>> Live, from Las Vegas it's theCUBE. Covering Informatica World 2019. Brought to you by Informatica. >> Welcome back everyone to theCUBE's live coverage of Informatica World 2019 here in Las Vegas. I'm your host Rebecca Knight along with my co-host John Furrier. We are joined by Anil Chakravarthy. He is the chief executive officer at Informatica. Thank you so much for returning to theCUBE. >> Oh my pleasure, thanks for having me back on your show here. >> So, on the main stage this morning you said that AI and ML need data, but data needs ML and AI. >> That's right. >> Can you just elaborate on that, riff on that a little bit. >> Yeah, yeah. You know if you look at AI and ML, hot topic obviously, every company is trying to take advantage of new machine learning AI technologies. One of the key components of making that happen is the availability of the right data, because you have to train these machine learning algorithms, the data scientists have to be able to find the right data, and then they have to prepare the right data, make sure that they have access to the data, clean it up, and then put it into their AI models into their AI algorithms and so on. Because the training of the algorithms is very sensitive to the quality of the data. It's really garbage in garbage out. If you don't feed it the right data, the results will be skewed. And so, that's the key part of what we mean by when we say AI machine learning needs data. The flip side is in what we do and help customers, which is manage their vast complexity and scale of data. If you look at customers petabytes of data, thousands of databases, hundreds of thousands of cables, so how do they manage all of the data? Because the management of data is not just about availability of data or the performance of those systems and so on. All that is super important, but it's also the security of the data, the governance of the data, the availability of the data to the right users at the right time. Trying to do all that manually, you just can't keep up and that's where you need machine learning and AI to be able to do that for you in an automated manner. >> Anil, we've talked in the past multiple years ago. Every year, it's the same story. You guys had on that RightWave data everyone is now talking about what you were talking about four years ago. >> Yep. You're continuing to talk about it and adding to it. You also talk about being the Switzerland the neutral third party, because data needs to connect around >> Right from multiple sources. You had a lot of industry players up on stage today. How is that going? How are you continuing to be that role in the industry as more and more people come in? What's it say about the momentum and for Informatica strategy? >> Yeah, I think it's really because of what customers really want. Take any customer, any enterprise customer or government customer, of any scale, they're usually using a lot of different both on-premise and cloud, technology offerings. So it could be multiple software service offerings, multiple maybe public clouds, where they're running it as platform of service. A lot of different on-premise offerings et cetera. Which means that all of those offerings that they're using have a data footprint. From a customer's perspective, if they're using different tools to manage the data for each one of those well they have all the old problems they've always had. Data inconsistency, inability to manage it, and just who's going to learn, if you're a data administrator, are you going to learn four or five different tools to manage it? So that's does not really going to work. That's where customers are demanding hey, I need a data management platform that can help me manage the data consistently and that's where we come in, that's what helps us be the Switzerland of data. >> So data feeds machine learning, machine learning powers AI. This is the formula you guys talk about all the time. No data, no AI. But if data is constrained, from either infrastructure legacy, or a regulation, that's going to slow the feeder concept down >> Yeah. or maybe incomplete data. This is really about operationalizing AI so this is, you've got to solve that data problem first if you want to scale up operations around AI. What's the state of the art from Informatica? What are you guys doing in this area and where is the customers' progress in this new operationalizing of AI with data at the heart of it? >> Yes, from an operationalization perspective, what you need is, first of all, help your data scientists and others using AI to find the right data. Finding the right data, you do it through the catalog, for example, it'll tell you what data you can access and then what's the metadata around the data, what you can use the data for. Maybe there's some data that you say look, we have the data set but we don't have the customers opt-in to use that data. Fine, you can't use that data. That's the first step, finding the right data. Then getting access to that data that's what you get through an integration, the cloud tools, the big data tools, et cetera. Then you prepare the data. We have a number of tools to prepare the data to make sure that the AI and machine learning models can use them well. Then you feed the data. You run it, you get your result, but then the explain-ability is a big deal. Whether it's regulators or even your own internal executives. They say, oh that's the result of running the AI model but how did it come to that decision? You know, for instance, in financial services, if you're using AI to do, let's say, a decision on who gets to get a loan or not, well you have to make sure that there is no bias in that, right? In order to explain the result, you need to know where the source data came from. That's what we do as well, through our governance and lineage. >> Well we'd love talkin about SAS success you look at the cloud-native, born in the cloud, great examples how data has really been driving the new generation of innovation. The more enterprises we talk to around digital transformation, the more that we hear we want to be consumer-like. >> Yeah. With a SAS, whether it's an app for banking or an IoT app, or anything. SAS is kind of an unique data for that. How should a enterprise architect that solution? Because it's harder when you don't have clean, one cloud native so you got to bring in some cloud, you got to bring in the on-premise. Where does the data sit (laughs) in all this? How do you architect the data on-premise, in the cloud, or in general, so that the customers have a really, road map to a SAS solution? >> It's a great question, you know. What you see right now is the focus on building it through customer data platform. We obviously just acquired a company, AllSight, that helps build the get inside sort of the customer data platform. The way we think of it at Informatica is you have a customer data platform, well then the last mile of how you reach the customer, keeps changing and evolving. That last mile could be through a call center. It could be through a web application. It could be through a mobile app. It could be through a sales person, who is reaching the customer with a live interaction. It could be a lot of different ones and it could be all of them. That's where the omnichannel comes in. The way to do what you are asking for, John is to truly focus on building a customer data platform that can support multiple kinds of last mile when it comes to actually interacting with the customer. That's how you ensure a very good, consistent, customer experience. And then you take advantage of whatever the latest technologies. Tomorrow, like we were just talking about here, if there is AI enabled bots or something else that's a better way of interacting with the customer, you're still working off of the same consistent customer data platform. That's how we see it. >> I want to ask you about the skills gap. >> Yeah. >> We know that there is a great demand for people who are data scientists, experts in cloud and analytics, and yet there are so few qualified candidates. >> That's right. >> I want to hear your thoughts about it and then also what Informatica is doing to make sure you are recruiting and retaining the right employees. >> Yeah, I think one I completely agree with you on the skills gap and obviously that's also a great opportunity as well, because, in reality a lot of the younger folks are looking at what careers they want to pursue. With the right mindset and the right training these will be great careers for them. There's also, the other great thing about this is this is across the country and across the world so you don't have to be in a specific location to have a successful career as a data scientist or as a data steward, et cetera et cetera. I think from a training perspective we are actually working with a number of different universities. We actually started working with Indiana University to build a curriculum that can then be available online available to a lot of different folks. We obviously work with a lot of different system integrators and consulting partners who hire hundreds of thousands of people and they are starting to build some very very large practices around data science. That's another avenue for career growth there. And last, we're also starting at a much younger age. Last year we talked about the next 25 program and tomorrow, when Sally is back on stage, you will see an update on the next 25 program. Were trying to get kids at the middle school level interested in this as a career. >> Anil, real quick on the follow up on that is what curriculum specifically do you see in high demand? Is it machine learning? Is it analytics? Is it cognitive? What specific skills that you see in demand and for folks to start thinking about? >> I think what my advice to folks, in fact my daughter is a freshman in college too and I've been giving her the same advice because I think this is a great way to go, is when you think of skills development first think of a broad platform that will give you the right skills regardless of the changes in technology, because technology will keep changing. So what is that broad platform? The broad platform is, I think you need a background in statistics, you need a background in computer modeling and programming, and you need a broad platform in overall math. And again, I don't mean to scare anybody, it's not calculus level math, but it's math that helps you understand concepts et cetera. That's the broad foundation you need. Then you have a number of different new technologies whether it's Python, whether it's Math Lab. There are a lot of different ways of approaching and doing data science. But then, once you have that foundation, it's easy to pick this up. And the rest of it, just like in any other job, once you start doin it, you're going to pick up the rest of it and you'll become an expert there. >> Great. Amil Chakravarthy, thank you so much for coming back to theCUBE. >> Perfect, thank you so much for having me. >> Yeah, thanks for havin us. >> Thank you. >> You are watching theCUBE Informatica 2019. I'm Rebecca Knight, for John Furrier, stay tuned. (electronic music)

>> Narrator: Live from Las Vegas, it's the Cube. Covering Informatica World 2018. Brought to you by Informatica. >> Hey, welcome back everyone. We're here live, it's the Cube. Exclusive coverage of Informatica World 2018. It's our fourth year, exclusive coverage. I'm John Furrier, your co-host of the Cube, with Peter Burris, my co-host and chief analyst at Wikibon, and SiliconANGLE, and the Cube. Our next guest is the CEO of Informatica, chief executive Anil Chakravarthy, who's back again for his fifth Cube appearance. We went back all the way to 2014 at AWS Reinvent when cloud was on the horizon. Now you running a really high growth company. Congratulations. It's great to see you. >> Thank you. It's great to see you. Great to be back on the Cube again. I appreciate it. >> One of the things I want to point out, you know, we're independent, we want to point all the things that you guys should be working on, but I got to say, you guys have done an amazing job. Executing on the product front in a market that's growing and changing erratically with data, and not a lot of people got that. Amazon was early on we saw them executing. They were misunderstood. You guys are not misunderstood anymore. >> Yep, I appreciate that. >> Data is at the center. Congratulations. >> Thank you. I think one of the things that we've learned over the last 25 years, 25 years old this year, and you got that in the sign behind you, is there is a few things we are really good at. Data management is what we are really good at. Now, it just so happens data is everywhere in all kinds of platforms, and we want to make sure that wherever our customers are we are there as well to help them in data management. >> So, let's talk about what's going on. So first of all, a lot of interesting things here going on. One last year, we talked about, data lakes, data swamps. This year it's about the enterprise catalog and all the goodness, MDM, and the things you guys have done, kind of check check. The catalog brings in the notion of the full visibility. And then you got the multi-cloud hybrid-cloud adoption and the announcement of Azure. This is bringing in a new era. You called it data 3.0 up on stage. What is data 3.0? Can you take a minute to describe the vision and what does it mean for your customers. >> Yeah, data 3.0 is the name we are using to talk about the generational market disruption that's going on right now. If you think of what's changing in the data world, there are multiple trends happening at the same time. Volume of data doubling every year. You have a lot of new types. >> Six months. >> Well, for us too, the cloud is six months, but across the industry it's about a year every year. Still faster than computing in fact. Faster than Moore's law. Then, you have the variety of data, all kinds of data. You have the velocity of data, all the speed at which data needs to get processed. All the new techniques of processing data, like AI and advanced analytics and so on. And if any single one of these was happening that would be a big trend in itself. Everything happening at the same time, that's the generational market disruption and that's what we call, I said look, it would be easier if we gave it a name, and that's what we call data 3.0. >> So, you know, you just made a really great point. And I want to highlight it and suggest, again, looking at the board, where are the next generation of innovations going to come from? It used to be that we relied Moore's Law, double performance every 18 months, and in so doing we could put more software into it. But what you just described is doubling the amount of data every year, faster than Moore's Law. Means that it's inevitable. We have to move more of the innovation up into software, especially software that manages data. >> Absolutely, right. I think there's, just like you had said, the rate of growth of data being so much faster than even the rate of processing power growth means a couple of things happen. First of all, you're going to move more data into the cloud because in the cloud you can expand horizontally must faster, so than you can ever do in your own on-premise. So that's going to happen. The second big thing that's going to happen is as data gets into the cloud and people are using all these different types of new data processing techniques to your point about the catalog, if you don't have a fundamental catalog that tells you where your data is, who's using it, what it is for etc., you just lose control. You just cannot keep in control of your data. And so what people are realizing is as they do new business initiatives they got to have the data catalog. They got to put in place the data catalog and then let the catalog expand. >> A horizontally scalable cloud. That's a really significant point. And this has been a customer challenge, right? So, we're now in the obvious mode of the cloud is there. Azure, you mentioned Microsoft is growing significant. The shift has been made, everyone kind of gets cloud. But the cloud scale is still the pressure. Now you got data coming in, into the cloud scale, and you got things like GDPR, which is a shot across the bow saying okay, now you got to start thinking about compliance and management, and growth. Kind of a lot of things being juggled there. How do you see that unfolding, because it's challenging for customers? I mean there's a lot of things going. A lot of moving parts. >> The way I think about it is, think of this way. Customers have been working with databases for a long time. Over 50 years right now. And the first generation of databases, customers used to say, "Look, I just need a database "that runs all the time. "I can't have a database that crashes "every two hours or so." It just needs reliability as the first thing in a database. The next thing people started thinking about, once reliability was a solved problem, was they said, "I need scale and performance. "The number of records are increasing, etc." Once these became design principles databases started to become more and more robust. The only way to solve the kinds of problems that you mentioned today is every new database that you think of, whether it's for structured data, unstructured data, any kind of data. And you think of a database, think not only of reliability, performance, scale, also think of connectivity, governance, security, privacy. All these need to become design principles for whoever is thinking about the database, and that's what we mean by the catalog. It's the catalog helps you put the discipline in place. When you start a new database, register it in the catalog. That way you know what you are doing with the database. When you set up a copy of a database, put in the catalog. That's what we mean by the discipline. That way you can track. Tomorrow if you say, look I want to know where my European customer data is, just go to the catalog and it will tell you. >> So, I want to build on that. Actually, many years ago when I was first screwing around with databases, one of the things that was explained to me was bring in a database the application developer no longer has to know as much about the underlying infrastructure. >> That's correct. >> Because the data base administrator will take responsibility for how the data got spread on disc and access paths and all that other stuff so the developer could focus on the development. Now when we think about the cloud and all these other technologies and raising things up the catalog allows developers to increasingly focus on how they're going to use data. As opposed to the process that they are going to build. So we were talking about his earlier with a couple of different guests. Microsoft and when Rohan was here. >> Right. >> And the idea that ultimately we're talking about a data-first approach to thinking about how we create application value. >> That's exactly right. And to your point, I think the principles have not changed. What has changed is the way that you apply those principles. Which is you take a data-first approach, but then that's what the APIs let you do. The APIs expose the data to different applications and users. They don't need to know how the processing is happening. So today the data might be processed through Spark. Tomorrow you might say I got a new engine that processes it. They don't need to know it at the application level. At the application level, it's exposed through APIs, and the get to use the APIs. >> So, if you think about, from our perspectives, sorry John, when you think about it from our perspectives, we've always believed that digital business means something, and the difference between business and digital business is digital businesses use data as an asset. And a digital business transformation is the degree to which you are transforming, re-institutionalizing your work, reorganizing around data as an asset. >> That's right. >> So very, very important concept. Challenging for a lot of CEOs. >> Yeah, exactly. >> So look. Informatica's a software business, which means in many respects it has a whole bunch of data assets associated with it, but you're engagement model hasn't always been data, your service model hasn't always been data-oriented. As a CEO, is Informatica more of a digital business today, >> Absolutely. >> And if it is, how would you advise other CEOs to think about this kind of a transformation? >> Yeah, let me just give you the kind of the intelligent disruption we've gone through, because we were a software business, we're a cloud business today. And that's the transformation of the digital business-- >> Peter: Product to a services-oriented approach. >> And even in the product, our business model used to be that we basically said look our goal is to try to sell software upfront, go work with customers, make the business case for software, and sell the software upfront. Today we're selling a service which means we not only want to self the software, we want to know how customers are using the software, are they successful with the software, is it doing what they expected, and that is the most notion of land, adapt, expand, and then renew. And that's a much better approach, because it works for the customer, it works for us. There's less shelf ware in this process. So a lot of people, everybody's happy with that. But in order to make that happen, we got to collect a lot of data on whether customers are being successful. >> The business model and the product model's got to be aligned completely and that's really what you guys have done. And is that where people are making mistakes, in your mind, when you see people going to the cloud? That they kind of do it with the cloud, then forget to change their... >> And that corporate, that's exactly right. When you think of this digital transformation or digital business you got to do three things all in sync. The new customer engagement models like ours change from upfront to ongoing. And then there's new products and services, which is all the stuff that we have done around the cloud portfolio. And then there's new operating models, new processes, customer success is a new process that we did not have four years ago. Which is we proactively reach out to customers to find out what they're doing with our software, are they successful with it, et cetera. We used to wait for them to call us. Now we do it proactively. >> But isn't that also one of the businesses of taking a product to services approach, is because you're now establish a relationship with a customer that says, it's not just proactively, you're exchanging data on a continuous basis. In the form of updates on the one hand, but also utilization information et cetera, build a better product, better engagement. >> Exactly. In fact, you'll see one of the packed events here has been what we call the the Ops Insight, or Operational Insight, that's the product we built to do exactly what you said. Get the telemetry data, help customers use our products better. And that's the transformation from a product to a service. >> And we had Toyota on earlier, and they were very complimentary. But the big ah-ha for them was we had this crisis, we weren't connected, but we actually had the data. They just didn't connect at all. So they kind of had it, the answer, couldn't get it. >> And then we're using data excellently in each of the different functions. >> Then we did the transformation, and then they realized, had they gone down a different route, they wouldn't have been prepared for the tsunami of telemetry data coming from the cars. >> That's exactly it. >> So now, again, this is not going away. This is going to to be the pattern. There's going to be a new set of inbound data coming in. How should customers prepare for that? Is there an ingestion mechanism? Is that where you guys do the cataloging? This is kind of the important, headroom question. Where's the... >> There's different points depending on the style of the organization. I often ask questions, what is the nature of the culture of your organization? Do you guys work top-down better, bottom-up better, how do you work? So somebody who says looking at it, we actually work bottom-up really well, right? Top-down dictates don't work really well. Then I say to them, why don't you start and profile the top hundred data elements that really matter for your business. So if they're an insurance company, a policy number. That's one of the top hundred data elements. A claim number, that's one of the top hundred data elements. Just identify the top hundred data elements, and then just tell yourself that you have a consistent business definition for that data element, you have a consistent technical definition, you know where the data resides, et cetera et cetera. Just start bottom-up. For some companies that works really well. Other companies are more like, no no no. We work more better top-down. Then you start with what is your strategy as a business? How are you going to transform yourself, who is your competitive threats, and so on. And then you go through what are you doing in terms of transformation, new operating models, new customer engagement, et cetera? And then translate that into a data strategy, and that becomes a data architecture. So I think it depends on the style of the organization. Some of them are trying both and meeting in the middle, but what I tell customers is based on your culture, based on your style, there's different models that work. >> Great relationship with Microsoft announced here. Scott Guthrie's on stage. How's that relationship going? I know it just didn't start yesterday, because there's deep production integration, shipping, it's not GA but it's previewed shipping soon. Couple weeks coming, or months. By September, I think that estimate is. Ballpark. Where'd this come from, how you guys doing, can you just give some color to the Informatica, Microsoft, Azure relationship? >> Absolutely. The relationship with Microsoft itself has been going on for a very long time. We have over 2,000 common customers with Microsoft, so it's something that especially on-premise, has been something that we have been working with SQL server and other Microsoft products for a very long time. The relationship specifically with Scott and with the Azure team started in 2014. So we went up there to Seattle just to learn about what they were doing with the cloud and so on. We were actually pretty impressed. We said, look, this is clearly the new Microsoft. This is the Microsoft that wants to work with partners, that wants to be a true enterprise player, and we said, you know what, this is the kind of partner that we want to bet on. So we made a few proactive investments initially. We, at that point, which was not clear that Azure would take off like it did. But just like you mentioned with Reinvent, we said these guys are really clearly betting on it. So 2014 was when we started making the bets on Azure, SQL data wheelhouse, et cetera. And that was when it started growing. And in the last, we have obviously seen the hockey stick now. We have 200 or so enterprises. >> Yeah, completely top-down, said we're doing that in cloud. Everyone's in line, it's beautiful. The growth has been there, the stock was the... I remember when it was trading at 26. I think it might have been about that time. >> Well you look at it now, exactly. >> So you're really confident that this is going to be a positive impact for customers? >> A very positive impact. Because with them, you see both the on-premise, we have clear synergy and partnerships with them, and in Azure as well, we have the clear partnership and value proposition with them. >> And let's be honest. There are not a lot of times when betting against Microsoft turned out to be the right thing to do. Maybe with phones, but that's about it. >> There's some things there, but anyway. I want to get to the company question. You're the chief executive officer, you're leading now a growing team, growing company. Talk about the culture, because you guys have always had a culture of innovation. Although private equity took you over, there was a story there, but I really want to get at the key points in the company, and talk about the R&D. Because you talked about bets. You bet on Amazon. We were there in 2014 with you. We say you there, and we saw Azure. You guys sniffing out the good tech. You guys are smart. But you got to put the rubber to the road for investment. Where's your priorities? Talk about the R&D. >> Yeah. Just to set the context, when we went private, we went private with the clear understanding that we would transform the company. We saw the potential for the company but we also knew that changing from a software company to the cloud company that we just talked about, that was not easy to do as a public company. Obviously there's a lot of investment required, plus there's some unpredictability. >> Earnings, and... >> We said look, we went private with the explicit aim of transforming the company. And the investors, our sponsors, had the same goal as well. You know, sometimes there's a misperception that all PE is about cost cutting. >> But most are. >> Exactly, and that's just not true. It's like you have to look at every PE form and every PE deal, and a number of PE deals that are growth-oriented. Because they know that, hey, with the investments we're making, ultimately if you can get a company to grow, the valuation is way better than you can ever get through just cost cutting. They saw that potential in Informatica. We worked closely with them to define the plan that we've been executing on since 2015. By the way, Microsoft and Salesforce.com came in as strategic investors, so when we went private that was a good endorsement for us. And so we've been executing on that front. And so we've never stopped investing in R&D. As a public company we invested about 15%, 16% on R&D. This year we're actually investing 17% on R&D, so we've really done what it takes to be continually best of breed and integrated, that's-- >> And I'll count cloud subscription models there, what are some other priorities can you share? Some of the priorities for you guys in terms of key areas you're getting out front on being proactive. >> Yeah, so biggest priorities for the company are continue to be a clear best of breed product line in everything we do That we believe that we should never ask any of our customers to sacrifice anything when they buy Informatica. It is best of breed. Second clear priority for the company, make sure that we have an integrated product suite. That's not easy to do, when you're both best of breed and integrated. But that's why we invest as much as we do in R&D. The third clear priority for the company is the transformation journey that we're on. All the key parts of the transformation, product portfolio, go to market, business model, customer success, brand. They all have to work in concert. That's where I mentioned the values and the culture of the company. We've really have always been a customer-focused company. But we said look, what really will take us for the next 25 years is what we call the values that are real data. >> I really appreciate your time, I know you're super busy. I have one final question, cause it's pretty obvious. We were kind of speculating on our intros, at our editorial overview is your ecosystem is, I won't say massive 'cause you're growing, but we predict it's going to be pretty big. Given if this continues, the trend continues, it's going to be a matter of time before you start rolling in developers and all kinds of new partners, just global system integrators, on and on and on. What's the strategy for the ecosystem, do you guys have clear visibility on how that's going to play out? Where is global partners or customers? How are people engaging with you guys in the ecosystem? >> We already have over 500 partners, and that's where this focus on being an API-driven, micro-services driven architecture really helps us. That way when you scale new partners, you don't have to do custom work for each partner. And that really helps us scale much faster. In the past we have a 100+ OEMs, and each OEM is to take a little more work because it was all custom interfaces. Now in this new API, micro-services driven world, we can scale to the kind of volume that you're talking about, and I'm pretty confident with-- >> In many respects that is the definition of horizontal scaling. >> Exactly. >> Horizontal scaling, it's the magic of the cloud. Certainly opening up and changing the game. Certainly changing the infrastructure with cloud-native. You're starting to see a shift to a new infrastructure on the internet is all happening with data, cloud, and who knows. Maybe blockchain and crypto will be in the conversation soon. How do you do the MDM on that? That's a hard one, we'll get to that later. Anil, thank you for coming on the Cube. Really appreciate it. Great to see you. >> Thank you for having me, I really appreciate it. >> Alright, John Furrier, Peter Burris here, the CEO of Informatica at Informatica World 2018. We'll be back. Stay with us for more coverage after this short break.

>> Announcer: Live from San Francisco, it's theCUBE! Covering Informatica World 2017. Brought to you by Informatica. >> Welcome back, everyone. We're live in San Francisco for CUBE's exclusive coverage of Informatica World 2017. I'm John Furrier, SiliconANGLE. Our next guest, Anil Chakravarthy who's the CEO of Informatica, CUBE alumni multiple times, but the chief executive officer leading the charge of a great private company doing very well. Welcome back to theCUBE. >> It's great to be here, John. Thanks very much. >> We've got a couple of things to talk about, but I want to just jump in. Behind us you see the new logo, Informatica. Really kind of the last leg of the stool, if you will, you guys have gone private, >> Yep. >> Great product work over the years. You know I've been pretty complimentary of you guys, although we've had a critical analysis session yesterday. But all the big bets were very well done playing off. You've got a great product team, great leadership team, new CIO hire. But the last leg of the stool is the brand. >> Anil: That's right. >> You guys haven't been showboating much. Now you got to kind of brag and be humble about it and get the word out. New marketing program, what's that all about? >> Yeah that's exactly right. So you just said, the transformation that we are going through, three big steps is the transformation. The product portfolio transformation, we've been talking about that. This is all driven by cloud, by big data, and machine learning, and all of that. Then the transformation of the business model, from license to subscription and cloud services. And now the brand transformation. And we see the brand transformation as actually catching up to where the company actually was. We were just talking about that right before we got started. We actually have done a lot of things. Like for instance, did you know that we are doing 1 trillion transactions a month in the cloud? I mean, very few people knew about that. >> Yeah, what's more impressive on that, I found that out earlier it was 1 billion in January. >> Anil: It's unbelievable. It's-- >> I mean how do you do that? It's a growth hockey stick, straight up. >> It's a hockey stick, it's huge, it's huge growth, and that's driven by the fact that we are the leader in cloud data management for the biggest ecosystems, for Salesforce, for Amazon, for Azure, and that drives a lot of the data volume across the cloud. >> Before we get in the keynotes, on that note, one of the big bets you know I've been very impressed on is the cloud play, right? The data architecture of things, the winning formula. But you got cloud presses, you had Amazon Web Services. Google just announced span or horizontally scalable database, generally available. You were on the of the three data partners on the front end of that. >> Anil: That's correct. >> And part of the launch of Google. >> That's correct, yeah. >> I didn't know that. >> So you know, the way we think of the world is from our customer's perspective. It really is the best way to think about it is as the enterprise cloud. Put it together. All the data you have in the enterprise that you have generated over the years, that's still very valuable data. And then the data you have in the cloud. And you can't think of those two things as separate. For instance, you could have customer data, the same customer. John, you're the customer of a retailer. Some of that data about you is in their on-premises systems, and some of the data may be in a cloud system, but it is all interconnected data and you can't have two separate silos. We believe that we are the only ones that can really manage that. And that's why we are supporting every major cloud platform or cloud system, just like we are supporting every major on-premises system. >> Yeah, you guys call it Switzerland. It was a great way to describe it. But really to me it puts bigger than that, is that you guys make data ready. And that's really the value of what I call the tier two data layer that's building, where you've got stuff in memory, I get that, it's some odyssey streaming stuff, and things going on there. But now, then you have third tier, archive, but data tier two is just like all the data: IoT, structured data. That's growing, but the cost of storage is getting lower and lower. Now companies are incented to store. How is that impacting your business? We heard that at DellEMC World over and over and obviously they're in the storage business, but the tier two storage is significantly growing. >> Well data is still growing at over 25% a year. That's a huge number given all the way the size that you have, so it's going to be within by 2020, it'll be over 15 zetabytes, and a zetabyte, for those of you who are interested, is 10 to the 21. That's a huge amount of data. And what we're seeing is, the value comes from being able to first of all see your way through the data, being able to understand what data is valuable and what's not, and then connect the data. If you have customer data, product data, location data, et cetera, being able to put all of that together. That's really where the value comes from. >> So I've got to ask you about your keynote. You talk about the digital transformation's unfolding and data is the critical foundation for digital transformation. Okay, we've heard digital transformation. I mean, I'm not to say it's played, I know you guys have your theme, but this business transformation going on. So digital transformation is a known trend, but it kind of is played in my mind. I want to know what's different about Informatica now. Why is it unfolding now versus two years ago when we started talking about digital transformation? What's the most relevant thing now? >> Well I think the biggest relevance is, two years ago, as you exactly said, people were talking about digital transformation. Now they're doing digital transformation. Now you're seeing, you know, we talk about our own customers like Tesla or GE or Amazon doing it, but lots of other customers are actually doing the digital transformation. Now when you first take the first step toward the digital transformation, that's when you realize, my data, I got to fix the data foundation. If I can't have a data foundation, then I just, you know, everybody cares about a good customer experience. If I can't tell all the interactions a customer has with my company, and that data is in different places, there is no way I can provide a good customer experience because the customer knows what they're doing with me and I don't know what they're doing with me. And that's really the foundation for the data foundation. >> I want you to take a minute to just re-explain that because this is something comes up all the time and I get different answers and people have different definitions. What does it mean to have a digital data foundation and what are some of the impacts to the customers when they do have that? >> Think of it the simplest way. Let's say you have a customer and a lot of the new customers are like that. You are a bank, and you have a customer who doesn't want to talk to anybody. They only want to do everything through a mobile application. They want to file a loan application through the mobile, they want to check their balance through mobile, they want to deposit a check through mobile, et cetera, et cetera. If they have a problem, they might talk to somebody through a chat on a mobile, but they don't really want to talk to a live person. And this is, by the way, a common scenario now. Now they are doing probably 20 different things through the mobile. But when you get into your back end, that's the front end. You can put 20 things on the mobile, but the back end you've got 20 different things. But you have to have a single picture across those 20 things. When did the customer interact with us? What did they do? What is the pattern of that customer? How do you profile what the customer is doing? If you don't have that picture, everything that you do with the customer is going to just appear disconnected to them. It's going to frustrate them even more. And that's really the reason we have to have the data foundation. >> Okay, so, that's kind of a data layer, I get that, and believe me, horizontally-scalable data, making it accessible only helps the apps. The question to you is, your reaction to people saying, "Hey, Anil, I got to be innovative. "I got to free the data up and I got to let it grow "and you know a thousand flowers bloom, all this goodness. "But hey, I got to control it." So that's a huge issue. I've got governance, I've got compliance, there's laws now. So am I stuck in the mud? I want to be innovative and go fast, but now I've got to govern it and control it. How do you answer that question? >> You can do both now and that's the reason why we're announcing CLAIRE and all these innovations that we announced this. The advent of machine learning and metadata let's you do both. You basically say, look, I can use all these new technologies to find out what data I have. It's not going to slow you down. In fact, if you set up something like an intelligent data lake, because it has the metadata layer, you are actually opening up the data you have to the end user without having to come through IT for every piece of data, which means they can go faster. That's where the innovation happens. So you can do both. >> John: So it's a control catalog, basically. >> It's exactly right. It's a controlled catalog and you basically get to define different levels of trust. You can say, this data is curated data, it's trusted data and we can vouch for it. And maybe other data that's just shared collaboratively, and you can just flag it and then that way the user knows, okay here's data that I'm getting from a central system and this is what I need to use when I'm talking about something like revenue. And I'm tying something like a trend of what's going on. I might be able to use other data and that's the key there. >> Talk about the trend around CLAIRE. A lot of buzz here at the show. CLAIRE stands for clairvoyant. It's got the word AI in it. It's a name. SAP's got Leonardo, Salesforce has Einstein, all these different terms, but it's a clever way to point to AI, augmented intelligence, and machine learning. >> Anil: Correct. >> What does that mean for Informatica as a company? Certainly it kind of humanizes it. >> Anil: Correct. >> Shows the access of data should be democratized. What does it mean for you guys and the customers? How does that play out in your mind as the CEO? What do you see CLAIRE doing? >> Well the three big points I'll make about CLAIRE. First of all, when we built CLAIRE, we did not invent the artificial intelligence or the machine learning. A lot of that is already available. So we took a lot of the best algorithms in machine learning and applied them to metadata and applied them to data management. That's the secret sauce. It's not the building the AI itself, it's the use of the AI for data management. That's number one. Second, we defined CLAIRE very clearly and we said it's not a product. It's an engine, it's an AI-powered engine. In fact, I call for CLAIRE, I say it's cloud-scale, AI-powered real time engine, that's CLAIRE. Right, so it's an acronym, but it's the engine that powers other products. The third big thing is we're telling customers, you're going to get the benefit of CLAIRE, but you don't need to deploy CLAIRE. When you buy any of our products that are powered by CLAIRE or any of our solutions that are powered by CLAIRE, that will automatically come in there. So it means once you have any product like our enterprise information catalog or our secured source or data governance, you're starting to use CLAIRE and then you can use CLAIRE for other use cases as well. >> What's been the reaction? You know, and obviously you get nervous, CEO, probably got these things out there, probably wonder what the reaction is. What's your take on the reaction? >> People are very intrigued. I know that's what they, they look at CLAIRE and go, what is CLAIRE? How are you guys using it? I think people are asking us, tell us a little bit more about how AI is being used in the world of data and data management. So it's absolutely the reaction we wanted. >> So I got to ask you this question. I asked Mark Hurd the same question at the Oracle media day a few weeks ago. I want to ask you the same question. Everyone's number one at everything now. You guys are number one in six quadrants. Oracle's number one, the Dell E's. Everyone's number one at something. So the question really is, not so much about being number one, congratulations, you've got some magic quadrant wins that was highlighted in the keynote. But you guys are going through a transformation. You're telling your customers that they're going through a transformation. Wouldn't it make sense that the transformation scoreboard looks different than the old way? And I want to get your thoughts on this because, not that we have the answer, but there's one answer in customer wins, but as this new world transforms and unfolds, what's the scoreboard look like? How, because it's not as clean to say, this is the category, you're starting to see a little blending, as you mentioned how data is evolving. What's the new scoreboard look like? >> Is it the scoreboard for us or for the customer? >> John: You guys, the industry. How do I know if you're doing well? Obviously customer wins is obviously number one. >> Yeah, I think the best way to. I'll give you a couple of metrics, financial and nonfinancial, okay. From a nonfinancial perspective, as you said, a couple of key metrics. One is customers. How many new customers, how many new customers, reference customers do we have? Second one that you want to look at is just mind share or when people think about digital transformation, do they think of, hey, Informatica, they have a key role in my digital transformation. Just looking at mind share and so on, because that's a good leading indicator. In terms of the nonfinancial, or the financial metrics for us, obviously as more customers do what we call enterprise cloud data management, you're going to see our subscription revenue grow dramatically and you know, that's something that when you look at our subscription revenue, you'll see that impact of the enterprise cloud data management. >> And you guys made the move to subscription, obviously went private. Bruce Chizen and Jerry Held, your board members talked about this. You can do a lot of things 'cause it doesn't, it impacts the P&L but that it's still baking out, it's evolving, you're private, not public, but you want to get it right before you go public. >> That's correct. >> How do you feel about the progress on that front now? >> Oh we're making fabulous progress. We're very pleased with where we are. From my perspective, we are ahead of where we thought we would be by this time. I think customer buying behavior has converged really nicely with where we are in terms of where we want to go. So I think that's definitely been a big plus. >> Sally Jenkins, your new CMO, you got to feel good about her coming on the board-- >> Anil: Oh she's done a great job. >> High impact. She said on theCUBE that you guys are the hottest privately held pre-IPO startup. >> Anil: That's right. >> Twenty years in the making, whatever. I mean, but you guys are private. >> Billion dollar startup. >> But you act like a startup, which is why we like you guys a lot. You guys are like a very hustling like a startup. But now you're growing and you're getting beyond the 200 million, over a billion dollars now. When's the IPO coming? >> Yeah, I mean, you know look, I can tell you the factors that will be the lead to the perfect timing for the IPO. When those factors come together, I don't have a crystal ball right now, but I can tell you it weighs both on us and the market. From our perspective, we are making this big shift in the business model. We want to make sure that we can say, hey look, now the shift is very clear and stable and we can see where they where you know we'll be able to project out our own forecast for the next three, four quarters. So that's one key indicator for us. The second key indicator that we look at is the total revenue growth of the company and what percent of the growth of the revenue is recurring revenue for us. So we're going to be looking at those two factors. And of course from the market perspective, we want to make sure that the market wants to, continues to be. >> If you wait four years til we have a new president, and then heard all the politics from the Kara Swisher thing was, got a lot of people stirred up, in the conversation. But in all seriousness now, you also have private equity so you have to make the company worth money after they go public so you've got to have some growth left in you, right, I mean you guys are, you feel good about the? >> Oh we really do because you know, we look, that's where these six categories that we talked about make a lot of sense. You look at data integration, data quality, master data management, these are all categories that are well established. We know the patterns and we are seeing very good growth in those categories. Then you look at the new categories: cloud, big data management, data security. Those are all coming into their own right now. So that's why when you look at our portfolio, you go, wow, there are some that you already have great, well established and going well. These other ones, they're well established but they also have a lot of promise and future growth. >> Great chatting with you. You're a great, insightful, and inspiration. You guys have done a great job. But I've got to ask you the question because I think you have an interesting role. I mean, you have, you're acting like a startup, but you're not a startup. You went private from a public company. You've got a great board of directors. You've got Jerry Held and Bruce Chizen on there, but you've also got private equity sharks on the board. So, that's my definition, I won't say you said that. >> No, no, but I was actually in the private equity world, to my pleasant surprise, I've seen the whole spectrum of investors and our guys on the board are very much growth-oriented. They know that the value gets created for them through growth so it's well aligned. >> Yeah, but you're not sitting back having pizza and drinking wine. These PE guys, they're financially driven. >> Anil: That's right. >> So the question is, advice to other startups, whether they're venture backed or other companies going through innovation strategy. How do you manage the success of having such good product excellence? I know you've got good people, so that's an easy one answer. How as a CEO do you maintain the disciple to have the cadence of the financial performance? Because those guys look, they're probably not going to give you, hey how we doing? Numbers matter, but you're transforming technology and products. >> That's right, so what we do is-- >> How do you do it? >> We have a scorecard which has both the short term and the longterm metrics and we look at both of those. You know, we do monthly business reviews. So the pulse of the company has definitely quickened. We're operating at a new level of intensity. But when we look at the scorecard, it's not just the immediate financial metrics. It's things like, for example, are we building the back end infrastructure to be a subscription company? That doesn't get done in a month. >> John: That's an IT challenge, right? >> That's an IT challenge, a process challenge, it takes 12 months, 18 months, the kind of things that you talk with Graeme about. But that is an example of, you can have a scorecard. You don't necessarily have to look at a scorecard just for the short term metrics. You look at it for both short term and what makes you successful over the longterm. And that's, you know, that's what we're doing is just keep our eye on the ball, focus on a few things, both short term and longterm, and make sure we're doing them well. >> How about customer wins? To me, that's the scoreboard ultimately as we look at it at our team. How are you doing on customer wins? Can you share some, I see you have a lot of great customers. I met a few last night, obviously big wigs, big names. >> Anil: Yeah, exactly. >> What are some of the big wins look like and why are you winning? >> Well you know, we have 7,000 plus customers. We have a great customer base. Just at this show we've had 85% of our sessions here at the show have had customer or partner speakers. That gives you a sense of customers want to talk about us. A couple of ones that I would highlight for example, which are fairly recent for example, Amazon is one. They just spoke at the show and in fact the CMO of Amazon was here, Ariel Kelman. And he spoke about he is a customer of Informatica and how he's using Informatica for his own marketing systems and the marketing data analytics that he is doing. Another example is Tesla. You know, we talked about them at the show. >> I got a test drive on Friday with one. >> There you go, exactly, and then they are using us for the Tesla and the Solar City acquisition and driving synergies there. So lots of great examples. >> John: Tough customers, by the way, very, very finicky. >> Oh they are very demanding, very demanding customers and we are really proud to be serving them. >> Okay, final question, Anil. What's next? How do you look forward. Obviously this event, congratulations on getting the branding out. Peggy and the team did a great job. Sally and the team did a great job. What about next? What's next? >> Yeah, you know, what's next for us is simply work with customers to first of all get our story out, understand their priorities, and make sure that they understand that we can be a great partner for them. So we believe that this is the beginning of that journey. We talked about digital transformation and how we help them. Now we take the show on the road to our customers, make sure that we help them at their pace to transform. >> So bring the message out, build the brand. >> Absolutely. >> That's the key priority. >> And then continue. >> Product side, what's going on the products? >> Well on the product side, for instance, you saw a teaser of all the big trends. Machine learning, cloud, big data, security, all of these have full-fledged roadmaps that we're going to be working on over the course of the next six months. >> Anil, great to see you. Congratulations, you can tell, you're still intense. You've got the intensity, it's not going to stop by the way. >> Anil: No it's not. >> It's not like you're not going to get more intense as you guys grow. And congratulations. >> Thank you for having me on your show. >> We are here live in San Francisco for Informatica World 2017 with the CEO here, Anil Chakravarthy, inside theCUBE. I'm John Furrier. Thanks for watching. Stay with us for more coverage from Informatica World after this short break. (techno music)

>> Live from Las Vegas. It's theCUBE. Covering Informatica World 2019, brought to you by Informatica. >> Welcome back everyone to theCUBE's live coverage of Informatica World. I am your host, Rebecca Knight, along with co-host, John Furrier. We have two guests for this segment. We have Abhiman Matlapudi. He is the Product Master at Deloitte. Welcome. >> Thanks for having us. >> And we have Kubalahm Rajeev Krishnan, Specialist Leader at Deloitte. Thank you both so much for coming on theCUBE. >> Thanks Rebecca, John. It's always good to be back on theCUBE. >> Love the new logos here, what's the pins? What's the new take on those? >> It looks like a honeycomb! >> Yeah, so interesting that you ask, so this is our joined Deloitte- Informatica label pin. You can see the Deloitte green colors, >> Nice! They're beautiful. >> And the Informatica colors. This shows the collaboration, the great collaboration that we've had over, you know, the past few years and plans, for the future as well. Well that's what we're here to talk about. So why don't you start the conversation by telling us a little bit about the history of the collaboration, and what you're planning ahead for the future. Yeah. So, you know, if we go like you know, ten years back the collaboration between Deloitte and Informatica has not always been that, that strong and specifically because Deloitte is a huge place to navigate, and you know, in order to have those meaningful collaborations. But over the past few years, we've... built solid relationships with Informatica and vise versa. I think we seek great value. The clear leaders in the Data Management Space. It's easy for us to kind of advise clients in terms of different facets of data management. You know, because no other company actually pulls together you know, the whole ecosystem this well. >> Well you're being polite. In reality, you know where it's weak and where it's real. I mean, the reality is there's a lot of fun out there, a lot of noise, and so, I got to ask you, cause this is the real question, because there's no one environment that's the same. Customers want to get to the truth faster, like, where's the deal? What's the real deal with data? What's gettable? What's attainable? What's aspirational? Because you could say "Hey, well I make data, data-driven organization, Sass apps everywhere." >> Yeah. Yeah absolutely. I mean every, every company wants to be more agile. Business agility is what's driving companies to kind of move all of their business apps to the Cloud. The uh, problem with that is that, is that people don't realize that you also need to have your data management governance house in order, right, so according to a recent Gartner study, they say by next year, 75% of companies who have moved their business apps to the Cloud, is going to, you know, unless they have their data management and data assets under control, they have some kind of information governance, that has, you know, context, or purview over all of these business apps, 50% of their data assets are going to erode in value. So, absolutely the need of the hour. So we've seen that great demand from our clients as well, and that's what we've been advising them as well. >> What's a modern MDM approach? Because this is really the heart of the conversation, we're here at Informatica World. What's- What does it look like? What is it? >> So I mean, there are different facets or functionalities within MDM that actually make up what is the holistic modern MDM, right. In the past, we've seen companies doing MDM to get to that 360-degree view. Somewhere along the line, the ball gets dropped. That 360 view doesn't get combined with your data warehouse and all of the transaction information, right, and, you know, your business uses don't get the value that they were looking for while they invested in that MDM platform. So in today's world, MDM needs to provide front office users with the agility that they need. It's not about someone at the back office doing some data stewardship. It's all about empowering the front office users as well. There's an aspect of AIML from a data stewardship perspective. I mean everyone wants cost take out, right, I mean there's fewer resources and more data coming in. So how how do you manage all of the data? Absolutely you need to have AIML. So Informatica's CLAIRE product helps with suggestions and recommendations for algorithms, matching those algorithms. Deloitte has our own MDM elevate solution that embeds AIML for data stewardship. So it learns from human data inputs, and you know, cuts through the mass of data records that have to be managed. >> You know Rajeev, it was interesting, last year we were talking, the big conversation was moving data around is really hard. Now there's solutions for that. Move the data integrity on premise, on Cloud. Give us an update on what's going on there, because there seems to be a lot of movement, positive movement, around that. In terms of, you know, quality, end to end. We heard Google up here earlier saying "Look, we can go into end to end all you want". This has been a big thing. How are you guys handling this? >> Yeah absolutely, so in today's key note you heard Anil Chakravarthy and Thomas Green up on the stage and Anil announced MDM on GCP, so that's an offering that Deloitte is hosting and managing. So it's going to be an absolutely white-glove service that gives you everything from advice to implement to operate, all hosted on GCP. So it's a three-way ecosystem offering between Deloitte, Informatica, and GCP. >> Well just something about GCP, just as a side note before you get there, is that they are really clever. They're using Sequel as a way to abstract all the under the hood kind of configuration stuff. Smart move, because there's a ton of Sequel people out there! >> Exactly. >> I mean, it's not structured query language for structured data. It's lingua franca for data. They've been changing the game on that. >> Exactly, it should be part of their Cloud journey. So organizations, when they start thinking about Cloud, first of all, what they need to do is they have to understand where all the data assets are and they read the data feeds coming in, where are the data lakes, and once they understand where their datas are, it's not always wise, or necessary to move all their data to the Cloud. So, Deloitte's approach or recommendation is to have a hybrid approach. So that they can keep some of their legacy datas, data assets, in the on premise and some in the Cloud applications. So, Informatica, MDM, and GCP, powered by Deloitte, so it acts as an MDM nimble hub. In respect of where your data assets are, it can give you the quick access to the data and it can enrich the data, it can do the master data, and also it can protect your data. And it's all done by Informatica. >> Describe what a nimble hub is real quick. What does a nimble hub mean? What does that mean? >> So it means that, in respect of wherever your data is coming in and going out, so it gives you a very light feeling that the client wouldn't know. All we- Informatica, MDM, on GCP powered by Deloitte, what we are saying is we are asking clients to just give the data. And everything, as Rajeev said, it's a white-glove approach. It's that from engagement, to the operation, they will just feel a seamless support from Deloitte. >> Yeah, and just to address the nimbleness factor right, so we see clients that suddenly need to get into new market, or they want to say, introduce a new product, so they need the nimbleness from a business perspective. Which means that, well suddenly you've got to like scale up and down your data workloads as well, right? And that's not just transactional data, but master data as well. And that's where the Cloud approach, you know, gives them a positive advantage. >> I want to get back to something Abhiman said about how it's not always wise or necessary to move to the Cloud. And this is a debate about where do you keep stuff. Should it be on on prem, and you said that Deloitte recommends a hybrid approach and I'm sure that's a data-driven recommendation. I'm wondering what evidence you have and what- why that recommendation? >> So, especially when it depends on the applications you're putting on for MDM, and the sources and data is what you are trying to get, for the Informatica MDM to work. So, it's not- some of your social systems are already tied up with so many other applications within your on premise, and they don't want to give every other data. And some might have concerns of sending this data to the Cloud. So that's when you want to keep those old world legacy systems, who doesn't want to get upgrades, to your on premise, and who are all Cloud-savy and they can all starting new. So they can think of what, and which, need a lot of compute power, and storage. And so those are the systems we want to recommend to the Cloud. So that's why we say, think where you want to move your data bases. >> And some of it is also driven by regulation, right, like GDPR, and where, you know, which providers offer in what countries. And there's also companies that want to say "Oh well my product strategy and my pricing around products, I don't want to give that away to someone." Especially in the high tech field, right. Your provider is going to be a confidere. >> Rajeev, one of the things I'm seeing here in this show, is clearly that the importance of the Cloud should not be understated. You see, and you guys, you mentioned you get the servers at Google. This is changing not just the customers opportunity, but your ability to service them. You got a white-glove service, I'm sure there's a ton more head room. Where do you guys see the Cloud going next? Obviously it's not going away, and the on premise isn't going away. But certainly, the importance of the Cloud should not be understated. That's what I'm hearing clearly. You see Amazon, Azure, Google, all big names with Informatica. But with respect to you guys, as you guys go out and do your services. This is good for business. For you guys, helping customers. >> Yeah absolutely, I think there's value for us, there's value for our clients. You know, it's not just the apps that are kind of going to the Cloud, right? I mean you see all data platforms that are going to the Cloud. For example, Cloudera. They just launched CDP. Being GA by July- August. You know, Snowflake's on the Cloud doing great, getting good traction in the market. So eventually what were seeing is, whether it's business applications or data platforms, they're all moving to the Cloud. Now the key things to look out for in the future is, how do we help our clients navigate a multi Cloud environment, for example, because sooner or later, they wouldn't want to have all of their eggs invested in one basket, right? So, how do we help navigate that? How do we make that seamless to the business user? Those are the challenges that we're thinking about. >> What's interesting about Databricks and Snowflake, you mentioned them, is that it really is a tell sign that start-ups can break through and crack the enterprise with Cloud and the ecosystem. And you're starting to see companies that have a Sass-like mindset with technology. Coming into an enterprise marketed with these ecosystems, it's a tough crowd believe me, you know the enterprise. It's not easy to break into the enterprise, so for Databricks and Snowflake, that's a huge tell sign. What's your reaction to that because it's great for Informatica because it's validation for them, but also the start-ups are now growing very fast. I mean, I wouldn't call Snowflake 3 billion dollar start-up their unicorn but, times three. But it's a tell sign. It's just something new we haven't seen. We've seen Cloudera break in. They kind of ramped their way in there with a lot of raise and they had a big field sales force. But Data Bear and Snowflake, they don't have a huge set in the sales force. >> Yeah, I think it's all about clients and understanding, what is the true value that someone provides. Is it someone that we can rely on to keep our data safe? Do they have the capacity to scale? If you can crack those things, then you'll be in the market. >> Who are you attracting to the MDM on Google Cloud? What's the early data look like? You don't have to name names, but whats some of the huge cases that get the white glove service from Deloitte on the Google Cloud? Tell us about that. Give us more data on that. >> So we've just announced that, here at Informatica World, we've got about three to four mid to large enterprises. One large enterprise and about three mid-size companies that are interested in it. So we've been in talks with them in terms of- and that how we want to do it. We don't want to open the flood gates. We'd like to make sure it's all stable, you know, clients are happy and there's word of mouth around. >> I'm sure the end to end management piece of it, that's probably attractive. The end to end... >> Exactly. I mean, Deloitte's clearly the leader in the data analytics space, according to Gartner Reports. Informatica is the leader in their space. GCP has great growth plans, so the three of them coming together is going to be a winner. >> One of the most pressing challenges facing the technology industry is the skills gap and the difficulty in finding talent. Surveys show that I.T. managers can't find qualified candidates for open Cloud roles. What are Deloitte's thought on this and also, what are you doing as a company to address it? >> I mean, this is absolutely a good problem to have, for us. Right, which means that there is a demand. But unless we beat that demand, it's a problem. So we've been taking some creative ways, in terms of addressing that. An example would be our analytics foundry offering, where we provide a pod of people that go from data engineers you know, with Python and Sparks skills, to, you know, Java associates, to front end developers. So a whole stack of developers, a full stack, we provide that full pod so that they can go and address a particular business analytics problem or some kind of visualization issues, in terms of what they want to get from the data. So, we teach Leverate that pod, across multiple clients, I think that's been helping us. >> If you could get an automated, full time employee, that would be great. >> Yeah, and this digital FD concept is something that we'd be looking at, as well. >> I would like to add on that, as well. So, earlier- with the data disruption, Informatica's so busy and Informatica's so busy that Deloitte is so busy. Now, earlier we used plain Informatica folks and then, later on because of the Cloud disruption, so we are training them on the Cloud concepts. Now what the organizations have to think, or the universities to think is that having the curriculum, the Cloud concepts in their universities and their curriculum so that they get all their Cloud skills and after, once they have their Cloud skills, we can train them on the Informatica skills. And Informatica has full training on that. >> I think it's a great opportunity for you guys. We were talking with Sally Jenkins to the team earlier, and the CEO. I was saying that it reminds me of early days of VMware, with virtualization you saw the shift. Certainly the economics. You replaced servers, do a virtual change to the economics. With the data, although not directly, it's a similar concept where there's new operational opportunities, whether it's using leverage in Google Cloud for say, high-end, modern data warehousing to whatever. The community is going to respond. That's going to be a great ecosystem money making opportunity. The ability to add new services, give you guys more capabilities with customers to really move the needle on creating value. >> Yeah, and it's interesting you mention VMware because I actually helped, as VMware stood up there, VMCA, AW's and NSA's offerings on the Cloud. We actually helped them get ready for that GA and their data strategy, in terms of support, both for data and analytics friendliness. So we see a lot of such tech companies who are moving to a flexible consumption service. I mean, the challenges are different and we've got a whole practice around that flex consumption. >> I'm sure Informatica would love the VMware valuation. Maybe not worry for Dell technology. >> We all would love that. >> Rajeem, Abhiman, thank you so much for joining us on theCube today. >> Thank you very much. Good talking to you. >> I'm Rebecca Knight for John Furrier. We will have more from Informatica World tomorrow.

>> Live from Las Vegas, it's theCUBE covering Informatica World 2019. Brought to you by Informatica. >> Welcome everyone, you are watching theCUBE. We are kicking off a two-day event here at Informatica World 2019 in Las Vegas. I'm your host, and I'm co-hosting along with John Furrier. It's great to have you. Great to be here. >> Great to see you again. >> So, Informatica is really sitting in the sweet spot of a fast-growing area of technology, cloud and big data. I want to ask you a big question. Where is the market? What do you see happening in this sweet spot area? >> Well we're here in Informatica World. I think it's our fourth Cube coverage. We've been following these guys since they've gone private two years ago in depth. Interesting changeover. They went private just like Michael Dell did with Dell Technologies. And then they went public in great performance. We said at that time, if they can go private with the product skills that they have in their senior leadership, they could do well. And they've been on the same trend line, which has been really positive data. Now data is the hottest thing on the planet. This is the theme of the industry. Data is everything. Machine learning needs data. Data feeds machine learning. Machine learning feeds AI. This is a core innovator. Now the challenge is on the enterprise side is that data is structured. It's in all these different databases. So in an enterprise, data's kind of has all these legacy structures and legacy systems. And the cloud for instance. Cloud is where SaaS wins. And SaaS winners like Zoom Communications, Air BNB, you name all those successful cloud data companies. Data's at the heart of their value proposition. And data is unencumbered. There's no restrictions. They use data, data as analysis. They look at customer behavior, AB testing. So data is the heart of innovation. This is Informatica's plan here. CLAIRE is their AI product. Their theme is kind of clever. CLAIRE starts here. And this is really the focus for Informatica. Their opportunity is to be that independent vendor supplier, the Switzerland as it has been called, the neutral third party to bring data together On Premise and Cloud. That's what they're saying. That's their opportunity. The challenges are high. The data business is being regulated. We talk about it last time. You know, privacy, GDPR one-year anniversary, Microsoft's calling for more privacy. As more regulation comes in, that puts more restrictions on data. That requires more software. That creates overhead. Overhead is not good for SaaS business models. And that is where the conflict is. This is the opportunity, and if they can overcome that as a supplier, then they can do well. And data growth is just massive. Cloud, IoT Edge, you name it. Data is the center of the value proposition. >> Well, and we're going to have a lot of great guests on the program this week, in particular we're going to have Sally Jenkins talking about these four customer journeys that the customers are going on. And in fact data governance and privacy is one of the big tenants. So, they are making, they are saying this is our wheelhouse. We can do this. We can help you do this. >> Well, the thing is we're going to ask every guest the question of the week is What's the skill gaps? Because digital transformation although very relevant is only as good as the people and the culture that's behind it. And that's a theme that we hear all throughout our different CUBE events. If people have the culture for it, they could do it. DevOps is another word that has been kicked around. But ultimately if you don't have the people and just machines, it's really going to be a tough balance to strike. You need the machines, you need the data, you need the people. And this is where the challenge is in the industry. I think the skill gaps is a huge problem for digital transformation. It's to me the big blocker in seeing innovation accelerate. So customers are now having that journey. They're starting, they really think about how to architect their enterprise with an On Premise, with a Legacy and Cloud Native with full SaaS. And the companies that can get to a SaaS business model, managing the On-Premise's legacy will have a winning shot at taking new market share or top one down incumbents in leadership positions. >> I'm really excited about this idea. Asking people about the skill gap and where the next generation of jobs are going to be in big data. I saw a statistic, a survey from Google, 94% of IT managers can't find qualified candidates for open Cloud roles. That is-that's astonishing. I also saw an interesting quote from Tim Cook, who recently said that half of Apple's new hires are not going to have a college degree this year. He said when our own founder didn't have one. It kind of really shows you what you can do. >> It's really early. >> You might not need this degree. >> First of all, it's really, first of all I agree that degrees don't really matter. In some cases, old degrees might not apply to the new jobs. I'll give you an example. My daughter just graduated from Cal Berkeley this week. And they had the inaugural class of data, data science, data analytics. For the first time, first graduating class. That's a tell-sign that we're at the early, early stages. But data science can come from anyone. You could be, you know, anthropologist, you could be any any skill. You can solve a problem, you're good at math. You can see the big picture. You're seeing data science really becoming a career. And again, there's just not enough job openings. And data science isn't just for the data jockeys out there who just want to do data. There's cyber security, huge data-driven. Everything is data-driven. The big growth area in the enterprise is the IoT, the Edge. As devices come online for manufacturing to oil rigs to wind farms. The edge computing is a huge thing. And that's a data problem. Everything is a data problem. So this is where the industry is focused I think Informatica was really on it early. And now everyone's jumping in. You got Amazon, Google, Microsoft, the big cloud players, and you got all the existing incumbent enterprise suppliers all putting data at the center-value proposition. You know you got a lot of competition now for Informatica, and they have to make some good moves here. And what I'm going to be looking for here, Rebecca, is how they transform as a company. Because I think that they have to be an integration company. They want to be that Switzerland. They got to integrate to all the clouds. They got to integrate to all the different platforms and environments on the enterprise and create that one operating model. And this is something they say they want to do, and we're going to ask them. >> And you not only called them Switzerland, they've called themselves Switzerland. And so I think that they are. They do want that. They want that for themselves. They want they are having these partnerships with all of the major cloud providers. So, you said this is what you're going to be asking. This is what you're going to be looking for. What is it that you think will set them apart? >> I think ultimately I think Informatica's got a great management team when it comes to product and engineering. One of the things I've been impressed with is they get the product around data. The only thing I think that could be a headwind for them as a challenge is this regulatory environment. I brought that up earlier. I think this could be a challenge and an opportunity, and it could be the difference maker because there's no question that their value proposition or how they're dealing with data management, their deals we're going to hear about with the cloud and all of the new innovation they have with CLAIRE and AI. Certainly that's good. But if you don't have data-feeding machine learning, and the data's hard to get at, and it's regulated, you got clouds with geographies and countries have new regulations. This is a complicated problem. If they could create software to make that easier and create an abstraction layer and use the power of the cloud, I think they could have a winning formula. So to me, that's a killer opportunity. And then making data work for SaaS-oriented business models, On-Premise and in the cloud. >> I think you're absolutely right and we heard Anil Chakravarthy say this today. Data needs the machine learning an AI, AI machine learning need data. And any application of AI and machine learning is only as good as the data that's been collected. So, the other big challenge is what I think is going to be really exciting about for this show is seeing all of these use cases. In industry after industry we are seeing applications of AI and machine learning transforming business models and approaches and leadership and big ideas around these important game-changers in our industry. >> Yeah, one of the things that's interesting I had an interview with in the city of Howie Xu, who's formally VMWare engineer, entrepreneur, sold his company to Zscaler. He's an AI guy, and we talked about the SaaS business model. And one of the things that's key is if you don't have the data feeding the SaaS, it's not going to work, so to me if they could get that data back in to the system quicker with all that regulation, that's going to be a game changer. And I think they got to start thinking how they can show the customer proof points. That's going to be interesting when the customers start adapting in that scale. >> And as we've also said many times on theCUBE the governance is kind of a mess itself. I mean Washington doesn't quite know what to do with this and how to regulate it. How do you think that these technology companies should be working with Washington on this? >> Well that's a loaded question. First of all, I think the government is not the bellwether for technology innovation. In fact, I think innovation is stifled by too much regulation. There's got to have a balance there. One of the things that's positive is in the cyber-security area you see private, public partnerships go on where there's some joint sharing. I think cloud is going to be a catalyst. We're going to have the VP of marketing from Amazon web services on, I'm going to ask him that direct question. This is where the action is. So I think this notion of collaboration the enterprise and cloud players is going to be key because if you look at like just how search engines used to work back in the old days, if it was not encumbered by all this legacy infrastructure in the enterprise, it works great. The more you add complexity to things, the more you need software. The more you need software, you need horsepower to compute. You need more storage. So all these things are creating a different environment than it was just three years ago. So, you know can they adjust, can the industry shape itself out? I think the industry needs to lead here, not the government. >> What about the idea of Informatica working together with customers and making sure that they are in fact deriving value? Because I mean I think that's the other thing is that all of these companies know they need to have an AI strategy, they need to be using more machine learning. It's very complicated as you said. But then there's this question of am I really going to see a return of investment on this? >> Well, I think Informatica can do a good job working with cloud architecture and looking at because you got again IoT edge is coming around the corner. But if they can nail the architecture On-Premises and Cloud, that is a great start. The second thing that Informatica can help customers at, and this is a customer challenge, is where do you store the data? Because moving data around is very expensive. So this scenario is where you want it all on the cloud. This scenario is where you want it all On Premise. And this scenario is where you want it on both locations. And then with the edge, you want to move data I mean compute to where the data is. So, data becomes a very critical piece of the overall architecture and whoever can build this operating system's mindset will have a winning formula, and again being neutral is a critical strategy. And the more Informatica can help enterprise be more like consumer companies, the better. If you look at Slack for instance, it's an IPO candidate coming out very popular. It's just a chat kind of message board app. What made Slack successful is that they built connectors and APIs into all different tools. If Informatica could do that, that would be a winning formula because they want to be data brokering, they want to be data connecting, and they want to feed the applications and machine learning data. If they can't get data to the machine learning and AI, the AI will not be sufficient. And that will be a problem. >> Well, this is all the things we are going to be talking about over these next two days. John, I look forward to it. I'm Rebecca Knight, you are watching theCUBE. (lighthearted techno music)

>> Narrator: Live from Las Vegas, it's theCUBE covering Informatica World 2018, brought to you by Informatica. >> Welcome back, everyone, this is theCube, exclusive coverage of Informatica World 2018, live in Las Vegas at the Venetian Ball Room here. I'm John Furrier, the host of theCUBE, analyst here at theCUBE, with Peter Burris, analyst and also my co-host these past two days. Our next guest is Bruce Chizen, who is the executive chairman of Informatica, one of the leaders of the company. Great to have you back, good to see you. >> Good, great to be here, guys. >> It's like an annual pilgrimage. We get together here, and hear the perspective. Also, we had Jerry Held on yesterday, board member, very senior in the industry. You guys are legends. You've been there, done that. You've seen how many waves, how many waves have you seen? >> Yeah, I was just sharing with somebody, I was at Microsoft in 1983, so I guess I go back a little while. >> You've seen a lot of waves. Okay, so this wave is interesting, because we were talking about the keynote and talking about the timing of how data, super important, there's no debate on the role of data, but timing in the industry, you got cloud, multi-cloud, you've got things like containerization, Kubernetes, you're starting to see that microservices model appear. The role of virtualization is not as prominent as it once was, given what's happening in the stack, but certainly, data is super-strategic. GDPR, this Friday, goes into action. So, shot across the bow with GDPR, data at the center. Explain the phenomenon. >> Yeah, so, look, what's happening is, more data is being generated today than ever before. I think Anil Chakravarthy, CEO, said this morning during his keynote, it's increasing twofold every six months. It's just an amazing amount of data that's occurring, both through data warehouses, as well as realtime data through things like IoT and other streaming types of mechanisms, and at the same time, every enterprise in the world is trying to figure out how to transform this business, leveraging that data, and that data exists across so many different platforms, whether it's on-premise, whether it's the cloud, whether it's a combination of both, whether it's multiple clouds. So, trying to homogenize all this data, or to be able to capture it and get it usable in one place for analytics, for decision making, is an incredible task. Fortunately, it plays into Informatica's strength. >> I want to get your thoughts on two dimensions to that, because I agree, that's all happening, but you add the pressure to scale with the cloud, okay, that is a huge deal, okay, as well as, build then new applications faster. So, this pressure, not just to kind of get it right in the data, you got to scale with the cloud, so there's a lot of big things being built out. >> Yeah, and it's not as simple as the cloud, it's the combination of leveraging on-premise workflows with the cloud, with new applications or new workflows, and how do you make sure you have data integrity between those two environments? And I'll add another layer to it, most enterprises don't want to be held hostage to one cloud infrastructure provider, and what you are seeing is, those enterprises leveraging multiple cloud infrastructures. So, between the data that's on-premise, the data that might be residing in Azure, data that might be residing in AWS, trying to make sure that there's one view of this data, and that it's secure, it's cleansed, it's of high quality, is a greater task than ever before. >> So, Bruce, let me build on that and see if you agree with this. It sounds to what you're suggesting is that we've got all this data, it's growing very fast, but we have to be able to do two things to it. We have to be able to organize it, and we have to turn it into objects or things that have business value so that we can generate returns on it, appreciable increasing returns on it. Is that kind of the centerpiece of what we're talking about here at Informatica World? >> Absolutely, and if you look at the quick success of the enterprise data catalog that was launched last year and the number of customers that have already adopted the platform, which really is a catalog of the metadata that sits across the data across the entire enterprise. The fact that so many customers have adopted a 1.O product that quickly is validation that they want to be able to leverage and take advantage of all of this data that's sitting in thousands and thousands of different entities within their own enterprise. >> So with your experience, you think the adoption's greater than what you've seen, but put it in comparison, compare the magnitude of that adoption. >> We expected a handful of customers to adopt it in the first year, we have hundreds of customers that have adopted it in the first year. >> John: So, well over the forecast. >> Well over our forecast. >> Well, they bought it. Are they adopting and changing the practices, evolving their organizations, imagining new ways of generating work, as a consequence of being able to discover and apply data faster? >> They know they want to analyze their data. They want to use tools like Power BI, tools like Tableau. What they haven't been able to do is use those tools as effectively as they would have liked to, 'cause they didn't a mechanism to capture all that data or to view all that data across their entire enterprise. The other challenge they had was there was no data integrity that existed, because the data in one repository was different than the data in a different repository. To be able to have one view of that data means that the information that they're analyzing is accurate, which didn't exist before. >> Alright, so what's next? That's table, not table stakes, but the first low-hanging fruit. Value proposition is, okay, I get a sense of the metadata, where is everything, so that's check. >> Yeah, so, there's two things in my mind, one is making sure that we make it easy for them to use any of the cloud platforms. So today, the company announced their relationship with Microsoft, with Azure, with Informatica's IPaaS running natively on Azure, in addition to what already exists with Amazon AWS. The second thing is to continue to add AI capability to that metadata, so instead of a person having to navigate and collect all of that information, is to use intelligence to be able to make sense of-- >> John: Machines. >> Machines. >> Streaming the data in faster, handling the volume. >> And being able to throw out garbage and use only what's really-- >> That's what I want to push you on, so everybody said, oh, we're going to apply AI, but they don't say what the AI is going to do, and I think specifically, as it relates to MDM, as it relates to catalogs, replaces some of these other things, it's identifying patterns, identifying inconsistencies in data objects, it's identifying how it feeds different workflows commonly. That kind of stuff. Are there other things that we're really trying to apply this AI to to improve data quality, data consistency, data flows, usability? >> It's going to do all of that, which is what was, it required a human to do in the past. In addition, as the machine, as the AI engine or the machine learns, the ability to do this more quickly is going to become apparent. So, with this massive amount of data being exposed, the last thing you want to do is to have the decision maker being slowed down. So AI is just going to speed it up significantly. >> Bruce, talk about the state of the company. Obviously, we've had Bruce on, we tried to get a little teaser out of him on what's going on with the board level, stock option, grants, so on and so forth. I'm only kidding. Obviously a valuable company, we've been watching it and covering you guys and pointing out, actually earlier on than others, the benefits of the data. Certainly it's become a very valuable private company. Once public, now private. You were involved in that journey, outcome for an offering soon, or bankers must be licking their chops, prospects, not saying when are they going public, I don't want to ask that question, but there's obviously a trajectory. What's the company's position, vis-à-vis the financial health and growth? >> Informatica will be one of those rare instances in the world of private equity, where a sponsor has come in and decided on a growth model top line revenue versus bottom line profitability. >> You mean shedding the parts? >> Shedding the parts, really squeezing the company for maintenance revenue, for cash. What Permira and CPP, the two investors, have done has really helped the company to continue to focus on growth. So, when we look at R&D expenditures, they're close to 200 million dollars, which is well above industry average as a percentage of revenue. >> So they came in to build the company. >> Came in to build it, and more importantly, grow it. It's exceeded our expectations, haven't determined a timeline to go public, there is a possibility you could see an offering sometime in 2019. >> And we talked with also Jerry and others yesterday about this notion of timing, right? Timing's everything in life. You couldn't ask for a better time to be the Switzerland, or whatever domicile you want to call that's neutral to multiple platforms. Certainly, the data layers' a nice position, you've got companies like NetApp underneath, having a nice layer, storage, so you've got the data fabric there, you guys are playing across multiple clouds. This makes it a unique opportunity. Now, why is this time for being the Switzerland of data important, and how should customers look at this timing of the movement for Informatica vis-à-vis the industry trend? >> Yeah, enterprises want to make sure they don't get held hostage to any one vendor. That happened in the past with the likes of an SAP for ERP. They don't want to fall into that trap. They want to be able to move their workflows between Azure, between AWS, between Oracle, and continue to have legacy workflows on-premise where necessary. So, they want someone, they want a provider who's going to provide them with a solution that's not biased and is not going to show any preference towards any one provider. Many years ago, I had the privilege of being the CEO of Adobe, and if you think about it, PDF, Acrobat, was the Swiss solution, or the Switzerland of documents. And the reason why PDF became so popular and became the standard was because nobody was comfortable with .DOC being that solution. The same is true-- >> Because of the incompatibility of the operating systems? >> .DOC, two reasons, one is nobody wanted to be held hostage to Microsoft, they already felt uncomfortable with Windows and Office. >> Ended up becoming hostage to Microsoft anyway, but that's all good. >> And, at the same time, .DOC showed preference towards a Microsoft environment. >> Peter: And it was the wrong technology. >> And it didn't work across platform. >> Exactly. >> In the case of Informatica, Informatica is the only scaled provider in the data business that has a solution that works across all environments, all vendors, all providers, hybrid, on-premise, cloud, multiple infrastructure providers. >> So, my summary of what everything you said Bruce is that Informatica today is a company that's going to help you organize your data, so you can put more data to work. >> Absolutely. >> Alright, Bruce, thanks for coming on. Great to see you, always a pleasure. We've got to do it again in the studio in Palo Alto, get you in, get some information out of you on what's going on with the public offering. (Bruce laughs) Great company, congratulations, it's been a fun ride, I can't wait to hear all the war stories when it's all said and done, great job. Switzerland of data here. At Informatica World, it's theCUBE, out in the open, sharing you the data here in Las Vegas. More live coverage, stay with us, Be right back. (techno music)