>> Announcer: Live from midtown Manhattan, it's theCUBE. Covering Big Data New York City 2017. Brought to you by SiliconANGLE Media and its ecosystem sponsors. >> Okay welcome back everyone, live here in New York City it's theCUBE's coverage of Big Data NYC. It's our event we've been doing for five years in conjunction with Strata Hadoop now called Strata Data right around the corner, separate place. Every year we get the best voices tech. Thought leaders, CEO's, executives, entrepreneurs anyone who's bringing the signal, we share that with you. I'm John Furrier, the co-host of theCUBE. Eight years covering Big Data, since 2010, the original Hadoop world. I'm here with Amit Walia, who's the Executive Vice President, Chief Product Officer for Informatica. Welcome back, good to see you. >> Good to be here John. >> theCUBE alumni, always great to have you on. Love product we had everyone on from Hortonworks. >> I just saw that. >> Product guys are great, can share the road map and kind of connect the dots. As Chief Product Officer, you have to have a 20 mile stare into the future. You got to know what the landscape is today, where it's going to be tomorrow. So I got to ask you, where's it going to be tomorrow? It seems that the rubber's hit the road, real value has to be produced. The hype of AI is out there, which I love by the way. People can see through that but they get it's good. Where's the value today? That's what customers want to know. I got hybrid cloud on the table, I got a lot of security concerns. Governance is a huge problem. The European regulations are coming over the top. I don't have time to do IoT and these other things, or do I? I mean this is a lot of challenges but how do you see it playing out? >> I think, to be candid, it's the best of times. The changing times are the best of times because people can experiment. I would say if you step back and take a look, we've been talking for such a long time. If there was any time, where forget the technology jargon of infrastructure, cloud, IoT, data has become the currency for every enterprise right? Everybody wants data. I say like you know, business users want today's data yesterday to make a decision tomorrow. IT has always been in the business of data, everybody wants more data. But the point you're making is that while that has become more relevant to an enterprise, it brings into the lot of other things, GDPR, it brings governance, it brings security issues, I mean hybrid clouds, some data on-prem, some data on cloud but in essence, what I think every company has realized that they will live and die by how well do they predict the future with the data they have on all their customers, products, whatever it is, and that's the new normal. >> Well hate to say it, admit pat myself on the back, but we in theCUBE team and Wikibon saw this early. You guys did too, and I want to bring up a comment we've talked about a couple of years ago. One, you guys were in the data business, Informatica. You guys went private but that was an early indicator of the trend that everyone's going private now. And that's a signal. For the first time, private equity finance have had trumped bigger venture capital asset class financing. Which is a signal that the waves are coming. We're surfing these little waves right now, we think they're big but they big ones are coming. The indicator is everyone's retrenching. Private equity's a sign of undervaluation. They want to actually also transform maybe some of the product engineering side of it or go to market. Basically get the new surfboard. >> Yeah. >> For the big waves. >> I mean that was the premise for us too because we saw as we were chatting right. We knew the new world, which was going towards predictive analytics or AI. See data is the richest thing for AI to be applied to but the thing is that it requires some heavy lifting. In fact that was our thesis, that as we went private, look we can double down on things like cloud. Invest truly for the next four years which being in public markets sometimes is hard. So we step back and look where we are as you were acting from my cover today. Our big believers look, there's so much data, so many varying architecture, so many different places. People are in Azure, or AWS, on-prem, by the way, still on mainframe. That hasn't gone away, you go back to the large customers. But ultimately when you talk about the biggest, I would say the new normal, which is AI, which clearly has been overtalked about but in my opinion has been barely touched because the biggest application of machine learning is on data. And that predicts things, whether you want to predict forecasting, or you predict something will come down or you can predict, and that's what we believe is where the world is going to go and that's what we double down on with our Claire technology. Just go deep, bring AI to data across the enterprise. >> We got to give you guys props, you guys are right on the line. I got to say as a product person myself, I see you guys executing great strategy, you've been very complimentary to your team, think you're doing a great job. Let's get back to AI. I think if you look at the hype cycles of things, IoT certainly has, still think there's a lot more hype to have there, there's so much more to do there. Cloud was overhyped, remember cloud washing? Pexus back in 2010-11, oh they're just cloud washing. Well that's a sign that ended up becoming what everyone was kind of hyping up. It did turn out. AI thinks the same thing. And I think it's real because you can almost connect the dots and be there but the reality is, is that it's just getting started. And so we had Rob Thomas from IBM on theCUBE and, you know we were talking. He made a comment, I want to get your reaction to, he said, "You can't have AI without IA." Information architecture. And you're in the information Informatica business you guys have been laying out an architecture specifically around governance. You guys kind of saw that early too. You can't just do AI, AI needs to be trained as data models. There's a lot of data involved that feeds AI. Who trains the machines that are doing the learning? So, you know, all these things come into play back to data. So what is the preferred information architecture, IA, that can power AI, artificial intelligence? >> I think it's a great question. I think of what typically, we recommend and we see large companies do look in the current complex architectures the companies are in. Hybrid cloud, multicloud, old architecture. By the way mainframe, client server, big data, you pick your favorite archit, everything exists for any enterprise right. People are not, companies are not going to move magically, everything to one place, to just start putting data in one place and start running some kind of AI on it. Our belief is that that will get organized around metadata. Metadata is data about data right? The organizing principle for any enterprise has to be around metadata. Leave your data wherever it is, organize your metadata, which is a much lighter footprint and then, that layer becomes the true central nervous system for your new next gen information architecture. That's the layer on which you apply machine learning too. So a great example is look, take GDPR. I mean GDPR is, if I'm a distributor, large companies have their GDPR. I mean who's touching my data? Where is my data coming from? Which database has sensitive data? All of these things are such complex problems. You will not move everything magically to one place. You will apply metadata approach to it and then machine learning starts to telling you gee I some anomaly detection. You see I'm seeing some data which does not have access to leave the geographical boundaries, of lets say Germany, going to, let's say UK. Those are kind of things that become a lot easier to solve once you go organize yourself at the metadata layer and that's the layer on which you apply AI. To me, that's the simplest way to describe as the organizing principle of what I call the data architecture or the information architecture for the next ten years. >> And that metadata, you guys saw that earlier, but how does that relate to these new things coming in because you know, one would argue that the ideal preferred infrastructure would be one that says hey no matter what next GDPR thing will happen, there'll be another Equifax that's going to happen, there'll be some sort of state sponsor cyber attack to the US, all these things are happening. I mean hell, all securities attacks are going up-- >> Security's a great example of that. We saw it four years ago you know, and we worked on a metadata driven approach to security. Look I've been on the security business however that's semantic myself. Security's a classic example of where it was all at the infrastructure layer, network, database, server. But the problem is that, it doesn't matter. Where is your database? In the cloud. Where is your network? I mean, do you run a data center anymore right? If I may, figuratively you don't. Ultimately, it's all about the data. The way at which we are going and we want more users like you and me access to data. So security has to be applied at the data layer. So in that context, I just talked about the whole metadata driven approach. Once you have the context of your data, you can apply governance to your data, you can apply security to your data, and as you keep adding new architectures, you do not have to create a paddle architecture you have to just append your metadata. So security, governance, hybrid cloud, all of those things become a lot easier for you, versus clearing one new architecture after another which you can never get to. >> Well people will be afraid of malware and these malicious attacks so auditing becomes now a big thing. If you look at the Equifax, it might take on, I have some data on that show that there was other action, they were fleeced out for weeks and months before the hack was even noticed. >> All this happens. >> I mean, they were ten times phished over even before it was discovered. They were inside, so audit trail would be interesting. >> Absolutely, I'll give you, typically, if you read any external report this is nothing tied to Equifax. It takes any enterprise three months minimum to figure out they're under attack. And now if a sophisticated attacker always goes to right away when they enter your enterprise, they're finding the weakest link. You're as secure as your weakest link in security. And they will go to some data trail that was left behind by some business user who moved onto the next big thing. But data was still flowing through that pipe. Or by the way, the biggest issue is inside our attack right? You will have somebody hack your or my credentials and they don't download like Snowden, a big fat document one day. They'll go drip by drip by drip by drip. You won't even know that. That again is an anomaly detection thing. >> Well it's going to get down to the firmware level. I mean look at the sophisticated hacks in China, they run their own DNS. They have certificates, they hack the iPhones. They make the phones and stuff, so you got to assume packing. But now, it's knowing what's going on and this is really the dynamic nature. So we're in the same page here. I'd love to do a security feature, come into the studio in our office at Palo Alto, think that's worthy. I just had a great cyber chat with Vidder, CTO of Vidder. Junaid is awesome, did some work with the government. But this brings up the question around big data. The landscape that we're in is fast and furious right now. You have big data being impacted by cloud because you have now unlimited compute, low latency storage, unlimited power source in that engine. Then you got the security paradigm. You could argue that that's going to slow things down maybe a little bit, but it also is going to change the face of big data. What is your reaction to the impact to security and cloud to big data? Because even though AI is the big talk of the show, what's really happening here at Strata Data is it's no longer a data show, it's a cloud and security show in my opinion. >> I mean cloud to me is everywhere. It was the, when Hadoop started it was on-prem but it's pretty much in the cloud and look at AWS and Azure, everyone runs natively there, so you're exactly right. To me what has happened is that, you're right, companies look at things two ways. If I'm experimenting, then I can look at it in a way where I'm not, I'm in dev mode. But you're right. As things are getting more operational and production then you have to worry about security and governance. So I don't think it's a matter of slowing down, it's a nature of the business where you can be fast and experiment on one side, but as you go prod, as you go real operational, you have to worry about controls, compliance and governance. By the way in that case-- >> And by the way you got to know what's going on, you got to know the flows. A data lake is a data lake, but you got the Niagara falls >> That's right. >> streaming content. >> Every, every customer of ours who's gone production they always want to understand full governance and lineage in the data flow. Because when I go talk to a regulator or I got talk to my CEO, you may have hundred people going at the data lake. I want to know who has access to it, if it's a production data lake, what are they doing, and by the way, what data is going in. The other one is, I mean walk around here. How much has changed? The world of big data or the wild wild west. Look at the amount of consolidation that has happened. I mean you see around the big distribution right? To me it's going to continue to happen because it's a nature of any new industry. I mean you looked at securities, cyber security big data, AI, you know, massive investment happens and then as customers want to truly go to scale they say look I can only bet on a few that can not only scale, but had the governance and compliance of what a large company wants. >> The waves are coming, there's no doubt about it. Okay so, let me get your reaction to end this segment. What's Informatica doing right now? I mean I've seen a whole lot 'cause we've cover you guys with the show and also we keep in touch, but I want you to spend a minute to talk about why you guys are better than what's out there on the floor. You have a different approach, why are customers working with you and if the folks aren't working with you yet, why should they work with Informatica? >> Our approach in a way has changed but not changed. We believe we operate in what we call the enterprise cloud data management. Our thing is look, we embrace open source. Open source, parks, parkstreaming, Kafka, you know, Hive, MapReduce, we support them all. To us, that's not where customers are spending their time. They're spending their time, once I got all that stuff, what can I do with it? If I'm truly building next gen predictive analytics platform I need some level of able to manage batch and streaming together. I want to make sure that it can scale. I want to make sure it has security, it has governance, it has compliance. So customers work with us to make sure that they can run a hybrid architecture. Whether it is cloud on-prem, whether it is traditional or big data or IoT, all in once place, it is scale-able and it has governance and compliance bricked into it. And then they also look for somebody that can provide true things like, not only data integration, quality, cataloging, all of those things, so when we working with large or small customers, whether you are in dev or prod, but ultimately helping you, what I call take you from an experiment stage to a large scale operational stage. You know, without batting an eyelid. That's the business we are in and in that case-- >> So you are in the business of operationalizing data for customers who want to add scale. >> Our belief is, we want to help our customers succeed. And customers will only succeed, not just by experimenting, but taking their experiments to production. So we have to think of the entire lifecycle of a customer. We cannot stop and say great for experiments, sorry don't go operational with us. >> So we've had a theme here in theCUBE this week called, I'm calling it, don't be a tool, and too many tools are out there right now. We call it the tool shed phenomenon. The tool shed phenomenon is customers aren't, they're tired of having too many tools and they bought a hammer a couple years ago that wants to try to be a lawn mower now and so you got to understand the nature of having great tooling, which you need which defines the work, but don't confuse a tool with a platform. And this is a huge issue because a lot of these companies that are flowing by wayside are groping for platforms. >> So there are customers tell us the same thing, which is why we-- >> But tools have to work in context. >> That's exactly, so that's why you heard, we talked about that for the last couple, it was the intelligent data platform. Customers don't buy a platform but all of our products, like are there microservices on our platform. Customers want to build the next gen data management platform, which is the intelligent data platform. A lot of little things are features or tools along the way but if I am a large bank, if I'm a large airline, and I want to go at scale operational, I can't stitch hundred tools and expect to run my IT shop from there. >> Yeah >> I can't I will never be able to do it. >> There's good tools out there that have a nice business model, lifestyle business or cashflow business, or even tools that are just highly focused and that's all they do and that's great. It's the guys who try to become something that they're not. It's hard, it's just too difficult. >> I think you have to-- >> The tool shed phenomenon is real. >> I think companies have to realize whether they are a feature. I always say are you a feature or are you a product? You have to realize the difference between the two and in between sits our tool. (John laughing) >> Well that quote came, the tool comment came from one of our chief data officers, that was kind of sparked the conversation but people buy a hammer, everything looks like a nail and you don't want to mow your lawn with a hammer, get a lawn mower right? Do the right tool for the job. But you have to platform, the data has to have a holistic view. >> That's exactly right. The intelligent data platform, that's what we call it. >> What's new with Informatica, what's going on? Give us a quick update, we'll end the segment with a quick update on Informatica. What do you got going on, what events are coming up? >> Well we just came off a very big release, we call it 10-2 which had lot of big data, hybrid cloud, AI and catalog and security and governance, all five of them. Big release, just came out and basically customers are adopting it. Which obviously was all centered around the things we talked in Informatica. Again, single platform, cloud, hybrid, big data, streaming and governance and compliance. And then right now, we are basically in the middle, after Informatica, we go on as barrage of tours across multiple cities across the globe so customers can meet us there. Paris is coming up, I was in London a few weeks ago. And then separately we're getting up for coming up, I will probably see you there at Amazon re:Invent. I mean we are obviously all-in partner for-- >> Do you have anything in China? >> China is a- >> Alibaba? >> We're working with them, I'll leave it there. >> We'll be in Alibaba in two weeks for their cloud event. >> Excellent. >> So theCUBE is breaking into China, CUBE China. We need some translators so if anyone out there wants to help us with our China blog. >> We'll be at Dreamforce. We were obviously, so you'll see us there. We were at Amazon Ignite, obviously very close to- >> re:Invent will be great. >> Yeah we will be there and Amazon obviously is a great partner and by the way a great customer of ours. >> Well congratulations, you guys are doing great, Informatica. Great to see the success. We'll see you at re:Invent and keep in touch. Amit Walia, the Executive Vice President, EVP, Chief Product Officer, Informatica. They get the platform game, they get the data game, check em out. It's theCUBE ending day two coverage. We've got a big event tonight. We're going to be streaming live our research that we are going to be rolling out here at Big Data NYC, our even that we're running in conjunction with Strata Data. They run their event, we run our event. Thanks for watching and stay tuned, stay with us. At five o'clock, live Wikibon coverage of their new research and then Party at Seven, which will not be filmed, that's when we're going to have some cocktails. I'm John Furrier, thanks for watching. Stay tuned. (techno music)