 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 Informatica World 2015. This is theCUBE SiliconANGLE's flagship program. We go out to the events and extract the soonest noise. I'm John Furrier, my co-host, Jeff Frick. Our next guest is Rob Carroll, who's a VP of Information Quality at Informatica. Welcome to theCUBE. Thank you, great to be here. Pretty interesting time you're living in now. You're on the product side, looking at all the customer activity you guys have, great business model you guys have going on, big data, applications, transformation. What's going on with you guys? Tell us what's going on in your world. Well, you know, we're going through a massive disruption across every single industry where data is becoming the thing that they need to compete. And it doesn't matter what industry, whether it's a regulatory industry and you need it to survive or whether it's just the move toward customer centricity and saying, well, if we don't know our customers better, we're not going to provide the best experience. Doesn't matter how good our products or services are, we're not going to be able to keep them loyal. So every function within every organization needs to figure out how to harness that data somehow. And that's where all these different trends are leading to, are saying, how can we make better use of that data? And you know, we heard the transition from productivity error to engagement error. Love that messaging because it's really about the engagement data. Which kind of is interesting, right? Is it just engaging on Twitter, on social data? Is it retail data, customer data? So describe what is engagement data and how is it evolving? Right, well, I think just starting with the transactional data from the productivity, it's just the data you collect when you actually have a processed interaction with a customer. But engagement, sure the social engagement, Twitter, LinkedIn, Facebook, whatever, but there's also the internet of things. It's all of this machine data. You know, it's not just human interactions, it's device interactions. People are interacting with devices. Devices are interacting with devices. And it's so much data and a lot of it's unusable in its current form. So how do you bring that into a usable format? How do you marry human engagement data, machine engagement data with your traditional transactional data so you actually leverage it to actually change your business? So talk about the customer dynamic right now because it really is a crazy time. You mentioned a bunch of things that make people go, oh my God, you got, I have a silo of data here, I got an island of data there, or a pond, whatever you want to call it. Put it in a data lake and it sounds so magical. Where the hell do I start? Kind of is where people, but they know they need to go to this transformational digital transformation. So take us through that customer problem. The opportunity that they have. Yeah and the data lake or the data swamp concept, if you just do it without any governance or quality concerns, you just throw everything in there and let's see what we can find. But that's the rational experimentation side of it. Let's learn about the new technology and build some competency. But like any initiative, there has to be a business objective. By putting this data in there, you're trying to answer a question. You're trying to serve a need, solve a problem. And if you don't identify that, all the data in the world isn't going to help you because you have to figure out what you're trying to accomplish. So that's really the journey is say, play in these environments, but as quickly as possible, identify some of those squeaky wheels, some of those low-hanging fruit cliches that you can throw out there to say, we're actually going to start delivering value on these investments and that's going to allow us to keep investing and build momentum so we can actually do that kind of cultural shift and technology shift that's necessary. Talk about the investments that customers are making because that's interesting. We talk about data quality is hard. Everyone knows that's a really hard problem. You guys solve that. But the investments have to be made and mostly it's coming from the consumerization trend of hey, I want these apps, I want to put some apps out there and it makes them rethink the whole data equation. So take us through that customer investment. Is it on the app side? Is it across the board up and down the stack? What's your take on that? Clearly billions are still being spent on apps. Apps are just ways to automate enterprise processes. They do a great job of it. But let's think of a typical app, whether CRM or ERP. It's a deterministic set of processes. They say step A goes to step B goes to step C but it's irrespective of what's happening with the data. The next generation, the transformation here is these are data fueled applications that are now being developed and required and that's where we say to saying, okay, let's not assume we know the next step of the process, let's see what the data's telling us. Once the data tells us something, that's going to guide us and recommend the next best step in that process, the next best action, and let the app be subservient to the data which has actually got the context. That's really the goal. That's that whole data driven apps concept. Exactly. When you talk about the digital transformation that the customers are going through, you see more sticks or more nut hammers? Yeah. Goodness or badness? Yeah, well, you know. Carrots, that's what I'm looking for, sorry. Sticks or carrots, what's driving it? Well, you get a little bit of both. You get the early adopters, the real innovators. They're all carrot. They're seeing huge opportunity to differentiate and because they invested early, because they went through all of that hard stuff with quality and hard stuff with connectivity and just getting all this stuff together, they now have this opportunity to differentiate before anyone else can. But the stick's there because everyone else needs to compete with those guys. Certainly on the compliance side of things, big stick, huge stick, right? Two trillion dollars almost a year in U.S. alone to deal with compliance. So you imagine just the data management portion alone is got to be a significant percentage of that all stick. No one wants to spend money on compliance. They just have to. But once you do that, if you can spend that money with that stick and actually make sure it's actually scalable and reusable to support other parts of your business, there's no reason that stick can't turn into a carrot. And that's really the value in terms of the reuse and the scale and the flexibility that we're trying to evangelize. Our best customers may enter with a compliance initiative, but quickly reuse that same technology and that same governance that they put in place to support efficiencies, customer engagement, or other types of initiatives. I mean, you have to deal with the realities in these big, large companies where you have the governance structure, if you will. And so we always want to get to the point of from experts like yourself, like how do you talk to customers and give them the comfort that you can be creative and do experimentation in an organic way and let a thousand flowers bloom and go look for any signals and use the data frictionlessly. At the same time, there's a command and a control. Wait a minute, there we go. We have control. So what's the balance? I mean, who leads, who dances? I mean, how do you have those conversations? I often like to talk about your concept of governance is this balance and this fight between agility and bureaucracy, right? You know, bureaucracy has this awful reputation of being something that slows me down and it's gonna inhibit my ability to be agile and productive. And agility's on this pedestal. Agility, as long as you're agile, everything's great. But I always use the example of like a tourniquet versus a surgical room. One's agility, one's bureaucracy. You know, if you fall off a cliff, tourniquet's great right away, but it's not gonna be a long-term solution at all. But surgical room, that's bureaucracy and it's fullest thank goodness because that's where that policy and that discipline and those repeatable standardized processes could save your life. So put governance in that perspective. You gotta do the right amount of discipline and to make sure that it can be safe and trustworthy to make sure you protect your customer's data, make sure you can be compliant with whatever regulations. But beyond that, allow for flexibility because your business model changes on a daily basis almost and you have to be able to adapt. And if you can't allow your business to adapt, whatever policies you're putting in place. So if you get it right, so if you get it right, the innovation strategy can flower effectively, if you will. If you don't, you're constricted. So what do you see as examples of people who get it right? I mean, what's some examples? You don't have to name names, you can name names if you'd like or give some kind of high-level examples of people who get it right. They have good command and control, good governance, but yet let that agility happen. A great example, our keynote speaker this morning, Devon Energy. They started their data governance initiative back in 2012 because of a compliance edict around greenhouse gases and they had to ensure that they were clean. And that was a catalyst that builds out governance. But now they move to a well-headmaster and they want to get some real efficiency and agility, reduce costs and make sure that they can monitor the effectiveness of these wells. That same governance foundation that they built to ensure compliance, they were able to expand and leverage to support this better decision insights and just information about their well-heads so they can better manage productivity. So that's a great example of someone that leverages. So how much of that was them being proactive and seeing an opportunity to put in a data platform that would enable them to go beyond the initial application space, which was this compliance, versus how much of that was we put it in, we fulfilled our obligation. Oh my gosh, look at the exhaust that's coming off this thing. I think there's an opportunity. Yeah, it was very forward thinking their architects when they made their selection saying, these are the requirements we need to meet. These are the reporting and traceability type requirements we need. Let's make sure we invest in a foundation that's not just going to check those boxes but allow us to actually develop new capabilities beyond that. So they invested in Informatica. We're happy to say and they were able to leverage that to support multiple initiatives beyond and that's the majority of our customers are not a one-time customer. They keep coming back and they keep expanding their footprint into a lot of our different capabilities as they tackle some different, different strategic imperatives. Talk about the case where usually people get in trouble first and they got to go back and build something from scratch. A growing company, you see a lot of companies right now in this new transformation really growing rapidly. They've gone from start-up and then maybe go pre-IPO or go public and they go, well we don't have the HR systems, we don't have to go. And all of a sudden, bang, they're hit with the ton of bricks on their back saying you got to go do something. So how does that use case, how does that company build an effective data governance program and what are the steps and what are some of the things they got to do? Yeah, and I could tell you, we have a data governance maturity model from zero to five. We have a governornewdata.com where customers can go and do self-assessments. We have almost 240 completed assessments. Average maturity across all industries, but over 1.6. On a five scale. At a five scale. Most organizations are still figuring it out and that's okay. The way to do it is forget the big bang. You got to focus. You got to focus on what are you trying to solve for? What's your most critical need that's going to deliver the most business value with the least amount of effort and investment so you can actually deliver those results and build experience, build momentum internally as your culture shifts from being, you know, maybe a product-centric organization into a customer-data-centric organization. It takes time and it's okay. You just got to deliver that incremental value by focusing on your critical few. And once you do that, you're going to continue to have wins. You're going to continue to get that sponsorship and support to invest into that next area. So that's actually comforting for some folks out there to know that. Okay, you don't have to be that good to be good. You're right on the move. But that means it's early. So probably early days, right? It's early and look to some of those that have that early success. We have some fantastic thought leader customers who are doing the right thing for their businesses and evangelizing these best practices on find the sponsor, identify the business case, make sure the business finds themselves accountable for the data and it's not IT's job to find quality because they don't know the definition of quality. It's the business. The business always drives down the business. Rob, talk about this new role, this chief data officer. Very controversial. We've had many crowd chats and conversations on theCUBE about it. When, where, who, who's it report to? There's a lot of conversations. The answer is yes. The answer is yes. But no, it's a fantastic role. Report to the CEO, CIO? I mean, there's a lot of different depending on. All of the above. And because it's a not yet solidified role like a CFO or a CMO, but the one thing that's consistent with the chief data officers that we've come across, they all feel personal ownership and accountability for data governance. They all feel that no matter whether they're reporting to the CIO or the CEO, they feel it's their job to figure out how to operationalize and institutionalize data governance best practices within their organization. Now, some have a whole lot of influence and are able to really drive the process and cultural changes. That's fantastic. A lot of them are still kind of the grassroots. They've got the title and they've got the support to do that discovery and help build the case, but they still have to build the case. And others, they're just trying to raise visibility and awareness and the fact that that job title was even given to someone is a good signal, even if the maturity isn't there yet that they have teeth yet. And it's still early days, so a lot of stuff's evolving in real time. It's like a moving train. You got the apps coming in. What are some of the big things that have surprised you with the past three years in the data governance, CDO role, the role of data being frictionlessly available, which is the trend everyone wants to move to? What has surprised you and what have you learned that have been magnified by some of your experiences? I think on one side, from the CDO conversation, not surprisingly, about almost 50% of financial services companies have identified a chief data officer. I think the fact that commercial, not as highly regulated industries are really embracing this as well. That's been a pleasant surprise. It shows that, you know what, this is something we need to do to remain competitive and to remain effective as a business. So that's been really positive. I think the surprise clearly is just the velocity of new technologies. I think about it, for many years, everyone figured, oh, we're just gonna be consolidating and consolidating and we're gonna try to get as homogeneous as possible. And the market said, no, no, that's not what your aims should be. Your aims should certainly be to rationalize and have just as much as necessary, but not to stop thinking about new emerging technologies that you can really benefit from. So don't worry about homogeneity. Let's focus on the right amount of technology to serve your business and be open and have a flexible enough architecture to be able to experiment with these new technologies. And that's been a pleasant change as well. Yeah, and so you've got things like data as an asset and it's a competitive advantage as one driver. And then security, I mean, the threat of losing data. There's a big driver in all this, right? Yeah, talk about the stick, you know, not being in the front page of any major financial publication is a fantastic driver to put a little bit of resource into this problem. But yeah, protecting your data, not just at the perimeter, but you know, where it lives and where it moves is a critical gap. And it's good that folks are now focusing on that. Rob, thanks for taking the time to share some insights here on theCUBE here at your show Informatica World 2015. Appreciate it. Thanks for taking the time. It's my pleasure. We'll be right back after this short break. Sharon, sharing the data with you here on theCUBE, we'll be right back.