why from Las Vegas it's the cube covering informatica world 2018 bacio by inform Attica hey welcome back it runs the cubes exclusive coverage of informatica world 2018 we're here at the Venetian in Las Vegas live I'm John for your co-host with Peterborough's coasting and head of analyst said we keep on insulating all the cube our next guest is jammed the dalla who's the enterprise analytics architecture engineer sire pharmaceutical and some named director of the enterprise analytic solutions lead at sire as well great to have you guys thanks for joining us thank you so love getting the practitioner view of kind of the reality right of what's going on off see dramatic has their show you guys are a customer you're looking at some of their products take a minute first to talk about what you guys do first see Pharma got some stuff going on Davies involved privacy's involves you're in Europe in the u.s. GDP ours here think I'm gonna talk about what you guys do sure so char Pharmaceuticals is a global leader in rare diseases so there's about 350 million patients who are effective remedies is today and so art group with NIT enterprise analytics so we're focused on making sure we bring the right technologies and capabilities around bi and analytics to the organization so we look at products tools figure out how they fit into our our ecosystem of bi stack of tools and make that available to our RIT colleagues as well as our business colleagues so rare disease can you just explain kind of categorically what that is cuz I'm assuming this fits rare is not a lot of data on it or there's data you got to figure out what is that how do you guys categorize that so rare disease you know majority the rare disease affected by affected children so that's a kind of a critical aspect of what we do you know rare disease could be in immunology it could be in oncology GI I mean there's very disease typically you know people who are affected affected probably less than a thousand or 2,000 I think one of our drugs the population is around 5,000 people and these are chronic diseases typically their chronic diseases so they're they're they're diseases that affect the quality of life of an individual so what you guys are doing is identifying what is it about the genealogy etc the genome associated with the disease but then providing treatments that will allow especially kids an opportunity to have live a better life over extensive time yeah and what do you guys do there in terms the data side can you explain what your roles are yeah so like I said we're you're in the enterprise analytics so we're focused on bringing technologies and capabilities around bi and analytics spaces so how do we bring data in and ingest it how do we curate the data how do we do if data visualizations how do we do data discovery advanced analytics so all of those kind of capabilities and we're responsible for so what's your architecture today you have some on premises their cloud involved you just kind of lay out kind of the environment as much as you can share I know maybe some confidential information but for the most part what's the current landscape internally for you guys what are you dealing with the data sure so we fill out a new a new next generation analytics we called it our marketplace or the analytics marketplace we're leveraging both on Prem as well as cloud technologies so we're leveraging Microsoft Azure hdinsight for Hadoop the Big Data technologies as well as informatica for data ingestion and bringing data and transform or transforming yet but there are many tools involved in that one so it's like the whole ecosystem we call does marketplace which is backbone for shared enterprise analytics strategy and future you guys put a policy around what tools people can bring to work so to speak and we're seeing a proliferation of tools there's a tool vendor everywhere we look around the big data it's right I got a tool for this I got a tool for wrangling I've seen everything how do you guys deal with that onslaught of tools coming in do you guys look at it more from a platform respective how are you guys handling that right so look at a platform perspective and we try to bring tools in and make that a standard within the organization we look at you know the security is it enterprise grade technology and yeah it's a challenge I mean they're basically certified you kick the tires give it a pace test through its paces and then we have our own operations team so we can support that that tool set the platform itself so and what are your customers do with the data they doing self service or they data scientists are they like just business analysts what's the profile of the users of your customers of your we have all set of users they have like a technical folks which they want to use the data like traditional ETL reality so there are folks from the business they want to do like self-serve and unless they want to do analysis on the data so we have all the capabilities in our marketplace so some tools enable those guys to get the data for the selves or like the tools we have and dalibor does their own stuff like the eld talk a little bit about the one of the key challenges associated with pharmaceuticals especially in the types of rare disease chronic young people types of things that you guys are mainly focused on a big challenge has always been that people when they start taking a drug that can significantly improve their lives they start to feel better and when they start to feel better they stop taking it so how are you using big data to or using analytics to identify people help describe potential treatments for them help keep them on the regimen how do you do are you first of all are you doing those things and as you do it how are you ensuring that you are compliant with basic ethical and privacy laws and what types of tools are you using to do that it's a big question yeah yeah so we are doing some of that you know we have looked at things around persistence and adherence and understanding kind of you know what what combination of drugs may work best for certain individuals or groups of people yeah and definitely you know some compliance is a big factor in that so when I'm working close with a compliance group understanding how we're allowed to use that data in between which parts of the organization do you anticipate that you'll have a direct relationship as some of these customers or is there an optimist in other words does analytics provide you an opportunity to start to alter the way that you engage the core users of your products and services like I believe so you know I think one thing that we're looking at which strategic standpoint is um how do we diagnose people sooner a lot of these chronic diseases you know they go through 2-3 years of undiagnosed so they'll jump around from you know doctor a doctor if I understand what you know what the issue is so I think one thing we're looking at is how do we use data and AI to to more quickly be able to diagnose patients has a 360 view helped you guys of data you guys have a 360 view how do you cuz we'll look at that in terms of a channel selling a product and serving because we have a different perspective what's the 360 view benefit that you guys are getting yeah so we have a kind of a customer care model which is kind of a 360 for our customer so understanding you know around just drug manufacturing to making sure they have the right you know they have the right supply to understand is it working for the patient's so we've always been talking about the role a big day you mentioned had to do that Hadoop supposed to be this whole industry now it's a feature of data right so there's a variety of you know infrastructure as a service platform as a service some say I pass and Big Data how are you guys looking at that as as as builders of IT next-generation IT the role of I pass and Big Data we see it as a role in a blur you know I think what cloud brings us in the past type solutions is agility you know we as the market is so evolving so quickly and there's new versions of new software coming out so quickly that you wanna be able to embrace that and leverage that give it benefit of like give it some sort of a comparison old way versus a cloud like is there been some immediate benefits that just pop out yeah that a lot more benefits with doing the world way and the cloud way because with the cloud that brings a lot more scalability in in all India's to get like 10 servers you need to work with the infrastructure team I get it like it takes three months or two months again it with the cloud based one you've worked out you can scale up or scale down so that's one thing because it's so you're talking about Big Data yeah you're getting the volume of data you're getting you need to scale up your storage or your any compute you either JMS and compute bring data to the table and then you gotta have the custom tooling for the visualization yeah how that kind of together right you talk about them from your perspective the balance that you have to have guys have to deal with every day like you got to deal with the current situation NIT you got cloud you got an electrical customers personas of people using the product but you got to stay in the cutting edge it's like what's next cuz we going down the cloud road you're looking at containers kubernetes service meshes you need a lot more stuff coming down the pike if you will coming down the road for you guys how are you guys looking at that and how are you managing it you have some greenfield projects do you do a little you know Rd you integrated in how are you dealing with this new cloud native set of technologies yeah definitely a balancing act you know I think we do a lot of pocs and we actually work with our business and IT counterparts to see hey if there's a new use case that is coming down you know how do we solve that use case with some of the newer technologies and we try a POC may bring in a product to just see if it works and then see how do we then do we then take that to the enterprise so I got one final question for you guys and maybe you do as well John but but in life and death businesses like pharmaceuticals is a life and death business the quality of the data is really really important getting it wrong has major implications the fidelity of the system is really crucial you say using informatica for for example ingest and other types of services how has that choice made the business feel more certain about the quality of their data that you're using in your analytic systems into standardization so you know if between MDM round mastering our data - ingesting data transforming our data just having that data lineage having that standard around how that data gets transformed is that fundamentally a feature of the services that you're providing is you not only were you you know the ability to do visualization on data but actually providing your scientists and your businesspeople and your legal staff explicit knowledge about where this data came from and how trustworthy it is and whether they should be making these kind of free complex very real hardcore human level decisions on is that is that all helping yes because it seems like it would be a really crucial determination of what tools you guys would use right it is yeah and absolutely I think also as we move more towards self-service and having these people having data scientists do their things on their own being able to have the tools that can do that kind of audit and data lineage is crucial great to have you guys on we had a wrap I want to ask one more question here you guys were an innovation award e informática congratulations any advice for your peers out there want to unleash the power data and be on the cutting edge and potentially be an honoree yeah I would say just definitely think outside the box seem to try new things try puce you know do POCs is there so much new technologies coming down so quickly that it's hard to keep up Jam cuz it's like a moving target you need to chase your movie target and based on B was it that gets you like what you want it to do you know siding yeah get out front don't keep your eye on the prize yeah focus on task at hand bring in the new technologies guys thanks so much for coming on great to hear the practitioners reality from the trenches certainly front lines you know life-or-death situations of quality of the data matter scaling is important cloud era of data I'm John for a Peterborough's more live coverage after the short break

>> Announcer: From Austin, Texas, it's theCUBE, covering Pure Storage Accelerate 2019, brought to you by Pure Storage. (air whooshes) >> Welcome to theCUBE's day two coverage of Pure Accelerate 2019 from Austin, Texas. I am Lisa Martin, Dave Vellante is my co-host, and we're pleased to welcome back to theCUBE, here is VP of Strategy Matt Kixmoeller. Kix, welcome back! >> Thank you very much, happy to be here. >> This has been a, being shot out of a cannon. Yesterday and today, lots of news. First of all, happy 10th anniversary to you and Pure. >> Thank you very much, yeah. >> Tremendous amount of innovation, as Tara Lee said yesterday, overnight in 10 years. (laughs) >> It's a really fun time at Pure. Just something about the nostalgia of 10 years gets people, naturally, to start thinking about what the next 10 years are about. And so, there's just a lot of that spirit right now at the company, so it's almost like people are really charging into the second chapter with a lot of energy, so that's cool. >> A lot of energy, I think, all fueled by this massive sea of orange that has descended on Austin. >> Absolutely. >> So, four announcements yesterday. Let's start with Cloud Block Store, what you guys are doing with AWS, and kind of this vision of Pure's cloud strategy. >> Yeah, look, the cloud discussions I've had with customers here at the show have been awesome. And I think more than anything, people have realized that we've really built something very unique with Cloud Block Store, something that doesn't exist anywhere else in the industry right now. And, you know, if you look at kind of other storage vendors over the time, people have certainly taken their storage OSes and put them in the cloud kind of as a test-dev experiment, a way to try things out, but never really thinking, "I want to build something "that runs tier-one applications." And that was our goal from day one. We looked at the Amazon platform and said, they really built EBS, their block offering, as kind of a way to beat boot VMs, but it was really never meant for a way to run mission-critical applications. So they've been very open in partnering with us to say, look, let's bring this capability onto the platform. And we really rearchitected our Purity Operating Environment, and so, the whole lower half of that is really optimized for the AWS services to help customers move tier-one apps to the cloud. >> Was that joint engineering, or was it really mostly Pure doing that work? >> You know, it was Pure engineering in the sense that we wrote the code, but there was a lot of co-architecture work with AWS so we could fundamentally understand the basics of all of their services and how to optimize for it. And one of the big realizations and choices that came out of that was not to base the storage layer of this on EBS, but instead to base it on S3. And if you look at your average cloud customer, they really use S3 as the storage basis for the apps they build on Amazon, and so, S3 is the 11-nines durable storage platform there. And so our whole goal here was, how do you use S3, but still deliver the level of performance you'd expect out of a tier-one block environment? >> Well, when you read the sort of cloud storage press release du jour, you can't really get into the nuance, but if I understand it correctly, you guys essentially have architected, using AWS services, a new class of block storage that runs on AWS, but looks like Pure. >> That's exactly it. >> So you're essentially front-ending cheap S3 storage with high-priority EC2s, you've got some mirroring for rights to give it high availability, and again, it looks like Pure. >> Kix: Yep. >> So you win, 'cause you're making money on the software, (laughs) AWS is selling services, and the customer has a Pure experience. Did we get that right? >> Yeah, and I think the combination, the one-two punch, that's been very interesting for customers is not only what we're doing with Cloud Block Store, but the new Pure as-a-Service offering. And so, Pure as-a-Service is our as-a-service consumption mechanism that allows you to essentially subscribe to or rent Pure arrays from Pure in your data center, but it's a license that can go between on-prem and cloud. And so, imagine you're a customer that is mostly on-prem today, but you have that mandate, "I've got to get to the cloud." You might need more storage, but the last thing you want to do is commit to another three- or five-year purchase of a storage array that just puts off that cloud journey that much longer. So a customer can subscribe to Pure as-a-Service, they'll maybe subscribe to 100 terabytes, and we put an array in their data center right now, but a year from now, they decide they're going to move 50 terabytes to Cloud Block Store in Amazon, that's just a transparent movement, they're already licensed for it. And so that-- >> And there's already, oh, sorry, sorry. >> Kix: No, go ahead. >> There's already customers that are in beta with Cloud Block Store, is that correct? >> Correct, yeah. >> Lisa: Any interesting insights that you can share without giving away secret sauce? >> Oh, absolutely. You know, I think the thing that pleased us the most about the beta was really the divergence of use cases. You know, we created this, but there's always, you create something, and you don't know what people are going to do with it, right? And so, we have this goal of going after tier-one apps. Obviously, there's a lot of people that are just focused on migration, "How do I get the tier-one app from on-prem to cloud?" And so that was what I would say would be the dominant use case. But there were a lot of interested in test-dev type use cases. And really interesting, I think we saw it in both directions. So we saw some customers who wanted to develop their app in the cloud, but then deploy on-prem. We saw the opposite, we saw people that wanted to develop on-prem but then deploy in the scalable infrastructure in the cloud. And so I thought that was quite interesting. >> How much of the impetus to do that offering was hardcore customer demand, "We need this," versus, "Hey, we need to embrace the cloud "and make it a tailwind and not be defensive about it"? >> You know, I think when we looked at what was going to be the buy-in criteria for the storage array of tomorrow, fundamentally, this is it, right? People want on-prem infrastructure that's connected to the cloud and provides them a roadmap or a bridge to the cloud. And I think we've seen a big change in mindset over even the last couple years. I'd say two or three years ago, the mindset from customers was, "I'm all in on cloud." I think we've seen that soften, where they've realized that the cloud is not a panacea, it's usually actually not cheaper or faster, but it is more agile, it is more flexible, and so, a combination of on-prem and cloud is the right answer. And so, what does that mean from a storage platform? Storage is the hard part. And so, I then need a storage architecture that can support both on-prem and cloud and drive commonality, as opposed to having it be totally different architecture. >> Was Outposts at all a catalyst in your thinking on this, or was this happening way before you even saw that? >> No, we started this effort before that, but I think Outposts is a good example, I believe, of how Amazon is just getting serious about saying, look, we can't ask everybody to rearchitect every application for web scale. There are certain apps that it won't make sense to rearchitect. How do we bring those to the cloud in an efficient way? And those are really the types of applications and the first-generation Cloud Block Store is perfect for. You connect your existing on-prem app, move it to the cloud without changing it, and then maybe slowly you rearchitect parts of the application, you evolve it over time, but that's not a gate to going to the cloud anymore. >> I like the way you said it, you thought about what storage is going to look like in the next 10 years. And we've said this a lot, it's the cloud experience, bringing that cloud experience to your data is what storage is going to look like, you know, wherever it lives, is going to look like in the next 10 years. >> Absolutely, and I think the other real mindset shift I think we've seen is how people are thinking about truly running their on-prem environment more like a service. You know, if you look at, the key message that we had at the show here was really the Modern Data Experience, and defining for customers what that meant. And in a lot of ways, I've been in the storage industry for a little while, I think back, 20 years ago, the buzzword was utility storage. I think one of our competitors had that as their slogan sometime in the '90s. >> Yeah, right. >> And the reality, though, is when you talk to most storage teams, they just never did that. They still ran a bunch of arrays on a project-by-project basis, and it didn't look at all like the cloud. And so, now people have learned the lessons from the public cloud and said, "We really need to apply those on-prem "to truly bring our infrastructure together "into much more of a virtual pool, "truly deliver it on demand, abstract consumption "from the back-end infrastructure to give flexibility." And so, that's really what we're trying to deliver with the Modern Storage Experience, is to say, look, let's get out of the world of array-by-array management. If a customer buys 50 or 100 of our arrays, how do they take that pool of arrays and turn it into a block service, turn it into a file service, turn it into an object service for their customers, with real abstractions and real APIs for those services that have nothing to do with the back-end infrastructure? >> Dave: Mm-hm. >> When Charlie talked yesterday, Kix, about the Modern Data Experience, the three S's pop up. >> Kix: Yeah. (clears throat) >> Simple, seamless, sustainable. But as IT is getting more and more complex, and customers are in a multi-cloud environment, not necessarily from a strategic perspective, right, acquisition, et cetera, how does Pure actually take that word, simple, from a marketing concept into reality for your customers? >> Yeah, you know, I think simple is the most underappreciated but biggest differentiator (coughs) that Pure has. I was recalling for someone, you talked to Coz earlier today. I had a conversation about three weeks into the existence of Pure, (coughs) excuse me, with Coz, and we were just debating, I mean, this is before we wrote any code at all, about, what would be Pure's long-term differentiator? And I was kind of like, "Ah, we'll be the flash people, or high-performance, or whatever," and he's like, "No, no, no, we're going to be simple. "We are going to deliver a culture that drives "simplicity into our products, "and that'll be game-changing." And I thought he was a little crazy at the time, but he's absolutely turned out to be right. And if you look over the years, that started with just an appliance experience, a 10-card install, just a really easy environment. But that's manifested itself into every product we create. And it's really hard to reverse-engineer that. It's an engineering discipline thing that you have to build into the DNA of the company. >> Yeah, he kind of shared that with us, Lisa. He was basically, my words, saying, you don't ever want to suboptimize simple to get a little knob turn on performance, because you'll be turning knobs your entire career. There's a lot of storage arrays out there that, it's all about turning the knobs. >> Kix: Yeah, well-- >> If you can't fix it, you feature it. >> Oh, and if you think about really trying to automate something, it's really hard to automate complex stuff. If something's simple, if it's consistent, it plugs into an automation framework. >> You talked about "get your 10X"-- >> Kix: Yeah. >> I think, is that what you said? And an entrepreneur who was very successful once told me, "I look for two things, a large market and a 10X impact." >> Yep. >> So, what is your 10X? >> You know, we have two 10Xs at the show this year. So first was really kind of a 10-year jump in performance. When we first entered, people were used to 10-millisecond latency from disk, and we introduced them to one-millisecond latency. Now, with the shipping in direct memory and bringing SCM into the architecture, we can do 100 microseconds. That's another 10X. And so, it's hard to ignore that. >> Lisa: That's game-changing, as you said yesterday. >> (coughs) Exactly. The other is really around our next product, FlashArray C, which brings flash to tier-two data. And there, it's all about consolidation. Most people have not used flash to fix tier one, but their biggest problem now is tier two. They have less-important applications, but because they haven't optimized that, it's taking up way too much of IT time. And so, FlashArray C is, "How do I go "and basically consolidate 10X consolidation "at that tier-two level to really bring "sanity to tier-two storage?" >> And you've got NAM pricing, we talked to Charlie about this, that it ultimately should be a tailwind for you guys as NAM pricing comes down, as NOR fab capacity's coming online in China to go after the thumb drives, right, so that's going to leave the enterprise for all the traditional flash guys that we know and love. So that should open up new markets for you. Today, if you look at pricing for flash C class storage, if I got it right, I'm guessing $1, $1.50 a gigabyte. You see hybrid still at probably half that, 65, 70 cents. Do you see that compressing over the next, let's call it 18, 24 months? >> Absolutely, I mean, what we can do with this product is really bring out flash at disk prices. And so, if you think about the difference, I mean, what we now have in the product line is two platforms, FlashArray X, optimized for performance, at hundreds of microseconds of latency, but C, at a little bit slower performance, still in the millisecond range, can really get down now to those disk prices you just mentioned. And so, it fundamentally gives customers the chance to ask, "Can I really now eliminate disk from the data center?" You know, as I said in my keynote, that the slogan from Pure from day one has been "the all-flash data center." And 10 years ago, people didn't believe it. We were maybe leaning over our skis a little bit in doing that. It now really feels possible to go and have the all-flash data center. >> Well, I'll tell you, we believed it. David Floyer picked up on it early on, and he was-- >> Kix: Yeah. >> He was actually probably too aggressive with (laughs) his forecast. We missed the NAND supply constraints. >> Kix: Yeah. >> But now that seems to be loosening up. >> Well, and, look, one of the things that really helps us build the perfect product around QLC is the work we've done to integrate with raw flash. We cannot just use QLC, but we can use it really efficiently, and the challenge there is to make it reliable. It's inherently a less-reliable flash. And so, that's what we're good at, taking things that are less reliable and making them enterprise-grade. >> And your custom flash modules allow that? >> Yeah. >> Can you add some color to that? >> Basically, what we do is we source raw NANDs, put it in our system, but then do all the work in software to manage the flash. And so, when you have a less-reliable flash medium like QLC, generally, what you have to do is add more flash to overprovision and be careful writing to it. And so, when do it globally, we don't do it inside every SSD, we can do it across the whole system, which makes the whole thing more efficient, thus allowing us to drive costs down even more. >> Hm. >> One of the things that we have heard over the last day and a half from customers, even those that were onstage yesterday, those that were on theCUBE yesterday and those that will come on today, is, they talk about the customer experience. They don't talk about FlashBlade, FlashArray, they're not talking about product names. They're talking about maybe workloads that they're running on there. But the interesting thing is, when we go to some other shows, you hear a lot of names of boxes. >> Kix: Yep. >> We haven't heard that. Talk to me a little bit about how Pure has evolved and really maybe even created this customer experience that's focused on simplicity, on outcomes, that is, in your perspective, why people aren't talking about the specific technologies-- >> Kix: Yeah. >> But rather, this single pane of glass that they have. >> Look, when we started the company, I obviously talked to a lot of customers, and I found, in general, there was frustration with products, but they also just generally didn't like their storage company. And so, from day one, we said, how do we reinvent the experience? Of course, we have to build a better product, and we can use flash as kind of an excuse to do that, but we also want to work on the business model of storage, and we also want to work on the customer experience, the support experience, the just 360 view of how you deal with a vendor. And so, from day one, we've been very disciplined about all of that. Going all-flash was a key part of the product. Evergreen has probably been our quintessential investment in just, how do you change that buying cycle? And so, you can buy into an experience and nondisrupt the way they evolve, versus replace your storage array every three to five years. And then, I think the overall customer experience just comes from the culture of the company, right? Everybody at Pure is centered on making customers happy, doing the right thing, being a vendor that you actually want to work with. And that's not something you can really legislate, that's not something you can put rules around, it's just the culture at Pure. >> When we talked about Evergreen yesterday with a number of customers, including Formula 1. I said, "You know, as a marketer, "how much of that nondisruptive operations, "take me from marketing to reality," and all of them articulated the exact value prop that you guys talk about. It was really remarkable. And another customer that we talked to, I think from a legal firm here in the U.S., didn't even do a POC, talked to a peer of his at another company that was a Pure fan-- >> Kix: Yep. >> And (snaps fingers) bought it right on the spot. So the validation that you're getting from the voice of the customer is pretty remarkable. >> Yeah, this is our number one asset, right? And I mean, so when we think about, how do we spread the religion of Pure, it's just all about giving voice to our customers, so they can share their stories. 'Cause that's so much more credible than anything we say, obviously, as a vendor. >> You're one of only two billion-dollar independent storage companies, which, we love independent storage companies, 'cause, you know, the competition's great. How far out do you look and do you think about being an independent storage company? You've seen, as a "somewhat" historian of the industry, you've seen TAM expansion, you guys are working hard on TAM expansion now, new workloads. You got backup stuff goin' on. You got the cloud as an opportunity, multi-cloud as an opportunity. So you got some runway there. >> Yeah. >> Beyond that, you've seen companies try to vertically integrate, buy backup software companies, you know, a converged infrastructure, whatever it is. How far out do you think about it from a business model standpoint? Or do you not worry about that? >> You know, look, to put it in context a little bit, you look at the latest IDC numbers, we're maybe one-third in to the transition to flash, right? The world still buys two-thirds disk, one-third flash. That's a huge opportunity. We're now five or six globally in storage. That's a few spots that we have to go, right? And so, we're not at all market-share limited, or opportunity limited, even within the storage industry, so we could make a much, much larger company. And so, that's mission number one at Pure. But when we think beyond that, that's just a launching point. And so, you've seen us do some stuff here at the show where we're getting into different types of storage. The first obvious expansion is, let's make sure anything that is a storage product comes from Pure, and there's obvious categories we don't play in today. You saw us introduce a new product around VM Analytics Pro, where we're reaching up the stack and adding real value at the VM tier, taking our Meta AI technology and using to give VM-level optimization recommendations. And so, yeah, I think we increasingly understand that IT's a full-stack game, and so storage is maybe the hardest part of the stack, and that gives us a great base to work from, but we don't constrain our engineers to say, you can only solve storage problems. >> Geography's another upside for you. I mean, most of your business, the vast majority of your business, is in the U.S., whereas you take a company like some of these other ones around here, more than half their business is outside the U.S, so. >> Yeah, no, our international businesses, we've been international five or six years now, and it felt like the first couple years are investment years, and it took time. But we're really starting to see them grow and take hold, and so, it's great to see the international business grow. And I think Pure as a company is also learning to really think internationally, not just because we want the opportunity, but the largest customers in the world that we now deal with have international operations, and they want to deal with one Pure globally. >> So when you're talking, and maybe this has even happened the last day and a half, with a prospective customer who is still investing a lot on-prem, still not yet gone the route of flash, as you were saying, those numbers speak for themselves. What do you say to them? >> If they're not on flash yet? >> Lisa: Yeah, yeah, to show them the benefits. I mean, what's that conversation like? >> It's rare, to be honest, now to find customers who haven't started with flash. But I think the biggest thing I try to encourage folks is that flash is not just about performance. And when I look at the history of people who have embraced Pure, they usually start with some performance need, but very quickly, they realize it's all about simplicity, it's all about efficiency. And if they can make storage fundamentally simpler and more efficient, they free up dollars to put towards innovation. And we unlock the ability to drive dollars towards innovation, and then we drive storage to the new innovation projects, like analytics, like AI, et cetera. And so, we just try to talk about that broader opportunity. And I think that's the hardest thing for people to grasp, because the IT history has always been lots of ROI pitches that say, "Hey, this thing costs a lot, but trust me, "you'll make it up in all these other benefits," that no one believes. And so, you just have to get them to taste it to begin with, and when they see it for themselves, that's when it clicks and they start to really understand the ROI around that. >> Well, congratulations on 10 years of Pure unlocking innovation, not just internally, but externally across the globe. We appreciate your time, Kix. >> Thank you, we're looking forward to the next 10 years. >> All right, to the next 10! For Dave Vellante, I'm Lisa Martin. You're watching theCUBE from Pure Accelerate 2019. (upbeat music)

>> Announcer: Live from the Bill Graham Auditorium in San Francisco, it's theCUBE! Covering Pure Storage Accelerate 2018 brought to you by Pure Storage. >> Welcome back to theCUBE's continuing coverage of Pure Storage Accelerate 2018, I'm Lisa Martin, sporting the clong and apparently this symbol actually has a name, the clong, I learned that in the last half an hour. I know, who knew? >> Really? >> Yes! Is that a C or a K? >> Is that a Prince orientation or, what is that? >> Yes, I'm formerly known as. >> Nice. >> Who of course played at this venue, as did Roger Daltry, and The Who. >> And I might have been staff for one of those shows. >> You could have been, yeah, could I show you to your seat? >> Maybe you're performing later. You might not even know this. We have a couple of guests joining us. We've got Matt Burr, the GM of FlashBlade, and Rob Ober, the Chief Platform Architect at NVIDIA. Guys, welcome to theCUBE. >> Hi. >> Thank you. >> Dave: Thanks for coming on. >> So, lots of excitement going on this morning. You guys announced Pure and NVIDIA just a couple of months ago, a partnership with AIRI. Talk to us about AIRI, what is it? How is it going to help organizations in any industry really democratize AI? >> Well, AIRI, so AIRI is something that we announced, the AIRI Mini today here at Accelerate 2018. AIRI was originally announced at the GTC, Global Technology Conference, for NVIDIA back in March, and what it is is, it essentially brings NVIDIA's DGX servers, connected with either Arista or Cisco switches down to the Pure Storage FlashBlade, so this is something that sits in less than half a rack in the data center, that replaces something that was probably 25 or 50 racks of compute and store, so, I think Rob and I like to talk about it as kind of a great leap forward in terms of compute potential. >> Absolutely, yeah. It's an AI supercomputer in a half rack. >> So one of the things that this morning, that we saw during the general session that Charlie talked about, and I think Matt (mumbles) kind of a really brief history of the last 10 to 20 years in storage, why is modern external storage essential for AI? >> Well, Rob, you want that one, or you want me to take it? Coming from the non storage guy, maybe? (both laugh) >> Go ahead. >> So, when you look at the structure of GPUs, and servers in general, we're talking about massively parallel compute, right? These are, we're now taking not just tens of thousands of cores but even more cores, and we're actually finding a path for them to communicate with storage that is also massively parallel. Storage has traditionally been something that's been kind of serial in nature. Legacy storage has always waited for the next operation to happen. You actually want to get things that are parallel so that you can have parallel processing, both at the compute tier, and parallel processing at the storage tier. But you need to have big network bandwidth, which was what Charlie was eluding to, when Charlie said-- >> Lisa: You like his stool? >> When Charlie was, one of his stools, or one of the legs of his stool, was talking about, 20 years ago we were still, or 10 years ago, we were at 10 gig networks, in merges of 100 gig networks has really made the data flow possible. >> So I wonder if we can unpack that. We talked a little bit to Rob Lee about this, the infrastructure for AI, and wonder if we can go deeper. So take the three legs of the stool, and you can imagine this massively parallel compute-storage-networking grid, if you will, one of our guys calls it uni-grid, not crazy about the name, but this idea of alternative processing, which is your business, really spanning this scaled out architecture, not trying to stuff as much function on a die as possible, really is taking hold, but what is the, how does that infrastructure for AI evolve from an architect's perspective? >> The overall infrastructure? I mean, it is incredibly data intensive. I mean a typical training set is terabytes, in the extreme it's petabytes, for a single run, and you will typically go through that data set again and again and again, in a training run, (mumbles) and so you have one massive set that needs to go to multiple compute engines, and the reason it's multiple compute engines is people are discovering that as they scale up the infrastructure, you actually, you get pretty much linear improvements, and you get a time to solution benefit. Some of the large data centers will run a training run for literally a month and if you start scaling it out, even in these incredibly powerful things, you can bring time to solution down, you can have meaningful results much more quickly. >> And you be a sensitive, sort of a practical application of that. Yeah there's a large hedge fund based in the U.K. called Man AHL. They're a system-based quantitative training firm, and what that means is, humans really aren't doing a lot of the training, machines are doing the vast majority if not all of the training. What the humans are doing is they're essentially quantitative analysts. The number of simulations that they can run is directly correlative to the number of trades that their machines can make. And so the more simulations you can make, the more trades you can make. The shorter your simulation time is, the more simulations that you can run. So we're talking about in a sort of a meta context, that concept applies to everything from retail and understanding, if you're a grocery store, what products are not on my shelves at a given time. In healthcare, discovering new forms of pathologies for cancer treatments. Financial services we touched on, but even broader, right down into manufacturing, right? Looking at, what are my defect rates on my lines, and if it used to take me a week to understand the efficiency of my assembly line, if I can get that down to four hours, and make adjustments in real time, that's more than just productivity, it's progress. >> Okay so, I wonder if we can talk about how you guys see AI emerging in the marketplace. You just gave an example. We were talking earlier again to Rob Lee about, it seems today to be applied and, in narrow use cases, and maybe that's going to be the norm, whether it's autonomous vehicles or facial recognition, natural language processing, how do you guys see that playing out? Whatever be, this kind of ubiquitous horizontal layer or do you think the adoption is going to remain along those sort of individual lines, if you will. >> At the extreme, like when you really look out at the future, let me start by saying that my background is processor architecture. I've worked in computer science, the whole thing is to understand problems, and create the platforms for those things. What really excited me and motivated me about AI deep learning is that it is changing computer science. It's just turning it on its head. And instead of explicitly programming, it's now implicitly programming, based on the data you feed it. And this changes everything and it can be applied to almost any use case. So I think that eventually it's going to be applied in almost any area that we use computing today. >> Dave: So another way of asking that question is how far can we take machine intelligence and your answer is pretty far, pretty far. So as processor architect, obviously this is very memory intensive, you're seeing, I was at the Micron financial analyst meeting earlier this week and listening to what they were saying about these emerging, you got T-RAM, and obviously you have Flash, people are excited about 3D cross-point, I heard it, somebody mentioned 3D cross-point on the stage today, what do you see there in terms of memory architectures and how they're evolving and what do you need as a systems architect? >> I need it all. (all talking at once) No, if I could build a GPU with more than a terabyte per second of bandwidth and more than a terabyte of capacity I could use it today. I can't build that, I can't build that yet. But I need, it's a different stool, I need teraflops, I need memory bandwidth, and I need memory capacity. And really we just push to the limit. Different types of neural nets, different types of problems, will stress different things. They'll stress the capacity, the bandwidth, or the actual compute. >> This makes the data warehousing problem seem trivial, but do you see, you know what I mean? Data warehousing, it was like always a chase, chasing the chips and snake swallowing a basketball I called it, but do you see a day that these problems are going to be solved, architecturally, it talks about, More's laws, moderating, or is this going to be this perpetual race that we're never going to get to the end of? >> So let me put things in perspective first. It's easy to forget that the big bang moment for AI and deep learning was the summer of 2012, so slightly less than six years ago. That's when Alex Ned get the seed and people went wow, this is a whole new approach, this is amazing. So a little less than six years in. I mean it is a very young, it's a young area, it is in incredible growth, the change in state of art is literally month by month right now. So it's going to continue on for a while, and we're just going to keep growing and evolving. Maybe five years, maybe 10 years, things will stabilize, but it's an exciting time right now. >> Very hard to predict, isn't it? >> It is. >> I mean who would've thought that Alexa would be such a dominant factor in voice recognition, or that a bunch of cats on the internet would lead to facial recognition. I wonder if you guys can comment, right? I mean. >> Strange beginnings. (all laughing) >> But very and, I wonder if I can ask you guys ask about the black box challenge. I've heard some companies talk about how we're going to white box everything, make it open and, but the black box problem meaning if I have to describe, and we may have talked about this, how I know that it's a dog. I struggle to do that, but a machine can do that. I don't know how it does it, probably can't tell me how it does it, but it knows, with a high degree of accuracy. Is that black box phenomenon a problem, or do we just have to get over it? >> Up to you. >> I think it's certain, I don't think it's a problem. I know that mathematicians, who are friends, it drives them crazy, because they can't tell you why it's working. So it's a intellectual problem that people just need to get over. But it's the way our brains work, right? And our brains work pretty well. There are certain areas I think where for a while there will be certain laws in place where you can't prove the exact algorithm, you can't use it, but by and large, I think the industry's going to get over it pretty fast. >> I would totally agree, yeah. >> You guys are optimists about the future. I mean you're not up there talking about how jobs are going to go away and, that's not something that you guys are worried about, and generally, we're not either. However, machine intelligence, AI, whatever you want to call it, it is very disruptive. There's no question about it. So I got to ask you guys a few fun questions. Do you think large retail stores are going to, I mean nothing's in the extreme, but do you think they'll generally go away? >> Do I think large retail stores will generally go away? When I think about retail, I think about grocery stores, and the things that are going to go away, I'd like to see standing in line go away. I would like my customer experience to get better. I don't believe that 10 years from now we're all going to live inside our houses and communicate over the internet and text and half of that be with chat mods, I just don't believe that's going to happen. I think the Amazon effect has a long way to go. I just ordered a pool thermometer from Amazon the other day, right? I'm getting old, I ordered readers from Amazon the other day, right? So I kind of think it's that spur of the moment item that you're going to buy. Because even in my own personal habits like I'm not buying shoes and returning them, and waiting five to ten times, cycle, to get there. You still want that experience of going to the store. Where I think retail will improve is understanding that I'm on my way to their store, and improving the experience once I get there. So, I think you'll see, they need to see the Amazon effect that's going to happen, but what you'll see is technology being employed to reach a place where my end user experience improves such that I want to continue to go there. >> Do you think owning your own vehicle, and driving your own vehicle, will be the exception, rather than the norm? >> It pains me to say this, 'cause I love driving, but I think you're right. I think it's a long, I mean it's going to take a while, it's going to take a long time, but I think inevitably it's just too convenient, things are too congested, by freeing up autonomous cars, things that'll go park themselves, whatever, I think it's inevitable. >> Will machines make better diagnoses than doctors? >> Matt: Oh I mean, that's not even a question. Absolutely. >> They already do. >> Do you think banks, traditional banks, will control of the payment systems? >> That's a good one, I haven't thought about-- >> Yeah, I'm not sure that's an AI related thing, maybe more of a block chain thing, but, it's possible. >> Block chain and AI, kind of cousins. >> Yeah, they are, they are actually. >> I fear a world though where we actually end up like WALLE in the movie and everybody's on these like floating chez lounges. >> Yeah lets not go there. >> Eating and drinking. No but I'm just wondering, you talked about, Matt, in terms of the number of, the different types of industries that really can verge in here. Do you see maybe the consumer world with our expectation that we can order anything on Amazon from a thermometer to a pair of glasses to shoes, as driving other industries to kind of follow what we as consumers have come to expect? >> Absolutely no question. I mean that is, consumer drives everything, right? All flash arrays were driven by you have your phone there, right? The consumerization of that device was what drove Toshiba and all the other fad manufacturers to build more NAM flash, which is what commoditized NAM flash, which what brought us faster systems, these things all build on each other, and from a consumer perspective, there are so many things that are inefficient in our world today, right? Like lets just think about your last call center experience. If you're the normal human being-- >> I prefer not to, but okay. >> Yeah you said it, you prefer not to, right? My next comment was going to be, most people's call center experiences aren't that good. But what if the call center technology had the ability to analyze your voice and understand your intonation, and your inflection, and that call center employee was being given information to react to what you were saying on the call, such that they either immediately escalated that call without you asking, or they were sent down a decision path, which brought you to a resolution that said that we know that 62% of the time if we offer this person a free month of this, that person is going to view, is going to go away a happy customer, and rate this call 10 out of 10. That is the type of things that's going to improve with voice recognition, and all of the voice analysis, and all this. >> And that really get into how far we can take machine intelligence, the things that machines, or the humans can do, that machines can't, and that list changes every year. The gap gets narrower and narrower, and that's a great example. >> And I think one of the things, going back to your, whether stores'll continue being there or not but, one of the biggest benefits of AI is recommendation, right? So you can consider it userous maybe, or on the other hand it's great service, where a lot of, something like an Amazon is able to say, I've learned about you, I've learned about what people are looking for, and you're asking for this, but I would suggest something else, and you look at that and you go, "Yeah, that's exactly what I'm looking for". I think that's really where, in the sales cycle, that's really where it gets up there. >> Can machines stop fake news? That's what I want to know. >> Probably. >> Lisa: To be continued. >> People are working on that. >> They are. There's a lot, I mean-- >> That's a big use case. >> It is not a solved problem, but there's a lot of energy going into that. >> I'd take that before I take the floating WALLE chez lounges, right? Deal. >> What if it was just for you? What if it was just a floating chez lounge, it wasn't everybody, then it would be alright, right? >> Not for me. (both laughing) >> Matt and Rob, thanks so much for stopping by and sharing some of your insights and we should have a great rest of the day at the conference. >> Great, thank you very much. Thanks for having us. >> For Dave Vellante, I'm Lisa Martin, we're live at Pure Storage Accelerate 2018 at the Bill Graham Civic Auditorium. Stick around, we'll be right back after a break with our next guest. (electronic music)