 Live from the MGM Grand Hotel in Las Vegas. Extracting the signal from the noise. It's theCUBE, covering Splunk.com 2015. Brought to you by Splunk. Now, here are your hosts, John Furrier and Jeff Ricks. Okay, welcome back everyone. We're live here in Las Vegas with Splunk.comference.com. 2015, our fourth year covering Splunk's major end user event, a developer event. Whatever you want to call it, it's their big show. This is theCUBE's SiliconANGLE's flagship program. We go out to the events and extract the signal from the noise. I'm John Furrier, the founder of SiliconANGLE. Here's my co-host, Jeff Frick, the general manager of theCUBE. Our next guest is Andre Peach, product owner and manager at Auto Group, Auto. Big retailer, huge conglomerate in Germany. Welcome to theCUBE. Thank you very much. So, huge company, so a lot of data. I'm imagining the data must be massive. A lot of different channels. Give us a quick overview of what's going on in the back end. What's, I mean, Splunk is great for getting data from all different places. So, you're like a great use case. We have a great use case, yeah. But I have to tell you that our Splunk installation is not that huge. Our business intelligence installation is much larger than that. About six petabyte of data is stored in there. Our Splunk installation is kind of small if I compare it to the other guys around here. But there are a lot of stuff in there. We have about 63 different software systems running in the background. And all of them have to be watched and have to be monitored. And so we connect it to all of them and all of the data goes through our Splunk installation. So the Auto Group has 53,000 employees, 123 different kind of subsidiaries or groups. Three segments, multi-channel, retail, financial services services in 20 countries. So very disparate data. Yes. But the backend consists of only the retail part of that company and not everything, but I think about 20 different subsidiaries are connected to the backend of Auto and let their data be processed by it. So retail honestly is hot because you want real-time information to get a mobile point of sale. It is. Predictive analytics for using collective intelligence to provide the right kind of recommendations. It is. So it's changing significantly. What are you seeing? It is changing, yeah. But we set up two different installations of Splunk, two different instances of Splunk. And each one of them is specialized on what they are doing. One instance is my instance. That is on the backend and processes all the data. The other instance is on the front end looking on the shop and what the mobile devices the mobile users do and so on. So, but I can't tell you much about that because this is not my domain. What about digital infrastructure? Because digital transformation is the big buzzword. Oh my God, yeah. So. And we are in the middle of the digital transformation because we come originally from a catalog, paper catalog kind of company. We started in 1949 and had a paper catalog. It was nice. Printed pictures and glued into onto paper, bound together. Oh really? Yeah, yeah. And in I think 1995, they started to put the catalog into the internet. On the first website, it was hilarious. Not hilarious. Oh sorry, that's the wrong word. That was great. But it was nothing like the shopping experience you have today. It was only the printed catalog online. And but a transformation to a digital company happened in the last years, yes. What should retailers expect for mobile and IoT? Because that's changing the data too because now it's not just point of sale machines. You have now mobile devices that could tie to a back end catalog. You have people that are doing price comparisons. So what are the tricks of the trade for the new retail? What are some of the technology things that are happening and what should retailers expect around the user modeling around mobile and IoT? Yeah, as a retailer you have to be, especially in the future, you have to be where the customers are. The customers in earlier days were depending on the catalog and all the trends and so on. We're coming to the catalog today at home and nowadays the customer looks for what he's interested in. He doesn't get the trend for one year on the basic catalog that was huge, among us. But they go through the internet, go what they're interested in and as a retailer you have to get them where they are. You have to have them interested in what they need, what they're looking for and so on and that will be the huge change in the future. So data security is big exposure in digital world. How can companies keep up with being fully secure? I have no idea. How do you guys look at it? Oh my God, we have a whole team of security guys behind the wall. But you're not using Splunk for any security? No, no, no. We don't use Splunk for security, we only use it for business stuff, to monitor the background. So I want to follow up on John's earlier question about kind of the evolution of retail, because it's interesting, right? You had on the ground retail, then you had online retail. But now one probably argue there's fistication and tracking where people go, empty cards, what they blend is more sophisticated on the online experience and now the mobile experience. But it sounds like now that's going to shift back into the store, where now there's technologies in terms of where you're moving through the store, how long do you stay in the front of an aisle, where are you looking? So they're starting to do more kind of geolocation and behavior monitoring inside the store, which more kind of mimics some of the things that they would track on the online experience. You guys seeing any of those? I think they see it on some of the subsidiaries. They have point of sales and stores and so on. But auto in itself and its core is, was always a multi-channel retailer with phone support or online business. So, but as you said, this behavior can be transferred to the online customer as well. Geolocation is also a big part of how to know what a customer needs. So, yeah, yeah. So talk about the DevOps component around, if any of you guys are doing in the back end, I'll see in Germany, data's big, right? So we know about Germany. It is. How are you handling the upside of the data? Is there any nuances going on with Splunk and your team? What do you mean by upside? I'm not that familiar with that. Well, the operation side of the, of getting the data, Splunking data and then implementing Splunk, you're dealing with a lot of different data. In some cases, outside Germany, inside Germany, that's where your headquarters is. Policy, compliance. Oh my God, yeah. What are some of the things that you're, that you're challenged with that creates opportunity? The most challenges are the information that rush through the system. You have to watch out what goes through. You have to carefully not monitor the credit card information. You have to, you have to mask them. You have to hash them, whatever, to not get data into the typical stream of data. So you have to get very, you have to keep up, get up your fences around these, this stuff to not be in the position to get the attorneys on your back for having the customer data floating around through the company. So give us a day in the life of your work. Through a month or a week, snapshot of what's it like, what are you doing? How you, what are you doing? I mean, it's just plunking stuff. I mean, like, it's like magic, right? Almost like, just take us through how you, what you do, what data you touch, what you do, the value you're creating and getting out of this plunk system. Yeah, the way we use Splunk is that because of these many software systems we have, I can't know each and every bit of data in the company. So what we are trying to do is enable our users to use Splunk. So we have some kind of a crash course, two hours. And so our time to value is about two hours. They get a crash course and they can analyze their data. They know what is in their systems. So they are the best people who can analyze the data and get the value out of the data. I am only there to provide the platform. And who are these, these, the buyers, the merchants? No, no, no. These are the support people for the different software products we use at Auto. Okay, it's the software part, yeah. So we teach them how to use Splunk. Use it like a search engine, like Google. Can I say that? Yeah, yeah, absolutely. Use it like Google. Make your dashboard out of the results. And sometimes in a team of people who attend or who support the software, you have this one guy, this one guy who programs, who helps their colleagues to get their computers up and running. And we pick that guy, teach him a little more, maybe put him on the Splunk certification course or something like that. And he is, and he gives this information, this knowledge to his colleagues. And so they are able to use, to squeeze out the maximum out of the data they have. And is that a formal role or that's just kind of the informal guy that you know everybody goes to? Yeah, it's a formal guy, yeah. We put a hat on him saying the Splunk guy. So he's then the official guy, no. But these people are the core of what we are doing. Because without them, nobody would know anything about what is happening in a company. Because I can't know the software or the details of each and every of the 63 different software systems. So that's impossible, yeah. Share with the folks that are watching what the vibe is like here at the show. What's your take here at Splunk Conference this year? The conference is awesome. It's my first time, I have to say. So I'm a little excited and a little shocked. But I won't tell you about that. The vibe is really good. You have some feeling of home, of familiarity throughout the people. And that's really, really nice. We as Otto are treated as a valued customer. That's also a very, very nice feel and very nice to get. I arrived at Friday. So I attended university for three days to get some more certification. It is necessary nowadays, so yeah. Did you get the pool at least? I had no chance. Yesterday evening I was at a party. It was really good. Have you tried the Oculus Rift? No, the line was long. The line was very long. Oh, it was? Oh, it was great. I had a chance too, I didn't get a little dizzy after a while, but that was really great. Or the other thing, the silent disco? The silent disco, I did do the silent disco. I'd never done that before. I didn't want to get out there. I would have fell down. Well, we really appreciate you coming on the journey and helping us get the data out of your perspective. Thanks for sharing. Thank you for giving me the chance. And we really appreciate it. Thank you very much. Just theCUBE, live here at Splunk.conf 2015. We'll be back with more after this short break.