 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. This is our event we've been doing for five years. In conjunction with Strata, Hadoop, now called Strata Data, right around the corner in a separate place. Every year we get the best voices in tech, thought leaders, CEOs, 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 Wally, who's the executive vice president, chief product officer for Informatica. Welcome back, good to see you. Good to be here, Doc. Yeah, CUBE alumni, always great to have you on. Love product, we had Ed Rune on from Orton Works. I just thought that. Product guides 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's 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. 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 think 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 are 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 cloud, some data on-prem, some data cloud, but in essence, what I think every company's realized that they will live and die by. How well do they predict the future with the data they have around their customers, products, whatever it is? And that's the new normal. Well, I hate to say, I admit, Pat myself on the back, but we in the CUBE team, Wikibon saw this early. You guys did too. And I want to bring up a comment that 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 financers have trumped bigger venture capital asset class financing, which is a signal that the waves are coming. This is what we're surfing these little waves right now. We think they're big, but the big ones are coming. The indicator is everyone's retrenching. Private equity is 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. 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 market sometimes is hard. So we step back and look where we are as you were at Informatica world today. Our big belief is, look, there's so much data, so many varying architectures, so many different places. People are in Azure, 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 new normal, which is AI, which clearly has been over talked 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 on your 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 clear technology. Just go deep, bring AI to data across the enterprise. You've got to give you guys props. You guys are right on the line. I've got to say as a product person myself, I see you guys on executing great strides. You've been very complimentary to your team. 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, I still think there's a lot more hype to have there. There's so much more to do there. Cloud was over hype. Remember cloud washing? Exits back in 2010, 11. Oh, that's just cloud washing. Well, that's a sign that ended up becoming, what everyone was kind of hyping up. It did turn out. AI, I think, is 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 we were talking, he made a comment. I want to get your reaction to it. He said, you can't have AI without IA, information architecture. And you're in the information informatic of 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. There's data modeling. There's a lot of data involved that feeds AI. Who trains the machines that are doing the learning? So 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 and companies are in. Hybrid on hybrid cloud, multi-cloud, old architecture, by the way, mainframe, client server, big data. You pick your favorite, everything exists for any enterprise, right? People are not, companies are not going to move magically everything to one place to 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 to. So a great example is, look, take GDPR. I mean, GDPR is, if I am a distributor, large companies have to adhere to 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 telling you, gee, I see some anomaly detection. You see, I'm seeing some data which does not have access to leave the geographical boundaries of, let's 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 is the organizing principle, what I call the data architecture or the information architecture for the next 10 years. And that metadata, you guys saw that earlier, but how does that relate to these new things that we're living in? Because 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-sponsored cyber attack to the US. All these things are happening. I mean, hell, all securities attacks are going up. I mean, security is a great example of that. We saw it four years ago, and we worked on a metadata-driven approach to security. Look, I've been in the security business. I was at Symantec myself. Security is a classic example that 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? 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're growing, 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 parallel architecture. You have to just append your metadata. So security, governance, hybrid cloud, all of those things become a lot easier for you versus creating 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. I mean, they were 10 times fished over even before it was discovered, but they were inside. So audit trail would be interesting. Absolutely, I'll give you, typically if you read any external report, this is not a nothing tied to Equifax. It takes any enterprise three months minimum to figure out their 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 on to the next big thing, but data was still flowing through that pipe. Or by the way, the biggest issue is insider 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 every day. You won't even know that. That again is an anomaly detection. Well, it's going to get down to the firmware levels. 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've got to assume hacking, but now it's knowing what's going on. And this is really the dynamic nature. So we're on the same page. I'd love to do a security feature coming to the studio in our office in Palo Alto. I think that's worthy. I just had a great cyber chat with Vitter, CTO Vitter. Junay is awesome to do 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 get 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 of security and cloud to big data? Is that, 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 of security show, in my opinion. 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. Everybody runs natively there or they support it. So, exactly that. 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 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 proud, 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've got Niagara Falls streaming content. 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 go talk to my CEO, you may have 100 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 was a wild west. Look at the amount of consolidation that has happened. I mean, you see around the big distributions, right? To me, it's going to continue to happen because it's a nature of any new industry. I mean, you looked at security, cyber security, big data, AI, 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 at the governance and compliance of what a large company wants. I knew it. 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, obviously I know a lot because we'd 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? I mean, our approach is very, 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, Spark, Spark streaming, 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 don't want, 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 one place, it is scalable, and it has governance and compliance baked 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're 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're in the business of operationalizing data for customers who want it at scale? My, our belief is we want to help our customers succeed. And customers will only succeed, not just by experimenting, but taking that experiments to production. So we have to think of the entire life cycle of a customer. We cannot stop and say, great for experiments. Sorry, don't go operational with us. So we had a theme, we've had a theme here in the queue this week called, I'm calling it, don't be a tool. And around too many tools are out there right now. And 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 of 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 formed by the wayside are groping for a platform. So their customers tell us the same thing, which is why we... The tools have to work in context. That's exactly it. So that's why you heard, we talked about that for the last couple years, the intelligent data platform. People, customers don't buy a platform, but all of our products, like other microservices on a 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 am a large airline, and I want to go at scale operational, I can't stitch 100 tools and expect to run my IT shop from there. I can't. I will never be able to do it. Or, I mean, there's good tools out there that have a nice business model, lifestyle business or cash flow 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, I mean... The tool shed phenomenon is real. I mean, you have to, 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 a tool. 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 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 called it 10-2, which had a 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 themes we talked about Informatica. And 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 this barrage of tours across multiple cities across the globe. So customers can meet us there whether it's like 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 an all-in partner for... Do you have anything in China? China is an idiot. Alibaba. We were 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. That's great. theCUBE China, we need some translators. So if anyone out there wants to help us with our China blog. We'll be at re-invent, we'll be at Dreamforce. We were obviously, so you'll see us there. We were at Amazon Ignite, obviously very close to all of this. Yeah, re-invent will be great. Yeah, we were there. And Amazon obviously is a great partner. And by the way, great customer awards. Well, congratulations. You guys are doing great, Informatica. Great to see the success. We'll see you at re-invent and keep in touch. I mean, while it's executive vice president, EVP, chief product officer at Informatica, they get the platform game, they get the data game, check them 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're going to be rolling out here at Big Data NYC. Our event 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'll have some cocktails. I'm John Furrier. Thanks for watching. Stay tuned.