Live from San Francisco, it's theCUBE, covering Informatica World 2017, brought to you by Informatica. Hello everyone, welcome back to theCUBE coverage, exclusive coverage of Informatica 2017. We are live in San Francisco, breaking down all the action for Informatica's big conference Informatica World 2017. I'm John Furrier with SiliconANGLE theCUBE. My co-host Peter Burris, head of research and also general manager wikibon.com. Check it out. Great research there. Next guest is Richard Cramer, chief healthcare strategist for Informatica. Welcome to theCUBE. Thank you, John. Great to see you. We just talked before we went live about you love data, you love customers and healthcare is booming. Certainly healthcare is one of those use cases. It's a vertical that everyone can relate to, one, two. It's the most dynamic with data right now and internet of things, connected sensors. We know what a room looks like, it's a zillion things connected. Now you got wearables. Still you got the data problem. It's never going away. Certainly it exists there, but now it's changing. So break it down for us. What is the challenges and drivers right now in the healthcare industry relative to getting great software and great solutions to help patients? Well, you're 100% right. One of the things that's exciting about healthcare is it matters to all of us. Every one of us is a patient. Every one of us has a horror story of interacting with a healthcare system. And so when we look at the opportunity for data, healthcare is historically not used data very well. We had the high tech act in 2009 that got electronic healthcare records in place. We're coming out of the backside of that. So arguably for the first time, we finally have the deep rich clinical data that we've needed to do analytics with for the first time. We now have the technology that's coming around with what we call data 3.0 and big data processing power. And then as you mentioned, internet of things and all of the rich sources of new data that we can do discovery on and learn new things about how to treat patients better. And then really the final component is we have the financial incentives are finally aligned. We used to in healthcare pay for piecework. The more you did, the more you got paid. And shockingly, we were inefficient, we did too much. And now we're changing to paying for value. And we can pay for value because we can finally measure quality and outcomes because we have the data. And so that's really the analytics opportunity that's so exciting in healthcare right now. What's interesting is in this digital transformation and business transformation and all the conversations we've had over the years in theCUBE and we go to all the top shows in the enterprise and emerging tech. You're seeing one pattern. We had the Chicago Cubs on yesterday talking baseball, but whether it's sports, business, or healthcare or whatever vertical, there's kind of three things. And we'll take baseball, right? Fan experience, how to run the players and the team and how to run the organization. Healthcare is the same thing. How to run an organization, how to take care of the players, the doctors and the practitioners. And then also the end user, the fan experience, the patient experience. So now you have, it used to be, hey, are we running our organization and the practitioners were part of that, maybe subordinate to it, maybe they interacted with it. But now like a baseball team, you have, how do I run my organization? How do I make the players, the doctors and practitioners successful? And now the patients, the end users are now part of it as well. This is opening up massive innovation opportunities. What's your reaction to that and how should people think about the data in that context? So I think the first piece of what you said is very true, which is really for the first time, healthcare organizations are behaving like real businesses. When you start to get paid for results, you now care about a lot of things that you didn't care about before. Patient experience matters because consumers have choice, those types of things. So all of those digital transformation examples from other industries are now relevant and front and center for healthcare organizations, which is radically different. And so that opportunity to use data and use it for a specific purpose is very valuable. I think the other thing that's important with digital transformation is historically healthcare is very local. It's regional. You go to the hospital that's closest to you. And digital disruption is all about removing geographic barriers. The goal in healthcare today is where we're reducing costs. You want to push healthcare out of that high cost hospital into the most cost effective, highest quality organization you can. That may be a retail clinic in a shopping mall. And how do you do that? You do that with digital technology, telehealth in the home. All of those types of things are traditional digital transformation types of capabilities that healthcare is not traditionally cared about. So optimizing a network effect, if you will. We always hear in network, out of network is a term. We go, my wife and I go, oh, it's in network, oh good. So out of network always kind of means benefit. But now you're talking about a reconfiguration of making things much more efficient as piece parts. It, well, exactly right. And the idea of the network, the network used to be drive everybody to the hospital because that's where we made our money. Well, when you're getting paid for results, the hospital's a cost center, not a revenue center. You actually want to keep people out of the hospital. And as a consumer and as somebody who's paying for healthcare, that's actually a good thing. If I can avoid going to the hospital and get healthcare in a more convenient setting that I want to do at home or someplace closer to home and not be admitted to a hospital, hospitals are dangerous places. Peter, you've been doing, I've seen you and I comment on the Facebook all the time. Certainly the healthcare thing sparks the conversation, but big data can solve a lot of this stuff. I know you're doing a lot of thinking around this. Well, so there's a fascinating conversation. I'd say a couple of things really quickly and then get your take on them. First off, a lot of the evidence-based management techniques we heard about yesterday originated in healthcare because of the- You mean like data management and all that stuff? Because of the peer review, how we handle clinical trials, the amount of data that's out there. So a lot of the principles about how data could be used in a management framework began in healthcare and they have kind of diffused through the marketplace, but the data hasn't been there. Now there's some very powerfully aligned interests. Hospitals like their data, manufacturers of products like their data, doctors like their data, consumers don't know what to do with their data. They don't know what value the data is. So if we take a look at those interests, it's going to be hard and there's a lot of standards, there's a lot of conventions, each of those groups have their- So now the data is available, but the integration is going to be a major challenge. People are using HIPAA as an excuse not to do it, manufacturers and other folks are using other kinds of excuses not to facilitate the data because everybody wants control of the final money. So we've heard a lot at the conference about how liberate the data, free it up, make it available to do more work. But the second step is integration. You have got the integration problem of all integration problems and data. Talk about how some of the healthcare leaders are starting to think about how they're going to break down some of these barriers and begin the process of integrating some of their data so they can in fact enact different types of behaviors. Yeah, and great context for what's happening in healthcare with data. So if you think of five, six, seven years ago at Informatica, my role was to go and look at what other industries had done for traditional enterprise data warehousing and bring that knowledge back into healthcare and say healthcare, you're 10 years behind the rest of industry, here's how you should think about your data analytics. Well, that's completely different now. The data challenge as you've outlined it, we've always had data complexity, we now have Internet of Things data like nobody's business and we also have this obligation to use the data far more effectively than we ever had before. Well, one of the key parts of this is that the idea of centralizing and controlling data as a path to value is no longer viable. We can argue whether it was ever successful but it really is not even an option anymore. When you look at the proliferation of data sources, the proliferation of data types, the complexity, we simply can't govern data to perfection before we get using it, which is traditionally the healthcare approach. What we're really looking at now is this whole idea of big data analytics applied to all data and being able to do discovery that says we can make good decisions with data that may not be perfect. And this is the big data, put it into a data lake, do some self-service discovery, some self-service data preparation, reduce the distance between the people who know what the data means and being able to get hands on and work with it so that you can iterate and you can discover. You cannot do that in an old-fashioned EDW context where we have to extract, transform, load, govern to perfection all of the data before anybody ever gets to use it. That's why I'm excited about data in motion. Well, even data, we'll get to that in a second, I think of support, but even before we get there, John, I mean, again, think about how powerful some of these are. Drug companies keep drug prices high in the US because they have visibility into the data, the nature of the treatments, et cetera. One of the most interesting things, this is one of my tests with you on, is that doctors, where a lot of this evidence-based management has started because of peer review, because of their science orientation, even though they get grooved into their own treatments, generally speaking, are interested in exploring new pathways to health and wellness. So, do you have a very powerful user group that will adopt this ability to integrate data very quickly because they can get greater visibility into new tactics, new techniques, new healthcare regimes, as well as new information about patients? Are doctors going to be crucial to this process, in your opinion? Doctors are going to be crucial to the discussion. We had a healthcare breakfast with a speaker from Deloitte the other day who talked about using data with clinicians to have a data discussion. Not use data to tell them you're wrong or whatnot, but actually to engage them in the discovery process of here's what the data shows about your practice. And you talk about the idea of data control, that's absolutely one of the biggest barriers. The technology does not solve data control. In the old days, everybody admits we have silo data, we have HIPAA. It was so hard to break down those barriers and actually share data that nobody really addressed the fact that people didn't want to, because they couldn't. Well, now with the technology that's available. It's possible, aren't it possible? Yeah, now it's possible to actually get data from everywhere and do things with it quickly. We run into the fact that people have to explicitly say I don't want to share. But here's where that data movement issue becomes so important, John, and I think that this is a play for Informatica because metadata is going to be crucial to this process. Giving people who do have some understanding of data, clinicians, physicians, because of their background, because of the way that medicine is supposed to be run at that level. Giving them visibility into the data that's available that could inform their practices and their decisions is really crucial. Absolutely, one of the good friend who's a clinician has been asking for years, he says, if all you did was give me access to data about my patients so I could explore my own clinical practice. He says, I'm guaranteed I take care of diabetics the way I learned in medical school 25 years ago. There has been a lot of innovation in that and just having the perspective on my own practice patterns and patterns from my own data would change my behavior. And typically, I haven't been able to do that. We can now. So I got to ask you, so let's get down and dirty on informatica, because first of all, I think the instrumentation of everything now is a reality. I think people now are warming up to it, certainly in levels. Super hot to like, I realize it's a transformation area. What are you guys saying to customers? Because they're kind of drowning in the data. One, two, they are maybe held back because a hip end of the things, now it's time to act. So the art of the possible, things are now possible. Damn, I got to get a plan. So they're hustling around to put a plan together, architecture, plan. What are you guys pitched to customers? What is the value proposition that you go in and take us through an example, a use case of a day in the life of your role with customers? So I have the best job in informatica. I get to go out and meet with senior customer executive teams and talk about data, how they're going to use data and how we can help them do it. So it's the best job in the company. But if you look at the typical pitch we start out, we first, we get them to agree with the principle centralizing control is dead, being able to manage data as an enterprise asset in a decentralized fashion with customer self-services the future reality. And everybody universally says, yep, we get it, we agree. So then we talk, check. But then we talk about what does that actually mean? And it's amazing how at, you know, every step in my presentation, the 20 questions always at the same, it comes down to well, how do we control that? How do we control that? How do we manage it? And so you start with, you think of this idea that says, hey, decentralized data, customer self-service, well, you got to have a data catalog. Well, enterprise information catalog is a perfect solution. If you don't know where your data assets are and who's using them, you cannot manage data as an asset. And they're comfortable with that because that's the old mindset of the warehouse, you know, like that big fenced in organization. But now they say, okay, I can free it up and manage it with a catalog and get the control I need. That's right. And so the first piece is the catalog. Well, then the minute you say to people, the catalog is the way to get value from your data. There's somebody in every room that says, ooh, that value represents risk. It's like, you're telling people, see data and make data easy to find. That can't possibly be good. It's risky. Well, then we have secure source was the opposite product from enterprise information catalog that says, here's the risk profile of all of those data sources for HIPAA and protected health information. So we got a great answer to that question. And then you look at and you say, well, how do I fundamentally work with data differently? And that's the idea of a data lake. Rather than making data hard to get in so it's easy to query, which is the traditional enterprise data warehouse. And even people who do enterprise data warehousing, well, you know, little secret is takes too long cost too much and it's not agile. We're not suggesting for a second that a centralized repository of trustworthy data governed within an inch of its life so that it can be used broadly throughout the organization without people hurting themselves. It's not good. It can't be the only place to work with data. Takes too long cost too much and it's not agile. What you want is the data lake that says put all the data that you care about in a place, big data, IOT data, data that you don't know what you're going to use and apply effort at query time only to the data that you care about. And we were talking about, you know, cleanliness and hygiene yesterday versus heart surge and all the different roles in the organization. The big fear that we hear from customers that we talked to on theCUBE and I want to get your thoughts on them and reaction to this is that my data lake's turned into a data swamp because it's just, I'm not using it.  I'm not managing it properly. I'm not vectoring it into the right apps in real time, moving it around. Your reaction to that objection. Early days of the data lake absolutely data swamp because we didn't have the tools, people weren't using them correctly. So just because you put it in a data lake doesn't mean that it's ungoverned. It doesn't mean you don't want to put the catalog on it so you know what's there and how to use it. It doesn't mean you don't want to have end-to-end transparency and visibility from the data consumer to the data source because transparency is actually the first level of governance. That's what provides confidence. It's not agreeing on a single version of the truth and making sure the data's right. It's just simply allowing the transparency. And so when you have a data lake with a catalog with intelligent data lake for self-service data preparation with the ability to see end-to-end what's happening with that data, I don't care that it's not been governed if I can inspect it easily and quickly to validate that your assumptions are reasonable because this is the biggest thing in healthcare. We can't handle the new data, the IoT data and the scope of things that we want to do that we haven't thought about the old way. Yeah, we have limited time for that. One last question. Sure. Framingham Heart Study has shown us that healthcare data ages differently than most other data. How do we anticipate what data is going to be important today and what data is going to be important in the future? Given that we're talking about people and how they age over time. So the key thing with that, and we talked about it earlier, you can't analyze data that you threw away. And so a big part of this is if the data might potentially be of interest, staging. And don't put it in an archive, don't put it someplace in a database backup. It's got to be staged and accessible, which is the data lake. And ready. And ready. And you can't have distance between it. Somebody can't have to go and request it. They need to be able to work on it. And that's the revolution that really is represented by data 3.0. We finally can afford to save data, huge amounts of data that we don't know we care about. Because somebody may care about it in the future. That's right. Great, Richard. Great commentary, great insight and appreciate you coming on theCUBE and sharing with update in the healthcare. Obviously it's super important. Again, they're running like business, a lot of optimization, a lot of changes going on. You guys are doing some good work. Congratulations, data 3.0 strategy. Hopefully that'll permeate down to the healthcare organizations and hopefully the user experience, me, the patient, when I go in, I want to be in and out of the hospital. And also preventative, which I'm trying to do a good job on, but too many CUBE interviews keeping me busy, I'm going to have a heart attack on theCUBE. No, I'm only kidding. Great coverage here at Informatica World in San Francisco. I'm John Furrier, Peter Barris. More live coverage of day two at Informatica World's CUBE. We'll be right back, stay with us. Thank you.