's a lot of innovation that'd be unlocked right within your four walls that probably you're not being tapped into. Well, that's right. That's something that innovation and then innovation culture is something that we're working hard at, right? So if you think about Western Digital, you might think of us as, you know, legacy Western Digital is sort of a, you know, fast-following, very operational centric company. We're still good at those things. Right. But over the last five years, we've really pushed this notion of innovation and really sort of pressing in to becoming more influential in those future architectures. That drives a culture that, you know, if we think about the technical community, if we create the right sort of mix of opportunity, appetite for some risk, that allows the best creativity to come out of our technical, technical community to innovate along these lines. Right. I'll give you the last word. Sure. I can't believe we're going to turn the calendar here on 2017, which is a little scary. As you look forward to 2018, what are some of your top priorities? What are you going to be working on as we come into the new calendar? Yeah, so as we look into 2018 and beyond, we really want to drive this continued architectural shift. You'll see us be very active. And I think you talked about it. You'll see us getting increasingly active in sort of this democratization. So we're going to have to figure out how we engage the broader open source development where whether it be hardware or software, we agree with that mantra. We will support that. Obviously we can do unique development, but with some hooks and keys that we can drive a broader ecosystem movement. So that's something that's sort of central to us. And one last word would be, one of the things that Martin Fink has talked about, which is really part of our plans as we go into the new year, is really this inverting the model, where we want to continue to drive an architecture that brings compute to the storage and enables some things that just can't be done today. All right, well, Mike Cardano, thanks for taking a few minutes and congratulations on a terrific event. Thank you, appreciate it. He's Mike Cardano, I'm Jeff Frick. You're watching theCUBE. We're at Western Digital, the headquarters in San Jose, Albany Campus. This is the story, check it out. Thanks for watching.