 Live from San Francisco, it's theCUBE, covering Informatica World 2016. Brought to you by Informatica. Now, here are your hosts, John Furrier and Peter Burris. Okay, welcome back everyone. We are here live in San Francisco for Informatica World 2016. This is SiliconANGLE Media's theCUBE, our flagship program where we go out to the events and extract the signal from the noise. This is the conclusion of our two days of wall-to-wall live coverage. I'm John Furrier, my co-host Peter Burris, and our next guest is Anil Chakravarti, who's the CEO, Chief Executive Officer of Informatica. Formerly the Chief Product Officer, you might have recognized him on theCUBE two years ago. And then last year we had the Informatica 20th World Tourism. Welcome back to theCUBE. Great to see you. You got a promotion, this is your last talk. You know the CEO. Yeah, good to see you, John. Good to see you, Peter. Good to see both of you. I say in tongue-in-cheek, I'm a big fan of what you guys have done, and I only go back two years when we were on theCUBE at AWS re-invent 2014. I remember saying to myself, hmm, this guy's smart, but I must say Informatica. They just get that old school data warehouse, but I was blown away because you were really on top of data engagement data. Really stuff that was really known and was really talking about at that time. So very clear, you guys had the right vision. You made good bets, the right bets. Two years later, it's panning out. What fruit is coming off that tree right now? I know, we essentially got a two-year head start on the market because of that. We read it correctly that what was really going on was a revolution in the data market that was leading to an opportunity to focus on data as an independent platform, rather than the exhaust from operational systems, as Jim likes to say. And so we call this new age as the age of data 3.0. Opportunity to build new business models based on data. And some of the fruits of that vision, the big ones are what you've seen a lot and heard a lot at this show, live data map, which is your own internal Google for your data inside the enterprise and in the cloud. What data do you have? Where is it? Who has access to it? Is it sensitive or not? Essential questions that everybody has about their data, but hard to get answers. Easy to ask the question, hard to get answers. Live data map helps provide those answers. Cloud MDM also getting a lot of buzz. Absolutely. Again, re-invent, like, oh, I'm not gonna. You've had a cloud strategy from day one to be Switzerland, being all clouds. That's exactly right. And that is a big feature. Talk about the MDM, why is that so important? Yeah, it's basically exactly what we thought about as we talked about the intelligent data platform being on-premise in the cloud and hybrid. That was a vision we talked about two years ago. Cloud MDM fits squarely in that. We recognize that MDM, the core technology we have around MDM, that's our intellectual property. Where that is run is really depends on where the data is. If the customer's data happens to be on-premise, we run it on-premise. If the customer's data happens to be within Salesforce, we run it within Salesforce. If the customer wants to run it on Amazon, which is what we're doing with Cloud MDM, we run it on Amazon. So the real advancement there is being able to make it work in a hybrid manner so that you can have data sources anywhere you want on-premise in the cloud and be able to run your Cloud MDM in the cloud. So we're really happy to have this out in a lot of bus. It's simply the keys of the kingdom. I think I used the word keys of the kingdom when we talked about MDM back then. I got to ask you because it's a longer journey. You guys have picked the right vector. Certainly the right team was seeing Jim pointed out as well. And that is that you don't want to get ahead of yourself and get over your skis, as they say. So you don't want to overplay your hand, try to force it too much. So I got to ask you the question. How are you managing that? Because you're now increasing your total addressable market now by elevating the business outcome scenario. Versus being in the trenches, under the hood with great data governance technology, which is where Informatica came from. But you're also sticking to that same formula of data governance. But now you have this new TAM expanding. How are you managing that? Because you're the CEO, you got to keep the troops kind of focused and disciplined. How do you do that? So that's what we're doing. Basically we're in six key markets. And the good thing is those markets are growing. The TAM is expanding because we've stayed in those same six key markets. And the TAM is expanding better lucky than good I guess. So for us, those markets are data integration, data quality, master data management, big data, data security. So those are the key markets that we're in, the six key markets that we're in. And in those markets, each one of them, the TAM is expanding and that cumulative effect is where you're getting the expansion of TAM. Well, the one TAM that's kind of embedded in all those that's rising the tide is security. Bill Burns was on earlier. That's correct. And there's also that's a tie into the cloud strategy. You kind of piece that together in real time. Not real time, but as you rolled out to the cloud with Amazon, you had to kind of fix the security. Exactly. Can you expand on that and why that happened? Yeah, absolutely. And we talked about it two years ago. We were the first ones to even start talking about it. And the reason we got into the security market is a fundamental belief that we have that the right way to do security is by being aware of the data, to have the context of the data, because otherwise, what are you really protecting? If I'm protecting a machine which has no worthwhile data on it, why would I spend any money on that? I mean, I don't care if somebody hacks it, there's nothing on it. But whereas when I know something is really sensitive, I want to make sure that that is really protected. Now how are you going to know that if you don't have the data context? So we said, you know what? We're sitting at the right place in the infrastructure to do data security. And that's what has led to this huge explosion in how we can integrate data security into other parts of the platform and deliver something in the market that nobody else has. So if you think about the question then of the evolving role of data, and you're an executive. Yep. It's data as an asset becomes a conversation that's not relegated to a product, certainly not infrastructure, but has to be elevated to a conversation about what the business does and how it goes about doing it. So what kind of conversations are you having with fellow CEOs about the role that data needs, how they need to look at data within their businesses? Well, you know, I'll tell you, this is, the timing is perfect for that. You know, we had, yesterday, we had something called the executive summit that was over at the Intercontinental. We had planned for it to be about 100 people. We've finished at over 150 people, jam-packed in the room, and it was exactly for this reason that you just outlined. There's a ton of interest. A lot of people have been thinking about this executive CEO's boards, have been thinking about this from a variety of different angles. You know, some of them have thought about it because they've heard about the digital economy. Everybody wants to be part of the digital economy. So that got them thinking, what do I need to do to be part of the digital economy? They quickly realized, data is a big part of that. Some people start with, they've heard of things like the Internet of Things and what's going on, and they go, what does that mean for me? Well, I need to do data. A third set of comparators, they look at the ubers of the world and others and say, what if I get disrupted? Or what do I need to do to make sure I don't get disrupted? How do I change my business? Well, again, data is a part of that. So the good thing is, as people have thought about it a little bit more, they've already come to the conclusion that their data, their backend, their systems, all play a critical role in that transformation. So we believe that the timing is right. I just actually joined the board of a company called the USAA Bank. You know, USA is one of the biggest insurance companies in the world, financial services companies in the world. One of the best client experience companies in the planet. And that's the reason I joined it. I wanted to learn from them on that. But they asked me to join specifically because of my experience in data and digital systems. And that tells you exactly what you asked for. This is a board level issue and I joined the board for that reason. So let's talk about the relationship between data and digital. And I'll put forward a thesis. I'd like to see, you know, agree, disagree, and then expand. Okay. Everybody talks about digital. Often they do so without even talking about data. So they talk about what the outcomes might be or what the capabilities might be. But at the end of the day, if it ain't data, how can it be digital? That in many respects, the whole motion of the digital economy or digitization or digital strategy is how are you going to transform more of your business into data so that you can utilize the economics and the other possibilities associated with data processing? What do you think about that? No, I completely agree. Data is an essential element of making your digital strategy work. I mean, people start talking about digital. Once they start mapping it out in any detail, they quickly realize that's when they need the data. That's what we mean by data 3.0. For instance, take a bank just to continue that example. Actually every bank is saying, look, I want all of my banking services. You know, maybe my checking account, my savings account, my loans, my credit cards, brokerage, everything available via mobile application. So you have a mobile app, you click on the mobile app, you want to be able to do all of these services. Well, that hits the back end, that has security, that has all kinds of implications. So if you want to be able to do that digital transformation where you become a mobile bank, there's a lot of data that's required at the back end to make it happen. And this is true in industry after industry. You're an airline and you want to provide a mobile app. So it's great for initially small things, but if you want people to be able to manage their entire experience with you, you got to have all of your data available through that mobile app. So we had a couple of great guests come on, some board members came on. So, you know, Jerry Held was, we'll start with him. He really talked about the real time. And I love his point that I want to get your take on. This is something that we kind of teased that a couple of years ago, but it's certainly very relevant now. In the moment now, data really is one of the most valuable assets, but can get stale very quickly. But he kind of talked about that, that dynamic. And his point was people are looking back to get insights. That's kind of like been there, done that. People are doing that. People look forward, take their old data and try to predict it forward. But it's very difficult to get there here and now. You guys are really focused on this now. We're streaming. That's right. What's the strategy? What's the directive? What's the product focus with real time? Yeah, first of all, Jerry has been enormously influential in shaping our roadmap. He has so much experience and he brings from the industry that he's been very helpful to us. The strategy is really simple. In the past, we had a difference between operational systems and analytical systems. You want to do an analysis, you know, you had data transferred over on a batch basis and you could do the analytics on day old data, maybe six hour old data, et cetera, didn't matter. Now those systems are together, a great example. One of our customers, big airline at the Hub Airport, what they want to do is they're getting alerts on flight status all the time. So they want those alerts in real time and then they check that, the manifest and say, or any of our top tier passengers on those flights that are getting delayed. If somebody, one of the top tier passengers is there, they want to send an agent to the gate, rebook those passengers, or if there's a flight that's not available, take the passenger, tell them when the next flight is, escort them to the lounge and make them feel good so that they have a great experience. You got to do that in real time. There's no point in doing it next day, the flights have all gone. Minutes count, yeah. Minutes count. And that's an example of a system that's both operational and analytical. You had data come in in real time, but then you had to actually join the data with your mileage club and all of that data to know who's really your top tier customer and then you had to take an action based on that. That's the kind of- That's disparate data in context to a situation that's analytical and operational and valuable. But you can apply that to any business process. Yeah, and some are worth doing, some are not worth doing. You try to do it with everything, you're going to lose your shirt, right? I mean, you got to make sure that you're doing it only for those top tier passengers. Well, one, is the data available? Is the data available and is it worth doing? There's ultimately a cost-benefit analysis. But there is no process for defining how that works, right? So that's one of the biggest challenges here. That's exactly right. We're looking at the data to discern the patterns that are associated with customer experience and loyalty and et cetera. And then we are utilizing the data to then create. That's correct. When Jim was here, I'm sure he talked to you about this enterprise data competency model. Yes, absolutely. That's exactly to your point, which is how do we help our customers understand what they do with the data and what is valuable? Where do you want to go be at level five? Where do you want to be at level two or level three? And that depends on your business and your business model. That's exactly what we're trying to do. So we talked about that, it's a great progress bar for customers to put it, you know, feel out where they are in the different spectrum of that. But the other theme to build on that is integration. You know, the data hub that you guys have is very interesting in Navels, SaaS developers. But the notion of how do I integrate? So you guys are Switzerland, I get that strategy. That's technically an integration hub as a company, as a product technology. Data quality matters. Now, so I got to ask you, not data quality question in general, but how is data quality changing? You bring in real time, the word quality means something different. It might be bad data that's now good data to transform because of the situation, the context. How is quality changing? Yeah, the way the data quality is changing is you look at what do you need for that business process? So you might need one level of quality for data. You're a bank and you're showing some reserve, capital reserve data to your regulators. That's a level of quality that you need. Every number needs to be right because you lose your credibility with your regulator if the numbers are wrong. Now, in the world of real time, what you want from quality is, you're getting, say, data off of a machine. This is an engine, the flight just landed, you're just taking data off the engine. You're going to do a quick analysis on that. And what you're looking for is a range, right? Temperature, pressure, all the key ranges you're looking for and as long as it's within that range, it's good quality, you let it be. If something is not in range, you want somebody to look at that engine right away. It doesn't have to be perfect. You just give it a range and say, this is the normal range. It's been a six hour flight. I expect the pressure and temperature et cetera to be in this range. If it's not, somebody should look at it. If it's in range, it doesn't matter, it doesn't have to be ultra precise. But that's something, I mean, that's a great example, because it's really a two part decision. Is the data accurate and the engine's wrong? Yep. Or is the engine accurate and the data's wrong? And it doesn't matter because in that case, it's just a life or death decision, exactly. And so it draws forward this key connection between process in the physical world. That's exactly right. And process in the digital world and the outcome is the same. You have to get high quality, reliable, accurate data because in many respects, that's what the business is making the decision on. It doesn't know anything about the engine unless the data's available. That's exactly right. And then there's ways to, that's where you do the analytical processing. That's where our tools can help is, so I was just talking to one of the customers here. They are getting real time streaming data out of the ICU. Why? Because they want to develop a process where they check it in real time and even before the patient is wheeled out of the ICU, if they feel that there is, something is wrong here. Just keep the person in the ICU until we know. Now that's, there the range is much narrower, right? There the range is like, hey, oxygen levels, et cetera, et cetera. They go, look, look, there's something here. Maybe we should take a second look because one of the big things in hospitals is if you move a person out of the ICU prematurely, the chances of fatalities is a life or death situation. So if you keep them, keep them at the ICU if you feel that there's, so those are the kinds of things we're talking about. I think these are phenomenal applications of real time data. So let's talk about this notion of applications because one of the things that both John and I are passionate about is the eventual role that development and developers are going to play in this space. So here's the scenario. We like to say that the first 50 years of the computing industry were dominated by known process, unknown technology. Accounting, HR, known process could turn them into programs. What do we run them on? Client server, mainframe, a lot of others. Had it, the entire industry was structured on that. I like that, have you trademarked it or can I use it? We're, more than welcome. Today's world is about unknown process, known technology. Right. We got the cloud, we know how it works. You know, there's degrees of variability but it's all pretty well coming into focus for us. But it's unknown process. And you identified, for example, in that ICU, that notion of they want to create a process by looking at the data that reveals patterns. How do we, in this, we know how to develop applications in the known process, unknown technology. How does, how is Informatica going to galvanize, catalyze, get the development universe excited to go from data, data patterns, process applications? You know, we believe that we don't have to reinvent the wheel there. The world has done so much work on processes. You know, some of them are probably too extreme for a lot of our developers. Think Six Sigma, for example. But there's a lot of good work done on how to look at processes from various perspectives. You basically look at the outcomes and you develop a process based on that. Data is no exception. So what we are doing with this data competency model is saying you are looking at data to serve an outcome. Now, the process you build around it is exactly what you did with Six Sigma or other things. These are companies that are probably not using Six Sigma, if you were manufacturing, you did. If you were healthcare, you didn't do that. But you could use elements so that there's nothing in there which basically, you can simplify it for your purpose. But you basically say, this is the outcome I want and here's the process and here's the role that data plays. I think he's saying, that's interesting that your point is as these new unknown processes emerge, those are innovation opportunities. IoT is a great example. And what's interesting is you can't automate what you don't understand. Correct. What's the opportunity? How do you be agile? Exactly. And as you bump into these new patterns and revelations or inventions and you want to innovate on those, you got to have the data. Correct. So the data is part of the identification of the process. And the innovation process. And the innovation process. Then you automate it. That's correct. So the question is, this is kind of a visionary question so I'll put you on the spot. DevOps was a great movement. DevOps fueled Amazon and new developer community because you had developers who didn't want to deal with operations. Just provision whatever I want at any time. Elastic resources. Seeing a dev data ops, a new layer with data, with the developers. I don't really want to deal with the data. I don't want to get involved in all that complicated compliance regulations. The new regulations come around the corner on drone data and IoT data. I don't want to deal. I'm just writing native apps. That's a new opportunity. That's a huge opportunity. Share your thoughts on this dynamic. It's kind of unknown, but is there a DevOps-like effect? You're almost looking at what's going to come from next from Informatica. It's kind of like the data cloud, which is you can think of, hey, you're a developer. Just like you've used a lot of other tools, then the interfaces are well understood and clean. Same thing's going to happen with data. We're going to say, look, these are the different types of here's, if you want to use SQL, here's what the data models look like. If you want to use Hadoop, this is what it looks like. If you want to use no SQL, this is what it looks like. And then we basically use those data types to fuel a data cloud, and then everything else follows, like provisioning, et cetera. Anil, thanks for sharing. It's your future roadmap of Informatica. You're a private company. No, it's going to, the stock price is not going to drop. It's only going to go up. No, it's only going to go up, exactly. Thanks so much for sharing, like you. They're literally going to pull the plug here live. They're setting up for the big party. Congratulations on all your success. Congratulations on the sell out here. And it's great to be following you guys and feel free to use anything that we said you can use it, we're sharing it. We're all open, and thanks for spending the time. Wonderful discussion. Thank you very much, Peter. We're watching theCUBE here live, wrap up for Informatica World. We're here with the CEO, and he'll be right back with us. We're not going to be right back. That's a wrap from Informatica World. I'm John Furrier with Peter Burris. Thanks for watching. It's always fun to come back to theCUBE because the discussion is always interesting and relevant.