 Live from Las Vegas, Nevada, extracting the signal from the noise. It's theCUBE covering Informatica World 2015, brought to you by Informatica World. Now, here's John Furrier and Jeff Frick. Okay, welcome back everyone. We are live in Las Vegas for theCUBE's Silicon Angles flagship program. We go out to the events and extract the silken noise. I'm John Furrier, the founder of Silicon Angles. I'm Joe McCose, Jeff Frick. Our next guest is Arun Vara Darjan. Assistant Vice President, Business Leader, Enterprise, Information Management, Cognizant. Welcome to theCUBE. Thank you, John. Thank you. We'd love having Cognizant on. Thanks so much for coming on, great content. Tell us what's going on with you guys right now at the show here. Digital transformations, the hottest trend on the planet, big data, applications, the cloud, all kind of coming together. So what's your take here at the show? What are you guys doing? I think Informatica has always been pivotal to our strategy. As you know, I represent the Enterprise Analytics Group within Cognizant. We operate in the entire data value chain, helping our clients source different kinds of data. You heard that today, multiple source systems. Basically, I think a lot of our clients are definitely moving beyond transaction data because they see value in the interactions that are happening with their clients, with their suppliers, with their partner ecosystem. So there's a lot of that, I would say, a huge variety of data sources that are being now looked at very, very intently. And customers are starting to see a strong business case in bringing that into the Enterprise data fold, if you will. And we're hearing that it's moving from the bowels of systems, data's moving up and from the plumbing, if you will, to another level. What does that mean? I mean, does that mean it's moving or it's just sitting in two places? I think the data has been there. It's just that the kinds of data and the variety of data and the ability to acquire the different types of data, I think that's simplified significantly. So you're finding clients now realizing that it's not enough to just look at the transaction systems in order to create business insights or to support their decision-making. So I'll give you an instance. I'm working with the CIO and the Chief Analytics Officer of a fairly large multinational that manufactures heavy engineering equipment. And traditionally, if you look at their business, they have issues when the energy prices have fluctuations. They have challenges when there are construction, industry nuances and changes that are going on. Now how do they bring some of that contextual data and information into their planning cycle? That's been a big question for them, right? So traditionally, they've done planning based on looking at past sales history, past sales history by geography and just kind of creating trends and perhaps forecasting what the business would look like. But today, they have the ability to get real-time data. Real-time data, whether it's currency fluctuations, whether it's changes in monetary policies, regulatory changes, and really trying to see how that can influence or improve their planning process. And also their adjustment in their strategies as they move forward. So they're adding non-internal data sources. Yes. Slow processes to now have better insight into actually making forecasting decisions and other business decisions that they just couldn't do before. Exactly, because the ability for you to source that kind of data has become that much more easier. You heard Informatica today, right? There's a lot of focus on going beyond the transaction data. Right, right. A lot of focus. And that's all being driven by the customer because today, customers are realizing that if they have to make prudent investment decisions, whether it's in R&D, whether it's in sales dollars, whether it's in just operational efficiency, if they can get some of that data, then they can forecast and have foresight into how these are going to have implications across their value chain. So whether you're in the theme park world or whether you're a manufacturer or whether you're a bank or an insurer, right? It's very interesting that a lot of this ambient data is critical to really making these better decisions. So Cognizant, in fact, we've been very bullish about this whole digital world. It's reflected in our SMAC strategy where we talk about social media, cloud analytics. We have that as a concept and it's been in play for the last three years. We had, again, an interesting notion around defining an entity and its persona in the digital world, right? Which we call as Code Halo. So Code Halo to us is a kind of a definition of an entity, be it a product, be it a brand, be it an enterprise, be it a customer, be it a device in the whole digital world. And we've been working on a lot of the technologies that you've heard today which are getting commercialized and productionized. We've been using some of those concepts in helping our customers really create that persona or definition of that entity in the digital world. So that's been a big play for us. So that brings up a great point. First of all, we love that because we have our CrowdChat application, which is all about real time data and engagement. But you're talking about something that's about new data. Not old email addresses or this guy came and filled out a form, came to our site, did some stuff, bought something. You're talking about giving something an identity in the engagement data space. If I hear you correctly, that's what Halo is, right? And it could be an entity, it could be a person. That is engagement. That's the engagement holy grail. Isn't it? You talk about that dynamic. Is that your onto something there? I think it's really powerful. When you're out within the engagement space, there's data there too. And that's what we're hearing here at this show, engagement. Expand on that concept of engagement data. Absolutely. I think you heard that again during the course of the conference. There's the whole notion of what is mastering and what is master data or authoritative data is changing over time. At one point in time, I would refresh my master data strategy or definition once every few years. And today, in a dynamic world, I have the option of doing probably a refresh a week. I'm thinking that all of this is going to change in warp speed. So when you talk about a customer, I don't know if you were in one of the breakout sessions, when people are looking at segmentation of a customer and really looking at attributes that define a customer. Now, who do you, if you have X amount of marketing dollars and you want to invest in your customers who are going to drive more loyalty and more revenue and bring you that value, you got to determine who are that set of customers. It was very difficult for me to do that before. I would still use bureau data to do some historical analysis, maybe get some trending, do some better segmentation. All of that was the thing of the past. So to your point, John, today, I don't need to just rely on bureau data which is 60 days old or 100 days old. I can actually go out there and listen to what my customers are doing, whether it's social interactions, whether it's just interactions with my product. So if I'm a cable operator and I've got set up boxes out there, they're no longer dumb terminals, right? They hold a lot of data on what my customer's doing with my products and services. What kind of shows is he or she watching at what times of the day? So what I'm basically trying to say is that because of today's technology, customers are able to do things a lot faster, what they could take, what they would take months to do, they're getting done in weeks. I mean, this is the holy grail in my mind because you're talking about an area, I mean, you see Oracle out there with engagement cloud sales force and all this stuff. They're not even hitting the real nerd which is engagement cloud in my mind. But you're talking about real time in the moment. So I got to ask you, what's your take on the real time piece? Because if you can connect the dots there, the growth opportunities for your customers are significant and that sounds like what you're working on. Customers want to grow and have happy customers and sell stuff. So their growth is going to be dependent upon tapping into this new ability to connect on the data. Can you stand on that? How customers are growing around that? Sure. I think real time for a long period was a cool project in the engineering world or a cool project in academia. What I think a lot of our clients are realizing is that there's a real use case now for real time. Because if I can really provide you contextual information as a client or as a partner in my ecosystem for you to engage with me better, why would you not do that, right? So I think the notion of real time has changed significantly because one, you're going to have competitive pressures in the marketplace. Either you do it or somebody else is going to do it. So like in the, I would say, when I was in Oracle many years ago, there was a big push for everybody to have an ERP system, right? And a lot of them still didn't know the value of why you needed an ERP system. And it was quite honestly, pure pressure that got them to adopt ERP systems. But I can see that it's changing today, right? The customers are demanding more. And because the customers are demanding more and they have multiple options, our clients are seeing real time no longer as a project or an engineering job in the academia world that it's really applicable today. And it can improve, like I'll give you a classic case. My customers are able to do dynamic program management in the media space because of their ability to crunch clickstream data. They can make changes to even the ad spots management to maximize their ad sales revenue. You know, a lot of the broadcasters, 80% of their revenue comes from advertising revenue. So there's a huge impact. If I can make these adjustments and sell spot rates to my advertisers in near real time and say, hey, you got this opportunity. Do you want to take advantage of it? We're seeing everybody now gravitating from one program to another program. I know you had spent your money advertising within this program and this channel. If you divert your dollars here, you're likely to get a much better hit because of this segment of customers or the demographic of customers that you are targeting. Why wouldn't an advertiser want to do that? So I think to your question specifically, I do believe that real time is going to become the norm. It's probably going to be the right time for you to get things done. And technology is obviously there for you to do it. Give me an example of some customer examples you guys always have great engagements with. You've gone out, they're on the journey, digital transformation, they see all the data and they just want to get started. And then give me an example of someone who's kind of been down that road that you're accelerating more efforts with for digital transformation. So once it's getting started, you've helped them in what they've done and then someone who's in the middle of the path that wanted to pour the gas on, go faster. So let me give you, let me take the same customer example and maybe walk you through that journey. And I'll take a very simple example. This is a banking customer and they would take anywhere between 12 to 16 weeks from campaign idea to execution, right? 16 weeks. So you had a new product offering, you wanted- And these are like new credit card offerings or new mortgage, whatever, just regular financial products. Just sort of a financial project. A financial product. Okay. And they would take, as I said- You just want to give it away. Yeah. It's financial services. Financial services. 14 to 16 weeks from thinking of the product, coming up to the campaign and executing the campaign. And the client was, and the customer felt that this was really delaying product launches for them. Because by the time they would execute this campaign, somebody else would come up with a variant of that product. Now guess what? I got to start again all over again. So they wanted that adaptability. And if you looked at their infrastructure, they obviously ran a state of the art CRM system. They had a certain level of mastering already in place. But if you looked at their mastering, it was very static, right? They would get these refreshers, as I said, every three months and four months to recalibrate their customer profile. So customer profiling was not dynamic at all. Right. And then we went back, and I think they realized that if they bring in, as I said, other contextual data where they could listen, whether it's social data, whether it's other interaction data, just interaction with their call centers, in web logs that showed how the customers were engaging with them, they felt they could get a better sense of what their customers are wanting and buying. So all we did at that point in time was to enhance their customer profiling system to bring in these new data sets, right? And that changed. So if you looked at their cycle time of security, even their own internal data sets, you said their own call centers, it's not even external data sources. It's not even external as yet, right? It's just external in what they've been using, not external from outside the organization. Exactly. So what we found was that a significant portion of that campaign to execution cycle was all around defining, coming up with the set of customers you want to target. So that took the most, that was the big, what do I say, the day it chewed, right? The effort bandwidth was all spent there. So if we attacked just that part of the value chain, our ability to cut down campaign cycle time came down significantly lower. So we brought in this data sets and we were able to bring down their campaign execution cycle down to eight weeks, right? So it was not significant, but it was down to eight weeks, there were 12 to eight. That's 30%, that's pretty good. But our clients are not happy with that kind of change, right? They want quantum leap. So then we said, why don't we bring in social data? So social data gave us, again, another sense of who are the naysayers, how many people are promoters, how many are the influencers. So you don't necessarily want to waste your campaign dollars on customers who are not necessarily positively inclined towards your brand. So just bringing in that sentiment data again gave us the next level of improvement. But now they want hyper personalization, right? So when we talk about hyper personalization, they're saying, I want to be able to, I don't want to be wasting my time building these long drawn campaign cycles. As in when I build products, I must have the ability to offer that product to a customer based on how I see that one individual customer is being relevant to my ecosystem. So when you're talking about hyper personalization, you're talking about reducing the compute cycle significantly, right? You're now saying that I must be able to run this across zillions and gazillions of customer records. And at that point in time be able to say, I'm going to make these offers dynamically right now as these customers are engaging with me. So now I need to bring in, I need to integrate the engagement infrastructure that they have, which could be their social media infrastructure, their whole CRM infrastructure, their CTI infrastructure. So all of that, what you heard today in terms of ability to integrate a lot of these diverse applications that are probably on-premise in the cloud and have a compute platform that has got that distributed ability to acquire data, compute the data and then also not just provide the data but help you execute a business cycle. So you're talking about a smart process, being able to execute on its own without any human intervention. So that's what the clients are now saying, that same client is saying they want to get to. So have you delivered that yet or that's on the road now? That's on the road now, right? So that's when you start using things like Spark, you're looking at, and very interesting concepts, right? So if you look at some of the high compute, I would say high compute techniques or the fast compute techniques today, a lot of them are based on really getting these real-time streaming type of data and being able to kind of compute on the fly and deliver fast data. And now if you kind of commingle that with vast amounts of enterprise data that you're collecting, right? Because you're now going to have a lot of this data that's going to exist in the systems. One is the real-time feeds, next is you've got a lot of these historical feeds that you have collected over time, where also there are some- Bring them together as a key. Bring them together as a key. So today I think there are some challenges that we're going to face as a, I would say as an industry, where we're going to try and combine your ability to take these compute methodologies that are predominantly designed for real-time computing and combine it and mash it with data on rest, right? Because data at rest is very different versus data that's getting streamed in. So I think these are some of the interesting challenges that we're going to face. Yeah, it's an architectural dream for someone who's going to be an disruptor because if you can come in there, take advantage of these new dynamics by taking the at rest data in motion data, bring them together, then you're going to start getting into some very interesting things. And there's some enabling technologies out there like Spark you mentioned, machine learning. And there's also security issues too around all this. But at the same time, that's an opportunity. How far are your customers getting that picture? I mean, do they see the picture and where are they in that journey? Because that's the nirvana, that's the endpoint. We see you got to get to this real-time compute, automation, orchestration, a lot of the cloud concepts. That's the evolution of the cloud. Are they seeing the picture? Are they understand that that's a road? They got to go down. I mean, how many of your customers see that big picture? So I think there are two dimensions that we should look at here, right? One is the customer's preparedness and their own thinking. The second is I think a lot of the service providers today still operate, I would say, in kind of silos in addressing this problem. So what we've done at Cognizant is we've realized that this is not, this is a multi-dimensional issue. It's not just about the data. It's about the application. It's about the infrastructure. It's about that entire ecosystem that needs to go through change. So we've created a new organizational construct called digital works, right? And what digital works is trying to really look at this problem in a more holistic fashion, because we believe there are going to be changes across the layers that are required, whether it's your infrastructure layer, your application layer, your integration layer, your data layer, and even your presentation layer, right? And how you engage with your clients. So we've realized that in order to help our clients really go through this transformation, we need to be able to provide that kind of advisory that addresses all these issues. So part of it, in my opinion, I think customers are ready. A lot of them are concerned that they are grappling with a lot of their legacy systems, and how do they coexist with legacy? Because legacy also has a role to play, right? It runs their business. And they want to do change the business, right? So they run the business and change the business. How do I get to that little balancing act to make sure that I don't disrupt what I've got, but really also transform as I'm going through? And that's what digital works is all about, right? What we're saying is we will look at how do we continue to run and optimize what you have today, and create a path for you to really get that transformation going. So let's look at impactful use cases, and that's a great place to start, right? What can we do to impact your customers and improve customer experience? What can we do to improve revenue assurance? What can we do for you to improve your ability to capitalize on every opportunity to be more profitable, right? So if you look at those kind of use cases and deliver to those use cases, then we find the change being a lot easier, and also our clients are able to get buy-in internally, because there's a lot of change management on the business side, on technology side. It's not, you know, you don't just switch on the button and all of this works, right? So I think that is where I think our customers are, where they're a little unsure, how do they balance the act? And that's the advisory and consulting that we are providing. Well, you guys do a great job. Really appreciate you taking the time to come on theCUBE and give you the final word here, and the segment is Uninformatica World here. What's the vibe here? A lot of folks who aren't here, here at the Cosmopolitan, what's the show like? What's been some of the hallway conversation? What's the vibe share to the audience remotely? What's happening? I think the vibe has been that it's going to be a hybrid environment for some time now. I think all clients are wanting to move to that Nirvana and Holy Grail, where everything is a kind of a seamless structure that can operate and deliver to this, the new ass of the digital world. It is going to be hybrid for a while. There's going to be coexistence of legacy and new technology. I think, as you saw in every one of the keynote addresses and also the breakout sessions, there's a lot of focus around how do I build those integrations and make that easy, low cost, because clients want, I can tell you what my client was willing to accept as a deliverable in six months as a project. He or she wants it in two months. It's all accelerating cycles. So I think a lot of focus, as I said, on faster deployment, easy integration, and how do we get this coexistence that's going to be a reality for some time going, while still not compromising on their ability to move ahead on the whole digital transformation path. I think that's the general vibe that I'm getting out of conversations with people. Arun, Vera, Dara, John, thank you very much for joining us on theCUBE here from Cognizant. We are live in Las Vegas for Informatica World 2015. We'll be right back after this short break.