>> Announcer: Live, from Las Vegas, it's theCUBE! Covering Informatica World 2018. Brought to you by Informatica. >> Hello welcome back everyone, we're here for exclusive CUBE coverage here at The Venetian in Las Vegas, day one, getting setup for the exclusive pavilion opening kick-off party, we've been here all day, for two days, I'm John Furrier your host of theCUBE, with Peter Burris, analyst at SiliconANGLE, we keep on theCUBE, our next guest, Board Member of Informatica for 10 years now, CUBE alumni Jerry Held, industry legend, veteran, been there done that, seen all the ways of innovation, Jerry great to see you, thanks for coming on! >> Great to be here, nice to see you guys again! >> Ten years at the board for Informatica, a lot, that's like, how many waves can happen in 10 years, what's been the journey, what's been your view? You're in all the board meetings approving all the, all the hires and stock option grants, and all the action, you see in the front row what's happening, what's the story? >> Well, it's been a great ride, it's an interesting company, I've been on a lot of boards, I've lost count of how many, both startups and then big public company boards, but Informatica's been a really fun ride. When I joined, we're goin' through super growth, my really good friend Sohaib Abbasi was running the place, he had a phenomenal 10 year run, I think 36 quarters of record growth in profit, just unbelievable, took it from an ETL company back when it started, to a full data integration company, kind of went from the first phase of data to the second phase where it was more than just moving data to a data warehouse, but all phases of data integration, and that was terrific, and then we got a point where it was time for another phase, and lot of things were happening, not only in terms of where the company was going, but where the industry was going. >> And what year was that, when that happened? >> So that was about two and a half, three years ago, when we decided that the best route was actually to go private, because some of the transitions were going to be pretty profound, for instance, just the model of selling software going from license to subscription, requires a dip in revenue, it requires restructuring your field, a lot of changes. >> John: A lot of product work? >> Yeah, yeah, so, we did go very successfully, we went private, and I don't know for some reason, they asked me to stay on the board through that transition, (John and Peter laughing) >> and it's been interesting being on the private side, now that it's a private company, it's run differently, we have some great private equity firms who are the investors, owners of the company, the board makeup is completely different, and we have a lot of people with a financial look at the company, but they're growth investors, they're some PE firms, that come in, and take a company apart, just try to get the most they can out of it. Luckily the investors that we've found believed in the future of the company, it's a growth company, it just needed to go through some restructuring. We're also really fortunate, when Sohaib decided it's time to retire, to promote Anil to be the CEO, and he's turned out to be fantastic, and we've had a number of changes really bringing in some fresh blood, new people into positions, really strengthen the team, and in the last couple years of Sohaib's tenure, he put a real focus on innovation, because we had gone down a path of requiring a number of pieces, putting them all together, but the innovation had sort of slowed down, well he started the process, and it really picked up speed through this transition, so the company has come out with a series of really new, innovative, products. So now, Informatica's like one of the hottest pre-IPO companies in the industry, if you think about enterprise software companies, >> Yeah, and we talk, I mean we've been here, watchin' from three, four years ago, we talked to Anil before he was the CEO, and he was doing the products, they brought in some product people, and they did the work, they buckled down. Okay, so I got to step back, before we came, before you came on, you and I were talking about waves, and you've seen waves, the relational database wave, and our comment was, people tend to poo-poo them, well that's never going to happen, eh, it's never going to happen. So I got to ask you, take us through what the wave is right now, what're you excited about because certainly, there's no doubt that commerce on this scalable cloud has opened up a new, kind of a new aperture, if you will, of opportunity, and it's impacting everybody, data is not just a category, it's fundamental in the fabric of this next big wave, what is your vision of this wave, what's exciting you? Take us through that. >> Well as we were saying, I've been in this data management business for 50 years now, so I've seen a lot of waves, 'about every 10 years you get a big wave, and I was there back at the birth of the relational database client server, and web, and cloud, and SaaS, and all these, each one, when they start, people poof--ooh, it's very cool, but, never take off, and there's a lot of people who miss great opportunities at the beginning of a wave, now we're clearly well into the cloud wave, as I think most people realize it's for real, and there's a lot happening. The one that I'm most excited about right now is in what I would call, you know we've had DBMS, Database Management Systems, I'll make up a new term right here, I've never used this before, so this is a first on your show >> John: Exclusive. >> Instead of DBMS, how about DAMS, Data Asset Management System? That's what we need. We have got such a proliferation of data, relational databases, no sequel databases, hadoop databases, we've got structured, unstructured, text, image, every kind of data, but it's proliferating at an amazing rate, right, we've got all kinds of types of data, sources of data, users of data, people now want to use data, not just the IT people but end-users, but it's out of control. We have this asset, and everybody talks about it, you can see here at these session, what's going to transform your business? Data, data disruption. But it's out of control. Nobody knows where the data is. Ask the CFO where all the financial assets, they can show you the spreadsheets, they can show you the reports, ask the Chief Information Officer, Chief Data Officer, they can't tell you. So what we need to do is manage the data asset, and how are we going to do that? As far as I'm concerned the single-most exciting thing coming out of Informatica, and there's a lot of exciting things at this conference, far-and-away to me the most exciting thing Enterprise Data Catalog. That is a Data Asset Management System, it allows you to look across every type of data in the enterprise, on-prem, in the cloud, all kinds of data, and get your hands around it, and you need to do it for two big reasons. One: Risk reduction, and two is: Reward enhancement, in other words, you have a way to reduce risk, improve governance, and, where you can just look at the news everyday, Facebook, GDPR, which is coming-- >> Friday. >> this week, this week is very timely, Europe is way ahead of us here, they're forcing companies to get their act together, but how do you do it? You need to get your act together on managing the data asset it's not managing the actual data, it's managing the metadata, where is the data, who has access to it, what's the security, how many copies do you have, how many different views of a customer do you have that are inconsistent? The way you need to do that is through an enterprise data catalog, and Informatica has a super exciting product, the most exciting products in the 10 years I've been on the board, this is the single most exciting product the company's come out with. >> Sounds like your bullish on this one, so we'll put that as a check-mark on that one. Let me ask you a question just to kind of take that to the next level. Jerry, what is this order of magnitude impact, in your opinion, obviously it's a big wave, can you kind of just give us a perspective, waves have multi-year lives, sometimes 10 plus years, Pat Gelsinger, former intel, would always talks about waves, sometimes they're 10, 20 year waves, what is the impact of this one, specifically around the catalog, what's it going to impact, order of magnitude, share your color commentary on how you see it shaping out. >> Well it's going to have these two huge impacts, let's just talk about on the risk reduction side, on the governance side, I mean, think about the potential impact, to Facebook, of losing control of their data, that company could well get split up. I mean there's a lot of talk about splitting up, how big an impact is that? Pretty damn big, right? >> Pretty big, yeah. >> I mean, it's huge. >> Yeah, billions, trillions. >> Yeah, and those kinds of risks are out there, and they've reached a point where the public, the government, is no longer willing to put up with it. Now think about the rewards side of it, the positive side. If you can get control over your data, and now you're doin' all this great analytics, people create data lakes, you know what's in those data lakes? Most of them are data swamps. They put a lot of data in there, but they don't know what's there. If you could take all that data in the data lakes, plus the stuff you have in the cloud, plus stuff you have other places, and now you want to answer that hard question. Get your analysts to be way more productive. How important is it when you get that insight, how do you measure the business value? I'm sure on your show you've had dozens of people give you a specific instance of oh, look what I did with Tableau, great product, I did all this stuff, and I discovered this, and I changed my business, right? You've had that? >> Oh, insights, come out of the woodwork, everywhere. >> Okay, however, ask the question, How many insights didn't come out, because these analysts didn't know where the data is, they didn't have access to all this data? They did find something, but think about what they could have found if they had a complete view of all the enterprise data, and how it related to all the other data coming from social media and everything. So, what's the value of an enterprise data catalog? I think it's enormous, enormous! >> Peter: But Jerry it's, so I think that's an interesting game, thought experiment, but if I were to combine that with another thing that excites me about what I'm hearing this week, the reality is there aren't enough analysts in the world to find it all. When we start applying machine learning to the process of creating, maintaining, sustaining, the understanding of the data assets, reforming, reforging data assets, ensuring that we are, not dependent on a manual processes in a catalog, it's that combination that makes it possible to actually augment the way that human beings look at these things. Ultimately these types of systems are going to provide options to the business. >> Yeah, and you hit it on an absolutely key point, what does it take to have a great data catalog? There are a number of companies that are trying to do data catalogs, some of 'em are doing small pieces, cataloging bits and pieces of the enterprise, interesting, but the word enterprise is key, you need something that spans the entire enterprise. And when you get that complicated, the human brain can't deal with it, so, you've hit on maybe on the most important points, you must have an enterprise data catalog that's based around a AI, machine learning, at least tool assistant. You're going to still have people that are going to be curating, you're going to have people that are going to be adding glossaries and all kinds of things, but at the core, there's so much data that you need to take the machine learning technology that's moving along quite quickly, and try to figure out what are all these relationships? That is at a core component of it. >> So we talked, so I want to throw this at you, you tell me if you agree with me. What that comes down to is, if everybody talks about AI, you talked about it earlier, taking jobs away, doing the work, increasingly I think we're going to look at AI as a technology that provides humans options, better forged, better formulated, well structured options, based on data, and that increasingly the thing about creating data value is, is your system creating new classes of options for pursuing the value of data, and this combination thing, AI, augmenting, by presenting options to human decision makers so that they can look at all that range, all those possible vectors that they could be pursuing, and choose the ones that are most attractive. >> Yeah I think there's two things-- >> Does that make sense? >> So there's two parts to it, one: you're exactly right, you can augment and give choices, but before it does that, it can eliminate a massive amount of just grunge work, most analysts, this is a well documented fact, most analysts spend 80% of their time in data prep, and 20% in analysis, that's pretty well industry standard right now, if you're doin' better than that you're doin' great. And what you can do, if you do the right form of cataloging get the data organized and then you use things like MDM, and data quality to cleanse it. Now you get to the point where the analyst is doing analysis and they're doing things, number one: That are more interesting, number two: That are more productive, and number three: That are going to have a bigger effect on your bottom line. >> Peter: Right, right. >> Let's talk about the role of data when it comes to IOT Edge for instance, in the cloud, okay this is now, 'cause of the scale, you mentioned the scale with AI, that helps with the scale of data coming in, you got that, now a customer's looking at an architectural shift with cloud, multi-cloud, and IOT whether it's Edge, or whatever that's defined as. How does the cataloging and the data vision you put forth, impacted by that, accelerates it, does it change it radically for the buyer, the user, the enterprise, how does that enterprise customer think about--? >> Well, it's another important source, so we have all these different sources of data, and a growing source is going to be IOT data, and if it's streaming in, going in to some repository, it needs to be cataloged, and correlated, with the rest of the data in your enterprise. Right now, a lot of IOT data is just going into some system off to the side, not correlated with the mainstream data. The thing that, I think is the big shift, when you go from DBMS, Database Management System, we're focused typically on a single data, whether it's IOT data, or it could be accounting data, the focus was on just that data, the difference with Data Asset Management System is think about your data as a whole, across your whole enterprise. >> A portfolio. >> The whole, the whole of your data asset, how do you manage that, it's not the bits and bytes, it's the overall thing, it's not the actual data, it's actually the metadata that you're managing. >> Or it's the data as it's being used, and the metadata describes data that's being used, so data, like anything else, you apply it to work, it generates value. Metadata describes how it's being applied, and then the underlying data elements are given context and semantic richness by the metadata. >> Jerry: Exactly, exactly. >> Alright so here, I'll throw out the old, if I'm Joe six-pack out in the street, I hear catalog, I go whoa! >> Yeah, he's talkin' about this stuff all the time! (chuckles) >> I go whoa, catalog? In my mind I get a mental model of a centralized database, I think hacker! 'Cause you know, government and all the hacks goin' on, you know, decentralized data's probably better, distributed data? So I hear catalog, my mind goes centralized, is that the right way to think about it, or obviously, I mean share, because security's critical on this. >> Absolutely, and so as you bring this view of data, just like when you have your financial books, where you have a central view of all your financial assets, there needs to be security, you have to have, allow access for people for the appropriate level of information that they're going to pull out, the data asset is no different. So you want to have a full view of all of your data, and you want to have ways to allow and restrict access to the information, it's not the data, it's just where is the data, and each of the data systems have secondary-- >> So it's not centralized, it's just metadata for visibility and auditing-- >> I think there's an important point, and I want to test this on you, 'cause you're askin' a great question. The information model from IBM, we used to, we've had catalogs with databases, we've had catalogs all over the place, highly stylized processes, stylized data, stuck in a catalog. One of the things that's especially interesting, is not the idea that we're going to start with a whole bunch of designs and put them in the catalog, but we're going to discover stuff about our data, and the catalog will emerge out of the attributes of data, and how it's working and how it's being used. >> If you, let's rewind back-- >> John: So the answer is no not centralized? >> Well, but it's not-- >> Peter: The metadata may be so much centralized, but the data's not. >> It's not a, we're not trying to do a centrally-designed architecture, so let's rewind 50 years, and go back to the beginning of relational databases, we had schemas, and back in the '70s, people were talkin' about, oh, let's come up with the schema for the corporation, we'll have one group go off, and they'll design everything: failed. Then they had data dictionaries where they were going to put it all in place: failed. And all of these things, where there was an attempt to centrally define and control the structure of data around the enterprise: failed. That is not what we're talking about. Data exists in all forms, with all sorts of schemas and definitions, and all types of databases in Oracle and SAP, and everything all we're doing is taking the metadata and relating it-- >> Peter: Allowing it to merge! >> So that we have a view of where everything is, that data's different than this data, it's managed by different software, but we have one view so that now, when an analyst wants to know how do I get the latest information on customer preferences for purchasing this? I can go here, here, and here, and I'll correlate those, and I'll pull 'em together with some tool. >> Final question, final question for you. If you think that to next level, you're implying, or actually saying, that philosophy of a catalog, implies that it's okay to have a zillion databases, I might have a post-risk database on this application, I might have an unstructured database over here, so in the future world, where we're living in a tsunami of data, apps need databases. So the idea of-- >> And they got to be different. >> And they're going to be a zillion, yeah, a lot of different databases proliferating is not a bad thing under your model. >> Absolutely, and we've tried having one answer, it doesn't work. And even if you ever could get a company, a large company you can't do it, but if you get a company that'd get one form, then they do an acquisition, and now they got other forms. That concept just doesn't work, it has to be a heterogeneous world, and you have to have a way to pull the pieces together, and that's why, just as a final point, I think what Informatica has done with this data enterprise data catalog, which is a phenomenal product, still early days, but growing at a phenomenal rate, fastest growth of any product ever. You need a company that's independent, that's not a stack company, it's not an Oracle or an SAP, it's not a cloud company, or an AWS, or an Azure, or Google, it's not a SaaS company, it's somebody who is the Switzerland of data, who can take data from every place, and just collect that metadata, and it has to be a company that understands machine learning and AI, that can use it to pull it together. >> And they got to work with the clouds too, they got to work with all the clouds. >> And it has to be a company that has interfaces to everything, which is what Informatica is, so it's a perfect fit. >> And it's not going to try to then use that to exact significant control over how everything operates. >> Exactly, and it's not trying to sell you an application, or a database, so, you need that Switzerland, and I think that's why, to me, in the 10 years that I've been on the board, I haven't seen a more exciting product, nor have I seen a customer reaction as dramatic as this, every customer's talking about EDC, and if they haven't before this conference, they will after this conference. (laughs) >> And the timing is critical on this too, talk about timing, the tailwinds for this movement right now, more than ever, sometimes timing is-- >> This week is a, I mean GDPR is a big deal, a big deal, >> It's a signal. >> And what's goin' on with Facebook and others is a big deal so, the timing is appropriate, and the product is fantastic, and I think it's going to be, when we look back next year, and we do this show. >> (laughing) That's great, we have nine years of history, you go back and say hey, 'member you said that? Right? Data is the central strategic asset not some corner case, GDPR is a signal, it's a shot across the bow, for all companies to get in the center. We coined the new term Database Asset Management System. >> No Data Asset Management System. >> Data Asset Management System. >> And we actually have research on that from a couple years ago. >> Okay, well we here, exclusive on theCUBE here, Data Asset Management System, asset is data, it's going to be worth money, it's going to be on the balance sheet soon. theCUBE is here, out in the open, Informatica World 2018. Jerry Held, Board Member, bringing his insight, thank you for sharing the data on theCUBE, we'll be back with more, stay with us, after this short break. (bubbly music)

>> Narrator: Live from Las Vegas, it's theCUBE, covering Informatica World 2018. Brought to you by Informatica. >> Okay, welcome back everyone. This is theCUBE, here at Informatica World 2018 in Las Vegas. CUBE's exclusive coverage. I'm John Furrier, here for the wrap-up of day two of Informatica World, wrapping up the show coverage. Peter Burris has been my co-host all week, chief analyst at Wikibon.org, SiliconANGLE and theCUBE. And Jim Kobielus, lead researcher on AI analytics, big data for Wikibon, SiliconANGLE and theCUBE as well. Guys, let's kind of analyze and dissect what we heard from the conversations. Peter and Jim, we heard from the customers, we heard from the executive management, top partners and top executives. So interesting, and Jim, you've been at the analyst one-on-ones, the keynotes. Good show, I thought it was well done, the messaging, again, continuing the brand. The 25th anniversary of Informatica. Which, that's okay for me, but it's really not 25 years old. It's really like five years old. When the private equity came in, they took the legacy and made it new. >> Well they're a continually renewed company. They're a very different company from what they were even ten years ago, and they've got a fairly aggressive roadmap in terms of evolving into the world of AI and so forth. So they continually renew, as every vendor that hopes to survive inflection points must. >> Jim, what was your takeaway from your sessions? I mean, you saw the keynote, you saw the messaging, you had a chance to sit down one-on-one and ask some tough questions. You heard the hallway conversations amongst the other analysts and customers. What's your personal takeaway? >> A personal takeaway is that Informatica understands that their future must be in the cloud and a subscription model. That means they need to get closer to their core established cloud partners, Microsoft Azure, AWS, Google. At this show, Microsoft, they had the most important new announcements at this show, were all about further integration of the new ICCS, which is the Informatica-- >> Intelligent cloud service. >> Integration and platform service offerings, into the Azure cloud. That was the most important new piece of news in terms of enabling their customers, they have many joint customers already, to bring all of their Informatica assets more completely into the Azure cloud. That was quite important. But there was of lot of showing from AWS here on the main stage and so forth. And we expect further deepening of their Informatica footprint on AWS from those customers. So a, Informatica's future and their customers' future is in public clouds, and I think Informatica knows that the prem-based deployments will decline over time. But this will be-- >> Still good now, so the migration-- >> Well it's a hybrid cloud store. They have Informatica, a strong hybrid cloud store in the same way that an IBM does, or that a Hortonworks does, because most of their customers will have hybridized, multi-cloud models for deployment of this technology for the long term, really, with an emphasis on more public deployments, and I think it's understood. >> Peter, what's your thoughts? You had some great observations and questions. I was listening to you highlighted some of the digital business imperatives that you've been observing and researching and reporting on with the team, but also these guys have been doing it themselves. Any takeaways from you on any change of landscape on digital business, the role of data, the role of the asset. What's your thoughts on that? >> Yeah, I think if we look at the 25 year history, and Jim mentioned there've been a lot of inflection points. The thing that's distinguished Informatica for years is that it always was a company that sought to serve underserved data requirements. So it started out when relational database was the rage, started out doing OLAP and new types of analytics. And then when the data warehouse became what it was it became a data integration issue. And you can kind of see Informatica's always tried to be one step ahead of the needs of hardcore data people. And I think we're saying that here too. They have got really, really smart people that went private so that they could re-tool the company and they are introducing a portfolio that is very focused on the next needs, the next rounds of needs of data people. >> That's a lot of cloud too. >> They're a data pipeline power-- >> Well I would say they're a data pipeline pure player, I think you're doing a-- >> The closest of anybody out there. >> But I think the key thing is, right now, they're at the vanguard of talking about data as an asset, what it means to present data as an asset, tools that should provide for managing data as an asset. And they have the pipeline and all the other stuff, the catalog store that they have is very tied to that. The CLAIRE store that they have is very tied to that. Data is very, very complex. And often it takes an enormous amount of manual labor. >> I think they're checking the boxes on some of the things that I've observed over the years, going back to the early Adobe days streaming data requires some machine intelligence, obviously machine learning, AI, CLAIRE, check. Ingestion of data, managing, getting it all in an intelligent, not a data lake or data swamp, in a fabric that's going to be horizontally scalable-- >> Yeah, absolutely. >> With APIs-- >> Well horizontally scalable actually means something, it means expanding out through APIs and finding new ways of leveraging data. And I think we can make a prediction here based on four years of being here, that Informatica will probably be at the vanguard of the next round of data needs. So today, we're talking about cloud versus on-premise. I wouldn't be surprised if in a year to two years Informatica isn't talking more about how IoT data gets incorporated-- >> And blockchain. >> Yeah, IoT was not mentioned, nor was blockchain, and I think those are kind of significant deficiencies in terms of what we're hearing at this show from Informatica in terms of strategic-- >> Well hold on-- >> But I've think they've got a great team and I expect to see more of that in coming years. >> Well that's a double-edged sword, when the hype's not there, they have a lot of sizzle at stake. >> When I say deficiencies, I mean in terms of strategic discussions of where they're going. I would have liked to have heard more of Peter's discussion. >> I would too, let's get to that in a second. But I want to get your reaction on the whole enterprise catalog piece. Pretty much promoted by Jerry Held, founder of INGRES, legend in the industry, Bruce Chizen, really pumping that up. Their quote was, "This is probably "the most important product." Now, is that a board perspective bias, or is that really something that you guys believe? >> That's really organic. Metadata management is their core competency, and really their core asset inside of all their applications at Informatica, and that's what the big data catalog is all about. It's not just a data catalog, it's a metadata catalog for data discovery and so forth. Everything that is done inside of the Informatica portfolio requires a central metadata repository, and I think we at Wikibon, in our recent report on the big data market, focused on the big data catalog as being one of the key pieces of infrastructure going forward in multi-cloud. You know, there's not just Informatica, there's Alation, and there's Codero, Hortonworks and IBM and others that are going deep on their big data catalogs. >> So you see that's a flagship product for these companies. >> Well let's put it this way, AI has been around since the late 1940s. The algorithms for doing AI have been around, '40s, '50s. The algorithms have been around for years. But the point is, what's occurred recently is the introduction of technology that can actually run these algorithms, that can actually sustain the algorithms against very large volumes of data. So the technology's gotten to the point where you can actually do some of this stuff. The catalog concept has been around for as long as database managers have been around. The problem was you could only build a catalog for just that database manager. The promise of building enterprise-wide catalogs, that dream has been in place for years. One of the worst two days of my life was flying back from Japan, into New York, and sitting in an IBM information model meeting for analysts. It was absolutely-- >> Was that the 40s or 50s? (laughter) >> That was in the 80s. It was absolute hell. But the point is that Informatica is now-- >> You were the prodigy. >> Yeah, I was a prodigy. Informatica is now bringing together a combination of technologies, including CLAIRE, to make it possible to actually do catalog in a very active way. And that's trend setting. >> I think they're right too. I think that's clearly, they make a good product because I've got to say, you know, watching them for five years. This is our fourth year coming to Informatica World. Our first meeting with Anil, when he was chief product officer, was 2014 and so we've seen the progression. They're right on track, and I think they have an opportunity with IoT and blockchain, but the question I want to ask you guys is, this event of about 4,000 people, not a huge big data show, but it's really all about data. There's no distractions. The fact that they can't even get a lot of IoT airtime means that there's been a lot of core discussions. >> They're really focused. >> This is not like a Strata-- >> No. >> Where everyone's marketing some tool or platform. >> These guys are down and dirty with the products. >> They are really focused on their core opportunities, and like Peter was saying, they're really focused, they're the premier, I see the data pipeline solution or platform vendor. The data pipeline is the center of the AI revolution. And so in many ways, all of the forces, all of the trends have converged to the advantage of Informatica as being the core, go-to vendor for a complete data pipeline for all your requirements, including machine learning development. >> There's one more thing. We didn't hear blockchain, we didn't hear IoT, although I bet you there's a lot of conversation, one-on-ones between customers and Informatica about some of those things. But there's one other thing we didn't hear, which I think is very telling, and speaks to some of our trends. We didn't hear open source. Open source was not once mentioned on theCUBE, except maybe you mentioned it once. >> John: You're right. >> Now, if we think about where the big data market was forged, and where it was going to always remain, was it was going to be this big, huge, open-source play. And that has not happened. Informatica, by saying, "We're going to have "a great individual product, "and a great portfolio that works together," is demonstrating that the way to show how the new compute model is going to work is to take a coherent, integrated, focused approach on how to do it. >> It's interesting, I mean we could dissect this. Open source is a great observation, because is there really open source needed if you have a pipeline thing? I'd much rather have a discussion about open data, which I think as your deal points to, is getting into hybrid cloud as fast as possible in a console. To me, that's so much more powerful than open source. >> Jim: Open APIs. >> Open APIs where I can not get locked into Azure. >> I think open source is still important, but I'll bet you that the open source, if you start looking at what these guys are doing and others like them are doing, my guess is that we'll see open source vendors saying, "Oh, so that's how you're going to do catalog. "Okay great, so let's take an open source approach "to doing that." And you know, Informatica's going to have to stay in front of that. >> They might be using some open source. It might not be a top-line message. But let's go the next level, let's go critical analysis on Informatica. What does Informatica need to do, obviously they've got a tail wind, they've got great timing with GDPR, you couldn't ask for a better time to showcase engineering data, governance and application integration across clouds than now. So they're in a good spot. Where are they strong? What do they need to work on? >> Well okay, let's just focus on GDPR, because it is three days from now for that compliance date. GDPR, I mean, Informatica's had some good announcements at this show and prior to this show, in terms of tools for discovery of all your PII and so forth, so you can catalog it in the big data catalog. What needs to be built up by them and other vendors as well, is a more fully fleshed-out, GDPR compliance platform, or portfolio, or ecosystem. There's a lot of things that are needed, like a standardized consent portal so your customers can go in, look up their PII in your big data catalog and indicate their consent or their withdrawal of consent for you to use particular pieces of data. Hortonworks a few weeks ago at their data works in Berlin, they made an announcement related to such a portal. What I'm getting at is that more vendors, including this, every big data catalog vendor needs to have in their portfolio, and will, and I predict within the next two years, a consent portal as one of several important components to enable not just GDPR compliance, but really compliance with any such privacy-- >> A subject portal that offers consent but then is verified. >> Jim: For example, but it needs to be open source. >> Here's what I'll say, John. And we had a conversation about it with Amil, the present chief product officer. I think that if Informatica, similar to what we think, is on the right path, the world is moving to an acknowledgment that data has to be treated as an asset. That tooling is required so that you can do so. And that you have to re-institutionalize work, re-organize work, and re-think, culturally, what it means to use data as an asset. >> With penalties down the road, obviously on the horizon. >> Well there are penalties, and you know, proximate like GDPRs, but also you're out of business if you don't do these kinds of penalties. But one of the things that's going to determine what's going to gate their growth is how many people will actually end up utilizing these technologies? And so if I were to have one thing that I think they absolutely have to do, we're coming out of a world that's focused on we use process, and process models and process-oriented tools to build applications. We're moving into a world where we use data, data methods, data models to build applications. This notion of a data-first world as opposed to a process-first world, Informatica has to take a lead on what it means to be data-first, tooling for data-first, building applications that are data-first, and very importantly, that's how you're going to grow your user base. >> Sajit was talking about data value, data value chains or whatever it's called. >> Supply chains. >> Data supply chains. I think there's going to be a series of data supply chains that are going to be well-formed, well-defined, and ones that are going to be dynamic. Seeing it happening now. >> And actually that's an interesting discussion, data value chains, data supply chains, but really, data monetization chains. The whole GDPR phenomenon is that your customer's PI is their property, and that you need their consent to use it, and to the extent that they give you consent. On some level, the customer's expecting a return of value to them. You know, maybe monetization. Maybe they make money, but more enterprises have to start thinking of data as a product. And then they need to license the IP from whoever owns it. >> Peter: This is a huge issue. >> And vendors like Informatica need to understand that phenomenon and bake it, as it were, into their solution portfolio. >> Either they're going to be on the right side of history on that, or the wrong side, because you're right and you just highlighted Peter's point, which is that data direction, not the process, to your point. >> Data first. >> If I own the data, it's got to be very dynamic. Okay, my final comment would be, and I mentioned this last night when we were talking, is that I think that things are clicking for them. I think they've got tail winds, I think they're smart enough on the product side. The trend is their friend. They've got the clould deals in place. They're in a nice layer in the stack where they can be that Switzerland. You've got storage vendors underneath, there's a nice data layer, so in the position, with coming over the top cloud-native Kubernetes and containers-- >> This is going to get messy fast. >> John: I didn't hear Kubernetes at all this show. >> Hold on, let me finish. This is going to be a robust Switzerland model where I don't think they can handle the onboarding of partners. I think they have a lot of partners now from their standpoint, but I think they might have an AWS factor where they're going to have to start thinking really hard about how to be efficient about onboarding partners. To your point about adoption, this is going to be a huge issue that could make or break them. They could scale the partnership model through the APIs, they could have a robust ecosystem. That could show us 15,000-- >> If they could be a magnet brand inside Azure, or a magnet brand inside AWS for how you think about building new classes of value, applications and others, with a data-first approach, then a lot of interesting things could happen. >> Yeah, they could be a magnet brand to avoid getting disintermediated by their public cloud partners because Microsoft's got a portfolio they could place with theirs. AWS has built one. >> Everybody wants this. >> Yeah, everybody wants them. >> Guys, great job. Peter, great to host with you. Jim, great to have you on, making an appearance in between your meetings, one-on-ones and the analyst stuff. >> I'm a busy man. >> That's theCUBE here, wrapping up day two of coverage here at Informatica World 2018. The trend is their friend. Data's at the center of the value proposition, and more strategic ever, data engineering, governance, application. This is all happening right now. Regulations on the horizon. A cultural shift happening. And we're out here in the open doing it, sharing the data with you. Thanks for watching Informatica World 2018. (energetic 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)

>> 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)

>> Narrator: Live, from San Francisco, it's the Cube, covering Informatica World 2017. Brought to you by Informatica. (techno music) >> Hey, welcome back, everyone. Live here in San Francisco, this is the Cube's exclusive coverage of Informatica World 2017, our third year covering Informatica, and more to come. I'm John Furrier with Silicon Angle, the Cube. My co-host, Peter Burris, Head of Research for Silicon Angle Media, as well as General Manager of Wikibon.com, check out the great research at Wikibon. Some great stuff there on IOT, cloud ping data, great stuff. Of course, go to SiliconAngle.com for all the coverage YouTube.com/SiliconAngle for all the Cube videos. Our next guest is Bruce Chizen, board member of a lot of private companies, also Special Advisor at Informatica. You're on the board of Informatica, no? >> Executive Chair. >> John: Executive Chair of Informatica. Not only as Special Advisor, Executive Chair. Welcome back, good to see you. >> Great to be here. >> You were on last year, great to have you back. What a popular video. Jerry Held was on yesterday. Let's get some Board insights, so first question, when are you going public? (laughing) >> Good one. >> John: Warmed you up, and then, no. I mean the performance is doing well. Give us a quick update. >> Company's doing well. Q4 was a good quarter, Q1 was a good quarter. I think we will be positioned to do something late 2018, early 2019. A lot depends on how the company continues to do. A lot depends on the market. The private equity investors are in no hurry. >> John: Yeah. >> But it's always nice to have that option. >> So it's one of the things we, yeah, great option. Doing well. We heard that also from some of the management. We got O'Neil coming on, we'll press him on some of the performance side, but always had good products out, we talked about it last year. But the industry's going through a massive transformation. You've seen many waves over the years. The waves are hitting. What's your perspective right now? I mean, it's a pretty big wave. You got to get the surfboard out there, there's a set coming in. What's the big wave right now? >> So, data is driving every transformation within every organization. Any company that is not using and taking advantage of data will be left behind. You look at how companies like Amazon and Google and now a lot of our customers like Schwab and Tesla and others, the way they're using data, that will allow them to continue to either be successful in the case of a Schwab, or be a disruptor, like somebody like Tesla. Fortunately for us at Informatica, we are helping to drive that digital transformation. >> One of the things that I always observe, younger than you are, I've only seen a few waves in my day, but in the waves that were the most impactful in terms of creating wealth, and opportunity, and innovation, has had a cool and relevant factor. Meaning, if you go back to the PC days, it was cool and relevant. If you go back to mini computer, cool and relevant. And it goes on and on and on. And certainly internet, cool and relevant. But now, the, you mention Tesla. I'm testing driving one on Friday. My kids are like "Don't buy the Audi, buy the Tesla." This is my kids. So it's a cooler, it's a spaceship, it's cooler than the other cars. >> Bruce: Or an iPhone on wheels. >> Peter: (laughs) Exactly. A computer on wheels. >> So cool and relevant, talk about what is the cool and relevant thing right now. You talk about user experience, that's one. Data's changing it. So how is data being the cool and relevant trend? Point to some things that... >> If you look at what's happening from the chip on up, everything, everything will be intelligent. And I hate to use the term "internet of things," but the reality is everything will have intelligence. And that intelligent information will be able to be taken advantage of because of the scale of the cloud. Which means that any company will be able to take information, data, analyze it on the cloud, and then use it to do something with. And it's happening now. Fortunately, Informatica sits right in the middle of that, because they're the ones who could rationalize that data on behalf of their customers. 'Cause there's going to be a lot of it and somebody needs to govern it, secure it, homogenize it. >> John: You consider them an enabling platform? >> Absolutely, absolutely. I was joking, we just went through a rebranding exercise. And it's kind of cute, new logo, and it's kind of bold and sleek and it shows we'll have a leader, but it's a logo. But there's really around the messaging, we are finally getting across that we are the ones unleashing the power of data. That's what Informatica does. We'd just never really told anybody about it. We're very product focused, not really helping customers understand how uniquely positioned the company was. >> And it's also, you guys have done some things. Let's just go back and look at going private. Brought a new management team, have product chops again, we've talked about that in previous years. Last year in particular. So, okay, you have the wind at your back. Now you got Sally as a CMO, now you got to start being a humble braggart about the cool stuff you're doing. So which is marketing, basically. >> That's correct. >> John: But now, it's digital. >> Yeah. >> So, what's the Board conversation like, you say "Go, go build the brand!" >> So first of all, being private is great. (laughing) Because we get to do things you couldn't do as a public company. We're, a lot of our customers what to buy the products and solutions via subscription, that has huge impact to the P&L, especially in the short term. Cash flow's fine. So the PE guys are going okay, it's great, because we'll come out of this as a better company, and our customers like it because that's the way they want to buy products. So, that helps a lot. The conversation at the Board level has been, "Wow, we're number one in every category in which "we participate in. "Everything from big data to cloud integration "to traditional on-premise, to real-time streaming, "and, and, and data security." >> You're only one of three vendors in the Google general availabilities banner which went out yesterday. We covered that on Silicon Angle. >> We're number one there, we had AWS speak at our conference, we had Azure speak at our conference. All of the cloud guys love Informatica because we are the ones who are uniquely positioned to deal with all this data on behalf of their customers. As a private company, we're able to take advantage of that, spend some extra money on marketing. You know a lot of our customers know about us, but a lot more should know about us. So, part of coming out, having a new logo, having a new digital campaign, changing the website, that costs money. But as a private company, we get to do that. Because the fruits of those efforts will end up occurring a couple of years down the road, which is fine. >> So let me see if I can weave those two thoughts together in what I thought was an interesting way. Given that increasingly a lot of data's going to be in the cloud, and that's where the longer analysis is going to be required, that means a lot of the tools are going to have to be in the cloud. Amazon Marketplace is going to be a place where a lot of tools are going to be chosen. People are going to go into the Amazon Marketplace and see a lot of different options, including some that are free. They may not work as well, but they're free. You guys, what happens with marketing, and what's happening with that kind of a trend, is you need to buy, as customers, to choose tools that are actually going to work to serve or to solve the problem, to do the work that you need them to perform. And so what Sally Jenkins, the CMO, has done, with this new branding, is introduce the process of how do you buy us more customers to choose the right tool to do the right job? Does that make sense to you? >> It makes absolute sense, free is good. But be careful what you ask for. Sometimes you get what you pay for. You're talking about enterprise data. You want it to be governed, you want it to be secure. You want it to be accurate. >> John: Now there's laws coming out where you have to do it. >> You look at GTB... >> Peter: GDBPR. >> GDBPR in Europe, the privacy issues. You look at what's happening with Facebook, or what was reported today with France and how they're not happy with Facebook's privacy behaviors. It's an issue. It's an issue for anybody who does business anywhere, especially if you're a global company and you do business in Europe. You have to worry about corporate governance. Data security, data governance, data security. That's Informatica. The other thing is, while there will be some customers who will say "I'm going to AWS," there will be more customers who will either say "I have some legacy "systems that I'm going to leave on-premise, "and new projects will be in the cloud." Or they're going to say "I'm moving everything to "the cloud, but I don't want to be held hostage "by one cloud provider." And they're going to go with Amazon and Azure and Google and maybe Oracle, and, and, and. And again, because Informatica is Swiss, we're able to provide them with a solution that allows them to accomplish their data needs. >> Well, congratulations on the performance, I want to get that out of the way. But I want to ask a specific question on the historical, holistic picture of Informatica. Going back, what were the key bets that you guys made? 'Cause you guys sit around, and you got the private equity now coming to the table, they have expectations, but at the end of the day you've got to build a business. What were the key bets that is yielding the fruit that we're seeing? >> The number one bet was that the company had great products and a great R&D organization. We believed that, and fortunately, we got it right. Because if you don't have great products and passionate R&D organizations around the world, you can't make up for that. It doesn't make a difference how much you spend on marketing. At least not in the business that we're in. So that was number one bet, and that proved to play out well. The second thing was, this was a company that had done so well for so long that they never needed to change their business processes to behave like a billion, two billion, three billion, four billion dollar company. Many of their business processes were like that of a 200 million dollar company. And that's easier to fix. So things around back end, IT, legal, finance, go-to-market, marketing, sales. >> John: Less of a risk from an investment standpoint. >> That's correct. So that's what we believed, we were right And where we've been spending most of our energy and effort is helping the company, through the new management team, improve their business processes and their go-to-market. >> So we had a critical analysis yesterday during our wrap up session, and one of the comments I made, I want to get your reaction to this, was although impressive, your number one and all these Gartner Magic Quadrant categories, but that's an old scoreboard. If we're really living in digital transformation, those shouldn't really be a tell sign for what the performance of the new KBIs or the new metrics are. And so we were pontificating and analyzing what that would be, still unknown, we're going to see it. But Peter had a good point, he said "At the end "of the day, customer wins." >> Yeah, that was my reaction. It's like at the end of the day, all that matters do the customers.... >> What's the scoreboard look for customer wins? I know you were at the executive summit they had yesterday at the Intercontinental right around the corner. I had a chance to meet some of them at that dinner, some conversation. But I want to get your perspective. What is the vibe of the customers, what are those customer wins, and how does that translate into future growth for Informatica? >> Any customer who is looking at data, data management, strategically, is going with Informatica. >> Mmm hmm. >> There are a number of competitors that we have who try to compete with Informatica at the product level, and they end up doing okay through pricing, through better sales tactics, but when we have the opportunity to speak to the Chief Data Officer, the CIO, the CEO, they go with Informatica. It's the reason why Tesla went with Informatica on their project where they're trying to tie together the auto business with the solar business. Because if they get to know both sets of customers and are able to sync that up, one plus one will be greater than two for them, and that's why they did that deal. Or it's why Amazon has chosen our MDM solution for their sales operations. So you look at leading companies who are able to look at the enterprise level, at the strategic level, they are going with Informatica. That's why we know we're winning. >> So Bruce, give us three sentences, what is strategic data management? >> Strategic data management is being able to take reams and reams of data from all different platforms, traditional legacy, big data, real-time solutions, and data from the cloud and be able to look at it intelligently. Use artificial intelligence and machine learning to be able to analyze that data in a more intelligent way, and then act on it. >> So two questions on that point, I was going to ask about the AI washing going on in the industry. Every event now is like, "Oh my god, AI, we've got AI," but that's not really AI. What is AI, we call it augmented intelligence because you're really augmenting with the data, but even Google IO's got a little neural net throwback to the 80s, but what's your thoughts on how customers should look through the lens of b.s. to say, "Wow, that's the real AI, or the real "augmented intelligence." >> Does it do anything? That's ultimately the question that a Chief Data Officer or CIO or CEO...is something changing because of the artificial intelligence being applied? In the case of Informatica, we announced an AI platform called Clair, "clairvoyant," so artificial intelligence. What is Clair? It allows you to develop solutions like our enterprise information catalog, where an organization has thousands and thousands of databases, it's able to look at the metadata within those databases and then over time keep disclosing more and more data appropriate to the information that you're looking for. So then, if I'm an analyst or a businessperson, a marketing person, a sales person, I can take action on the right set of data. That's true artificial intelligence. >> Bruce, I want to get to one final point as we are winding down here. Again, you've seen many waves. But I want to talk about the companies that are trying to get through the transition of this transformation, Informatica certainly cleared the runway, they've got some things to work on, certainly brand-building. I see that as their air cover in many rising tide will float a lot of boats in the ecosystem. But there are companies where they have been in the infrastructure business and the cloud is one big infrastructure, selling boxes and whatnot. Other companies have traditional software models, download, whatever you want to call it, on-prem licenses, not subscriptions. They're working hard. Your advice to them if you are on their Board, or as a friend, what do you say to them, what do they got to do to get through this? And how should customers look at who's winning and who's losing, in terms of progress? >> The world of enterprise computing is moving to the cloud. Legacy systems will remain for a while. They need to figure out how to take their legacy solutions and make them relevant to the world of cloud computing. And if they can't do that, they should sell their company or get out of business. (laughing) >> And certainly data is the oil, it's the gold, it's the lifeblood of an organization. >> Of any organization. Even at Informatica, internally, we're using our own intelligent data platform to do our own marketing. Sally Jenkins is working closely with our CIO Graeme Thompson on working on solutions where we could help better understand what our customers want and need, so we can provide them with the right solution, leveraging our intelligent data leg. >> Bruce, thanks for coming on the Cube. Really appreciate your insight. Again, you've seen a lot of waves, you've been in the industry a long time, you have great Board presence, as well as other companies. Thanks for sharing the insight, and the data here on the Cube. A lot of insights and analytics being extracted here and sharing it with you. Certainly we're not legacy, we don't need to sell our business, we're doing great. If you haven't, make the transition. Good advice, thanks so much. >> Bruce: Great to be here. >> Bruce Chizen inside the Cube here. I'm John Furrier with Peter Burris. Stay with us for more coverage after this short break. (techno music)

>> Narrator: Live from San Francisco, it's The Cube. Covering Informatica World 2017. Brought to you by Informatica. >> Okay, welcome back, everyone. We're live in San Francisco, this the Cube's exclusive coverage of Informatica World 2017. It's the Cube, our flagship program. We go out to the events and extract the signal from the noise. I'm John Furrier with SiliconANGLE on the Cube. My co-host Peter Burris, Head of Research for SiliconANGLE Media, as well as General Manager at Wikibon.com research. Our next guest is Sally Jenkins, who's the Executive Vice President and Chief Marketing Officer. New to Informatica, not new to the industry, but certainly put her mark on the show, with the new branding. Sally, welcome to the Cube. Great to have you. >> Thank you. >> John: I know you must be exhausted, all the work you've done. >> Thank you. We're running on adrenaline, I can tell you that. But it's all good. We feel really good about it. >> John: So this is our third year following Informatica. We know a lot of the folks from other companies, see some Symantec product guys now running the show at Informatica. Always had great product shops, but with this industry transformation with the cloud, just in the past three or four years, there's been a massive shift and wave. And the pecking order of winners is changing pretty quickly. Informatica went private, kind of like what Dell did, Dell Computer, now Dell Technologies, and re-tooled. Now, you're going to be doing the brand reboot, which we can see behind us. >> Sally: Right. >> You've done that in three months. Take us through that, because this is an interesting story. You're now going to bring the brand perspective to Informatica. What's the strategy? What's your plan? How did you get all this done in three months? >> Yes, no, it's been an incredible journey, but you know, I was just made this enormous offer as a marketer. You couldn't dream for a better challenge than what we had at Informatica. So when I came in, what I recognized is, looking all around and trying to understand our strengths and our weaknesses, and what were the opportunities. We have everything in place. So, as I mentioned in my keynote yesterday, our brand is having to catch up with the business. So the business is there, we've got great products. The leadership that we hold, with all of the Gartner Magic Quadrants, you know, leadership in the six categories that we say that matter, we have a tremendous backing to come out with a new story, and that's exactly what we needed to do. It wasn't just about the logo. In fact, the logo was the last thing that we looked at. It was about, what's our strategy? What's our vision, our mission? What's the story we want to tell with our customers? And we were hearing from our customers, as well, that they wanted us to change, because they're going through transformations. So that was kind of the backdrop for how we got started on this, and so we went right off the bat, trying to nail down our messaging, and reviewing that with customers and partners. I mean, our new partner community is a big part of this, so we did our due diligence that led up to this unveiling. >> We're always kind of complimentary of you guys. Some critical. We had some critical analysis yesterday in the wrap-up session. Minor relative to the big bets. These guys have product shops. They always have had good product shops, and with going private, they've done a lot of re-tooling, a lot of change in the past year. And they talk about that. I'm going to see... We had Amit on, we're going to have Neil on earlier, but I've got to ask you the question, as the new exec. What does the brand stand for? Because the products change, the customers, they have some legacy customers that are growing with them and transforming. What does the brand stand for, from your perspective. And what is that story? >> Well, the brand stands for unleashing the power of data. And I think, as you've probably heard throughout this conference, that our whole stance on this is understanding what the destructive power of data holds for you as a customer. Because, as our customers are transforming, we are also recognizing that we have to transform, too. And our customers are moving from on-prem to cloud. They want to use our products on subscription versus perpetual license. So we're going through this massive change right alongside our customers, and so our brand had to support that. And our brand was, quite frankly, left behind. And so that was the opportunity for us to think differently about, what is that story that's in support of what our customers want? >> The promises you want to make to customers. >> That's right. >> So next for you, you're going to take a vacation. >> (laughs) I get Friday off. (laughter) >> Work from home, basically. >> Then you're going to start applying yourself to the challenges of using data within marketing, to improve Informatica's performance to customers. >> Sally: Absolutely. >> Talk about the transformation that you think your function's going to go through, as you use Informatica to be a better Informatica. >> Yeah, that's a great question. In fact, I talked about this also in our keynote yesterday, because I was talking about a little bit outside-in, and then I flipped and said let's talk inside-out, and I was explaining how my job is to deliver the best customer experience to our customers and our partners. And in order to do that, I need to have those unique insights that I gather from all the data that I'm collecting on our customers and our partners, to make sure that they're getting the right information at the right time to make those right decisions. And so I'm using our own internal intelligent data lake to create what we call our marketing data lake, and that gives me-- First of all, it gives me the whole perspective of the customer and what they're doing and where they're coming from, so that then I can turn that around and make that a unique experience for our customers. So I shared that, because I wanted our customers to understand that I'm going through the same thing that they're going through. In fact, if you've seen some of the quotes that are hanging around here at Informatica World. Jewelry, TV, AWS, they're all talking about delivering the best customer experience for their customers. So, I feel like I'm going through this just as well as our customers are. >> So what's the marketing perspective? Because now you have to sell to the customers. You're listening, so digital's going to be a big part of it. We're in a digital transformation, so we're here at a physical event, we're broadcasting digitally live, and all these assets are flying around. There's a lot of data out there. (laughs) How are you harnessing that data? What's your vision on how you're going to bring Informatica to that digital role, for listening to the customers, engaging with them-- >> Sally: That's right, that's right. >> And creating a touchpoint, digitally. >> Well, and that's-- Digital is a big part of what I'm responsible for, and we oftentimes talk about what's the digital journey our customers go on? And that gets back to, I'm needing to understand where they're coming from, what device are they coming to me from? What kind of information do they want back from me to help them make the right decisions for their company? And quite frankly, bring ideas back to their C-Suite. So, that's all right in my wheelhouse, and that's actually what I'll be turning my attention to post-Informatica World, is really getting deep under, having a better understanding of what that buyer's journey looks like. And it's all digital. I mean, these days, everything we do in marketing starts with digital. >> John: And in some cases, the moment of truth to the beginning of a journey is all digital. >> Yeah. >> John: Analog is kind of-- Is self-service, if you will. >> Peter: Well, except for those customers, except for those customers that you currently have, who you're trying to expand and develop. >> Of course, yeah. >> And help them as well, obviously. But this is... One of the things I find especially interesting about marketing, and I want to test you on this, is that in many respects marketing has been under-appreciated, because the output of marketing has been very information oriented, and the value of the information that the marketing has generated. While we're now starting to recognize how unbelievably valuable it is, historically it's been under-appreciated. >> Sally: That's right, that's right. >> So how are you bringing the story, marrying the ability to tool things, but also to better define... What's the value of a brand? >> That's right. >> Peter: We have no idea. It's goodwill on a balance sheet. >> Yeah, yeah. Well, that's a great question. This is a testament to the belief that our board and our executive team has around the power of a brand. This is why they're investing. They realize that they've invested, and done, and delivered in every facet across Informatica, and the last place that they needed to invest in is in marketing, because they realize the power of the brand in that story. And look, everybody's talking about us. I mean, if you've talked to any of our customers here at Informatica World, they're like, this is unexpected. We haven't seen this from Informatica. They've been hungry for this from Informatica. And so we're really putting our money where our mouth is on the brand this year. So you'll see it all come together. And I have to say, as a marketer, I mean there's nothing more special than the company realizing that they need to get behind the brand. >> John: You've got a great mandate, and you've got a good product behind you. I think that's going to be impressive. The question I want to ask you is twofold. One is, with the rebranding experience, you mentioned you went through digital transformation, a lot of your customers are going through he same thing. What experiences did you learn from that? If you could share some insight, whether it's personal or business, anecdotally, or specifically, quantitatively, what you learned from the rebranding experience. And then, the second part of the question is the brand-building process, how do you envision that road map? >> So, it's interesting. So, I actually brought a best practice in order to get this done in three months, honestly. This is normally like a nine month process. I use this rubric where we start with understanding what's our overall vision and mission, and what's the market opportunity? So, enterprise cloud data management. We're the leaders in that. We've never said that. And so understanding each of the bits and pieces that make up the entire story, before you get to the brand identity, that's actually a best practice that we've employed now, here at Informatica. And that was something that was foreign, just because they hadn't taken the time to focus on that. So that was, not necessarily learning a best practice, but deploying a best practice here at Informatica. And now, we need to turn back inside and change the culture. So we just rolled this out with the Informatica employee base last week, and they're all excited. And I said okay, we'll tune in once we get past Informatica World. So now the employees are excited to understand, how can they help tell the message, get the story out there? How can we change the culture so they understand who we are? You know, we've had many messages in the marketplace, so there's a little bit of confusion. And now we have one story. And now we need... Our employees are our best salespeople, so we need to engage them, and arm them with a story. >> I can just see people watching this video. Give me the rubric, where do I find that rubric? >> Oh, it's posted. It's on our intranet, absolutely. >> John: Interesting, so it's on a public blog? >> It's on our intranet inside, yeah. >> John: Oh, intranet, so it's not for the general public. >> Yes, yeah. >> John: I'm sure they're dying to find out the secret rubric. >> It's a guide to help them under-- Because everyone says, oh what's your new logo? And I'm like, we have a lot to do before we talk about colors and all of that, and so we wanted to make sure our employees understood the messaging, and what was behind that, so that when we got to the logo, they could understand how everything was unfolding. >> John: So what's going to iterate? So, you know, we see this digital transformation, whether it's deploying cloud. You get some structure, a rubric as a guidepost to kind of get the hard work done, foundationally. But then iterating and being agile with the brand. Do you have a philosophy on what points of the brand you're going to be iterating on, and what are the key areas that you see some evolution on the brand side? >> Yeah, well it's definitely that reiteration of our leadership stance that we have on the marketplace. You know, we've been humble, and there's nothing wrong with humble, but we also can be proud, and we can be proud to be proud. >> John: Yeah. >> So you'll be seeing a lot more from us around our leadership that we have in the marketplace, and we're going to be taking that on the road. So what you see here this week at Informatica World, then we roll them out all around the rest of the world through our Informatica World Tours. So we'll package up the story, we'll package up the look and feel, and we'll take that out so that our customers around the world can experience what we're experiencing this week. >> Take us through... I always love to ask this question for new folks, and I did this with Jeremy Burton when he joined EMC, now he's CMO of the Dell Technologies. >> Mm-hmm. >> Because you're new. You see everything fresh, with the fresh eyes. And of course, you've got to come in a little skeptical. Wait a minute, is this going to be a good opportunity? So when you were assessing the jewels, if you will, inside Informatica, what are some of the things that jumped out at you, that you could share? What's the coolest thing you saw? What motivated you? What was the tipping point? Was there a moment when you go, okay, go the next level? >> Yeah. >> John: Was it just a sustained, hmm. Or was there one-- >> No, there were a couple of things. I mean, first and foremost, our leadership. I mean, you guys... There's no other company, I'm sure you can validate this. There's no other company who has leadership in six-- Not just in leader quadrant, but the leader, in the leadership quadrant, in six categories. That's unheard of, and it's something that we need to be proud of. We don't ever talk about that. So that was the first thing. I said okay, we'll check that box. That's really good. Second thing is this interest in investment in the brand. And I thought okay, I've heard that before, but let's see if we're serious about it. >> John: Test that. You had to test that. >> And I've tested it, I've proven it, we've delivered it, and everybody's proud. And so I think those two things combined, our leadership and the fact that we actually can get behind the story, and we have one story, that's the momentum we've needed. So, that's just validation itself. >> Jerry Held, who's a board member, was on yesterday, is very proud of the work you've done, and he's excited. So he's pumped up. You've got one board member on your side. >> Sally: Great, yeah. >> We'll get to see what Bruce thinks this afternoon. >> Board members, we've got our channel partners. I mean look, our channel, for us, is our mouthpiece. And we needed to provide them the story, too. So the channel's engaged, and more excited than ever. Our sales teams are engaged. I mean, they've needed this story. So, you know, it was just guide rails that we needed to bring to the company, and I think this just solidifies that. >> John: You have the wind at your back. Certainly we heard from the channel, sales are up. Certainly the product's doing good. Looking at over a billion dollars in revenue. Great pre-IPO. I mean it's pretty obvious-- >> Sally: Hottest pre-IPO out there. >> Okay, we're going to evaluate that, but we think it's pretty hot right now. Is it the hottest? Mm, I think so. But what are you worried about? Because with all that pressure, being aggressive on the marketing side, you've got to be... You have the wind at your back. What are you worried about, if anything? >> It all comes down to execution, right? So, we've done the heavy lifting to get us here, but as I've said to executive staff and the board, this is our starting line, it's not our finish line. And so the rest of this year, and of course going into 2018, it's all about execution. And I feel really good about that, because you can't execute without a great strategy, and we have a great strategy. And we have a great story to tell. >> And a great management team. I mentioned it earlier, and John and I talked about it last night on the wrap-up, Informatica has a track record of making promises, big promises, and at least recently, keeping them. >> Sally: That's right. >> So you have a track record of executing. Customers are able to bank in you. So going back to kind of why this might be a great opportunity is, from our perspective, you've got good products, you've got good management, you've got a good customer base, you've got a good financial position. Marketing can make a big difference. >> That's right. Now we have a good story, and we have a great brand, and we've got investment, so we'll be out there. I mean, this is our year. I hope you all see that this is our year. >> We'll be watching. You've got a lot of air cover coming in for the folks to try more business and customer satisfaction. >> Yeah. >> What are we going to be talking about next year? (laughs) >> Wait and see. Wait and see. There's more in store. >> Tell us about your first 100 days. (laughter) >> No, no, no, no, no. >> Oh, I rebranded the company. (laughs) We'll just leave it at that. >> Sally Jenkins, Executive Vice President, Chief Marketing Officer, changing the brand, building the brand for Informatica. Wind at her back. Congratulations, great to have you on the Cube. >> John: Thanks for supporting the Cube, being on the Cube. >> Thank you. Exclusive coverage here from Informatica World, I'm John Furrier with Peter Burris. Stay with us more after this short break. (electronic music)

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

>>live from San Francisco. It's the Cube covering Informatica World 2016. Brought to you by Informatica. Now here are your hosts John Furrier and Peter Burress. Okay. Welcome back, everyone. We are here live in San Francisco for Informatica World 2016. Exclusive coverage from Silicon Angle Media is the Cube. This is our flagship programme. We go out to the events and extract the signal to noise. I'm John from my co host, Peter Burst. We have tree conflict comedy Global Head of Data Management and Steve Jones, global vice president. Big data from Capt. Jeff and I insights and data. You. Good to see you again. You sure you're welcome back. Welcome to the Cube. Thank you. And you've got my name right? It was a tongue twister, but, uh, we were talking about big data before we started rolling and kind of like where we've come to talk about over the really big data. You look back only a few years ago. Go back five years, Duke movement to where it is now. The modernisation is certainly loud and clear, but it's just not about Hadoop anymore. There's a lot of operational challenges and also the total cost of owners who want to get your thoughts. What's the trends? What do you guys see as the big trends now relative to this modernisation of taking open source the next big day to the next level? >>I think part of the pieces were actually about to publish a report we've done within the massacre on exactly that question, Uh, particular and governance and how people are making it operational. We did a report recently with our captain consulting division around Operation Analytics. Really fascinating thing that found out was the two real interesting in governance, right? The age old thing on governance has been the business doesn't engage. Well, guess what we found when you look at big data programmes is when the big data programmes start to deliver value. Guess who wants to take them over business? Guess who then actually starts leading the governance efforts, the business. So suddenly, this piece where the history of sort of data management has been, you know, going you really care about quality and the business, to be honest, going? Yeah, we don't care that much. We're still using excel, um, to the stage of which you're delivering real analytical value those pieces are going through. It's something we've been on a long journey for. I mean, we talked the other day. 2011 was the first time at camp we published a white paper on on our learnings around Big Data and governance. Um, it's amazing. Five years ago, we were talking about actually how you do governance and big data because of some of our more, uh, sort of forward looking clients. But that shift and what we're finding in that the report is the fact that people are really looking to replace this substrate. It's absolutely not about just about Hadoop, but that's the foundation, right? And unlike sort of historical pieces where there hasn't really been a data foundation, there's been lots of data silos but not a data foundation. Companies are looking to move towards actual firm data foundations across their entire business. That's a huge leap for it organisations to make and in terms of its impact on, you know, MDM and data quality and pace of delivery. Um, and those are the pieces. >>So also talk about the trends outside the US, for instance, because now you have in the UK uh, talk about that because your clients have a global footprint. The governance then crosses over the boundaries, blurring if you will virtual. But you still have physical, uh, locations. Well, I am sort of the UK and based out of London, And, uh so I see that side of the pond more often than, uh, this side. But the trends are pretty similar. And what Steve said, in fact, we were joking about it yesterday and we said, It's not for the tweet, but maybe, you know, was a little bit more big data doesn't need data quality. And my other favorite statement is MDM is dead. Long live India. Both of them are relevant. Big data doesn't need data quality in the sense that you cleanse all your data and put it into a TD WR uh, or a data lake because you can't only part of it is data owned by you. The rest comes from external sources where it needs quality is building the context on top when the end user of the analysts have a view, and there, if you build the context, then even good data could turn too bad, because in a particular context. That data is no more relevant. But bad data can turn to good because you're bringing in the context. And there was this eggs example we were talking about. You know, you you run a marketing campaign and you have all these likes and tweets and everybody loved it. Somebody then said, Okay, how about how good is this campaign? That's great. We need more. How good is it in the context of sales? Guess what? When the campaign ran, there was no difference to your sales. So then this good data that you had on the marketing campaign has turned back just to the company. That was a wasted effort that marketing. So you need contextual quality, not pure data quality. You know, if you look at e t l. You transform you do data quality before you, Lord. Now you're talking of E l t. And that's where you need quality. You need the linkages, the references, this data changes the data, and real time has been the conversation earlier so far today, the context defines the quality quality. A data swamp could be a data, you know, clean and environment. I mean, one >>of the reasons why we should presented that we present my presentation That I did on Monday was on avoiding a data swamp. So we actually think. But what we say is you've already got it. The myth is that you don't have data swamp right today, which is Oh, we've got my perfect data warehouse and it's got a perfect schemer. Really? And what does your business use Excel spreadsheets? Where do they get the data from? Well, they get from S a p. They download this and we got a macro. Somebody wrote in 1998 which means we can't upgrade that despot desktop from office 97. Right? So that desktop is office 97 because it's the only one that has a supply chain spreadsheet on. So the reality is you have the spread. Have it today. I think to the point you said about the country difference. One of the things we've seen, I think from a sort of a culture difference between Europe and here in the U. S. Is the U. S. Has been very much the technology pioneer, right is well, you know, the Hadoop stuff. The sparks of all that technology push European companies are seeing a lot of have taken quite a while to get into the, uh the Hadoop marketplace, but particularly the larger manufacturers, Um and sort of I'd say the more robust, like pharmaceuticals and these large scale organisations are now going all in. But after thinking about it. So what I mean is is that we've seen sort of lots of POC is used to be, like, four or five years ago. People doing PhDs here in North America. They're very technically centric. And then people like Okay, >>Exactly. Whereas >>over in now, in Europe, we're seeing more people going. Okay, We know where we want to get, too, because we've seen all the technology. Now it works. We're gonna start with thinking about the governance and thinking about that. What's the right way to go about this? So I think from a timing perspective, the thing that was interesting we felt beginning of last year that we begin to see some earlier states. Larger programmes in Europe, Maybe towards the end of the reality was by the middle of the year we were seeing very, very large pieces. There was almost a switch that happened, but we've our return, this notion of governance because it's really important. And you've said it here today about 20 times the rules of data Governments have been written piecemeal over the past few decades. Uh, started off by saying, uh is which application owns what data? And is the data quality enough so that the application runs or not? Uh, then compliance kind of kicked in, and we utilised compliance related rules to write the new rules of data governance. What is data governance in the context of big data? And the reason I ask questions specifically and maybe put some bounds on it is we're trying to get to a point where the business puts a value on data trade data as an asset that has a value. And the only way we're gonna be able to do that is through governance rules to support it. So what does data governance mean in a big data context, I >>think, Yeah. So the value is really the impact, and I go back to a very simple analogy people, When you didn't have computers, you had your ledges. You locked it up in a safe and took the key home. So you protected who had access to your data? You then put it on PCs. But then you give them access with Loggins. Then you said, Well, I'll tell you what you can do with my data. That was the era of B I. Because you had reports all they could do was print a report. Now you've given them access to do whatever they want with data. Now, how do you know? First thing on the governance aspect is what are they doing with the data? Where did they get the data for which they used to come up with that? What is the exposure to your organisation if somebody has, you know, uh, traded around, they traded around with labour rates or, uh, you know, fix them or done something you're talking about. And then you work backwards, Arlene. Age. So now I need to know first thing what? Not just who accesses my data. And I need to know. What are they doing that I need to know where they got the data with it. >>Well, I think this is >>You don't know what they're when they're going to access it and what they're going to do with at any given time. But I >>think that's the thing is where we have the This is where the sort of contention comes in. Right. To be honest between the areas back to the value is from a data management data governance that those things are all true, right? We need to know those pieces. The other reality is that today how do you show the business, Actually that they value the pieces, which is ultimately the outcome. So the piece we're finding on the research and the research we're about to publish soon with Informatica is one of things it's really finding. Is that where when do you get the business to care about governance? And the answer is when you demonstrate an outcome which relies on having good governance. So if you do a set of analytics and you prove that this is going to improve the effectiveness, the bottom line, the top line or whatever, the firm and particularly Operational analytics customer analytics, where they're real measurable numbers, we can save you 6% on your global supply chain costs. But in order to do that, you need a single view of product and parts, which means you need to do a product. MDM Well, that's a very easy way to get the business engaging government, as opposed to we need to do product MDM What? >>We're going to 3 60 view of the customer. >>So you So we're still pricing the value of data based on the outcome? Absolutely. And then presumably at some point, there is some across all those different utilisation and that will become the true value of the data. Is that I think the piece, I'd say in terms of that, if we sum it up, it's sort of it becomes a challenge because ultimately the business pays. Right? So one of the things I like about the big data stuff and the programmes are doing these large scale companies is the ability to deliver value to an area. So what we call insight at the point of action, and that's the bit where I pay. So, yes, I could sum it up in Theoretically and the C I can say, Well, I'm delivering this much value, but it's at those points of action. And if you say to something right, I deliver you $2 million. It costs you $100,000. That's much better than we have to say in totality. This delivers you, you know, $2 billion and it costs you $20 million or $200 million. That's an abstract piece, whereas except when I'm thinking about investment BAC, because I need to be able to appropriate the right set of resources, financial and otherwise, to the data based not just on individual exploitations but across an entire range of applications. Tyre range of utilisation, right? I think I think so. But again, in terms of the ability to bill and charges that if I can, my total is the summation of the individuals. So that's why I worked with the CFO once you have the CIA was in the room, said the business case for their for one of their programmes, and CFO said, Well, if I had, it took all your business cases and adding together this company twice the size and cost nothing to run. So there's been a history of theoretical use cases. So what we're seeing, I think on the data and the outcome side is the fact that particular Operation Analytics they're absolutely quantifiable outcomes. So while then you can say? Well, yes, If you then add this up. We need to make an investment on based platform. The two things we're finding are because you can use these much more agile technologies. These projects don't take 12 months to deliver first value, so you can. And because the incremental cost of working in a lake environment is so much less, you know, I don't have a 12 month schema change problem. So that's one of the things we're seeing is the ability to say yes as a strategy. We're going to spend 20 million or whatever over the next five years on this. But every three months, I'm going to prove to you that I've delivered value back because one thing I've seen on data governance, sort of strategic programmes historically is 18 months in. What have you delivered? What have you done for me? Proves that it has value right that >>you've forgotten. And I think also what we're seeing with big data initiatives is the failed fast methodology like the drug trials and farmers. So what's your project? It's actually the sum of all the all the programmes you've run. And we were talking about apportioning uh the budget, whose budget? Because it's now being done by the individual businesses in their own areas. So there's no CF or sitting there and saying, Well, this is the budget I give I t. And this is how you apportion it. It's all at the point of the business and they find we'll do all these fail fast programmes and I've then hit one, which makes me big bucks. And I love this concept because essentially talking about the horizontal disruption, which is what cloud and data does just fantastic. And I'm sure this is driving a lot of client engagements for you guys. So I got to ask a question on that thread Jerry Held talked about earlier today. I want to ask the question. He made a comment, but alternative questions. You guys, he said. Most CFOs know where their assets are. When you ask him to go down, the legend they go, Oh, yeah, they asked. What's about data? Where the data assets. The question is, when you go talk to your clients, uh, what do they look at when they say data assets? Because you're bringing up in the notion of not inventory of data I'm sitting around whether it's dirty, clean, you can argue and things will happen. But when it gets put to use for a purpose, Peter says, data with a purpose that's this would keep on narrative. What is there a chief data officer like a CFO role that actually knows what's going on? And probably no. But how do you have the clients? They're just share some colour because this is now a new concept of who's tracking the asset value. >>And I think there's two bits and I'll start without it. And then if you talk specifically post an L, which I think is a great example of what happens with data when it becomes an asset, is the ability to understand the totality of data within any nontrivial organisation is basically zero because it's not just inside your firewalls. I'd also question the idea that CFOs know where all the assets are. I'm working with a very large manufacturer, and after they've sold it, they need to service it, and they can't tell you where every asset is because that information now lives within a client. So actually knowing where all of the assets they need to service are, they might know their physical plants and factories are. But some of these assets a pretty big things they don't know necessarily where they are on planet Earth. So the piece on data is really to the stage of because it's also external data, right? So really the piece for me about government and other ones Do I understand the relationships of these pieces in terms of the do I value data as an individual pieces because of what I can do with it? Sometimes the data itself is the value, But most of the time we're finding in terms of when people describe value, it's to the outcome that it's based upon. And that's something that's much easier to define than how much is my, uh, product master worth. Well, I can't really say that, but you know what? I can absolutely say that 6% reduction in my supply chain costs because I have a product master. But I think post and l is a great example of what happens when you go the next step on data >>because you're looking at addressed it. And actually, it's not just posting now. We were talking to another uh, male company. A postal company. Where? Data asset. Okay, my address is our data assets, but I have multiple addresses for one person, and what they wanted to offer was based on the value of the packages that you get delivered. They wanted to give you a priority or a qualification of the addresses. They said this is a more trustworthy address because anything about £50 this person gets it delivered there. This is a lot of mail. So do you consider the insurance or the value of the packages that you get delivered to be a data asset? Most people wouldn't. They would say, Yeah, the addresses a asset. That's the data asset. But there's a second part to it, which you don't even know. So the answer really is yes and no. And it all is contextual because in a particular context, you can see if I know where everybody lives. I know where everybody is and I have all the address. You almost got to look back after the outcome and kind of reverse track the data and say, OK, that stream. I >>would say that people who start with we've had 30 years of trying to say it's the data object that has the value, and it's never ever happened. As soon as we're starting talking about the outcome and then backtracking and going in order to this outcome, we needed addresses which historically issues that would have been the value. But actually it was It was that plus the analytics of prioritising them for risk that suddenly that's a lot more valuable. That outcome of you know, what this person tends to be here, this area people seem to see as lower risk. This is where I can therefore look at the work office for those people. It gives you more information about the >>notion of the data swamp turning into data quality because the context, Sri says, is really key. Because now, if you can move data to context in real time data in motion where people call these days the buzzword. But that's the value. When you when you when you stumble upon that, that's where you say, Well, I thought I had bad data. No, Actually, it's hanging around waiting to be used as potential energy. As you know, it's the same thing with questionable. They're moving from being a postal supplier to delivering packages. Now, you know they have a very short window to deliver packages. So just how do you get to a building? Do you have to go through the backyard? Do you have to call somebody to get it? Now that data becomes valuable because otherwise you know all their deliveries go off the radar screen, right? Because they just shot to schedule >>was going to say about the quality. Want a great example of qualities that we spend a lot of times say process data and manufacturing will clean it up before it goes in the reporting structure, which is great, and that gives you a really great operational reports. There's now an entire business of people doing the digital discovery of processes so they can use the bad data to discover what your processes are and where your operational processes are currently breaking down process. If I cleaned up the data, they wouldn't be able to do their jobs. And it's this fascinating stuff we're finding a lot with. The data science piece is its ability to get different value out of data, >>chemical reactions, alchemy. It's all the interactions of the data. This is interesting. And I want to ask you guys, I know we have a minute left, and I want to have you guys take a minute to explain to the audience Cap Gemini and how people how you engage with the customer, uh, and context to their progress. Where are your customers? On the progress bar of these kinds of Congress? Because we have a nice conversation. I'd love to do an hour for this. Go up. We can geek out. But reality is day to run a business, right? So and in the tier one system integrators like captain and I all have kind of different differentiation. What do you guys do differently with this area of your practise? How are you engaging with your customers? And where are they on the progress bar of Are they like while you're talking gibberish to me, are they on board? Where are they? >>I think I think we've got a bit of a man. We've been on this journey a lot longer than most. Like I say, 2011. We're talking actual data governance and big data. You don't talk about that if you haven't been doing it for a while. we were the first systems integrated and as we Cloudera pivotal with massive partner with homework. So most of what's interesting is when people talk about data lakes and some people are thinking that stuff new. We're talking about the problem of most of our clients are now looking at the problem of having We will have multiple data lakes for P. I reasons for operational efficiency reasons from budget reasons. Whatever it may be we're looking at, how do you collaborate beyond the firewall? So I'd say, Obviously, we've got a continuity of customers. But a lot of our customers are going beyond the stage at which they're worrying about big data within their four walls to the stage of how do I collaborate beyond my four walls? And this, for us, is the switch on governance and data, and what we do is is the difference between sort of capture announcement other ones is. So when's recess is the global MGM guy and Gold Data Management guy? He actually his team is in all of the countries, so he has P and l responsibility for that. When I have it for big data in the >>country, you're out implementing the value extraction >>were in multi. I mean, it's really at the stage of kicking tyres. We're at the stage >>behind the kicking tyres a long way back in 2000, 11 >>1,002,011. By now, sort >>of driving the Ferrari on the autobahn. You know, 90 miles an hour straight, narrow. It's a lot more work to do, right. There's always a lot more things keep changing and that's that's the best part >>of what we do next. And that's the point for us is the reason we're in this is that it's what's next and I think that people, the reason governments are changing fundamentally is this move towards global collaboration. So the more you look at health exchanges and all of these things, the more people collaborate outside the four walls. That for us, is the problem we want to solve next, which is why we're working on industrialising what we now consider the boring stuff which is building a data lake and doing the internals and ingestion in those pieces that were not interested in putting bodies on that. It's about how you solve the next problem. >>Stephen Pre, thank you so much for joining the Cuba because you're good to see you again. And welcome to the Cuban love nightclub. You made it, um, great to have you love to do it. Do this again and again. I love the context. I love that you guys are on this, you know, data quality at the right time. Really? Right message? Certainly we think certainly relevant. So thanks for sharing your insights on here. And And the data on the Cube live streaming from San Francisco. You're watching the Cuba right back. It's always fun to come back to the cube because