 Live from Las Vegas, Nevada, it's theCUBE covering EMC World 2015, brought to you by EMC, Brocade and VCE. Welcome back everyone, Jeff Frick here with theCUBE. We are live from EMC World 2015. This is our third day of continuous coverage. We have two cubes running back to back. We have a ton of great guests, a ton of great content. Hopefully you're enjoying it out there. Getting a sense of what's going on here at the show as we get our tech athletes, as we like to say, to come on inside theCUBE and share some of their knowledge and insight. So we're excited for this next segment. We've got John Cardente, Frequent Cube alumni. Good to have you back, John. Distinguished engineer, Corporate CTO Office at EMC. We always like distinguished engineers and fellows too. We get those too sometimes. Craig Steele, GM and Senior Director, Global Strategic Alliance from Pivotal. Awesome. So welcome. First time? Yes, it's my first time. Excellent. So Strategic Alliance, I've got two companies here. Talk a little bit about the relationship between Pivotal and EMC. Certainly. So Pivotal is the majority ownership is held by EMC. Part of the Federation. Part of the Federation. So we try and stay within that Federation framework and our go-to-market structure and some of the engineering campaigns that we have in building out technology and solutions together. And so far it's been working pretty well. Customers seem to gravitate towards this sort of ease of use. Right. And, you know, at the end of the day, a one-throat to choke model is always helpful as well. So yeah, we're well on the path from a strategic alliance perspective. Yeah. And then what do you think, John? Has the Federation worked in terms of differences than kind of the traditional alliance that you might have with other companies that aren't part of the Federation? Yeah. So having Pivotal as part of the Federation really enables us to work very closely on building and delivering some complete solutions to customers, right? So for the Federated Business Data Lake, we very much take the view that it's about data analytics and applications. You need to be able to do all three. Right. And so EMCII has great infrastructure products. With VMware, we can build flexible and virtualized environments. And with Pivotal, we have the analytics. And most importantly, the application development capability. Right. And talk about the difference really from, you talk about data-driven applications. How has that a different approach to maybe traditional application development and kind of use in the past? Yeah. So, you know, if you look at traditional business intelligence, having applications to do, but dashboards and reporting and things like that are, you know, an important part of the things. But with big data, what you're really trying to do is deliver value on insights, right? So it's all about looking at the data in new ways, finding new relationships, and then quickly monetizing that. And so in order to do that, you need the applications to deliver that information, either to customers or folks in the field. And so you really need a way to develop applications quickly so that you can take that insight and deliver it in a way where it can be consumed. Right. I would just dovetail on that and say that, you know, that's the entire business model for Pivotal, and it really relates well to the Federation Business Data Lake model. Our go-to market is really focused on building new agile applications. Those applications eventually have data associated with them. That data can be analyzed, and then you leverage that analytics to recreate or iterate on the application and then build more use cases into the environment. The data lake solves a big problem for that, for customers there. And the way that the applications are developed, leveraging technologies like Pivotal Cloud Foundry really speeds up that process in new and interesting ways. If you think about it, you know, the process for developing applications prior to this has really been, you need hardware, you need middleware, you need operating system, you need messaging and load balancing. Pivotal Cloud Foundry really takes all of that sort of time-consuming issues out of play and makes it really easy to build the application in the first place, but also scale and manage it in that process. Right. Now you said the interesting thing, that as the data comes in and you start to get insight from the application, you're actually iterating on the application as really thinking about it instead of building a new application. So that is a very different type of approach. Yeah, we believe it is. So if you look at the, you know, sort of traditional application development, it's very, very slow. Now if you look at the new applications that are kind of following the message of software eating the world, take an example like Uber, it's the biggest transportation company in the world, and they don't own a single car. Right, right. Airbnb, you know, number one hospitality company in the world, they don't own any property. It's really about the end-user experience. So once you develop an application that's around that end-user experience, and then you analyze that data, you're then able to come up with new use cases, new value that you can drive, and you have to very quickly be able to iterate that application to go out and monetize those capabilities. Right. So that's what makes it interesting. Yeah, and another important facet of this too is that the ability to create mobile applications quickly and easily enables gathering more data from the field, from customers or from people out there making observations about how people are using products and things like that. So it's not only delivering insights to the edge, but it's collecting data from the edge as well. That's really important. Right, and then two, the other thing that's so different, right, is now integrating other data besides your data and really being able to bring a much broader, more disparate data set into play. How are you seeing that kind of working out in the field with real customers? Well, we're seeing it in a lot of different places, right, because customers are realizing that not only do they have hidden treasures in their own data, but when they want to do things like sentiment analysis or lead generation or things like that, they need to pull in some external resources, right? A lot of it's messy and unstructured, and so it needs these new tools in order to be able to capture it. Right. So we're seeing a lot of potential capability that we're building inside the Federated Business Data Lake is to be able to take both the data you have and the data that you have access to and use it and analyze it to get those insights. Right. Yeah, I would say that's part of the structure of a pre-engineered capability when you look at something like a Federation Business Data Lake. All that capability is built into the solution day one. And it's built in such a way that you can, again, iterate on the application, but you also might be finding, you know, different information that you can bring in from outside your traditional organization that you can leverage for business value and marry the two. You leverage technologies like, let's say Gem XD as an example, as something that can also be sort of a modern day messaging, right? So you can take sentiment information from Twitter and marry that with weather analysis, if you will, in real time and come up with ways that affect outcomes. Right. So the other funny thing I think that's interesting here is the whole concept of agile and software development and agile and iterating your applications. But now it's really driven to being an agile business in terms of the business models, the business process. You know, using that exhaust, using some of that new stuff that you didn't even know that you had or you're seeing it in a different way to now actually really bring an agile kind of methodology process mindset into your actual way you run your business. Yeah. Yeah. You know, I view big data in a lot of ways as the long tail brought to analytics and that, you know, the relationships and the behaviors that are easy to monetize, we've done that. And so now you're at that long tail where there are these, you know, ephemeral short lived, you know, relationships that you can monetize, but you're going to act quickly, right? Because they might go away. Or, you know, there might be three of them. And so what you really need is an infrastructure that you can do, you can capture many of those, get the volume of the tail with the right economics so that we actually make money. And that's really what big data is changing, right? It's now it's possible to do that. We couldn't do that before. You couldn't make money going after those, you know, transient or very rare insights, right? Right, right. It's like the old, you know, early days of the electronic training where the guys that, you know, could get ahead of the curve and see those little opportunities that were so transient and jump on them were way ahead of everybody else. Absolutely. It's really true. And the other thing that we sort of looked at when we built out this model was understanding that if you have an application development process and a platform on top of that. And so as an example, Pivotal Cloud Foundry runs on top of the sphere, runs on top of Amazon Web Services. It runs on top of EHC and other, you know, vendor supplied infrastructure. So the good news is it's not like the old days where you're kind of locked in. I mean there are several customers that are, you know, paying a tax to IBM to continuously run their cold ball. And right now we're seeing customers that are writing application in the Amazon Cloud that, you know, down the line because they're so intertwined in that Amazon that they're going to be kind of locked into that. To that infrastructure. So Pivotal Cloud Foundry allows that application to move to different, you know, different infrastructures, public, private, and then leverage the best technology for the use case, which we really believe we've cracked the code with in terms of the Federation business data. Yeah, because it's really about, at the end of the day, it's about the workload and the application of that workload at that moment of time. Whether it's test dev early days or PLC trial or massive scale in production and being able to move that wherever it needs to be for whatever the appropriate level of security and access and speed, et cetera, et cetera. I want to shift gears a little bit and talk about it, you know, real time. It's like about real time. What does real time mean to you in this kind of fast paced agile development and business model world in which we live? Yeah, I would follow, you know, I follow our CEO. So the message that we hear there is really about capturing things or people in the act of doing something and be able to affect the outcome in real time. So if you start looking at it that way, you know, the talk track is everything from your socks to jet engines will have some sort of sensor data or information on it. And, you know, they're really smart people, data scientists included that can figure out how to monetize those different real time capabilities. And then again, it goes back to the application. How do you very successfully go and attach that application and user experience to the 1.5 billion cell phones that are out there to then monetize that and bring value back to your business. So real time is really about capturing that information on whether it's a machine or a person and then affecting the outcome in actual real time. It's very exciting stuff. The example I like to use is that, you know, in the dawn of time, you know, you knew that men bought razor blades. It was a pretty easy thing to figure out, right? And then you did a little bit more work and you figured out, you know, maybe men between 30 and 40 like triple blades, right? So a little bit of market segmentation, a little bit of digging, kind of your traditional BIDW. For me, real time in big data is Craig tweeted this morning that he forgot his razor blade at home. So let's send him a coupon so he can go buy a razor blade, you know, one of ours, right? And so now maybe that's the beginning of a relationship, right? If you think about what's necessary to monetize that event, you've got to eat the Twitter fire hose. You've got to find that tweet that's relevant to you. And you've got to be able to quickly send a coupon, right? And perhaps go through a lift model to figure out whether or not that's even worth sending to someone like him. That's real time. That's acting on an insight before he goes down to the lobby and buys a razor blade. Right, right, right. And even then, that's still kind of, that's still kind of after the fact, right? It's event driven because you, because you tweet it. Because the other thing that people love to talk about kind of the dream of big data is moving from that model to really predictive, right? That's right. And then beyond that, prescriptive, which I guess in your instance would be, your phone indicated that you rushed out of the house, you know, from the time you picked it up when the alarm clock went out to the time you were in the Uber was a very short period. Good chance maybe you forgot the Dopp kit in the, in the bathroom. So maybe I should send you that razor blade coupon before you even land because I could put those things together. Amazing how much data, I'm always fascinated by people's concern of, you know, kind of big brothery types of stuff when we're all packing this little GPS with an accelerometer. That's right. That knows exactly where we are, how fast we're moving all the time. So it's really an interesting feature and how that starts to be delivered in terms of new products and services on the positive side versus some of the things people worry about. Yeah. There are new types of communities being developed around different things that many people don't even think of. I'll give you an example. So Rip Curl is a company that has a legacy business of building wetsuits for surfers. Okay. They came out with a watch. That's a GPS watch that has geospatial sensors in it that tells you how many miles you paddled, how many waves you caught, what your longest ride was. Right, right. All these different statistics and data in real time and there are communities being built up for others that use this technology to compete in real time in the water for those different statistics and then share with their friends globally. So it's really amazing that some of the things that's going on with in terms of data-driven outcomes and people leveraging that for their personal life as well as business. Right. Well, it's funny you mentioned the socks because down the street in downtown Vegas this week is the collision comp. I don't know if you've been paying attention. We're very busy here in the sea world, obviously. But I'm getting a lot of stuff from people reaching out to see if we're going to be there. And one of the companies is an athletic tech sock company where it's got sensors in the socks. It's got receivers on the sensors. I'm sure it's got an application for your iPhone. They sent me like the whole pricing package and get replacement socks, replacement sensors. So it's happening today and it's happening now and it'll be interesting to see from kind of a psychological impact when the feedback starts to come. Now people know that I walked 10,000 steps or not. No one ever knew that. It was an arbitrary thing, but now suddenly, I'm only at 8,000. I got to go walk down to the block a couple of times. So it is interesting how now these machines and the feedback loop can really start to influence behavior. Yeah. And I think to draw that forward, the internet of people is kind of an interesting thing because we all have these devices, right? So a good example of going from the general to the specific is we could take a lot of telemetry and say, well, people who walk 10,000 steps a day are generally more healthy, right? So it's a general recommendation. But more specific is I looked at your calendar and I noticed that you have to be from this building and this building. So instead of taking a shuttle, why don't you walk and that'll get you this much closer to your goal? That's the kind of prescriptive kinds of things that you can do with analytics that is only enabled though if you can process that stuff really quickly. One last thing, one last point I'd like to make. So we're seeing this sort of influx of new capabilities, new requirements from different customers on a daily basis. Folks that wouldn't normally, you would see like in a Pivotal Labs environment, CEOs of major corporations coming in to see how Pivotal Labs is building these applications that can be leveraged in a data lake environment. It's interesting to watch because the market is still nascent. Hadoop is kind of, I think people have figured out what Hadoop is and what you can leverage it for but it's really the analytics and the real-time analytics now and going forward that are going to drive real business value for many customers. It's great to see you. Our much shorter answer to the real-time question is in time to do something about it. Yes. Can you get in time to do something about it? Whatever that means, whether it's ice cream melting and you got a little time or somebody's making a financial transaction on their Schwab account, do you have time to really, like you said, influence it in flight versus post-haze? Great. So I'm going to give you the last word, Craig, before we sign off. What are you excited about in the next six months? What are you working on? What should we be looking for? So I think it's a continuation of sort of the same progress that we've had over the last six months where we're seeing a significant amount of interest and adoption in the technologies that we're putting forward as a federation. I'm really excited about some of the additional use cases that we'll be able to add to the Federation Business Data Lake environment and I think the partnership with EMC, VMware, and Pivotal is stronger than ever and will continue to be that way as long as customers still have the demand for what it is we're creating. So really excited about the future. Excellent. Well, thanks for stopping by, Craig. John, always good to see you. I'm sure we'll see you again. I'm Jeff Frick. You're watching The Cube. We're at EMC World 2015. Three days of wall-to-wall coverage. We're in day three. We're on the backside of the last day but we're excited. We're standing at the end and we'll be right back with our next guest after this short break.