 Live from Berlin, Germany. It's theCUBE, covering NetApp Insight 2017. Brought to you by NetApp. Welcome back to theCUBE's live coverage of NetApp Insight here in Berlin, Germany. I'm your host, Rebecca Knight, along with my co-host, Peter Burris. We are joined by Manfred Buchanan. He is the VP Systems Engineering EMEA for NetApp and Mark Carlton, who is an independent IT consultant. Manfred, Mark, thanks so much for coming on the show. Thank you. Thank you for having us. Manfred, I want to start with you. You're a company veteran. You've been with NetApp for a long time. Let's talk about the data management innovations that make IT modernization possible. It's a big question. That's a great question. As a veteran talking about AI and the futures and data management, things make it capable, but just coming off the general session and take something like our object store and think about, I put an object, a picture from you. I just put it into the storage and it gets handed over into Amazon Analytics and Amazon Analytics. Oh, you are smiling. And think about this without any coding and just a few things to plug it together and it works. And if you take it further, it works at scale. So it's not only your face. It's the 2,000, 4,000, 10,000 faces here. You just put it in, in parallel at scale, Amazon at scale, does the analytics on top, and you get the results back. Just as a plug-in architecture, is this data management at scale? Is this innovation? Is this the next gen data centers? All of them. But it's not magic. Something allows that to happen. So what are those kind of two or three technologies that are so crucial to ensuring that that change in system actually is possible? I would put it pretty simple. The core technology we provide connect an on-premise data center with a public cloud and make this whole thing seamless happen and make it happen for all different protocols. You have it in the sand space and then an ice castle in the cloud. You have it on files, on-premise, move the file over and you have it with an object. And an object, even if we go further, we integrate it into a message bus. Maybe it's too technical, but a message bus is just, I got an event and I tell somebody else there's an event coming, do something. And that's what we do with the picture analyzes. I got an event, which is I get the picture. And with this event, I tell Amazon, please do something with the picture and I give you the picture to analyze. So it's a fabric, there's object storage and there's AI and related technologies that allow you to do something as long as the data's ready for that to be done. And even move the data with it basically. That's what we do. And if you think about it, that's unbelievable magic. So Mark, I want to ask you, you're an independent IT consultant. You've been following NetApp for a long time. You have your own blog. What are some of the biggest trends that you're seeing? What are some of the biggest concerns you hear from customers? Really from customers, it's more around what steps to take. The market's changing as we can see, what we were saying there, data's sprawling and it's spreading so fast, it's growing so fast. What we were storing a few years ago where, a few years ago when I first started, someone talked about a terabyte and you thought that's a big system or you got 50 terabytes and you're huge. Now we're talking 500 terabytes, 100 terabytes. And the difference is what sort of data that is. Is it stored in the right place? And I think that's one of the biggest challenges is knowing what data you have, how to use it and how to get the most out of the data in the right place. So we've talked about the on-premises, whether it be in the cloud, whether it be in object. And I think that's key from where we're moving with the data fabric within NetApp and how NetApp's creating their data management suite as such for ONTAP, for the Solidify suite and how they're joining the products up. So it makes it seamless that we can move this data about from these different platforms. And I think one of the biggest things, biggest thing for me, especially when I'm talking to customers, is it's the strategy of what you can do with data. It's the, there's no complications. As Manfred said, it's as if it's magic, as that type of thing. It will go, you can do whatever you want with it. And I think from a customer point of view, because they don't have to make that choice and say, that's what I want to do today. They've got scale, they've got flexibility. They can control where their data sits. They can move it back and forth. And the sprawl out into AWS Azure and then Google and with a cloud that side and been able to use those three, the different cloud platforms, even IBM cloud and how they can plug into those. It's really starting to open those doors and really argue the point around the challenges. You've got a lot of answers to a lot of different things. So how do you help customers make sense of all of this? I mean, as you said, there are a lot of options. They can go a lot of different ways. They know that they need to use their data as an asset. They need to deploy it, find that value. What's your advice? You know, let me also take a step back. We talk about, we get more and more data. We talk about connecting the different clouds. But at the same time, we also talked about basics. I move from flesh into storage glass memory and I make everything faster. If you think about more data, to process more data in the same time, everything needs to go faster. And I give you a simple example or just challenge you. How many have you sitting before a business application in your company and you sit, you press the enter button and it takes a minute, it takes another and you go. Sorry, why does it take so long? As a veteran in the old days, what we said is basically, we press the enter button and we said, we need to go for a coffee and come back and after the coffee, the transaction is done. Now, we talked about on stage about microseconds and milliseconds and all these things, but put it into relation. Take a transaction, I press the enter button and it would have taken, let me say, 10 minutes until I got a result out of it. And this was in times of when storage response times were 10 milliseconds. Take this one into response time is now one millisecond and you do the same amount of data, you press the enter button and it's not 10 minutes, it's a minute. Now you say the next generation technology we showed, it's even 1,000 times faster. You go now from a minute to 1,000 of a minute, a millisecond. You know what a millisecond means for you? You press the enter button, result is there. And now you think, we get more and more data, petabytes of data, how can I make sure and process it as fast as possible? So that's one character you look into and I believe the future is also for AI and for all these things is how fast can you process, maybe we get a measurement which calls petabytes per second or petabytes per millisecond, can you process to get information out of it? And then at the same time you said, which solution, which choices? I believe in the current world, as it's more fast moving, all the solutions evolve at a high speed. So at a certain point in time, I just make a decision, I go with this one. And even if you go with the public cloud, you choose the public cloud, one is price, but you also choose it on capabilities. If you go to the IBM side, what an IBM Watson is doing in terms of AI, incredible. And that's what we use for active IQ in the support side. So it's not only the system, the speed of the system, where do you deploy the data? But at the same time, I give you all the information, what are you doing with your data on the support side? And connecting this and customers will choose, like we do it internally, the best solution. And what we give them, we give them the choice, we give them reference architectures, how it works with this one, how it works with this one. We may give them some kind of guidance, but to be frank, and as a veteran, and sometimes as the guys know me, I'm straightforward, the decision is something the customer needs to make, or the partner with the customer together, because you have the knowledge basically on the implementation side, need to make, I'm the best one in this one, I know how it works, I know how I can do it. But that's the choice, which is more on the customer together with their implementation partners. Great. Well, Manfred Mark, thanks so much for coming on theCUBE. This was great, great having you on. Thank you very much. I'm Rebecca Knight for Peter Burris. We will have more from NetApp Insight just after this.