 Live from the BuildGram Auditorium in San Francisco, it's theCUBE, covering Pure Storage Accelerate 2018. Brought to you by Pure Storage. Welcome back to Pure, Pure Storage Accelerate 2018. I'm Lisa Martin with theCUBE. I'm with Dave Vellante. We are here in San Francisco at the BuildGram Civic Auditorium, which is why we're sporting some concert t-shirts. Who? The Who and the Clong. Roja. Roja Deltry. Roja, we are here with the CIO of the David Geffen School of Medicine at UCLA. Pure customer, Ben Nathan. Ben, welcome to theCUBE. Thanks for having me. So talk to us about the School of Medicine at UCLA. You are the CIO there. You've been there for about three years. Give us a little bit of the kind of a 10,000 foot view of what your organization looks like to support the School of Medicine. Sure. We're about 170 people. We have changed a lot over the last three years. When I got to UCLA, there was kind of 25 separate IT organizations, all smaller groups operating in each individual department. And they had built their own sets of managed infrastructure distributed throughout, you know, every sort of closet and cranny, nook and cranny in the school. And so we've consolidated all of that under, you know, one set of service lines, one organization, and that's included consolidating all the systems and applications as well. So we've brought all those together and now we're additionally running IT for three more health sciences schools at UCLA, nursing, dentistry, and the school of public health, building school of public health. Like a lot of CIOs, you serve many masters. You've got the administration, you've got the students, you've got the broader constituency, the community, UCLA, where do you start? What's the quote-unquote customer experience that you're trying to achieve? That's a great way to put it. There's really sort of four pillars that we try to serve, the patient being first and foremost. So for us, everything is built around a great patient experience. And that means that when we're educating students, it's so they can be great providers of patient care. When we're doing research, we're doing that research in the effort to eradicate disease, et cetera. And when we're doing community outreach, it's also around improving health and people's lives. So in IT, we try to stay very connected to those missions and I think it's a large part of what drives people to be part of an organization that's healthcare or that's a provider. That mission is really, really important. So yes, we're serving all four of those things at once. So you had lots of silos, lots of data that's only continuing to grow, but this is data that literally life and death decisions can be made on this. Talk to us about the volumes of data, all of the different sources that are generating data, people, sensors, things, and how did you make this decision to consolidate leveraging peer storage as part of that foundation? Yeah, there's an incredible amount of work going on at UCLA, particularly in the research, education, and patient care spaces. We had every brand of server and storage that you've never heard of, things bought at sort of just sort of lowest, bitter methods, but the technical debt that we had incurred as part of that was enormous, right? It's unsustainable, it's unsupportable, it's insecure-able. So when I got there and we started to think about how do we deal with all of this, we knew we had an opportunity to sort of green field an infrastructure and consolidate everything onto it. That was the first, that was what started us down the road that led us to Pure as one of our major storage vendors. I had worked with them before, but they won on their merits, right? We do these very rigorous RFP processes when we buy things. The thing that really, I think, got them the victory with us is that the deduplication of data got us to something like an eight to one ratio of virtual to physical. So we get a lot of virtual servers running on relatively small amount of storage and that it's encrypted sort of all the time, right? It's not like a switch you might flip or something a vendor says they'll do, but it doesn't really do, it is always on and it's critical for us. We were really building a far more secure and manageable set of services and so all the vendors we work with to kind of meet that criteria. So as a CIO, I would imagine you don't want to wake up every day and think about storage. With all due respect to our friends at Pure. That is true. So how has bringing an infrastructure in like Pure that prides itself on simplicity allowed you to do the things that you really want to do and need to do for your organization? Yeah, I'll give you a two part answer. I mean, one is simply like, I think it's operationally a really great service. I think that it's well designed and run and managed and we get great use out of it. I think the thing that makes it so that I don't have to think about it is actually the business model that they have. So the fact that I know that it's not going to really obsolete on its own, you know, that you get to, as long as you're like in the support model, you're upgrading the system every few years, changes, you know, the model for me because I don't have to think about these new massive capitalization efforts. It's more of a predictable operational cost and that helps me sleep, you know, well because I know what we look like over the next few years and I can explain that to my financial organization. Just a follow up on that. A large incumbent storage supplier or a system vendor might say, well we can make that transparent to you. We can use our financial services arm to hide that complexity or make a cloud like rental experience or do play financial games to hide that. Why does that not suffice for you? Well, I mean I think first and foremost we sort of want to run our financials on our own and we're pretty anxious about having anyone else in the middle of all that. And then number two is it seems to me different in terms of Pure having built that model from the ground up as part of their service offering. So I don't think we see that with too many other vendors and I think that obviously there's far less technical debt than what I had in the previous design but it still can add up if you're not careful about whatever, what server mechanism you have in place, et cetera. But it eliminates the forklift upgrade. Even with those financial incentives or tricks, you still got to forklift it and it's a disruption to your operations. And I'm sure that's true, yeah. So when you guys were back one year and a half or so, maybe two years ago, looking at this consolidation, where were your thoughts in terms of beyond consolidation and looking at being able to harness the power of AI, for example, we've heard a lot about AI today already and this need for legacy infrastructures are insufficient to support that. Was that also part of your plan was not simply to consolidate and bring your VMware environment onto Pure Storage but also to leverage a modern platform that could allow you to harness the power of AI? Yeah, that was sort of the later phase bonus period that we're starting to enter now. So after we sort of consolidate and secure everything, now we can actually do far more interesting things that would have been much more difficult before. And in terms of Pure, I think when we had set out to do this, we imagined doing a lot of our analytics and AI machine learning kind of cloud only and we tried that, we're doing a lot of really great things in the cloud but not all of it makes sense in that environment, either from a cost perspective or from a capabilities perspective. So particularly with what Pure has been announcing lately, I think there's a really good opportunity for us to build high performance computing clusters in our on-premise environment that leveraged Pure as a potential storage back end. And that's where our really interesting data goes. So we can do the analytics or the AI machine learning on the data that's in our electronic medical record or in our genomics workflows or things like that can all flow through a service like that and there's some interesting discoveries that ought to come from it. Ben, there's a lot of talk at this event about artificial intelligence, machine intelligence. How do you see AI in healthcare generally and specifically how you're going to apply it? Is it helping doctors with diagnoses? Is it maybe maintaining better compliance or? I think there's two things that I can think of off the top of my head. The first is decision support. So this is helping physicians when they're working directly with patients. There's only, there's so many systems, so many data sets, so many ways to analyze and yet getting it all in front of them in some kind of real-time way so that they can use it effectively as tricky. So AI, machine learning have a chance to help us funnel that into something that's immediately useful in the moment. And then the other thing that we're seeing is that most of the research on genomics and the outcomes that have resulted in changes to clinical care are around individualized mutations in a single nucleotide. So those are, I guess, quote, relatively easy for a researcher to pick out. There's a letter here that is normally a different letter. But there are other scenarios where there's not a direct easy tie from a single mutation to an outcome. So in autism or diabetes, we're not sure what the genetic components are, but we think that with AI and machine learning, those things will start to identify patterns in genomic sequences that humans aren't finding with their typical approaches. And so we're really excited to see our genomic platforms built up to the point where they have enough sequences in them to do that sort of analysis. And you need big compute, fast storage to do that kind of thing. How is it going to help the big compute, the fast storage, this modern infrastructure help, whether it's genomics or clinicians, be able to sort through massive amounts of data to try to find those needles in the haystack? Because I think the stat this morning that Charlie G. and Carla mentioned was that half a percent of data in the world is analyzed. So how is that under the hood infrastructure going to help facilitate your smart folks getting those needles in the haystack to start really making big impacts? UCLA has incredible faculty, like brilliant, brilliant researchers. And sometimes what I've found since I've gotten there, the only ingredient that's missing is the platform where they can do some of this stuff. So some of them are incredibly enterprising. They've built their own platforms for their own analysis. Others we work with, they have a lot of data sets. They don't have a place to put them where they can properly interrelate them and apply their algorithms at scale. So we've run into people that are trying to do these massive analyses on like a laptop or a little computer or whatever. And it just fails, right? Or it runs forever. So giving them, you know, providing a way to have the infrastructure that they can run these things is really the ingredient that we're trying to add. And so that's, you know, about storage and compute, et cetera. How do you see the role of the CIO evolving? We hear a lot of people on theCUBE and in these conferences talk about digital, digital transformation, the digital CIO. How much of that is permeating your organization and what do you think it means to the CIO role going forward? Yeah, I wish I knew the real answer to that question. I don't know, time will tell. But I think that certainly we're trying to follow the trends that we see more broadly, which is that, you know, there's a job of keeping the lights on of operations. And like, you're not really, you shouldn't have a seat at any other table until those things are quite excellent. Table stakes. Yeah, right, exactly, table stakes, security, all that stuff. Once you've got that, you know, my belief is like you need to deeply understand the business and find your way into helping to solve problems for it. And so, you know, in our realm, a lot of that these days is, how do we sort of understand the student journey from prior to, you know, from when they maybe want to apply all the way so when they go out and become a resident and then a physician, there's a ton of data that's gathered along that way. And, you know, but we get asked a lot of questions. We don't have easy answers to, but if we put the data together properly, we start to, right? On the research side, you know, same sort of idea, right? Where the more we know about the particular like clinical outcomes they're trying to achieve or even just basic science research that they're looking into, the better that we can kind of micro-target a solution to them or so, whether it's an on-prem like private cloud or public cloud, either one of those can be harnessed for like really specific workloads. And I think when we start to do that, we've enabled our faculty to do things that, you know, it's been tougher for them to do before. So, once we, yeah, understand the business in those ways, I think we really start to have, you know, an impact at the strategic level of the organization, you know? So, you've got this centralized services model that was a strategic initiative that you put in place. You've got the foundation there that's going to allow you to start opening up other opportunities. I'm curious, in the UCLA system, maybe the UC system, are there other organizations or schools that are looking at what you're doing as a model to maybe replicate across the system? I think there's, I don't know about a model. I think there's certainly efforts among some to find, to centralize at least some services because of economies of scale or security or, you know, all the normal things. With the anticipated, and then anticipating that that could like ultimately provide more value once the sort of baseline stuff is out of the way. You see it's, you know, vast and varied system. So, there's a lot of amazing things going on in different realms. I think doing more than ever working together and trying to find common solutions to problems. So, we'll see whose model, you know, works out. Well, Ben, thanks so much for stopping by theCUBE and sharing the impact that you're making at the UCLA School of Medicine, leveraging storage and all the different capabilities that that is generating. We thank you for your time. Thanks so much for having me. We want to thank you for watching theCUBE. I'm Lisa Martin with Dave Vellante. We are live at Pure Accelerate 2018 and San Francisco, stick around. We'll be right back with our next guest.