>> Narrator: It's theCUBE covering Sapphire Now 2017 brought to you by SAP Cloud Platform and HANA Enterprise Cloud. >> Welcome back everyone to our special Sapphire Now 2017 coverage in our Palo Alto Studios. We have folks on the ground in Orlando. It's the third day of Sapphire Now and we're bringing our friends and experts inside our new 4500 square foot studio where we're starting to get our action going and covering events anywhere they are from here. If we can't get there we'll do it from here in Palo Alto. Our next guest is Satyen Sangani, CEO of Alation. A hot start-up funded by Custom Adventures, Catalyst Data Collective, and I think Andreessen Horowitz is also an investor? >> Satyen: That's right. >> Satyen, welcome to the cube conversation here. >> Thank you for having me. >> So we are doing this special coverage, and I wanted to bring you in and discuss Sapphire Now as it relates to the context of the biggest wave hitting the industry, with waves are ones cloud. We've known that for a while. People surfing that one, then the data wave is coming fast, and I think this is a completely different animal in the sense of it's going to look different, but be just as big. Your business is in the data business. You help companies figure this out. Give us the update on, first take a minute talk about Alation, for the folks who aren't following you, what do you guys do, and then let's talk about data. >> Yeah. So for those of you that don't know about what Alation is, it's basically a data catalog. You know, if you think about all of the databases that exist in the enterprise, stuff on Prem, stuff in the cloud, all the BI tools like Tableau and MicroStrategy, and Business Objects. When you've got a lot of data that sits inside the enterprise today and a wide variety of legacy and modern tools, and what Alation does is, it creates a catalog, crawling all of those systems like Google crawls the web and effectively looks at all the logs inside of those systems, to understand how the data is interrelated and we create this data social graph, and it kind of looks >> John: It's a metadata catalog? >> We call you know, we don't use the word metadata because metadata is the word that people use when you know that's that's Johnny back in the corner office, Right? And people don't want to talk about metadata if you're a business person you think about metadata you're like, I don't, not my thing. >> So you guys are democratizing what data means to an organization? That's right. >> We just like to talk about context. We basically say, look in the same way that information, or in the same way when you're eating your food, you need, you know organic labeling to understand whether or not that's good or bad, we have on some level a provenance problem, a trust problem inside of data in the enterprise, and you need a layer of you know trust, and understanding in context. >> So you guys are a SAS, or you guys are a SAS solution, or are you a software subscription? >> We are both. Most of this is actually on Prem because most of the people that have the problem that Alation solves are very big complicated institutions, or institutions with a lot of data, or a lot of people trying to analyze it, but we do also have a SAS offering, and actually that's how we intersect with SAP Altiscale, and so we have a cloud base that's offering that we work with. >> Tell me about your relation SAP because you kind of backdoored in through an acquisition, quickly note that we'll get into the conversation. >> Yeah that's right, So Altiscale to big intersections, big data, and then they do big data in the cloud SAP acquired them last year and what we do is we provide a front-end capability for people to access that data in the cloud, so that as analysts want to analyze that data, as data governance folks want to manage that data, we provide them with a single catalog to do that. >> So talk about the dynamics in the industry because SAP clearly the big news there is the Leonardo, they're trying to create this framework, we just announced an alpha because everyone's got these names of dead creative geniuses, (Satyen laughs) We just ingest our Nostradamus products, Since they have Leonardo and, >> That's right. >> SAP's got Einstein, and IBM's got Watson, and Informatica has got Claire, so who thought maybe we just get our own version, but anyway, everyone's got some sort of like bot, or like AI program. >> Yep. >> I mean I get that, but the reality is, the trend is, they're trying to create a tool chest of platform re-platforming around tooling >> Satyen: Yeah. >> To make things easier. >> Satyen: Yeah. >> You have a lot of work in this area, through relation, trying to make things easier. >> Satyen: Yeah. >> And also they get the cloud, On-premise, HANA Enterprise Cloud, SAV cloud platform, meaning developers. So the convergence between developers, cloud, and data are happening. What's your take on that strategy? You think SAP's got a good move by going multi cloud, or should they, should be taking a different approach? >> Well I think they have to, I mean I think the economics in cloud, and the unmanageability, you know really human economics, and being able to have more and more being managed by third-party providers that are, you know, effectively like AWS, and how they skill, in the capability to manage at scale, and you just really can't compete if you're SAP, and you can't compete if your customers are buying, and assembling the toolkits On-premise, so they've got to go there, and I think every IT provider has to >> John: Got to go to the cloud you mean? >> They've got to go to the cloud, I think there's no question about it, you know I think that's at this point, a foregone conclusion in the world of enterprise IT. >> John: Yeah it's pretty obvious, I mean hybrid cloud is happening, that's really a gateway to multi-cloud, the submission is when I build Norton, a guest in latency multi-cloud issues there, but the reality is not every workloads gone there yet, a lot of analytics going on in the cloud. >> Satyen: Yeah. >> DevTest, okay check the box on DevTest >> Satyen: That's right. >> Analytics is all a ballgame right now, in terms of state of the art, your thoughts on the trends in how companies are using the cloud for analytics, and things that are challenges and opportunities. >> Yeah, I think there's, I think the analytics story in the cloud is a little bit earlier. I think that the transaction processing and the new applications, and the new architectures, and new integrations, certainly if you're going to build a new project, you're going to do that in the cloud, but I think the analytics in a stack, first of all there's like data gravity, right, you know there's a lot of gravity to that data, and moving it all into the cloud, and so if you're transaction processing, your behavioral apps are in the cloud, then it makes sense to keep the data in an AWS, or in the cloud. Conversely you know if it's not, then you're not going to take a whole bunch of data that sits on Prem and move it whole hog all the way to the cloud just because, right, that's super expensive, >> Yeah. >> You've got legacy. >> A lot of risks too and a lot of governance and a lot of compliance stuff as well. >> That's exactly right I mean if you're trying to comply with Basel II or GDPR, and you know you want to manage all that privacy information. How are you going to do that if you're going to move your data at the same time >> John: Yeah. >> And so it's a tough >> John: Great point. >> It's a tough move, I think from our perspective, and I think this is really important, you know we sort of say look, in a world where data is going to be on Prem, on the cloud, you know in BI tools, in databases and no SQL databases, on Hadoop, you're going to have data everywhere, and in that world where data is going to be in multiple locations and multiple technologies you got to figure out a way to manage. >> Yeah. I mean data sprawls all over the place, it's a big problem, oh and this oh and by the way that's a good thing, store it to your storage is getting cheaper and cheaper, data legs are popping out, but you have data links, for all you have data everywhere. >> Satyen: That's right. >> How are you looking at that problem as a start-up, and how a customer's dealing with that, and what is this a real issue, or is this still too early to talk about data sprawl? >> It's a real issue, I mean it, we liken it to the advent of the Internet in the time of traditional media, right, so you had you had traditional media, there were single sort of authoritative sources we all watched it may be CNN may be CBS we had the nightly news we had Newsweek, we got our information, also the Internet comes along, and anybody can blog about anything, right and so the cost of creating information is now this much lower anybody can create any reality anybody can store data anywhere, right, and so now you've got a world where, with tableau, with Hadoop, with redshift, you can build any stack you want to at any cost, and so now what do you do? Because everybody's creating their own thing, every Dev is doing their own thing, everybody's got new databases, new applications, you know software is eating the world right? >> And data it is eating software. >> And data is eating software, and so now you've got this problem where you're like look I got all this stuff, and I don't know I don't know what's fake news, what's real, what's alternative fact, what doesn't make any sense, and so you've got a signal and noise problem, and I think in that world you got to figure out how to get to truth, right, >> John: Yeah. And what's the answer to that in your mind, not that you have the answer, if you did, we'd be solving it better. >> Yeah. >> But I mean directionally where's the vector going in your mind? I try to talk to Paul Martino about this at bullpen capital he's a total analytics geek he doesn't think this big data can solve that yet but they started to see some science around trying to solve these problems with data. What's your vision on this? >> Satyen: Yeah you know so I believe that every I think that every developer is going to start building applications based on data I think that every business person is going to have an analytical role in their job because if they're not dealing with the world on the certainty, and they're not using all the evidence, at their disposable, they're not making the best decisions and obviously they're going to be more and more analysts and so you know at some level everybody is an analyst >> I wrote a post in 2008, my old blog was hosted on WordPress, before I started SilicionANGLE, data is the new developer kid. >> That's right. >> And I saw that early, and it was still not as clear to this now as obvious as least to us because we're in the middle, in this industry, but it's now part of the software fabric, it's like a library, like as developer you'd call a library of code software to come in and be part of your program >> Yeah >> Building blocks approach, Lego blocks, but now data as Lego blocks completely changes the game on things if you think of it that way. Where are we on that notion of you really using data as a development component, I mean it seems to be early, I don't, haven't seen any proof points, that says, well that company's actually using the data programmatically with software. >> Satyen: Yeah. well I mean look I think there's features in almost every software application whether it's you know 27% of the people clicked on this button into this particular thing, I mean that's a data based application right and so I think there is this notion that we talked a lot about, which is data literacy, right, and so that's kind of a weird thing, so what does that exactly mean? Well data is just information like a news article is information, and you got to decide whether it's good or it's bad, and whether you can come to a conclusion, or whether you can't, just as if you're using an API from a third-party developer you need documentation, you need context about that data, and people have to be intelligent about how they use it. >> And literacies also makes it, makes it addressable. >> That's right. >> If you have knowledge about data, at some point it's named and addressed at some point in a network. >> Satyen: Yeah. >> Especially Jada in motion, I mean data legs I get, data at rest, we start getting into data in motion, real-time data, every piece of data counts. Right? >> That's exactly right. And so now you've got to teach people about how to use this stuff you've got to give them the right data you got to make that discoverable you got to make that information usable you've got to get people to know who the experts are about the data, so they can ask questions, you know these are tougher problems, especially as you get more and more systems. >> All right, as a start up, you're a growing start-up, you guys are, are lean and mean, doing well. You have to go compete in this war. It's a lot of, you know a lot of big whales in there, I mean you got Oracle, SAP, IBM, they're all trying to transform, everybody is transforming all the incumbent winners, potential buyers of your company, or potentially you displacing this, as a young CEO, they you know eat their lunch, you have to go compete in a big game. How are you guys looking at that compass, I see your focus so I know a little bit about your plan, but take us through the mindset of a start-up CEO, that has to go into this world, you guys have to be good, I mean this is a big wave, see it's a big wave. >> Yeah. Nobody buys from a start-up unless you get, and a start-up could be even a company, less than a 100-200 people, I mean nobody's buying from a company unless there's a 10x return to value relative to the next best option, and so in that world how do you build 10x value? Well one you've got to have great technology, and then that's the start point, but the other thing is you've got to have deep focus on your customers, right, and so I think from our perspective, we build focus by just saying, look nobody understands data in your company, and by and large you've got to make money by understanding this data, as you do the digital transformation stuff, a big part of that is differentiating and making better products and optimizing based upon understanding your data because that helps you and your business make better decisions, >> John: Yeah. >> And so what we're going to do is help you understand that data better and faster than any other company can do. >> You really got to pick your shots, but what you're saying, if I hear you saying is as a start-up you got to hit the beachhead segment you want to own. >> Satyen: That's right. >> And own it. >> Satyen: That's exactly. >> No other decision, just get it, and then maybe get to a bigger scope later, and sequence around, and grow it that way. >> Satyen: You can't solve 10 problems >> Can't be groping for a beachhead if you don't know what you want, you're never going to get it. >> That's right. You can't solve 10 problems unless you solve one, right, and so you know I think we're at a phase where we've proven that we can scalably solved one, we've got customers like, you know Pfizer and Intuit and Citrix and Tesco and Tesla and eBay and Munich Reinsurance and so these are all you know amazing brands that are traditionally difficult to sell into, but you know I think from our perspective it's really about focus and just helping customers that are making that digital analytical transformation. Do it faster, and do it by enabling their people. >> But a lot going on this week for events, we had Informatica world this week, we got V-mon. We had Google I/O. We had Sapphire. It's a variety of other events going on, but I want to ask you kind of a more of a entrepreneurial industry question, which is, if we're going through the so-called digital transformation, that means a new modern era an old one movie transformed, yet I go to every event, and everyone's number one at something, that's like I was just at Informatica, they're number one in six squadrons. Michael Dell we're number in four every character, Mark Hurr at the press meeting said they're number one in all categories, Ross Perot think quote about you could be number one depends on how you slice the market, seems to be in play, my point is I kind of get a little bit, you know weirded out by that, but that is okay, you know I guess theCUBE's number one in overall live videos produced at an enterprise event, you know I, so we're number one at something, but my point is. >> Satyen: You really are. >> My point is, in a new transformation, what is the new scoreboard going to look like because a lot of things that you're talking about is horizontally integrated, there's new use cases developing, a new environment is coming online, so if someone wanted to actually try to keep score of who number one is and who's winning, besides customer wins, because that's clearly the one that you can point to and say hey they're winning customers, customer growth is good, outside of customer growth, what do you think will be the key requirements to get some sort of metric on who's really doing well these are the others, I mean we're not yet there with >> Yeah it's a tough problem, I mean you know used to be the world was that nobody gets fired for choosing choosing IBM. >> John: Yeah. >> Right, and I think that that brand credibility worked in a world where you could be conservative right, in this world I think, that looking for those measures, it is going to be really tough, and I think on some level that quest for looking for what is number one, or who is the best is actually the sort of fool's errand, and if that's what you're looking for, if you're looking for, you know what's the best answer for me based upon social signal, you know it's kind of like you know I'm going to go do the what the popular kids do in high school, I mean that could lead to you know a path, but it doesn't lead to the one that's going to actually get you satisfaction, and so on some level I think that customers, like you are the best signal, you know, always, >> John: Yeah, I mean it's hard, it's a rhetorical question, we ask it because, you know, we're trying to see not mystical with the path of fact called the fashion, what's fashionable. >> Satyen: Yeah. >> That's different. I mean talk about like really a cure metro, in the old days market share is one, actually IDC used a track who had market shares, and they would say based upon the number of shipments products, this is the market share winner, right? yeah that's pretty clean, I mean that's fairly clean, so just what it would be now? Number of instances, I mean it's so hard to figure out anyway, I digress. >> No, I think that's right, I mean I think I think it's really tough, that I think customers stories that, sort of map to your case. >> Yeah. It all comes back down to customer wins, how many customers you have was the >> Yeah and how much value they are getting out of your stuff. >> Yeah. That 10x value, and I think that's the multiplier minimum, if not more and with clouds and the scale is happening, you agree? >> Satyen: Yeah. >> It's going to get better. Okay thanks for coming on theCUBE. We have Satyen Sangani. CEO, co-founder of Alation, great start-up. Follow them on Twitter, these guys got some really good focus, learning about your data, because once you understand the data hygiene, you start think about ethics, and all the cool stuff happening with data. Thanks so much for coming on CUBE. More coverage, but Sapphire after the short break. (techno music)

>> Announcer: Live from San Francisco it's the CUBE. Covering Informatica World 2017. Brought to you by Informatica. >> Welcome back everyone. We are here live in San Francisco for Informatica World 2017 exclusive coverage from the CUBE. Third year covering the transformation of Informatica as a company. I'm John Furrier, Silicon Angle. My co-host this week is Peter Burris, General Manager of Wikibon.com and Head of Research for Silicon Angle Media. Our next guest is eight time CUBE alumni, Amit Walia Executive Vice President of Products at Informatica. Amit, great to see you. >> Good to be here. >> Thanks for spending the time to come on. Saw you had a nice dinner last night with all your top customers. Very happy customers. Welcome to the CUBE. >> Yes, thank you. We keep them happy. Eleventh year in a row we got number one in customer loyalty. We work hard for that. >> There's a lot of exciting things happening. I just want to jump into some of the products though because that's your wheelhouse. You guys have been an amazing product company. I've always been kind of bullish on you guys, very complimentary. The one thing that, when we've talked on FaceBook and also on the CUBE is that not everyone knows about Informatica. They know about the old Informatica. We had Jerry Held on yesterday talking about the transformation, how hybrid cloud's here to stay. You guys have made great strides on the product front, the platform front, decentralizing data with control. Now you got the new brand. What's going on, give us the update. You got to be pretty pumped now, you got a megaphone out there with the new CMO. >> Yeah, lots happening at that end. I'll go back and paint a picture about how we see where the industry is and then how we are basically transforming that. My fundamental belief is that we're going through this massive transformation. Pick any word, but underlying at the technology level, the systems of records, all the databases and all the apps are massively fragmenting. Cloud, on-premise, hundreds and hundreds of choices. Systems of engagement for customers are fragmenting, right. When I talk to customers, they're struggling to figure out what is the system of intelligence. What's the organizing principle? Take a great example, my customer data and what I know about you John, is available inside the system, within multiple databases, multiple apps, outside the systems, what you do on LinkedIn, FaceBook, Twitter, how do I get a handle of you to be able to effectively engage with you? That is a fundamental change that is happening in the industry is what is my organizing principle to have the system of intelligence? We've honed in at the metadata layer for that. We believe leave the data wherever it is because it's going to be in different places. Use your best of breed apps. Organize the metadata because the scale and scope of that, while small, power of that is very high. Yesterday in my keynote, I announced the launch of Claire, our AIML offering. The idea is that we are going to be the Google of the enterprise to bring the entire metadata together. When we apply machine learning to it, it's the same algorithms that LinkedIn applies, or FaceBook applies for photo tagging or relationships, or Amazon applies for recommendations. We're going to apply it for data and make that then be what I call organizing principle, the system of intelligence for an enterprise. That's the nutshell of what we're trying to do. >> Also this Jada 3.0 thing, I want to press you on this because this is really cool. You guys have increased the surface area of addressibility of data and we talked about that last year, making it horizontally scalable yet with all the goodness of the controls as we talked about in the past. Now you're bringing in access methods via machine learning and AI techniques to make it accessible. Think Alexa, right. People at home, "Hey give me a song." How are you guys using the algorithms because now algorithms have become a super important part of what to look at. FaceBook, you mentioned FaceBook and Google, they've been criticized for their algorithms suppressing quality data. News cycle, things pop up once they see some traction. How do you guys tweak and enable algorithms to surface the best data possible? >> The best way to describe is that our philosophy is different. Claire, our AI engine, our goal is to make sure we can surface all of the data to the customer, but in an organized fashion. We're not looking to say, filter something. The best example is that predictive maintenance. If I am BMW and I'm running a robotic driven shop floor, how do I know when something's about to go down? I have a lot of old, historical data on my shop floor, but real time streaming data's coming from the sensor of the robot. I want to marry the two together and then let the system tell me, boy I feel like in the next 30 minutes, something is about to happen. We are doing those kind of things, solving those problems so we're not looking to filter or suppress anything. Our goal is to make sure we can bring more and more and more data together and with the help of machine learning, Claire, make it easy for customers to make decisions. Intelligent decisions, smart decisions, easier versus hundreds of people having to guess or predict which ends up not being very smart. >> On the road map side, I want you to take a minute to explain it. It's a good laying out the value proposition there, but I want to tie the cloud together with this because Jerry Held said yesterday, hybrid cloud's going to be a very long journey because legacy doesn't go away. You guys have a great business on-prem that's been historical for you guys. As you guys have modernized, what is the connection on a product basis that's available today and that's being worked on on a road map basis that says, you can do all this stuff with the data, but it's going to be cloud enabled. How do you get that cloud, hybrid cloud connection so the customer doesn't feel pain in moving to the cloud? >> First of all, I can boldly say that we were probably the only software company in the industry that disrupted our own industry to go to the cloud. By the way, data integration which is our core model, 11 years ago we invested in the cloud. We didn't know where it will go and we announced that Informatica 11 years ago and today 11 years later, we are the number one market share leader in cloud integration, number one in Gartner Magic Quadrant, and our cloud platform today is transacting a trillion transactions a month. In some ways, we were disrupting ourselves as you speak. >> Yeah, I mean the Gartner thing, I always say this cause those are old metrics, but the new metric is customer traction. You guys were in the announcement with Google Spanner as they globally GA their spanner distributed database which is a horizontally scalable database. You have a relationship with Amazon, you're in Microsoft. What is the customer uptake and what are some use cases? Give us some specifics. >> Three specific use cases. The customer started a journey in cloud more connecting cloud applications. On SalesForce, connected with World Gate, connected to SAP, so on and so forth. Simple application integration, all API management. Where data gravity is moving to cloud, where fundamental workloads are going and we see more and more traction is taking analytics to the cloud. I'm moving my workload to Redshift or I'm moving to an Azure data warehouse. That's where, by the way between January and May, we have moved half a trillion data objects to cloud data warehouses. Half a trillion. Clearly in that context we work with AWS. Three years ago, we started with them. Azure -- >> Just to put an exclamation point on that, in January it was a billion so between January and now, it's up to a trillion. Huge. That's a hockey stick. >> Kale is a hockey stick over there because so much more is being created outside the enterprise and customers don't want to bring it on-premise. They say look I just want to put it in Redshift or Azure database and I want to process there and over time, what they want, more to your point is connect me to my on-premise data warehouse too. Let's say I've done some analytics here, connect the relevant analytics and move it to, let's say my on-premise data warehouse and over a period of time as I get comfortable with this hybrid, I may take this workload and 100% flip over to the cloud too. They want this bi-directional journey. That's what's really enabling customers. >> It's always kind of hard to cobble together things that customers language that they're used to speaking in, to new concepts. It seems to me that data integration is your business of business. >> That's the foundation. We discovered data integration is the foundational layer and everything else we do is what I call more value added data management capabilities. Like MDM. Data integration allows you to connect, bring data together, MDM is a value added data management solution to say now I can get a 360 degree view of my customer like Nordstrom is using us for. Or a 360 degree view of my products, or a 360 degree view of my suppliers to make more business decisions. >> John: So integration is table stakes from your standpoint? Foundational. >> It's foundational. >> John: Foundational. Okay, better word. >> In that context, we operate like the Switzerland in the world of data. Whether it's Amazon, Google, Azure, tomorrow Oracle, SAP, we connect to the whole world. >> Amit, you have a vision of where this is all going to go. It's one thing to say, we've got our product set and we're moving it to a new technology base, which is good. That'll improve productivity. This whole concept of data management is bigger than just moving existing tooling, existing practices to a new set of platforms, no matter how much more productivity you might get out of those new platforms. It means something more. It means the way your business operates differently, business thinks differently, it means different ways of institutionalizing work. Give us the vision that you're laying out to your product team about how, yes we're re-platforming, we're introducing these new development technologies and all these other things, but here's where we're going. Here's the role we want to have in business. What is the role that Informatica wants to have in business? >> Our vision is to be what I call the system of intelligence for our customers because the organizing layer for that is data. When we say data management, data management's a very broad word you could argue. Our goal is that we want to organize the enterprises data. The vision that Google has for the internet, organize the customer's data whether it's inside their four walls or outside, in the context of the business processes. I'll translate that for you in two ways. We used to optimize for the IT technical user. A couple of years ago we made a big pivot to put an AND to it. We are also optimizing it for the business user because data now is such a powerful asset that business users want direct access to it. One of the things you would see from us in the last three or four years is we have been putting out a lot of out of the box data solutions. Intelligent Data Lake is a great example of that. We are giving IT full control of it, but we have a bi-modal experience where a business user can self service analytics. I just want to walk in as a marketing analyst and understand what was my lead to revenue conversion. I don't care about all the underlying infrastructure. I don't (mumble), but I just want to do my job. IT also wants to make sure as business users are accessing it, there's governance, security, compliance issues. We're marrying the two together. That's a very high bar for ourselves. >> Let me see if I can follow up on that because I want to make sure that at least I understand it. When you say you want to be the Google for enterprises data, there's actually a couple subtle things in there. First off, number one is that Google is looking at mainly public data and you want to look at public and an enterprises private data. As you said, that requires a whole level of functionality >> Amit: Totally right. >> That Google doesn't worry about like privacy, like ownership, like management and control. Secondly, increasingly the enterprise concept, especially when it comes to data is being able to get access to any data, anywhere. It's not organize the internet. It's not organize the enterprises data, it's organize all data for that enterprise. >> For the enterprise. >> Is that right? >> Exactly. We don't own the data. The enterprise owns the data. Big difference for us. >> The enterprise is also going to go out to all those sources that Google's looking at - >> Two big differences, the data within the enterprise and outside the enterprise for the enterprise, and we don't own the data, we want to bring it together for the enterprise to consume and operate and execute a lot more easy and efficiently. >> We're not talking about just small corners of data. >> No, not at all. >> We're talking about the enterprise, all data that's possible -- >> We are going outside the world, we're looking at unstructured data because, for example when you are, let's say on Twitter. Today we're going to be Tweeting, that's unstructured data, but it's about you and me. Today if Nordstrom wants to figure out something, what John likes, what John thinks, they want that, they want to. We are bringing that together within the MDM to say, oh you know what John bought for you, here's what John is saying on FaceBook or here's what John's saying on Twitter. Marry the two together and you understand John a whole lot better. That's what we want to do. >> And make it addressable and make it available to not only databases and systems, but developers. >> Amit: Oh absolutely! >> When I asked the question about data management, kind of the vision of data management, in many respects, it's the enterprises access to data that's relevant to it, number one. The ability from a metadata standpoint to know where it is and have the properties of ownership and privacy and rights and privileges and identities, and number two, the ability to move it around according to, as you noted, the integration laws that the -- >> That's exactly right. Because we've been operating for the enterprise for the last 25 years, we understand what they need. What regulations, what security concerns, what governance and compliance issues. If I had to summarize that context, look, we want to organize the enterprises data whether it's inside the four walls or outside for them, at their level of scale and security and governance and then with the help of Claire, democratize that for any user to truly use it. >> Democratization's a big angle and I want to ask you that because as much as you see the future, and I think you do, we've been talking to you many times here in they keynotes, customers aren't in the future. You've got to kind of come to earth and get to reality so I've got to ask you the question for customers, because they're trying to just deal, I'm trying to move to the cloud, I've got some VM Ware, I've got Amazon over here, I've got Azure, I haven't really baked out my full how I'm going to integrate cloud in my business model, what are some of the use cases that you guys are engaging customers with? You have good vision, products are solid. When you go out to the field, talk to customers, what are the use cases? What are you engaging them on? >> The journey to cloud is a big use case. In the journey to cloud, as I said there are two specific journeys customers are on. One is I'm deploying these thousands and thousands or hundreds and hundreds of enterprise SaaS apps. Help me weave them together in the context of data integration or MDM. Second is, the whole data gravity going to cloud. We talked about data warehousing analytics. Second is all of that. Move my data warehousing, but give me the flexibility in the hybrid. As I said, right, I want to bring outside data within Redshift, but connect it to my. Those are our two biggest use cases we see. Third we see that rides on both of them is self-service analytics. If I'm able to do both of these, then I'm much more easily able to do self-service analytics. Those three are the ones -- >> John: Are primary use cases right now? >> Those are the three prime use cases. Second one, on the other hand we see governance and compliance come up very big. Clearly customers are realizing that all of this re-architecture that's happening, you still need the same governance and compliance. If I am a large bank, if I'm a large insurance company, the laws didn't change for me. Cloud may have come, Hadoop may have come, the laws still stay the same so governance and compliance is a huge one for us. Look at GDPR. There is a deadline in May 2018 and customers are unprepared for that. That's the number two, I see governance a lot I see. >> In Europe it's even worse. You could get a top line, is that the top line, four percent of you -- >> Amit: Customers don't realize if you're a US company, even if you transact with one, single European entity, you are now -- >> The liability's there so let's just go to the root cause of what causes that liability potential, that's security. Quickly, security obviously's on the mind of you guys. You have an interesting security product. You guys are digging in the product, what's the product vision on security? >> That's the last one I was going to say. Four years ago, we saw that coming that security is an unsolved problem at the data layer and that's where the world is going to organize itself. We invested, and we have to invest ahead of the curve. We launched the product Secure@Source. Today, it's basically the industry's number one product. 11 awards at Odyssey. Raymond James is a customer, deployed within their four walls. Seven thousand databases go through Secure@Source to give them a full view of my sensitive data, who's accessing it, all of those risks that are now coming to the data layer. As data gets democratized, the security issues become bigger and broader. >> Final question for you. I want you to take a minute to end the segment because I want to give you the chance to say that because you know I'm a big fan of product work. Watching you guys go private and seeing the transition with the new management team, the product guys came in. I've said this on the CUBE many times, you've got the brand marketing going on now, new CMO, things going to be pumping out there. What is special about Informatica right now from a product standpoint? What makes you guys unique? You guys have done some good things, products coming down the pike. What are the guiding principles for you as the leader of the product team to continue to stay on that wave and innovate and make these products valuable to customers? >> I think the biggest change I would say is that we are innovating at the space of a start up. But we have the skill and breadth in the world of data management that is unparalleled to anyone. In this space, whether it's the traditional architecture, big data architecture, real-time streaming architecture or a cloud architecture or it's MDM and security and governance, nobody can do it at scale as us. By the way, we firmly believe in the best of breed concept. All of those capabilities are best of breed within their own market. Our belief is that look, we can solve a customers transition a lot more seamlessly and a lot more risk-free, and a lot more in the future proof way. Of course, we are modeling ourselves to move at the pace of a startup. I call ourselves the hottest pre-IPO -- >> John: I was just going to ask the revenue question. >> A billion dollar in revenue company, not billion dollar market cap company. >> John: You're doing over a billion in revenue? >> Doing over a billion in revenue. >> I'm going to add one more thing to that Amit. I'm not even going to test it. We are especially impressed that you have made very, very bold promises the past few years and you've executed on them. You're one of the few companies in this space in the whole data management, this emerging data management next generation world that has executed on the promises that it's made. Your promises make sense and all the things that you said are excellent. The promises make sense, but your execution makes is safe for customers. >> Well we had some critical analysis yesterday so we're not going to just all fawn all over you guys, there's some things to work on. The big bets are paying out. You guys made some great bets. The cloud bet was key. Congratulations. Amit, great to see you. Coming on the CUBE, thanks for spending the time. You got a keynote coming up this afternoon. Real quick, what's going to be the topic? >> Well I'm going to talk about how Claire will be able to solve a lot of future-looking problems. Today's keynote is all about the futures and what the vision of the future is. I'm going to showcase a few examples of what machine learning and AI can do to increase productivity and help ease the pain of our users and customers. >> Get that data integrated, democratize it and create freedom for data to fly around and get those apps addressing it. This is the CUBE, bringing you all the data here inside the CUBE, but soon we'll have an AI bot doing all the interviews in the future sometime. I'm John Furrier with Peter Burris. We'll do them today. Informatica day two exclusive coverage from the CUBE. We'll be back with more coverage after this short break. Stay with us.