 from Las Vegas, it's theCUBE. Cover EMC World 2016, brought to you by EMC. And welcome back to Las Vegas. We're inside the Sands Expo here at EMC World 2016, continuing our coverage here on theCUBE. We're talking about big data, it's a big deal these days and what to do with it. That's a quandary for a lot of businesses from looking at analytics and trying to make sense of all that data they have at their disposal. With us to talk about that is the dean of data. Bill Schmarzo, who is the CTO of Global Services at EMC. Bill, glad to have you with us here. Thank you very much. Also with us, John Kenevich, who is the VP of IT and the CIO at the Pachanga Resort and Casino in Temecula, California. John, thank you for being here. Glad to be here. And Ray Caesar, who's the CIO of 10 Brazil, the second largest wireless carrier in Brazil, 75 million subs. And Ray, thank you as well for joining us here. So Bill, before we jump in, let's talk about big data projects that EMC did for both of the gentleman's companies here. What is a project all about? What are the pieces of that? And ultimately, what do you want to deliver to the customer? So let me kind of reverse that question and what we focus in on as outcomes. It's really key that we understand what kind of business outcomes you're kind of drive and who the key stakeholders are in the organization. That understanding of the outcomes we're trying to drive, the business initiatives we're going after, the decisions we're trying to support, help us to fill her down to all the more difficult decision regarding the architecture and the technology. So it's very much focused on the business conversation. And what I want to do is to start this conversation, Ray, and I'll start with you. Is to share with us, for Tim Brazil, what were the business problems you were going after or the business outcomes you were trying to drive? Really, we address two different topics. The first one was network enhancement. So how is it possible to optimize the investment in network with big data? And the second one is reduction of charn and increase of output. That's a classic topic for telco operator. But really with the big data, it's possible to manage this topic in real time. Normally, with data warehouse, it's not possible to manage in real time way. So we address two different topics in the first phase of the project. And in this moment, big data is a core of our digital architecture. In particular, we have three different layers, hot layer in memory grid and the warm layer, green plan database and cold layer, it is ICLON. And we have a memory grid as a boundary between classical architecture of IT, like CRM and building and digital architecture. And so we have all the information that we need in order to conversation with outside of Tim, like with app and so on, in our memory database, in order to manage in millisecond their relationship with outside. And this is two pinch, but I think that we have to have another topics that is related to product leadership or in other word, data monetization. But I have to, we have to study all these topics. Very good. Hey, John Pachanga, what was your area of focus? What were you trying to achieve with your big data initiative? Gosh, what weren't we trying to achieve? I mean, from a casino perspective, we're very, very data driven and we wanted to take that next evolutionary step and big data was a logical avenue to take. And for us, customers are our business and getting to know those customers better was extremely important. And aggregating large amounts of data in a centralized location where we could really get a holistic view of that player, not just with their gaming habits, but where they potentially spend their money in other areas of the property was important. And it's a dream we've had for years. The technology wasn't quite there and now we're there. And it's just really exciting, you know, where that's taking us. Excellent. So I still hear from lots of companies that they don't know how to build interest on the business side in this big data initiative. John, what is it you guys did for Changa to sort of get the business people engaged? Buy-in, getting everybody together to feel like they were part of the process and engaged. We did the data vision workshop with the emcee, which I think was a really good stepping stone to getting that accomplished. You know, even from an organization as large as ours, having the top level executives also interacting with even line level team members and getting them involved in the process and understanding how big data could potentially help their, you know, what they do on a daily basis was huge. And the end of the day, it really, I think took hold because of that. Yeah, I think this big data is a team sport. It is. It's not just an IT initiative. It's a complete property initiative and getting everybody on board and getting that buy-in is big. Excellent. Ray, what did you do at Tim Brazil in order to sort of help champion this initiative and make it real for the, not only the IT people, but also the business people. Really, we began with a gap analysis because the idea is to understand, to identify the project that we need in order to reach our goal. And with the data scientists of emcee, with our users, we became to do a gap analysis and after we identified the project that have a short time, a lab set because the idea was to finance innovation with innovation so the approach was shrink-to-change approach. So we chose the project that have a little lab set and a big result for business in order to involve the users and the other part of the company. And the approach was gradually approach because we start with Pivotaladup and after step by step we increase until to arrive ICL on the memory grid and in parallel we implement a sandbox approach in order to have an agile approach on the development. So what did you find out, Ray, then, in terms of producing churn and raising your average revenue per user here? I mean, what did you put in the practice? What did you find out from the data maybe that you weren't expecting or it was a bit of a surprise that you've been able to put into increased revenues and then lowering that churn rate on your networks. But in order to manage the churn it's important to manage in short time the actual up-selling and cross-selling on the customer. And so that's clear that if we manage the observation of our behavior of the customer in memory and big data, it's possible to achieve this result in short time. So there was no doubt that there was a lot of education going on on the value of big data and getting the business users and stakeholders to buy into the process. John, what kind of challenges do you guys face with Chang in order to get this thing sort of off the ground and going? For us, we were experienced with working with data but we didn't have the infrastructure in place in the organization to be able to really work with big data and that was a transformation process for us. Building governance councils within the organization so we have teams of people that are responsible for making sure that the use cases are going and they're measuring those and then at least twice a week they meet back with our analytical governance council where we basically discuss how those use cases are moving and also to discuss any new use cases that they wanna bring to the table. It works out pretty well. We didn't have that structure in the organization before and we also have representation across the organization at those council levels so it really does help us out in making sound business decisions around big data. So Ray, if you had to give advice to somebody out there who's trying to figure out where and how they start their big data journey, what are the sort of bullet points that you would share with these people to say about how to get going here? It's important to switch the mindset of the user because we start, generally the approach is a waterfall approach but we need to start in different way and different methodology, agile methodology with how I say sandbox and so on. So every user in team has a sandbox and they work on prototyping for every area, a different area of team and with the data scientist of EMC and architect of EMC and after we implement a use case, a different use case that are output of prototyping. That's clear that in the first phase everybody understand in worst way that the big data is a data warehouse. That is a different, there is a completely different approach because that's clear that with big data we have more opportunity than data warehouse. So Ray's a good point and John I'm going to put you on the spot in this one. Big data is different than a data warehouse and in fact a data warehouse mentality can slow you down. You had a really solid data warehouse organization. How did you more fact group to get them to start thinking more like data scientists? Well for us it was wanting to understand our customers in real time where in the past and I think traditionally for most casinos it's you market your customers after the fact and we wanted to get more predictive and be able to target those customers in real time and we're making those steps now. It's just really exciting to be able to look at patterns and to see what's happening on the floor and maybe not just the gaming element but how else they're interacting with our property and to be able to hit those touch points with a guest that they come into our property and maybe they don't come back and we don't ever know why. It would be nice to be able to interact with that guest prior to that and really understand maybe there's something we can do to have an interaction to keep them as a long-term customer. So we weren't able to do that before and we're in a position now where we can and that to me is really exciting. If I take your story about the sandbox and use cases and your story about how to move from being about reporting it's really about how do you excite the business about creating a predictive organization so you can make better decisions regarding churn and networks and customer play and how they're spending the money across the casino. Right, right. I mean even like with casinos we typically we have segmentation with our players and usually based on the play they get dropped in certain categories and I have this vision of singular segmentation and we couldn't do that before. Humans couldn't sit there and be able to mark it like that. So now the machines were able to build logic in there that can look for patterns and predict things and we can get to that point where we'll get to singular marking which I think is huge because now everybody's equal. Yeah, that's right. Yeah, I agree with you. Yeah, to the question really the bill post that derages a little bit ago too if you were talking in perspective even maybe even in your own space for that matter we are in Las Vegas, right? Sure, sure. The fact that you could be forward thinking and reacting in real time it seems to be just a paradigm shift and how you approach your business. Like a no-brainer. Right, but not just in the casino business. Yeah. In retail space, financial services, you name it. I mean to be able to react to a customer in real time seems to be like that's the golden pass right there. I agree, it's a journey. You have to go through iterations and processes and I think it's teaching people, particularly in my industry there's a lot of people that have a certain way of thinking and getting them to essentially think outside the box and look outside of our vertical and what's happening and getting that buy-in, getting people on board to understand what big data is about. I like to call it little data sometimes because I think it's just getting down to many details of players and whatnot at least in our world. But yeah, it does seem like a no-brainer but sometimes there's a little bit of an education process with the organization. So I equate it to a journey. You've got the dean educating you, what more do you need right now? And a professor too at the same time. I want to thank you all for coming on and Bill, I know you've been involved, we have a little March Badness here on theCUBE. Yes. And you've been a participant, I mean maybe not William, but you have been. What do we got to do to get you to the mountaintop? I don't know, I just got to keep building a number of followers and help the clients being successful and that's part of the best thing I can do. We've got to expand that network a little bit, good deal. Big data working well for Tim Brazil and Pachanga, we appreciate the time. Thank you. Thank you both. We'll continue with our coverage here from EMC World 2016 to Las Vegas and just a bit, you are watching theCUBE.