 From New York, it's theCUBE. Covering Big Data New York City 2016. Brought to you by headline sponsors, Cisco, IBM, NVIDIA, and our ecosystem sponsors. Now, here are your hosts, Dave Vellante and Jeff Frick. Welcome back to New York City, everybody. This is theCUBE. We are the worldwide leader in live tech coverage. Jeff Frick and I are pleased to have Amit Walia here. He's the executive vice president and chief product officer at Informatica. Good to see you again. Good to be here. So, we had Ronan on earlier this morning and talking about some of the themes that you discussed at Informatica World this year. Sort of the evolution of data management. One.o being tied to applications. Two.o we all know well the data warehouse and now this new sort of horizontal layer of data management across cloud and hybrid and so forth. So, maybe we could build on that but first of all, tell us what's going on here at Strata. I mean, Strata is big for us. You know, we've been here a couple of years last year, we were here as well with you guys. I mean, it's great to see how it's evolved. 10 years of Hadoop, first of all, right? I mean, that's a big accomplishment. I think the one difference I see coming here so many years is that and I think if you guys walk there is, you know, five, six years ago, it was a very tech speak. You could see the denim and the sneakers and the t-shirts, polo shirts and you do see now business because, you know, it's gone mainstream Hadoop, big data is driving business value. It is now business is looking at it and you can see by the folks that are coming here are looking for, hey, and the business speak is there. I think it's, to me, it's a maturation of a technology and getting mainstream is what Strata has become. It's good. Well, and you know, the hoodies didn't get there alone, right? It required companies like Informatica and, you know, big players like an IBM to come in and bring some adult supervision to this space. Would you agree? Oh yeah, I mean, look, obviously any new technology starts in some ways, you know, it starts on its own, there is some groundswell and then needless to say, customers need some level of scalability, maturity, automation and that's where software comes into play. So yes, of course, I mean, we, it's a joint effort in this case. So talk about your vision. Let's build on that sort of evolution of data management. We talk about 3.0, what is 3.0 to you and where does it go from here? Yeah, so 3.0 for us, I think it's, our vision is based on where we think customers want to go. I mean, we talk to customers across the globe, right? So to us, the fundamental difference is you articulated 1.0, 2.0, we know it's the app and then the data warehousing, 3.0 in my mind is the democratization of data. Where now truly data is driving decisions for companies. I mean, look, every company, whether they understand that or not, but if they do not leverage their data, if they do not democratize their data away from databases, applications, they're going to die. And if you look at the world today, think of the world of cloud. When we do use cloud apps, what do we do? We rent those applications, they're not our applications. It's kind of like living in a rental house. What do you own in a rental house? Your couch, your chair, we, what do companies own? The data in that rented app. So data is the only asset we all have going forward and the companies that can connect the dots between the data they have, they're going to be the winners in the future. And you see, we used to use the word born in the cloud. They're born with the data companies. I mean, what is Uber? What is Facebook? What is Amazon? They're born with the data, born in the cloud companies. When I talked to chief data officers and asked them, all right, what do you recommend? How do you get started? These particular financial services in healthcare and public sector, a lot of CDOs, but now as that role starts to move into more mainstream, they say, look, there's a couple of things you have to do immediately in parallel. You got to form a partnership with the line of business. You have to develop new skill sets. Okay, that's a simultaneous thing, but they say there's something that you have to figure out with your data, and it's sequential. You have to start by understanding how you make money. Not how you make money with the data necessarily, but how the data can support your monetization strategies. And I think a lot of people early on in this big data mean made a mistake, how can I make money with data? And then it's like, ooh, that's hard. Versus, how can I support my agenda? And then the second step was really what are the sources of data? Where do I get the data? Is it internal? Is it external? And then that gets to the really important part, was I got to be able to trust this data. There's a data quality issue. There's a governance and provenance issue. And that's, well, I guess you really come in in two and three, right? Is that fair? I mean, you touched a lot of good things. So I would say you're exactly right. Where big data got its hype cycle and it failed a couple of years ago, where people were doubting it because, as you said, it was a technology solution. People said, well, I'm going to play around with it. I'm going to put it in a box. And then suddenly people said, oh, it works. How can I scale it out? And it failed because it couldn't scale out because you just cobbled something together. And then, of course, it didn't have the governance. It did not even have the right business case behind it. That's changing now. It all has to start with some business value you're going to deliver, right? Are we solving marketing analytics, like cross-sell, upsell valuation? Are we solving fraud? What are we solving? Are we solving operational effectiveness in a, think of a shop floor, be with BMW, whether it's robots running around. You got to understand that data. So to me, that's where now the industry is. And then work your way back and then to your point, now how do you bring this all together? You got to bring data from so many places. Make sure it has the right quality metrics to it. It can be governed. It can be compliant. It can scale. And it's usable. And my belief is there are three principles where we are helping our customers with. First is consumerization. Big data was a technology speak. You need to consumerize it and make it easy for customers to consume. And I'll give you some examples of that. Second is it has to be agile. It's not necessarily just a big bang implementation or just an on-premise, on-premise, cloud, start small, but have the ability it can scale. The third one is at the end of the day, it has to be at enterprise scale. I mean, governance, compliance, scalability. Those are all enterprise features that look, they don't go out of fashion. Customers still need it. And those are the three attributes to me that are critical for success. And that's what we have been investing a lot. I mean, a great example of that is, for example, carrying this book today, is while we make infrastructure software, we make this data lake product, which we've been talking about here, where it is out of the box for the business analyst. All of the technology that we talk about is integrated. So our customers are not in the system integration business. They are in creating business value business. So now all that complexity has gone away. You can out of the box, use a very simple for the business analyst product that has everything that we want to. We're getting data from anywhere. High quality, full governance, ease of search. Yet, you don't feel the pain that it's a six month project out of one year project. Right. You know, there's a lot of companies that have been making money on data for a long time. At an advanced level, you think of like CPG companies that are very sophisticated in their analytics. I mean, banking is data, right? There's no money, there's no branches anymore. I mean, it's basically numbers on a page and models. So for those types of companies that have a historical precedent in playing in data and using data as a competitive advantage, how do you see that in them changing and really grabbing onto this kind of next wave of data-based competitive advantage? I mean, it's a very relevant question because I think when I look at our customer base, well, I look at customers across the globe, I think I would say that 50% of the customers are still trying to grapple with what is this data economy. About another 30, 35%, I would say, have at least are very aware and they are figuring it out as to what, how do they even play in the data economy? And I'm being very obviously harsh because everybody feels like they have a data initiative. Another 10% are well underway. They have at least thought through the business, critical business drivers and how to pivot. And 5% or less probably have figured out in the right way. And a great example, if you take in banking, what is fintech? Fintech is disrupting banking, in which way? The banks own the customer, they have all the information on our customers and everything, but the banks have probably, where they're struggling, they have not given the new experience to their customers. They have, and all of that is nothing, it's not like they don't know the customer. They just haven't thought through a new business model leveraging the same data. They're consumerization. And they have the data. They know everything about it. It's very obvious to them, like the millennial does not go into a branch. They don't care for a branch. You know it. They're not even allowed. But now, are you in the 50% that have no idea you will not look at that data? Or you're in the 5% that have looked at that data and are proactively working to reach out to the millennial. And I think that customers who are aware, and their customers who are still coming to grips with it. They're two ends of the spectrum. And our job is to help educate our customers because we see the value, this spectrum, that to go to the 50% and say, look, this is what you can do. Otherwise somebody will disrupt you. Do it too huge. So as the head of products at Informatica, how are these concepts getting into the products and out to the market? Yeah. I mean, three fundamental things that we are innovating, I would say. One is, we are hyper-innovating in the context of cloud. We want to make cloud, obviously that's the agility part. Clouds make it easy for customers to write out of the box, get ready, start small, go big. So we are basically everything cloud, right? We are the leader in the cloud market. I mean, we were the leader in the traditional market. Started 10 years ago, and we are the market leader in the cloud and I pass market today. So we were fortunate that, unlike a lot of companies established leaders, we invested way before the curve. Second for us is consumerization. I personally believe enterprise software has to get easier and easier. No, we sell infrastructure software, but we are invested a lot in business-focused solutions. The data lake is a great example. We're talking about here at Strada, our security source solution for security is an out-of-the-box solution for a business user, a CISO, the true analyst, our data governance solution. So consumerization of the offering, make it easy for use. And the third one to us is agility. Agility is real-time, all kinds of data, real-time data, right? And making sure that it can be seamless, hybrid, right? You can run a workload here and if you have some peak workload, you can flip it over to AWS or you can go to AWS and spin up our big data solution there, do some dev work there, bring it back. So consumerization, cloud, agility, and those are the kind of spare things that we are working on in the data 3.0 world because we know we have to work with customers who are business, NIT, batch, and real-time, cloud, and on-premise. And to be by the way, big data is nothing else but big data started on-premise, big data is going to cloud much faster as well. So when I say cloud and on-premise, we cover big data on both spectrums. So whether it's EMR, HD inside, cloud era, Hortonworks, we think customers will go and do everything. Data is kind of the way you want it and you're comfortable with putting the data in the cloud because you have a unique differentiation, you're not as worried about some of the other players. And our job is to help our customers be comfortable. Our job is to make it easier for them to feel comfortable to drive business value. That's the data platform then, right? Wherever you are, whatever you are doing, the data platform guides you. So it doesn't matter, you can shut this app down and go here, you can move the data here because as I said, ultimately, what do you want at the end of the day? Your data, you own nothing else in the world of cloud. You rent everything else. Only thing you want is data. You're going to get an analyst down here. Data's got to get on the balance sheet. It opens up a whole new discussion about data as capital, data value, but unfortunately we don't have time. Sir, thank you very much, Amit, for coming on. My pleasure to be here. Thank you very much. All right, our pleasure. Keep right there, buddy. We'll be back with our next guest. We are wrapping up day two at Big Data NYC. We'll be right back.