>> Live, from San Jose, in the heart of Silicon Valley, it's theCUBE, covering DataWorks Summit 2018. Brought to you by Hortonworks. >> Welcome back everyone to theCUBE's live coverage of DataWorks here in San Jose, California. I'm your host, Rebecca Knight, along with my cohost James Kobielus. We are joined by Mike McNamara, he is the Senior Product and Solutions Marketing at NetApp. Thanks so much for coming on theCUBE. >> Thanks for having me. >> You're a first timer, >> Yes, >> So this is very exciting! >> Happy to be here. >> Welcome. >> Thanks. >> So, before the cameras were rolling, we were talking about how NetApp has been in this space for a while, but is really just starting to be recognized as a player. So, talk a little bit about your company's evolution. >> Sure. So, in the whole analytic space, is something NetApp was in a long time ago, and then sort got out of it, and then over the last several years, we've gotten back in, and we recognize it's a huge opportunity for data storage, data management, if you look at IDC Data, massive, massive market, but, the opportunity for us, is like you know what, they're mainly using a direct attached storage model where compute and storage is tied together. And now, with data just exploding, and growing like crazy, it's always been growing, but now it seems like it's just growing like crazy now, that, and customers wanting to have data on-prem, but also being able to move it off to the cloud, we're like, hey this is a great opportunity for us to come in with a solution that's, external storage solution that can come in and show them the benefits of have a more reliable, have an opportunity to move their data off to the cloud, we've got great solutions with that, so it's gone well, but it's been a little bit different, like at this show, a lot of the people, the data scientists, data engineers, some who know us, some still don't like, so, NetApp, what do you guys do, and so it's a little bit of an education, 'cause it's not a traditional buyer, if you will, we look at them as influencers, but it's only one influence than we traditionally have sold to say Vice President of Infrastructure, as an example, or maybe a Director of Storage Admin, but most of those folks are not here, so we're, this is just kind of a new market for us that we're making inroads. >> How do data scientists, or do they influence the purchase of storage solutions, or data management solutions? >> Sure, so they want to have access to the data, they want to be able analyze it quickly and effectively, they want to make sure it's always available, you know, at their fingertips so to speak. We can help them by giving them very fast, very reliable solutions, and specially with our software, they want to do for example, do some virtual clone of that data, and just do some testing on that without impacting their production data, we can do that in a snap, so we can make their lives a lot easier, so we can show them how, hey, mister data scientist, we can make your life a little easier-- >> Or miss data scientist. >> Or miss, we were talking about that, >> There are a lot of women in this field. >> Yeah, yeah. >> More than we realize, and they're great. >> So we can help you do your job better, and then, that, him or her can then influence who's making the purchase decisions. >> Yeah, training sets, test sets, validation sets of data for the machine learning and analytics development pipeline, yes, you need a solid storage infrastructure to do it right. >> Absolutely. >> So, when you're getting inside the head of your potential buyer here, the VP of Infrastructure, or data admin, what is it that you're hearing from those people most, what are their concerns, what keeps them up at night, and where do you come in? >> Yeah, so one of the concerns is, often times, you're, hey, how do I, do you have a cloud storage, connected to the cloud, you know, I'm doing things on-prem now, but is there a path, so that's a big one. And we, NetApp, pride ourselves on being the most cloud-connected, all flash storage in the industry. So, that's a big focus, big push for us. If you saw our marketing, it shows data authority for the hybrid cloud, so we really honestly do, whether it's with Google, or Azure, or AWS, we know our software runs in those environments, it also runs on-premises, but because it's the same on-tap software, we can move data between those environments. So, we get a real good storage, so we can you know, boom, check the box, we got you covered if you want to utilize the cloud, and I think the next piece of that is just from a protecting, protecting the data, you know, again I said data is just growing so much, I want to make sure it's always available, and we can back it up and all that, and that's been a core, core strength, versus like a lot of these traditional solutions they've been using, these direct attached models, they just don't have anywhere near the enterprise-grade data protection that NetApp has always prided itself on, over many decades now. And so, we can help them do that, and quite honestly, a lot of people think, well you know, you guys are external storage, how do you compare versus direct attached storage from our total cost, that's another one. I can tell you definitively, and we've got data to back it up from a total cost of ownership point of view, because of the fact that, of the advantages we bring from, up-time, and you know from RAID, but you know, in a Hadoop environment, often times there's three copies of data. With our solution, a good piece of software, there's only one copy of your data, so have three versus one is a big saving, but even what we do with the data, compressing it, and compacting it, a lot of benefits. So, we do have honest to goodness, outwards to 50% better total cost of ownership, versus a DAS model. >> Do you use machine learning within your portfolio? I'm hearing of more stories, >> Great question, yeah. >> Incorporating machine learning to automate or facilitate more of the functions in the data protection or data management life-cycle. >> Yeah, that's a great question, and we do use, so we've got a piece of software which we call Active IQ, it was referred to as Ace Update, you may have, it may ring a bell, but to answer your question, so we've got thousands of thousands of NetApp systems out there, and those customers that allow us, we have, think of it as kind of a call home feature, where we're getting data back from all our installed customers, and then we will go and do predictive analytics, and do some machine learning on that data, so then we can go back to those customers and say, hey you know what, you've got this volume that's unprotected, you should protect this, or we can show them, if you were to move that data off into our cloud environment, here's maybe performance you would see, so we do do a lot of that predictive-- >> Predictive performance assessment, it sounds like there's anomaly detection in there as well. >> Anomaly as well, letting them know, hey, you know, it's time for this drive, it may fail on you, let's ship you out a new drive now before it happens, so yeah, a lot of, from an analytics, predictive analysis going on. And you know, it's a huge benefit to our customers. Huge benefit. >> I know you're also doing a push toward artificial intelligence, so I'd like to hear more about that, and then also, if there's any best practices that have emerged. >> Sure, sure, so yes. That is another big area, so it's kind of a logical progression from where we were, if you will, in the analytics space, data lakes, but now moving into artificial intelligence, which has always been around, but it's really taking more of a more prominent role, I mean just a quick fun fact, I read that, you know that at the royal wedding that recently happened, did you know that Amazon used artificial intelligence to help us, the TV viewer, identify who the guests were. >> Ooh. >> So, you know it's like, it's everywhere, right? And so for us, we see that trend, a ton of data that needs to be managed, and so we kind of look at it from the edge to the core, to the cloud, those three, not pillars, but directional ways, taking data from IOT centers at the edge, bring it into the core, doing training, and then if the customer so chooses, out to the cloud. So, yeah it is a big push for us now, and we're going a lot with Nvidia, is a key partner with us. >> Really? This is a bit futuristic, but I can see a role going forward for AI to look into large data volumes, like video objects, to find things like faces, and poses and gestures and so forth, and see, to use that intelligence to be able to reduce the data sets down to where it's reduced, to de-duplicate, so that you can use less storage and then you can re-construct the original video objects or whatever going forward, I mean as a potential use of AI within the storage efficiency. >> Yep, yeah you're right, and that again, like in the analytic space, how we roll our in-line efficiency capabilities and data protection, is you know, very important, and then being able to move the data off into the cloud, if the customer so chooses, or just wants to use the cloud. So yeah, some of the same benefits from cloud connectivity, performance and efficiency that analytics apply certainly to AI. You know, another fun fact too about AI, which might help us, you and I living in the Boston area, is that I've read IBM has a patent out to use AI in traffic signaling, so in conjunction with cameras, to get AI, so hopefully that, you know, that works well it could alleviate-- >> Lead them out of the Tip O'Neill tunnel easy. (laughing) >> You got it maybe worse in D.C. (laughing) >> I'd like to hear though, if you have any best practices that with this moving into AI, how are you experimenting with it, and how are you finding it used most efficiently and effectively. >> Yeah, so I think one way we are eating our own dog food, so to speak, in that we're using it internally, we're using it on our customers' data, as I was explaining to help look at trends, and do analysis. So that's one, and then it's other things, just you know, partnering with companies like Nvidia as well and coming out with a joint solution, so we're doing work with them on different solution areas. >> Great, great. Well, Mike thanks so much for coming on theCUBE, >> Thanks for having me! >> It was fun having you. >> You survived! >> Yes! (laughs) >> We'll look forward to many more CUBE conversations. >> Great to hear from NetApp, you're very much in the game. >> Indeed, indeed. >> Alright, thank you very much. >> I'm Rebecca Knight for James Kobielus, we will have more from theCUBE's coverage of DataWorks coming up in just a little bit. (electronic music)