>> Announcer: Live from Midtown Manhattan. It's the CUBE. Covering Big Data New York City 2017. Brought to you by Silicon Angle Media and its ecosystem sponsor. (electronic music) >> Hey, welcome back everyone, live here in New York. This is the CUBE here in Manhattan for Big Data NYC's three days of coverage. We're one day three, things are starting to settle in, starting to see the patterns out there. I'll say it's Big Data week here, in conjunction with Hadoop World, formerly known as Strata Conference, Strata-Hadoop, Strata-Data, soon to be Strata-AI, soon to be Strata-IOT. Big Data, Mike Maccaux who's the Global Big Data Practice Lead at Dell EMC. We've been in this world now for multiple years and, well, what a riot it's been. >> Yeah, it has. It's been really interesting as the organizations have gone from their legacy systems, they have been modernizing. And we've sort of seen Big Data 1.0 a couple years ago. Big Data 2.0 and now we're moving on sort of the what's next? >> Yeah. >> And it's interesting because the Big Data space has really lagged the application space. You talk about microservices-based applications, and deploying in the cloud and stateless things. The data technologies and the data space has not quite caught up. The technology's there, but the thinking around it, and the deployment of those, it seems to be a slower, more methodical process. And so what we're seeing in a lot of enterprises is that the ones that got in early, have built out capabilities, are now looking for that, how do we get to the next level? How do we provide self-service? How do we enable our data scientists to be more productive within the enterprise, right? If you're a startup, it's easy, right? You're somewhere in the public cloud, you're using cloud based API, it's all fine. But if you're an enterprise, with the inertia of those legacy systems and governance and controls, it's a different problem to solve for. >> Let's just face it. We'll just call a spade a spade. Total cost of ownership was out of control. Hadoop was great, but it was built for something that tried to be something else as it evolved. And that's good also, because we need to decentralize and democratize the incumbent big data warehouse stuff. But let's face it, Hadoop is not the game anymore, it's everything else. >> Right, yep. >> Around it so, we've seen that, that's a couple years old. It's about business value right now. That seems to be the big thing. The separation between the players that can deliver value for the customers. >> Matt: Yep. >> And show a little bit of headroom for future AI things, they've seen that. And have the cloud on premise play. >> Yep. >> Right now, to me, that's the call here. What do you, do you agree? >> I absolutely see it. It's funny, you talk to organizations and they say, "We're going cloud, we're doing cloud." Well what does that mean? Can you even put your data in the cloud? Are you allowed to? How are you going to manage that? How are you going to govern that? How are you going to secure that? So many organizations, once they've asked those questions, they've realized, maybe we should start with the model of cloud on premise. And figure out what works and what doesn't. How do users actually want to self serve? What do we templatize for them? And what do we give them the freedom to do themselves? >> Yeah. >> And they sort of get their sea legs with that, and then we look at sort of a hybrid cloud model. How do we be able to span on premise, off premise, whatever your public cloud is, in a seamless way? Because we don't want to end up with the same thing that we had with mainframes decades ago, where it was, IBM had the best, it was the fastest, it was the most efficient, it was the new paradigm. And then 10 years later, organizations realized they were locked in, there was different technology. The same thing's true if you go cloud native. You're sort of locked in. So how do you be cloud agnostic? >> How do you get locked in a cloud native? You mean with Amazon? >> Or any of them, right? >> Okay. >> So they all have their own APIs that are really good for doing certain things. So Google's TensorFlow happens to be very good. >> Yeah. Amazon EMR. >> But you build applications that are using those native APIS, you're sort of locked. And maybe you want to switch to something else. How do you do that? So the idea is to-- >> That's why Kubernetes is so important, right now. That's a very key workload and orchestration container-based system. >> That's right, so we believe that containerization of workloads that you can define in one place, and deploy anywhere is the path forward, right? Deploy 'em on prem, deploy 'em in a private cloud, public cloud, it doesn't matter the infrastructure. Infrastructure's irrelevant. Just like Hadoop is sort of not that important anymore. >> So let me get your reaction on this. >> Yeah. So Dell EMC, so you guys have actually been a supplier. They've been the leading supplier, and now with Dell EMC across the portfolio of everything. From Dell computers, servers and what not, to storage, EMC's run the table on that for many generations. Yeah, there's people nippin' at your heels like Pure, okay that's fine. >> Sure. It's still storage is storage. You got to store the data somewhere, so storage will always be around. Here's what I heard from a CXO. This is the pattern I hear, but I'll just summarize it in one conversation. And then you can give a reaction to it. John, my life is hell. I have application development investment plan, it's just boot up all these new developers. New dev ops guys. We're going to do open source, I got to build that out. I got that, trying to get dev ops going on. >> Yep. >> That's a huge initiative. I got the security team. I'm unbundling from my IT department, into a new, difference in a reporting to the board. And then I got all this data governance crap underneath here, and then I got IOT over the top, and I still don't know where my security holes are. >> Yep. And you want to sell me what? (Matt laughs) So that's the fear. >> That's right. >> Their plates are full. How do you guys help that scenario? You walk in, actually security's pretty much, important obviously you can see that. But how do you walk into that conversation? >> Yeah, it's sort of stop the madness, right? >> (laughs) That's right. >> And all of that matters-- >> No, but this is all critical. Every room in the house is on fire. >> It is. >> And I got to get my house in order, so your comment to me better not be hype. TensorFlow, don't give me this TensorFlow stuff. >> That's right. >> I want real deal. >> Right, I need, my guys are-- >> I love TensorFlow but, doesn't put the fire out. >> They just want spark, right? I need to speed up my-- >> John: All right, so how do you help me? >> So, what we'd do is, we want to complement and augment their existing capabilities with better ways of scaling their architecture. So let's help them containerize their big data workload so that they can deploy them anywhere. Let's help them define centralized security policies that can be defined once and enforced everywhere, so that now we have a way to automate the deployment of environments. And users can bring their own tools. They can bring their data from outside, but because we have intelligent centralized policies, we can enforce that. And so with our elastic data platform, we are doing that with partners in the industry, Blue Talent and Blue Data, they provide that capability on top of whatever the customer's infrastructure is. >> How important is it to you guys that Dell EMC are partnering. I know Michael Dell talks about it all the time, so I know it's important. But I want to hear your reaction. Down in the trenches, you're in the front lines, providing the value, pulling things together. Partnerships seem to be really important. Explain how you look at that, how you guys do your partners. You mentioned Blue Talent and Blue Data. >> That's right, well I'm in the consulting organization. So we are on the front lines. We are dealing with customers day in and day out. And they want us to help them solve their problems, not put more of our kit in their data centers, on their desktops. And so partnering is really key, and our job is to find where the problems are with our customers, and find the best tool for the best job. The right thing for the right workload. And you know what? If the customer says, "We're moving to Amazon," then Dell EMC might not sell any more compute infrastructure to that customer. They might, we might not, right? But it's our job to help them get there, and by partnering with organizations, we can help that seamless. And that strengthens the relationship, and they're going to purchase-- >> So you're saying that you will put the customer over Dell EMC? >> Well, the customer is number one to Dell EMC. Net promoter score is one of the most important metrics that we have-- >> Just want to make sure get on the record, and that's important, 'cause Amazon, and you know, we saw it in Net App. I've got to say, give Net App credit. They heard from customers early on that Amazon was important. They started building into Amazon support. So people saying, "Are you crazy?" VMware, everyone's saying, "Hey you capitulated "by going to Amazon." Turns out that that was a damn good move. >> That's right. >> For Kelsinger. >> Yep. >> Look at VM World. They're going to own the cloud service provider market as an arms dealer. >> Yep. >> I mean, you would have thought that a year ago, no way. And then when they did the deal, they said, >> We have really smart leadership in the organization. Obviously Michael is a brilliant man. And it sort of trickles on down. It's customer first, solve the customer's problems, build the relationship with them, and there will be other things that come, right? There will be other needs, other workloads. We do happen to have a private cloud solution with Virtustream. Some of these customers need that intermediary step, before they go full public, with a hosted private solution using a Virtustream. >> All right, so what's the, final question, so what's the number one thing you're working on right now with customers? What's the pattern? You got the stack rank, you're requests, your deliverables, where you spend your time. What's the top things you're working on? >> The top thing right now is scaling architectures. So getting organizations past, they've already got their first 20 use cases. They've already got lakes, they got pedabytes in there. How do we enable self service so that we can actually bring that business value back, as you mentioned. Bring that business value back by making those data scientists productive. That's number one. Number two is aligning that to overall strategy. So organizations want to monetize their data, but they don't really know what that means. And so, within a consulting practice, we help our customers define, and put a road map in place, to align that strategy to their goals, the policies, the security, the GDP, or the regulations. You have to marry the business and the technology together. You can't do either one in isolation. Or ultimately, you're not going to be efficient. >> All right, and just your take on Big Data NYC this year. What's going on in Manhattan this year? What's the big trend from your standpoint? That you could take away from this show besides it becoming a sprawl of you know, everyone just promoting their wares. I mean it's a big, hyped show that O'Reilly does, >> It is. >> But in general, what's the takeaway from the signal? >> It was good hearing from customers this year. Customer segments, I hope to see more of that in the future. Not all just vendors showing their wares. Hearing customers actually talk about the pain and the success that they've had. So the Barclay session where they went up and they talked about their entire journey. It was a packed room, standing room only. They described their journey. And I saw other banks walk up to them and say, "We're feeling the same thing." And this is a highly competitive financial services space. >> Yeah, we had Packsotta's customer on Standard Bank. They came off about their journey, and how they're wrangling automating. Automating's the big thing. Machine learning, automation, no doubt. If people aren't looking at that, they're dead in my mind. I mean, that's what I'm seeing. >> That's right. And you have to get your house in order before you can start doing the fancy gardening. >> John: Yeah. >> And organizations aspire to do the gardening, right? >> I couldn't agree more. You got to be able to drive the car, you got to know how to drive the car if you want to actually play in this game. But it's a good example, the house. Got to get the house in order. Rooms are on fire (laughs) right? Put the fires out, retrench. That's why private cloud's kicking ass right now. I'm telling you right now. Wikibon nailed it in their true private cloud survey. No other firm nailed this. They nailed it, and it went viral. And that is, private cloud is working and growing faster than some areas because the fact of the matter is, there's some bursting through the clouds, and great use cases in the cloud. But, >> Yep. >> People have to get the ops right on premise. >> Matt: That's right, yep. >> I'm not saying on premise is going to be the future. >> Not forever. >> I'm just saying that the stack and rack operational model is going cloud model. >> Yes. >> John: That's absolutely happening, that's growing. You agree? >> Absolutely, we completely, we see that pattern over and over and over again. And it's the Goldilocks problem. There's the organizations that say, "We're never going to go cloud." There's the organizations that say, "We're going to go full cloud." For big data workloads, I think there's an intermediary for the next couple years, while we figure out operating pulse. >> This evolution, what's fun about the market right now, and it's clear to me that, people who try to get a spot too early, there's too many diseconomies of scale. >> Yep. >> Let the evolution, Kubernetes looking good off the tee right now. Docker containers and containerization in general's happened. >> Yep. >> Happening, dev ops is going mainstream. >> Yep. >> So that's going to develop. While that's developing, you get your house in order, and certainly go to the cloud for bursting, and other green field opportunities. >> Sure. >> No doubt. >> But wait until everything's teed up. >> That's right, the right workload in the right place. >> I mean Amazon's got thousands of enterprises using the cloud. >> Yeah, absolutely. >> It's not like people aren't using the cloud. >> No, they're, yeah. >> It's not 100% yet. (laughs) >> And what's the workload, right? What data can you put there? Do you know what data you're putting there? How do you secure that? And how do you do that in a repeatable way. Yeah, and you think cloud's driving the big data market right now. That's what I was saying earlier. I was saying, I think that the cloud is the unsubtext of this show. >> It's enabling. I don't know if it's driving, but it's the enabling factor. It allows for that scale and speed. >> It accelerates. >> Yeah. >> It accelerates... >> That's a better word, accelerates. >> Accelerates that horizontally scalable. Mike, thanks for coming on the CUBE. Really appreciate it. More live action we're going to have some partners on with you guys. Next, stay with us. Live in Manhattan, this is the CUBE. (electronic music)